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Sample records for sample size conventions

  1. Ethics and sample size.

    Science.gov (United States)

    Bacchetti, Peter; Wolf, Leslie E; Segal, Mark R; McCulloch, Charles E

    2005-01-15

    The belief is widespread that studies are unethical if their sample size is not large enough to ensure adequate power. The authors examine how sample size influences the balance that determines the ethical acceptability of a study: the balance between the burdens that participants accept and the clinical or scientific value that a study can be expected to produce. The average projected burden per participant remains constant as the sample size increases, but the projected study value does not increase as rapidly as the sample size if it is assumed to be proportional to power or inversely proportional to confidence interval width. This implies that the value per participant declines as the sample size increases and that smaller studies therefore have more favorable ratios of projected value to participant burden. The ethical treatment of study participants therefore does not require consideration of whether study power is less than the conventional goal of 80% or 90%. Lower power does not make a study unethical. The analysis addresses only ethical acceptability, not optimality; large studies may be desirable for other than ethical reasons.

  2. Sample size for beginners.

    OpenAIRE

    Florey, C D

    1993-01-01

    The common failure to include an estimation of sample size in grant proposals imposes a major handicap on applicants, particularly for those proposing work in any aspect of research in the health services. Members of research committees need evidence that a study is of adequate size for there to be a reasonable chance of a clear answer at the end. A simple illustrated explanation of the concepts in determining sample size should encourage the faint hearted to pay more attention to this increa...

  3. Sample size methodology

    CERN Document Server

    Desu, M M

    2012-01-01

    One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropria

  4. Determination of Sample Size

    OpenAIRE

    Naing, Nyi Nyi

    2003-01-01

    There is a particular importance of determining a basic minimum required ‘n’ size of the sample to recognize a particular measurement of a particular population. This article has highlighted the determination of an appropriate size to estimate population parameters.

  5. Sample size for beginners.

    Science.gov (United States)

    Florey, C D

    1993-05-01

    The common failure to include an estimation of sample size in grant proposals imposes a major handicap on applicants, particularly for those proposing work in any aspect of research in the health services. Members of research committees need evidence that a study is of adequate size for there to be a reasonable chance of a clear answer at the end. A simple illustrated explanation of the concepts in determining sample size should encourage the faint hearted to pay more attention to this increasingly important aspect of grantsmanship.

  6. Sample size determination and power

    CERN Document Server

    Ryan, Thomas P, Jr

    2013-01-01

    THOMAS P. RYAN, PhD, teaches online advanced statistics courses for Northwestern University and The Institute for Statistics Education in sample size determination, design of experiments, engineering statistics, and regression analysis.

  7. Biostatistics Series Module 5: Determining Sample Size.

    Science.gov (United States)

    Hazra, Avijit; Gogtay, Nithya

    2016-01-01

    Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 - β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the

  8. How Sample Size Affects a Sampling Distribution

    Science.gov (United States)

    Mulekar, Madhuri S.; Siegel, Murray H.

    2009-01-01

    If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…

  9. Effect of imperfect detectability on adaptive and conventional sampling: simulated sampling of freshwater mussels in the upper Mississippi River.

    Science.gov (United States)

    Smith, David R; Gray, Brian R; Newton, Teresa J; Nichols, Doug

    2010-11-01

    Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

  10. Effect of imperfect detectability on adaptive and conventional sampling: Simulated sampling of freshwater mussels in the upper Mississippi River

    Science.gov (United States)

    Smith, D.R.; Gray, B.R.; Newton, T.J.; Nichols, D.

    2010-01-01

    Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

  11. How to calculate sample size and why.

    Science.gov (United States)

    Kim, Jeehyoung; Seo, Bong Soo

    2013-09-01

    Calculating the sample size is essential to reduce the cost of a study and to prove the hypothesis effectively. Referring to pilot studies and previous research studies, we can choose a proper hypothesis and simplify the studies by using a website or Microsoft Excel sheet that contains formulas for calculating sample size in the beginning stage of the study. There are numerous formulas for calculating the sample size for complicated statistics and studies, but most studies can use basic calculating methods for sample size calculation.

  12. Sample size determination for the fluctuation experiment.

    Science.gov (United States)

    Zheng, Qi

    2017-01-01

    The Luria-Delbrück fluctuation experiment protocol is increasingly employed to determine microbial mutation rates in the laboratory. An important question raised at the planning stage is "How many cultures are needed?" For over 70 years sample sizes have been determined either by intuition or by following published examples where sample sizes were chosen intuitively. This paper proposes a practical method for determining the sample size. The proposed method relies on existing algorithms for computing the expected Fisher information under two commonly used mutant distributions. The role of partial plating in reducing sample size is discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Additional Considerations in Determining Sample Size.

    Science.gov (United States)

    Levin, Joel R.; Subkoviak, Michael J.

    Levin's (1975) sample-size determination procedure for completely randomized analysis of variance designs is extended to designs in which antecedent or blocking variables information is considered. In particular, a researcher's choice of designs is framed in terms of determining the respective sample sizes necessary to detect specified contrasts…

  14. Determining Sample Size for Research Activities

    Science.gov (United States)

    Krejcie, Robert V.; Morgan, Daryle W.

    1970-01-01

    A formula for determining sample size, which originally appeared in 1960, has lacked a table for easy reference. This article supplies a graph of the function and a table of values which permits easy determination of the size of sample needed to be representative of a given population. (DG)

  15. Sample size in qualitative interview studies

    DEFF Research Database (Denmark)

    Malterud, Kirsti; Siersma, Volkert Dirk; Guassora, Ann Dorrit Kristiane

    2016-01-01

    Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is “saturation.” Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose...... the concept “information power” to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power...... depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning...

  16. Basic Statistical Concepts for Sample Size Estimation

    Directory of Open Access Journals (Sweden)

    Vithal K Dhulkhed

    2008-01-01

    Full Text Available For grant proposals the investigator has to include an estimation of sample size .The size of the sample should be adequate enough so that there is sufficient data to reliably answer the research question being addressed by the study. At the very planning stage of the study the investigator has to involve the statistician. To have meaningful dialogue with the statistician every research worker should be familiar with the basic concepts of statistics. This paper is concerned with simple principles of sample size calculation. Concepts are explained based on logic rather than rigorous mathematical calculations to help him assimilate the fundamentals.

  17. Particle size distribution in ground biological samples.

    Science.gov (United States)

    Koglin, D; Backhaus, F; Schladot, J D

    1997-05-01

    Modern trace and retrospective analysis of Environmental Specimen Bank (ESB) samples require surplus material prepared and characterized as reference materials. Before the biological samples could be analyzed and stored for long periods at cryogenic temperatures, the materials have to be pre-crushed. As a second step, a milling and homogenization procedure has to follow. For this preparation, a grinding device is cooled with liquid nitrogen to a temperature of -190 degrees C. It is a significant condition for homogeneous samples that at least 90% of the particles should be smaller than 200 microns. In the German ESB the particle size distribution of the processed material is determined by means of a laser particle sizer. The decrease of particle sizes of deer liver and bream muscles after different grinding procedures as well as the consequences of ultrasonic treatment of the sample before particle size measurements have been investigated.

  18. Determining sample size for tree utilization surveys

    Science.gov (United States)

    Stanley J. Zarnoch; James W. Bentley; Tony G. Johnson

    2004-01-01

    The U.S. Department of Agriculture Forest Service has conducted many studies to determine what proportion of the timber harvested in the South is actually utilized. This paper describes the statistical methods used to determine required sample sizes for estimating utilization ratios for a required level of precision. The data used are those for 515 hardwood and 1,557...

  19. Improving your Hypothesis Testing: Determining Sample Sizes.

    Science.gov (United States)

    Luftig, Jeffrey T.; Norton, Willis P.

    1982-01-01

    This article builds on an earlier discussion of the importance of the Type II error (beta) and power to the hypothesis testing process (CE 511 484), and illustrates the methods by which sample size calculations should be employed so as to improve the research process. (Author/CT)

  20. Predicting sample size required for classification performance

    Directory of Open Access Journals (Sweden)

    Figueroa Rosa L

    2012-02-01

    Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

  1. Sample size for morphological traits of pigeonpea

    Directory of Open Access Journals (Sweden)

    Giovani Facco

    2015-12-01

    Full Text Available The objectives of this study were to determine the sample size (i.e., number of plants required to accurately estimate the average of morphological traits of pigeonpea (Cajanus cajan L. and to check for variability in sample size between evaluation periods and seasons. Two uniformity trials (i.e., experiments without treatment were conducted for two growing seasons. In the first season (2011/2012, the seeds were sown by broadcast seeding, and in the second season (2012/2013, the seeds were sown in rows spaced 0.50 m apart. The ground area in each experiment was 1,848 m2, and 360 plants were marked in the central area, in a 2 m × 2 m grid. Three morphological traits (e.g., number of nodes, plant height and stem diameter were evaluated 13 times during the first season and 22 times in the second season. Measurements for all three morphological traits were normally distributed and confirmed through the Kolmogorov-Smirnov test. Randomness was confirmed using the Run Test, and the descriptive statistics were calculated. For each trait, the sample size (n was calculated for the semiamplitudes of the confidence interval (i.e., estimation error equal to 2, 4, 6, ..., 20% of the estimated mean with a confidence coefficient (1-? of 95%. Subsequently, n was fixed at 360 plants, and the estimation error of the estimated percentage of the average for each trait was calculated. Variability of the sample size for the pigeonpea culture was observed between the morphological traits evaluated, among the evaluation periods and between seasons. Therefore, to assess with an accuracy of 6% of the estimated average, at least 136 plants must be evaluated throughout the pigeonpea crop cycle to determine the sample size for the traits (e.g., number of nodes, plant height and stem diameter in the different evaluation periods and between seasons. 

  2. Determining sample size when assessing mean equivalence.

    Science.gov (United States)

    Asberg, Arne; Solem, Kristine B; Mikkelsen, Gustav

    2014-11-01

    When we want to assess whether two analytical methods are equivalent, we could test if the difference between the mean results is within the specification limits of 0 ± an acceptance criterion. Testing the null hypothesis of zero difference is less interesting, and so is the sample size estimation based on testing that hypothesis. Power function curves for equivalence testing experiments are not widely available. In this paper we present power function curves to help decide on the number of measurements when testing equivalence between the means of two analytical methods. Computer simulation was used to calculate the probability that the 90% confidence interval for the difference between the means of two analytical methods would exceed the specification limits of 0 ± 1, 0 ± 2 or 0 ± 3 analytical standard deviations (SDa), respectively. The probability of getting a nonequivalence alarm increases with increasing difference between the means when the difference is well within the specification limits. The probability increases with decreasing sample size and with smaller acceptance criteria. We may need at least 40-50 measurements with each analytical method when the specification limits are 0 ± 1 SDa, and 10-15 and 5-10 when the specification limits are 0 ± 2 and 0 ± 3 SDa, respectively. The power function curves provide information of the probability of false alarm, so that we can decide on the sample size under less uncertainty.

  3. Sample size calculations for skewed distributions.

    Science.gov (United States)

    Cundill, Bonnie; Alexander, Neal D E

    2015-04-02

    Sample size calculations should correspond to the intended method of analysis. Nevertheless, for non-normal distributions, they are often done on the basis of normal approximations, even when the data are to be analysed using generalized linear models (GLMs). For the case of comparison of two means, we use GLM theory to derive sample size formulae, with particular cases being the negative binomial, Poisson, binomial, and gamma families. By simulation we estimate the performance of normal approximations, which, via the identity link, are special cases of our approach, and for common link functions such as the log. The negative binomial and gamma scenarios are motivated by examples in hookworm vaccine trials and insecticide-treated materials, respectively. Calculations on the link function (log) scale work well for the negative binomial and gamma scenarios examined and are often superior to the normal approximations. However, they have little advantage for the Poisson and binomial distributions. The proposed method is suitable for sample size calculations for comparisons of means of highly skewed outcome variables.

  4. Poly (lactic-co-glycolic acid) particles prepared by microfluidics and conventional methods. Modulated particle size and rheology.

    Science.gov (United States)

    Perez, Aurora; Hernández, Rebeca; Velasco, Diego; Voicu, Dan; Mijangos, Carmen

    2015-03-01

    Microfluidic techniques are expected to provide narrower particle size distribution than conventional methods for the preparation of poly (lactic-co-glycolic acid) (PLGA) microparticles. Besides, it is hypothesized that the particle size distribution of poly (lactic-co-glycolic acid) microparticles influences the settling behavior and rheological properties of its aqueous dispersions. For the preparation of PLGA particles, two different methods, microfluidic and conventional oil-in-water emulsification methods were employed. The particle size and particle size distribution of PLGA particles prepared by microfluidics were studied as a function of the flow rate of the organic phase while particles prepared by conventional methods were studied as a function of stirring rate. In order to study the stability and structural organization of colloidal dispersions, settling experiments and oscillatory rheological measurements were carried out on aqueous dispersions of PLGA particles with different particle size distributions. Microfluidics technique allowed the control of size and size distribution of the droplets formed in the process of emulsification. This resulted in a narrower particle size distribution for samples prepared by MF with respect to samples prepared by conventional methods. Polydisperse samples showed a larger tendency to aggregate, thus confirming the advantages of microfluidics over conventional methods, especially if biomedical applications are envisaged. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Defining sample size and sampling strategy for dendrogeomorphic rockfall reconstructions

    Science.gov (United States)

    Morel, Pauline; Trappmann, Daniel; Corona, Christophe; Stoffel, Markus

    2015-05-01

    Optimized sampling strategies have been recently proposed for dendrogeomorphic reconstructions of mass movements with a large spatial footprint, such as landslides, snow avalanches, and debris flows. Such guidelines have, by contrast, been largely missing for rockfalls and cannot be transposed owing to the sporadic nature of this process and the occurrence of individual rocks and boulders. Based on a data set of 314 European larch (Larix decidua Mill.) trees (i.e., 64 trees/ha), growing on an active rockfall slope, this study bridges this gap and proposes an optimized sampling strategy for the spatial and temporal reconstruction of rockfall activity. Using random extractions of trees, iterative mapping, and a stratified sampling strategy based on an arbitrary selection of trees, we investigate subsets of the full tree-ring data set to define optimal sample size and sampling design for the development of frequency maps of rockfall activity. Spatially, our results demonstrate that the sampling of only 6 representative trees per ha can be sufficient to yield a reasonable mapping of the spatial distribution of rockfall frequencies on a slope, especially if the oldest and most heavily affected individuals are included in the analysis. At the same time, however, sampling such a low number of trees risks causing significant errors especially if nonrepresentative trees are chosen for analysis. An increased number of samples therefore improves the quality of the frequency maps in this case. Temporally, we demonstrate that at least 40 trees/ha are needed to obtain reliable rockfall chronologies. These results will facilitate the design of future studies, decrease the cost-benefit ratio of dendrogeomorphic studies and thus will permit production of reliable reconstructions with reasonable temporal efforts.

  6. Sample size estimation and sampling techniques for selecting a representative sample

    OpenAIRE

    Aamir Omair

    2014-01-01

    Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect ...

  7. Sample size estimation and sampling techniques for selecting a representative sample

    Directory of Open Access Journals (Sweden)

    Aamir Omair

    2014-01-01

    Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

  8. Sample size matters: Investigating the optimal sample size for a logistic regression debris flow susceptibility model

    Science.gov (United States)

    Heckmann, Tobias; Gegg, Katharina; Becht, Michael

    2013-04-01

    Statistical approaches to landslide susceptibility modelling on the catchment and regional scale are used very frequently compared to heuristic and physically based approaches. In the present study, we deal with the problem of the optimal sample size for a logistic regression model. More specifically, a stepwise approach has been chosen in order to select those independent variables (from a number of derivatives of a digital elevation model and landcover data) that explain best the spatial distribution of debris flow initiation zones in two neighbouring central alpine catchments in Austria (used mutually for model calculation and validation). In order to minimise problems arising from spatial autocorrelation, we sample a single raster cell from each debris flow initiation zone within an inventory. In addition, as suggested by previous work using the "rare events logistic regression" approach, we take a sample of the remaining "non-event" raster cells. The recommendations given in the literature on the size of this sample appear to be motivated by practical considerations, e.g. the time and cost of acquiring data for non-event cases, which do not apply to the case of spatial data. In our study, we aim at finding empirically an "optimal" sample size in order to avoid two problems: First, a sample too large will violate the independent sample assumption as the independent variables are spatially autocorrelated; hence, a variogram analysis leads to a sample size threshold above which the average distance between sampled cells falls below the autocorrelation range of the independent variables. Second, if the sample is too small, repeated sampling will lead to very different results, i.e. the independent variables and hence the result of a single model calculation will be extremely dependent on the choice of non-event cells. Using a Monte-Carlo analysis with stepwise logistic regression, 1000 models are calculated for a wide range of sample sizes. For each sample size

  9. Sample Size Growth with an Increasing Number of Comparisons

    Directory of Open Access Journals (Sweden)

    Chi-Hong Tseng

    2012-01-01

    Full Text Available An appropriate sample size is crucial for the success of many studies that involve a large number of comparisons. Sample size formulas for testing multiple hypotheses are provided in this paper. They can be used to determine the sample sizes required to provide adequate power while controlling familywise error rate or false discovery rate, to derive the growth rate of sample size with respect to an increasing number of comparisons or decrease in effect size, and to assess reliability of study designs. It is demonstrated that practical sample sizes can often be achieved even when adjustments for a large number of comparisons are made as in many genomewide studies.

  10. An expert system for the calculation of sample size.

    Science.gov (United States)

    Ebell, M H; Neale, A V; Hodgkins, B J

    1994-06-01

    Calculation of sample size is a useful technique for researchers who are designing a study, and for clinicians who wish to interpret research findings. The elements that must be specified to calculate the sample size include alpha, beta, Type I and Type II errors, 1- and 2-tail tests, confidence intervals, and confidence levels. A computer software program written by one of the authors (MHE), Sample Size Expert, facilitates sample size calculations. The program uses an expert system to help inexperienced users calculate sample sizes for analytic and descriptive studies. The software is available at no cost from the author or electronically via several on-line information services.

  11. Evaluation of various conventional methods for sampling weeds in potato and spinach crops

    Directory of Open Access Journals (Sweden)

    David Jamaica

    2014-04-01

    Full Text Available This study aimed to evaluate (at an exploratory level, some of the different conventional sampling designs in a section of a potato crop and in a commercial crop of spinach. Weeds were sampled in a 16 x 48 m section of a potato crop with a set grid of 192 sections. The cover and density of the weeds were registered in squares of from 0.25 to 64 m². The results were used to create a database that allowed for the simulation of different sampling designs: variables and square size. A second sampling was carried out with these results in a spinach crop of 1.16 ha with a set grid of 6 x 6 m cells, evaluating the cover in 4 m² squares. Another database was created with this information, which was used to simulate other sampling designs such as distribution and quantity of sampling squares. According to the obtained results, a good method for approximating the quantity of squares for diverse samples is 10-12 squares (4 m² for richness per ha and 18 or more squares for abundance per hectare. This square size is optimal since it allows for a sampling of more area without losing sight of low-profile species, with the cover variable best representing the abundance of the weeds.

  12. Optimal flexible sample size design with robust power.

    Science.gov (United States)

    Zhang, Lanju; Cui, Lu; Yang, Bo

    2016-08-30

    It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  13. Planning Educational Research: Determining the Necessary Sample Size.

    Science.gov (United States)

    Olejnik, Stephen F.

    1984-01-01

    This paper discusses the sample size problem and four factors affecting its solution: significance level, statistical power, analysis procedure, and effect size. The interrelationship between these factors is discussed and demonstrated by calculating minimal sample size requirements for a variety of research conditions. (Author)

  14. Sample size determination in clinical trials with multiple endpoints

    CERN Document Server

    Sozu, Takashi; Hamasaki, Toshimitsu; Evans, Scott R

    2015-01-01

    This book integrates recent methodological developments for calculating the sample size and power in trials with more than one endpoint considered as multiple primary or co-primary, offering an important reference work for statisticians working in this area. The determination of sample size and the evaluation of power are fundamental and critical elements in the design of clinical trials. If the sample size is too small, important effects may go unnoticed; if the sample size is too large, it represents a waste of resources and unethically puts more participants at risk than necessary. Recently many clinical trials have been designed with more than one endpoint considered as multiple primary or co-primary, creating a need for new approaches to the design and analysis of these clinical trials. The book focuses on the evaluation of power and sample size determination when comparing the effects of two interventions in superiority clinical trials with multiple endpoints. Methods for sample size calculation in clin...

  15. Sample size determination in medical and surgical research.

    Science.gov (United States)

    Flikkema, Robert M; Toledo-Pereyra, Luis H

    2012-02-01

    One of the most critical yet frequently misunderstood principles of research is sample size determination. Obtaining an inadequate sample is a serious problem that can invalidate an entire study. Without an extensive background in statistics, the seemingly simple question of selecting a sample size can become quite a daunting task. This article aims to give a researcher with no background in statistics the basic tools needed for sample size determination. After reading this article, the researcher will be aware of all the factors involved in a power analysis and will be able to work more effectively with the statistician when determining sample size. This work also reviews the power of a statistical hypothesis, as well as how to estimate the effect size of a research study. These are the two key components of sample size determination. Several examples will be considered throughout the text.

  16. Challenging Conventional Wisdom for Multivariate Statistical Models with Small Samples

    Science.gov (United States)

    McNeish, Daniel

    2017-01-01

    In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

  17. A review of software for sample size determination.

    Science.gov (United States)

    Dattalo, Patrick

    2009-09-01

    The size of a sample is an important element in determining the statistical precision with which population values can be estimated. This article identifies and describes free and commercial programs for sample size determination. Programs are categorized as follows: (a) multiple procedure for sample size determination; (b) single procedure for sample size determination; and (c) Web-based. Programs are described in terms of (a) cost; (b) ease of use, including interface, operating system and hardware requirements, and availability of documentation and technical support; (c) file management, including input and output formats; and (d) analytical and graphical capabilities.

  18. Preeminence and prerequisites of sample size calculations in clinical trials

    Directory of Open Access Journals (Sweden)

    Richa Singhal

    2015-01-01

    Full Text Available The key components while planning a clinical study are the study design, study duration, and sample size. These features are an integral part of planning a clinical trial efficiently, ethically, and cost-effectively. This article describes some of the prerequisites for sample size calculation. It also explains that sample size calculation is different for different study designs. The article in detail describes the sample size calculation for a randomized controlled trial when the primary outcome is a continuous variable and when it is a proportion or a qualitative variable.

  19. Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis

    Science.gov (United States)

    Adnan, Tassha Hilda

    2016-01-01

    Sensitivity and specificity analysis is commonly used for screening and diagnostic tests. The main issue researchers face is to determine the sufficient sample sizes that are related with screening and diagnostic studies. Although the formula for sample size calculation is available but concerning majority of the researchers are not mathematicians or statisticians, hence, sample size calculation might not be easy for them. This review paper provides sample size tables with regards to sensitivity and specificity analysis. These tables were derived from formulation of sensitivity and specificity test using Power Analysis and Sample Size (PASS) software based on desired type I error, power and effect size. The approaches on how to use the tables were also discussed. PMID:27891446

  20. Determination of the optimal sample size for a clinical trial accounting for the population size

    Science.gov (United States)

    Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

    2016-01-01

    The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision‐theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two‐arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. PMID:27184938

  1. Publication Bias in Psychology: A Diagnosis Based on the Correlation between Effect Size and Sample Size

    Science.gov (United States)

    Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

    2014-01-01

    Background The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. Methods We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values. Results We found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings. Conclusion The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology. PMID:25192357

  2. Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size.

    Science.gov (United States)

    Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

    2014-01-01

    The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values. We found a negative correlation of r = -.45 [95% CI: -.53; -.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings. The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology.

  3. Estimating population size with correlated sampling unit estimates

    Science.gov (United States)

    David C. Bowden; Gary C. White; Alan B. Franklin; Joseph L. Ganey

    2003-01-01

    Finite population sampling theory is useful in estimating total population size (abundance) from abundance estimates of each sampled unit (quadrat). We develop estimators that allow correlated quadrat abundance estimates, even for quadrats in different sampling strata. Correlated quadrat abundance estimates based on mark–recapture or distance sampling methods occur...

  4. Sample size computation for association studies using case–parents ...

    Indian Academy of Sciences (India)

    sample size for case–control association studies is discussed. Materials and methods. Parameter settings. We consider a candidate locus with two alleles A and a where. A is putatively associated with the disease status (increasing. Keywords. sample size; association tests; genotype relative risk; power; autism. Journal of ...

  5. Understanding Power and Rules of Thumb for Determining Sample Sizes

    OpenAIRE

    Betsy L. Morgan; Carmen R. Wilson Van Voorhis

    2007-01-01

    This article addresses the definition of power and its relationship to Type I and Type II errors. We discuss the relationship of sample size and power. Finally, we offer statistical rules of thumb guiding the selection of sample sizes large enough for sufficient power to detecting differences, associations, chi-square, and factor analyses.

  6. Understanding Power and Rules of Thumb for Determining Sample Sizes

    Directory of Open Access Journals (Sweden)

    Betsy L. Morgan

    2007-09-01

    Full Text Available This article addresses the definition of power and its relationship to Type I and Type II errors. We discuss the relationship of sample size and power. Finally, we offer statistical rules of thumb guiding the selection of sample sizes large enough for sufficient power to detecting differences, associations, chi-square, and factor analyses.

  7. Sample Size and Statistical Power Calculation in Genetic Association Studies

    Directory of Open Access Journals (Sweden)

    Eun Pyo Hong

    2012-06-01

    Full Text Available A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD, 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

  8. Considerations in determining sample size for pilot studies.

    Science.gov (United States)

    Hertzog, Melody A

    2008-04-01

    There is little published guidance concerning how large a pilot study should be. General guidelines, for example using 10% of the sample required for a full study, may be inadequate for aims such as assessment of the adequacy of instrumentation or providing statistical estimates for a larger study. This article illustrates how confidence intervals constructed around a desired or anticipated value can help determine the sample size needed. Samples ranging in size from 10 to 40 per group are evaluated for their adequacy in providing estimates precise enough to meet a variety of possible aims. General sample size guidelines by type of aim are offered.

  9. Determining the sample size required for a community radon survey.

    Science.gov (United States)

    Chen, Jing; Tracy, Bliss L; Zielinski, Jan M; Moir, Deborah

    2008-04-01

    Radon measurements in homes and other buildings have been included in various community health surveys often dealing with only a few hundred randomly sampled households. It would be interesting to know whether such a small sample size can adequately represent the radon distribution in a large community. An analysis of radon measurement data obtained from the Winnipeg case-control study with randomly sampled subsets of different sizes has showed that a sample size of one to several hundred can serve the survey purpose well.

  10. Sample Size of One: Operational Qualitative Analysis in the Classroom

    Directory of Open Access Journals (Sweden)

    John Hoven

    2015-10-01

    Full Text Available Qualitative analysis has two extraordinary capabilities: first, finding answers to questions we are too clueless to ask; and second, causal inference – hypothesis testing and assessment – within a single unique context (sample size of one. These capabilities are broadly useful, and they are critically important in village-level civil-military operations. Company commanders need to learn quickly, "What are the problems and possibilities here and now, in this specific village? What happens if we do A, B, and C?" – and that is an ill-defined, one-of-a-kind problem. The U.S. Army's Eighty-Third Civil Affairs Battalion is our "first user" innovation partner in a new project to adapt qualitative research methods to an operational tempo and purpose. Our aim is to develop a simple, low-cost methodology and training program for local civil-military operations conducted by non-specialist conventional forces. Complementary to that, this paper focuses on some essential basics that can be implemented by college professors without significant cost, effort, or disruption.

  11. Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

    Science.gov (United States)

    Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

    2017-09-14

    While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey.

  12. Sampling strategies for estimating brook trout effective population size

    Science.gov (United States)

    Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher

    2012-01-01

    The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...

  13. New shooting algorithms for transition path sampling: centering moves and varied-perturbation sizes for improved sampling.

    Science.gov (United States)

    Rowley, Christopher N; Woo, Tom K

    2009-12-21

    Transition path sampling has been established as a powerful tool for studying the dynamics of rare events. The trajectory generation moves of this Monte Carlo procedure, shooting moves and shifting modes, were developed primarily for rate constant calculations, although this method has been more extensively used to study the dynamics of reactive processes. We have devised and implemented three alternative trajectory generation moves for use with transition path sampling. The centering-shooting move incorporates a shifting move into a shooting move, which centers the transition period in the middle of the trajectory, eliminating the need for shifting moves and generating an ensemble where the transition event consistently occurs near the middle of the trajectory. We have also developed varied-perturbation size shooting moves, wherein smaller perturbations are made if the shooting point is far from the transition event. The trajectories generated using these moves decorrelate significantly faster than with conventional, constant sized perturbations. This results in an increase in the statistical efficiency by a factor of 2.5-5 when compared to the conventional shooting algorithm. On the other hand, the new algorithm breaks detailed balance and introduces a small bias in the transition time distribution. We have developed a modification of this varied-perturbation size shooting algorithm that preserves detailed balance, albeit at the cost of decreased sampling efficiency. Both varied-perturbation size shooting algorithms are found to have improved sampling efficiency when compared to the original constant perturbation size shooting algorithm.

  14. Methods for sample size determination in cluster randomized trials.

    Science.gov (United States)

    Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

    2015-06-01

    The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. © The Author 2015. Published by Oxford University Press on behalf of the International Epidemiological Association.

  15. Neuromuscular dose-response studies: determining sample size.

    Science.gov (United States)

    Kopman, A F; Lien, C A; Naguib, M

    2011-02-01

    Investigators planning dose-response studies of neuromuscular blockers have rarely used a priori power analysis to determine the minimal sample size their protocols require. Institutional Review Boards and peer-reviewed journals now generally ask for this information. This study outlines a proposed method for meeting these requirements. The slopes of the dose-response relationships of eight neuromuscular blocking agents were determined using regression analysis. These values were substituted for γ in the Hill equation. When this is done, the coefficient of variation (COV) around the mean value of the ED₅₀ for each drug is easily calculated. Using these values, we performed an a priori one-sample two-tailed t-test of the means to determine the required sample size when the allowable error in the ED₅₀ was varied from ±10-20%. The COV averaged 22% (range 15-27%). We used a COV value of 25% in determining the sample size. If the allowable error in finding the mean ED₅₀ is ±15%, a sample size of 24 is needed to achieve a power of 80%. Increasing 'accuracy' beyond this point requires increasing greater sample sizes (e.g. an 'n' of 37 for a ±12% error). On the basis of the results of this retrospective analysis, a total sample size of not less than 24 subjects should be adequate for determining a neuromuscular blocking drug's clinical potency with a reasonable degree of assurance.

  16. Determination of the optimal sample size for a clinical trial accounting for the population size.

    Science.gov (United States)

    Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

    2017-07-01

    The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Determining the effective sample size of a parametric prior.

    Science.gov (United States)

    Morita, Satoshi; Thall, Peter F; Müller, Peter

    2008-06-01

    We present a definition for the effective sample size of a parametric prior distribution in a Bayesian model, and propose methods for computing the effective sample size in a variety of settings. Our approach first constructs a prior chosen to be vague in a suitable sense, and updates this prior to obtain a sequence of posteriors corresponding to each of a range of sample sizes. We then compute a distance between each posterior and the parametric prior, defined in terms of the curvature of the logarithm of each distribution, and the posterior minimizing the distance defines the effective sample size of the prior. For cases where the distance cannot be computed analytically, we provide a numerical approximation based on Monte Carlo simulation. We provide general guidelines for application, illustrate the method in several standard cases where the answer seems obvious, and then apply it to some nonstandard settings.

  18. Effects of Mesh Size on Sieved Samples of Corophium volutator

    Science.gov (United States)

    Crewe, Tara L.; Hamilton, Diana J.; Diamond, Antony W.

    2001-08-01

    Corophium volutator (Pallas), gammaridean amphipods found on intertidal mudflats, are frequently collected in mud samples sieved on mesh screens. However, mesh sizes used vary greatly among studies, raising the possibility that sampling methods bias results. The effect of using different mesh sizes on the resulting size-frequency distributions of Corophium was tested by collecting Corophium from mud samples with 0·5 and 0·25 mm sieves. More than 90% of Corophium less than 2 mm long passed through the larger sieve. A significantly smaller, but still substantial, proportion of 2-2·9 mm Corophium (30%) was also lost. Larger size classes were unaffected by mesh size. Mesh size significantly changed the observed size-frequency distribution of Corophium, and effects varied with sampling date. It is concluded that a 0·5 mm sieve is suitable for studies concentrating on adults, but to accurately estimate Corophium density and size-frequency distributions, a 0·25 mm sieve must be used.

  19. Effects of sample size on the second magnetization peak in ...

    Indian Academy of Sciences (India)

    8+ crystals are observed at low temperatures, above the temperature where the SMP totally disappears. In particular, the onset of the SMP shifts to lower fields as the sample size decreases - a result that could be interpreted as a size effect in ...

  20. Planning Longitudinal Field Studies: Considerations in Determining Sample Size.

    Science.gov (United States)

    St.Pierre, Robert G.

    1980-01-01

    Factors that influence the sample size necessary for longitudinal evaluations include the nature of the evaluation questions, nature of available comparison groups, consistency of the treatment in different sites, effect size, attrition rate, significance level for statistical tests, and statistical power. (Author/GDC)

  1. Investigating the impact of sample size on cognate detection

    OpenAIRE

    List, Johann-Mattis

    2013-01-01

    International audience; In historical linguistics, the problem of cognate detection is traditionally approached within the frame-work of the comparative method. Since the method is usually carried out manually, it is very flexible regarding its input parameters. However, while the number of languages and the selection of comparanda is not important for the successfull application of the method, the sample size of the comparanda is. In order to shed light on the impact of sample size on cognat...

  2. Sample size requirements for training high-dimensional risk predictors.

    Science.gov (United States)

    Dobbin, Kevin K; Song, Xiao

    2013-09-01

    A common objective of biomarker studies is to develop a predictor of patient survival outcome. Determining the number of samples required to train a predictor from survival data is important for designing such studies. Existing sample size methods for training studies use parametric models for the high-dimensional data and cannot handle a right-censored dependent variable. We present a new training sample size method that is non-parametric with respect to the high-dimensional vectors, and is developed for a right-censored response. The method can be applied to any prediction algorithm that satisfies a set of conditions. The sample size is chosen so that the expected performance of the predictor is within a user-defined tolerance of optimal. The central method is based on a pilot dataset. To quantify uncertainty, a method to construct a confidence interval for the tolerance is developed. Adequacy of the size of the pilot dataset is discussed. An alternative model-based version of our method for estimating the tolerance when no adequate pilot dataset is available is presented. The model-based method requires a covariance matrix be specified, but we show that the identity covariance matrix provides adequate sample size when the user specifies three key quantities. Application of the sample size method to two microarray datasets is discussed.

  3. Sample size matters: investigating the effect of sample size on a logistic regression debris flow susceptibility model

    Science.gov (United States)

    Heckmann, T.; Gegg, K.; Gegg, A.; Becht, M.

    2013-06-01

    Predictive spatial modelling is an important task in natural hazard assessment and regionalisation of geomorphic processes or landforms. Logistic regression is a multivariate statistical approach frequently used in predictive modelling; it can be conducted stepwise in order to select from a number of candidate independent variables those that lead to the best model. In our case study on a debris flow susceptibility model, we investigate the sensitivity of model selection and quality to different sample sizes in light of the following problem: on the one hand, a sample has to be large enough to cover the variability of geofactors within the study area, and to yield stable results; on the other hand, the sample must not be too large, because a large sample is likely to violate the assumption of independent observations due to spatial autocorrelation. Using stepwise model selection with 1000 random samples for a number of sample sizes between n = 50 and n = 5000, we investigate the inclusion and exclusion of geofactors and the diversity of the resulting models as a function of sample size; the multiplicity of different models is assessed using numerical indices borrowed from information theory and biodiversity research. Model diversity decreases with increasing sample size and reaches either a local minimum or a plateau; even larger sample sizes do not further reduce it, and approach the upper limit of sample size given, in this study, by the autocorrelation range of the spatial datasets. In this way, an optimised sample size can be derived from an exploratory analysis. Model uncertainty due to sampling and model selection, and its predictive ability, are explored statistically and spatially through the example of 100 models estimated in one study area and validated in a neighbouring area: depending on the study area and on sample size, the predicted probabilities for debris flow release differed, on average, by 7 to 23 percentage points. In view of these results, we

  4. Sample size matters: investigating the effect of sample size on a logistic regression susceptibility model for debris flows

    Science.gov (United States)

    Heckmann, T.; Gegg, K.; Gegg, A.; Becht, M.

    2014-02-01

    Predictive spatial modelling is an important task in natural hazard assessment and regionalisation of geomorphic processes or landforms. Logistic regression is a multivariate statistical approach frequently used in predictive modelling; it can be conducted stepwise in order to select from a number of candidate independent variables those that lead to the best model. In our case study on a debris flow susceptibility model, we investigate the sensitivity of model selection and quality to different sample sizes in light of the following problem: on the one hand, a sample has to be large enough to cover the variability of geofactors within the study area, and to yield stable and reproducible results; on the other hand, the sample must not be too large, because a large sample is likely to violate the assumption of independent observations due to spatial autocorrelation. Using stepwise model selection with 1000 random samples for a number of sample sizes between n = 50 and n = 5000, we investigate the inclusion and exclusion of geofactors and the diversity of the resulting models as a function of sample size; the multiplicity of different models is assessed using numerical indices borrowed from information theory and biodiversity research. Model diversity decreases with increasing sample size and reaches either a local minimum or a plateau; even larger sample sizes do not further reduce it, and they approach the upper limit of sample size given, in this study, by the autocorrelation range of the spatial data sets. In this way, an optimised sample size can be derived from an exploratory analysis. Model uncertainty due to sampling and model selection, and its predictive ability, are explored statistically and spatially through the example of 100 models estimated in one study area and validated in a neighbouring area: depending on the study area and on sample size, the predicted probabilities for debris flow release differed, on average, by 7 to 23 percentage points. In

  5. Optimal sample sizes for Welch's test under various allocation and cost considerations.

    Science.gov (United States)

    Jan, Show-Li; Shieh, Gwowen

    2011-12-01

    The issue of the sample size necessary to ensure adequate statistical power has been the focus of considerableattention in scientific research. Conventional presentations of sample size determination do not consider budgetary and participant allocation scheme constraints, although there is some discussion in the literature. The introduction of additional allocation and cost concerns complicates study design, although the resulting procedure permits a practical treatment of sample size planning. This article presents exact techniques for optimizing sample size determinations in the context of Welch (Biometrika, 29, 350-362, 1938) test of the difference between two means under various design and cost considerations. The allocation schemes include cases in which (1) the ratio of group sizes is given and (2) one sample size is specified. The cost implications suggest optimally assigning subjects (1) to attain maximum power performance for a fixed cost and (2) to meet adesignated power level for the least cost. The proposed methods provide useful alternatives to the conventional procedures and can be readily implemented with the developed R and SAS programs that are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

  6. Sample Size Requirements for Traditional and Regression-Based Norms.

    Science.gov (United States)

    Oosterhuis, Hannah E M; van der Ark, L Andries; Sijtsma, Klaas

    2016-04-01

    Test norms enable determining the position of an individual test taker in the group. The most frequently used approach to obtain test norms is traditional norming. Regression-based norming may be more efficient than traditional norming and is rapidly growing in popularity, but little is known about its technical properties. A simulation study was conducted to compare the sample size requirements for traditional and regression-based norming by examining the 95% interpercentile ranges for percentile estimates as a function of sample size, norming method, size of covariate effects on the test score, test length, and number of answer categories in an item. Provided the assumptions of the linear regression model hold in the data, for a subdivision of the total group into eight equal-size subgroups, we found that regression-based norming requires samples 2.5 to 5.5 times smaller than traditional norming. Sample size requirements are presented for each norming method, test length, and number of answer categories. We emphasize that additional research is needed to establish sample size requirements when the assumptions of the linear regression model are violated. © The Author(s) 2015.

  7. A novel, stepwise approach combining conventional and endobronchial ultrasound needle aspiration for mediastinal lymph node sampling.

    Science.gov (United States)

    Liran, Levy; Rottem, Kuint; Gregorio, Fridlender Zvi; Avi, Abutbul; Neville, Berkman

    2017-09-07

    Since the introduction of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), most pulmonary centers use this technique exclusively for mediastinal lymph node (LN) sampling. Conventional "blind" TBNA (cTBNA), however, is cheaper, more accessible, provides more tissue, and requires less training. We evaluated whether sampling of mediastinal LN using EBUS-TBNA or cTBNA according to a predefined set of criteria provides acceptable diagnostic yield. Sampling method was determined prospectively according to a predefined set of criteria based on LN station, LN size, and presumed diagnosis. Sensitivity, specificity, positive, and negative predictive value were evaluated for each modality. One hundred and eighty-six biopsies were carried out over a 3-year period (86 cTBNA, 100 EBUS-TBNA). Seventy-seven percent of LN biopsied by EBUS-TBNA were <20 mm, while 83% of cTBNA biopsies were ≥20 mm. Most common sites of cTBNA sampling were station 7, 4R, and 11R as opposed to 7, 11R, 4R, and 4 L in the case of EBUS-TBNA. Most common EBUS-TBNA diagnosis was malignancy versus sarcoidosis in cTBNA. EBUS-TBNA and cTBNA both had a true positive yield of 65%, but EBUS-TBNA had a higher true negative rate (21% vs. 2% for cTBNA) and a lower false negative rate (7% vs. 28%). Sensitivity, specificity, positive predictive value, and negative predictive value for EBUS-TBNA were 90%, 100%, 100%, and 75%, respectively, and for cTBNA were 68%, 100%, 100%, and 7%, respectively. A stepwise approach based on LN size, station, and presumed diagnosis may be a reasonable, cost-effective approach in choosing between cTBNA and EBUS-TBNA.

  8. Mini-batch stochastic gradient descent with dynamic sample sizes

    OpenAIRE

    Metel, Michael R.

    2017-01-01

    We focus on solving constrained convex optimization problems using mini-batch stochastic gradient descent. Dynamic sample size rules are presented which ensure a descent direction with high probability. Empirical results from two applications show superior convergence compared to fixed sample implementations.

  9. Sample size formulae for the Bayesian continual reassessment method.

    Science.gov (United States)

    Cheung, Ying Kuen

    2013-01-01

    In the planning of a dose finding study, a primary design objective is to maintain high accuracy in terms of the probability of selecting the maximum tolerated dose. While numerous dose finding methods have been proposed in the literature, concrete guidance on sample size determination is lacking. With a motivation to provide quick and easy calculations during trial planning, we present closed form formulae for sample size determination associated with the use of the Bayesian continual reassessment method (CRM). We examine the sampling distribution of a nonparametric optimal design and exploit it as a proxy to empirically derive an accuracy index of the CRM using linear regression. We apply the formulae to determine the sample size of a phase I trial of PTEN-long in pancreatic cancer patients and demonstrate that the formulae give results very similar to simulation. The formulae are implemented by an R function 'getn' in the package 'dfcrm'. The results are developed for the Bayesian CRM and should be validated by simulation when used for other dose finding methods. The analytical formulae we propose give quick and accurate approximation of the required sample size for the CRM. The approach used to derive the formulae can be applied to obtain sample size formulae for other dose finding methods.

  10. Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

    Science.gov (United States)

    Morgan, Timothy M; Case, L Douglas

    2013-07-05

    In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.

  11. Uncertainty of the sample size reduction step in pesticide residue analysis of large-sized crops.

    Science.gov (United States)

    Omeroglu, P Yolci; Ambrus, Á; Boyacioglu, D; Majzik, E Solymosne

    2013-01-01

    To estimate the uncertainty of the sample size reduction step, each unit in laboratory samples of papaya and cucumber was cut into four segments in longitudinal directions and two opposite segments were selected for further homogenisation while the other two were discarded. Jackfruit was cut into six segments in longitudinal directions, and all segments were kept for further analysis. To determine the pesticide residue concentrations in each segment, they were individually homogenised and analysed by chromatographic methods. One segment from each unit of the laboratory sample was drawn randomly to obtain 50 theoretical sub-samples with an MS Office Excel macro. The residue concentrations in a sub-sample were calculated from the weight of segments and the corresponding residue concentration. The coefficient of variation calculated from the residue concentrations of 50 sub-samples gave the relative uncertainty resulting from the sample size reduction step. The sample size reduction step, which is performed by selecting one longitudinal segment from each unit of the laboratory sample, resulted in relative uncertainties of 17% and 21% for field-treated jackfruits and cucumber, respectively, and 7% for post-harvest treated papaya. The results demonstrated that sample size reduction is an inevitable source of uncertainty in pesticide residue analysis of large-sized crops. The post-harvest treatment resulted in a lower variability because the dipping process leads to a more uniform residue concentration on the surface of the crops than does the foliar application of pesticides.

  12. Thermophilic Campylobacter spp. in turkey samples: evaluation of two automated enzyme immunoassays and conventional microbiological techniques

    DEFF Research Database (Denmark)

    Borck, Birgitte; Stryhn, H.; Ersboll, A.K.

    2002-01-01

    , neckskin and environmental samples) were collected over a period of 4 months at a turkey slaughterhouse and meat-cutting plant in Denmark. Faecal and environmental samples were tested by the conventional culture method and by the two EIAs, whereas meat and neckskin samples were tested by the two EIAs only......Aims: To determine the sensitivity and specificity of two automated enzyme immunoassays (EIA), EiaFoss and Minividas, and a conventional microbiological culture technique for detecting thermophilic Campylobacter spp. in turkey samples. Methods and Results: A total of 286 samples (faecal, meat...

  13. SEM analysis of particle size during conventional treatment of CMP process wastewater

    Energy Technology Data Exchange (ETDEWEB)

    Roth, Gary A.; Neu-Baker, Nicole M.; Brenner, Sara A., E-mail: sbrenner@sunycnse.com

    2015-03-01

    Engineered nanomaterials (ENMs) are currently employed by many industries and have different physical and chemical properties from their bulk counterparts that may confer different toxicity. Nanoparticles used or generated in semiconductor manufacturing have the potential to enter the municipal waste stream via wastewater and their ultimate fate in the ecosystem is currently unknown. This study investigates the fate of ENMs used in chemical mechanical planarization (CMP), a polishing process repeatedly utilized in semiconductor manufacturing. Wastewater sampling was conducted throughout the wastewater treatment (WWT) process at the fabrication plant's on-site wastewater treatment facility. The goal of this study was to assess whether the WWT processes resulted in size-dependent filtration of particles in the nanoscale regime by analyzing samples using scanning electron microscopy (SEM). Statistical analysis demonstrated no significant differences in particle size between sampling points, indicating low or no selectivity of WWT methods for nanoparticles based on size. All nanoparticles appeared to be of similar morphology (near-spherical), with a high variability in particle size. EDX verified nanoparticles composition of silicon- and/or aluminum-oxide. Nanoparticle sizing data compared between sampling points, including the final sampling point before discharge from the facility, suggested that nanoparticles could be released to the municipal waste stream from industrial sources. - Highlights: • The discrete treatments of a semiconductor wastewater treatment system were examined. • A sampling scheme and method for analyzing nanoparticles in wastewater was devised. • The wastewater treatment process studied is not size-selective for nanoparticles.

  14. Sample-Size Planning for More Accurate Statistical Power: A Method Adjusting Sample Effect Sizes for Publication Bias and Uncertainty.

    Science.gov (United States)

    Anderson, Samantha F; Kelley, Ken; Maxwell, Scott E

    2017-11-01

    The sample size necessary to obtain a desired level of statistical power depends in part on the population value of the effect size, which is, by definition, unknown. A common approach to sample-size planning uses the sample effect size from a prior study as an estimate of the population value of the effect to be detected in the future study. Although this strategy is intuitively appealing, effect-size estimates, taken at face value, are typically not accurate estimates of the population effect size because of publication bias and uncertainty. We show that the use of this approach often results in underpowered studies, sometimes to an alarming degree. We present an alternative approach that adjusts sample effect sizes for bias and uncertainty, and we demonstrate its effectiveness for several experimental designs. Furthermore, we discuss an open-source R package, BUCSS, and user-friendly Web applications that we have made available to researchers so that they can easily implement our suggested methods.

  15. Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size

    Directory of Open Access Journals (Sweden)

    R. Eric Heidel

    2016-01-01

    Full Text Available Statistical power is the ability to detect a significant effect, given that the effect actually exists in a population. Like most statistical concepts, statistical power tends to induce cognitive dissonance in hepatology researchers. However, planning for statistical power by an a priori sample size calculation is of paramount importance when designing a research study. There are five specific empirical components that make up an a priori sample size calculation: the scale of measurement of the outcome, the research design, the magnitude of the effect size, the variance of the effect size, and the sample size. A framework grounded in the phenomenon of isomorphism, or interdependencies amongst different constructs with similar forms, will be presented to understand the isomorphic effects of decisions made on each of the five aforementioned components of statistical power.

  16. Sample size considerations for clinical research studies in nuclear cardiology.

    Science.gov (United States)

    Chiuzan, Cody; West, Erin A; Duong, Jimmy; Cheung, Ken Y K; Einstein, Andrew J

    2015-12-01

    Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software.

  17. Enhanced sun protection of nano-sized metal oxide particles over conventional metal oxide particles: an in vitro comparative study.

    Science.gov (United States)

    Singh, P; Nanda, A

    2014-06-01

    A systematic and detailed study has been designed and conducted, taking into account some of the proposed benefits such as increased efficiency, transparency, unique texture, protection of active ingredient and higher consumer compliance of cosmetics containing nano-sized metal oxides. This study also presents an in vitro method to determine sun protection factor of the investigational sunscreen cream samples containing zinc oxide and titanium dioxide with a varied range of particle size. Finally, a comparative study has been conducted between metal oxide particles, conventional as well as nanoparticles. All the skin cosmetics formulated were thermally stable with a pH ranging from 7.9 to 8.2. Moreover, the fatty acid substance content and residue were found to be analogous to the standard values in each skin cosmetic. The skin cosmetics containing the titanium or zinc oxide nanoparticles were found to have improved spreadability as compared to skin cosmetics containing conventional titanium or zinc oxide particles, respectively. All skin cosmetics were found to have uniform distribution of the particles. The sunscreen creams containing zinc oxide nanoparticles and titanium dioxide nanoparticles were found to have higher in vitro sun protection factor (SPF of 3.65 for ZnO nanoparticles and 4.93 for TiO2 nanoparticles) as compared to that of sunscreen creams containing conventional zinc oxide particles (SPF = 2.90) and conventional titanium dioxide (SPF = 1.29), clearly indicating the effect of reduction in particles size, from micro to nano, on the sun protection factor. Good texture, better spreadability and enhanced in vitro SPF proved the advantageous role of nanoparticles in cosmetics. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

  18. SEM analysis of particle size during conventional treatment of CMP process wastewater.

    Science.gov (United States)

    Roth, Gary A; Neu-Baker, Nicole M; Brenner, Sara A

    2015-03-01

    Engineered nanomaterials (ENMs) are currently employed by many industries and have different physical and chemical properties from their bulk counterparts that may confer different toxicity. Nanoparticles used or generated in semiconductor manufacturing have the potential to enter the municipal waste stream via wastewater and their ultimate fate in the ecosystem is currently unknown. This study investigates the fate of ENMs used in chemical mechanical planarization (CMP), a polishing process repeatedly utilized in semiconductor manufacturing. Wastewater sampling was conducted throughout the wastewater treatment (WWT) process at the fabrication plant's on-site wastewater treatment facility. The goal of this study was to assess whether the WWT processes resulted in size-dependent filtration of particles in the nanoscale regime by analyzing samples using scanning electron microscopy (SEM). Statistical analysis demonstrated no significant differences in particle size between sampling points, indicating low or no selectivity of WWT methods for nanoparticles based on size. All nanoparticles appeared to be of similar morphology (near-spherical), with a high variability in particle size. EDX verified nanoparticles composition of silicon- and/or aluminum-oxide. Nanoparticle sizing data compared between sampling points, including the final sampling point before discharge from the facility, suggested that nanoparticles could be released to the municipal waste stream from industrial sources. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Sample size for collecting germplasms–a polyploid model with ...

    Indian Academy of Sciences (India)

    Numerous expressions/results developed for germplasm collection/regeneration for diploid populations by earlier workers can be directly deduced from our general expression by assigning appropriate values of the corresponding parameters. A seed factor which influences the plant sample size has also been isolated to ...

  20. Sample size for collecting germplasms – a polyploid model with ...

    Indian Academy of Sciences (India)

    Unknown

    germplasm collection/regeneration for diploid populations by earlier workers can be directly deduced from our general expression by assigning appropriate values of the corresponding parameters. A seed factor which influences the plant sample size has also been isolated to aid the collectors in selecting the appropriate.

  1. Research Note Pilot survey to assess sample size for herbaceous ...

    African Journals Online (AJOL)

    A pilot survey to determine sub-sample size (number of point observations per plot) for herbaceous species composition assessments, using a wheel-point apparatus applying the nearest-plant method, was conducted. Three plots differing in species composition on the Zululand coastal plain were selected, and on each plot ...

  2. Determining sample size for assessing species composition in ...

    African Journals Online (AJOL)

    Species composition is measured in grasslands for a variety of reasons. Commonly, observations are made using the wheel-point apparatus, but the problem of determining optimum sample size has not yet been satisfactorily resolved. In this study the wheel-point apparatus was used to record 2 000 observations in each of ...

  3. Conservative Sample Size Determination for Repeated Measures Analysis of Covariance

    OpenAIRE

    Timothy M Morgan; Case, L. Douglas

    2013-01-01

    In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time.

  4. Sample Size Determinations for the Two Rater Kappa Statistic.

    Science.gov (United States)

    Flack, Virginia F.; And Others

    1988-01-01

    A method is presented for determining sample size that will achieve a pre-specified bound on confidence interval width for the interrater agreement measure "kappa." The same results can be used when a pre-specified power is desired for testing hypotheses about the value of kappa. (Author/SLD)

  5. Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

    Science.gov (United States)

    Duncanson, L.; Rourke, O.; Dubayah, R.

    2015-11-01

    Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height and crown radius. We use LiDAR remote sensing to isolate between 10,000 to more than 1,000,000 tree height and crown radius measurements per site in six U.S. forests. We find that fitted allometric parameters are highly sensitive to sample size, producing systematic overestimates of height. We extend our analysis to biomass through the application of empirical relationships from the literature, and show that given the small sample sizes used in common allometric equations for biomass, the average site-level biomass bias is ~+70% with a standard deviation of 71%, ranging from -4% to +193%. These findings underscore the importance of increasing the sample sizes used for allometric equation generation.

  6. Mongoloid-Caucasoid Differences in Brain Size from Military Samples.

    Science.gov (United States)

    Rushton, J. Philippe; And Others

    1991-01-01

    Calculation of cranial capacities for the means from 4 Mongoloid and 20 Caucasoid samples (raw data from 57,378 individuals in 1978) found larger brain size for Mongoloids, a finding discussed in evolutionary terms. The conclusion is disputed by L. Willerman but supported by J. P. Rushton. (SLD)

  7. Sensory profiles of bread made from paired samples of organic and conventionally grown wheat grain.

    Science.gov (United States)

    Annett, L E; Spaner, D; Wismer, W V

    2007-05-01

    The Canadian hard red spring wheat cultivar "Park" was grown in 2005 in Edmonton, AB, Canada on both conventionally and organically managed land, situated less than 1 km apart. Grains from the paired wheat samples were compared for cereal-grain-quality attributes. For sensory analysis, organically and conventionally produced wheat grains were milled into flour and baked into 60% whole wheat bread. Color, texture, taste, and aroma attributes of bread were compared using the sensory technique of descriptive analysis. Organic grain contained more wholemeal protein than conventional grain (P grain quality for yeast-leavened bread. Mixograph analysis revealed that conventional flour produced stronger bread dough than organic flour (P 0.05), but the panel perceived the organic bread to be more "dense" in texture (P < or = 0.05) with smaller air cells in the appearance of the crumb (P < or = 0.05) than conventional bread.

  8. Sample size and power calculation for molecular biology studies.

    Science.gov (United States)

    Jung, Sin-Ho

    2010-01-01

    Sample size calculation is a critical procedure when designing a new biological study. In this chapter, we consider molecular biology studies generating huge dimensional data. Microarray studies are typical examples, so that we state this chapter in terms of gene microarray data, but the discussed methods can be used for design and analysis of any molecular biology studies involving high-dimensional data. In this chapter, we discuss sample size calculation methods for molecular biology studies when the discovery of prognostic molecular markers is performed by accurately controlling false discovery rate (FDR) or family-wise error rate (FWER) in the final data analysis. We limit our discussion to the two-sample case.

  9. Aerosol Sampling Bias from Differential Electrostatic Charge and Particle Size

    Science.gov (United States)

    Jayjock, Michael Anthony

    Lack of reliable epidemiological data on long term health effects of aerosols is due in part to inadequacy of sampling procedures and the attendant doubt regarding the validity of the concentrations measured. Differential particle size has been widely accepted and studied as a major potential biasing effect in the sampling of such aerosols. However, relatively little has been done to study the effect of electrostatic particle charge on aerosol sampling. The objective of this research was to investigate the possible biasing effects of differential electrostatic charge, particle size and their interaction on the sampling accuracy of standard aerosol measuring methodologies. Field studies were first conducted to determine the levels and variability of aerosol particle size and charge at two manufacturing facilities making acrylic powder. The field work showed that the particle mass median aerodynamic diameter (MMAD) varied by almost an order of magnitude (4-34 microns) while the aerosol surface charge was relatively stable (0.6-0.9 micro coulombs/m('2)). The second part of this work was a series of laboratory experiments in which aerosol charge and MMAD were manipulated in a 2('n) factorial design with the percentage of sampling bias for various standard methodologies as the dependent variable. The experiments used the same friable acrylic powder studied in the field work plus two size populations of ground quartz as a nonfriable control. Despite some ill conditioning of the independent variables due to experimental difficulties, statistical analysis has shown aerosol charge (at levels comparable to those measured in workroom air) is capable of having a significant biasing effect. Physical models consistent with the sampling data indicate that the level and bipolarity of the aerosol charge are determining factors in the extent and direction of the bias.

  10. Effects of sample size on KERNEL home range estimates

    Science.gov (United States)

    Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.

    1999-01-01

    Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.

  11. A simulated Experiment for Sampling Soil Micriarthropods to Reduce Sample Size

    OpenAIRE

    Tamura, Hiroshi

    1987-01-01

    An experiment was conducted to examine a possibility of reducing the necessary sample size in a quantitative survey on soil microarthropods, using soybeans instead of animals. An artificially provided, intensely aggregated distribution pattern of soybeans was easily transformed to the random pattern by stirring the substrate, which is soil in a large cardboard box. This enabled the necessary sample size to be greatly reduced without sacrificing the statistical reliability. A new practical met...

  12. Quantity of remaining bacteria and cavity size after excavation with FACE, caries detector dye and conventional excavation in vitro.

    Science.gov (United States)

    Lennon, Aine M; Attin, Thomas; Buchalla, Wolfgang

    2007-01-01

    In this in vitro study, quantitative confocal microscopy was used to show differences in the quantity of bacteria remaining in dentin after excavation with different methods. A further parameter was the cavity volume after excavation relative to the original lesion size. Teeth with dentin caries were divided into three groups of 20 each. The caries was removed by a single operator using a slow handpiece and a round bur. In the first group, Fluorescence Aided Caries Excavation (FACE) was carried out: violet light was used to illuminate the operating field and the operator observed the cavity through a high-pass filter and removed the orange-red fluorescing areas. The second group was excavated using Caries Detector, while the third group used conventional excavation. After excavation, cavity volume was measured; samples were stained for bacteria with ethidium bromide, and they were examined using confocal microscopy under standardized conditions. The bound stain was quantified in terms of fluorescence intensity on the confocal images. Total pixel intensity was significantly lower in the FACE Group than in the Caries Detector group (p = 0.046) and in the conventional excavation group (p = 0.021). Differences in cavity volume relative to original lesion size were not statistically significant (p = 0.86, 0.35 and 0.51). Within the limitations of this in vitro study, it can be concluded that FACE is more effective in removing infected dentin without significantly increasing cavity size when compared to conventional excavation and excavation with the aid of caries detector dye.

  13. Estimation of individual reference intervals in small sample sizes

    DEFF Research Database (Denmark)

    Hansen, Ase Marie; Garde, Anne Helene; Eller, Nanna Hurwitz

    2007-01-01

    In occupational health studies, the study groups most often comprise healthy subjects performing their work. Sampling is often planned in the most practical way, e.g., sampling of blood in the morning at the work site just after the work starts. Optimal use of reference intervals requires...... of that order of magnitude for all topics in question. Therefore, new methods to estimate reference intervals for small sample sizes are needed. We present an alternative method based on variance component models. The models are based on data from 37 men and 84 women taking into account biological variation...... presented in this study. The presented method enables occupational health researchers to calculate reference intervals for specific groups, i.e. smokers versus non-smokers, etc. In conclusion, the variance component models provide an appropriate tool to estimate reference intervals based on small sample...

  14. Sample size determination for longitudinal designs with binary response.

    Science.gov (United States)

    Kapur, Kush; Bhaumik, Runa; Tang, X Charlene; Hur, Kwan; Reda, Domenic J; Bhaumik, Dulal K

    2014-09-28

    In this article, we develop appropriate statistical methods for determining the required sample size while comparing the efficacy of an intervention to a control with repeated binary response outcomes. Our proposed methodology incorporates the complexity of the hierarchical nature of underlying designs and provides solutions when varying attrition rates are present over time. We explore how the between-subject variability and attrition rates jointly influence the computation of sample size formula. Our procedure also shows how efficient estimation methods play a crucial role in power analysis. A practical guideline is provided when information regarding individual variance component is unavailable. The validity of our methods is established by extensive simulation studies. Results are illustrated with the help of two randomized clinical trials in the areas of contraception and insomnia. Copyright © 2014 John Wiley & Sons, Ltd.

  15. A power analysis for fidelity measurement sample size determination.

    Science.gov (United States)

    Stokes, Lynne; Allor, Jill H

    2016-03-01

    The importance of assessing fidelity has been emphasized recently with increasingly sophisticated definitions, assessment procedures, and integration of fidelity data into analyses of outcomes. Fidelity is often measured through observation and coding of instructional sessions either live or by video. However, little guidance has been provided about how to determine the number of observations needed to precisely measure fidelity. We propose a practical method for determining a reasonable sample size for fidelity data collection when fidelity assessment requires observation. The proposed methodology is based on consideration of the power of tests of the treatment effect of outcome itself, as well as of the relationship between fidelity and outcome. It makes use of the methodology of probability sampling from a finite population, because the fidelity parameters of interest are estimated over a specific, limited time frame using a sample. For example, consider a fidelity measure defined as the number of minutes of exposure to a treatment curriculum during the 36 weeks of the study. In this case, the finite population is the 36 sessions, the parameter (number of minutes over the entire 36 sessions) is a total, and the sample is the observed sessions. Software for the sample size calculation is provided. (c) 2016 APA, all rights reserved).

  16. Effects of sample size on the second magnetization peak in ...

    Indian Academy of Sciences (India)

    *E-mail: yeshurun@mail.biu.ac.il. Abstract. Effects of sample size on the second magnetization peak (SMP) in. Bi2Sr2CaCuO8+δ crystals are ... a termination of the measured transition line at Tl, typically 17–20 K (see figure 1). The obscuring and eventual disappearance of the SMP with decreasing tempera- tures has been ...

  17. Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

    OpenAIRE

    Duncanson, L.; Rourke, O.; Dubayah, R.

    2015-01-01

    Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height a...

  18. Simple and multiple linear regression: sample size considerations.

    Science.gov (United States)

    Hanley, James A

    2016-11-01

    The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Differences between Internet samples and conventional samples of men who have sex with men: implications for research and HIV interventions.

    Science.gov (United States)

    Ross, M W; Tikkanen, R; Månsson, S A

    2000-09-01

    The Internet is becoming a new erotic oasis for obtaining sex online or in person. We reviewed the literature on cybersex and compared differences in data from samples of homosexually active men obtained on identical questionnaires from a conventional written questionnaire, distributed through the mailing and contact lists of a large national gay organization in Sweden, and through the same organization's website and chat room. A total of 716 written questionnaires and 678 Internet questionnaires were obtained. The Internet sample was younger, more likely to live in small towns or cities, live with parents or a girlfriend, and have lower formal education. They are less likely to have previous sexual experience solely with other men (one in three of the Internet sample vs. 1 in 14 of the written sample defined themselves as bisexual) and more likely to visit erotic oases such as bathhouses, video clubs and erotic movie houses. They also visited Internet chat rooms more frequently (86% of the Internet sample vs. 50% of the written sample). One third of the Internet sample wanted the opportunity to talk with an expert about HIV compared with a quarter of the written sample. Sexual practices between the two samples were generally similar, although the Internet sample reported significantly less body contact, kissing, hugging, mutual masturbation, and more condom use for anal intercourse with steady partners. Over four times as many of the Internet samples reported sex with women in the past year as the written sample. These data indicate that Internet data collection is feasible and that this mode of data collection, despite the nonrandom and self-selected nature of both types of samples, is likely to be more significantly oriented toward the young, geographically more isolated, and more behaviorally and self-identified bisexual respondent than conventionally distributed written questionnaires.

  20. Sample size of the reference sample in a case-augmented study.

    Science.gov (United States)

    Ghosh, Palash; Dewanji, Anup

    2017-05-01

    The case-augmented study, in which a case sample is augmented with a reference (random) sample from the source population with only covariates information known, is becoming popular in different areas of applied science such as pharmacovigilance, ecology, and econometrics. In general, the case sample is available from some source (for example, hospital database, case registry, etc.); however, the reference sample is required to be drawn from the corresponding source population. The required minimum size of the reference sample is an important issue in this regard. In this work, we address the minimum sample size calculation and discuss related issues. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  1. MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach

    OpenAIRE

    Nyamundanda, Gift; Gormley, Isobel Claire; Fan, Yue; Gallagher, William M.; Brennan, Lorraine

    2013-01-01

    Background: Determining sample sizes for metabolomic experiments is important but due to the complexity of these experiments, there are currently no standard methods for sample size estimation in metabolomics. Since pilot studies are rarely done in metabolomics, currently existing sample size estimation approaches which rely on pilot data can not be applied. Results: In this article, an analysis based approach called MetSizeR is developed to estimate sample size for metabolomic experime...

  2. It's in the Sample: The Effects of Sample Size and Sample Diversity on the Breadth of Inductive Generalization

    Science.gov (United States)

    Lawson, Chris A.; Fisher, Anna V.

    2011-01-01

    Developmental studies have provided mixed evidence with regard to the question of whether children consider sample size and sample diversity in their inductive generalizations. Results from four experiments with 105 undergraduates, 105 school-age children (M = 7.2 years), and 105 preschoolers (M = 4.9 years) showed that preschoolers made a higher…

  3. QUANTITATIVE VS. CONVENTIONAL PCR FOR DETECTION OF HUMAN ADENOVIRUSES IN WATER AND SEDIMENT SAMPLES

    Directory of Open Access Journals (Sweden)

    Rodrigo STAGGEMEIER

    2015-08-01

    Full Text Available SUMMARY Human Adenoviruses (HAdV are notably resistant in the environment. These agents may serve as effective indicators of fecal contamination, and may act as causative agents of a number of different diseases in human beings. Conventional polymerase chain reaction (PCR and, more recently, quantitative PCR (qPCR are widely used for detection of viral agents in environmental matrices. In the present study PCR and SYBR(rGreen qPCR assays were compared for detection of HAdV in water (55 and sediments (20 samples of spring and artesian wells, ponds and streams, collected from dairy farms. By the quantitative methodology HAdV were detected in 87.3% of the water samples and 80% of the sediments, while by the conventional PCR 47.3% and 35% were detected in water samples and sediments, respectively.

  4. Size Matters: FTIR Spectral Analysis of Apollo Regolith Samples Exhibits Grain Size Dependence.

    Science.gov (United States)

    Martin, Dayl; Joy, Katherine; Pernet-Fisher, John; Wogelius, Roy; Morlok, Andreas; Hiesinger, Harald

    2017-04-01

    The Mercury Thermal Infrared Spectrometer (MERTIS) on the upcoming BepiColombo mission is designed to analyse the surface of Mercury in thermal infrared wavelengths (7-14 μm) to investigate the physical properties of the surface materials [1]. Laboratory analyses of analogue materials are useful for investigating how various sample properties alter the resulting infrared spectrum. Laboratory FTIR analysis of Apollo fine (exposure to space weathering processes), and proportion of glassy material affect their average infrared spectra. Each of these samples was analysed as a bulk sample and five size fractions: 60%) causes a 'flattening' of the spectrum, with reduced reflectance in the Reststrahlen Band region (RB) as much as 30% in comparison to samples that are dominated by a high proportion of crystalline material. Apollo 15401,147 is an immature regolith with a high proportion of volcanic glass pyroclastic beads [2]. The high mafic mineral content results in a systematic shift in the Christiansen Feature (CF - the point of lowest reflectance) to longer wavelength: 8.6 μm. The glass beads dominate the spectrum, displaying a broad peak around the main Si-O stretch band (at 10.8 μm). As such, individual mineral components of this sample cannot be resolved from the average spectrum alone. Apollo 67481,96 is a sub-mature regolith composed dominantly of anorthite plagioclase [2]. The CF position of the average spectrum is shifted to shorter wavelengths (8.2 μm) due to the higher proportion of felsic minerals. Its average spectrum is dominated by anorthite reflectance bands at 8.7, 9.1, 9.8, and 10.8 μm. The average reflectance is greater than the other samples due to a lower proportion of glassy material. In each soil, the smallest fractions (0-25 and 25-63 μm) have CF positions 0.1-0.4 μm higher than the larger grain sizes. Also, the bulk-sample spectra mostly closely resemble the 0-25 μm sieved size fraction spectrum, indicating that this size fraction of each

  5. Variance estimation, design effects, and sample size calculations for respondent-driven sampling.

    Science.gov (United States)

    Salganik, Matthew J

    2006-11-01

    Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling.

  6. Sample size requirement in analytical studies for similarity assessment.

    Science.gov (United States)

    Chow, Shein-Chung; Song, Fuyu; Bai, He

    2017-01-01

    For the assessment of biosimilar products, the FDA recommends a stepwise approach for obtaining the totality-of-the-evidence for assessing biosimilarity between a proposed biosimilar product and its corresponding innovative biologic product. The stepwise approach starts with analytical studies for assessing similarity in critical quality attributes (CQAs), which are relevant to clinical outcomes at various stages of the manufacturing process. For CQAs that are the most relevant to clinical outcomes, the FDA requires an equivalence test be performed for similarity assessment based on an equivalence acceptance criterion (EAC) that is obtained using a single test value of some selected reference lots. In practice, we often have extremely imbalanced numbers of reference and test lots available for the establishment of EAC. In this case, to assist the sponsors, the FDA proposed an idea for determining the number of reference lots and the number of test lots required in order not to have imbalanced sample sizes when establishing EAC for the equivalence test based on extensive simulation studies. Along this line, this article not only provides statistical justification of Dong, Tsong, and Weng's proposal, but also proposes an alternative method for sample size requirement for the Tier 1 equivalence test.

  7. Comparative efficacy of conventional and taqman polymerase chain reaction assays in the detection of capripoxviruses from clinical samples.

    Science.gov (United States)

    Balamurugan, Vinayagamurthy; Jayappa, Kallesh Danappa; Hosamani, Madhusudhan; Bhanuprakash, Veerakyathappa; Venkatesan, Gnanavel; Singh, Raj Kumar

    2009-03-01

    Sheeppox and goatpox are economically important viral diseases of sheep and goats, respectively. Both diseases are reportable to the World Organization for Animal Health. To implement a control and eradication program for these diseases, a rapid and user-friendly diagnostic tool is imperative for screening. Therefore, in the present study, TaqMan quantitative polymerase chain reaction (qPCR) and conventional PCR assays targeting the DNA polymerase (DNA pol) gene were developed for the detection of Capripoxvirus DNA from clinical specimens of sheep and goats. The 2 assays used different primer sets. Conventional PCR yielded a specific product of 134 bp, whereas qPCR yielded a 180-bp product. The specificity of amplified DNA pol gene products was confirmed by their size and by sequence analysis. The 2 assays were specific for Sheeppox virus and Goatpox virus. However, in comparison to conventional PCR, the qPCR was more rapid, specific, and 100 times more sensitive, with a detection limit as low as 0.042 pg of purified DNA. The qPCR assay was more sensitive (84.05%) than conventional PCR (76.06%) when used on clinical samples (n = 71) from sheep and goats.

  8. MEPAG Recommendations for a 2018 Mars Sample Return Caching Lander - Sample Types, Number, and Sizes

    Science.gov (United States)

    Allen, Carlton C.

    2011-01-01

    The return to Earth of geological and atmospheric samples from the surface of Mars is among the highest priority objectives of planetary science. The MEPAG Mars Sample Return (MSR) End-to-End International Science Analysis Group (MEPAG E2E-iSAG) was chartered to propose scientific objectives and priorities for returned sample science, and to map out the implications of these priorities, including for the proposed joint ESA-NASA 2018 mission that would be tasked with the crucial job of collecting and caching the samples. The E2E-iSAG identified four overarching scientific aims that relate to understanding: (A) the potential for life and its pre-biotic context, (B) the geologic processes that have affected the martian surface, (C) planetary evolution of Mars and its atmosphere, (D) potential for future human exploration. The types of samples deemed most likely to achieve the science objectives are, in priority order: (1A). Subaqueous or hydrothermal sediments (1B). Hydrothermally altered rocks or low temperature fluid-altered rocks (equal priority) (2). Unaltered igneous rocks (3). Regolith, including airfall dust (4). Present-day atmosphere and samples of sedimentary-igneous rocks containing ancient trapped atmosphere Collection of geologically well-characterized sample suites would add considerable value to interpretations of all collected rocks. To achieve this, the total number of rock samples should be about 30-40. In order to evaluate the size of individual samples required to meet the science objectives, the E2E-iSAG reviewed the analytical methods that would likely be applied to the returned samples by preliminary examination teams, for planetary protection (i.e., life detection, biohazard assessment) and, after distribution, by individual investigators. It was concluded that sample size should be sufficient to perform all high-priority analyses in triplicate. In keeping with long-established curatorial practice of extraterrestrial material, at least 40% by

  9. Aggregate size distribution in a biochar-amended tropical Ultisol under conventional hand-hoe tillage.

    Science.gov (United States)

    Fungo, Bernard; Lehmann, Johannes; Kalbitz, Karsten; Thionģo, Margaret; Okeyo, Irene; Tenywa, Moses; Neufeldt, Henry

    2017-01-01

    Biochar (or pyrogenic organic matter) is increasingly proposed as a soil amendment for improving fertility, carbon sequestration and reduction of greenhouse gas emissions. However, little is known about its effects on aggregation, an important indicator of soil quality and functioning. The aim of this study was to assess the effect of Eucalyptus wood biochar (B, pyrolyzed at 550 °C, at 0 or 2.5 t ha-1), green manure (T, from Tithonia diversifolia at 0, 2.5 or 5.0 t ha-1) and mineral nitrogen (U, urea, at 0, or 120 kg N ha-1) on soil respiration, aggregate size distribution and SOC in these aggregate size fractions in a 2-year field experiment on a low-fertility Ultisol in western Kenya under conventional hand-hoe tillage. Air-dry 2-mm sieved soils were divided into four fractions by wet sieving: Large Macro-aggregates (LM; >1000 μm); Small Macro-aggregates (SM, 250-1000 μm); Micro-aggregates (M, 250-53 μm) and Silt + Clay (S + C, < 53 μm). We found that biochar alone did not affect a mean weight diameter (MWD) but combined application with either T. diversifolia (BT) or urea (BU) increased MWD by 34 ± 5.2 μm (8%) and 55 ± 5.4 μm (13%), respectively, compared to the control (P = 0.023; n = 36). The B + T + U combination increased the proportion of the LM and SM by 7.0 ± 0.8%, but reduced the S + C fraction by 5.2 ± 0.23%. SOC was 30%, 25% and 23% in S + C, M and LM/SM fractions, and increased by 9.6 ± 1.0, 5.7 ± 0.8, 6.3 ± 1.1 and 4.2 ± 0.9 g kg-1 for LM, SM, M and S + C, respectively. MWD was not related to either soil respiration or soil moisture but decreased with higher SOC (R2  = 0.37, P = 0.014, n = 26) and increased with greater biomass production (R2  = 0.11, P = 0.045, n = 33). Our data suggest that within the timeframe of the study, biochar is stored predominantly as free particulate OC in the silt and clay fraction and promoted a movement of native SOC from larger-size

  10. Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data.

    Science.gov (United States)

    Ying, Jinfa; Delaglio, Frank; Torchia, Dennis A; Bax, Ad

    2017-06-01

    Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.

  11. Large sample area and size are needed for forest soil seed bank studies to ensure low discrepancy with standing vegetation.

    Directory of Open Access Journals (Sweden)

    You-xin Shen

    Full Text Available A large number of small-sized samples invariably shows that woody species are absent from forest soil seed banks, leading to a large discrepancy with the seedling bank on the forest floor. We ask: 1 Does this conventional sampling strategy limit the detection of seeds of woody species? 2 Are large sample areas and sample sizes needed for higher recovery of seeds of woody species? We collected 100 samples that were 10 cm (length × 10 cm (width × 10 cm (depth, referred to as larger number of small-sized samples (LNSS in a 1 ha forest plot, and placed them to germinate in a greenhouse, and collected 30 samples that were 1 m × 1 m × 10 cm, referred to as small number of large-sized samples (SNLS and placed them (10 each in a nearby secondary forest, shrub land and grass land. Only 15.7% of woody plant species of the forest stand were detected by the 100 LNSS, contrasting with 22.9%, 37.3% and 20.5% woody plant species being detected by SNLS in the secondary forest, shrub land and grassland, respectively. The increased number of species vs. sampled areas confirmed power-law relationships for forest stand, the LNSS and SNLS at all three recipient sites. Our results, although based on one forest, indicate that conventional LNSS did not yield a high percentage of detection for woody species, but SNLS strategy yielded a higher percentage of detection for woody species in the seed bank if samples were exposed to a better field germination environment. A 4 m2 minimum sample area derived from power equations is larger than the sampled area in most studies in the literature. Increased sample size also is needed to obtain an increased sample area if the number of samples is to remain relatively low.

  12. Sample size determinations for Welch's test in one-way heteroscedastic ANOVA.

    Science.gov (United States)

    Jan, Show-Li; Shieh, Gwowen

    2014-02-01

    For one-way fixed effects ANOVA, it is well known that the conventional F test of the equality of means is not robust to unequal variances, and numerous methods have been proposed for dealing with heteroscedasticity. On the basis of extensive empirical evidence of Type I error control and power performance, Welch's procedure is frequently recommended as the major alternative to the ANOVA F test under variance heterogeneity. To enhance its practical usefulness, this paper considers an important aspect of Welch's method in determining the sample size necessary to achieve a given power. Simulation studies are conducted to compare two approximate power functions of Welch's test for their accuracy in sample size calculations over a wide variety of model configurations with heteroscedastic structures. The numerical investigations show that Levy's (1978a) approach is clearly more accurate than the formula of Luh and Guo (2011) for the range of model specifications considered here. Accordingly, computer programs are provided to implement the technique recommended by Levy for power calculation and sample size determination within the context of the one-way heteroscedastic ANOVA model. © 2013 The British Psychological Society.

  13. 40 CFR 761.243 - Standard wipe sample method and size.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Standard wipe sample method and size... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas...

  14. Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.

    Science.gov (United States)

    Guo, Jiin-Huarng; Luh, Wei-Ming

    2009-05-01

    When planning a study, sample size determination is one of the most important tasks facing the researcher. The size will depend on the purpose of the study, the cost limitations, and the nature of the data. By specifying the standard deviation ratio and/or the sample size ratio, the present study considers the problem of heterogeneous variances and non-normality for Yuen's two-group test and develops sample size formulas to minimize the total cost or maximize the power of the test. For a given power, the sample size allocation ratio can be manipulated so that the proposed formulas can minimize the total cost, the total sample size, or the sum of total sample size and total cost. On the other hand, for a given total cost, the optimum sample size allocation ratio can maximize the statistical power of the test. After the sample size is determined, the present simulation applies Yuen's test to the sample generated, and then the procedure is validated in terms of Type I errors and power. Simulation results show that the proposed formulas can control Type I errors and achieve the desired power under the various conditions specified. Finally, the implications for determining sample sizes in experimental studies and future research are discussed.

  15. Comparison of conventional Papanicolaou cytology samples with liquid-based cervical cytology samples from women in Pernambuco, Brazil

    Directory of Open Access Journals (Sweden)

    M.O.L.P. Costa

    2015-01-01

    Full Text Available In the present study, we compared the performance of a ThinPrep cytological method with the conventional Papanicolaou test for diagnosis of cytopathological changes, with regard to unsatisfactory results achieved at the Central Public Health Laboratory of the State of Pernambuco. A population-based, cross-sectional study was performed with women aged 18 to 65 years, who spontaneously sought gynecological services in Public Health Units in the State of Pernambuco, Northeast Brazil, between April and November 2011. All patients in the study were given a standardized questionnaire on sociodemographics, sexual characteristics, reproductive practices, and habits. A total of 525 patients were assessed by the two methods (11.05% were under the age of 25 years, 30.86% were single, 4.4% had had more than 5 sexual partners, 44% were not using contraception, 38.85% were users of alcohol, 24.38% were smokers, 3.24% had consumed drugs previously, 42.01% had gynecological complaints, and 12.19% had an early history of sexually transmitted diseases. The two methods showed poor correlation (k=0.19; 95%CI=0.11–0.26; P<0.001. The ThinPrep method reduced the rate of unsatisfactory results from 4.38% to 1.71% (χ2=5.28; P=0.02, and the number of cytopathological changes diagnosed increased from 2.47% to 3.04%. This study confirmed that adopting the ThinPrep method for diagnosis of cervical cytological samples was an improvement over the conventional method. Furthermore, this method may reduce possible losses from cytological resampling and reduce obstacles to patient follow-up, improving the quality of the public health system in the State of Pernambuco, Northeast Brazil.

  16. Comparing Server Energy Use and Efficiency Using Small Sample Sizes

    Energy Technology Data Exchange (ETDEWEB)

    Coles, Henry C.; Qin, Yong; Price, Phillip N.

    2014-11-01

    This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency. The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro. Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured. At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a

  17. On Using a Pilot Sample Variance for Sample Size Determination in the Detection of Differences between Two Means: Power Consideration

    Science.gov (United States)

    Shieh, Gwowen

    2013-01-01

    The a priori determination of a proper sample size necessary to achieve some specified power is an important problem encountered frequently in practical studies. To establish the needed sample size for a two-sample "t" test, researchers may conduct the power analysis by specifying scientifically important values as the underlying population means…

  18. Effect size measures in a two-independent-samples case with nonnormal and nonhomogeneous data.

    Science.gov (United States)

    Li, Johnson Ching-Hong

    2016-12-01

    In psychological science, the "new statistics" refer to the new statistical practices that focus on effect size (ES) evaluation instead of conventional null-hypothesis significance testing (Cumming, Psychological Science, 25, 7-29, 2014). In a two-independent-samples scenario, Cohen's (1988) standardized mean difference (d) is the most popular ES, but its accuracy relies on two assumptions: normality and homogeneity of variances. Five other ESs-the unscaled robust d (d r* ; Hogarty & Kromrey, 2001), scaled robust d (d r ; Algina, Keselman, & Penfield, Psychological Methods, 10, 317-328, 2005), point-biserial correlation (r pb ; McGrath & Meyer, Psychological Methods, 11, 386-401, 2006), common-language ES (CL; Cliff, Psychological Bulletin, 114, 494-509, 1993), and nonparametric estimator for CL (A w ; Ruscio, Psychological Methods, 13, 19-30, 2008)-may be robust to violations of these assumptions, but no study has systematically evaluated their performance. Thus, in this simulation study the performance of these six ESs was examined across five factors: data distribution, sample, base rate, variance ratio, and sample size. The results showed that A w and d r were generally robust to these violations, and A w slightly outperformed d r . Implications for the use of A w and d r in real-world research are discussed.

  19. Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

    Science.gov (United States)

    Algina, James; Olejnik, Stephen

    2000-01-01

    Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

  20. (Sample) size matters! An examination of sample size from the SPRINT trial study to prospectively evaluate reamed intramedullary nails in patients with tibial fractures

    NARCIS (Netherlands)

    Bhandari, Mohit; Tornetta, Paul; Rampersad, Shelly-Ann; Sprague, Sheila; Heels-Ansdell, Diane; Sanders, David W.; Schemitsch, Emil H.; Swiontkowski, Marc; Walter, Stephen; Guyatt, Gordon; Buckingham, Lisa; Leece, Pamela; Viveiros, Helena; Mignott, Tashay; Ansell, Natalie; Sidorkewicz, Natalie; Agel, Julie; Bombardier, Claire; Berlin, Jesse A.; Bosse, Michael; Browner, Bruce; Gillespie, Brenda; O'Brien, Peter; Poolman, Rudolf; Macleod, Mark D.; Carey, Timothy; Leitch, Kellie; Bailey, Stuart; Gurr, Kevin; Konito, Ken; Bartha, Charlene; Low, Isolina; MacBean, Leila V.; Ramu, Mala; Reiber, Susan; Strapp, Ruth; Tieszer, Christina; Kreder, Hans; Stephen, David J. G.; Axelrod, Terry S.; Yee, Albert J. M.; Richards, Robin R.; Finkelstein, Joel; Holtby, Richard M.; Cameron, Hugh; Cameron, John; Gofton, Wade; Murnaghan, John; Schatztker, Joseph; Bulmer, Beverly; Conlan, Lisa; Laflamme, Yves; Berry, Gregory; Beaumont, Pierre; Ranger, Pierre; Laflamme, Georges-Henri; Jodoin, Alain; Renaud, Eric; Gagnon, Sylvain; Maurais, Gilles; Malo, Michel; Fernandes, Julio; Latendresse, Kim; Poirier, Marie-France; Daigneault, Gina; McKee, Michael M.; Waddell, James P.; Bogoch, Earl R.; Daniels, Timothy R.; McBroom, Robert R.; Vicente, Milena R.; Storey, Wendy; Wild, Lisa M.; McCormack, Robert; Perey, Bertrand; Goetz, Thomas J.; Pate, Graham; Penner, Murray J.; Panagiotopoulos, Kostas; Pirani, Shafique; Dommisse, Ian G.; Loomer, Richard L.; Stone, Trevor; Moon, Karyn; Zomar, Mauri; Webb, Lawrence X.; Teasdall, Robert D.; Birkedal, John Peter; Martin, David Franklin; Ruch, David S.; Kilgus, Douglas J.; Pollock, David C.; Harris, Mitchel Brion; Wiesler, Ethan Ron; Ward, William G.; Shilt, Jeffrey Scott; Koman, Andrew L.; Poehling, Gary G.; Kulp, Brenda; Creevy, William R.; Stein, Andrew B.; Bono, Christopher T.; Einhorn, Thomas A.; Brown, T. Desmond; Pacicca, Donna; Sledge, John B.; Foster, Timothy E.; Voloshin, Ilva; Bolton, Jill; Carlisle, Hope; Shaughnessy, Lisa; Ombremsky, William T.; LeCroy, C. Michael; Meinberg, Eric G.; Messer, Terry M.; Craig, William L.; Dirschl, Douglas R.; Caudle, Robert; Harris, Tim; Elhert, Kurt; Hage, William; Jones, Robert; Piedrahita, Luis; Schricker, Paul O.; Driver, Robin; Godwin, Jean; Hansley, Gloria; Obremskey, William Todd; Kregor, Philip James; Tennent, Gregory; Truchan, Lisa M.; Sciadini, Marcus; Shuler, Franklin D.; Driver, Robin E.; Nading, Mary Alice; Neiderstadt, Jacky; Vap, Alexander R.; Vallier, Heather A.; Patterson, Brendan M.; Wilber, John H.; Wilber, Roger G.; Sontich, John K.; Moore, Timothy Alan; Brady, Drew; Cooperman, Daniel R.; Davis, John A.; Cureton, Beth Ann; Mandel, Scott; Orr, R. Douglas; Sadler, John T. S.; Hussain, Tousief; Rajaratnam, Krishan; Petrisor, Bradley; Drew, Brian; Bednar, Drew A.; Kwok, Desmond C. H.; Pettit, Shirley; Hancock, Jill; Cole, Peter A.; Smith, Joel J.; Brown, Gregory A.; Lange, Thomas A.; Stark, John G.; Levy, Bruce; Swiontkowski, Marc F.; Garaghty, Mary J.; Salzman, Joshua G.; Schutte, Carol A.; Tastad, Linda Toddie; Vang, Sandy; Seligson, David; Roberts, Craig S.; Malkani, Arthur L.; Sanders, Laura; Gregory, Sharon Allen; Dyer, Carmen; Heinsen, Jessica; Smith, Langan; Madanagopal, Sudhakar; Coupe, Kevin J.; Tucker, Jeffrey J.; Criswell, Allen R.; Buckle, Rosemary; Rechter, Alan Jeffrey; Sheth, Dhiren Shaskikant; Urquart, Brad; Trotscher, Thea; Anders, Mark J.; Kowalski, Joseph M.; Fineberg, Marc S.; Bone, Lawrence B.; Phillips, Matthew J.; Rohrbacher, Bernard; Stegemann, Philip; Mihalko, William M.; Buyea, Cathy; Augustine, Stephen J.; Jackson, William Thomas; Solis, Gregory; Ero, Sunday U.; Segina, Daniel N.; Berrey, Hudson B.; Agnew, Samuel G.; Fitzpatrick, Michael; Campbell, Lakina C.; Derting, Lynn; McAdams, June; Goslings, J. Carel; Ponsen, Kees Jan; Luitse, Jan; Kloen, Peter; Joosse, Pieter; Winkelhagen, Jasper; Duivenvoorden, Raphaël; Teague, David C.; Davey, Joseph; Sullivan, J. Andy; Ertl, William J. J.; Puckett, Timothy A.; Pasque, Charles B.; Tompkins, John F.; Gruel, Curtis R.; Kammerlocher, Paul; Lehman, Thomas P.; Puffinbarger, William R.; Carl, Kathy L.; Weber, Donald W.; Jomha, Nadr M.; Goplen, Gordon R.; Masson, Edward; Beaupre, Lauren A.; Greaves, Karen E.; Schaump, Lori N.; Jeray, Kyle J.; Goetz, David R.; Westberry, Davd E.; Broderick, J. Scott; Moon, Bryan S.; Tanner, Stephanie L.; Powell, James N.; Buckley, Richard E.; Elves, Leslie; Connolly, Stephen; Abraham, Edward P.; Eastwood, Donna; Steele, Trudy; Ellis, Thomas; Herzberg, Alex; Brown, George A.; Crawford, Dennis E.; Hart, Robert; Hayden, James; Orfaly, Robert M.; Vigland, Theodore; Vivekaraj, Maharani; Bundy, Gina L.; Miclau, Theodore; Matityahu, Amir; Coughlin, R. Richard; Kandemir, Utku; McClellan, R. Trigg; Lin, Cindy Hsin-Hua; Karges, David; Cramer, Kathryn; Watson, J. Tracy; Moed, Berton; Scott, Barbara; Beck, Dennis J.; Orth, Carolyn; Puskas, David; Clark, Russell; Jones, Jennifer; Egol, Kenneth A.; Paksima, Nader; France, Monet; Wai, Eugene K.; Johnson, Garth; Wilkinson, Ross; Gruszczynski, Adam T.; Vexler, Liisa

    2013-01-01

    Inadequate sample size and power in randomized trials can result in misleading findings. This study demonstrates the effect of sample size in a large clinical trial by evaluating the results of the Study to Prospectively evaluate Reamed Intramedullary Nails in Patients with Tibial fractures (SPRINT)

  1. New and conventional pore size tests in virus-removing membranes

    NARCIS (Netherlands)

    Duek, A.; Arkhangelsky, E.; Krush, R.; Brenner, A.; Gitis, V.

    2012-01-01

    Microorganisms are retained by ultrafiltration (UF) membranes mainly due to size exclusion. The sizes of viruses and membrane pores are close to each other and retention of viruses can be guaranteed only if the precise pore diameter is known. Unfortunately and rather surprisingly, there is no direct

  2. Feed particle size evaluation: conventional approach versus digital holography based image analysis

    Directory of Open Access Journals (Sweden)

    Vittorio Dell’Orto

    2010-01-01

    Full Text Available The aim of this study was to evaluate the application of image analysis approach based on digital holography in defining particle size in comparison with the sieve shaker method (sieving method as reference method. For this purpose ground corn meal was analyzed by a sieve shaker Retsch VS 1000 and by image analysis approach based on digital holography. Particle size from digital holography were compared with results obtained by screen (sieving analysis for each of size classes by a cumulative distribution plot. Comparison between particle size values obtained by sieving method and image analysis indicated that values were comparable in term of particle size information, introducing a potential application for digital holography and image analysis in feed industry.

  3. Size variation in samples of fossil and recent murid teeth

    NARCIS (Netherlands)

    Freudenthal, M.; Martín Suárez, E.

    1990-01-01

    The variability coefficient proposed by Freudenthal & Cuenca Bescós (1984) for samples of fossil cricetid teeth, is calculated for about 200 samples of fossil and recent murid teeth. The results are discussed, and compared with those obtained for the Cricetidae.

  4. Sample Size Determination for Regression Models Using Monte Carlo Methods in R

    Science.gov (United States)

    Beaujean, A. Alexander

    2014-01-01

    A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…

  5. Distance software: design and analysis of distance sampling surveys for estimating population size.

    Science.gov (United States)

    Thomas, Len; Buckland, Stephen T; Rexstad, Eric A; Laake, Jeff L; Strindberg, Samantha; Hedley, Sharon L; Bishop, Jon Rb; Marques, Tiago A; Burnham, Kenneth P

    2010-02-01

    1.Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance.2.We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use.3.Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated.4.A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark-recapture distance sampling, which relaxes the assumption of certain detection at zero distance.5.All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap.6.Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software.7.Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of-the-art software that implements these methods is described that makes the methods

  6. Use of Conventional and Alternative Tobacco and Nicotine Products Among a Sample of Canadian Youth.

    Science.gov (United States)

    Czoli, Christine D; Hammond, David; Reid, Jessica L; Cole, Adam G; Leatherdale, Scott T

    2015-07-01

    The purpose of this study was to examine the use of conventional and alternative tobacco and nicotine products among secondary school students. Respondents were 44,163 grade 9-12 students who participated in Year 2 (2013-2014) of COMPASS, a cohort study of 89 purposefully sampled secondary schools in Ontario and Alberta, Canada. Past-month use of various tobacco and nicotine products was assessed, as well as correlates of use, using a generalized linear mixed effects model. Overall, 21.2% of the sample reported past-month use of any tobacco or nicotine product, with 7.2% reporting past-month use of e-cigarettes. E-cigarette users reported significantly greater prevalence of current use for all products. Students who were male, white, had more spending money, and had a history of tobacco use were more likely to report past-month use of e-cigarettes. Approximately one fifth of youth reported past-month use of a nicotine product, with e-cigarettes being the third most common product. Overall, the findings suggest a rapidly evolving nicotine market. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  7. Sample size reduction in groundwater surveys via sparse data assimilation

    KAUST Repository

    Hussain, Z.

    2013-04-01

    In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.

  8. Practical Approaches For Determination Of Sample Size In Paired Case-Control Studies

    OpenAIRE

    Demirel, Neslihan; Ozlem EGE ORUC; Gurler, Selma

    2016-01-01

    Objective: Cross-over design or paired case control studies that are using in clinical studies are the methods of design of experiments which requires dependent samples. The problem of sample size determination is generally difficult step of planning the statistical design. The aim of this study is to provide the researchers a practical approach for determining the sample size in paired control studies. Material and Methods: In this study, determination of sample size is mentioned in detail i...

  9. Effects of sample size on estimation of rainfall extremes at high temperatures

    Directory of Open Access Journals (Sweden)

    B. Boessenkool

    2017-09-01

    Full Text Available High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

  10. Effects of sample size on estimation of rainfall extremes at high temperatures

    Science.gov (United States)

    Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik

    2017-09-01

    High precipitation quantiles tend to rise with temperature, following the so-called Clausius-Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

  11. Calculating sample sizes for cluster randomized trials: we can keep it simple and efficient !

    NARCIS (Netherlands)

    van Breukelen, Gerard J.P.; Candel, Math J.J.M.

    2012-01-01

    Objective: Simple guidelines for efficient sample sizes in cluster randomized trials with unknown intraclass correlation and varying cluster sizes. Methods: A simple equation is given for the optimal number of clusters and sample size per cluster. Here, optimal means maximizing power for a given

  12. How many is enough? Determining optimal sample sizes for normative studies in pediatric neuropsychology.

    Science.gov (United States)

    Bridges, Ana J; Holler, Karen A

    2007-11-01

    The purpose of this investigation was to determine how confidence intervals (CIs) for pediatric neuropsychological norms vary as a function of sample size, and to determine optimal sample sizes for normative studies. First, the authors calculated 95% CIs for a set of published pediatric norms for four commonly used neuropsychological instruments. Second, 95% CIs were calculated for varying sample size (from n = 5 to n = 500). Results suggest that some pediatric norms have unacceptably wide CIs, and normative studies ought optimally to use 50 to 75 participants per cell. Smaller sample sizes may lead to overpathologizing results, while the cost of obtaining larger samples may not be justifiable.

  13. European guidelines for quality assurance in cervical cancer screening: recommendations for collecting samples for conventional and liquid-based cytology.

    NARCIS (Netherlands)

    Arbyn, M.; Herbert, A.; Schenck, U.; Nieminen, P.; Jordan, J.; Mcgoogan, E.; Patnick, J.; Bergeron, C.; Baldauf, J.J.; Klinkhamer, P.; Bulten, J.; Martin-Hirsch, P.

    2007-01-01

    The current paper presents an annex in the second edition of the European Guidelines for Quality Assurance in Cervical Cancer Screening. It provides guidance on how to make a satisfactory conventional Pap smear or a liquid-based cytology (LBC) sample. Practitioners taking samples for cytology should

  14. Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety

    OpenAIRE

    Wolf, Erika J.; Harrington, Kelly M.; Shaunna L Clark; Miller, Mark W.

    2013-01-01

    Determining sample size requirements for structural equation modeling (SEM) is a challenge often faced by investigators, peer reviewers, and grant writers. Recent years have seen a large increase in SEMs in the behavioral science literature, but consideration of sample size requirements for applied SEMs often relies on outdated rules-of-thumb. This study used Monte Carlo data simulation techniques to evaluate sample size requirements for common applied SEMs. Across a series of simulations, we...

  15. Bayesian sample size determination for a clinical trial with correlated continuous and binary outcomes.

    Science.gov (United States)

    Stamey, James D; Natanegara, Fanni; Seaman, John W

    2013-01-01

    In clinical trials, multiple outcomes are often collected in order to simultaneously assess effectiveness and safety. We develop a Bayesian procedure for determining the required sample size in a regression model where a continuous efficacy variable and a binary safety variable are observed. The sample size determination procedure is simulation based. The model accounts for correlation between the two variables. Through examples we demonstrate that savings in total sample size are possible when the correlation between these two variables is sufficiently high.

  16. Issues of sample size in sensitivity and specificity analysis with special reference to oncology

    Directory of Open Access Journals (Sweden)

    Atul Juneja

    2015-01-01

    Full Text Available Sample size is one of the basics issues, which medical researcher including oncologist faces with any research program. The current communication attempts to discuss the computation of sample size when sensitivity and specificity are being evaluated. The article intends to present the situation that the researcher could easily visualize for appropriate use of sample size techniques for sensitivity and specificity when any screening method for early detection of cancer is in question. Moreover, the researcher would be in a position to efficiently communicate with a statistician for sample size computation and most importantly applicability of the results under the conditions of the negotiated precision.

  17. Issues of sample size in sensitivity and specificity analysis with special reference to oncology.

    Science.gov (United States)

    Juneja, Atul; Sharma, Shashi

    2015-01-01

    Sample size is one of the basics issues, which medical researcher including oncologist faces with any research program. The current communication attempts to discuss the computation of sample size when sensitivity and specificity are being evaluated. The article intends to present the situation that the researcher could easily visualize for appropriate use of sample size techniques for sensitivity and specificity when any screening method for early detection of cancer is in question. Moreover, the researcher would be in a position to efficiently communicate with a statistician for sample size computation and most importantly applicability of the results under the conditions of the negotiated precision.

  18. Sample Size for Measuring Grammaticality in Preschool Children from Picture-Elicited Language Samples

    Science.gov (United States)

    Eisenberg, Sarita L.; Guo, Ling-Yu

    2015-01-01

    Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…

  19. Randomized controlled trials 5: Determining the sample size and power for clinical trials and cohort studies.

    Science.gov (United States)

    Greene, Tom

    2015-01-01

    Performing well-powered randomized controlled trials is of fundamental importance in clinical research. The goal of sample size calculations is to assure that statistical power is acceptable while maintaining a small probability of a type I error. This chapter overviews the fundamentals of sample size calculation for standard types of outcomes for two-group studies. It considers (1) the problems of determining the size of the treatment effect that the studies will be designed to detect, (2) the modifications to sample size calculations to account for loss to follow-up and nonadherence, (3) the options when initial calculations indicate that the feasible sample size is insufficient to provide adequate power, and (4) the implication of using multiple primary endpoints. Sample size estimates for longitudinal cohort studies must take account of confounding by baseline factors.

  20. CT dose survey in adults: what sample size for what precision?

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Stephen [Hopital Ambroise Pare, Department of Radiology, Mons (Belgium); Muylem, Alain van [Hopital Erasme, Department of Pneumology, Brussels (Belgium); Howarth, Nigel [Clinique des Grangettes, Department of Radiology, Chene-Bougeries (Switzerland); Gevenois, Pierre Alain [Hopital Erasme, Department of Radiology, Brussels (Belgium); Tack, Denis [EpiCURA, Clinique Louis Caty, Department of Radiology, Baudour (Belgium)

    2017-01-15

    To determine variability of volume computed tomographic dose index (CTDIvol) and dose-length product (DLP) data, and propose a minimum sample size to achieve an expected precision. CTDIvol and DLP values of 19,875 consecutive CT acquisitions of abdomen (7268), thorax (3805), lumbar spine (3161), cervical spine (1515) and head (4106) were collected in two centers. Their variabilities were investigated according to sample size (10 to 1000 acquisitions) and patient body weight categories (no weight selection, 67-73 kg and 60-80 kg). The 95 % confidence interval in percentage of their median (CI95/med) value was calculated for increasing sample sizes. We deduced the sample size that set a 95 % CI lower than 10 % of the median (CI95/med ≤ 10 %). Sample size ensuring CI95/med ≤ 10 %, ranged from 15 to 900 depending on the body region and the dose descriptor considered. In sample sizes recommended by regulatory authorities (i.e., from 10-20 patients), mean CTDIvol and DLP of one sample ranged from 0.50 to 2.00 times its actual value extracted from 2000 samples. The sampling error in CTDIvol and DLP means is high in dose surveys based on small samples of patients. Sample size should be increased at least tenfold to decrease this variability. (orig.)

  1. Comparison of Size Modulation Standard Automated Perimetry and Conventional Standard Automated Perimetry with a 10-2 Test Program in Glaucoma Patients.

    Science.gov (United States)

    Hirasawa, Kazunori; Takahashi, Natsumi; Satou, Tsukasa; Kasahara, Masayuki; Matsumura, Kazuhiro; Shoji, Nobuyuki

    2017-08-01

    This prospective observational study compared the performance of size modulation standard automated perimetry with the Octopus 600 10-2 test program, with stimulus size modulation during testing, based on stimulus intensity and conventional standard automated perimetry, with that of the Humphrey 10-2 test program in glaucoma patients. Eighty-seven eyes of 87 glaucoma patients underwent size modulation standard automated perimetry with Dynamic strategy and conventional standard automated perimetry using the SITA standard strategy. The main outcome measures were global indices, point-wise threshold, visual defect size and depth, reliability indices, and test duration; these were compared between size modulation standard automated perimetry and conventional standard automated perimetry. Global indices and point-wise threshold values between size modulation standard automated perimetry and conventional standard automated perimetry were moderately to strongly correlated (p 33.40, p modulation standard automated perimetry than with conventional standard automated perimetry, but the visual-field defect size was smaller (p modulation-standard automated perimetry than on conventional standard automated perimetry. The reliability indices, particularly the false-negative response, of size modulation standard automated perimetry were worse than those of conventional standard automated perimetry (p modulation standard automated perimetry than with conventional standard automated perimetry (p = 0.02). Global indices and the point-wise threshold value of the two testing modalities correlated well. However, the potential of a large stimulus presented at an area with a decreased sensitivity with size modulation standard automated perimetry could underestimate the actual threshold in the 10-2 test protocol, as compared with conventional standard automated perimetry.

  2. 45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations

    Science.gov (United States)

    2010-10-01

    ... applied when the sample is drawn from a population of one to 5,000 youth, because the sample is more than... Using Finite Population Correction The FPC is not applied when the sample is drawn from a population of... 45 Public Welfare 4 2010-10-01 2010-10-01 false Calculating Sample Size for NYTD Follow-Up...

  3. Implications of sampling design and sample size for national carbon accounting systems.

    Science.gov (United States)

    Köhl, Michael; Lister, Andrew; Scott, Charles T; Baldauf, Thomas; Plugge, Daniel

    2011-11-08

    Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources. We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives. Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

  4. Post-stratified estimation: with-in strata and total sample size recommendations

    Science.gov (United States)

    James A. Westfall; Paul L. Patterson; John W. Coulston

    2011-01-01

    Post-stratification is used to reduce the variance of estimates of the mean. Because the stratification is not fixed in advance, within-strata sample sizes can be quite small. The survey statistics literature provides some guidance on minimum within-strata sample sizes; however, the recommendations and justifications are inconsistent and apply broadly for many...

  5. Sample size calculations for pilot randomized trials: a confidence interval approach.

    Science.gov (United States)

    Cocks, Kim; Torgerson, David J

    2013-02-01

    To describe a method using confidence intervals (CIs) to estimate the sample size for a pilot randomized trial. Using one-sided CIs and the estimated effect size that would be sought in a large trial, we calculated the sample size needed for pilot trials. Using an 80% one-sided CI, we estimated that a pilot trial should have at least 9% of the sample size of the main planned trial. Using the estimated effect size difference for the main trial and using a one-sided CI, this allows us to calculate a sample size for a pilot trial, which will make its results more useful than at present. Copyright © 2013 Elsevier Inc. All rights reserved.

  6. Sample Size Induced Brittle-to-Ductile Transition of Single-Crystal Aluminum Nitride

    Science.gov (United States)

    2015-08-01

    Interestingly, the dislocation plasticity of the single- crystal AlN strongly depends on specimen sizes. As shown in Fig. 5a and b, the large plastic...ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to-Ductile Transition of Single- Crystal Aluminum...originator. ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to-Ductile Transition of Single- Crystal

  7. Not too big, not too small: a goldilocks approach to sample size selection.

    Science.gov (United States)

    Broglio, Kristine R; Connor, Jason T; Berry, Scott M

    2014-01-01

    We present a Bayesian adaptive design for a confirmatory trial to select a trial's sample size based on accumulating data. During accrual, frequent sample size selection analyses are made and predictive probabilities are used to determine whether the current sample size is sufficient or whether continuing accrual would be futile. The algorithm explicitly accounts for complete follow-up of all patients before the primary analysis is conducted. We refer to this as a Goldilocks trial design, as it is constantly asking the question, "Is the sample size too big, too small, or just right?" We describe the adaptive sample size algorithm, describe how the design parameters should be chosen, and show examples for dichotomous and time-to-event endpoints.

  8. Sample size determination in group-sequential clinical trials with two co-primary endpoints

    Science.gov (United States)

    Asakura, Koko; Hamasaki, Toshimitsu; Sugimoto, Tomoyuki; Hayashi, Kenichi; Evans, Scott R; Sozu, Takashi

    2014-01-01

    We discuss sample size determination in group-sequential designs with two endpoints as co-primary. We derive the power and sample size within two decision-making frameworks. One is to claim the test intervention’s benefit relative to control when superiority is achieved for the two endpoints at the same interim timepoint of the trial. The other is when the superiority is achieved for the two endpoints at any interim timepoint, not necessarily simultaneously. We evaluate the behaviors of sample size and power with varying design elements and provide a real example to illustrate the proposed sample size methods. In addition, we discuss sample size recalculation based on observed data and evaluate the impact on the power and Type I error rate. PMID:24676799

  9. Clinical trials with nested subgroups: Analysis, sample size determination and internal pilot studies.

    Science.gov (United States)

    Placzek, Marius; Friede, Tim

    2017-01-01

    The importance of subgroup analyses has been increasing due to a growing interest in personalized medicine and targeted therapies. Considering designs with multiple nested subgroups and a continuous endpoint, we develop methods for the analysis and sample size determination. First, we consider the joint distribution of standardized test statistics that correspond to each (sub)population. We derive multivariate exact distributions where possible, providing approximations otherwise. Based on these results, we present sample size calculation procedures. Uncertainties about nuisance parameters which are needed for sample size calculations make the study prone to misspecifications. We discuss how a sample size review can be performed in order to make the study more robust. To this end, we implement an internal pilot study design where the variances and prevalences of the subgroups are reestimated in a blinded fashion and the sample size is recalculated accordingly. Simulations show that the procedures presented here do not inflate the type I error significantly and maintain the prespecified power as long as the sample size of the smallest subgroup is not too small. We pay special attention to the case of small sample sizes and attain a lower boundary for the size of the internal pilot study.

  10. Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

    Directory of Open Access Journals (Sweden)

    Bruno Giacomini Sari

    2017-09-01

    Full Text Available ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.

  11. Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

    Science.gov (United States)

    Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

    2016-09-01

    In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous

  12. COMPARISON OF OCCURRENCE AND TOXINOGENITY OF ALTERNARIA SPP. ISOLATED FROM SAMPLES OF CONVENTIONAL AND NEW CROSSBRED WHEAT OF SLOVAK ORIGIN

    Directory of Open Access Journals (Sweden)

    Soňa Felšöciová

    2012-02-01

    Full Text Available The aim of this study was to compare the results of mycological and mycotoxicological analysis of two types of Slovak wheat samples, focusing on Alternaria genus. A total of 21 samples of conventional wheat grains and 3 samples of the new crossbred wheat were investigated for exogenous and endogenous mycobiota. The exogenous mycobiota was determined by using plate dilution method and the endogenous mycobiota by the method of direct placing of superficially sterilized grains on agar plates. Toxinogenity of selected isolates was analysed by means of thin layer chromatography. The obtained results of this study show a high isolation frequency of Alternaria isolates in samples of conventional as well as new crossbred wheat. A total of 4 species-groups of the genus Alternaria were isolated from conventional wheat (A. alternata, A. arborescens, A. infectoria, A. tenuissima and 3 species-groups from new crossbred wheat (A. arborescens, A. infectoria, A. tenuissima. A. tenuissima species-group was isolated within the endogenous mycobiota from all samples of conventional and new crossbred wheat. Species-group with the second highest isolation frequency in all tested samples was A. infectoria. The highest relative density in all samples belongs to A. infectoria and A. tenuissima species-groups. Selected strains isolated from both types of wheat were tested for production of altenuene, alternariol monomethylether and alternariol. In neither case of A. infectoria species-group isolates was confirmed the production of tested mycotoxins. The highest toxinogenity (100% was observed in strains of A. arborescens and A. tenuissima.

  13. Determining sample size and a passing criterion for respirator fit-test panels.

    Science.gov (United States)

    Landsittel, D; Zhuang, Z; Newcomb, W; Berry Ann, R

    2014-01-01

    Few studies have proposed methods for sample size determination and specification of passing criterion (e.g., number needed to pass from a given size panel) for respirator fit-tests. One approach is to account for between- and within- subject variability, and thus take full advantage of the multiple donning measurements within subject, using a random effects model. The corresponding sample size calculation, however, may be difficult to implement in practice, as it depends on the model-specific and test panel-specific variance estimates, and thus does not yield a single sample size or specific cutoff for number needed to pass. A simple binomial approach is therefore proposed to simultaneously determine both the required sample size and the optimal cutoff for the number of subjects needed to achieve a passing result. The method essentially conducts a global search of the type I and type II errors under different null and alternative hypotheses, across the range of possible sample sizes, to find the lowest sample size which yields at least one cutoff satisfying, or approximately satisfying all pre-determined limits for the different error rates. Benchmark testing of 98 respirators (conducted by the National Institute for Occupational Safety and Health) is used to illustrate the binomial approach and show how sample size estimates from the random effects model can vary substantially depending on estimated variance components. For the binomial approach, probability calculations show that a sample size of 35 to 40 yields acceptable error rates under different null and alternative hypotheses. For the random effects model, the required sample sizes are generally smaller, but can vary substantially based on the estimate variance components. Overall, despite some limitations, the binomial approach represents a highly practical approach with reasonable statistical properties.

  14. Efficacy of liquid-based cytology versus conventional smears in FNA samples

    OpenAIRE

    Tripathy, Kalpalata; Misra, Aparajita; Ghosh, Joydip Kumar

    2015-01-01

    Background: Liquid-based cytology (LBC) is fast becoming a useful method in evaluating both gynecological and non-gynecological preparations, including fine needle aspiration (FNA) cytology. Even distribution of cells, decreasing obscuring background elements like blood and mucus, well preserved nuclear and cytoplasmic details and rapid fixation helps in better visualization of cells. Aim: This study was conducted to asses the diagnostic accuracy of liquid-based cytology versus convention...

  15. Organic vs. Conventional Grassland Management: Do 15N and 13C Isotopic Signatures of Hay and Soil Samples Differ?

    Science.gov (United States)

    Klaus, Valentin H.; Hölzel, Norbert; Prati, Daniel; Schmitt, Barbara; Schöning, Ingo; Schrumpf, Marion; Fischer, Markus; Kleinebecker, Till

    2013-01-01

    Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the δ15N and δ13C isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Δδ15N (δ15N plant - δ15N soil) to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in δ13C in hay and δ15N in both soil and hay between management types, but showed that δ13C abundances were significantly lower in soil of organic compared to conventional grasslands. Δδ15N values implied that management types did not substantially differ in nitrogen cycling. Only δ13C in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be efficiently used in practice

  16. Organic vs. conventional grassland management: do (15N and (13C isotopic signatures of hay and soil samples differ?

    Directory of Open Access Journals (Sweden)

    Valentin H Klaus

    Full Text Available Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the δ(15N and δ(13C isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Δδ(15N (δ(15N plant - δ(15N soil to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in δ(13C in hay and δ(15N in both soil and hay between management types, but showed that δ(13C abundances were significantly lower in soil of organic compared to conventional grasslands. Δδ(15N values implied that management types did not substantially differ in nitrogen cycling. Only δ(13C in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be

  17. Cervical cancer incidence after normal cytological sample in routine screening using SurePath, ThinPrep, and conventional cytology

    DEFF Research Database (Denmark)

    Rozemeijer, Kirsten; Naber, Steffie K; Penning, Corine

    2017-01-01

    Objective To compare the cumulative incidence of cervical cancer diagnosed within 72 months after a normal screening sample between conventional cytology and liquid based cytology tests SurePath and ThinPrep.Design Retrospective population based cohort study.Setting Nationwide network and registry...... of histo- and cytopathology in the Netherlands (PALGA), January 2000 to March 2013.Population Women with 5 924 474 normal screening samples (23 833 123 person years).Exposure Use of SurePath or ThinPrep versus conventional cytology as screening test.Main outcome measure 72 month cumulative incidence...... was 58.5 (95% confidence interval 54.6 to 62.7) per 100 000 normal conventional cytology samples, compared with 66.8 (56.7 to 78.7) for ThinPrep and 44.6 (37.8 to 52.6) for SurePath. Compared with conventional cytology, the hazard of invasive cancer was 19% lower (hazard ratio 0.81, 95% confidence...

  18. Sample size and power calculations based on generalized linear mixed models with correlated binary outcomes.

    Science.gov (United States)

    Dang, Qianyu; Mazumdar, Sati; Houck, Patricia R

    2008-08-01

    The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effects. Using GLIMMIX based on these linearization methods, we derived formulas for power and sample size calculations for longitudinal designs with attrition over time. We found that the power and sample size estimates depend on the within-subject correlation and the size of random effects. In this article, we present tables of minimum sample sizes commonly used to test hypotheses for longitudinal studies. A simulation study was used to compare the results. We also provide a Web link to the SAS macro that we developed to compute power and sample sizes for correlated binary outcomes.

  19. Categorization of micronuclei by size and measurement of each ratio in cytokinesis-block and conventional cultures of human lymphocytes exposed to mitomycin C and colchicine

    National Research Council Canada - National Science Library

    Mure, K; Takeshita, T; Morimoto, K

    1996-01-01

    .... We investigated the effects of the culture method (either conventional or cytokinesis-block) and exposure time (48 or 72hr) on the frequency and size distribution of MN in human peripheral lymphocytes exposed to mitomycin C...

  20. Effects of Sample Size on Estimates of Population Growth Rates Calculated with Matrix Models

    Science.gov (United States)

    Fiske, Ian J.; Bruna, Emilio M.; Bolker, Benjamin M.

    2008-01-01

    Background Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (λ) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of λ–Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of λ due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of λ. Methodology/Principal Findings Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating λ for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of λ with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. Conclusions/Significance We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities. PMID:18769483

  1. Effects of sample size on estimates of population growth rates calculated with matrix models.

    Directory of Open Access Journals (Sweden)

    Ian J Fiske

    Full Text Available BACKGROUND: Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. METHODOLOGY/PRINCIPAL FINDINGS: Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. CONCLUSIONS/SIGNIFICANCE: We found significant bias at small sample sizes when survival was low (survival = 0.5, and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high

  2. Finding the optimal balance: challenges of improving conventional cancer chemotherapy using suitable combinations with nano-sized drug delivery systems.

    Science.gov (United States)

    Kratz, Felix; Warnecke, André

    2012-12-10

    Anticancer drugs as well as nano-sized drug delivery systems face many barriers that hinder penetration deeply and evenly into solid tumors: a chaotic, tortuous vascular compartment resulting in tumor tissue distant from microvessels, a heterogeneous blood flow distribution with a concomitant defective microcirculatory exchange process, and a high interstitial fluid pressure. Furthermore, a resulting hostile tumor microenvironment characterized by hypoxia and/or extracellular acidosis can reduce the efficacy of anticancer drugs and confer drug resistance. Conversely, the enhanced permeation and retention effect has become the gold standard for developing macromolecular prodrugs and nano-sized drug delivery systems. Preclinically, there are meanwhile numerous in vivo proof-of-concepts that demonstrate not only a better tolerability of nano-sized drug delivery systems but also of enhanced antitumor efficacy compared to the conventional clinical standard. When faced with such a complex and heterogeneous disease as cancer in humans, it is more likely that a tailor-made combination of different therapeutic strategies will achieve the best results. In this respect, combining low-molecular weight cytostatic drugs with nano-sized drug delivery systems appears to be a natural choice for combination therapy that aims at distributing anticancer drugs at higher concentrations in the tumor in a more even manner. To date, such drug delivery approaches have been inadequately explored. In this review, we summarize the state-of-the-art of combination approaches with liposomal doxorubicin (Doxil™), the paclitaxel-albumin nanoparticle (Abraxane™) and the albumin-binding doxorubicin prodrug DOXO-EMCH (INNO-206), and discuss the insights obtained and perspectives for further research in this intriguing and promising field of drug delivery research. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. Empirically determining the sample size for large-scale gene network inference algorithms.

    Science.gov (United States)

    Altay, G

    2012-04-01

    The performance of genome-wide gene regulatory network inference algorithms depends on the sample size. It is generally considered that the larger the sample size, the better the gene network inference performance. Nevertheless, there is not adequate information on determining the sample size for optimal performance. In this study, the author systematically demonstrates the effect of sample size on information-theory-based gene network inference algorithms with an ensemble approach. The empirical results showed that the inference performances of the considered algorithms tend to converge after a particular sample size region. As a specific example, the sample size region around ≃64 is sufficient to obtain the most of the inference performance with respect to precision using the representative algorithm C3NET on the synthetic steady-state data sets of Escherichia coli and also time-series data set of a homo sapiens subnetworks. The author verified the convergence result on a large, real data set of E. coli as well. The results give evidence to biologists to better design experiments to infer gene networks. Further, the effect of cutoff on inference performances over various sample sizes is considered. [Includes supplementary material].

  4. The PowerAtlas: a power and sample size atlas for microarray experimental design and research

    Directory of Open Access Journals (Sweden)

    Wang Jelai

    2006-02-01

    Full Text Available Abstract Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas 1. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO. The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC. Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.

  5. Reduced Sampling Size with Nanopipette for Tapping-Mode Scanning Probe Electrospray Ionization Mass Spectrometry Imaging.

    Science.gov (United States)

    Kohigashi, Tsuyoshi; Otsuka, Yoichi; Shimazu, Ryo; Matsumoto, Takuya; Iwata, Futoshi; Kawasaki, Hideya; Arakawa, Ryuichi

    2016-01-01

    Mass spectrometry imaging (MSI) with ambient sampling and ionization can rapidly and easily capture the distribution of chemical components in a solid sample. Because the spatial resolution of MSI is limited by the size of the sampling area, reducing sampling size is an important goal for high resolution MSI. Here, we report the first use of a nanopipette for sampling and ionization by tapping-mode scanning probe electrospray ionization (t-SPESI). The spot size of the sampling area of a dye molecular film on a glass substrate was decreased to 6 μm on average by using a nanopipette. On the other hand, ionization efficiency increased with decreasing solvent flow rate. Our results indicate the compatibility between a reduced sampling area and the ionization efficiency using a nanopipette. MSI of micropatterns of ink on a glass and a polymer substrate were also demonstrated.

  6. The Sample Size Influence in the Accuracy of the Image Classification of the Remote Sensing

    Directory of Open Access Journals (Sweden)

    Thomaz C. e C. da Costa

    2004-12-01

    Full Text Available Landuse/landcover maps produced by classification of remote sensing images incorporate uncertainty. This uncertainty is measured by accuracy indices using reference samples. The size of the reference sample is defined by approximation by a binomial function without the use of a pilot sample. This way the accuracy are not estimated, but fixed a priori. In case of divergency between the estimated and a priori accuracy the error of the sampling will deviate from the expected error. The size using pilot sample (theorically correct procedure justify when haven´t estimate of accuracy for work area, referent the product remote sensing utility.

  7. A behavioural Bayes approach to the determination of sample size for clinical trials considering efficacy and safety: imbalanced sample size in treatment groups.

    Science.gov (United States)

    Kikuchi, Takashi; Gittins, John

    2011-08-01

    The behavioural Bayes approach to sample size determination for clinical trials assumes that the number of subsequent patients switching to a new drug from the current drug depends on the strength of the evidence for efficacy and safety that was observed in the clinical trials. The optimal sample size is the one which maximises the expected net benefit of the trial. The approach has been developed in a series of papers by Pezeshk and the present authors (Gittins JC, Pezeshk H. A behavioral Bayes method for determining the size of a clinical trial. Drug Information Journal 2000; 34: 355-63; Gittins JC, Pezeshk H. How Large should a clinical trial be? The Statistician 2000; 49(2): 177-87; Gittins JC, Pezeshk H. A decision theoretic approach to sample size determination in clinical trials. Journal of Biopharmaceutical Statistics 2002; 12(4): 535-51; Gittins JC, Pezeshk H. A fully Bayesian approach to calculating sample sizes for clinical trials with binary responses. Drug Information Journal 2002; 36: 143-50; Kikuchi T, Pezeshk H, Gittins J. A Bayesian cost-benefit approach to the determination of sample size in clinical trials. Statistics in Medicine 2008; 27(1): 68-82; Kikuchi T, Gittins J. A behavioral Bayes method to determine the sample size of a clinical trial considering efficacy and safety. Statistics in Medicine 2009; 28(18): 2293-306; Kikuchi T, Gittins J. A Bayesian procedure for cost-benefit evaluation of a new drug in multi-national clinical trials. Statistics in Medicine 2009 (Submitted)). The purpose of this article is to provide a rationale for experimental designs which allocate more patients to the new treatment than to the control group. The model uses a logistic weight function, including an interaction term linking efficacy and safety, which determines the number of patients choosing the new drug, and hence the resulting benefit. A Monte Carlo simulation is employed for the calculation. Having a larger group of patients on the new drug in general

  8. Novel joint selection methods can reduce sample size for rheumatoid arthritis clinical trials with ultrasound endpoints.

    Science.gov (United States)

    Allen, John C; Thumboo, Julian; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Tan, York Kiat

    2017-10-03

    To determine whether novel methods of selecting joints through (i) ultrasonography (individualized-ultrasound [IUS] method), or (ii) ultrasonography and clinical examination (individualized-composite-ultrasound [ICUS] method) translate into smaller rheumatoid arthritis (RA) clinical trial sample sizes when compared to existing methods utilizing predetermined joint sites for ultrasonography. Cohen's effect size (ES) was estimated (ES^) and a 95% CI (ES^L, ES^U) calculated on a mean change in 3-month total inflammatory score for each method. Corresponding 95% CIs [nL(ES^U), nU(ES^L)] were obtained on a post hoc sample size reflecting the uncertainty in ES^. Sample size calculations were based on a one-sample t-test as the patient numbers needed to provide 80% power at α = 0.05 to reject a null hypothesis H0 : ES = 0 versus alternative hypotheses H1 : ES = ES^, ES = ES^L and ES = ES^U. We aimed to provide point and interval estimates on projected sample sizes for future studies reflecting the uncertainty in our study ES^S. Twenty-four treated RA patients were followed up for 3 months. Utilizing the 12-joint approach and existing methods, the post hoc sample size (95% CI) was 22 (10-245). Corresponding sample sizes using ICUS and IUS were 11 (7-40) and 11 (6-38), respectively. Utilizing a seven-joint approach, the corresponding sample sizes using ICUS and IUS methods were nine (6-24) and 11 (6-35), respectively. Our pilot study suggests that sample size for RA clinical trials with ultrasound endpoints may be reduced using the novel methods, providing justification for larger studies to confirm these observations. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  9. New method to estimate the sample size for calculation of a proportion assuming binomial distribution.

    Science.gov (United States)

    Vallejo, Adriana; Muniesa, Ana; Ferreira, Chelo; de Blas, Ignacio

    2013-10-01

    Nowadays the formula to calculate the sample size for estimate a proportion (as prevalence) is based on the Normal distribution, however it would be based on a Binomial distribution which confidence interval was possible to be calculated using the Wilson Score method. By comparing the two formulae (Normal and Binomial distributions), the variation of the amplitude of the confidence intervals is relevant in the tails and the center of the curves. In order to calculate the needed sample size we have simulated an iterative sampling procedure, which shows an underestimation of the sample size for values of prevalence closed to 0 or 1, and also an overestimation for values closed to 0.5. Attending to these results we proposed an algorithm based on Wilson Score method that provides similar values for the sample size than empirically obtained by simulation. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Optimal designs of the median run length based double sampling X chart for minimizing the average sample size.

    Directory of Open Access Journals (Sweden)

    Wei Lin Teoh

    Full Text Available Designs of the double sampling (DS X chart are traditionally based on the average run length (ARL criterion. However, the shape of the run length distribution changes with the process mean shifts, ranging from highly skewed when the process is in-control to almost symmetric when the mean shift is large. Therefore, we show that the ARL is a complicated performance measure and that the median run length (MRL is a more meaningful measure to depend on. This is because the MRL provides an intuitive and a fair representation of the central tendency, especially for the rightly skewed run length distribution. Since the DS X chart can effectively reduce the sample size without reducing the statistical efficiency, this paper proposes two optimal designs of the MRL-based DS X chart, for minimizing (i the in-control average sample size (ASS and (ii both the in-control and out-of-control ASSs. Comparisons with the optimal MRL-based EWMA X and Shewhart X charts demonstrate the superiority of the proposed optimal MRL-based DS X chart, as the latter requires a smaller sample size on the average while maintaining the same detection speed as the two former charts. An example involving the added potassium sorbate in a yoghurt manufacturing process is used to illustrate the effectiveness of the proposed MRL-based DS X chart in reducing the sample size needed.

  11. A comparison of conventional and computer-assisted semen analysis (CRISMAS software) using samples from 166 young Danish men

    DEFF Research Database (Denmark)

    Vested, Anne; Ramlau-Hansen, Cecilia H; Bonde, Jens P

    2011-01-01

    The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis (CASA) (Copenhagen Rigshospitalet Image House Sperm Motility Analysis System (CRISMAS) 4.6 software) us...... and motility analysis. This needs to be accounted for in clinics using this software and in studies of determinants of these semen characteristics.......The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis (CASA) (Copenhagen Rigshospitalet Image House Sperm Motility Analysis System (CRISMAS) 4.6 software......) using semen samples from 166 young Danish men. The CRISMAS software identifies sperm concentration and classifies spermatozoa into three motility categories. To enable comparison of the two methods, the four motility stages obtained by conventional semen analysis were, based on their velocity...

  12. Three-year-olds obey the sample size principle of induction: the influence of evidence presentation and sample size disparity on young children's generalizations.

    Science.gov (United States)

    Lawson, Chris A

    2014-07-01

    Three experiments with 81 3-year-olds (M=3.62years) examined the conditions that enable young children to use the sample size principle (SSP) of induction-the inductive rule that facilitates generalizations from large rather than small samples of evidence. In Experiment 1, children exhibited the SSP when exemplars were presented sequentially but not when exemplars were presented simultaneously. Results from Experiment 3 suggest that the advantage of sequential presentation is not due to the additional time to process the available input from the two samples but instead may be linked to better memory for specific individuals in the large sample. In addition, findings from Experiments 1 and 2 suggest that adherence to the SSP is mediated by the disparity between presented samples. Overall, these results reveal that the SSP appears early in development and is guided by basic cognitive processes triggered during the acquisition of input. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Sample size calculations in clinical research should also be based on ethical principles.

    Science.gov (United States)

    Cesana, Bruno Mario; Antonelli, Paolo

    2016-03-18

    Sample size calculations based on too narrow a width, or with lower and upper confidence limits bounded by fixed cut-off points, not only increase power-based sample sizes to ethically unacceptable levels (thus making research practically unfeasible) but also greatly increase the costs and burdens of clinical trials. We propose an alternative method of combining the power of a statistical test and the probability of obtaining adequate precision (the power of the confidence interval) with an acceptable increase in power-based sample sizes.

  14. An Update on Using the Range to Estimate σ When Determining Sample Sizes.

    Science.gov (United States)

    Rhiel, George Steven; Markowski, Edward

    2017-04-01

    In this research, we develop a strategy for using a range estimator of σ when determining a sample size for estimating a mean. Previous research by Rhiel is extended to provide dn values for use in calculating a range estimate of σ when working with sampling frames up to size 1,000,000. This allows the use of the range estimator of σ with "big data." A strategy is presented for using the range estimator of σ for determining sample sizes based on the dn values developed in this study.

  15. Publishing nutrition research: a review of sampling, sample size, statistical analysis, and other key elements of manuscript preparation, Part 2.

    Science.gov (United States)

    Boushey, Carol J; Harris, Jeffrey; Bruemmer, Barbara; Archer, Sujata L

    2008-04-01

    Members of the Board of Editors recognize the importance of providing a resource for researchers to insure quality and accuracy of reporting in the Journal. This second monograph of a periodic series focuses on study sample selection, sample size, and common statistical procedures using parametric methods, and the presentation of statistical methods and results. Attention to sample selection and sample size is critical to avoid study bias. When outcome variables adhere to a normal distribution, then parametric procedures can be used for statistical inference. Documentation that clearly outlines the steps used in the research process will advance the science of evidence-based practice in nutrition and dietetics. Real examples from problem sets and published literature are provided, as well as reference to books and online resources.

  16. Serving Real-Time Point Observation Data in netCDF using Climate and Forecasting Discrete Sampling Geometry Conventions

    Science.gov (United States)

    Ward-Garrison, C.; May, R.; Davis, E.; Arms, S. C.

    2016-12-01

    NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The Climate and Forecasting (CF) metadata conventions for netCDF foster the ability to work with netCDF files in general and useful ways. These conventions include metadata attributes for physical units, standard names, and spatial coordinate systems. While these conventions have been successful in easing the use of working with netCDF-formatted output from climate and forecast models, their use for point-based observation data has been less so. Unidata has prototyped using the discrete sampling geometry (DSG) CF conventions to serve, using the THREDDS Data Server, the real-time point observation data flowing across the Internet Data Distribution (IDD). These data originate in text format reports for individual stations (e.g. METAR surface data or TEMP upper air data) and are converted and stored in netCDF files in real-time. This work discusses the experiences and challenges of using the current CF DSG conventions for storing such real-time data. We also test how parts of netCDF's extended data model can address these challenges, in order to inform decisions for a future version of CF (CF 2.0) that would take advantage of features of the netCDF enhanced data model.

  17. A multi-cyclone sampling array for the collection of size-segregated occupational aerosols.

    Science.gov (United States)

    Mischler, Steven E; Cauda, Emanuele G; Di Giuseppe, Michelangelo; Ortiz, Luis A

    2013-01-01

    In this study a serial multi-cyclone sampling array capable of simultaneously sampling particles of multiple size fractions, from an occupational environment, for use in in vivo and in vitro toxicity studies and physical/chemical characterization, was developed and tested. This method is an improvement over current methods used to size-segregate occupational aerosols for characterization, due to its simplicity and its ability to collect sufficient masses of nano- and ultrafine sized particles for analysis. This method was evaluated in a chamber providing a uniform atmosphere of dust concentrations using crystalline silica particles. The multi-cyclone sampling array was used to segregate crystalline silica particles into four size fractions, from a chamber concentration of 10 mg/m(3). The size distributions of the particles collected at each stage were confirmed, in the air, before and after each cyclone stage. Once collected, the particle size distribution of each size fraction was measured using light scattering techniques to further confirm the size distributions. As a final confirmation, scanning electron microscopy was used to collect images of each size fraction. The results presented here, using multiple measurement techniques, show that this multi-cyclone system was able to successfully collect distinct size-segregated particles at sufficient masses to perform toxicological evaluations and physical/chemical characterization.

  18. Mineralogical, optical, geochemical, and particle size properties of four sediment samples for optical physics research

    Science.gov (United States)

    Bice, K.; Clement, S. C.

    1981-01-01

    X-ray diffraction and spectroscopy were used to investigate the mineralogical and chemical properties of the Calvert, Ball Old Mine, Ball Martin, and Jordan Sediments. The particle size distribution and index of refraction of each sample were determined. The samples are composed primarily of quartz, kaolinite, and illite. The clay minerals are most abundant in the finer particle size fractions. The chemical properties of the four samples are similar. The Calvert sample is most notably different in that it contains a relatively high amount of iron. The dominant particle size fraction in each sample is silt, with lesser amounts of clay and sand. The indices of refraction of the sediments are the same with the exception of the Calvert sample which has a slightly higher value.

  19. Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology.

    Science.gov (United States)

    Brown, Caleb Marshall; Vavrek, Matthew J

    2015-01-01

    Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes.

  20. Difficulties in obtaining representative samples for compliance with the Ballast Water Management Convention

    Digital Repository Service at National Institute of Oceanography (India)

    Carney, K.J.; Basurko, O.C.; Pazouki, K.; Marsham, S.; Delany, J.E.; Desai, D.V.; Anil, A.C.; Mesbahi, E.

    ). This study has shown the effect that low sampling frequency has on the accuracy of data obtained from a 1 tonne storage tank. In reality ships can carry between 100 and 100,000 tonnes of ballast water and discharge at flow rates of 100 to over 3000 m3hr-1... and uncertainty in the accuracy of data obtained from collecting only three replicate samples at three sampling points on discharge of ballast water will, in reality, be much greater than that seen in this study. Previous studies have used different...

  1. Sample size determination for logistic regression on a logit-normal distribution.

    Science.gov (United States)

    Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

    2017-06-01

    Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

  2. Efficacy of liquid-based cytology versus conventional smears in FNA samples

    Directory of Open Access Journals (Sweden)

    Kalpalata Tripathy

    2015-01-01

    Conclusion: LBC performed on FNA samples can be a simple and valuable technique. Only in few selected cases, where background factor is an essential diagnostic clue, a combination of both CP and TP is necessary.

  3. Sample Size Determination in a Chi-Squared Test Given Information from an Earlier Study.

    Science.gov (United States)

    Gillett, Raphael

    1996-01-01

    A rigorous method is outlined for using information from a previous study and explicitly taking into account the variability of an effect size estimate when determining sample size for a chi-squared test. This approach assures that the average power of all experiments in a discipline attains the desired level. (SLD)

  4. The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

    Science.gov (United States)

    Schoeneberger, Jason A.

    2016-01-01

    The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

  5. Estimating sample size for a small-quadrat method of botanical ...

    African Journals Online (AJOL)

    ... in eight plant communities in the Nylsvley Nature Reserve. Illustrates with a table. Keywords: Botanical surveys; Grass density; Grasslands; Mixed Bushveld; Nylsvley Nature Reserve; Quadrat size species density; Small-quadrat method; Species density; Species richness; botany; sample size; method; survey; south africa

  6. Sample size calculations in clinical research should also be based on ethical principles

    OpenAIRE

    Cesana, Bruno Mario; Antonelli, Paolo

    2016-01-01

    Sample size calculations based on too narrow a width, or with lower and upper confidence limits bounded by fixed cut-off points, not only increase power-based sample sizes to ethically unacceptable levels (thus making research practically unfeasible) but also greatly increase the costs and burdens of clinical trials. We propose an alternative method of combining the power of a statistical test and the probability of obtaining adequate precision (the power of the confidence interval) with an a...

  7. OPTIMAL SAMPLE SIZE FOR STATISTICAL ANALYSIS OF WINTER WHEAT QUANTITATIVE TRAITS

    OpenAIRE

    Andrijana Eđed; Dražen Horvat; Zdenko Lončarić

    2009-01-01

    In the planning phase of every research particular attention should be dedicated to estimation of optimal sample size, aiming to obtain more precise and objective results of statistical analysis. The aim of this paper was to estimate optimal sample size of wheat yield components (plant height, spike length, number of spikelets per spike, number of grains per spike, weight of grains per spike and 1000 grains weight) for determination of statistically significant differences between two treatme...

  8. Evaluation of different sized blood sampling tubes for thromboelastometry, platelet function, and platelet count

    DEFF Research Database (Denmark)

    Andreasen, Jo Bønding; Pistor-Riebold, Thea Unger; Knudsen, Ingrid Hell

    2014-01-01

    Background: To minimise the volume of blood used for diagnostic procedures, especially in children, we investigated whether the size of sample tubes affected whole blood coagulation analyses. Methods: We included 20 healthy individuals for rotational thromboelastometry (RoTEM®) analyses and compa......Background: To minimise the volume of blood used for diagnostic procedures, especially in children, we investigated whether the size of sample tubes affected whole blood coagulation analyses. Methods: We included 20 healthy individuals for rotational thromboelastometry (RoTEM®) analyses...

  9. Sample size for equivalence trials: a case study from a vaccine lot consistency trial.

    Science.gov (United States)

    Ganju, Jitendra; Izu, Allen; Anemona, Alessandra

    2008-08-30

    For some trials, simple but subtle assumptions can have a profound impact on the size of the trial. A case in point is a vaccine lot consistency (or equivalence) trial. Standard sample size formulas used for designing lot consistency trials rely on only one component of variation, namely, the variation in antibody titers within lots. The other component, the variation in the means of titers between lots, is assumed to be equal to zero. In reality, some amount of variation between lots, however small, will be present even under the best manufacturing practices. Using data from a published lot consistency trial, we demonstrate that when the between-lot variation is only 0.5 per cent of the total variation, the increase in the sample size is nearly 300 per cent when compared with the size assuming that the lots are identical. The increase in the sample size is so pronounced that in order to maintain power one is led to consider a less stringent criterion for demonstration of lot consistency. The appropriate sample size formula that is a function of both components of variation is provided. We also discuss the increase in the sample size due to correlated comparisons arising from three pairs of lots as a function of the between-lot variance.

  10. Unsatisfactory rate in liquid-based cervical samples as compared to conventional smears: A study from tertiary care hospital

    Directory of Open Access Journals (Sweden)

    Nalini Gupta

    2016-01-01

    Full Text Available Background: Developed countries adopted liquid-based cytology (LBC cervical cytology, partly because of its lower proportions of unsatisfactory (U/S/inadequate samples. This study was carried out to evaluate effect on the rate of U/S samples after introduction of LBC in our laboratory. Materials and Methods: An audit of U/S cervical samples was performed, which included split samples (n = 1000, only conventional Pap smear (CPS smears (n = 1000, and only LBC samples (n = 1000. The smears were reviewed by two observers independently, and adequacy for the samples was assessed as per The Bethesda System 2001. The reasons for U/S rate in split samples were categorized into various cytologic and/or technical reasons. Results: U/S rate was far less in only LBC samples (1.2% as compared to only CPS (10.5% cases. Cases in the satisfactory but limited category were also less in only LBC (0.4% as compared to only CPS (3.2% samples. The main reasons for U/S smears in split samples were low cell count (37.2% in CPS; 58.8% in LBC. The second main reason was low cellularity with excess blood and only excess blood in CPS samples. Conclusion: There was a significant reduction of U/S rate in LBC samples as compared to CPS samples, and the difference was statistically significant. The main cause of U/S samples in LBC was low cellularity indicating a technical fault in sample collection. The main cause of U/S rate in CPS was low cellularity followed by low cellularity with excess blood. Adequate training of sample takers and cytologists for the precise cell count to determine adequacy in smears can be of great help in reducing U/S rate.

  11. Unsatisfactory rate in liquid-based cervical samples as compared to conventional smears: A study from tertiary care hospital

    Science.gov (United States)

    Gupta, Nalini; Bhar, Vikrant S.; Rajwanshi, Arvind; Suri, Vanita

    2016-01-01

    Background: Developed countries adopted liquid-based cytology (LBC) cervical cytology, partly because of its lower proportions of unsatisfactory (U/S)/inadequate samples. This study was carried out to evaluate effect on the rate of U/S samples after introduction of LBC in our laboratory. Materials and Methods: An audit of U/S cervical samples was performed, which included split samples (n = 1000), only conventional Pap smear (CPS) smears (n = 1000), and only LBC samples (n = 1000). The smears were reviewed by two observers independently, and adequacy for the samples was assessed as per The Bethesda System 2001. The reasons for U/S rate in split samples were categorized into various cytologic and/or technical reasons. Results: U/S rate was far less in only LBC samples (1.2%) as compared to only CPS (10.5%) cases. Cases in the satisfactory but limited category were also less in only LBC (0.4%) as compared to only CPS (3.2%) samples. The main reasons for U/S smears in split samples were low cell count (37.2% in CPS; 58.8% in LBC). The second main reason was low cellularity with excess blood and only excess blood in CPS samples. Conclusion: There was a significant reduction of U/S rate in LBC samples as compared to CPS samples, and the difference was statistically significant. The main cause of U/S samples in LBC was low cellularity indicating a technical fault in sample collection. The main cause of U/S rate in CPS was low cellularity followed by low cellularity with excess blood. Adequate training of sample takers and cytologists for the precise cell count to determine adequacy in smears can be of great help in reducing U/S rate. PMID:27382408

  12. Sample size choices for XRCT scanning of highly unsaturated soil mixtures

    Directory of Open Access Journals (Sweden)

    Smith Jonathan C.

    2016-01-01

    Full Text Available Highly unsaturated soil mixtures (clay, sand and gravel are used as building materials in many parts of the world, and there is increasing interest in understanding their mechanical and hydraulic behaviour. In the laboratory, x-ray computed tomography (XRCT is becoming more widely used to investigate the microstructures of soils, however a crucial issue for such investigations is the choice of sample size, especially concerning the scanning of soil mixtures where there will be a range of particle and void sizes. In this paper we present a discussion (centred around a new set of XRCT scans on sample sizing for scanning of samples comprising soil mixtures, where a balance has to be made between realistic representation of the soil components and the desire for high resolution scanning, We also comment on the appropriateness of differing sample sizes in comparison to sample sizes used for other geotechnical testing. Void size distributions for the samples are presented and from these some hypotheses are made as to the roles of inter- and intra-aggregate voids in the mechanical behaviour of highly unsaturated soils.

  13. A margin based approach to determining sample sizes via tolerance bounds.

    Energy Technology Data Exchange (ETDEWEB)

    Newcomer, Justin T.; Freeland, Katherine Elizabeth

    2013-09-01

    This paper proposes a tolerance bound approach for determining sample sizes. With this new methodology we begin to think of sample size in the context of uncertainty exceeding margin. As the sample size decreases the uncertainty in the estimate of margin increases. This can be problematic when the margin is small and only a few units are available for testing. In this case there may be a true underlying positive margin to requirements but the uncertainty may be too large to conclude we have sufficient margin to those requirements with a high level of statistical confidence. Therefore, we provide a methodology for choosing a sample size large enough such that an estimated QMU uncertainty based on the tolerance bound approach will be smaller than the estimated margin (assuming there is positive margin). This ensures that the estimated tolerance bound will be within performance requirements and the tolerance ratio will be greater than one, supporting a conclusion that we have sufficient margin to the performance requirements. In addition, this paper explores the relationship between margin, uncertainty, and sample size and provides an approach and recommendations for quantifying risk when sample sizes are limited.

  14. Sample size calculation for differential expression analysis of RNA-seq data under Poisson distribution.

    Science.gov (United States)

    Li, Chung-I; Su, Pei-Fang; Guo, Yan; Shyr, Yu

    2013-01-01

    Sample size determination is an important issue in the experimental design of biomedical research. Because of the complexity of RNA-seq experiments, however, the field currently lacks a sample size method widely applicable to differential expression studies utilising RNA-seq technology. In this report, we propose several methods for sample size calculation for single-gene differential expression analysis of RNA-seq data under Poisson distribution. These methods are then extended to multiple genes, with consideration for addressing the multiple testing problem by controlling false discovery rate. Moreover, most of the proposed methods allow for closed-form sample size formulas with specification of the desired minimum fold change and minimum average read count, and thus are not computationally intensive. Simulation studies to evaluate the performance of the proposed sample size formulas are presented; the results indicate that our methods work well, with achievement of desired power. Finally, our sample size calculation methods are applied to three real RNA-seq data sets.

  15. Sample Size for Tablet Compression and Capsule Filling Events During Process Validation.

    Science.gov (United States)

    Charoo, Naseem Ahmad; Durivage, Mark; Rahman, Ziyaur; Ayad, Mohamad Haitham

    2017-12-01

    During solid dosage form manufacturing, the uniformity of dosage units (UDU) is ensured by testing samples at 2 stages, that is, blend stage and tablet compression or capsule/powder filling stage. The aim of this work is to propose a sample size selection approach based on quality risk management principles for process performance qualification (PPQ) and continued process verification (CPV) stages by linking UDU to potential formulation and process risk factors. Bayes success run theorem appeared to be the most appropriate approach among various methods considered in this work for computing sample size for PPQ. The sample sizes for high-risk (reliability level of 99%), medium-risk (reliability level of 95%), and low-risk factors (reliability level of 90%) were estimated to be 299, 59, and 29, respectively. Risk-based assignment of reliability levels was supported by the fact that at low defect rate, the confidence to detect out-of-specification units would decrease which must be supplemented with an increase in sample size to enhance the confidence in estimation. Based on level of knowledge acquired during PPQ and the level of knowledge further required to comprehend process, sample size for CPV was calculated using Bayesian statistics to accomplish reduced sampling design for CPV. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  16. Use of High-Frequency In-Home Monitoring Data May Reduce Sample Sizes Needed in Clinical Trials.

    Directory of Open Access Journals (Sweden)

    Hiroko H Dodge

    Full Text Available Trials in Alzheimer's disease are increasingly focusing on prevention in asymptomatic individuals. This poses a challenge in examining treatment effects since currently available approaches are often unable to detect cognitive and functional changes among asymptomatic individuals. Resultant small effect sizes require large sample sizes using biomarkers or secondary measures for randomized controlled trials (RCTs. Better assessment approaches and outcomes capable of capturing subtle changes during asymptomatic disease stages are needed.We aimed to develop a new approach to track changes in functional outcomes by using individual-specific distributions (as opposed to group-norms of unobtrusive continuously monitored in-home data. Our objective was to compare sample sizes required to achieve sufficient power to detect prevention trial effects in trajectories of outcomes in two scenarios: (1 annually assessed neuropsychological test scores (a conventional approach, and (2 the likelihood of having subject-specific low performance thresholds, both modeled as a function of time.One hundred nineteen cognitively intact subjects were enrolled and followed over 3 years in the Intelligent Systems for Assessing Aging Change (ISAAC study. Using the difference in empirically identified time slopes between those who remained cognitively intact during follow-up (normal control, NC and those who transitioned to mild cognitive impairment (MCI, we estimated comparative sample sizes required to achieve up to 80% statistical power over a range of effect sizes for detecting reductions in the difference in time slopes between NC and MCI incidence before transition.Sample size estimates indicated approximately 2000 subjects with a follow-up duration of 4 years would be needed to achieve a 30% effect size when the outcome is an annually assessed memory test score. When the outcome is likelihood of low walking speed defined using the individual-specific distributions of

  17. Blinded sample size re-estimation in three-arm trials with 'gold standard' design.

    Science.gov (United States)

    Mütze, Tobias; Friede, Tim

    2017-10-15

    In this article, we study blinded sample size re-estimation in the 'gold standard' design with internal pilot study for normally distributed outcomes. The 'gold standard' design is a three-arm clinical trial design that includes an active and a placebo control in addition to an experimental treatment. We focus on the absolute margin approach to hypothesis testing in three-arm trials at which the non-inferiority of the experimental treatment and the assay sensitivity are assessed by pairwise comparisons. We compare several blinded sample size re-estimation procedures in a simulation study assessing operating characteristics including power and type I error. We find that sample size re-estimation based on the popular one-sample variance estimator results in overpowered trials. Moreover, sample size re-estimation based on unbiased variance estimators such as the Xing-Ganju variance estimator results in underpowered trials, as it is expected because an overestimation of the variance and thus the sample size is in general required for the re-estimation procedure to eventually meet the target power. To overcome this problem, we propose an inflation factor for the sample size re-estimation with the Xing-Ganju variance estimator and show that this approach results in adequately powered trials. Because of favorable features of the Xing-Ganju variance estimator such as unbiasedness and a distribution independent of the group means, the inflation factor does not depend on the nuisance parameter and, therefore, can be calculated prior to a trial. Moreover, we prove that the sample size re-estimation based on the Xing-Ganju variance estimator does not bias the effect estimate. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. A comparison of conventional and computer-assisted semen analysis (CRISMAS software) using samples from 166 young Danish men.

    Science.gov (United States)

    Vested, Anne; Ramlau-Hansen, Cecilia H; Bonde, Jens P; Thulstrup, Ane M; Kristensen, Susanne L; Toft, Gunnar

    2011-05-01

    The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis (CASA) (Copenhagen Rigshospitalet Image House Sperm Motility Analysis System (CRISMAS) 4.6 software) using semen samples from 166 young Danish men. The CRISMAS software identifies sperm concentration and classifies spermatozoa into three motility categories. To enable comparison of the two methods, the four motility stages obtained by conventional semen analysis were, based on their velocity classifications, divided into three stages, comparable to the three CRISMAS motility categories: rapidly progressive (A), slowly progressive (B) and non-progressive (C+D). Differences between the two methods were large for all investigated parameters (P semen analysis, results were pooled into quarters according to date of semen analysis. CRISMAS motility results appeared more stable over time compared to the conventional analysis; however, neither method showed any trends. Apparently, CRISMAS CASA results and results from the conventional method were not comparable with respect to sperm concentration and motility analysis. This needs to be accounted for in clinics using this software and in studies of determinants of these semen characteristics.

  19. Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

    Science.gov (United States)

    Fienen, Michael N.; Selbig, William R.

    2012-01-01

    A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

  20. Stent sizing strategies in renal artery stenting: the comparison of conventional invasive renal angiography with renal computed tomographic angiography.

    Science.gov (United States)

    Kadziela, Jacek; Michalowska, Ilona; Pregowski, Jerzy; Janaszek-Sitkowska, Hanna; Lech, Katarzyna; Kabat, Marek; Staruch, Adam; Januszewicz, Andrzej; Witkowski, Adam

    2016-01-01

    Randomized trials comparing invasive treatment of renal artery stenosis with standard pharmacotherapy did not show substantial benefit from revascularization. One of the potential reasons for that may be suboptimal procedure technique. To compare renal stent sizing using two modalities: three-dimensional renal computed tomography angiography (CTA) versus conventional angiography. Forty patients (41 renal arteries), aged 65.1 ±8.5 years, who underwent renal artery stenting with preprocedural CTA performed within 6 months, were retrospectively analyzed. In CTA analysis, reference diameter (CTA-D) and lesion length (CTA_LL) were measured and proposed stent diameter and length were recorded. Similarly, angiographic reference diameter (ANGIO_D) and lesion length (ANGIO_LL) as well as proposed stent dimensions were obtained by visual estimation. The median CTA_D was 0.5 mm larger than the median ANGIO_D (p < 0.001). Also, the proposed stent diameter in CTA evaluation was 0.5 mm larger than that in angiography (p < 0.0001). The median CTA_LL was 1 mm longer than the ANGIO_LL (p = NS), with significant correlation of these variables (r = 0.66, p < 0.0001). The median proposed stent length with CTA was equal to that proposed with angiography. The median diameter of the implanted stent was 0.5 mm smaller than that proposed in CTA (p < 0.0005) and identical to that proposed in angiography. The median length of the actual stent was longer than that proposed in angiography (p = 0.0001). Renal CTA has potential advantages as a tool adjunctive to angiography in appropriate stent sizing. Careful evaluation of the available CTA scans may be beneficial and should be considered prior to the planned procedure.

  1. SMALL SAMPLE SIZE IN 2X2 CROSS OVER DESIGNS: CONDITIONS OF DETERMINATION

    Directory of Open Access Journals (Sweden)

    B SOLEYMANI

    2001-09-01

    Full Text Available Introduction. Determination of small sample size in some clinical trials is a matter of importance. In cross-over studies which are one types of clinical trials, the matter is more significant. In this article, the conditions in which determination of small sample size in cross-over studies are possible were considered, and the effect of deviation from normality on the matter has been shown. Methods. The present study has been done on such 2x2 cross-over studies that variable of interest is quantitative one and is measurable by ratio or interval scale. The method of consideration is based on use of variable and sample mean"s distributions, central limit theorem, method of sample size determination in two groups, and cumulant or moment generating function. Results. In normal variables or transferable to normal variables, there is no restricting factors other than significant level and power of the test for determination of sample size, but in the case of non-normal variables, it should be determined such large that guarantee the normality of sample mean"s distribution. Discussion. In such cross over studies that because of existence of theoretical base, few samples can be computed, one should not do it without taking applied worth of results into consideration. While determining sample size, in addition to variance, it is necessary to consider distribution of variable, particularly through its skewness and kurtosis coefficients. the more deviation from normality, the more need of samples. Since in medical studies most of the continuous variables are closed to normal distribution, a few number of samples often seems to be adequate for convergence of sample mean to normal distribution.

  2. Modeling gene flow distribution within conventional fields and development of a simplified sampling method to quantify adventitious GM contents in maize.

    Science.gov (United States)

    Melé, Enric; Nadal, Anna; Messeguer, Joaquima; Melé-Messeguer, Marina; Palaudelmàs, Montserrat; Peñas, Gisela; Piferrer, Xavier; Capellades, Gemma; Serra, Joan; Pla, Maria

    2015-11-24

    Genetically modified (GM) crops have been commercially grown for two decades. GM maize is one of 3 species with the highest acreage and specific events. Many countries established a mandatory labeling of products containing GM material, with thresholds for adventitious presence, to support consumers' freedom of choice. In consequence, coexistence systems need to be introduced to facilitate commercial culture of GM and non-GM crops in the same agricultural area. On modeling adventitious GM cross-pollination distribution within maize fields, we deduced a simple equation to estimate overall GM contents (%GM) of conventional fields, irrespective of its shape and size, and with no previous information on possible GM pollen donor fields. A sampling strategy was designed and experimentally validated in 19 agricultural fields. With 9 samples, %GM quantification requires just one analytical GM determination while identification of the pollen source needs 9 additional analyses. A decision support tool is provided.

  3. Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests

    Science.gov (United States)

    Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.

    2015-01-01

    The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…

  4. Sample sizes to control error estimates in determining soil bulk density in California forest soils

    Science.gov (United States)

    Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber

    2016-01-01

    Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...

  5. n4Studies: Sample Size Calculation for an Epidemiological Study on a Smart Device

    Directory of Open Access Journals (Sweden)

    Chetta Ngamjarus

    2016-05-01

    Full Text Available Objective: This study was to develop a sample size application (called “n4Studies” for free use on iPhone and Android devices and to compare sample size functions between n4Studies with other applications and software. Methods: Objective-C programming language was used to create the application for the iPhone OS (operating system while javaScript, jquery mobile, PhoneGap and jstat were used to develop it for Android phones. Other sample size applications were searched from the Apple app and Google play stores. The applications’ characteristics and sample size functions were collected. Spearman’s rank correlation was used to investigate the relationship between number of sample size functions and price. Results: “n4Studies” provides several functions for sample size and power calculations for various epidemiological study designs. It can be downloaded from the Apple App and Google play store. Comparing n4Studies with other applications, it covers several more types of epidemiological study designs, gives similar results for estimation of infinite/finite population mean and infinite/finite proportion from GRANMO, for comparing two independent means from BioStats, for comparing two independent proportions from EpiCal application. When using the same parameters, n4Studies gives similar results to STATA, epicalc package in R, PS, G*Power, and OpenEpi. Conclusion: “n4Studies” can be an alternative tool for calculating the sample size. It may be useful to students, lecturers and researchers in conducting their research projects.

  6. Constrained statistical inference: sample-size tables for ANOVA and regression

    Directory of Open Access Journals (Sweden)

    Leonard eVanbrabant

    2015-01-01

    Full Text Available Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient beta1 is larger than beta2 and beta3. The corresponding hypothesis is H: beta1 > {beta2, beta3} and this is known as an (order constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a smaller sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a prespecified power (say, 0.80 for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30% to 50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., beta1 > beta2 results in a higher power than assigning a positive or a negative sign to the parameters (e.g., beta1 > 0.

  7. Assessing terpene content variability of whitebark pine in order to estimate representative sample size

    Directory of Open Access Journals (Sweden)

    Stefanović Milena

    2013-01-01

    Full Text Available In studies of population variability, particular attention has to be paid to the selection of a representative sample. The aim of this study was to assess the size of the new representative sample on the basis of the variability of chemical content of the initial sample on the example of a whitebark pine population. Statistical analysis included the content of 19 characteristics (terpene hydrocarbons and their derivates of the initial sample of 10 elements (trees. It was determined that the new sample should contain 20 trees so that the mean value calculated from it represents a basic set with a probability higher than 95 %. Determination of the lower limit of the representative sample size that guarantees a satisfactory reliability of generalization proved to be very important in order to achieve cost efficiency of the research. [Projekat Ministarstva nauke Republike Srbije, br. OI-173011, br. TR-37002 i br. III-43007

  8. Nucleic acid sample preparation for in vitro molecular diagnosis: from conventional techniques to biotechnology.

    Science.gov (United States)

    Rahman, Md Mahbubor; Elaissari, Abdelhamid

    2012-11-01

    Nucleic acid (DNA and RNA)-based molecular diagnosis is a promising laboratory technique because of its ability to identify disease accurately. However, one of its disadvantages is the inevitable purification and detection of nucleic acids from other contaminated entities. Different nano- and microparticles have been developed for use in an advanced, efficient high-throughput autosystem for the purification and detection of nucleic acid samples for use in molecular diagnoses. In this review, we discuss recent advances in the development of particle-based nucleic acid purification and detection. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. Power and sample size calculations for Mendelian randomization studies using one genetic instrument.

    Science.gov (United States)

    Freeman, Guy; Cowling, Benjamin J; Schooling, C Mary

    2013-08-01

    Mendelian randomization, which is instrumental variable analysis using genetic variants as instruments, is an increasingly popular method of making causal inferences from observational studies. In order to design efficient Mendelian randomization studies, it is essential to calculate the sample sizes required. We present formulas for calculating the power of a Mendelian randomization study using one genetic instrument to detect an effect of a given size, and the minimum sample size required to detect effects for given levels of significance and power, using asymptotic statistical theory. We apply the formulas to some example data and compare the results with those from simulation methods. Power and sample size calculations using these formulas should be more straightforward to carry out than simulation approaches. These formulas make explicit that the sample size needed for Mendelian randomization study is inversely proportional to the square of the correlation between the genetic instrument and the exposure and proportional to the residual variance of the outcome after removing the effect of the exposure, as well as inversely proportional to the square of the effect size.

  10. Conventional and enantioselective gas chromatography with microfabricated planar columns for analysis of real-world samples of plant volatile fraction.

    Science.gov (United States)

    Cagliero, C; Galli, S; Galli, M; Elmi, I; Belluce, M; Zampolli, S; Sgorbini, B; Rubiolo, P; Bicchi, C

    2016-01-15

    Within a project exploring the application of lab-on-chip GC to in-field analysis of the plant volatile fraction, this study evaluated the performance of a set of planar columns (also known as microchannels, MEMS columns, or microfabricated columns) of different dimensions installed in a conventional GC unit. Circular double-spiral-shaped-channel planar columns with different square/rectangular sections up to 2m long were applied to the analysis of both essential oils and headspace samples of a group of medicinal and aromatic plants (chamomile, peppermint, sage, rosemary, lavender and bergamot) and of standard mixtures of related compounds; the results were compared to those obtained with reference narrow-bore columns (l:5m, dc:0.1mm, df:0.1 μm). The above essential oils and headspaces were first analyzed quali-and quantitatively with planar columns statically coated with conventional stationary phases (5%-phenyl-polymethylsiloxane and auto-bondable nitroterephthalic-acid-modified polyethylene glycol), and then submitted to chiral recognition of their diagnostic markers, by enantioselective GC with a planar columns coated with a cyclodextrin derivative (30% 6(I-VII)-O-TBDMS-3(I-VII)-O-ethyl-2(I-VII)-O-ethyl-β-cyclodextrin in PS-086). Column characteristics and analysis conditions were first optimized to obtain suitable retention and efficiency for the samples investigated. The planar columns tested showed performances close to the reference conventional narrow-bore columns, with theoretical plate numbers per meter (N/m) ranging from 6100 to 7200 for those coated with the conventional stationary phases, and above 5600 for those with the chiral selector. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. [Explanation of samples sizes in current biomedical journals: an irrational requirement].

    Science.gov (United States)

    Silva Ayçaguer, Luis Carlos; Alonso Galbán, Patricia

    2013-01-01

    To discuss the theoretical relevance of current requirements for explanations of the sample sizes employed in published studies, and to assess the extent to which these requirements are currently met by authors and demanded by referees and editors. A literature review was conducted to gain insight into and critically discuss the possible rationale underlying the requirement of justifying sample sizes. A descriptive bibliometric study was then carried out based on the original studies published in the six journals with the highest impact factor in the field of health in 2009. All the arguments used to support the requirement of an explanation of sample sizes are feeble, and there are several reasons why they should not be endorsed. These instructions are neglected in most of the studies published in the current literature with the highest impact factor. In 56% (95%CI: 52-59) of the articles, the sample size used was not substantiated, and only 27% (95%CI: 23-30) met all the requirements contained in the guidelines adhered to by the journals studied. Based on this study, we conclude that there are no convincing arguments justifying the requirement for an explanation of how the sample size was reached in published articles. There is no sound basis for this requirement, which not only does not promote the transparency of research reports but rather contributes to undermining it. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

  12. Sample Size for Assessing Agreement between Two Methods of Measurement by Bland-Altman Method.

    Science.gov (United States)

    Lu, Meng-Jie; Zhong, Wei-Hua; Liu, Yu-Xiu; Miao, Hua-Zhang; Li, Yong-Chang; Ji, Mu-Huo

    2016-11-01

    The Bland-Altman method has been widely used for assessing agreement between two methods of measurement. However, it remains unsolved about sample size estimation. We propose a new method of sample size estimation for Bland-Altman agreement assessment. According to the Bland-Altman method, the conclusion on agreement is made based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit. Under the theory of statistical inference, the formulae of sample size estimation are derived, which depended on the pre-determined level of α, β, the mean and the standard deviation of differences between two measurements, and the predefined limits. With this new method, the sample sizes are calculated under different parameter settings which occur frequently in method comparison studies, and Monte-Carlo simulation is used to obtain the corresponding powers. The results of Monte-Carlo simulation showed that the achieved powers could coincide with the pre-determined level of powers, thus validating the correctness of the method. The method of sample size estimation can be applied in the Bland-Altman method to assess agreement between two methods of measurement.

  13. A simple nomogram for sample size for estimating sensitivity and specificity of medical tests

    Directory of Open Access Journals (Sweden)

    Malhotra Rajeev

    2010-01-01

    Full Text Available Sensitivity and specificity measure inherent validity of a diagnostic test against a gold standard. Researchers develop new diagnostic methods to reduce the cost, risk, invasiveness, and time. Adequate sample size is a must to precisely estimate the validity of a diagnostic test. In practice, researchers generally decide about the sample size arbitrarily either at their convenience, or from the previous literature. We have devised a simple nomogram that yields statistically valid sample size for anticipated sensitivity or anticipated specificity. MS Excel version 2007 was used to derive the values required to plot the nomogram using varying absolute precision, known prevalence of disease, and 95% confidence level using the formula already available in the literature. The nomogram plot was obtained by suitably arranging the lines and distances to conform to this formula. This nomogram could be easily used to determine the sample size for estimating the sensitivity or specificity of a diagnostic test with required precision and 95% confidence level. Sample size at 90% and 99% confidence level, respectively, can also be obtained by just multiplying 0.70 and 1.75 with the number obtained for the 95% confidence level. A nomogram instantly provides the required number of subjects by just moving the ruler and can be repeatedly used without redoing the calculations. This can also be applied for reverse calculations. This nomogram is not applicable for testing of the hypothesis set-up and is applicable only when both diagnostic test and gold standard results have a dichotomous category.

  14. Exploratory factor analysis with small sample sizes: a comparison of three approaches.

    Science.gov (United States)

    Jung, Sunho

    2013-07-01

    Exploratory factor analysis (EFA) has emerged in the field of animal behavior as a useful tool for determining and assessing latent behavioral constructs. Because the small sample size problem often occurs in this field, a traditional approach, unweighted least squares, has been considered the most feasible choice for EFA. Two new approaches were recently introduced in the statistical literature as viable alternatives to EFA when sample size is small: regularized exploratory factor analysis and generalized exploratory factor analysis. A simulation study is conducted to evaluate the relative performance of these three approaches in terms of factor recovery under various experimental conditions of sample size, degree of overdetermination, and level of communality. In this study, overdetermination and sample size are the meaningful conditions in differentiating the performance of the three approaches in factor recovery. Specifically, when there are a relatively large number of factors, regularized exploratory factor analysis tends to recover the correct factor structure better than the other two approaches. Conversely, when few factors are retained, unweighted least squares tends to recover the factor structure better. Finally, generalized exploratory factor analysis exhibits very poor performance in factor recovery compared to the other approaches. This tendency is particularly prominent as sample size increases. Thus, generalized exploratory factor analysis may not be a good alternative to EFA. Regularized exploratory factor analysis is recommended over unweighted least squares unless small expected number of factors is ensured. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. A simulation study provided sample size guidance for differential item functioning (DIF) studies using short scales.

    Science.gov (United States)

    Scott, Neil W; Fayers, Peter M; Aaronson, Neil K; Bottomley, Andrew; de Graeff, Alexander; Groenvold, Mogens; Gundy, Chad; Koller, Michael; Petersen, Morten A; Sprangers, Mirjam A G

    2009-03-01

    Differential item functioning (DIF) analyses are increasingly used to evaluate health-related quality of life (HRQoL) instruments, which often include relatively short subscales. Computer simulations were used to explore how various factors including scale length affect analysis of DIF by ordinal logistic regression. Simulated data, representative of HRQoL scales with four-category items, were generated. The power and type I error rates of the DIF method were then investigated when, respectively, DIF was deliberately introduced and when no DIF was added. The sample size, scale length, floor effects (FEs) and significance level were varied. When there was no DIF, type I error rates were close to 5%. Detecting moderate uniform DIF in a two-item scale required a sample size of 300 per group for adequate (>80%) power. For longer scales, a sample size of 200 was adequate. Considerably larger sample sizes were required to detect nonuniform DIF, when there were extreme FEs or when a reduced type I error rate was required. The impact of the number of items in the scale was relatively small. Ordinal logistic regression successfully detects DIF for HRQoL instruments with short scales. Sample size guidelines are provided.

  16. Monte Carlo approaches for determining power and sample size in low-prevalence applications.

    Science.gov (United States)

    Williams, Michael S; Ebel, Eric D; Wagner, Bruce A

    2007-11-15

    The prevalence of disease in many populations is often low. For example, the prevalence of tuberculosis, brucellosis, and bovine spongiform encephalopathy range from 1 per 100,000 to less than 1 per 1,000,000 in many countries. When an outbreak occurs, epidemiological investigations often require comparing the prevalence in an exposed population with that of an unexposed population. To determine if the level of disease in the two populations is significantly different, the epidemiologist must consider the test to be used, desired power of the test, and determine the appropriate sample size for both the exposed and unexposed populations. Commonly available software packages provide estimates of the required sample sizes for this application. This study shows that these estimated sample sizes can exceed the necessary number of samples by more than 35% when the prevalence is low. We provide a Monte Carlo-based solution and show that in low-prevalence applications this approach can lead to reductions in the total samples size of more than 10,000 samples.

  17. Gridsampler – A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies

    Directory of Open Access Journals (Sweden)

    Mark Heckmann

    2017-01-01

    Full Text Available The repertory grid is a psychological data collection technique that is used to elicit qualitative data in the form of attributes as well as quantitative ratings. A common approach for evaluating multiple repertory grid data is sorting the elicited bipolar attributes (so called constructs into mutually exclusive categories by means of content analysis. An important question when planning this type of study is determining the sample size needed to a discover all attribute categories relevant to the field and b yield a predefined minimal number of attributes per category. For most applied researchers who collect multiple repertory grid data, programming a numeric simulation to answer these questions is not feasible. The gridsampler software facilitates determining the required sample size by providing a GUI for conducting the necessary numerical simulations. Researchers can supply a set of parameters suitable for the specific research situation, determine the required sample size, and easily explore the effects of changes in the parameter set.

  18. [On the impact of sample size calculation and power in clinical research].

    Science.gov (United States)

    Held, Ulrike

    2014-10-01

    The aim of a clinical trial is to judge the efficacy of a new therapy or drug. In the planning phase of the study, the calculation of the necessary sample size is crucial in order to obtain a meaningful result. The study design, the expected treatment effect in outcome and its variability, power and level of significance are factors which determine the sample size. It is often difficult to fix these parameters prior to the start of the study, but related papers from the literature can be helpful sources for the unknown quantities. For scientific as well as ethical reasons it is necessary to calculate the sample size in advance in order to be able to answer the study question.

  19. Species-genetic diversity correlations in habitat fragmentation can be biased by small sample sizes.

    Science.gov (United States)

    Nazareno, Alison G; Jump, Alistair S

    2012-06-01

    Predicted parallel impacts of habitat fragmentation on genes and species lie at the core of conservation biology, yet tests of this rule are rare. In a recent article in Ecology Letters, Struebig et al. (2011) report that declining genetic diversity accompanies declining species diversity in tropical forest fragments. However, this study estimates diversity in many populations through extrapolation from very small sample sizes. Using the data of this recent work, we show that results estimated from the smallest sample sizes drive the species-genetic diversity correlation (SGDC), owing to a false-positive association between habitat fragmentation and loss of genetic diversity. Small sample sizes are a persistent problem in habitat fragmentation studies, the results of which often do not fit simple theoretical models. It is essential, therefore, that data assessing the proposed SGDC are sufficient in order that conclusions be robust.

  20. Assessing the precision of a time-sampling-based study among GPs: balancing sample size and measurement frequency.

    Science.gov (United States)

    van Hassel, Daniël; van der Velden, Lud; de Bakker, Dinny; van der Hoek, Lucas; Batenburg, Ronald

    2017-12-04

    Our research is based on a technique for time sampling, an innovative method for measuring the working hours of Dutch general practitioners (GPs), which was deployed in an earlier study. In this study, 1051 GPs were questioned about their activities in real time by sending them one SMS text message every 3 h during 1 week. The required sample size for this study is important for health workforce planners to know if they want to apply this method to target groups who are hard to reach or if fewer resources are available. In this time-sampling method, however, standard power analyses is not sufficient for calculating the required sample size as this accounts only for sample fluctuation and not for the fluctuation of measurements taken from every participant. We investigated the impact of the number of participants and frequency of measurements per participant upon the confidence intervals (CIs) for the hours worked per week. Statistical analyses of the time-use data we obtained from GPs were performed. Ninety-five percent CIs were calculated, using equations and simulation techniques, for various different numbers of GPs included in the dataset and for various frequencies of measurements per participant. Our results showed that the one-tailed CI, including sample and measurement fluctuation, decreased from 21 until 3 h between one and 50 GPs. As a result of the formulas to calculate CIs, the increase of the precision continued and was lower with the same additional number of GPs. Likewise, the analyses showed how the number of participants required decreased if more measurements per participant were taken. For example, one measurement per 3-h time slot during the week requires 300 GPs to achieve a CI of 1 h, while one measurement per hour requires 100 GPs to obtain the same result. The sample size needed for time-use research based on a time-sampling technique depends on the design and aim of the study. In this paper, we showed how the precision of the

  1. Threshold-dependent sample sizes for selenium assessment with stream fish tissue.

    Science.gov (United States)

    Hitt, Nathaniel P; Smith, David R

    2015-01-01

    Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α=0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites

  2. Threshold-dependent sample sizes for selenium assessment with stream fish tissue

    Science.gov (United States)

    Hitt, Nathaniel P.; Smith, David R.

    2015-01-01

    Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased

  3. Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems.

    Science.gov (United States)

    Bonte, Anja; Neuweger, Heiko; Goesmann, Alexander; Thonar, Cécile; Mäder, Paul; Langenkämper, Georg; Niehaus, Karsten

    2014-10-01

    Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted using methanol and analysed by gas chromatography-mass spectrometry. Altogether 48 metabolites and 245 non-identified metabolites (TAGs) were detected in the cultivar Runal. Principal component analysis showed a sample clustering according to farming systems and significant differences in peak areas between the farming systems for 10 Runal metabolites. Results obtained from all 11 cultivars indicated a greater influence of the cultivar than the farming system on metabolite concentrations. Nevertheless, a t-test on data of all cultivars still detected 5 metabolites and 11 TAGs with significant differences between the farming systems. Based on individual cultivars, metabolite profiling showed promising results for the categorization of organic and conventional wheat. Further investigations are necessary with wheat from more growing seasons and locations before definite conclusions can be drawn concerning the feasibility to evolve a combined set of biomarkers for organically grown wheat using metabolite profiles. © 2014 Society of Chemical Industry.

  4. Chi-Squared Test of Fit and Sample Size-A Comparison between a Random Sample Approach and a Chi-Square Value Adjustment Method.

    Science.gov (United States)

    Bergh, Daniel

    2015-01-01

    Chi-square statistics are commonly used for tests of fit of measurement models. Chi-square is also sensitive to sample size, which is why several approaches to handle large samples in test of fit analysis have been developed. One strategy to handle the sample size problem may be to adjust the sample size in the analysis of fit. An alternative is to adopt a random sample approach. The purpose of this study was to analyze and to compare these two strategies using simulated data. Given an original sample size of 21,000, for reductions of sample sizes down to the order of 5,000 the adjusted sample size function works as good as the random sample approach. In contrast, when applying adjustments to sample sizes of lower order the adjustment function is less effective at approximating the chi-square value for an actual random sample of the relevant size. Hence, the fit is exaggerated and misfit under-estimated using the adjusted sample size function. Although there are big differences in chi-square values between the two approaches at lower sample sizes, the inferences based on the p-values may be the same.

  5. Predictors of Citation Rate in Psychology: Inconclusive Influence of Effect and Sample Size.

    Science.gov (United States)

    Hanel, Paul H P; Haase, Jennifer

    2017-01-01

    In the present article, we investigate predictors of how often a scientific article is cited. Specifically, we focus on the influence of two often neglected predictors of citation rate: effect size and sample size, using samples from two psychological topical areas. Both can be considered as indicators of the importance of an article and post hoc (or observed) statistical power, and should, especially in applied fields, predict citation rates. In Study 1, effect size did not have an influence on citation rates across a topical area, both with and without controlling for numerous variables that have been previously linked to citation rates. In contrast, sample size predicted citation rates, but only while controlling for other variables. In Study 2, sample and partly effect sizes predicted citation rates, indicating that the relations vary even between scientific topical areas. Statistically significant results had more citations in Study 2 but not in Study 1. The results indicate that the importance (or power) of scientific findings may not be as strongly related to citation rate as is generally assumed.

  6. Optimal sample size determinations from an industry perspective based on the expected value of information.

    Science.gov (United States)

    Willan, Andrew R

    2008-01-01

    Traditional sample size calculations for randomized clinical trials depend on somewhat arbitrarily chosen factors, such as type I and II errors. As an alternative, taking a societal perspective, and using the expected value of information based on Bayesian decision theory, a number of authors have recently shown how to determine the sample size that maximizes the expected net gain, i.e., the difference between the cost of the trial and the value of the information gained from the results. Other authors have proposed Bayesian methods to determine sample sizes from an industry perspective. The purpose of this article is to propose a Bayesian approach to sample size calculations from an industry perspective that attempts to determine the sample size that maximizes expected profit. A model is proposed for expected total profit that includes consideration of per-patient profit, disease incidence, time horizon, trial duration, market share, discount rate, and the relationship between the results and the probability of regulatory approval. The expected value of information provided by trial data is related to the increase in expected profit from increasing the probability of regulatory approval. The methods are applied to an example, including an examination of robustness. The model is extended to consider market share as a function of observed treatment effect. The use of methods based on the expected value of information can provide, from an industry perspective, robust sample size solutions that maximize the difference between the expected cost of the trial and the expected value of information gained from the results. The method is only as good as the model for expected total profit. Although the model probably has all the right elements, it assumes that market share, per-patient profit, and incidence are insensitive to trial results. The method relies on the central limit theorem which assumes that the sample sizes involved ensure that the relevant test statistics

  7. Max control chart with adaptive sample sizes for jointly monitoring process mean and standard deviation

    OpenAIRE

    Ching Chun Huang

    2014-01-01

    This paper develops the two-state and three-state adaptive sample size control schemes based on the Max chart to simultaneously monitor the process mean and standard deviation. Since the Max chart is a single variables control chart where only one plotting statistic is needed, the design and operation of adaptive sample size schemes for this chart will be simpler than those for the joint [Xmacr ] and S charts. Three types of processes including on-target initial, off-target initial and steady...

  8. Bayesian sample size determination for cost-effectiveness studies with censored data.

    Directory of Open Access Journals (Sweden)

    Daniel P Beavers

    Full Text Available Cost-effectiveness models are commonly utilized to determine the combined clinical and economic impact of one treatment compared to another. However, most methods for sample size determination of cost-effectiveness studies assume fully observed costs and effectiveness outcomes, which presents challenges for survival-based studies in which censoring exists. We propose a Bayesian method for the design and analysis of cost-effectiveness data in which costs and effectiveness may be censored, and the sample size is approximated for both power and assurance. We explore two parametric models and demonstrate the flexibility of the approach to accommodate a variety of modifications to study assumptions.

  9. Determining optimal sample sizes for multi-stage randomized clinical trials using value of information methods.

    Science.gov (United States)

    Willan, Andrew; Kowgier, Matthew

    2008-01-01

    Traditional sample size calculations for randomized clinical trials depend on somewhat arbitrarily chosen factors, such as Type I and II errors. An effectiveness trial (otherwise known as a pragmatic trial or management trial) is essentially an effort to inform decision-making, i.e., should treatment be adopted over standard? Taking a societal perspective and using Bayesian decision theory, Willan and Pinto (Stat. Med. 2005; 24:1791-1806 and Stat. Med. 2006; 25:720) show how to determine the sample size that maximizes the expected net gain, i.e., the difference between the cost of doing the trial and the value of the information gained from the results. These methods are extended to include multi-stage adaptive designs, with a solution given for a two-stage design. The methods are applied to two examples. As demonstrated by the two examples, substantial increases in the expected net gain (ENG) can be realized by using multi-stage adaptive designs based on expected value of information methods. In addition, the expected sample size and total cost may be reduced. Exact solutions have been provided for the two-stage design. Solutions for higher-order designs may prove to be prohibitively complex and approximate solutions may be required. The use of multi-stage adaptive designs for randomized clinical trials based on expected value of sample information methods leads to substantial gains in the ENG and reductions in the expected sample size and total cost.

  10. A simulation-based sample size calculation method for pre-clinical tumor xenograft experiments.

    Science.gov (United States)

    Wu, Jianrong; Yang, Shengping

    2017-04-07

    Pre-clinical tumor xenograft experiments usually require a small sample size that is rarely greater than 20, and data generated from such experiments very often do not have censored observations. Many statistical tests can be used for analyzing such data, but most of them were developed based on large sample approximation. We demonstrate that the type-I error rates of these tests can substantially deviate from the designated rate, especially when the data to be analyzed has a skewed distribution. Consequently, the sample size calculated based on these tests can be erroneous. We propose a modified signed log-likelihood ratio test (MSLRT) to meet the type-I error rate requirement for analyzing pre-clinical tumor xenograft data. The MSLRT has a consistent and symmetric type-I error rate that is very close to the designated rate for a wide range of sample sizes. By simulation, we generated a series of sample size tables based on scenarios commonly expected in tumor xenograft experiments, and we expect that these tables can be used as guidelines for making decisions on the numbers of mice used in tumor xenograft experiments.

  11. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

    Science.gov (United States)

    Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

    2014-12-19

    In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different

  12. Sample size bounding and context ranking as approaches to the HRA data problem

    Energy Technology Data Exchange (ETDEWEB)

    Reer, Bernhard

    2004-02-01

    This paper presents a technique denoted as sub sample size bounding (SSSB) useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications for human reliability analysis (HRA) are emphasized in the presentation of the technique. Exemplified by a sample of 180 abnormal event sequences, it is outlined how SSSB can provide viable input for the quantification of errors of commission (EOCs)

  13. Sample Size Bounding and Context Ranking as Approaches to the Human Error Quantification Problem

    Energy Technology Data Exchange (ETDEWEB)

    Reer, B

    2004-03-01

    The paper describes a technique denoted as Sub-Sample-Size Bounding (SSSB), which is useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications to human reliability analysis (HRA) are emphasised in the presentation of this technique. Exemplified by a sample of 180 abnormal event sequences, the manner in which SSSB can provide viable input for the quantification of errors of commission (EOCs) are outlined. (author)

  14. SAMPLE SIZE DETERMINATION IN NON-RADOMIZED SURVIVAL STUDIES WITH NON-CENSORED AND CENSORED DATA

    OpenAIRE

    Faghihzadeh, S.; M. Rahgozar

    2003-01-01

    Introduction: In survival analysis, determination of sufficient sample size to achieve suitable statistical power is important .In both parametric and non-parametric methods of classic statistics, randomn selection of samples is a basic condition. practically, in most clinical trials and health surveys randomn allocation is impossible. Fixed - effect multiple linear regression analysis covers this need and this feature could be extended to survival regression analysis. This paper is the resul...

  15. Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

    Science.gov (United States)

    Krishnamoorthy, K.; Xia, Yanping

    2008-01-01

    The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…

  16. Sample size calculations for clinical trials targeting tauopathies: A new potential disease target

    Science.gov (United States)

    Whitwell, Jennifer L.; Duffy, Joseph R.; Strand, Edythe A.; Machulda, Mary M.; Tosakulwong, Nirubol; Weigand, Stephen D.; Senjem, Matthew L.; Spychalla, Anthony J.; Gunter, Jeffrey L.; Petersen, Ronald C.; Jack, Clifford R.; Josephs, Keith A.

    2015-01-01

    Disease-modifying therapies are being developed to target tau pathology, and should, therefore, be tested in primary tauopathies. We propose that progressive apraxia of speech should be considered one such target group. In this study, we investigate potential neuroimaging and clinical outcome measures for progressive apraxia of speech and determine sample size estimates for clinical trials. We prospectively recruited 24 patients with progressive apraxia of speech who underwent two serial MRI with an interval of approximately two years. Detailed speech and language assessments included the Apraxia of Speech Rating Scale (ASRS) and Motor Speech Disorders (MSD) severity scale. Rates of ventricular expansion and rates of whole brain, striatal and midbrain atrophy were calculated. Atrophy rates across 38 cortical regions were also calculated and the regions that best differentiated patients from controls were selected. Sample size estimates required to power placebo-controlled treatment trials were calculated. The smallest sample size estimates were obtained with rates of atrophy of the precentral gyrus and supplementary motor area, with both measures requiring less than 50 subjects per arm to detect a 25% treatment effect with 80% power. These measures outperformed the other regional and global MRI measures and the clinical scales. Regional rates of cortical atrophy therefore provide the best outcome measures in progressive apraxia of speech. The small sample size estimates demonstrate feasibility for including progressive apraxia of speech in future clinical treatment trials targeting tau. PMID:26076744

  17. Size Distributions and Characterization of Native and Ground Samples for Toxicology Studies

    Science.gov (United States)

    McKay, David S.; Cooper, Bonnie L.; Taylor, Larry A.

    2010-01-01

    This slide presentation shows charts and graphs that review the particle size distribution and characterization of natural and ground samples for toxicology studies. There are graphs which show the volume distribution versus the number distribution for natural occurring dust, jet mill ground dust, and ball mill ground dust.

  18. B-graph sampling to estimate the size of a hidden population

    NARCIS (Netherlands)

    Spreen, M.; Bogaerts, S.

    2015-01-01

    Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is

  19. Required sample size for monitoring stand dynamics in strict forest reserves: a case study

    Science.gov (United States)

    Diego Van Den Meersschaut; Bart De Cuyper; Kris Vandekerkhove; Noel Lust

    2000-01-01

    Stand dynamics in European strict forest reserves are commonly monitored using inventory densities of 5 to 15 percent of the total surface. The assumption that these densities guarantee a representative image of certain parameters is critically analyzed in a case study for the parameters basal area and stem number. The required sample sizes for different accuracy and...

  20. Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

    Science.gov (United States)

    Li, Zhushan

    2014-01-01

    Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

  1. Got Power? A Systematic Review of Sample Size Adequacy in Health Professions Education Research

    Science.gov (United States)

    Cook, David A.; Hatala, Rose

    2015-01-01

    Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011,…

  2. Introduction to Sample Size Choice for Confidence Intervals Based on "t" Statistics

    Science.gov (United States)

    Liu, Xiaofeng Steven; Loudermilk, Brandon; Simpson, Thomas

    2014-01-01

    Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis…

  3. A Unified Approach to Power Calculation and Sample Size Determination for Random Regression Models

    Science.gov (United States)

    Shieh, Gwowen

    2007-01-01

    The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…

  4. Precise confidence intervals of regression-based reference limits: Method comparisons and sample size requirements.

    Science.gov (United States)

    Shieh, Gwowen

    2017-12-01

    Covariate-dependent reference limits have been extensively applied in biology and medicine for determining the substantial magnitude and relative importance of quantitative measurements. Confidence interval and sample size procedures are available for studying regression-based reference limits. However, the existing popular methods employ different technical simplifications and are applicable only in certain limited situations. This paper describes exact confidence intervals of regression-based reference limits and compares the exact approach with the approximate methods under a wide range of model configurations. Using the ratio between the widths of confidence interval and reference interval as the relative precision index, optimal sample size procedures are presented for precise interval estimation under expected ratio and tolerance probability considerations. Simulation results show that the approximate interval methods using normal distribution have inaccurate confidence limits. The exact confidence intervals dominate the approximate procedures in one- and two-sided coverage performance. Unlike the current simplifications, the proposed sample size procedures integrate all key factors including covariate features in the optimization process and are suitable for various regression-based reference limit studies with potentially diverse configurations. The exact interval estimation has theoretical and practical advantages over the approximate methods. The corresponding sample size procedures and computing algorithms are also presented to facilitate the data analysis and research design of regression-based reference limits. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Effect of sample moisture content on XRD-estimated cellulose crystallinity index and crystallite size

    Science.gov (United States)

    Umesh P. Agarwal; Sally A. Ralph; Carlos Baez; Richard S. Reiner; Steve P. Verrill

    2017-01-01

    Although X-ray diffraction (XRD) has been the most widely used technique to investigate crystallinity index (CrI) and crystallite size (L200) of cellulose materials, there are not many studies that have taken into account the role of sample moisture on these measurements. The present investigation focuses on a variety of celluloses and cellulose...

  6. [Sample size calculation in clinical post-marketing evaluation of traditional Chinese medicine].

    Science.gov (United States)

    Fu, Yingkun; Xie, Yanming

    2011-10-01

    In recent years, as the Chinese government and people pay more attention on the post-marketing research of Chinese Medicine, part of traditional Chinese medicine breed has or is about to begin after the listing of post-marketing evaluation study. In the post-marketing evaluation design, sample size calculation plays a decisive role. It not only ensures the accuracy and reliability of post-marketing evaluation. but also assures that the intended trials will have a desired power for correctly detecting a clinically meaningful difference of different medicine under study if such a difference truly exists. Up to now, there is no systemic method of sample size calculation in view of the traditional Chinese medicine. In this paper, according to the basic method of sample size calculation and the characteristic of the traditional Chinese medicine clinical evaluation, the sample size calculation methods of the Chinese medicine efficacy and safety are discussed respectively. We hope the paper would be beneficial to medical researchers, and pharmaceutical scientists who are engaged in the areas of Chinese medicine research.

  7. Influence of tree spatial pattern and sample plot type and size on inventory

    Science.gov (United States)

    John-Pascall Berrill; Kevin L. O' Hara

    2012-01-01

    Sampling with different plot types and sizes was simulated using tree location maps and data collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius circular plots, belt transects, and variable-radius plots were installed by...

  8. Size-Resolved Penetration Through High-Efficiency Filter Media Typically Used for Aerosol Sampling

    Czech Academy of Sciences Publication Activity Database

    Zíková, Naděžda; Ondráček, Jakub; Ždímal, Vladimír

    2015-01-01

    Roč. 49, č. 4 (2015), s. 239-249 ISSN 0278-6826 R&D Projects: GA ČR(CZ) GBP503/12/G147 Institutional support: RVO:67985858 Keywords : filters * size-resolved penetration * atmospheric aerosol sampling Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.953, year: 2015

  9. Estimating the Size of a Large Network and its Communities from a Random Sample.

    Science.gov (United States)

    Chen, Lin; Karbasi, Amin; Crawford, Forrest W

    2016-01-01

    Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V, E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K, and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios.

  10. Sample size calculations for evaluating treatment policies in multi-stage designs.

    Science.gov (United States)

    Dawson, Ree; Lavori, Philip W

    2010-12-01

    Sequential multiple assignment randomized (SMAR) designs are used to evaluate treatment policies, also known as adaptive treatment strategies (ATS). The determination of SMAR sample sizes is challenging because of the sequential and adaptive nature of ATS, and the multi-stage randomized assignment used to evaluate them. We derive sample size formulae appropriate for the nested structure of successive SMAR randomizations. This nesting gives rise to ATS that have overlapping data, and hence between-strategy covariance. We focus on the case when covariance is substantial enough to reduce sample size through improved inferential efficiency. Our design calculations draw upon two distinct methodologies for SMAR trials, using the equality of the optimal semi-parametric and Bayesian predictive estimators of standard error. This 'hybrid' approach produces a generalization of the t-test power calculation that is carried out in terms of effect size and regression quantities familiar to the trialist. Simulation studies support the reasonableness of underlying assumptions as well as the adequacy of the approximation to between-strategy covariance when it is substantial. Investigation of the sensitivity of formulae to misspecification shows that the greatest influence is due to changes in effect size, which is an a priori clinical judgment on the part of the trialist. We have restricted simulation investigation to SMAR studies of two and three stages, although the methods are fully general in that they apply to 'K-stage' trials. Practical guidance is needed to allow the trialist to size a SMAR design using the derived methods. To this end, we define ATS to be 'distinct' when they differ by at least the (minimal) size of effect deemed to be clinically relevant. Simulation results suggest that the number of subjects needed to distinguish distinct strategies will be significantly reduced by adjustment for covariance only when small effects are of interest.

  11. Comparison of the BBL CHROMagar Staph aureus agar medium to conventional media for detection of Staphylococcus aureus in respiratory samples.

    Science.gov (United States)

    Flayhart, Diane; Lema, Clara; Borek, Anita; Carroll, Karen C

    2004-08-01

    Screening for Staphylococcus aureus has become routine in certain patient populations. This study is the first clinical evaluation of the BBL CHROMagar Staph aureus agar (CSA) medium (BD Diagnostics, Sparks, Md.) for detection of S. aureus in nasal surveillance cultures and in respiratory samples from cystic fibrosis (CF) patients. S. aureus colonies appear mauve on CSA. Other organisms are inhibited or produce a distinctly different colony color. S. aureus was identified from all media by slide coagulase, exogenous DNase, and mannitol fermentation assays. Susceptibility testing was performed using the agar dilution method. A total of 679 samples were evaluated. All samples were inoculated onto CSA. Nasal surveillance cultures were inoculated onto sheep blood agar (SBA) (BD Diagnostics), and samples from CF patients were inoculated onto mannitol salt agar (MSA) (BD Diagnostics). Of the 679 samples cultured, 200 organisms produced a mauve color on CSA (suspicious for S. aureus) and 180 were positive for S. aureus on SBA or MSA. Of 200 CSA-positive samples 191 were identified as S. aureus. Nine mauve colonies were slide coagulase negative and were subsequently identified as Staphylococcus lugdunensis (one), Staphylococcus epidermidis (three), Staphylococcus haemolyticus (one), and Corynebacterium species (four). CSA improved the ability to detect S. aureus by recovering 12 S. aureus isolates missed by conventional media. Of the 192 S. aureus isolates recovered, 122 were methicillin susceptible and 70 were methicillin resistant. Overall, the sensitivity and specificity of CSA in this study were 99.5 and 98%, respectively. There was no difference in the performance of the slide coagulase test or in susceptibility testing performed on S. aureus recovered from CSA compared to SBA or MSA. Our data support the use of CSA in place of standard culture media for detection of S. aureus in heavily contaminated respiratory samples.

  12. Identifying Economies of Size in Conventional Surface Water Treatment and Brackish-Groundwater Desalination: Case Study in the Rio Grande Valley of Texas

    OpenAIRE

    Boyer, Christopher N.; Rister, M. Edward; Sturdivant, Allen W.; Lacewell, Ronald D.; Harris, Bill L.

    2008-01-01

    Two primary potable water-treatment technologies used in South Texas include conventional surface-water and reverse-osmosis (RO) desalination of brackish-groundwater. As the region's population continues to grow, municipalities are searching for economical means to expand their water supplies. Economies of size for both technologies are an important consideration for future expansion decisions.

  13. Percolating macropore networks in tilled topsoil: effects of sample size, minimum pore thickness and soil type

    Science.gov (United States)

    Jarvis, Nicholas; Larsbo, Mats; Koestel, John; Keck, Hannes

    2017-04-01

    The long-range connectivity of macropore networks may exert a strong control on near-saturated and saturated hydraulic conductivity and the occurrence of preferential flow through soil. It has been suggested that percolation concepts may provide a suitable theoretical framework to characterize and quantify macropore connectivity, although this idea has not yet been thoroughly investigated. We tested the applicability of percolation concepts to describe macropore networks quantified by X-ray scanning at a resolution of 0.24 mm in eighteen cylinders (20 cm diameter and height) sampled from the ploughed layer of four soils of contrasting texture in east-central Sweden. The analyses were performed for sample sizes ("regions of interest", ROI) varying between 3 and 12 cm in cube side-length and for minimum pore thicknesses ranging between image resolution and 1 mm. Finite sample size effects were clearly found for ROI's of cube side-length smaller than ca. 6 cm. For larger sample sizes, the results showed the relevance of percolation concepts to soil macropore networks, with a close relationship found between imaged porosity and the fraction of the pore space which percolated (i.e. was connected from top to bottom of the ROI). The percolating fraction increased rapidly as a function of porosity above a small percolation threshold (1-4%). This reflects the ordered nature of the pore networks. The percolation relationships were similar for all four soils. Although pores larger than 1 mm appeared to be somewhat better connected, only small effects of minimum pore thickness were noted across the range of tested pore sizes. The utility of percolation concepts to describe the connectivity of more anisotropic macropore networks (e.g. in subsoil horizons) should also be tested, although with current X-ray scanning equipment it may prove difficult in many cases to analyze sufficiently large samples that would avoid finite size effects.

  14. Utility of manual liquid-based cytology and conventional smears in the evaluation of various fine-needle aspiration samples

    Directory of Open Access Journals (Sweden)

    P Arul

    2016-01-01

    Full Text Available Background: Liquid-based cytology (LBC preparation is a way to improve and refine the fine-needle aspiration (FNA samples. There are a few studies comparing LBC with conventional smear (CS. Aim: The present study was undertaken to evaluate the utility of manual LBC (MLBC and CS preparations in various FNA samples. Materials and Methods: In this cross-sectional study, a total of 100 FNA samples from various anatomical sites were evaluated using MLBC and CS preparations. Cellularity, blood, informative background, monolayers, cell architecture, cytoplasmic, and nuclear preservation were compared with MLBC and CS preparations by Wilcoxon signed rank test. P < 0.05 is considered statistically significant. Results: MLBC preparations were superior to CS preparations in view of absence of blood and debris (P = 0.001, presence of monolayers (P < 0.001, and preservation of cytoplasmic (P = 0.001 and nuclear details (P = 0.001. However, no statistically significant differences were found between MLBC and CS preparations with regard to cellularity (P = 0.157, informative background (P = 0.083, and architecture (P = 0.739. Conclusion: MLBC preparations in FNAC are a safe, easy, and less time-consuming procedure, and it may have promising diagnostic value in the evaluation of FNA samples from various anatomical sites. However, the use of both MLBC and CS preparations is recommended to achieve optimal diagnostic yield.

  15. The impact of sample size and marker selection on the study of haplotype structures

    Directory of Open Access Journals (Sweden)

    Sun Xiao

    2004-03-01

    Full Text Available Abstract Several studies of haplotype structures in the human genome in various populations have found that the human chromosomes are structured such that each chromosome can be divided into many blocks, within which there is limited haplotype diversity. In addition, only a few genetic markers in a putative block are needed to capture most of the diversity within a block. There has been no systematic empirical study of the effects of sample size and marker set on the identified block structures and representative marker sets, however. The purpose of this study was to conduct a detailed empirical study to examine such impacts. Towards this goal, we have analysed three representative autosomal regions from a large genome-wide study of haplotypes with samples consisting of African-Americans and samples consisting of Japanese and Chinese individuals. For both populations, we have found that the sample size and marker set have significant impact on the number of blocks and the total number of representative markers identified. The marker set in particular has very strong impacts, and our results indicate that the marker density in the original datasets may not be adequate to allow a meaningful characterisation of haplotype structures. In general, we conclude that we need a relatively large sample size and a very dense marker panel in the study of haplotype structures in human populations.

  16. Performance of a reciprocal shaker in mechanical dispersion of soil samples for particle-size analysis

    Directory of Open Access Journals (Sweden)

    Thayse Aparecida Dourado

    2012-08-01

    Full Text Available The dispersion of the samples in soil particle-size analysis is a fundamental step, which is commonly achieved with a combination of chemical agents and mechanical agitation. The purpose of this study was to evaluate the efficiency of a low-speed reciprocal shaker for the mechanical dispersion of soil samples of different textural classes. The particle size of 61 soil samples was analyzed in four replications, using the pipette method to determine the clay fraction and sieving to determine coarse, fine and total sand fractions. The silt content was obtained by difference. To evaluate the performance, the results of the reciprocal shaker (RSh were compared with data of the same soil samples available in reports of the Proficiency testing for Soil Analysis Laboratories of the Agronomic Institute of Campinas (Prolab/IAC. The accuracy was analyzed based on the maximum and minimum values defining the confidence intervals for the particle-size fractions of each soil sample. Graphical indicators were also used for data comparison, based on dispersion and linear adjustment. The descriptive statistics indicated predominantly low variability in more than 90 % of the results for sand, medium-textured and clay samples, and for 68 % of the results for heavy clay samples, indicating satisfactory repeatability of measurements with the RSh. Medium variability was frequently associated with silt, followed by the fine sand fraction. The sensitivity analyses indicated an accuracy of 100 % for the three main separates (total sand, silt and clay, in all 52 samples of the textural classes heavy clay, clay and medium. For the nine sand soil samples, the average accuracy was 85.2 %; highest deviations were observed for the silt fraction. In relation to the linear adjustments, the correlation coefficients of 0.93 (silt or > 0.93 (total sand and clay, as well as the differences between the angular coefficients and the unit < 0.16, indicated a high correlation between the

  17. B-Graph Sampling to Estimate the Size of a Hidden Population

    Directory of Open Access Journals (Sweden)

    Spreen Marinus

    2015-12-01

    Full Text Available Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is respondent-driven sampling in which no sampling frame is used. However, in some studies multiple but incomplete sampling frames are available. In this article, we introduce the B-graph design that can be used in such situations. In this design, all available incomplete sampling frames are joined and turned into one sampling frame, from which a random sample is drawn and selected respondents are asked to mention their contacts. By considering the population as a bipartite graph of a two-mode network (those from the sampling frame and those who are not on the frame, the number of respondents who are directly linked to the sampling frame members can be estimated using Chao’s and Zelterman’s estimators for sparse data. The B-graph sampling design is illustrated using the data of a social network study from Utrecht, the Netherlands.

  18. Planosol soil sample size for computerized tomography measurement of physical parameters

    Directory of Open Access Journals (Sweden)

    Pedrotti Alceu

    2003-01-01

    Full Text Available Computerized tomography (CT is an important tool in Soil Science for noninvasive measurement of density and water content of soil samples. This work aims to describe the aspects of sample size adequacy for Planosol (Albaqualf and to evaluate procedures for statistical analysis, using a CT scanner with a 241Am source. Density errors attributed to the equipment are 0.051 and 0.046 Mg m-3 for horizons A and B, respectively. The theoretical value for sample thickness for the Planosol, using this equipment, is 4.0 cm for the horizons A and B. The ideal thickness of samples is approximately 6.0 cm, being smaller for samples of the horizon B in relation to A. Alternatives for the improvement of the efficiency analysis and the reliability of the results obtained by CT are also discussed, and indicate good precision and adaptability of the application of this technology in Planosol (Albaqualf studies.

  19. PIXE–PIGE analysis of size-segregated aerosol samples from remote areas

    Energy Technology Data Exchange (ETDEWEB)

    Calzolai, G., E-mail: calzolai@fi.infn.it [Department of Physics and Astronomy, University of Florence and National Institute of Nuclear Physics (INFN), Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Chiari, M.; Lucarelli, F.; Nava, S.; Taccetti, F. [Department of Physics and Astronomy, University of Florence and National Institute of Nuclear Physics (INFN), Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Becagli, S.; Frosini, D.; Traversi, R.; Udisti, R. [Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino (Italy)

    2014-01-01

    The chemical characterization of size-segregated samples is helpful to study the aerosol effects on both human health and environment. The sampling with multi-stage cascade impactors (e.g., Small Deposit area Impactor, SDI) produces inhomogeneous samples, with a multi-spot geometry and a non-negligible particle stratification. At LABEC (Laboratory of nuclear techniques for the Environment and the Cultural Heritage), an external beam line is fully dedicated to PIXE–PIGE analysis of aerosol samples. PIGE is routinely used as a sidekick of PIXE to correct the underestimation of PIXE in quantifying the concentration of the lightest detectable elements, like Na or Al, due to X-ray absorption inside the individual aerosol particles. In this work PIGE has been used to study proper attenuation correction factors for SDI samples: relevant attenuation effects have been observed also for stages collecting smaller particles, and consequent implications on the retrieved aerosol modal structure have been evidenced.

  20. Sample size calculation for microarray experiments with blocked one-way design

    Directory of Open Access Journals (Sweden)

    Jung Sin-Ho

    2009-05-01

    Full Text Available Abstract Background One of the main objectives of microarray analysis is to identify differentially expressed genes for different types of cells or treatments. Many statistical methods have been proposed to assess the treatment effects in microarray experiments. Results In this paper, we consider discovery of the genes that are differentially expressed among K (> 2 treatments when each set of K arrays consists of a block. In this case, the array data among K treatments tend to be correlated because of block effect. We propose to use the blocked one-way ANOVA F-statistic to test if each gene is differentially expressed among K treatments. The marginal p-values are calculated using a permutation method accounting for the block effect, adjusting for the multiplicity of the testing procedure by controlling the false discovery rate (FDR. We propose a sample size calculation method for microarray experiments with a blocked one-way design. With FDR level and effect sizes of genes specified, our formula provides a sample size for a given number of true discoveries. Conclusion The calculated sample size is shown via simulations to provide an accurate number of true discoveries while controlling the FDR at the desired level.

  1. Designing image segmentation studies: Statistical power, sample size and reference standard quality.

    Science.gov (United States)

    Gibson, Eli; Hu, Yipeng; Huisman, Henkjan J; Barratt, Dean C

    2017-12-01

    Segmentation algorithms are typically evaluated by comparison to an accepted reference standard. The cost of generating accurate reference standards for medical image segmentation can be substantial. Since the study cost and the likelihood of detecting a clinically meaningful difference in accuracy both depend on the size and on the quality of the study reference standard, balancing these trade-offs supports the efficient use of research resources. In this work, we derive a statistical power calculation that enables researchers to estimate the appropriate sample size to detect clinically meaningful differences in segmentation accuracy (i.e. the proportion of voxels matching the reference standard) between two algorithms. Furthermore, we derive a formula to relate reference standard errors to their effect on the sample sizes of studies using lower-quality (but potentially more affordable and practically available) reference standards. The accuracy of the derived sample size formula was estimated through Monte Carlo simulation, demonstrating, with 95% confidence, a predicted statistical power within 4% of simulated values across a range of model parameters. This corresponds to sample size errors of less than 4 subjects and errors in the detectable accuracy difference less than 0.6%. The applicability of the formula to real-world data was assessed using bootstrap resampling simulations for pairs of algorithms from the PROMISE12 prostate MR segmentation challenge data set. The model predicted the simulated power for the majority of algorithm pairs within 4% for simulated experiments using a high-quality reference standard and within 6% for simulated experiments using a low-quality reference standard. A case study, also based on the PROMISE12 data, illustrates using the formulae to evaluate whether to use a lower-quality reference standard in a prostate segmentation study. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  2. "PowerUp"!: A Tool for Calculating Minimum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies

    Science.gov (United States)

    Dong, Nianbo; Maynard, Rebecca

    2013-01-01

    This paper and the accompanying tool are intended to complement existing supports for conducting power analysis tools by offering a tool based on the framework of Minimum Detectable Effect Sizes (MDES) formulae that can be used in determining sample size requirements and in estimating minimum detectable effect sizes for a range of individual- and…

  3. The role of the upper sample size limit in two-stage bioequivalence designs.

    Science.gov (United States)

    Karalis, Vangelis

    2013-11-01

    Two-stage designs (TSDs) are currently recommended by the regulatory authorities for bioequivalence (BE) assessment. The TSDs presented until now rely on an assumed geometric mean ratio (GMR) value of the BE metric in stage I in order to avoid inflation of type I error. In contrast, this work proposes a more realistic TSD design where sample re-estimation relies not only on the variability of stage I, but also on the observed GMR. In these cases, an upper sample size limit (UL) is introduced in order to prevent inflation of type I error. The aim of this study is to unveil the impact of UL on two TSD bioequivalence approaches which are based entirely on the interim results. Monte Carlo simulations were used to investigate several different scenarios of UL levels, within-subject variability, different starting number of subjects, and GMR. The use of UL leads to no inflation of type I error. As UL values increase, the % probability of declaring BE becomes higher. The starting sample size and the variability of the study affect type I error. Increased UL levels result in higher total sample sizes of the TSD which are more pronounced for highly variable drugs. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Sample size allocation for food item radiation monitoring and safety inspection.

    Science.gov (United States)

    Seto, Mayumi; Uriu, Koichiro

    2015-03-01

    The objective of this study is to identify a procedure for determining sample size allocation for food radiation inspections of more than one food item to minimize the potential risk to consumers of internal radiation exposure. We consider a simplified case of food radiation monitoring and safety inspection in which a risk manager is required to monitor two food items, milk and spinach, in a contaminated area. Three protocols for food radiation monitoring with different sample size allocations were assessed by simulating random sampling and inspections of milk and spinach in a conceptual monitoring site. Distributions of (131)I and radiocesium concentrations were determined in reference to (131)I and radiocesium concentrations detected in Fukushima prefecture, Japan, for March and April 2011. The results of the simulations suggested that a protocol that allocates sample size to milk and spinach based on the estimation of (131)I and radiocesium concentrations using the apparent decay rate constants sequentially calculated from past monitoring data can most effectively minimize the potential risks of internal radiation exposure. © 2014 Society for Risk Analysis.

  5. The effects of focused transducer geometry and sample size on the measurement of ultrasonic transmission properties

    Science.gov (United States)

    Atkins, T. J.; Humphrey, V. F.; Duck, F. A.; Tooley, M. A.

    2011-02-01

    The response of two coaxially aligned weakly focused ultrasonic transducers, typical of those employed for measuring the attenuation of small samples using the immersion method, has been investigated. The effects of the sample size on transmission measurements have been analyzed by integrating the sound pressure distribution functions of the radiator and receiver over different limits to determine the size of the region that contributes to the system response. The results enable the errors introduced into measurements of attenuation to be estimated as a function of sample size. A theoretical expression has been used to examine how the transducer separation affects the receiver output. The calculations are compared with an experimental study of the axial response of three unpaired transducers in water. The separation of each transducer pair giving the maximum response was determined, and compared with the field characteristics of the individual transducers. The optimum transducer separation, for accurate estimation of sample properties, was found to fall between the sum of the focal distances and the sum of the geometric focal lengths as this reduced diffraction errors.

  6. A simple method for estimating genetic diversity in large populations from finite sample sizes

    Directory of Open Access Journals (Sweden)

    Rajora Om P

    2009-12-01

    Full Text Available Abstract Background Sample size is one of the critical factors affecting the accuracy of the estimation of population genetic diversity parameters. Small sample sizes often lead to significant errors in determining the allelic richness, which is one of the most important and commonly used estimators of genetic diversity in populations. Correct estimation of allelic richness in natural populations is challenging since they often do not conform to model assumptions. Here, we introduce a simple and robust approach to estimate the genetic diversity in large natural populations based on the empirical data for finite sample sizes. Results We developed a non-linear regression model to infer genetic diversity estimates in large natural populations from finite sample sizes. The allelic richness values predicted by our model were in good agreement with those observed in the simulated data sets and the true allelic richness observed in the source populations. The model has been validated using simulated population genetic data sets with different evolutionary scenarios implied in the simulated populations, as well as large microsatellite and allozyme experimental data sets for four conifer species with contrasting patterns of inherent genetic diversity and mating systems. Our model was a better predictor for allelic richness in natural populations than the widely-used Ewens sampling formula, coalescent approach, and rarefaction algorithm. Conclusions Our regression model was capable of accurately estimating allelic richness in natural populations regardless of the species and marker system. This regression modeling approach is free from assumptions and can be widely used for population genetic and conservation applications.

  7. Limitations of mRNA amplification from small-size cell samples

    Directory of Open Access Journals (Sweden)

    Myklebost Ola

    2005-10-01

    Full Text Available Abstract Background Global mRNA amplification has become a widely used approach to obtain gene expression profiles from limited material. An important concern is the reliable reflection of the starting material in the results obtained. This is especially important with extremely low quantities of input RNA where stochastic effects due to template dilution may be present. This aspect remains under-documented in the literature, as quantitative measures of data reliability are most often lacking. To address this issue, we examined the sensitivity levels of each transcript in 3 different cell sample sizes. ANOVA analysis was used to estimate the overall effects of reduced input RNA in our experimental design. In order to estimate the validity of decreasing sample sizes, we examined the sensitivity levels of each transcript by applying a novel model-based method, TransCount. Results From expression data, TransCount provided estimates of absolute transcript concentrations in each examined sample. The results from TransCount were used to calculate the Pearson correlation coefficient between transcript concentrations for different sample sizes. The correlations were clearly transcript copy number dependent. A critical level was observed where stochastic fluctuations became significant. The analysis allowed us to pinpoint the gene specific number of transcript templates that defined the limit of reliability with respect to number of cells from that particular source. In the sample amplifying from 1000 cells, transcripts expressed with at least 121 transcripts/cell were statistically reliable and for 250 cells, the limit was 1806 transcripts/cell. Above these thresholds, correlation between our data sets was at acceptable values for reliable interpretation. Conclusion These results imply that the reliability of any amplification experiment must be validated empirically to justify that any gene exists in sufficient quantity in the input material. This

  8. Evaluating the performance of species richness estimators: sensitivity to sample grain size

    DEFF Research Database (Denmark)

    Hortal, Joaquín; Borges, Paulo A. V.; Gaspar, Clara

    2006-01-01

    scores in a number of estimators (the above-mentioned plus ICE, Chao2, Michaelis-Menten, Negative Exponential and Clench). The estimations from those four sample sizes were also highly correlated. 4.  Contrary to other studies, we conclude that most species richness estimators may be useful......Fifteen species richness estimators (three asymptotic based on species accumulation curves, 11 nonparametric, and one based in the species-area relationship) were compared by examining their performance in estimating the total species richness of epigean arthropods in the Azorean Laurisilva forests...... different sampling units on species richness estimations. 2.  Estimated species richness scores depended both on the estimator considered and on the grain size used to aggregate data. However, several estimators (ACE, Chao1, Jackknife1 and 2 and Bootstrap) were precise in spite of grain variations. Weibull...

  9. Influence of Sample Size of Polymer Materials on Aging Characteristics in the Salt Fog Test

    Science.gov (United States)

    Otsubo, Masahisa; Anami, Naoya; Yamashita, Seiji; Honda, Chikahisa; Takenouchi, Osamu; Hashimoto, Yousuke

    Polymer insulators have been used in worldwide because of some superior properties; light weight, high mechanical strength, good hydrophobicity etc., as compared with porcelain insulators. In this paper, effect of sample size on the aging characteristics in the salt fog test is examined. Leakage current was measured by using 100 MHz AD board or 100 MHz digital oscilloscope and separated three components as conductive current, corona discharge current and dry band arc discharge current by using FFT and the current differential method newly proposed. Each component cumulative charge was estimated automatically by a personal computer. As the results, when the sample size increased under the same average applied electric field, the peak values of leakage current and each component current increased. Especially, the cumulative charges and the arc discharge length of dry band arc discharge increased remarkably with the increase of gap length.

  10. Decision rules and associated sample size planning for regional approval utilizing multiregional clinical trials.

    Science.gov (United States)

    Chen, Xiaoyuan; Lu, Nelson; Nair, Rajesh; Xu, Yunling; Kang, Cailian; Huang, Qin; Li, Ning; Chen, Hongzhuan

    2012-09-01

    Multiregional clinical trials provide the potential to make safe and effective medical products simultaneously available to patients globally. As regulatory decisions are always made in a local context, this poses huge regulatory challenges. In this article we propose two conditional decision rules that can be used for medical product approval by local regulatory agencies based on the results of a multiregional clinical trial. We also illustrate sample size planning for such trials.

  11. Gridsampler – A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies

    OpenAIRE

    Mark Heckmann; Lukas Burk

    2017-01-01

    The repertory grid is a psychological data collection technique that is used to elicit qualitative data in the form of attributes as well as quantitative ratings. A common approach for evaluating multiple repertory grid data is sorting the elicited bipolar attributes (so called constructs) into mutually exclusive categories by means of content analysis. An important question when planning this type of study is determining the sample size needed to a) discover all attribute categories relevant...

  12. Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

    OpenAIRE

    Bruno Giacomini Sari; Alessandro Dal’Col Lúcio; Cinthya Souza Santana; Dionatan Ketzer Krysczun; André Luís Tischler; Lucas Drebes

    2017-01-01

    ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix b...

  13. Epidemiological Studies Based on Small Sample Sizes – A Statistician's Point of View

    OpenAIRE

    Ersbøll Annette; Ersbøll Bjarne

    2003-01-01

    We consider 3 basic steps in a study, which have relevance for the statistical analysis. They are: study design, data quality, and statistical analysis. While statistical analysis is often considered an important issue in the literature and the choice of statistical method receives much attention, less emphasis seems to be put on study design and necessary sample sizes. Finally, a very important step, namely assessment and validation of the quality of the data collected seems to be completel...

  14. Nintendo Wii Fit as an adjunct to physiotherapy following lower limb fractures: preliminary feasibility, safety and sample size considerations.

    Science.gov (United States)

    McPhail, S M; O'Hara, M; Gane, E; Tonks, P; Bullock-Saxton, J; Kuys, S S

    2016-06-01

    The Nintendo Wii Fit integrates virtual gaming with body movement, and may be suitable as an adjunct to conventional physiotherapy following lower limb fractures. This study examined the feasibility and safety of using the Wii Fit as an adjunct to outpatient physiotherapy following lower limb fractures, and reports sample size considerations for an appropriately powered randomised trial. Ambulatory patients receiving physiotherapy following a lower limb fracture participated in this study (n=18). All participants received usual care (individual physiotherapy). The first nine participants also used the Wii Fit under the supervision of their treating clinician as an adjunct to usual care. Adverse events, fracture malunion or exacerbation of symptoms were recorded. Pain, balance and patient-reported function were assessed at baseline and discharge from physiotherapy. No adverse events were attributed to either the usual care physiotherapy or Wii Fit intervention for any patient. Overall, 15 (83%) participants completed both assessments and interventions as scheduled. For 80% power in a clinical trial, the number of complete datasets required in each group to detect a small, medium or large effect of the Wii Fit at a post-intervention assessment was calculated at 175, 63 and 25, respectively. The Nintendo Wii Fit was safe and feasible as an adjunct to ambulatory physiotherapy in this sample. When considering a likely small effect size and the 17% dropout rate observed in this study, 211 participants would be required in each clinical trial group. A larger effect size or multiple repeated measures design would require fewer participants. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  15. Sample size calculations for randomised trials including both independent and paired data.

    Science.gov (United States)

    Yelland, Lisa N; Sullivan, Thomas R; Price, David J; Lee, Katherine J

    2017-04-15

    Randomised trials including a mixture of independent and paired data arise in many areas of health research, yet methods for determining the sample size for such trials are lacking. We derive design effects algebraically assuming clustering because of paired data will be taken into account in the analysis using generalised estimating equations with either an independence or exchangeable working correlation structure. Continuous and binary outcomes are considered, along with three different methods of randomisation: cluster randomisation, individual randomisation and randomisation to opposite treatment groups. The design effect is shown to depend on the intracluster correlation coefficient, proportion of observations belonging to a pair, working correlation structure, type of outcome and method of randomisation. The derived design effects are validated through simulation and example calculations are presented to illustrate their use in sample size planning. These design effects will enable appropriate sample size calculations to be performed for future randomised trials including both independent and paired data. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Estimating the Size of a Large Network and its Communities from a Random Sample

    CERN Document Server

    Chen, Lin; Crawford, Forrest W

    2016-01-01

    Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V;E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that correctly estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhausti...

  17. A Bayesian adaptive blinded sample size adjustment method for risk differences.

    Science.gov (United States)

    Hartley, Andrew Montgomery

    2015-01-01

    Adaptive sample size adjustment (SSA) for clinical trials consists of examining early subsets of on trial data to adjust estimates of sample size requirements. Blinded SSA is often preferred over unblinded SSA because it obviates many logistical complications of the latter and generally introduces less bias. On the other hand, current blinded SSA methods for binary data offer little to no new information about the treatment effect, ignore uncertainties associated with the population treatment proportions, and/or depend on enhanced randomization schemes that risk partial unblinding. I propose an innovative blinded SSA method for use when the primary analysis is a non-inferiority or superiority test regarding a risk difference. The method incorporates evidence about the treatment effect via the likelihood function of a mixture distribution. I compare the new method with an established one and with the fixed sample size study design, in terms of maximization of an expected utility function. The new method maximizes the expected utility better than do the comparators, under a range of assumptions. I illustrate the use of the proposed method with an example that incorporates a Bayesian hierarchical model. Lastly, I suggest topics for future study regarding the proposed methods. Copyright © 2015 John Wiley & Sons, Ltd.

  18. Sample Size and Probability Threshold Considerations with the Tailored Data Method.

    Science.gov (United States)

    Wyse, Adam E

    This article discusses sample size and probability threshold considerations in the use of the tailored data method with the Rasch model. In the tailored data method, one performs an initial Rasch analysis and then reanalyzes data after setting item responses to missing that are below a chosen probability threshold. A simple analytical formula is provided that can be used to check whether or not the application of the tailored data method with a chosen probability threshold will create situations in which the number of remaining item responses for the Rasch calibration will or will not meet minimum sample size requirements. The formula is illustrated using a real data example from a medical imaging licensure exam with several different probability thresholds. It is shown that as the probability threshold was increased more item responses were set to missing and the parameter standard errors and item difficulty estimates also tended to increase. It is suggested that some consideration should be given to the chosen probability threshold and how this interacts with potential examinee sample sizes and the accuracy of parameter estimates when calibrating data with the tailored data method.

  19. The influence of removing sizing on strength and stiffness of conventional and high modulus E-glass fibres

    DEFF Research Database (Denmark)

    Petersen, Helga Nørgaard; Kusano, Yukihiro; Brøndsted, Povl

    2016-01-01

    was removed by either burning at 565◦C or soxhlet extraction with acetone. It was found that the density and the stiffness increased after removing the sizing by the two removal treatments whereas the diameter did not change significantly. The strength of the fibres decreased after burning as the sizing...

  20. Cervical cancer incidence after normal cytological sample in routine screening using SurePath, ThinPrep, and conventional cytology: population based study

    NARCIS (Netherlands)

    K. Rozemeijer (Kirsten); S.K. Naber (Steffie); C. Penning (Corine); L.I.H. Overbeek (Lucy); C.W.N. Looman (Caspar); I.M.C.M. de Kok (Inge); S.M. Matthijsse (Suzette); M. Rebolj (Matejka); F.J. van Kemenade (Folkert); M. van Ballegooijen (Marjolein)

    2017-01-01

    markdownabstract#### Objective To compare the cumulative incidence of cervical cancer diagnosed within 72 months after a normal screening sample between conventional cytology and liquid based cytology tests SurePath and ThinPrep. #### Design Retrospective population based cohort

  1. Effect of crop management and sample year on abundance of soil bacterial communities in organic and conventional cropping systems.

    Science.gov (United States)

    Orr, C H; Stewart, C J; Leifert, C; Cooper, J M; Cummings, S P

    2015-07-01

    To identify changes in the bacterial community, at the phylum level brought about by varied crop management. Next-generation sequencing methods were used to compare the taxonomic structure of the bacterial community within 24 agricultural soils managed with either organic or conventional methods, over a 3-year period. Relative abundance of the proportionately larger phyla (e.g. Acidobacteria and Actinobacteria) was primarily affected by sample year rather than crop management. Changes of abundance in these phyla were correlated with changes in pH, organic nitrogen and soil basal respiration. Crop management affected some of the less dominant phyla (Chloroflexi, Nitrospirae, Gemmatimonadetes) which also correlated with pH and organic N. Soil diversity can vary with changing environmental variables and soil chemistry. If these factors remain constant, soil diversity can also remain constant even under changing land use. The impact of crop management on environmental variables must be considered when interpreting bacterial diversity studies in agricultural soils. Impact of land use change should always be monitored across different sampling time points. Further studies at the functional group level are necessary to assess whether management-induced changes in bacterial community structure are of biological and agronomic relevance. © 2015 The Society for Applied Microbiology.

  2. SAMPLE SIZE DETERMINATION IN NON-RADOMIZED SURVIVAL STUDIES WITH NON-CENSORED AND CENSORED DATA

    Directory of Open Access Journals (Sweden)

    S FAGHIHZADEH

    2003-06-01

    Full Text Available Introduction: In survival analysis, determination of sufficient sample size to achieve suitable statistical power is important .In both parametric and non-parametric methods of classic statistics, randomn selection of samples is a basic condition. practically, in most clinical trials and health surveys randomn allocation is impossible. Fixed - effect multiple linear regression analysis covers this need and this feature could be extended to survival regression analysis. This paper is the result of sample size determination in non-randomnized surval analysis with censored and non -censored data. Methods: In non-randomnized survival studies, linear regression with fixed -effect variable could be used. In fact such a regression is conditional expectation of dependent variable, conditioned on independent variable. Likelihood fuction with exponential hazard constructed by considering binary variable for allocation of each subject to one of two comparing groups, stating the variance of coefficient of fixed - effect independent variable by determination coefficient , sample size determination formulas are obtained with both censored and non-cencored data. So estimation of sample size is not based on the relation of a single independent variable but it could be attain the required power for a test adjusted for effect of the other explanatory covariates. Since the asymptotic distribution of the likelihood estimator of parameter is normal, we obtained the variance of the regression coefficient estimator formula then by stating the variance of regression coefficient of fixed-effect variable, by determination coefficient we derived formulas for determination of sample size in both censored and non-censored data. Results: In no-randomnized survival analysis ,to compare hazard rates of two groups without censored data, we obtained an estimation of determination coefficient ,risk ratio and proportion of membership to each group and their variances from

  3. Sample size determination for a t test given a t value from a previous study: A FORTRAN 77 program.

    Science.gov (United States)

    Gillett, R

    2001-11-01

    When uncertain about the magnitude of an effect, researchers commonly substitute in the standard sample-size-determination formula an estimate of effect size derived from a previous experiment. A problem with this approach is that the traditional sample-size-determination formula was not designed to deal with the uncertainty inherent in an effect-size estimate. Consequently, estimate-substitution in the traditional sample-size-determination formula can lead to a substantial loss of power. A method of sample-size determination designed to handle uncertainty in effect-size estimates is described. The procedure uses the t value and sample size from a previous study, which might be a pilot study or a related study in the same area, to establish a distribution of probable effect sizes. The sample size to be employed in the new study is that which supplies an expected power of the desired amount over the distribution of probable effect sizes. A FORTRAN 77 program is presented that permits swift calculation of sample size for a variety of t tests, including independent t tests, related t tests, t tests of correlation coefficients, and t tests of multiple regression b coefficients.

  4. Early detection of nonnative alleles in fish populations: When sample size actually matters

    Science.gov (United States)

    Croce, Patrick Della; Poole, Geoffrey C.; Payne, Robert A.; Gresswell, Bob

    2017-01-01

    Reliable detection of nonnative alleles is crucial for the conservation of sensitive native fish populations at risk of introgression. Typically, nonnative alleles in a population are detected through the analysis of genetic markers in a sample of individuals. Here we show that common assumptions associated with such analyses yield substantial overestimates of the likelihood of detecting nonnative alleles. We present a revised equation to estimate the likelihood of detecting nonnative alleles in a population with a given level of admixture. The new equation incorporates the effects of the genotypic structure of the sampled population and shows that conventional methods overestimate the likelihood of detection, especially when nonnative or F-1 hybrid individuals are present. Under such circumstances—which are typical of early stages of introgression and therefore most important for conservation efforts—our results show that improved detection of nonnative alleles arises primarily from increasing the number of individuals sampled rather than increasing the number of genetic markers analyzed. Using the revised equation, we describe a new approach to determining the number of individuals to sample and the number of diagnostic markers to analyze when attempting to monitor the arrival of nonnative alleles in native populations.

  5. Sample size and power determination when limited preliminary information is available

    Directory of Open Access Journals (Sweden)

    Christine E. McLaren

    2017-04-01

    Full Text Available Abstract Background We describe a novel strategy for power and sample size determination developed for studies utilizing investigational technologies with limited available preliminary data, specifically of imaging biomarkers. We evaluated diffuse optical spectroscopic imaging (DOSI, an experimental noninvasive imaging technique that may be capable of assessing changes in mammographic density. Because there is significant evidence that tamoxifen treatment is more effective at reducing breast cancer risk when accompanied by a reduction of breast density, we designed a study to assess the changes from baseline in DOSI imaging biomarkers that may reflect fluctuations in breast density in premenopausal women receiving tamoxifen. Method While preliminary data demonstrate that DOSI is sensitive to mammographic density in women about to receive neoadjuvant chemotherapy for breast cancer, there is no information on DOSI in tamoxifen treatment. Since the relationship between magnetic resonance imaging (MRI and DOSI has been established in previous studies, we developed a statistical simulation approach utilizing information from an investigation of MRI assessment of breast density in 16 women before and after treatment with tamoxifen to estimate the changes in DOSI biomarkers due to tamoxifen. Results Three sets of 10,000 pairs of MRI breast density data with correlation coefficients of 0.5, 0.8 and 0.9 were simulated and generated and were used to simulate and generate a corresponding 5,000,000 pairs of DOSI values representing water, ctHHB, and lipid. Minimum sample sizes needed per group for specified clinically-relevant effect sizes were obtained. Conclusion The simulation techniques we describe can be applied in studies of other experimental technologies to obtain the important preliminary data to inform the power and sample size calculations.

  6. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

    Science.gov (United States)

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-12-08

    Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

  7. Parameters in the estimation of the most suitable F2 population size in conventional maize (Zea mays L. breeding programs

    Directory of Open Access Journals (Sweden)

    Delić Nenad

    2010-01-01

    Full Text Available The objective of the present study was to observe differences among four sizes of the F2 populations (100, 200, 300 and 500 plants on the basis of test-crosses for grain yield according to the average values of the populations, genetic and phenotypic variances, genotypic and phenotypic coefficients of variations and broad-sense heritability. The values of genetic variance did not significantly differ over population sizes according to all possible comparisons, including the comparison of values obtained for the phenotypic variance. Furthermore, the values of broadsense heritability (67.8%-69% did not significantly vary over different F2 population sizes. Genetic variability of the observed progenies, as a principal prerequisite of successful selection, was at the satisfactory level in all population sizes.

  8. Forest inventory using multistage sampling with probability proportional to size. [Brazil

    Science.gov (United States)

    Parada, N. D. J. (Principal Investigator); Lee, D. C. L.; Hernandezfilho, P.; Shimabukuro, Y. E.; Deassis, O. R.; Demedeiros, J. S.

    1984-01-01

    A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.

  9. Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

    Science.gov (United States)

    Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

    2017-06-30

    Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  10. Relative power and sample size analysis on gene expression profiling data

    Directory of Open Access Journals (Sweden)

    den Dunnen JT

    2009-09-01

    Full Text Available Abstract Background With the increasing number of expression profiling technologies, researchers today are confronted with choosing the technology that has sufficient power with minimal sample size, in order to reduce cost and time. These depend on data variability, partly determined by sample type, preparation and processing. Objective measures that help experimental design, given own pilot data, are thus fundamental. Results Relative power and sample size analysis were performed on two distinct data sets. The first set consisted of Affymetrix array data derived from a nutrigenomics experiment in which weak, intermediate and strong PPARα agonists were administered to wild-type and PPARα-null mice. Our analysis confirms the hierarchy of PPARα-activating compounds previously reported and the general idea that larger effect sizes positively contribute to the average power of the experiment. A simulation experiment was performed that mimicked the effect sizes seen in the first data set. The relative power was predicted but the estimates were slightly conservative. The second, more challenging, data set describes a microarray platform comparison study using hippocampal δC-doublecortin-like kinase transgenic mice that were compared to wild-type mice, which was combined with results from Solexa/Illumina deep sequencing runs. As expected, the choice of technology greatly influences the performance of the experiment. Solexa/Illumina deep sequencing has the highest overall power followed by the microarray platforms Agilent and Affymetrix. Interestingly, Solexa/Illumina deep sequencing displays comparable power across all intensity ranges, in contrast with microarray platforms that have decreased power in the low intensity range due to background noise. This means that deep sequencing technology is especially more powerful in detecting differences in the low intensity range, compared to microarray platforms. Conclusion Power and sample size analysis

  11. Prediction accuracy of a sample-size estimation method for ROC studies.

    Science.gov (United States)

    Chakraborty, Dev P

    2010-05-01

    Sample-size estimation is an important consideration when planning a receiver operating characteristic (ROC) study. The aim of this work was to assess the prediction accuracy of a sample-size estimation method using the Monte Carlo simulation method. Two ROC ratings simulators characterized by low reader and high case variabilities (LH) and high reader and low case variabilities (HL) were used to generate pilot data sets in two modalities. Dorfman-Berbaum-Metz multiple-reader multiple-case (DBM-MRMC) analysis of the ratings yielded estimates of the modality-reader, modality-case, and error variances. These were input to the Hillis-Berbaum (HB) sample-size estimation method, which predicted the number of cases needed to achieve 80% power for 10 readers and an effect size of 0.06 in the pivotal study. Predictions that generalized to readers and cases (random-all), to cases only (random-cases), and to readers only (random-readers) were generated. A prediction-accuracy index defined as the probability that any single prediction yields true power in the 75%-90% range was used to assess the HB method. For random-case generalization, the HB-method prediction-accuracy was reasonable, approximately 50% for five readers and 100 cases in the pilot study. Prediction-accuracy was generally higher under LH conditions than under HL conditions. Under ideal conditions (many readers in the pilot study) the DBM-MRMC-based HB method overestimated the number of cases. The overestimates could be explained by the larger modality-reader variance estimates when reader variability was large (HL). The largest benefit of increasing the number of readers in the pilot study was realized for LH, where 15 readers were enough to yield prediction accuracy >50% under all generalization conditions, but the benefit was lesser for HL where prediction accuracy was approximately 36% for 15 readers under random-all and random-reader conditions. The HB method tends to overestimate the number of cases

  12. Relative power and sample size analysis on gene expression profiling data

    Science.gov (United States)

    van Iterson, M; 't Hoen, PAC; Pedotti, P; Hooiveld, GJEJ; den Dunnen, JT; van Ommen, GJB; Boer, JM; Menezes, RX

    2009-01-01

    Background With the increasing number of expression profiling technologies, researchers today are confronted with choosing the technology that has sufficient power with minimal sample size, in order to reduce cost and time. These depend on data variability, partly determined by sample type, preparation and processing. Objective measures that help experimental design, given own pilot data, are thus fundamental. Results Relative power and sample size analysis were performed on two distinct data sets. The first set consisted of Affymetrix array data derived from a nutrigenomics experiment in which weak, intermediate and strong PPARα agonists were administered to wild-type and PPARα-null mice. Our analysis confirms the hierarchy of PPARα-activating compounds previously reported and the general idea that larger effect sizes positively contribute to the average power of the experiment. A simulation experiment was performed that mimicked the effect sizes seen in the first data set. The relative power was predicted but the estimates were slightly conservative. The second, more challenging, data set describes a microarray platform comparison study using hippocampal δC-doublecortin-like kinase transgenic mice that were compared to wild-type mice, which was combined with results from Solexa/Illumina deep sequencing runs. As expected, the choice of technology greatly influences the performance of the experiment. Solexa/Illumina deep sequencing has the highest overall power followed by the microarray platforms Agilent and Affymetrix. Interestingly, Solexa/Illumina deep sequencing displays comparable power across all intensity ranges, in contrast with microarray platforms that have decreased power in the low intensity range due to background noise. This means that deep sequencing technology is especially more powerful in detecting differences in the low intensity range, compared to microarray platforms. Conclusion Power and sample size analysis based on pilot data give

  13. Generalized sample size determination formulas for experimental research with hierarchical data.

    Science.gov (United States)

    Usami, Satoshi

    2014-06-01

    Hierarchical data sets arise when the data for lower units (e.g., individuals such as students, clients, and citizens) are nested within higher units (e.g., groups such as classes, hospitals, and regions). In data collection for experimental research, estimating the required sample size beforehand is a fundamental question for obtaining sufficient statistical power and precision of the focused parameters. The present research extends previous research from Heo and Leon (2008) and Usami (2011b), by deriving closed-form formulas for determining the required sample size to test effects in experimental research with hierarchical data, and by focusing on both multisite-randomized trials (MRTs) and cluster-randomized trials (CRTs). These formulas consider both statistical power and the width of the confidence interval of a standardized effect size, on the basis of estimates from a random-intercept model for three-level data that considers both balanced and unbalanced designs. These formulas also address some important results, such as the lower bounds of the needed units at the highest levels.

  14. Back to basics: explaining sample size in outcome trials, are statisticians doing a thorough job?

    Science.gov (United States)

    Carroll, Kevin J

    2009-01-01

    Time to event outcome trials in clinical research are typically large, expensive and high-profile affairs. Such trials are commonplace in oncology and cardiovascular therapeutic areas but are also seen in other areas such as respiratory in indications like chronic obstructive pulmonary disease. Their progress is closely monitored and results are often eagerly awaited. Once available, the top line result is often big news, at least within the therapeutic area in which it was conducted, and the data are subsequently fully scrutinized in a series of high-profile publications. In such circumstances, the statistician has a vital role to play in the design, conduct, analysis and reporting of the trial. In particular, in drug development it is incumbent on the statistician to ensure at the outset that the sizing of the trial is fully appreciated by their medical, and other non-statistical, drug development team colleagues and that the risk of delivering a statistically significant but clinically unpersuasive result is minimized. The statistician also has a key role in advising the team when, early in the life of an outcomes trial, a lower than anticipated event rate appears to be emerging. This paper highlights some of the important features relating to outcome trial sample sizing and makes a number of simple recommendations aimed at ensuring a better, common understanding of the interplay between sample size and power and the final result required to provide a statistically positive and clinically persuasive outcome. Copyright (c) 2009 John Wiley & Sons, Ltd.

  15. Adjustable virtual pore-size filter for automated sample preparation using acoustic radiation force

    Energy Technology Data Exchange (ETDEWEB)

    Jung, B; Fisher, K; Ness, K; Rose, K; Mariella, R

    2008-05-22

    We present a rapid and robust size-based separation method for high throughput microfluidic devices using acoustic radiation force. We developed a finite element modeling tool to predict the two-dimensional acoustic radiation force field perpendicular to the flow direction in microfluidic devices. Here we compare the results from this model with experimental parametric studies including variations of the PZT driving frequencies and voltages as well as various particle sizes and compressidensities. These experimental parametric studies also provide insight into the development of an adjustable 'virtual' pore-size filter as well as optimal operating conditions for various microparticle sizes. We demonstrated the separation of Saccharomyces cerevisiae and MS2 bacteriophage using acoustic focusing. The acoustic radiation force did not affect the MS2 viruses, and their concentration profile remained unchanged. With optimized design of our microfluidic flow system we were able to achieve yields of > 90% for the MS2 with > 80% of the S. cerevisiae being removed in this continuous-flow sample preparation device.

  16. Effect of sample size on the fluid flow through a single fractured granitoid

    Directory of Open Access Journals (Sweden)

    Kunal Kumar Singh

    2016-06-01

    Full Text Available Most of deep geological engineered structures, such as rock caverns, nuclear waste disposal repositories, metro rail tunnels, multi-layer underground parking, are constructed within hard crystalline rocks because of their high quality and low matrix permeability. In such rocks, fluid flows mainly through fractures. Quantification of fractures along with the behavior of the fluid flow through them, at different scales, becomes quite important. Earlier studies have revealed the influence of sample size on the confining stress–permeability relationship and it has been demonstrated that permeability of the fractured rock mass decreases with an increase in sample size. However, most of the researchers have employed numerical simulations to model fluid flow through the fracture/fracture network, or laboratory investigations on intact rock samples with diameter ranging between 38 mm and 45 cm and the diameter-to-length ratio of 1:2 using different experimental methods. Also, the confining stress, σ3, has been considered to be less than 30 MPa and the effect of fracture roughness has been ignored. In the present study, an extension of the previous studies on “laboratory simulation of flow through single fractured granite” was conducted, in which consistent fluid flow experiments were performed on cylindrical samples of granitoids of two different sizes (38 mm and 54 mm in diameters, containing a “rough walled single fracture”. These experiments were performed under varied confining pressure (σ3 = 5–40 MPa, fluid pressure (fp ≤ 25 MPa, and fracture roughness. The results indicate that a nonlinear relationship exists between the discharge, Q, and the effective confining pressure, σeff., and Q decreases with an increase in σeff.. Also, the effects of sample size and fracture roughness do not persist when σeff. ≥ 20 MPa. It is expected that such a study will be quite useful in correlating and extrapolating the laboratory

  17. Reference calculation of light propagation between parallel planes of different sizes and sampling rates.

    Science.gov (United States)

    Lobaz, Petr

    2011-01-03

    The article deals with a method of calculation of off-axis light propagation between parallel planes using discretization of the Rayleigh-Sommerfeld integral and its implementation by fast convolution. It analyses zero-padding in case of different plane sizes. In case of memory restrictions, it suggests splitting the calculation into tiles and shows that splitting leads to a faster calculation when plane sizes are a lot different. Next, it suggests how to calculate propagation in case of different sampling rates by splitting planes into interleaved tiles and shows this to be faster than zero-padding and direct calculation. Neither the speedup nor memory-saving method decreases accuracy; the aim of the proposed method is to provide reference data that can be compared to the results of faster and less precise methods.

  18. Sample-size calculations for multi-group comparison in population pharmacokinetic experiments.

    Science.gov (United States)

    Ogungbenro, Kayode; Aarons, Leon

    2010-01-01

    This paper describes an approach for calculating sample size for population pharmacokinetic experiments that involve hypothesis testing based on multi-group comparison detecting the difference in parameters between groups under mixed-effects modelling. This approach extends what has been described for generalized linear models and nonlinear population pharmacokinetic models that involve only binary covariates to more complex nonlinear population pharmacokinetic models. The structural nonlinear model is linearized around the random effects to obtain the marginal model and the hypothesis testing involving model parameters is based on Wald's test. This approach provides an efficient and fast method for calculating sample size for hypothesis testing in population pharmacokinetic models. The approach can also handle different design problems such as unequal allocation of subjects to groups and unbalanced sampling times between and within groups. The results obtained following application to a one compartment intravenous bolus dose model that involved three different hypotheses under different scenarios showed good agreement between the power obtained from NONMEM simulations and nominal power. Copyright © 2009 John Wiley & Sons, Ltd.

  19. Autoregressive Prediction with Rolling Mechanism for Time Series Forecasting with Small Sample Size

    Directory of Open Access Journals (Sweden)

    Zhihua Wang

    2014-01-01

    Full Text Available Reasonable prediction makes significant practical sense to stochastic and unstable time series analysis with small or limited sample size. Motivated by the rolling idea in grey theory and the practical relevance of very short-term forecasting or 1-step-ahead prediction, a novel autoregressive (AR prediction approach with rolling mechanism is proposed. In the modeling procedure, a new developed AR equation, which can be used to model nonstationary time series, is constructed in each prediction step. Meanwhile, the data window, for the next step ahead forecasting, rolls on by adding the most recent derived prediction result while deleting the first value of the former used sample data set. This rolling mechanism is an efficient technique for its advantages of improved forecasting accuracy, applicability in the case of limited and unstable data situations, and requirement of little computational effort. The general performance, influence of sample size, nonlinearity dynamic mechanism, and significance of the observed trends, as well as innovation variance, are illustrated and verified with Monte Carlo simulations. The proposed methodology is then applied to several practical data sets, including multiple building settlement sequences and two economic series.

  20. Comparison of Unsatisfactory Samples from Conventional Smear versus Liquid-Based Cytology in Uterine Cervical Cancer Screening Test

    Directory of Open Access Journals (Sweden)

    Hoiseon Jeong

    2017-05-01

    Full Text Available Background Cervical cytology for uterine cervical cancer screening has transitioned from conventional smear (CS to liquid-based cytology (LBC, which has many advantages. The aim of this study was to compare the proportion of unsatisfactory specimens from CS versus LBC at multiple institutions including general hospitals and commercial laboratories. Methods Each participating institution provided a minimum of 500 Papanicolaou (Pap test results for analysis. Pap tests were classified according to the participating institution (commercial laboratory or general hospital and the processing method (CS, ThinPrep, SurePath, or CellPrep. The causes of unsatisfactory results were classified as technical problems, scant cellularity, or complete obscuring factors. Results A total of 38,956 Pap test results from eight general hospitals and three commercial laboratories were analyzed. The mean unsatisfactory rate of LBC was significantly lower than that of CS (1.26% and 3.31%, p = .018. In the LBC method, samples from general hospitals had lower unsatisfactory rates than those from commercial laboratories (0.65% vs 2.89%, p = .006. The reasons for unsatisfactory results were heterogeneous in CS. On the other hand, 66.2% of unsatisfactory results in LBC were due to the scant cellularity. Conclusions Unsatisfactory rate of cervical cancer screening test results varies according to the institution and the processing method. LBC has a significantly lower unsatisfactory rate than CS.

  1. Conventional liquid-based techniques versus Cytyc Thinprep® processing of urinary samples: a qualitative approach

    Directory of Open Access Journals (Sweden)

    Hutin Karine

    2005-10-01

    Full Text Available Abstract Background The aim of our study was to objectively compare Cytyc Thinprep® and other methods of obtaining thin layer cytologic preparations (cytocentrifugation, direct smearing and Millipore® filtration in urine cytopathology. Methods Thinprep slides were compared to direct smears in 79 cases. Cytocentrifugation carried out with the Thermo Shandon Cytospin® 4 was compared to Thinprep in 106 cases, and comparison with Millipore filtration followed by blotting was obtained in 22 cases. Quality was assessed by scoring cellularity, fixation, red blood cells, leukocytes and nuclear abnormalities. Results The data show that 1 smearing allows good overall results to be obtained, 2 Cytocentrifugation with reusable TPX® chambers should be avoided, 3 Cytocentrifugation using disposable chambers (Cytofunnels® or Megafunnel® chambers gives excellent results equalling or surpassing Thinprep and 4 Millipore filtration should be avoided, owing to its poor global quality. Despite differences in quality, the techniques studied have no impact on the diagnostic accuracy as evaluated by the rate of abnormalities. Conclusion We conclude that conventional methods such as cytocentrifugation remain the most appropriate ones for current treatment of urinary samples. Cytyc Thinprep processing, owing to its cost, could be used essentially for cytology-based molecular studies.

  2. Dealing with varying detection probability, unequal sample sizes and clumped distributions in count data.

    Directory of Open Access Journals (Sweden)

    D Johan Kotze

    Full Text Available Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly. For example, when effort varies in space and/or time it becomes necessary to take variation in detectability into account when data are analyzed. We demonstrate the importance of incorporating seasonality into the analysis of data with unequal sample sizes due to lost traps at a particular density of a species. A case study of count data was simulated using a spring-active carabid beetle. Traps were 'lost' randomly during high beetle activity in high abundance sites and during low beetle activity in low abundance sites. Five different models were fitted to datasets with different levels of loss. If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under- or overestimated the true effect size. Results did not improve when seasonality and number of trapping days were included in these models as offset terms, but only performed well when the response variable was specified as following a negative binomial distribution. Finally, if seasonal variation of a species is unknown, which is often the case, seasonality can be added as a free factor, resulting in well-performing negative binomial models. Based on these results we recommend (a add sampling effort (number of trapping days in our example to the models as an offset term, (b if precise information is available on seasonal variation in detectability of a study object, add seasonality to the models as an offset term; (c if information on seasonal variation in detectability is inadequate, add seasonality as a free factor; and (d specify the response variable of count data as following a negative binomial or over-dispersed Poisson distribution.

  3. High-dimensional, massive sample-size Cox proportional hazards regression for survival analysis.

    Science.gov (United States)

    Mittal, Sushil; Madigan, David; Burd, Randall S; Suchard, Marc A

    2014-04-01

    Survival analysis endures as an old, yet active research field with applications that spread across many domains. Continuing improvements in data acquisition techniques pose constant challenges in applying existing survival analysis methods to these emerging data sets. In this paper, we present tools for fitting regularized Cox survival analysis models on high-dimensional, massive sample-size (HDMSS) data using a variant of the cyclic coordinate descent optimization technique tailored for the sparsity that HDMSS data often present. Experiments on two real data examples demonstrate that efficient analyses of HDMSS data using these tools result in improved predictive performance and calibration.

  4. Magnetic response and critical current properties of mesoscopic-size YBCO superconducting samples

    Energy Technology Data Exchange (ETDEWEB)

    Lisboa-Filho, P N [UNESP - Universidade Estadual Paulista, Grupo de Materiais Avancados, Departamento de Fisica, Bauru (Brazil); Deimling, C V; Ortiz, W A, E-mail: plisboa@fc.unesp.b [Grupo de Supercondutividade e Magnetismo, Departamento de Fisica, Universidade Federal de Sao Carlos, Sao Carlos (Brazil)

    2010-01-15

    In this contribution superconducting specimens of YBa{sub 2}Cu{sub 3}O{sub 7-{delta}} were synthesized by a modified polymeric precursor method, yielding a ceramic powder with particles of mesoscopic-size. Samples of this powder were then pressed into pellets and sintered under different conditions. The critical current density was analyzed by isothermal AC-susceptibility measurements as a function of the excitation field, as well as with isothermal DC-magnetization runs at different values of the applied field. Relevant features of the magnetic response could be associated to the microstructure of the specimens and, in particular, to the superconducting intra- and intergranular critical current properties.

  5. Determining the sample size required to establish whether a medical device is non-inferior to an external benchmark

    National Research Council Canada - National Science Library

    Adrian Sayers; Michael J Crowther; Andrew Judge; Michael R Whitehouse; Ashley W Blom

    2017-01-01

    ... to the performance benchmark of interest. We aim to describe the methods and sample size required to conduct a one-sample non-inferiority study of a medical device for the purposes of benchmarking...

  6. Characteristics of competitive adsorption between 2-methylisoborneol and natural organic matter on superfine and conventionally sized powdered activated carbons.

    Science.gov (United States)

    Matsui, Yoshihiko; Yoshida, Tomoaki; Nakao, Soichi; Knappe, Detlef R U; Matsushita, Taku

    2012-10-01

    When treating water with activated carbon, natural organic matter (NOM) is not only a target for adsorptive removal but also an inhibitory substance that reduces the removal efficiency of trace compounds, such as 2-methylisoborneol (MIB), through adsorption competition. Recently, superfine (submicron-sized) activated carbon (SPAC) was developed by wet-milling commercially available powdered activated carbon (PAC) to a smaller particle size. It was reported that SPAC has a larger NOM adsorption capacity than PAC because NOM mainly adsorbs close to the external adsorbent particle surface (shell adsorption mechanism). Thus, SPAC with its larger specific external surface area can adsorb more NOM than PAC. The effect of higher NOM uptake on the adsorptive removal of MIB has, however, not been investigated. Results of this study show that adsorption competition between NOM and MIB did not increase when NOM uptake increased due to carbon size reduction; i.e., the increased NOM uptake by SPAC did not result in a decrease in MIB adsorption capacity beyond that obtained as a result of NOM adsorption by PAC. A simple estimation method for determining the adsorbed amount of competing NOM (NOM that reduces MIB adsorption) is presented based on the simplified equivalent background compound (EBC) method. Furthermore, the mechanism of adsorption competition is discussed based on results obtained with the simplified EBC method and the shell adsorption mechanism. Competing NOM, which likely comprises a small portion of NOM, adsorbs in internal pores of activated carbon particles as MIB does, thereby reducing the MIB adsorption capacity to a similar extent regardless of adsorbent particle size. SPAC application can be advantageous because enhanced NOM removal does not translate into less effective removal of MIB. Molecular size distribution data of NOM suggest that the competing NOM has a molecular weight similar to that of the target compound. Copyright © 2012 Elsevier Ltd. All

  7. Power and sample size calculation for paired recurrent events data based on robust nonparametric tests.

    Science.gov (United States)

    Su, Pei-Fang; Chung, Chia-Hua; Wang, Yu-Wen; Chi, Yunchan; Chang, Ying-Ju

    2017-05-20

    The purpose of this paper is to develop a formula for calculating the required sample size for paired recurrent events data. The developed formula is based on robust non-parametric tests for comparing the marginal mean function of events between paired samples. This calculation can accommodate the associations among a sequence of paired recurrent event times with a specification of correlated gamma frailty variables for a proportional intensity model. We evaluate the performance of the proposed method with comprehensive simulations including the impacts of paired correlations, homogeneous or nonhomogeneous processes, marginal hazard rates, censoring rate, accrual and follow-up times, as well as the sensitivity analysis for the assumption of the frailty distribution. The use of the formula is also demonstrated using a premature infant study from the neonatal intensive care unit of a tertiary center in southern Taiwan. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  8. Sample size for regression analyses of theory of planned behaviour studies: case of prescribing in general practice.

    Science.gov (United States)

    Rashidian, Arash; Miles, Jeremy; Russell, Daphne; Russell, Ian

    2006-11-01

    Interest has been growing in the use of the theory of planned behaviour (TBP) in health services research. The sample sizes range from less than 50 to more than 750 in published TPB studies without sample size calculations. We estimate the sample size for a multi-stage random survey of prescribing intention and actual prescribing for asthma in British general practice. To our knowledge, this is the first systematic attempt to determine sample size for a TPB survey. We use two different approaches: reported values of regression models' goodness-of-fit (the lambda method) and zero-order correlations (the variance inflation factor or VIF method). Intra-cluster correlation coefficient (ICC) is estimated and a socioeconomic variable is used for stratification. We perform sensitivity analysis to estimate the effects of our decisions on final sample size. The VIF method is more sensitive to the requirements of a TPB study. Given a correlation of .25 between intention and behaviour, and of .4 between intention and perceived behavioural control, the proposed sample size is 148. We estimate the ICC for asthma prescribing to be around 0.07. If 10 general practitioners were sampled per cluster, the sample size would be 242. It is feasible to perform sophisticated sample size calculations for a TPB study. The VIF is the appropriate method. Our approach can be used with adjustments in other settings and for other regression models.

  9. Elemental analysis of size-fractionated particulate matter sampled in Goeteborg, Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, Annemarie [Department of Chemistry, Atmospheric Science, Goeteborg University, SE-412 96 Goeteborg (Sweden)], E-mail: wagnera@chalmers.se; Boman, Johan [Department of Chemistry, Atmospheric Science, Goeteborg University, SE-412 96 Goeteborg (Sweden); Gatari, Michael J. [Institute of Nuclear Science and Technology, University of Nairobi, P.O. Box 30197-00100, Nairobi (Kenya)

    2008-12-15

    The aim of the study was to investigate the mass distribution of trace elements in aerosol samples collected in the urban area of Goeteborg, Sweden, with special focus on the impact of different air masses and anthropogenic activities. Three measurement campaigns were conducted during December 2006 and January 2007. A PIXE cascade impactor was used to collect particulate matter in 9 size fractions ranging from 16 to 0.06 {mu}m aerodynamic diameter. Polished quartz carriers were chosen as collection substrates for the subsequent direct analysis by TXRF. To investigate the sources of the analyzed air masses, backward trajectories were calculated. Our results showed that diurnal sampling was sufficient to investigate the mass distribution for Br, Ca, Cl, Cu, Fe, K, Sr and Zn, whereas a 5-day sampling period resulted in additional information on mass distribution for Cr and S. Unimodal mass distributions were found in the study area for the elements Ca, Cl, Fe and Zn, whereas the distributions for Br, Cu, Cr, K, Ni and S were bimodal, indicating high temperature processes as source of the submicron particle components. The measurement period including the New Year firework activities showed both an extensive increase in concentrations as well as a shift to the submicron range for K and Sr, elements that are typically found in fireworks. Further research is required to validate the quantification of trace elements directly collected on sample carriers.

  10. Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

    Science.gov (United States)

    Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

    2017-09-27

    For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Strategies for informed sample size reduction in adaptive controlled clinical trials

    Science.gov (United States)

    Arandjelović, Ognjen

    2017-12-01

    Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. The main goal is to make the process of introducing new medical interventions to patients more efficient. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper, we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment, i.e. by reducing the number of trial participants in a statistically informed manner. Our key idea is to select the sample subset for removal in a manner which minimizes the associated loss of information. We formalize this notion and describe three algorithms which approach the problem in different ways, respectively, using (i) repeated random draws, (ii) a genetic algorithm, and (iii) what we term pair-wise sample compatibilities. Experiments on simulated data demonstrate the effectiveness of all three approaches, with a consistently superior performance exhibited by the pair-wise sample compatibilities-based method.

  12. Sample size calculations for micro-randomized trials in mHealth.

    Science.gov (United States)

    Liao, Peng; Klasnja, Predrag; Tewari, Ambuj; Murphy, Susan A

    2016-05-30

    The use and development of mobile interventions are experiencing rapid growth. In "just-in-time" mobile interventions, treatments are provided via a mobile device, and they are intended to help an individual make healthy decisions 'in the moment,' and thus have a proximal, near future impact. Currently, the development of mobile interventions is proceeding at a much faster pace than that of associated data science methods. A first step toward developing data-based methods is to provide an experimental design for testing the proximal effects of these just-in-time treatments. In this paper, we propose a 'micro-randomized' trial design for this purpose. In a micro-randomized trial, treatments are sequentially randomized throughout the conduct of the study, with the result that each participant may be randomized at the 100s or 1000s of occasions at which a treatment might be provided. Further, we develop a test statistic for assessing the proximal effect of a treatment as well as an associated sample size calculator. We conduct simulation evaluations of the sample size calculator in various settings. Rules of thumb that might be used in designing a micro-randomized trial are discussed. This work is motivated by our collaboration on the HeartSteps mobile application designed to increase physical activity. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  13. Power and sample size determination for measures of environmental impact in aquatic systems

    Energy Technology Data Exchange (ETDEWEB)

    Ammann, L.P. [Univ. of Texas, Richardson, TX (United States); Dickson, K.L.; Waller, W.T.; Kennedy, J.H. [Univ. of North Texas, Denton, TX (United States); Mayer, F.L.; Lewis, M. [Environmental Protection Agency, Gulf Breeze, FL (United States)

    1994-12-31

    To effectively monitor the status of various freshwater and estuarine ecological systems, it is necessary to understand the statistical power associated with the measures of ecological health that are appropriate for each system. These power functions can then be used to determine sample sizes that are required to attain targeted change detection likelihoods. A number of different measures have been proposed and are used for such monitoring. these include diversity and evenness indices, richness, and organisms counts. Power functions can be estimated when preliminary or historical data are available for the region and system of interest. Unfortunately, there are a number of problems associated with the computation of power functions and sample sizes for these measures. These problems include the presence of outliers, co-linearity among the variables, and non-normality of count data. The problems, and appropriate methods to compute the power functions, for each of the commonly employed measures of ecological health will be discussed. In addition, the relationship between power and the level of taxonomic classification used to compute the measures of diversity, evenness, richness, and organism counts will be discussed. Methods for computation of the power functions will be illustrated using data sets from previous EPA studies.

  14. On tests of treatment-covariate interactions: An illustration of appropriate power and sample size calculations.

    Science.gov (United States)

    Shieh, Gwowen

    2017-01-01

    The appraisals of treatment-covariate interaction have theoretical and substantial implications in all scientific fields. Methodologically, the detection of interaction between categorical treatment levels and continuous covariate variables is analogous to the homogeneity of regression slopes test in the context of ANCOVA. A fundamental assumption of ANCOVA is that the regression slopes associating the response variable with the covariate variable are presumed constant across treatment groups. The validity of homogeneous regression slopes accordingly is the most essential concern in traditional ANCOVA and inevitably determines the practical usefulness of research findings. In view of the limited results in current literature, this article aims to present power and sample size procedures for tests of heterogeneity between two regression slopes with particular emphasis on the stochastic feature of covariate variables. Theoretical implications and numerical investigations are presented to explicate the utility and advantage for accommodating covariate properties. The exact approach has the distinct feature of accommodating the full distributional properties of normal covariates whereas the simplified approximate methods only utilize the partial information of covariate variances. According to the overall accuracy and robustness, the exact approach is recommended over the approximate methods as a reliable tool in practical applications. The suggested power and sample size calculations can be implemented with the supplemental SAS and R programs.

  15. On tests of treatment-covariate interactions: An illustration of appropriate power and sample size calculations.

    Directory of Open Access Journals (Sweden)

    Gwowen Shieh

    Full Text Available The appraisals of treatment-covariate interaction have theoretical and substantial implications in all scientific fields. Methodologically, the detection of interaction between categorical treatment levels and continuous covariate variables is analogous to the homogeneity of regression slopes test in the context of ANCOVA. A fundamental assumption of ANCOVA is that the regression slopes associating the response variable with the covariate variable are presumed constant across treatment groups. The validity of homogeneous regression slopes accordingly is the most essential concern in traditional ANCOVA and inevitably determines the practical usefulness of research findings. In view of the limited results in current literature, this article aims to present power and sample size procedures for tests of heterogeneity between two regression slopes with particular emphasis on the stochastic feature of covariate variables. Theoretical implications and numerical investigations are presented to explicate the utility and advantage for accommodating covariate properties. The exact approach has the distinct feature of accommodating the full distributional properties of normal covariates whereas the simplified approximate methods only utilize the partial information of covariate variances. According to the overall accuracy and robustness, the exact approach is recommended over the approximate methods as a reliable tool in practical applications. The suggested power and sample size calculations can be implemented with the supplemental SAS and R programs.

  16. Sample Size Considerations of Prediction-Validation Methods in High-Dimensional Data for Survival Outcomes

    Science.gov (United States)

    Pang, Herbert; Jung, Sin-Ho

    2013-01-01

    A variety of prediction methods are used to relate high-dimensional genome data with a clinical outcome using a prediction model. Once a prediction model is developed from a data set, it should be validated using a resampling method or an independent data set. Although the existing prediction methods have been intensively evaluated by many investigators, there has not been a comprehensive study investigating the performance of the validation methods, especially with a survival clinical outcome. Understanding the properties of the various validation methods can allow researchers to perform more powerful validations while controlling for type I error. In addition, sample size calculation strategy based on these validation methods is lacking. We conduct extensive simulations to examine the statistical properties of these validation strategies. In both simulations and a real data example, we have found that 10-fold cross-validation with permutation gave the best power while controlling type I error close to the nominal level. Based on this, we have also developed a sample size calculation method that will be used to design a validation study with a user-chosen combination of prediction. Microarray and genome-wide association studies data are used as illustrations. The power calculation method in this presentation can be used for the design of any biomedical studies involving high-dimensional data and survival outcomes. PMID:23471879

  17. A comparison of different estimation methods for simulation-based sample size determination in longitudinal studies

    Science.gov (United States)

    Bahçecitapar, Melike Kaya

    2017-07-01

    Determining sample size necessary for correct results is a crucial step in the design of longitudinal studies. Simulation-based statistical power calculation is a flexible approach to determine number of subjects and repeated measures of longitudinal studies especially in complex design. Several papers have provided sample size/statistical power calculations for longitudinal studies incorporating data analysis by linear mixed effects models (LMMs). In this study, different estimation methods (methods based on maximum likelihood (ML) and restricted ML) with different iterative algorithms (quasi-Newton and ridge-stabilized Newton-Raphson) in fitting LMMs to generated longitudinal data for simulation-based power calculation are compared. This study examines statistical power of F-test statistics for parameter representing difference in responses over time from two treatment groups in the LMM with a longitudinal covariate. The most common procedures in SAS, such as PROC GLIMMIX using quasi-Newton algorithm and PROC MIXED using ridge-stabilized algorithm are used for analyzing generated longitudinal data in simulation. It is seen that both procedures present similar results. Moreover, it is found that the magnitude of the parameter of interest in the model for simulations affect statistical power calculations in both procedures substantially.

  18. Size and thickness effect on creep behavior in conventional and vitamin E-diffused highly crosslinked polyethylene for total hip arthroplasty.

    Science.gov (United States)

    Takahashi, Yasuhito; Tateiwa, Toshiyuki; Shishido, Takaaki; Masaoka, Toshinori; Kubo, Kosuke; Yamamoto, Kengo

    2016-09-01

    Since the early 2000s, the use of large femoral heads is becoming increasingly popular in total hip arthroplasty (THA), which provides an improved range of motion and joint stability. Large femoral heads commonly necessitate to be coupled with thinner acetabular liners than the conventionally used because of the limited sizes of outer shells (especially for patients with small pelvic size). However, the influence of the liner thinning on the mechanical performance is still not clearly understood. The objective of this study was to experimentally clarify the size and thickness effect on the rates of compressive creep strain in conventional (virgin low-crosslinked) and vitamin E-diffused highly crosslinked, ultra-high molecular weight polyethylene (UHMWPE) acetabular liners. We applied uniaxial compression to these liners of various internal diameters (28, 32 and 36mm) and thicknesses (4.8, 6.8 and 8.9mm) up to 4320min under the constant load of 3000N. Vitamin E-diffused highly crosslinked UHMWPE components showed significantly greater creep resistance than the conventional ones. In the both types of UHMWPE, the rates of creep strain significantly decreased by increasing the internal diameter and thickness. Varying the component thickness contributed more largely to the creep behavior rather than the internal diameter. Our results suggest the positive mechanical advantage of using large femoral heads, but at the same time, a considerable liner thinning is not recommended for minimizing creep strain. Therefore, the further in-vitro as well as in-vivo research are necessary to conclude the optimal balance of head diameter and liner thickness within the limited sizes of outer shells. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Relationship between the size of the samples and the interpretation of the mercury intrusion results of an artificial sandstone

    NARCIS (Netherlands)

    Dong, H.; Zhang, H.; Zuo, Y.; Gao, P.; Ye, G.

    2018-01-01

    Mercury intrusion porosimetry (MIP) measurements are widely used to determine pore throat size distribution (PSD) curves of porous materials. The pore throat size of porous materials has been used to estimate their compressive strength and air permeability. However, the effect of sample size on

  20. Sampling surface particle size distributions and stability analysis of deep channel in the Pearl River Estuary

    Science.gov (United States)

    Feng, Hao-chuan; Zhang, Wei; Zhu, Yu-liang; Lei, Zhi-yi; Ji, Xiao-mei

    2017-06-01

    Particle size distributions (PSDs) of bottom sediments in a coastal zone are generally multimodal due to the complexity of the dynamic environment. In this paper, bottom sediments along the deep channel of the Pearl River Estuary (PRE) are used to understand the multimodal PSDs' characteristics and the corresponding depositional environment. The results of curve-fitting analysis indicate that the near-bottom sediments in the deep channel generally have a bimodal distribution with a fine component and a relatively coarse component. The particle size distribution of bimodal sediment samples can be expressed as the sum of two lognormal functions and the parameters for each component can be determined. At each station of the PRE, the fine component makes up less volume of the sediments and is relatively poorly sorted. The relatively coarse component, which is the major component of the sediments, is even more poorly sorted. The interrelations between the dynamics and particle size of the bottom sediment in the deep channel of the PRE have also been investigated by the field measurement and simulated data. The critical shear velocity and the shear velocity are calculated to study the stability of the deep channel. The results indicate that the critical shear velocity has a similar distribution over large part of the deep channel due to the similar particle size distribution of sediments. Based on a comparison between the critical shear velocities derived from sedimentary parameters and the shear velocities obtained by tidal currents, it is likely that the depositional area is mainly distributed in the northern part of the channel, while the southern part of the deep channel has to face higher erosion risk.

  1. Platelet function investigation by flow cytometry: Sample volume, needle size, and reference intervals.

    Science.gov (United States)

    Pedersen, Oliver Heidmann; Nissen, Peter H; Hvas, Anne-Mette

    2017-09-29

    Flow cytometry is an increasingly used method for platelet function analysis because it has some important advantages compared with other platelet function tests. Flow cytometric platelet function analyses only require a small sample volume (3.5 mL); however, to expand the field of applications, e.g., for platelet function analysis in children, even smaller volumes are needed. Platelets are easily activated, and the size of the needle for blood sampling might be of importance for the pre-activation of the platelets. Moreover, to use flow cytometry for investigation of platelet function in clinical practice, a reference interval is warranted. The aims of this work were 1) to determine if small volumes of whole blood can be used without influencing the results, 2) to examine the pre-activation of platelets with respect to needle size, and 3) to establish reference intervals for flow cytometric platelet function assays. To examine the influence of sample volume, blood was collected from 20 healthy individuals in 1.0 mL, 1.8 mL, and 3.5 mL tubes. To examine the influence of the needle size on pre-activation, blood was drawn from another 13 healthy individuals with both a 19- and 21-gauge needle. For the reference interval study, 78 healthy adults were included. The flow cytometric analyses were performed on a NAVIOS flow cytometer (Beckman Coulter, Miami, Florida) investigating the following activation-dependent markers on the platelet surface; bound-fibrinogen, CD63, and P-selectin (CD62p) after activation with arachidonic acid, ristocetin, adenosine diphosphate, thrombin-receptor-activating-peptide, and collagen. The study showed that a blood volume as low as 1.0 mL can be used for platelet function analysis by flow cytometry and that both a 19- and 21-gauge needle can be used for blood sampling. In addition, reference intervals for platelet function analyses by flow cytometry were established.

  2. Determining Sample Size with a Given Range of Mean Effects in One-Way Heteroscedastic Analysis of Variance

    Science.gov (United States)

    Shieh, Gwowen; Jan, Show-Li

    2013-01-01

    The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the…

  3. Allocating Sample Sizes to Reduce Budget for Fixed-Effect 2×2 Heterogeneous Analysis of Variance

    Science.gov (United States)

    Luh, Wei-Ming; Guo, Jiin-Huarng

    2016-01-01

    This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…

  4. Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems

    OpenAIRE

    Bonte, Anja; Neuweger, Heiko; Goesmann, Alexander; Thonar, Cécile; Mäder, Paul; Langenkämper, Georg; Niehaus, Karsten

    2014-01-01

    Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted usingmethanol and analysed by gas chromatography–mass spectrometry.

  5. Size-fractionated measurement of coarse black carbon particles in deposition samples

    Science.gov (United States)

    Schultz, E.

    In a 1-year field study, particle deposition flux was measured by transparent collection plates. Particle concentration was simultaneously measured with a cascade impactor. Microscopic evaluation of deposition samples provided the discrimination of translucent (mineral or biological) and black carbon particles, i.e. soot agglomerates, fly-ash cenospheres and rubber fragments in the size range from 3 to 50 μm. The deposition samples were collected in two different sampling devices. A wind- and rain-shielded measurement was achieved in the Sigma-2 device. Dry deposition data from this device were used to calculate mass concentrations of the translucent and the black particle fraction separately, approximating particle deposition velocity by Stokes' settling velocity. In mass calculations an error up to 20% has to be considered due to assumed spherical shape and unit density for all particles. Within the limitations of these assumptions, deposition velocities of the distinguished coarse particles were calculated. The results for total particulate matter in this range are in good agreement with those from impactor measurement. The coarse black carbon fraction shows a reduced deposition velocity in comparison with translucent particles. The deviation depends on precipitation amount. Further measurements and structural investigations of black carbon particles are in preparation to verify these results.

  6. Impact of metric and sample size on determining malaria hotspot boundaries.

    Science.gov (United States)

    Stresman, Gillian H; Giorgi, Emanuele; Baidjoe, Amrish; Knight, Phil; Odongo, Wycliffe; Owaga, Chrispin; Shagari, Shehu; Makori, Euniah; Stevenson, Jennifer; Drakeley, Chris; Cox, Jonathan; Bousema, Teun; Diggle, Peter J

    2017-04-12

    The spatial heterogeneity of malaria suggests that interventions may be targeted for maximum impact. It is unclear to what extent different metrics lead to consistent delineation of hotspot boundaries. Using data from a large community-based malaria survey in the western Kenyan highlands, we assessed the agreement between a model-based geostatistical (MBG) approach to detect hotspots using Plasmodium falciparum parasite prevalence and serological evidence for exposure. Malaria transmission was widespread and highly heterogeneous with one third of the total population living in hotspots regardless of metric tested. Moderate agreement (Kappa = 0.424) was observed between hotspots defined based on parasite prevalence by polymerase chain reaction (PCR)- and the prevalence of antibodies to two P. falciparum antigens (MSP-1, AMA-1). While numerous biologically plausible hotspots were identified, their detection strongly relied on the proportion of the population sampled. When only 3% of the population was sampled, no PCR derived hotspots were reliably detected and at least 21% of the population was needed for reliable results. Similar results were observed for hotspots of seroprevalence. Hotspot boundaries are driven by the malaria diagnostic and sample size used to inform the model. These findings warn against the simplistic use of spatial analysis on available data to target malaria interventions in areas where hotspot boundaries are uncertain.

  7. Mixed modeling and sample size calculations for identifying housekeeping genes.

    Science.gov (United States)

    Dai, Hongying; Charnigo, Richard; Vyhlidal, Carrie A; Jones, Bridgette L; Bhandary, Madhusudan

    2013-08-15

    Normalization of gene expression data using internal control genes that have biologically stable expression levels is an important process for analyzing reverse transcription polymerase chain reaction data. We propose a three-way linear mixed-effects model to select optimal housekeeping genes. The mixed-effects model can accommodate multiple continuous and/or categorical variables with sample random effects, gene fixed effects, systematic effects, and gene by systematic effect interactions. We propose using the intraclass correlation coefficient among gene expression levels as the stability measure to select housekeeping genes that have low within-sample variation. Global hypothesis testing is proposed to ensure that selected housekeeping genes are free of systematic effects or gene by systematic effect interactions. A gene combination with the highest lower bound of 95% confidence interval for intraclass correlation coefficient and no significant systematic effects is selected for normalization. Sample size calculation based on the estimation accuracy of the stability measure is offered to help practitioners design experiments to identify housekeeping genes. We compare our methods with geNorm and NormFinder by using three case studies. A free software package written in SAS (Cary, NC, U.S.A.) is available at http://d.web.umkc.edu/daih under software tab. Copyright © 2013 John Wiley & Sons, Ltd.

  8. What about N? A methodological study of sample-size reporting in focus group studies

    Science.gov (United States)

    2011-01-01

    Background Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. Results We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96). Thirty seven (17%) studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Conclusions Based on these findings we suggest that journals adopt more stringent requirements for focus group method reporting. The often poor and

  9. What about N? A methodological study of sample-size reporting in focus group studies.

    Science.gov (United States)

    Carlsen, Benedicte; Glenton, Claire

    2011-03-11

    Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96). Thirty seven (17%) studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Based on these findings we suggest that journals adopt more stringent requirements for focus group method reporting. The often poor and inconsistent reporting seen in these

  10. What about N? A methodological study of sample-size reporting in focus group studies

    Directory of Open Access Journals (Sweden)

    Glenton Claire

    2011-03-01

    Full Text Available Abstract Background Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. Results We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96. Thirty seven (17% studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Conclusions Based on these findings we suggest that journals adopt more stringent requirements for focus group method

  11. Are lead-free hunting rifle bullets as effective at killing wildlife as conventional lead bullets? A comparison based on wound size and morphology

    Energy Technology Data Exchange (ETDEWEB)

    Trinogga, Anna, E-mail: anna_trinogga@gmx.de; Fritsch, Guido; Hofer, Heribert; Krone, Oliver

    2013-01-15

    Fragmentation of the lead core of conventional wildlife hunting rifle bullets causes contamination of the target with lead. The community of scavenger species which feed on carcasses or viscera discarded by hunters are regularly exposed to these lead fragments and may die by acute or chronic lead intoxication, as demonstrated for numerous species such as white-tailed eagles (Haliaeetus albicilla) where it is among the most important sources of mortality. Not only does hunting with conventional ammunition deposit lead in considerable quantities in the environment, it also significantly delays or threatens the recovery of endangered raptor populations. Although lead-free bullets might be considered a suitable alternative that addresses the source of these problems, serious reservations have been expressed as to their ability to quickly and effectively kill a hunted animal. To assess the suitability of lead-free projectiles for hunting practice, the wounding potential of conventional bullets was compared with lead-free bullets under real life hunting conditions. Wound dimensions were regarded as good markers of the projectiles' killing potential. Wound channels in 34 killed wild ungulates were evaluated using computed tomography and post-mortem macroscopical examination. Wound diameters caused by conventional bullets did not differ significantly to those created by lead-free bullets. Similarly, the size of the maximum cross-sectional area of the wound was similar for both bullet types. Injury patterns suggested that all animals died by exsanguination. This study demonstrates that lead-free bullets are equal to conventional hunting bullets in terms of killing effectiveness and thus equally meet the welfare requirements of killing wildlife as painlessly as possible. The widespread introduction and use of lead-free bullets should be encouraged as it prevents environmental contamination with a seriously toxic pollutant and contributes to the conservation of a wide

  12. Are lead-free hunting rifle bullets as effective at killing wildlife as conventional lead bullets? A comparison based on wound size and morphology.

    Science.gov (United States)

    Trinogga, Anna; Fritsch, Guido; Hofer, Heribert; Krone, Oliver

    2013-01-15

    Fragmentation of the lead core of conventional wildlife hunting rifle bullets causes contamination of the target with lead. The community of scavenger species which feed on carcasses or viscera discarded by hunters are regularly exposed to these lead fragments and may die by acute or chronic lead intoxication, as demonstrated for numerous species such as white-tailed eagles (Haliaeetus albicilla) where it is among the most important sources of mortality. Not only does hunting with conventional ammunition deposit lead in considerable quantities in the environment, it also significantly delays or threatens the recovery of endangered raptor populations. Although lead-free bullets might be considered a suitable alternative that addresses the source of these problems, serious reservations have been expressed as to their ability to quickly and effectively kill a hunted animal. To assess the suitability of lead-free projectiles for hunting practice, the wounding potential of conventional bullets was compared with lead-free bullets under real life hunting conditions. Wound dimensions were regarded as good markers of the projectiles' killing potential. Wound channels in 34 killed wild ungulates were evaluated using computed tomography and post-mortem macroscopical examination. Wound diameters caused by conventional bullets did not differ significantly to those created by lead-free bullets. Similarly, the size of the maximum cross-sectional area of the wound was similar for both bullet types. Injury patterns suggested that all animals died by exsanguination. This study demonstrates that lead-free bullets are equal to conventional hunting bullets in terms of killing effectiveness and thus equally meet the welfare requirements of killing wildlife as painlessly as possible. The widespread introduction and use of lead-free bullets should be encouraged as it prevents environmental contamination with a seriously toxic pollutant and contributes to the conservation of a wide variety

  13. The quality of the reported sample size calculations in randomized controlled trials indexed in PubMed.

    Science.gov (United States)

    Lee, Paul H; Tse, Andy C Y

    2017-05-01

    There are limited data on the quality of reporting of information essential for replication of the calculation as well as the accuracy of the sample size calculation. We examine the current quality of reporting of the sample size calculation in randomized controlled trials (RCTs) published in PubMed and to examine the variation in reporting across study design, study characteristics, and journal impact factor. We also reviewed the targeted sample size reported in trial registries. We reviewed and analyzed all RCTs published in December 2014 with journals indexed in PubMed. The 2014 Impact Factors for the journals were used as proxies for their quality. Of the 451 analyzed papers, 58.1% reported an a priori sample size calculation. Nearly all papers provided the level of significance (97.7%) and desired power (96.6%), and most of the papers reported the minimum clinically important effect size (73.3%). The median (inter-quartile range) of the percentage difference of the reported and calculated sample size calculation was 0.0% (IQR -4.6%;3.0%). The accuracy of the reported sample size was better for studies published in journals that endorsed the CONSORT statement and journals with an impact factor. A total of 98 papers had provided targeted sample size on trial registries and about two-third of these papers (n=62) reported sample size calculation, but only 25 (40.3%) had no discrepancy with the reported number in the trial registries. The reporting of the sample size calculation in RCTs published in PubMed-indexed journals and trial registries were poor. The CONSORT statement should be more widely endorsed. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

  14. Determination of reference limits: statistical concepts and tools for sample size calculation.

    Science.gov (United States)

    Wellek, Stefan; Lackner, Karl J; Jennen-Steinmetz, Christine; Reinhard, Iris; Hoffmann, Isabell; Blettner, Maria

    2014-12-01

    Reference limits are estimators for 'extreme' percentiles of the distribution of a quantitative diagnostic marker in the healthy population. In most cases, interest will be in the 90% or 95% reference intervals. The standard parametric method of determining reference limits consists of computing quantities of the form X̅±c·S. The proportion of covered values in the underlying population coincides with the specificity obtained when a measurement value falling outside the corresponding reference region is classified as diagnostically suspect. Nonparametrically, reference limits are estimated by means of so-called order statistics. In both approaches, the precision of the estimate depends on the sample size. We present computational procedures for calculating minimally required numbers of subjects to be enrolled in a reference study. The much more sophisticated concept of reference bands replacing statistical reference intervals in case of age-dependent diagnostic markers is also discussed.

  15. Realistic weight perception and body size assessment in a racially diverse community sample of dieters.

    Science.gov (United States)

    Cachelin, F M; Striegel-Moore, R H; Elder, K A

    1998-01-01

    Recently, a shift in obesity treatment away from emphasizing ideal weight loss goals to establishing realistic weight loss goals has been proposed; yet, what constitutes "realistic" weight loss for different populations is not clear. This study examined notions of realistic shape and weight as well as body size assessment in a large community-based sample of African-American, Asian, Hispanic, and white men and women. Participants were 1893 survey respondents who were all dieters and primarily overweight. Groups were compared on various variables of body image assessment using silhouette ratings. No significant race differences were found in silhouette ratings, nor in perceptions of realistic shape or reasonable weight loss. Realistic shape and weight ratings by both women and men were smaller than current shape and weight but larger than ideal shape and weight ratings. Compared with male dieters, female dieters considered greater weight loss to be realistic. Implications of the findings for the treatment of obesity are discussed.

  16. Some basic aspects of statistical methods and sample size determination in health science research.

    Science.gov (United States)

    Binu, V S; Mayya, Shreemathi S; Dhar, Murali

    2014-04-01

    A health science researcher may sometimes wonder "why statistical methods are so important in research?" Simple answer is that, statistical methods are used throughout a study that includes planning, designing, collecting data, analyzing and drawing meaningful interpretation and report the findings. Hence, it is important that a researcher knows the concepts of at least basic statistical methods used at various stages of a research study. This helps the researcher in the conduct of an appropriately well-designed study leading to valid and reliable results that can be generalized to the population. A well-designed study possesses fewer biases, which intern gives precise, valid and reliable results. There are many statistical methods and tests that are used at various stages of a research. In this communication, we discuss the overall importance of statistical considerations in medical research with the main emphasis on estimating minimum sample size for different study objectives.

  17. Sample size and power for a stratified doubly randomized preference design.

    Science.gov (United States)

    Cameron, Briana; Esserman, Denise A

    2016-11-21

    The two-stage (or doubly) randomized preference trial design is an important tool for researchers seeking to disentangle the role of patient treatment preference on treatment response through estimation of selection and preference effects. Up until now, these designs have been limited by their assumption of equal preference rates and effect sizes across the entire study population. We propose a stratified two-stage randomized trial design that addresses this limitation. We begin by deriving stratified test statistics for the treatment, preference, and selection effects. Next, we develop a sample size formula for the number of patients required to detect each effect. The properties of the model and the efficiency of the design are established using a series of simulation studies. We demonstrate the applicability of the design using a study of Hepatitis C treatment modality, specialty clinic versus mobile medical clinic. In this example, a stratified preference design (stratified by alcohol/drug use) may more closely capture the true distribution of patient preferences and allow for a more efficient design than a design which ignores these differences (unstratified version). © The Author(s) 2016.

  18. Estimating effective population size from temporally spaced samples with a novel, efficient maximum-likelihood algorithm.

    Science.gov (United States)

    Hui, Tin-Yu J; Burt, Austin

    2015-05-01

    The effective population size [Formula: see text] is a key parameter in population genetics and evolutionary biology, as it quantifies the expected distribution of changes in allele frequency due to genetic drift. Several methods of estimating [Formula: see text] have been described, the most direct of which uses allele frequencies measured at two or more time points. A new likelihood-based estimator [Formula: see text] for contemporary effective population size using temporal data is developed in this article. The existing likelihood methods are computationally intensive and unable to handle the case when the underlying [Formula: see text] is large. This article tries to work around this problem by using a hidden Markov algorithm and applying continuous approximations to allele frequencies and transition probabilities. Extensive simulations are run to evaluate the performance of the proposed estimator [Formula: see text], and the results show that it is more accurate and has lower variance than previous methods. The new estimator also reduces the computational time by at least 1000-fold and relaxes the upper bound of [Formula: see text] to several million, hence allowing the estimation of larger [Formula: see text]. Finally, we demonstrate how this algorithm can cope with nonconstant [Formula: see text] scenarios and be used as a likelihood-ratio test to test for the equality of [Formula: see text] throughout the sampling horizon. An R package "NB" is now available for download to implement the method described in this article. Copyright © 2015 by the Genetics Society of America.

  19. Sediment grain size estimation using airborne remote sensing, field sampling, and robust statistic.

    Science.gov (United States)

    Castillo, Elena; Pereda, Raúl; Luis, Julio Manuel de; Medina, Raúl; Viguri, Javier

    2011-10-01

    Remote sensing has been used since the 1980s to study parameters in relation with coastal zones. It was not until the beginning of the twenty-first century that it started to acquire imagery with good temporal and spectral resolution. This has encouraged the development of reliable imagery acquisition systems that consider remote sensing as a water management tool. Nevertheless, the spatial resolution that it provides is not adapted to carry out coastal studies. This article introduces a new methodology for estimating the most fundamental physical property of intertidal sediment, the grain size, in coastal zones. The study combines hyperspectral information (CASI-2 flight), robust statistic, and simultaneous field work (chemical and radiometric sampling), performed over Santander Bay, Spain. Field data acquisition was used to build a spectral library in order to study different atmospheric correction algorithms for CASI-2 data and to develop algorithms to estimate grain size in an estuary. Two robust estimation techniques (MVE and MCD multivariate M-estimators of location and scale) were applied to CASI-2 imagery, and the results showed that robust adjustments give acceptable and meaningful algorithms. These adjustments have given the following R(2) estimated results: 0.93 in the case of sandy loam contribution, 0.94 for the silty loam, and 0.67 for clay loam. The robust statistic is a powerful tool for large dataset.

  20. Determination of metformin in human plasma and urine by high-performance liquid chromatography using small sample volume and conventional octadecyl silane column.

    Science.gov (United States)

    Gabr, Raniah Q; Padwal, Raj S; Brocks, Dion R

    2010-01-01

    To develop a selective and sensitive high-performance liquid chromatographic method for the determination of metformin in human plasma and urine, using a conventional reverse phase column and low specimen volume. Extraction of metformin and ranitidine (as internal standard) from plasma and urine samples (100 µL) was performed with a 1-butanol-hexane (50:50, v/v) mixture under alkaline conditions followed by back-extraction into diluted acetic acid. Chromatography was carried out using a C18 column (250 mm×4.6 mm, 5 μm). A mobile phase consisting of acetonitrile and KH2PO4 (34:66, v/v) and sodium dodecyl sulphate (3 mM) was pumped at an isocratic flow rate of 0.7 mL/min. The calibration curves were linear (>0.995) in the concentration ranges of 10-5000 and 2-2000 μg/mL for metformin in plasma and urine respectively. .The mean absolute recoveries for 100 and 1000 ng/mL metformin in plasma using the present extraction procedure were 93.7 and 88.5%, respectively. The intra- and inter-day coefficients of variation in plasma and urine were <20% at the lowest, and <16% at other concentrations. The percent error values were less than 2% in plasma while it reached ~9% in urine. The lower limits of quantification were 7.8 ng/mL and 1.6 μg/mL of metformin base in plasma and urine respectively. The method showed high calibers of sensitivity and selectivity for monitoring therapeutic concentrations of metformin in both plasma and urine based on a 0.1 ml sample size._____________________________________________________________________________________

  1. Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data.

    Science.gov (United States)

    Li, Chung-I; Su, Pei-Fang; Shyr, Yu

    2013-12-06

    Sample size calculation is an important issue in the experimental design of biomedical research. For RNA-seq experiments, the sample size calculation method based on the Poisson model has been proposed; however, when there are biological replicates, RNA-seq data could exhibit variation significantly greater than the mean (i.e. over-dispersion). The Poisson model cannot appropriately model the over-dispersion, and in such cases, the negative binomial model has been used as a natural extension of the Poisson model. Because the field currently lacks a sample size calculation method based on the negative binomial model for assessing differential expression analysis of RNA-seq data, we propose a method to calculate the sample size. We propose a sample size calculation method based on the exact test for assessing differential expression analysis of RNA-seq data. The proposed sample size calculation method is straightforward and not computationally intensive. Simulation studies to evaluate the performance of the proposed sample size method are presented; the results indicate our method works well, with achievement of desired power.

  2. Impact of sample size on principal component analysis ordination of an environmental data set: effects on eigenstructure

    Directory of Open Access Journals (Sweden)

    Shaukat S. Shahid

    2016-06-01

    Full Text Available In this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50 on the eigenvalues and eigenvectors resulting from principal component analysis (PCA. For each sample size, 100 bootstrap samples were drawn from environmental data matrix pertaining to water quality variables (p = 22 of a small data set comprising of 55 samples (stations from where water samples were collected. Because in ecology and environmental sciences the data sets are invariably small owing to high cost of collection and analysis of samples, we restricted our study to relatively small sample sizes. We focused attention on comparison of first 6 eigenvectors and first 10 eigenvalues. Data sets were compared using agglomerative cluster analysis using Ward’s method that does not require any stringent distributional assumptions.

  3. SAMPLE SIZE DETERMINATION IN CLINICAL TRIALS BASED ON APPROXIMATION OF VARIANCE ESTIMATED FROM LIMITED PRIMARY OR PILOT STUDIES

    Directory of Open Access Journals (Sweden)

    B SOLEYMANI

    2001-06-01

    Full Text Available In many casses the estimation of variance which is used to determine sample size in clinical trials, derives from limited primary or pilot studies in which number of samples is small. since in such casses the estimation of variance may be much far from the real variance, the size of samples is suspected to be less or more than what is really needed. In this article an attempt has been made to give a solution to this problem. in the case of normal distribution. Based on distribution of (n-1 S2/?2 which is chi-square for normal variables, an appropriate estimation of variance is determined an used to calculate sample size. Also, total probability to ensure specific precision and power has been achived. In method presented here, The probability for getting desired precision and power is more than that of usual method, but results of two methods get closer when sample size increases in primary studies.

  4. Comparison of four monolithic zirconia materials with conventional ones: Contrast ratio, grain size, four-point flexural strength and two-body wear.

    Science.gov (United States)

    Stawarczyk, Bogna; Frevert, Kathrin; Ender, Andreas; Roos, Malgorzata; Sener, Beatrice; Wimmer, Timea

    2016-06-01

    To test the mechanical and optical properties of monolithic zirconia in comparison to conventional zirconia. Specimens were prepared from: monolithic zirconia: Zenostar (ZS), DD Bio ZX(2) hochtransluzent (DD), Ceramill Zolid (CZ), InCoris TZI (IC) and a conventional zirconia Ceramill ZI (CZI). Contrast ratio (N=75/n=15) was measured according to ISO 2471:2008. Grain sizes (N=75/n=15) were investigated with scanning electron microscope. Four-point flexural strength (N=225/n=15/zirconia and aging regime) was measured initially, after aging in autoclave or chewing simulator (ISO 13356:2008). Two-body wear of polished and glazed/veneered specimens (N=108/n=12) was analyzed in a chewing simulator using human teeth as antagonists. Data were analyzed using 2-/1-way ANOVA with post-hoc Scheffé, Kruskal-Wallis-H, Mann-Whitney-U, Spearman-Rho, Weibull statistics and linear mixed models (pzirconia showed higher optical, but lower mechanical properties than conventional zirconia. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. PET/CT in cancer: moderate sample sizes may suffice to justify replacement of a regional gold standard

    DEFF Research Database (Denmark)

    Gerke, Oke; Poulsen, Mads Hvid; Bouchelouche, Kirsten

    2009-01-01

    /CT also performs well in adjacent areas, then sample sizes in accuracy studies can be reduced. PROCEDURES: Traditional standard power calculations for demonstrating sensitivities of both 80% and 90% are shown. The argument is then described in general terms and demonstrated by an ongoing study...... of metastasized prostate cancer. RESULTS: An added value in accuracy of PET/CT in adjacent areas can outweigh a downsized target level of accuracy in the gold standard region, justifying smaller sample sizes. CONCLUSIONS: If PET/CT provides an accuracy benefit in adjacent regions, then sample sizes can be reduced...

  6. Cervical cancer incidence after normal cytological sample in routine screening using SurePath, ThinPrep, and conventional cytology: population based study

    NARCIS (Netherlands)

    Rozemeijer, K.; Naber, S.K.; Penning, C.; Overbeek, L.I.H.; Looman, C.W.; Kok, I.M. de; Matthijsse, S.M.; Rebolj, M.; Kemenade, F.J. van; Ballegooijen, M. van

    2017-01-01

    Objective To compare the cumulative incidence of cervical cancer diagnosed within 72 months after a normal screening sample between conventional cytology and liquid based cytology tests SurePath and ThinPrep.Design Retrospective population based cohort study.Setting Nationwide network and registry

  7. Antibodies to major pasture borne helminth infections in bulk-tank milk samples from organic and nearby conventional dairy herds in south-central Sweden.

    Science.gov (United States)

    Höglund, Johan; Dahlström, Frida; Engström, Annie; Hessle, Anna; Jakubek, Eva-Britt; Schnieder, Thomas; Strube, Christina; Sollenberg, Sofia

    2010-08-04

    The objective of this randomised pairwise survey was to compare the regional distribution of antibody levels against the three most important helminth infections in organic and conventional dairy herds in Sweden. Bulk-tank milk from 105 organic farms and 105 neighbouring conventional dairy farms with access to pasture in south-central Sweden were collected in September 2008. Samples were also collected from 8 organic and 8 conventional herds located in a much more restricted area, on the same as well as 3 additional occasions during the grazing season, to reveal evidence for seasonal patterns against cattle stomach worm (Ostertagia ostertagi). Antibody levels to the stomach worm (O. ostertagi), liver fluke (Fasciola hepatica) and lungworm (Dictyocaulus viviparus) were then determined by detection of specific antibodies using three different enzyme-linked immunosorbent assays (ELISAs). According to the Svanovir Ostertagia ELISA, the mean optical density ratio (ODR) was significantly higher in the milk from organic compared to conventional herds, i.e. 0.82 (95% CL=0.78-0.86) versus 0.66 (0.61-0.71). However, no significant differences were observed in the samples collected at different time points from the same 16 herds (F(3,39)=1.18, P=0.32). Antibodies to D. viviparus infection were diagnosed with an ELISA based on recombinant major sperm protein (MSP), and seropositivity was found in 21 (18%) of the 113 organic herds and 11 (9%) of the 113 conventional herds. The seroprevalence of D. viviparus was somewhat higher in the organic herds (Chi-square=3.65, P=0.056), but with the positive conventional herds were located in the vicinity of infected organic herds. Of the 16 herds that were sampled on repeated occasions, as many as 10 (63%), were seropositive on at least one sampling occasion. Many of these turned positive towards the end of the grazing season. Only one herd was positive in all 4 samples and 3 were positive only at turn-out. Considering F. hepatica there

  8. Particle size distribution and chemical composition of total mixed rations for dairy cattle: water addition and feed sampling effects.

    Science.gov (United States)

    Arzola-Alvarez, C; Bocanegra-Viezca, J A; Murphy, M R; Salinas-Chavira, J; Corral-Luna, A; Romanos, A; Ruíz-Barrera, O; Rodríguez-Muela, C

    2010-09-01

    Four dairy farms were used to determine the effects of water addition to diets and sample collection location on the particle size distribution and chemical composition of total mixed rations (TMR). Samples were collected weekly from the mixing wagon and from 3 locations in the feed bunk (top, middle, and bottom) for 5 mo (April, May, July, August, and October). Samples were partially dried to determine the effect of moisture on particle size distribution. Particle size distribution was measured using the Penn State Particle Size Separator. Crude protein, neutral detergent fiber, and acid detergent fiber contents were also analyzed. Particle fractions 19 to 8, 8 to 1.18, and 19 mm was greater than recommended for TMR, according to the guidelines of Cooperative Extension of Pennsylvania State University. The particle size distribution in April differed from that in October, but intermediate months (May, July, and August) had similar particle size distributions. Samples from the bottom of the feed bunk had the highest percentage of particles retained on the 19-mm sieve. Samples from the top and middle of the feed bunk were similar to that from the mixing wagon. Higher percentages of particles were retained on >19, 19 to 8, and 8 to 1.18 mm sieves for wet than dried samples. The reverse was found for particles passing the 1.18-mm sieve. Mean particle size was higher for wet than dried samples. The crude protein, neutral detergent fiber, and acid detergent fiber contents of TMR varied with month of sampling (18-21, 40-57, and 21-34%, respectively) but were within recommended ranges for high-yielding dairy cows. Analyses of TMR particle size distributions are useful for proper feed bunk management and formulation of diets that maintain rumen function and maximize milk production and quality. Water addition may help reduce dust associated with feeding TMR. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. Determination of PCR efficiency in chelex-100 purified clinical samples and comparison of real-time quantitative PCR and conventional PCR for detection of Chlamydia pneumoniae

    Directory of Open Access Journals (Sweden)

    Jensen Jørgen

    2002-07-01

    Full Text Available Abstract Background Chlamydia pneumoniae infection has been detected by serological methods, but PCR is gaining more interest. A number of different PCR assays have been developed and some are used in combination with serology for diagnosis. Real-time PCR could be an attractive new PCR method; therefore it must be evaluated and compared to conventional PCR methods. Results We compared the performance of a newly developed real-time PCR with a conventional PCR method for detection of C. pneumoniae. The PCR methods were tested on reference samples containing C. pneumoniae DNA and on 136 nasopharyngeal samples from patients with a chronic cough. We found the same detection limit for the two methods and that clinical performance was equal for the real-time PCR and for the conventional PCR method, although only three samples tested positive. To investigate whether the low prevalence of C. pneumoniae among patients with a chronic cough was caused by suboptimal PCR efficiency in the samples, PCR efficiency was determined based on the real-time PCR. Seventeen of twenty randomly selected clinical samples had a similar PCR efficiency to samples containing pure genomic C. pneumoniae DNA. Conclusions These results indicate that the performance of real-time PCR is comparable to that of conventional PCR, but that needs to be confirmed further. Real-time PCR can be used to investigate the PCR efficiency which gives a rough estimate of how well the real-time PCR assay works in a specific sample type. Suboptimal PCR efficiency of PCR is not a likely explanation for the low positivity rate of C. pneumoniae in patients with a chronic cough.

  10. Bayesian adaptive determination of the sample size required to assure acceptably low adverse event risk.

    Science.gov (United States)

    Lawrence Gould, A; Zhang, Xiaohua Douglas

    2014-03-15

    An emerging concern with new therapeutic agents, especially treatments for type 2 diabetes, a prevalent condition that increases an individual's risk of heart attack or stroke, is the likelihood of adverse events, especially cardiovascular events, that the new agents may cause. These concerns have led to regulatory requirements for demonstrating that a new agent increases the risk of an adverse event relative to a control by no more than, say, 30% or 80% with high (e.g., 97.5%) confidence. We describe a Bayesian adaptive procedure for determining if the sample size for a development program needs to be increased and, if necessary, by how much, to provide the required assurance of limited risk. The decision is based on the predictive likelihood of a sufficiently high posterior probability that the relative risk is no more than a specified bound. Allowance can be made for between-center as well as within-center variability to accommodate large-scale developmental programs, and design alternatives (e.g., many small centers, few large centers) for obtaining additional data if needed can be explored. Binomial or Poisson likelihoods can be used, and center-level covariates can be accommodated. The predictive likelihoods are explored under various conditions to assess the statistical properties of the method. Copyright © 2013 John Wiley & Sons, Ltd.

  11. The effect of noise and sampling size on vorticity measurements in rotating fluids

    Science.gov (United States)

    Wong, Kelvin K. L.; Kelso, Richard M.; Mazumdar, Jagannath; Abbott, Derek

    2008-11-01

    This paper describes a new technique for presenting information based on given flow images. Using a multistep first order differentiation technique, we are able to map in two dimensions, vorticity of fluid within a region of investigation. We can then present the distribution of this property in space by means of a color intensity map. In particular, the state of fluid rotation can be displayed using maps of vorticity flow values. The framework that is implemented can also be used to quantify the vortices using statistical properties which can be derived from such vorticity flow maps. To test our methodology, we have devised artificial vortical flow fields using an analytical formulation of a single vortex. Reliability of vorticity measurement from our results shows that the size of flow vector sampling and noise in flow field affect the generation of vorticity maps. Based on histograms of these maps, we are able to establish an optimised configuration that computes vorticity fields to approximate the ideal vortex statistically. The novel concept outlined in this study can be used to reduce fluctuations of noise in a vorticity calculation based on imperfect flow information without excessive loss of its features, and thereby improves the effectiveness of flow

  12. Sampling design and required sample size for evaluating contamination levels of 137Cs in Japanese fir needles in a mixed deciduous forest stand in Fukushima, Japan.

    Science.gov (United States)

    Oba, Yurika; Yamada, Toshihiro

    2017-05-01

    We estimated the sample size (the number of samples) required to evaluate the concentration of radiocesium (137Cs) in Japanese fir (Abies firma Sieb. & Zucc.), 5 years after the outbreak of the Fukushima Daiichi Nuclear Power Plant accident. We investigated the spatial structure of the contamination levels in this species growing in a mixed deciduous broadleaf and evergreen coniferous forest stand. We sampled 40 saplings with a tree height of 150 cm-250 cm in a Fukushima forest community. The results showed that: (1) there was no correlation between the 137Cs concentration in needles and soil, and (2) the difference in the spatial distribution pattern of 137Cs concentration between needles and soil suggest that the contribution of root uptake to 137Cs in new needles of this species may be minor in the 5 years after the radionuclides were released into the atmosphere. The concentration of 137Cs in needles showed a strong positive spatial autocorrelation in the distance class from 0 to 2.5 m, suggesting that the statistical analysis of data should consider spatial autocorrelation in the case of an assessment of the radioactive contamination of forest trees. According to our sample size analysis, a sample size of seven trees was required to determine the mean contamination level within an error in the means of no more than 10%. This required sample size may be feasible for most sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Estimating everyday portion size using a 'method of constant stimuli': in a student sample, portion size is predicted by gender, dietary behaviour, and hunger, but not BMI.

    Science.gov (United States)

    Brunstrom, Jeffrey M; Rogers, Peter J; Pothos, Emmanuel M; Calitri, Raff; Tapper, Katy

    2008-09-01

    This paper (i) explores the proposition that body weight is associated with large portion sizes and (ii) introduces a new technique for measuring everyday portion size. In our paradigm, the participant is shown a picture of a food portion and is asked to indicate whether it is larger or smaller than their usual portion. After responding to a range of different portions an estimate of everyday portion size is calculated using probit analysis. Importantly, this estimate is likely to be robust because it is based on many responses. First-year undergraduate students (N=151) completed our procedure for 12 commonly consumed foods. As expected, portion sizes were predicted by gender and by a measure of dieting and dietary restraint. Furthermore, consistent with reports of hungry supermarket shoppers, portion-size estimates tended to be higher in hungry individuals. However, we found no evidence for a relationship between BMI and portion size in any of the test foods. We consider reasons why this finding should be anticipated. In particular, we suggest that the difference in total energy expenditure of individuals with a higher and lower BMI is too small to be detected as a concomitant difference in portion size (at least in our sample).

  14. The proportionator: unbiased stereological estimation using biased automatic image analysis and non-uniform probability proportional to size sampling

    DEFF Research Database (Denmark)

    Gardi, Jonathan Eyal; Nyengaard, Jens Randel; Gundersen, Hans Jørgen Gottlieb

    2008-01-01

    The proportionator is a novel and radically different approach to sampling with microscopes based on well-known statistical theory (probability proportional to size - PPS sampling). It uses automatic image analysis, with a large range of options, to assign to every field of view in the section a ...

  15. Field sampling of loose erodible material: A new system to consider the full particle-size spectrum

    Science.gov (United States)

    Klose, Martina; Gill, Thomas E.; Webb, Nicholas P.; Van Zee, Justin W.

    2017-10-01

    A new system is presented to sample and enable the characterization of loose erodible material (LEM) present on a soil surface, which may be susceptible for entrainment by wind. The system uses a modified MWAC (Modified Wilson and Cooke) sediment sampler connected to a corded hand-held vacuum cleaner. Performance and accuracy of the system was tested in the laboratory using five reference soil samples with different textures. Sampling was most effective for sandy soils, while effectiveness decreases were found for soils with high silt and clay contents in dry dispersion. This effectiveness decrease can be attributed to loose silt and clay-sized particles and particle aggregates adhering to and clogging a filter attached to the MWAC outlet. Overall, the system was found to be effective in collecting sediment for most soil textures and theoretical interpretation of the measured flow speeds suggests that LEM can be sampled for a wide range of particle sizes, including dust particles. Particle-size analysis revealed that the new system is able to accurately capture the particle-size distribution (PSD) of a given sample. Only small discrepancies (maximum cumulative difference vacuuming for all test soils. Despite limitations of the system, it is an advance toward sampling the full particle-size spectrum of loose sediment available for entrainment with the overall goal to better understand the mechanisms of dust emission and their variability.

  16. Critical analysis of consecutive unilateral cleft lip repairs: determining ideal sample size.

    Science.gov (United States)

    Power, Stephanie M; Matic, Damir B

    2013-03-01

    Objective : Cleft surgeons often show 10 consecutive lip repairs to reduce presentation bias, however the validity remains unknown. The purpose of this study is to determine the number of consecutive cases that represent average outcomes. Secondary objectives are to determine if outcomes correlate with cleft severity and to calculate interrater reliability. Design : Consecutive preoperative and 2-year postoperative photographs of the unilateral cleft lip-nose complex were randomized and evaluated by cleft surgeons. Parametric analysis was performed according to chronologic, consecutive order. The mean standard deviation over all raters enabled calculation of expected 95% confidence intervals around a mean tested for various sample sizes. Setting : Meeting of the American Cleft Palate-Craniofacial Association in 2009. Patients, Participants : Ten senior cleft surgeons evaluated 39 consecutive lip repairs. Main Outcome Measures : Preoperative severity and postoperative outcomes were evaluated using descriptive and quantitative scales. Results : Intraclass correlation coefficients for cleft severity and postoperative evaluations were 0.65 and 0.21, respectively. Outcomes did not correlate with cleft severity (P  =  .28). Calculations for 10 consecutive cases demonstrated wide 95% confidence intervals, spanning two points on both postoperative grading scales. Ninety-five percent confidence intervals narrowed within one qualitative grade (±0.30) and one point (±0.50) on the 10-point scale for 27 consecutive cases. Conclusions : Larger numbers of consecutive cases (n > 27) are increasingly representative of average results, but less practical in presentation format. Ten consecutive cases lack statistical support. Cleft surgeons showed low interrater reliability for postoperative assessments, which may reflect personal bias when evaluating another surgeon's results.

  17. Reliable calculation in probabilistic logic: Accounting for small sample size and model uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Ferson, S. [Applied Biomathematics, Setauket, NY (United States)

    1996-12-31

    A variety of practical computational problems arise in risk and safety assessments, forensic statistics and decision analyses in which the probability of some event or proposition E is to be estimated from the probabilities of a finite list of related subevents or propositions F,G,H,.... In practice, the analyst`s knowledge may be incomplete in two ways. First, the probabilities of the subevents may be imprecisely known from statistical estimations, perhaps based on very small sample sizes. Second, relationships among the subevents may be known imprecisely. For instance, there may be only limited information about their stochastic dependencies. Representing probability estimates as interval ranges on has been suggested as a way to address the first source of imprecision. A suite of AND, OR and NOT operators defined with reference to the classical Frochet inequalities permit these probability intervals to be used in calculations that address the second source of imprecision, in many cases, in a best possible way. Using statistical confidence intervals as inputs unravels the closure properties of this approach however, requiring that probability estimates be characterized by a nested stack of intervals for all possible levels of statistical confidence, from a point estimate (0% confidence) to the entire unit interval (100% confidence). The corresponding logical operations implied by convolutive application of the logical operators for every possible pair of confidence intervals reduces by symmetry to a manageably simple level-wise iteration. The resulting calculus can be implemented in software that allows users to compute comprehensive and often level-wise best possible bounds on probabilities for logical functions of events.

  18. Grain size of loess and paleosol samples: what are we measuring?

    Science.gov (United States)

    Varga, György; Kovács, János; Szalai, Zoltán; Újvári, Gábor

    2017-04-01

    Particle size falling into a particularly narrow range is among the most important properties of windblown mineral dust deposits. Therefore, various aspects of aeolian sedimentation and post-depositional alterations can be reconstructed only from precise grain size data. Present study is aimed at (1) reviewing grain size data obtained from different measurements, (2) discussing the major reasons for disagreements between data obtained by frequently applied particle sizing techniques, and (3) assesses the importance of particle shape in particle sizing. Grain size data of terrestrial aeolian dust deposits (loess and paleosoil) were determined by laser scattering instruments (Fritsch Analysette 22 Microtec Plus, Horiba Partica La-950 v2 and Malvern Mastersizer 3000 with a Hydro Lv unit), while particles size and shape distributions were acquired by Malvern Morphologi G3-ID. Laser scattering results reveal that the optical parameter settings of the measurements have significant effects on the grain size distributions, especially for the fine-grained fractions (camera. However, this is only one outcome of infinite possible projections of a three-dimensional object and it cannot be regarded as a representative one. The third (height) dimension of the particles remains unknown, so the volume-based weightings are fairly dubious in the case of platy particles. Support of the National Research, Development and Innovation Office (Hungary) under contract NKFI 120620 is gratefully acknowledged. It was additionally supported (for G. Varga) by the Bolyai János Research Scholarship of the Hungarian Academy of Sciences.

  19. Applying Individual Tree Structure From Lidar to Address the Sensitivity of Allometric Equations to Small Sample Sizes.

    Science.gov (United States)

    Duncanson, L.; Dubayah, R.

    2015-12-01

    Lidar remote sensing is widely applied for mapping forest carbon stocks, and technological advances have improved our ability to capture structural details from forests, even resolving individual trees. Despite these advancements, the accuracy of forest aboveground biomass models remains limited by the quality of field estimates of biomass. The accuracies of field estimates are inherently dependent on the accuracy of the allometric equations used to relate measurable attributes to biomass. These equations are calibrated with relatively small samples of often spatially clustered trees. This research focuses on one of many issues involving allometric equations - understanding how sensitive allometric parameters are to the sample sizes used to fit them. We capitalize on recent advances in lidar remote sensing to extract individual tree structural information from six high-resolution airborne lidar datasets in the United States. We remotely measure millions of tree heights and crown radii, and fit allometric equations to the relationship between tree height and radius at a 'population' level, in each site. We then extract samples from our tree database, and build allometries on these smaller samples of trees, with varying sample sizes. We show that for the allometric relationship between tree height and crown radius, small sample sizes produce biased allometric equations that overestimate height for a given crown radius. We extend this analysis using translations from the literature to address potential implications for biomass, showing that site-level biomass may be greatly overestimated when applying allometric equations developed with the typically small sample sizes used in popular allometric equations for biomass.

  20. Effects of the sample size of reference population on determining BMD reference curve and peak BMD and diagnosing osteoporosis.

    Science.gov (United States)

    Hou, Y-L; Liao, E-Y; Wu, X-P; Peng, Y-Q; Zhang, H; Dai, R-C; Luo, X-H; Cao, X-Z

    2008-01-01

    Establishing reference databases generally requires a large sample size to achieve reliable results. Our study revealed that the varying sample size from hundreds to thousands of individuals has no decisive effect on the bone mineral density (BMD) reference curve, peak BMD, and diagnosing osteoporosis. It provides a reference point for determining the sample size while establishing local BMD reference databases. This study attempts to determine a suitable sample size for establishing bone mineral density (BMD) reference databases in a local laboratory. The total reference population consisted of 3,662 Chinese females aged 6-85 years. BMDs were measured with a dual-energy X-ray absorptiometry densitometer. The subjects were randomly divided into four different sample groups, that is, total number (Tn) = 3,662, 1/2n = 1,831, 1/4n = 916, and 1/8n = 458. We used the best regression model to determine BMD reference curve and peak BMD. There was no significant difference in the full curves between the four sample groups at each skeletal site, although some discrepancy at the end of the curves was observed at the spine. Peak BMDs were very similar in the four sample groups. According to the Chinese diagnostic criteria (BMD >25% below the peak BMD as osteoporosis), no difference was observed in the osteoporosis detection rate using the reference values determined by the four different sample groups. Varying the sample size from hundreds to thousands has no decisive effect on establishing BMD reference curve and determining peak BMD. It should be practical for determining the reference population while establishing local BMD databases.

  1. ANALYSIS AND IDENTIFICATION SPIKING CHEMICAL COMPOUNDS RELATED TO CHEMICAL WEAPON CONVENTION IN UNKNOWN WATER SAMPLES USING GAS CHROMATOGRAPHY AND GAS CHROMATOGRAPHY ELECTRON IONIZATION MASS SPECTROMETRY

    Directory of Open Access Journals (Sweden)

    Harry Budiman

    2010-06-01

    Full Text Available The identification and analysis of chemical warfare agents and their degradation products is one of important component for the implementation of the convention. Nowadays, the analytical method for determination chemical warfare agent and their degradation products has been developing and improving. In order to get the sufficient analytical data as recommended by OPCW especially in Proficiency Testing, the spiking chemical compounds related to Chemical Weapon Convention in unknown water sample were determined using two different techniques such as gas chromatography and gas chromatography electron-impact ionization mass spectrometry. Neutral organic extraction, pH 11 organic extraction, cation exchanged-methylation, triethylamine/methanol-silylation were performed to extract the chemical warfare agents from the sample, before analyzing with gas chromatography. The identification of chemical warfare agents was carried out by comparing the mass spectrum of chemicals with mass spectrum reference from the OPCW Central Analytical Database (OCAD library while the retention indices calculation obtained from gas chromatography analysis was used to get the confirmation and supported data of  the chemical warfare agents. Diisopropyl methylphosphonate, 2,2-diphenyl-2-hydroacetic acid and 3-quinuclidinol were found in unknown water sample. Those chemicals were classified in schedule 2 as precursor or reactant of chemical weapons compound in schedule list of Chemical Weapon Convention.   Keywords: gas chromatography, mass spectrometry, retention indices, OCAD library, chemical warfare agents

  2. Comparison of microscopy, two xenic culture techniques, conventional and real-time PCR for the detection of Dientamoeba fragilis in clinical stool samples.

    Science.gov (United States)

    Stark, D; Barratt, J; Roberts, T; Marriott, D; Harkness, J; Ellis, J

    2010-04-01

    Dientamoeba fragilis is a pathogenic protozoan parasite that is notoriously difficult to diagnose. The aim of this study was to determine the gold standard for laboratory detection of D. fragilis. A total of 650 human faecal samples were included in the study. All specimens underwent the following: microscopy using a permanent stain (modified iron-haematoxylin), culture using a modified Boeck and Drbohlav's medium (MBD) and TYGM-9, a conventional polymerase chain reaction (PCR) and a real-time PCR (RT-PCR). The overall prevalence of D. fragilis in the study population was 5.4% (35/650). RT-PCR detected 35 isolates, conventional PCR detected 15 isolates, MBD culture detected 14 isolates, TYGM-9 detected ten isolates, while microscopy detected 12 isolates. RT-PCR detected an additional 15 positive samples compared to the other diagnostic methods, all of which were confirmed by sequencing. When all methods were compared to each other, RT-PCR showed a sensitivity and specificity of 100 and 100%, conventional PCR 42.9 and 100%, MBD culture 40 and 100%, TYGM-9 culture 28.6 and 100%, and microscopy 34.3 and 99%, respectively. These results show that RT-PCR is the diagnostic method of choice for the detection of D. fragilis in clinical samples and, as such, should be considered as the gold standard for diagnosis.

  3. Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples.

    Science.gov (United States)

    Uyaguari-Diaz, Miguel I; Slobodan, Jared R; Nesbitt, Matthew J; Croxen, Matthew A; Isaac-Renton, Judith; Prystajecky, Natalie A; Tang, Patrick

    2015-04-17

    Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA libraries are needed for optimal results from next-generation sequencing. Environmental samples such as water may have low quality and quantities of DNA as well as contaminants that co-precipitate with DNA. The mechanical and enzymatic processes involved in extraction and library preparation may further damage the DNA. Gel size selection enables purification and recovery of DNA fragments of a defined size for sequencing applications. Nevertheless, this task is one of the most time-consuming steps in the DNA library preparation workflow. The protocol described here enables complete automation of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments. In this study, we describe a high-throughput approach to prepare high quality DNA libraries from freshwater samples that can be applied also to other environmental samples. We used an indirect approach to concentrate bacterial cells from environmental freshwater samples; DNA was extracted using a commercially available DNA extraction kit, and DNA libraries were prepared using a commercial transposon-based protocol. DNA fragments of 500 to 800 bp were gel size selected using Ranger Technology, an automated electrophoresis workstation. Sequencing of the size-selected DNA libraries demonstrated significant improvements to read length and quality of the sequencing reads.

  4. The Quantitative LOD Score: Test Statistic and Sample Size for Exclusion and Linkage of Quantitative Traits in Human Sibships

    OpenAIRE

    Page, Grier P.; Amos, Christopher I.; Boerwinkle, Eric

    1998-01-01

    We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, ...

  5. Discrepancies in sample size calculations and data analyses reported in randomised trials: comparison of publications with protocols

    DEFF Research Database (Denmark)

    Chan, A.W.; Hrobjartsson, A.; Jorgensen, K.J.

    2008-01-01

    of handling missing data was described in 16 protocols and 49 publications. 39/49 protocols and 42/43 publications reported the statistical test used to analyse primary outcome measures. Unacknowledged discrepancies between protocols and publications were found for sample size calculations (18/34 trials...... in publications, sample size calculations and statistical methods were often explicitly discrepant with the protocol or not pre-specified. Such amendments were rarely acknowledged in the trial publication. The reliability of trial reports cannot be assessed without having access to the full protocols......OBJECTIVE: To evaluate how often sample size calculations and methods of statistical analysis are pre-specified or changed in randomised trials. DESIGN: Retrospective cohort study. Data source Protocols and journal publications of published randomised parallel group trials initially approved...

  6. Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure.

    Science.gov (United States)

    Ciarleglio, Maria M; Arendt, Christopher D; Peduzzi, Peter N

    2016-06-01

    When designing studies that have a continuous outcome as the primary endpoint, the hypothesized effect size ([Formula: see text]), that is, the hypothesized difference in means ([Formula: see text]) relative to the assumed variability of the endpoint ([Formula: see text]), plays an important role in sample size and power calculations. Point estimates for [Formula: see text] and [Formula: see text] are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed. This article presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of [Formula: see text] and [Formula: see text] into the study's power calculation. Conditional expected power, which averages the traditional power curve using the prior distributions of [Formula: see text] and [Formula: see text] as the averaging weight, is used, and the value of [Formula: see text] is found that equates the prespecified frequentist power ([Formula: see text]) and the conditional expected power of the trial. This hypothesized effect size is then used in traditional sample size calculations when determining sample size for the study. The value of [Formula: see text] found using this method may be expressed as a function of the prior means of [Formula: see text] and [Formula: see text], [Formula: see text], and their prior standard deviations, [Formula: see text]. We show that the "naïve" estimate of the effect size, that is, the ratio of prior means, should be down-weighted to account for the variability in the parameters. An example is presented for designing a placebo-controlled clinical trial testing the antidepressant effect of alprazolam as monotherapy for major depression. Through this method, we are able to formally integrate prior information on the uncertainty and variability of both the treatment effect and the common standard deviation into the design of the study while maintaining a frequentist framework for

  7. Elaboration of austenitic stainless steel samples with bimodal grain size distributions and investigation of their mechanical behavior

    Science.gov (United States)

    Flipon, B.; de la Cruz, L. Garcia; Hug, E.; Keller, C.; Barbe, F.

    2017-10-01

    Samples of 316L austenitic stainless steel with bimodal grain size distributions are elaborated using two distinct routes. The first one is based on powder metallurgy using spark plasma sintering of two powders with different particle sizes. The second route applies the reverse-annealing method: it consists in inducing martensitic phase transformation by plastic strain and further annealing in order to obtain two austenitic grain populations with different sizes. Microstructural analy ses reveal that both methods are suitable to generate significative grain size contrast and to control this contrast according to the elaboration conditions. Mechanical properties under tension are then characterized for different grain size distributions. Crystal plasticity finite element modelling is further applied in a configuration of bimodal distribution to analyse the role played by coarse grains within a matrix of fine grains, considering not only their volume fraction but also their spatial arrangement.

  8. Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments.

    Science.gov (United States)

    Bi, Ran; Liu, Peng

    2016-03-31

    RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments. In this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method. Our proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network ( http://cran.r-project.org ).

  9. Generalized SAMPLE SIZE Determination Formulas for Investigating Contextual Effects by a Three-Level Random Intercept Model.

    Science.gov (United States)

    Usami, Satoshi

    2017-03-01

    Behavioral and psychological researchers have shown strong interests in investigating contextual effects (i.e., the influences of combinations of individual- and group-level predictors on individual-level outcomes). The present research provides generalized formulas for determining the sample size needed in investigating contextual effects according to the desired level of statistical power as well as width of confidence interval. These formulas are derived within a three-level random intercept model that includes one predictor/contextual variable at each level to simultaneously cover various kinds of contextual effects that researchers can show interest. The relative influences of indices included in the formulas on the standard errors of contextual effects estimates are investigated with the aim of further simplifying sample size determination procedures. In addition, simulation studies are performed to investigate finite sample behavior of calculated statistical power, showing that estimated sample sizes based on derived formulas can be both positively and negatively biased due to complex effects of unreliability of contextual variables, multicollinearity, and violation of assumption regarding the known variances. Thus, it is advisable to compare estimated sample sizes under various specifications of indices and to evaluate its potential bias, as illustrated in the example.

  10. Characterizing the size distribution of particles in urban stormwater by use of fixed-point sample-collection methods

    Science.gov (United States)

    Selbig, William R.; Bannerman, Roger T.

    2011-01-01

    The U.S Geological Survey, in cooperation with the Wisconsin Department of Natural Resources (WDNR) and in collaboration with the Root River Municipal Stormwater Permit Group monitored eight urban source areas representing six types of source areas in or near Madison, Wis. in an effort to improve characterization of particle-size distributions in urban stormwater by use of fixed-point sample collection methods. The types of source areas were parking lot, feeder street, collector street, arterial street, rooftop, and mixed use. This information can then be used by environmental managers and engineers when selecting the most appropriate control devices for the removal of solids from urban stormwater. Mixed-use and parking-lot study areas had the lowest median particle sizes (42 and 54 (u or mu)m, respectively), followed by the collector street study area (70 (u or mu)m). Both arterial street and institutional roof study areas had similar median particle sizes of approximately 95 (u or mu)m. Finally, the feeder street study area showed the largest median particle size of nearly 200 (u or mu)m. Median particle sizes measured as part of this study were somewhat comparable to those reported in previous studies from similar source areas. The majority of particle mass in four out of six source areas was silt and clay particles that are less than 32 (u or mu)m in size. Distributions of particles ranging from 500 (u or mu)m were highly variable both within and between source areas. Results of this study suggest substantial variability in data can inhibit the development of a single particle-size distribution that is representative of stormwater runoff generated from a single source area or land use. Continued development of improved sample collection methods, such as the depth-integrated sample arm, may reduce variability in particle-size distributions by mitigating the effect of sediment bias inherent with a fixed-point sampler.

  11. An HPLC-MALDI MS method for N-glycan analyses using smaller size samples: application to monitor glycan modulation by medium conditions.

    Science.gov (United States)

    Gillmeister, Michael P; Tomiya, Noboru; Jacobia, Scott J; Lee, Yuan C; Gorfien, Stephen F; Betenbaugh, Michael J

    2009-12-01

    Existing HPLC methods can provide detailed structure and isomeric information, but are often slow and require large initial sample sizes. In this study, a previously established two-dimensional HPLC technique was adapted to a two-step identification method for smaller sample sizes. After cleavage from proteins, purification, and fluorescent labeling, glycans were analyzed on a 2-mm reverse phase HPLC column on a conventional HPLC and spotted onto a MALDI-TOF MS plate using an automated plate spotter to determine molecular weights. A direct correlation was found for 25 neutral oligosaccharides between the 2-mm Shim-Pack VP-ODS HPLC column (Shimadzu) and the 6-mm CLC-ODS column (Shimadzu) of the standard two- and three-dimensional methods. The increased throughput adaptations allowed a 100-fold reduction in required amounts of starting protein. The entire process can be carried out in 2-3 days for a large number of samples as compared to 1-2 weeks per sample for previous two-dimensional HPLC methods. The modified method was verified by identifying N-glycan structures, including specifying two different galactosylated positional isomers, of an IgG antibody from human sera samples. Analysis of tissue plasminogen activator (t-PA) from CHO cell cultures under varying culture conditions illustrated how the method can identify changes in oligosaccharide structure in the presence of different media environments. Raising glutamine concentrations or adding ammonia directly to the culture led to decreased galactosylation, while substituting GlutaMAX-I, a dipeptide of L-alanine and L-glutamine, resulted in structures with more galactosylation. This modified system will enable glycoprofiling of smaller glycoprotein samples in a shorter time period and allow a more rapid evaluation of the effects of culture conditions on expressed protein glycosylation.

  12. Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

    Directory of Open Access Journals (Sweden)

    Simon Boitard

    2016-03-01

    Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

  13. Sample size estimation to substantiate freedom from disease for clustered binary data with a specific risk profile

    DEFF Research Database (Denmark)

    Kostoulas, P.; Nielsen, Søren Saxmose; Browne, W. J.

    2013-01-01

    SUMMARY Disease cases are often clustered within herds or generally groups that share common characteristics. Sample size formulae must adjust for the within-cluster correlation of the primary sampling units. Traditionally, the intra-cluster correlation coefficient (ICC), which is an average meas...... subsp. paratuberculosis infection, in Danish dairy cattle and a study on critical control points for Salmonella cross-contamination of pork, in Greek slaughterhouses....

  14. Validation of fixed sample size plans for monitoring lepidopteran pests of Brassica oleracea crops in North Korea.

    Science.gov (United States)

    Hamilton, A J; Waters, E K; Kim, H J; Pak, W S; Furlong, M J

    2009-06-01

    The combined action of two lepidoteran pests, Plutella xylostella L. (Plutellidae) and Pieris rapae L. (Pieridae),causes significant yield losses in cabbage (Brassica oleracea variety capitata) crops in the Democratic People's Republic of Korea. Integrated pest management (IPM) strategies for these cropping systems are in their infancy, and sampling plans have not yet been developed. We used statistical resampling to assess the performance of fixed sample size plans (ranging from 10 to 50 plants). First, the precision (D = SE/mean) of the plans in estimating the population mean was assessed. There was substantial variation in achieved D for all sample sizes, and sample sizes of at least 20 and 45 plants were required to achieve the acceptable precision level of D < or = 0.3 at least 50 and 75% of the time, respectively. Second, the performance of the plans in classifying the population density relative to an economic threshold (ET) was assessed. To account for the different damage potentials of the two species the ETs were defined in terms of standard insects (SIs), where 1 SI = 1 P. rapae = 5 P. xylostella larvae. The plans were implemented using different economic thresholds (ETs) for the three growth stages of the crop: precupping (1 SI/plant), cupping (0.5 SI/plant), and heading (4 SI/plant). Improvement in the classification certainty with increasing sample sizes could be seen through the increasing steepness of operating characteristic curves. Rather than prescribe a particular plan, we suggest that the results of these analyses be used to inform practitioners of the relative merits of the different sample sizes.

  15. Sample size estimates for determining treatment effects in high-risk patients with early relapsing-remitting multiple sclerosis.

    Science.gov (United States)

    Scott, Thomas F; Schramke, Carol J; Cutter, Gary

    2003-06-01

    Risk factors for short-term progression in early relapsing remitting MS have been identified recently. Previously we determined potential risk factors for rapid progression of early relapsing remitting MS and identified three groups of high-risk patients. These non-mutually exclusive groups of patients were drawn from a consecutively studied sample of 98 patients with newly diagnosed MS. High-risk patients had a history of either poor recovery from initial attacks, more than two attacks in the first two years of disease, or a combination of at least four other risk factors. To determine differences in sample sizes required to show a meaningful treatment effect when using a high-risk sample versus a random sample of patients. Power analyses were used to calculate the different sample sizes needed for hypothetical treatment trials. We found that substantially smaller numbers of patients should be needed to show a significant treatment effect by employing these high-risk groups of patients as compared to a random population of MS patients (e.g., 58% reduction in sample size in one model). The use of patients at higher risk of progression to perform drug treatment trials can be considered as a means to reduce the number of patients needed to show a significant treatment effect for patients with very early MS.

  16. Strategies for the inclusion of an internal amplification control in conventional and real time PCR detection of Campylobacter spp. in chicken fecal samples

    DEFF Research Database (Denmark)

    Lund, Marianne; Madsen, Mogens

    2006-01-01

    To illustrate important issues in optimization of a PCR assay with an internal control four different primer combinations for conventional PCR, two non-competitive and two competitive set-ups for real time PCR were used for detection of Campylobacter spp. in chicken faecal samples....... In the conventional PCR assays the internal control was genomic DNA from Yersinia ruckeri, which is not found in chicken faeces. This internal control was also used in one of the set LIPS in real time PCR. In the three other set-ups different DNA fragments of 109 bp length prepared from two oligos of each 66 bp...... against faecal inhibitors to ensure that the internal control and the target PCR had the same sensitivity towards inhibitors....

  17. A simple method to generate equal-sized homogenous strata or clusters for population-based sampling.

    Science.gov (United States)

    Elliott, Michael R

    2011-04-01

    Statistical efficiency and cost efficiency can be achieved in population-based samples through stratification and/or clustering. Strata typically combine subgroups of the population that are similar with respect to an outcome. Clusters are often taken from preexisting units, but may be formed to minimize between-cluster variance, or to equalize exposure to a treatment or risk factor. Area probability sample design procedures for the National Children's Study required contiguous strata and clusters that maximized within-stratum and within-cluster homogeneity while maintaining approximately equal size of the strata or clusters. However, there were few methods that allowed such strata or clusters to be constructed under these contiguity and equal size constraints. A search algorithm generates equal-size cluster sets that approximately span the space of all possible clusters of equal size. An optimal cluster set is chosen based on analysis of variance and convexity criteria. The proposed algorithm is used to construct 10 strata based on demographics and air pollution measures in Kent County, MI, following census tract boundaries. A brief simulation study is also conducted. The proposed algorithm is effective at uncovering underlying clusters from noisy data. It can be used in multi-stage sampling where equal-size strata or clusters are desired. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Effects of sample size on differential gene expression, rank order and prediction accuracy of a gene signature.

    Directory of Open Access Journals (Sweden)

    Cynthia Stretch

    Full Text Available Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65 ♀ in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n = 10 (5 ♂, 5 ♀ to n = 120 (60 ♂, 60 ♀ thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n = 134, we identified 717 differentially expressed transcripts (p<0.0001 and we were able predict sex with ~90% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n = 10 (5 ♂, 5 ♀, no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ~50% (no better than chance. We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.

  19. Annual design-based estimation for the annualized inventories of forest inventory and analysis: sample size determination

    Science.gov (United States)

    Hans T. Schreuder; Jin-Mann S. Lin; John Teply

    2000-01-01

    The Forest Inventory and Analysis units in the USDA Forest Service have been mandated by Congress to go to an annualized inventory where a certain percentage of plots, say 20 percent, will be measured in each State each year. Although this will result in an annual sample size that will be too small for reliable inference for many areas, it is a sufficiently large...

  20. Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

    NARCIS (Netherlands)

    Uijlenhoet, R.; Porrà, J.M.; Sempere Torres, D.; Creutin, J.D.

    2006-01-01

    A stochastic model of the microstructure of rainfall is used to derive explicit expressions for the magnitude of the sampling fluctuations in rainfall properties estimated from raindrop size measurements in stationary rainfall. The model is a marked point process, in which the points represent the

  1. Survey Research: Determining Sample Size and Representative Response. and The Effects of Computer Use on Keyboarding Technique and Skill.

    Science.gov (United States)

    Wunsch, Daniel R.; Gades, Robert E.

    1986-01-01

    Two articles are presented. The first reviews and suggests procedures for determining appropriate sample sizes and for determining the response representativeness in survey research. The second presents a study designed to determine the effects of computer use on keyboarding technique and skill. (CT)

  2. Population Validity and Cross-Validity: Applications of Distribution Theory for Testing Hypotheses, Setting Confidence Intervals, and Determining Sample Size

    Science.gov (United States)

    Algina, James; Keselman, H. J.

    2008-01-01

    Applications of distribution theory for the squared multiple correlation coefficient and the squared cross-validation coefficient are reviewed, and computer programs for these applications are made available. The applications include confidence intervals, hypothesis testing, and sample size selection. (Contains 2 tables.)

  3. Methods for flexible sample-size design in clinical trials: Likelihood, weighted, dual test, and promising zone approaches.

    Science.gov (United States)

    Shih, Weichung Joe; Li, Gang; Wang, Yining

    2016-03-01

    Sample size plays a crucial role in clinical trials. Flexible sample-size designs, as part of the more general category of adaptive designs that utilize interim data, have been a popular topic in recent years. In this paper, we give a comparative review of four related methods for such a design. The likelihood method uses the likelihood ratio test with an adjusted critical value. The weighted method adjusts the test statistic with given weights rather than the critical value. The dual test method requires both the likelihood ratio statistic and the weighted statistic to be greater than the unadjusted critical value. The promising zone approach uses the likelihood ratio statistic with the unadjusted value and other constraints. All four methods preserve the type-I error rate. In this paper we explore their properties and compare their relationships and merits. We show that the sample size rules for the dual test are in conflict with the rules of the promising zone approach. We delineate what is necessary to specify in the study protocol to ensure the validity of the statistical procedure and what can be kept implicit in the protocol so that more flexibility can be attained for confirmatory phase III trials in meeting regulatory requirements. We also prove that under mild conditions, the likelihood ratio test still preserves the type-I error rate when the actual sample size is larger than the re-calculated one. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Comparison of fused-core and conventional particle size columns by LC-MS/MS and UV: application to pharmacokinetic study.

    Science.gov (United States)

    Song, Wei; Pabbisetty, Deepthi; Groeber, Elizabeth A; Steenwyk, Rick C; Fast, Douglas M

    2009-10-15

    The chromatographic performance of fused-core (superficially porous) HPLC packing materials was compared with conventional fully porous particle materials for LC-MS/MS analysis of two pharmaceuticals in rat plasma. Two commercially available antidepressants, imipramine and desipramine, were assayed using a conventional analytical C(18) column (5 microm, 2.0 mm x 30 mm) and a fused-core C(18) column (2.7 microm, 2.1 mm x 30 mm). Retention time, column efficiency, pressure drop, resolution, and loading capacity were compared under the same operating conditions. The fused-core column demonstrated reduced assay time by 34% and 2-3-fold increased efficiency (N). Loading capacity up to 25 microl of extract injected on column showed no peak distortion. The registered back-pressure from a flow rate of 1.0 ml/min did not exceed 3400 psi making it compatible with standard HPLC equipment (typically rated to 6000 psi). Two mobile phases were examined, and morpholine as an organic base modifier yielded a 2-5-fold increase in S/N near the limit of detection over triethylamine. The 2.7 microm fused-core column was applied to the analysis of imipramine and desipramine in extracted, protein precipitated rat plasma by LC-MS/MS. The calibration curves were linear in the concentration range of 0.5-1000 ng/ml for both imipramine and desipramine. Intra-run precisions (%CV) and accuracies (%bias) were within +/-7.8% and +/-7.3% at three QC levels and within 14.7% and 14.4% at the LOQ level for both analytes. Following a single method qualification run, the method was applied to the quantitation of pharmacokinetic study samples after oral administration of imipramine to male rats.

  5. Bayesian adaptive approach to estimating sample sizes for seizures of illicit drugs.

    Science.gov (United States)

    Moroni, Rossana; Aalberg, Laura; Reinikainen, Tapani; Corander, Jukka

    2012-01-01

    A considerable amount of discussion can be found in the forensics literature about the issue of using statistical sampling to obtain for chemical analyses an appropriate subset of units from a police seizure suspected to contain illicit material. Use of the Bayesian paradigm has been suggested as the most suitable statistical approach to solving the question of how large a sample needs to be to ensure legally and practically acceptable purposes. Here, we introduce a hypergeometric sampling model combined with a specific prior distribution for the homogeneity of the seizure, where a parameter for the analyst's expectation of homogeneity (α) is included. Our results show how an adaptive approach to sampling can minimize the practical efforts needed in the laboratory analyses, as the model allows the scientist to decide sequentially how to proceed, while maintaining a sufficiently high confidence in the conclusions. © 2011 American Academy of Forensic Sciences.

  6. Measuring proteins with greater speed and resolution while reducing sample size

    OpenAIRE

    Hsieh, Vincent H.; Wyatt, Philip J.

    2017-01-01

    A multi-angle light scattering (MALS) system, combined with chromatographic separation, directly measures the absolute molar mass, size and concentration of the eluate species. The measurement of these crucial properties in solution is essential in basic macromolecular characterization and all research and production stages of bio-therapeutic products. We developed a new MALS methodology that has overcome the long-standing, stubborn barrier to microliter-scale peak volumes and achieved the hi...

  7. Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats

    Science.gov (United States)

    Ellison, Laura E.; Lukacs, Paul M.

    2014-01-01

    Concern for migratory tree-roosting bats in North America has grown because of possible population declines from wind energy development. This concern has driven interest in estimating population-level changes. Mark-recapture methodology is one possible analytical framework for assessing bat population changes, but sample size requirements to produce reliable estimates have not been estimated. To illustrate the sample sizes necessary for a mark-recapture-based monitoring program we conducted power analyses using a statistical model that allows reencounters of live and dead marked individuals. We ran 1,000 simulations for each of five broad sample size categories in a Burnham joint model, and then compared the proportion of simulations in which 95% confidence intervals overlapped between and among years for a 4-year study. Additionally, we conducted sensitivity analyses of sample size to various capture probabilities and recovery probabilities. More than 50,000 individuals per year would need to be captured and released to accurately determine 10% and 15% declines in annual survival. To detect more dramatic declines of 33% or 50% survival over four years, then sample sizes of 25,000 or 10,000 per year, respectively, would be sufficient. Sensitivity analyses reveal that increasing recovery of dead marked individuals may be more valuable than increasing capture probability of marked individuals. Because of the extraordinary effort that would be required, we advise caution should such a mark-recapture effort be initiated because of the difficulty in attaining reliable estimates. We make recommendations for what techniques show the most promise for mark-recapture studies of bats because some techniques violate the assumptions of mark-recapture methodology when used to mark bats.

  8. Sample Size Effect of Magnetomechanical Response for Magnetic Elastomers by Using Permanent Magnets

    Directory of Open Access Journals (Sweden)

    Tsubasa Oguro

    2017-01-01

    Full Text Available The size effect of magnetomechanical response of chemically cross-linked disk shaped magnetic elastomers placed on a permanent magnet has been investigated by unidirectional compression tests. A cylindrical permanent magnet with a size of 35 mm in diameter and 15 mm in height was used to create the magnetic field. The magnetic field strength was approximately 420 mT at the center of the upper surface of the magnet. The diameter of the magnetoelastic polymer disks was varied from 14 mm to 35 mm, whereas the height was kept constant (5 mm in the undeformed state. We have studied the influence of the disk diameter on the stress-strain behavior of the magnetoelastic in the presence and in the lack of magnetic field. It was found that the smallest magnetic elastomer with 14 mm diameter did not exhibit measurable magnetomechanical response due to magnetic field. On the opposite, the magnetic elastomers with diameters larger than 30 mm contracted in the direction parallel to the mechanical stress and largely elongated in the perpendicular direction. An explanation is put forward to interpret this size-dependent behavior by taking into account the nonuniform field distribution of magnetic field produced by the permanent magnet.

  9. Measurements of Plutonium and Americium in Soil Samples from Project 57 using the Suspended Soil Particle Sizing System (SSPSS)

    Energy Technology Data Exchange (ETDEWEB)

    John L. Bowen; Rowena Gonzalez; David S. Shafer

    2001-05-01

    As part of the preliminary site characterization conducted for Project 57, soils samples were collected for separation into several size-fractions using the Suspended Soil Particle Sizing System (SSPSS). Soil samples were collected specifically for separation by the SSPSS at three general locations in the deposited Project 57 plume, the projected radioactivity of which ranged from 100 to 600 pCi/g. The primary purpose in focusing on samples with this level of activity is that it would represent anticipated residual soil contamination levels at the site after corrective actions are completed. Consequently, the results of the SSPSS analysis can contribute to dose calculation and corrective action-level determinations for future land-use scenarios at the site.

  10. Sample size requirements to estimate key design parameters from external pilot randomised controlled trials: a simulation study.

    Science.gov (United States)

    Teare, M Dawn; Dimairo, Munyaradzi; Shephard, Neil; Hayman, Alex; Whitehead, Amy; Walters, Stephen J

    2014-07-03

    External pilot or feasibility studies can be used to estimate key unknown parameters to inform the design of the definitive randomised controlled trial (RCT). However, there is little consensus on how large pilot studies need to be, and some suggest inflating estimates to adjust for the lack of precision when planning the definitive RCT. We use a simulation approach to illustrate the sampling distribution of the standard deviation for continuous outcomes and the event rate for binary outcomes. We present the impact of increasing the pilot sample size on the precision and bias of these estimates, and predicted power under three realistic scenarios. We also illustrate the consequences of using a confidence interval argument to inflate estimates so the required power is achieved with a pre-specified level of confidence. We limit our attention to external pilot and feasibility studies prior to a two-parallel-balanced-group superiority RCT. For normally distributed outcomes, the relative gain in precision of the pooled standard deviation (SDp) is less than 10% (for each five subjects added per group) once the total sample size is 70. For true proportions between 0.1 and 0.5, we find the gain in precision for each five subjects added to the pilot sample is less than 5% once the sample size is 60. Adjusting the required sample sizes for the imprecision in the pilot study estimates can result in excessively large definitive RCTs and also requires a pilot sample size of 60 to 90 for the true effect sizes considered here. We recommend that an external pilot study has at least 70 measured subjects (35 per group) when estimating the SDp for a continuous outcome. If the event rate in an intervention group needs to be estimated by the pilot then a total of 60 to 100 subjects is required. Hence if the primary outcome is binary a total of at least 120 subjects (60 in each group) may be required in the pilot trial. It is very much more efficient to use a larger pilot study, than to

  11. A convenient method and numerical tables for sample size determination in longitudinal-experimental research using multilevel models.

    Science.gov (United States)

    Usami, Satoshi

    2014-12-01

    Recent years have shown increased awareness of the importance of sample size determination in experimental research. Yet effective and convenient methods for sample size determination, especially in longitudinal experimental design, are still under development, and application of power analysis in applied research remains limited. This article presents a convenient method for sample size determination in longitudinal experimental research using a multilevel model. A fundamental idea of this method is transformation of model parameters (level 1 error variance [σ(2)], level 2 error variances [τ 00, τ 11] and its covariance [τ 01, τ 10], and a parameter representing experimental effect [δ]) into indices (reliability of measurement at the first time point [ρ 1], effect size at the last time point [Δ T ], proportion of variance of outcomes between the first and the last time points [k], and level 2 error correlation [r]) that are intuitively understandable and easily specified. To foster more convenient use of power analysis, numerical tables are constructed that refer to ANOVA results to investigate the influence on statistical power by respective indices.

  12. [Comparison of characteristics of heavy metals in different grain sizes of intertidalite sediment by using grid sampling method].

    Science.gov (United States)

    Liang, Tao; Chen, Yan; Zhang, Chao-sheng; Li, Hai-tao; Chong, Zhong-yi; Song, Wen-chong

    2008-02-01

    384 surface sediment samples were collected from mud flat, silt flat and mud-silt flat of Bohai Bay by 1 m and 10 m interval using grid sampling method. Concentrations of Al, Fe, Ti, Mn, Ba, Sr, Zn, Cr, Ni and Cu in each sample were measured by ICP-AES. To figure out the random distribution and concentration characteristics of these heavy metals, concentration of them were compared between districts with different grain size. The results show that varieties of grain size cause the remarkable difference in the concentration of heavy metals. Total concentration of heavy metals are 147.37 g x kg(-1), 98.68 g x kg(-1) and 94.27 g x kg(-1) in mud flat, mud-silt flat and silt flat respectively. Majority of heavy metals inclines to concentrate in fine grained mud, while Ba and Sr have a tendency to concentrate in coast grained silt which contains more K2O * Al2O3 * 6SiO2. Concentration of Sr is affected significantly by the grain size, while concentration of Cr and Ti are affected a little by the grain size.

  13. A multi-scale study of Orthoptera species richness and human population size controlling for sampling effort.

    Science.gov (United States)

    Cantarello, Elena; Steck, Claude E; Fontana, Paolo; Fontaneto, Diego; Marini, Lorenzo; Pautasso, Marco

    2010-03-01

    Recent large-scale studies have shown that biodiversity-rich regions also tend to be densely populated areas. The most obvious explanation is that biodiversity and human beings tend to match the distribution of energy availability, environmental stability and/or habitat heterogeneity. However, the species-people correlation can also be an artefact, as more populated regions could show more species because of a more thorough sampling. Few studies have tested this sampling bias hypothesis. Using a newly collated dataset, we studied whether Orthoptera species richness is related to human population size in Italy's regions (average area 15,000 km(2)) and provinces (2,900 km(2)). As expected, the observed number of species increases significantly with increasing human population size for both grain sizes, although the proportion of variance explained is minimal at the provincial level. However, variations in observed Orthoptera species richness are primarily associated with the available number of records, which is in turn well correlated with human population size (at least at the regional level). Estimated Orthoptera species richness (Chao2 and Jackknife) also increases with human population size both for regions and provinces. Both for regions and provinces, this increase is not significant when controlling for variation in area and number of records. Our study confirms the hypothesis that broad-scale human population-biodiversity correlations can in some cases be artefactual. More systematic sampling of less studied taxa such as invertebrates is necessary to ascertain whether biogeographical patterns persist when sampling effort is kept constant or included in models.

  14. A multi-scale study of Orthoptera species richness and human population size controlling for sampling effort

    Science.gov (United States)

    Cantarello, Elena; Steck, Claude E.; Fontana, Paolo; Fontaneto, Diego; Marini, Lorenzo; Pautasso, Marco

    2010-03-01

    Recent large-scale studies have shown that biodiversity-rich regions also tend to be densely populated areas. The most obvious explanation is that biodiversity and human beings tend to match the distribution of energy availability, environmental stability and/or habitat heterogeneity. However, the species-people correlation can also be an artefact, as more populated regions could show more species because of a more thorough sampling. Few studies have tested this sampling bias hypothesis. Using a newly collated dataset, we studied whether Orthoptera species richness is related to human population size in Italy’s regions (average area 15,000 km2) and provinces (2,900 km2). As expected, the observed number of species increases significantly with increasing human population size for both grain sizes, although the proportion of variance explained is minimal at the provincial level. However, variations in observed Orthoptera species richness are primarily associated with the available number of records, which is in turn well correlated with human population size (at least at the regional level). Estimated Orthoptera species richness (Chao2 and Jackknife) also increases with human population size both for regions and provinces. Both for regions and provinces, this increase is not significant when controlling for variation in area and number of records. Our study confirms the hypothesis that broad-scale human population-biodiversity correlations can in some cases be artefactual. More systematic sampling of less studied taxa such as invertebrates is necessary to ascertain whether biogeographical patterns persist when sampling effort is kept constant or included in models.

  15. Children's Use of Sample Size and Diversity Information within Basic-Level Categories.

    Science.gov (United States)

    Gutheil, Grant; Gelman, Susan A.

    1997-01-01

    Three studies examined the ability of 8- and 9-year-olds and young adults to use sample monotonicity and diversity information according to the similarity-coverage model of category-based induction. Found that children's difficulty with this information was independent of category level, and may be based on preferences for other strategies…

  16. Joint risk of interbasin water transfer and impact of the window size of sampling low flows under environmental change

    Science.gov (United States)

    Tu, Xinjun; Du, Xiaoxia; Singh, Vijay P.; Chen, Xiaohong; Du, Yiliang; Li, Kun

    2017-11-01

    Constructing a joint distribution of low flows between the donor and recipient basins and analyzing their joint risk are commonly required for implementing interbasin water transfer. In this study, daily streamflow data of bi-basin low flows were sampled at window sizes from 3 to183 days by using the annual minimum method. The stationarity of low flows was tested by a change point analysis and non-stationary low flows were reconstructed by using the moving mean method. Three bivariate Archimedean copulas and five common univariate distributions were applied to fit the joint and marginal distributions of bi-basin low flows. Then, by considering the window size of sampling low flows under environmental change, the change in the joint risk of interbasin water transfer was investigated. Results showed that the non-stationarity of low flows in the recipient basin at all window sizes was significant due to the regulation of water reservoirs. The general extreme value distribution was found to fit the marginal distributions of bi-basin low flows. Three Archimedean copulas satisfactorily fitted the joint distribution of bi-basin low flows and then the Frank copula was found to be the comparatively better. The moving mean method differentiated the location parameter of the GEV distribution, but did not differentiate the scale and shape parameters, and the copula parameters. Due to environmental change, in particular the regulation of water reservoirs in the recipient basin, the decrease of the joint synchronous risk of bi-basin water shortage was slight, but those of the synchronous assurance of water transfer from the donor were remarkable. With the enlargement of window size of sampling low flows, both the joint synchronous risk of bi-basin water shortage, and the joint synchronous assurance of water transfer from the donor basin when there was a water shortage in the recipient basin exhibited a decreasing trend, but their changes were with a slight fluctuation, in

  17. Size-dependent ultrafast ionization dynamics of nanoscale samples in intense femtosecond x-ray free-electron-laser pulses.

    Science.gov (United States)

    Schorb, Sebastian; Rupp, Daniela; Swiggers, Michelle L; Coffee, Ryan N; Messerschmidt, Marc; Williams, Garth; Bozek, John D; Wada, Shin-Ichi; Kornilov, Oleg; Möller, Thomas; Bostedt, Christoph

    2012-06-08

    All matter exposed to intense femtosecond x-ray pulses from the Linac Coherent Light Source free-electron laser is strongly ionized on time scales competing with the inner-shell vacancy lifetimes. We show that for nanoscale objects the environment, i.e., nanoparticle size, is an important parameter for the time-dependent ionization dynamics. The Auger lifetimes of large Ar clusters are found to be increased compared to small clusters and isolated atoms, due to delocalization of the valence electrons in the x-ray-induced nanoplasma. As a consequence, large nanometer-sized samples absorb intense femtosecond x-ray pulses less efficiently than small ones.

  18. Quantification and size characterisation of silver nanoparticles in environmental aqueous samples and consumer products by single particle-ICPMS.

    Science.gov (United States)

    Aznar, Ramón; Barahona, Francisco; Geiss, Otmar; Ponti, Jessica; José Luis, Tadeo; Barrero-Moreno, Josefa

    2017-12-01

    Single particle-inductively coupled plasma mass spectrometry (SP-ICPMS) is a promising technique able to generate the number based-particle size distribution (PSD) of nanoparticles (NPs) in aqueous suspensions. However, SP-ICPMS analysis is not consolidated as routine-technique yet and is not typically applied to real test samples with unknown composition. This work presents a methodology to detect, quantify and characterise the number-based PSD of Ag-NPs in different environmental aqueous samples (drinking and lake waters), aqueous samples derived from migration tests and consumer products using SP-ICPMS. The procedure is built from a pragmatic view and involves the analysis of serial dilutions of the original sample until no variation in the measured size values is observed while keeping particle counts proportional to the dilution applied. After evaluation of the analytical figures of merit, the SP-ICPMS method exhibited excellent linearity (r2>0.999) in the range (1-25) × 104 particlesmL-1 for 30, 50 and 80nm nominal size Ag-NPs standards. The precision in terms of repeatability was studied according to the RSDs of the measured size and particle number concentration values and a t-test (p = 95%) at the two intermediate concentration levels was applied to determine the bias of SP-ICPMS size values compared to reference values. The method showed good repeatability and an overall acceptable bias in the studied concentration range. The experimental minimum detectable size for Ag-NPs ranged between 12 and 15nm. Additionally, results derived from direct SP-ICPMS analysis were compared to the results conducted for fractions collected by asymmetric flow-field flow fractionation and supernatant fractions after centrifugal filtration. The method has been successfully applied to determine the presence of Ag-NPs in: lake water; tap water; tap water filtered by a filter jar; seven different liquid silver-based consumer products; and migration solutions (pure water and

  19. Sample size calculation based on generalized linear models for differential expression analysis in RNA-seq data.

    Science.gov (United States)

    Li, Chung-I; Shyr, Yu

    2016-12-01

    As RNA-seq rapidly develops and costs continually decrease, the quantity and frequency of samples being sequenced will grow exponentially. With proteomic investigations becoming more multivariate and quantitative, determining a study's optimal sample size is now a vital step in experimental design. Current methods for calculating a study's required sample size are mostly based on the hypothesis testing framework, which assumes each gene count can be modeled through Poisson or negative binomial distributions; however, these methods are limited when it comes to accommodating covariates. To address this limitation, we propose an estimating procedure based on the generalized linear model. This easy-to-use method constructs a representative exemplary dataset and estimates the conditional power, all without requiring complicated mathematical approximations or formulas. Even more attractive, the downstream analysis can be performed with current R/Bioconductor packages. To demonstrate the practicability and efficiency of this method, we apply it to three real-world studies, and introduce our on-line calculator developed to determine the optimal sample size for a RNA-seq study.

  20. A spectroscopic sample of massive, quiescent z ∼ 2 galaxies: implications for the evolution of the mass-size relation

    Energy Technology Data Exchange (ETDEWEB)

    Krogager, J.-K.; Zirm, A. W.; Toft, S.; Man, A. [Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen O (Denmark); Brammer, G. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21210 (United States)

    2014-12-10

    We present deep, near-infrared Hubble Space Telescope/Wide Field Camera 3 grism spectroscopy and imaging for a sample of 14 galaxies at z ≈ 2 selected from a mass-complete photometric catalog in the COSMOS field. By combining the grism observations with photometry in 30 bands, we derive accurate constraints on their redshifts, stellar masses, ages, dust extinction, and formation redshifts. We show that the slope and scatter of the z ∼ 2 mass-size relation of quiescent galaxies is consistent with the local relation, and confirm previous findings that the sizes for a given mass are smaller by a factor of two to three. Finally, we show that the observed evolution of the mass-size relation of quiescent galaxies between z = 2 and 0 can be explained by the quenching of increasingly larger star forming galaxies at a rate dictated by the increase in the number density of quiescent galaxies with decreasing redshift. However, we find that the scatter in the mass-size relation should increase in the quenching-driven scenario in contrast to what is seen in the data. This suggests that merging is not needed to explain the evolution of the median mass-size relation of massive galaxies, but may still be required to tighten its scatter, and explain the size growth of individual z = 2 galaxies quiescent galaxies.

  1. Sample size requirements for studies of treatment effects on beta-cell function in newly diagnosed type 1 diabetes.

    Directory of Open Access Journals (Sweden)

    John M Lachin

    Full Text Available Preservation of β-cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet, repeated 2-hour Mixed Meal Tolerance Tests (MMTT were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC of the C-peptide values. The natural log(x, log(x+1 and square-root (√x transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8-12 years of age, adolescents (13-17 years and adults (18+ years. The sample size needed to detect a given relative (percentage difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13-17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(x+1 and √x transformed values in terms of the original units of measurement (pmol/ml. Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab versus masked placebo. These results provide the information needed to

  2. Comparison of conventional PCR, quantitative PCR, bacteriological culture and the Warthin Starry technique to detect Leptospira spp. in kidney and liver samples from naturally infected sheep from Brazil.

    Science.gov (United States)

    Fornazari, Felipe; da Silva, Rodrigo Costa; Richini-Pereira, Virginia Bodelão; Beserra, Hugo Enrique Orsini; Luvizotto, Maria Cecília Rui; Langoni, Helio

    2012-09-01

    Leptospirosis is an infectious disease of worldwide importance. The development of diagnostic techniques allows sick animals to be identified, reservoirs to be eliminated and the disease prevented and controlled. The present study aimed to compare different techniques for diagnosing leptospirosis in sheep. Samples of kidney, liver and blood were collected from 465 animals that originated from a slaughterhouse. The sera were analyzed by the Microscopic Agglutination Test (MAT), and kidney and liver samples of seropositive animals were analyzed using four techniques: bacteriological culture, the Warthin Starry (WS) technique, conventional PCR (cPCR), and quantitative PCR (qPCR). With the MAT, 21 animals were positive (4.5%) to serovars Hardjo (n=12), Hebdomadis (n=5), Sentot (n=2), Wolfii (n=1) and Shermani (n=1). Titers were 100 (n=10), 200 (n=2), 400 (n=6) and 1600 (n=3). No animal was positive by bacteriological culture; four animals were positive by the WS technique in kidney samples; six animals were positive by cPCR in kidney samples; and 11 animals were positive by qPCR, eight of which in kidney samples and three in liver. The bacterial quantification revealed a median of 4.3 bacteria/μL in liver samples and 36.6 bacteria/μL in kidney samples. qPCR presented the highest sensitivity among the techniques, followed by cPCR, the WS technique and bacteriological culture. These results indicate that sheep can carry leptospires of the Sejroe serogroup, and demonstrate the efficiency of quantitative PCR to detect Leptospira spp. in tissue samples. Published by Elsevier B.V.

  3. [Sample size for the estimation of F-wave parameters in healthy volunteers and amyotrophic lateral sclerosis patients].

    Science.gov (United States)

    Fang, J; Cui, L Y; Liu, M S; Guan, Y Z; Ding, Q Y; Du, H; Li, B H; Wu, S

    2017-03-07

    Objective: The study aimed to investigate whether sample sizes of F-wave study differed according to different nerves, different F-wave parameters, and amyotrophic lateral sclerosis(ALS) patients or healthy subjects. Methods: The F-waves in the median, ulnar, tibial, and deep peroneal nerves of 55 amyotrophic lateral sclerosis (ALS) patients and 52 healthy subjects were studied to assess the effect of sample size on the accuracy of measurements of the following F-wave parameters: F-wave minimum latency, maximum latency, mean latency, F-wave persistence, F-wave chronodispersion, mean and maximum F-wave amplitude. A hundred stimuli were used in F-wave study. The values obtained from 100 stimuli were considered "true" values and were compared with the corresponding values from smaller samples of 20, 40, 60 and 80 stimuli. F-wave parameters obtained from different sample sizes were compared between the ALS patients and the normal controls. Results: Significant differences were not detected with samples above 60 stimuli for chronodispersion in all four nerves in normal participants. Significant differences were not detected with samples above 40 stimuli for maximum F-wave amplitude in median, ulnar and tibial nerves in normal participants. When comparing ALS patients and normal controls, significant differences were detected in the maximum (median nerve, Z=-3.560, PF-wave latency (median nerve, Z=-3.243, PF-wave chronodispersion (Z=-3.152, PF-wave persistence in the median (Z=6.139, PF-wave amplitude in the tibial nerve(t=2.981, PF-wave amplitude in the ulnar (Z=-2.134, PF-wave persistence in tibial nerve (Z=2.119, PF-wave amplitude in ulnar (Z=-2.552, PF-wave amplitude in peroneal nerve (t=2.693, PF-wave study differed according to different nerves, different F-wave parameters , and ALS patients or healthy subjects.

  4. Sex determination by tooth size in a sample of Greek population.

    Science.gov (United States)

    Mitsea, A G; Moraitis, K; Leon, G; Nicopoulou-Karayianni, K; Spiliopoulou, C

    2014-08-01

    Sex assessment from tooth measurements can be of major importance for forensic and bioarchaeological investigations, especially when only teeth or jaws are available. The purpose of this study is to assess the reliability and applicability of establishing sex identity in a sample of Greek population using the discriminant function proposed by Rösing et al. (1995). The study comprised of 172 dental casts derived from two private orthodontic clinics in Athens. The individuals were randomly selected and all had clear medical history. The mesiodistal crown diameters of all the teeth were measured apart from those of the 3rd molars. The values quoted for the sample to which the discriminant function was first applied were similar to those obtained for the Greek sample. The results of the preliminary statistical analysis did not support the use of the specific discriminant function for a reliable determination of sex by means of the mesiodistal diameter of the teeth. However, there was considerable variation between different populations and this might explain the reason for lack of discriminating power of the specific function in the Greek population. In order to investigate whether a better discriminant function could be obtained using the Greek data, separate discriminant function analysis was performed on the same teeth and a different equation emerged without, however, any real improvement in the classification process, with an overall correct classification of 72%. The results showed that there were a considerably higher percentage of females correctly classified than males. The results lead to the conclusion that the use of the mesiodistal diameter of teeth is not as a reliable method as one would have expected for determining sex of human remains from a forensic context. Therefore, this method could be used only in combination with other identification approaches. Copyright © 2014. Published by Elsevier GmbH.

  5. Applicability of submerged jet model to describe the liquid sample load into measuring chamber of micron and submillimeter sizes

    Science.gov (United States)

    Bulyanitsa, A. L.; Belousov, K. I.; Evstrapov, A. A.

    2017-11-01

    The load of a liquid sample into a measuring chamber is one of the stages of substance analysis in modern devices. Fluid flow is effectively calculated by numerical simulation using application packages, for example, COMSOL MULTIPHYSICS. In the same time it is often desirable to have an approximate analytical solution. The applicability of a submerged jet model for simulation the liquid sample load is considered for the chamber with sizes from hundreds micrometers to several millimeters. The paper examines the extent to which the introduction of amendments to the jet cutting and its replacement with an energy equivalent jet provide acceptable accuracy for evaluation of the loading process dynamics.

  6. The N-Pact Factor: Evaluating the Quality of Empirical Journals with Respect to Sample Size and Statistical Power

    Science.gov (United States)

    Fraley, R. Chris; Vazire, Simine

    2014-01-01

    The authors evaluate the quality of research reported in major journals in social-personality psychology by ranking those journals with respect to their N-pact Factors (NF)—the statistical power of the empirical studies they publish to detect typical effect sizes. Power is a particularly important attribute for evaluating research quality because, relative to studies that have low power, studies that have high power are more likely to (a) to provide accurate estimates of effects, (b) to produce literatures with low false positive rates, and (c) to lead to replicable findings. The authors show that the average sample size in social-personality research is 104 and that the power to detect the typical effect size in the field is approximately 50%. Moreover, they show that there is considerable variation among journals in sample sizes and power of the studies they publish, with some journals consistently publishing higher power studies than others. The authors hope that these rankings will be of use to authors who are choosing where to submit their best work, provide hiring and promotion committees with a superior way of quantifying journal quality, and encourage competition among journals to improve their NF rankings. PMID:25296159

  7. The influence of sampling unit size and spatial arrangement patterns on neighborhood-based spatial structure analyses of forest stands

    Energy Technology Data Exchange (ETDEWEB)

    Wang, H.; Zhang, G.; Hui, G.; Li, Y.; Hu, Y.; Zhao, Z.

    2016-07-01

    Aim of study: Neighborhood-based stand spatial structure parameters can quantify and characterize forest spatial structure effectively. How these neighborhood-based structure parameters are influenced by the selection of different numbers of nearest-neighbor trees is unclear, and there is some disagreement in the literature regarding the appropriate number of nearest-neighbor trees to sample around reference trees. Understanding how to efficiently characterize forest structure is critical for forest management. Area of study: Multi-species uneven-aged forests of Northern China. Material and methods: We simulated stands with different spatial structural characteristics and systematically compared their structure parameters when two to eight neighboring trees were selected. Main results: Results showed that values of uniform angle index calculated in the same stand were different with different sizes of structure unit. When tree species and sizes were completely randomly interspersed, different numbers of neighbors had little influence on mingling and dominance indices. Changes of mingling or dominance indices caused by different numbers of neighbors occurred when the tree species or size classes were not randomly interspersed and their changing characteristics can be detected according to the spatial arrangement patterns of tree species and sizes. Research highlights: The number of neighboring trees selected for analyzing stand spatial structure parameters should be fixed. We proposed that the four-tree structure unit is the best compromise between sampling accuracy and costs for practical forest management. (Author)

  8. Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies

    Directory of Open Access Journals (Sweden)

    Finch Stephen J

    2005-04-01

    Full Text Available Abstract Background Phenotype error causes reduction in power to detect genetic association. We present a quantification of phenotype error, also known as diagnostic error, on power and sample size calculations for case-control genetic association studies between a marker locus and a disease phenotype. We consider the classic Pearson chi-square test for independence as our test of genetic association. To determine asymptotic power analytically, we compute the distribution's non-centrality parameter, which is a function of the case and control sample sizes, genotype frequencies, disease prevalence, and phenotype misclassification probabilities. We derive the non-centrality parameter in the presence of phenotype errors and equivalent formulas for misclassification cost (the percentage increase in minimum sample size needed to maintain constant asymptotic power at a fixed significance level for each percentage increase in a given misclassification parameter. We use a linear Taylor Series approximation for the cost of phenotype misclassification to determine lower bounds for the relative costs of misclassifying a true affected (respectively, unaffected as a control (respectively, case. Power is verified by computer simulation. Results Our major findings are that: (i the median absolute difference between analytic power with our method and simulation power was 0.001 and the absolute difference was no larger than 0.011; (ii as the disease prevalence approaches 0, the cost of misclassifying a unaffected as a case becomes infinitely large while the cost of misclassifying an affected as a control approaches 0. Conclusion Our work enables researchers to specifically quantify power loss and minimum sample size requirements in the presence of phenotype errors, thereby allowing for more realistic study design. For most diseases of current interest, verifying that cases are correctly classified is of paramount importance.

  9. Determining optimal sample sizes for multistage adaptive randomized clinical trials from an industry perspective using value of information methods.

    Science.gov (United States)

    Chen, Maggie H; Willan, Andrew R

    2013-02-01

    Most often, sample size determinations for randomized clinical trials are based on frequentist approaches that depend on somewhat arbitrarily chosen factors, such as type I and II error probabilities and the smallest clinically important difference. As an alternative, many authors have proposed decision-theoretic (full Bayesian) approaches, often referred to as value of information methods that attempt to determine the sample size that maximizes the difference between the trial's expected utility and its expected cost, referred to as the expected net gain. Taking an industry perspective, Willan proposes a solution in which the trial's utility is the increase in expected profit. Furthermore, Willan and Kowgier, taking a societal perspective, show that multistage designs can increase expected net gain. The purpose of this article is to determine the optimal sample size using value of information methods for industry-based, multistage adaptive randomized clinical trials, and to demonstrate the increase in expected net gain realized. At the end of each stage, the trial's sponsor must decide between three actions: continue to the next stage, stop the trial and seek regulatory approval, or stop the trial and abandon the drug. A model for expected total profit is proposed that includes consideration of per-patient profit, disease incidence, time horizon, trial duration, market share, and the relationship between trial results and probability of regulatory approval. The proposed method is extended to include multistage designs with a solution provided for a two-stage design. An example is given. Significant increases in the expected net gain are realized by using multistage designs. The complexity of the solutions increases with the number of stages, although far simpler near-optimal solutions exist. The method relies on the central limit theorem, assuming that the sample size is sufficiently large so that the relevant statistics are normally distributed. From a value of

  10. RNA Profiling for Biomarker Discovery: Practical Considerations for Limiting Sample Sizes

    Directory of Open Access Journals (Sweden)

    Danny J. Kelly

    2005-01-01

    Full Text Available We have compared microarray data generated on Affymetrix™ chips from standard (8 micrograms or low (100 nanograms amounts of total RNA. We evaluated the gene signals and gene fold-change estimates obtained from the two methods and validated a subset of the results by real time, polymerase chain reaction assays. The correlation of low RNA derived gene signals to gene signals obtained from standard RNA was poor for less to moderately abundant genes. Genes with high abundance showed better correlation in signals between the two methods. The signal correlation between the low RNA and standard RNA methods was improved by including a reference sample in the microarray analysis. In contrast, the fold-change estimates for genes were better correlated between the two methods regardless of the magnitude of gene signals. A reference sample based method is suggested for studies that would end up comparing gene signal data from a combination of low and standard RNA templates; no such referencing appears to be necessary when comparing fold-changes of gene expression between standard and low template reactions.

  11. Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data

    KAUST Repository

    Dong, Kai

    2015-09-16

    DNA sequencing techniques bring novel tools and also statistical challenges to genetic research. In addition to detecting differentially expressed genes, testing the significance of gene sets or pathway analysis has been recognized as an equally important problem. Owing to the “large pp small nn” paradigm, the traditional Hotelling’s T2T2 test suffers from the singularity problem and therefore is not valid in this setting. In this paper, we propose a shrinkage-based diagonal Hotelling’s test for both one-sample and two-sample cases. We also suggest several different ways to derive the approximate null distribution under different scenarios of pp and nn for our proposed shrinkage-based test. Simulation studies show that the proposed method performs comparably to existing competitors when nn is moderate or large, but it is better when nn is small. In addition, we analyze four gene expression data sets and they demonstrate the advantage of our proposed shrinkage-based diagonal Hotelling’s test.

  12. Distribution of human waste samples in relation to sizing waste processing in space

    Science.gov (United States)

    Parker, Dick; Gallagher, S. K.

    1992-01-01

    Human waste processing for closed ecological life support systems (CELSS) in space requires that there be an accurate knowledge of the quantity of wastes produced. Because initial CELSS will be handling relatively few individuals, it is important to know the variation that exists in the production of wastes rather than relying upon mean values that could result in undersizing equipment for a specific crew. On the other hand, because of the costs of orbiting equipment, it is important to design the equipment with a minimum of excess capacity because of the weight that extra capacity represents. A considerable quantity of information that had been independently gathered on waste production was examined in order to obtain estimates of equipment sizing requirements for handling waste loads from crews of 2 to 20 individuals. The recommended design for a crew of 8 should hold 34.5 liters per day (4315 ml/person/day) for urine and stool water and a little more than 1.25 kg per day (154 g/person/day) of human waste solids and sanitary supplies.

  13. The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study

    Directory of Open Access Journals (Sweden)

    Jamshid Jamali

    2017-01-01

    Full Text Available Evaluating measurement equivalence (also known as differential item functioning (DIF is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.

  14. Dealing with large sample sizes: comparison of a new one spot dot blot method to western blot.

    Science.gov (United States)

    Putra, Sulistyo Emantoko Dwi; Tsuprykov, Oleg; Von Websky, Karoline; Ritter, Teresa; Reichetzeder, Christoph; Hocher, Berthold

    2014-01-01

    Western blot is the gold standard method to determine individual protein expression levels. However, western blot is technically difficult to perform in large sample sizes because it is a time consuming and labor intensive process. Dot blot is often used instead when dealing with large sample sizes, but the main disadvantage of the existing dot blot techniques, is the absence of signal normalization to a housekeeping protein. In this study we established a one dot two development signals (ODTDS) dot blot method employing two different signal development systems. The first signal from the protein of interest was detected by horseradish peroxidase (HRP). The second signal, detecting the housekeeping protein, was obtained by using alkaline phosphatase (AP). Inter-assay results variations within ODTDS dot blot and western blot and intra-assay variations between both methods were low (1.04-5.71%) as assessed by coefficient of variation. ODTDS dot blot technique can be used instead of western blot when dealing with large sample sizes without a reduction in results accuracy.

  15. Gavage of Fecal Samples From Patients With Colorectal Cancer Promotes Intestinal Carcinogenesis in Germ-Free and Conventional Mice.

    Science.gov (United States)

    Wong, Sunny H; Zhao, Liuyang; Zhang, Xiang; Nakatsu, Geicho; Han, Juqiang; Xu, Weiqi; Xiao, Xue; Kwong, Thomas N Y; Tsoi, Ho; Wu, William K K; Zeng, Benhua; Chan, Francis K L; Sung, Joseph J Y; Wei, Hong; Yu, Jun

    2017-12-01

    Altered gut microbiota is implicated in development of colorectal cancer (CRC). Some intestinal bacteria have been reported to potentiate intestinal carcinogenesis by producing genotoxins, altering the immune response and intestinal microenvironment, and activating oncogenic signaling pathways. We investigated whether stool from patients with CRC could directly induce colorectal carcinogenesis in mice. We obtained stored stool samples from participants in a metagenome study performed in Hong Kong. Conventional (male C57BL/6) mice were given azoxymethane to induce colon neoplasia after receiving a course of antibiotics in drinking water. Mice were gavaged twice weekly with stool from 5 patients with CRC or 5 healthy individuals (controls) for 5 weeks. Germ-free C57BL/6 mice were gavaged once with stool from 5 patients with CRC or 5 controls. We collected intestinal tissues from mice and performed histology, immunohistochemistry, expression microarray, quantitative polymerase chain reaction, immunoblot, and flow cytometry analyses. We performed 16S ribosomal RNA gene sequencing analysis of feces from mice. Significantly higher proportions of conventional mice fed with stool from individuals with CRC than control stool developed high-grade dysplasia (P < .05) and macroscopic polyps (P < .01). We observed a higher proportion of proliferating (Ki-67-positive) cells in colons of germ-free mice fed with stool from patients with CRC vs those fed with stool from controls (P < .05). Feces from germ-free and conventional mice fed with stool from patients with CRC vs controls contained different microbial compositions, with lower richness in mice fed with stool from patients with CRC. Intestines collected from conventional and germ-free mice fed with stool from patients with CRC had increased expression of cytokines that modulate inflammation, including C-X-C motif chemokine receptor 1, C-X-C motif chemokine receptor 2, interleukin 17A (IL17A), IL22, and IL23A. Intestines

  16. Effects of dislocation density and sample-size on plastic yielding at the nanoscale: a Weibull-like framework.

    Science.gov (United States)

    Rinaldi, Antonio

    2011-11-01

    Micro-compression tests have demonstrated that plastic yielding in nanoscale pillars is the result of the fine interplay between the sample-size (chiefly the diameter D) and the density of bulk dislocations ρ. The power-law scaling typical of the nanoscale stems from a source-limited regime, which depends on both these sample parameters. Based on the experimental and theoretical results available in the literature, this paper offers a perspective about the joint effect of D and ρ on the yield stress in any plastic regime, promoting also a schematic graphical map of it. In the sample-size dependent regime, such dependence is cast mathematically into a first order Weibull-type theory, where the power-law scaling the power exponent β and the modulus m of an approximate (unimodal) Weibull distribution of source-strengths can be related by a simple inverse proportionality. As a corollary, the scaling exponent β may not be a universal number, as speculated in the literature. In this context, the discussion opens the alternative possibility of more general (multimodal) source-strength distributions, which could produce more complex and realistic strengthening patterns than the single power-law usually assumed. The paper re-examines our own experimental data, as well as results of Bei et al. (2008) on Mo-alloy pillars, especially for the sake of emphasizing the significance of a sudden increase in sample response scatter as a warning signal of an incipient source-limited regime.

  17. The design of high-temperature thermal conductivity measurements apparatus for thin sample size

    Directory of Open Access Journals (Sweden)

    Hadi Syamsul

    2017-01-01

    Full Text Available This study presents the designing, constructing and validating processes of thermal conductivity apparatus using steady-state heat-transfer techniques with the capability of testing a material at high temperatures. This design is an improvement from ASTM D5470 standard where meter-bars with the equal cross-sectional area were used to extrapolate surface temperature and measure heat transfer across a sample. There were two meter-bars in apparatus where each was placed three thermocouples. This Apparatus using a heater with a power of 1,000 watts, and cooling water to stable condition. The pressure applied was 3.4 MPa at the cross-sectional area of 113.09 mm2 meter-bar and thermal grease to minimized interfacial thermal contact resistance. To determine the performance, the validating process proceeded by comparing the results with thermal conductivity obtained by THB 500 made by LINSEIS. The tests showed the thermal conductivity of the stainless steel and bronze are 15.28 Wm-1K-1 and 38.01 Wm-1K-1 with a difference of test apparatus THB 500 are −2.55% and 2.49%. Furthermore, this apparatus has the capability to measure the thermal conductivity of the material to a temperature of 400°C where the results for the thermal conductivity of stainless steel is 19.21 Wm-1K-1 and the difference was 7.93%.

  18. Sample size affects 13C-18O clumping in CO2 derived from phosphoric acid digestion of carbonates

    Science.gov (United States)

    Wacker, U.; Fiebig, J.

    2011-12-01

    In the recent past, clumped isotope analysis of carbonates has become an important tool for terrestrial and marine paleoclimate reconstructions. For this purpose, 47/44 ratios of CO2 derived from phosphoric acid digestion of carbonates are measured. These values are compared to the corresponding stochastic 47/44 distribution ratios computed from determined δ13C and δ18O values, with the deviation being finally expressed as Δ47. For carbonates precipitated in equilibrium with its parental water, the magnitude of Δ47 is a function of temperature only. This technique bases on the fact that the isotopic fractionation associated with phosphoric acid digestion of carbonates is kinetically controlled. In this way, the concentration of 13C-18O bondings in the evolved CO2 remains proportional to the number of corresponding bondings inside the carbonate lattice. A relationship between carbonate growth temperature and Δ47 has recently been determined experimentally by Ghosh et al. (2006)1, who performed the carbonate digestion with 103% H3PO4 at 25°C after precipitating the carbonates inorganically at temperatures ranging from 1-50°C. In order to investigate the kinetic parameters associated with the phosphoric acid digestion reaction at 25°C, we have analyzed several natural carbonates at varying sample sizes. Amongst these are NBS 19, internal Carrara marbel, Arctica islandica and cold seep carbonates. Sample size was varied between 4 and 12mg. All samples exhibit a systematic trend to increasing Δ47 values with decreasing sample size, with absolute variations being restricted to ≤0.10%. Additional tests imply that this effect is related to the phosphoric acid digestion reaction. Most presumably, either the kinetic fractionation factor expressing the differences in 47/44 ratios between evolved CO2 and parental carbonate slightly depends on the concentration of the digested carbonate or traces of water exchange with C-O-bearing species inside the acid, similar to

  19. Assessment of minimum sample sizes required to adequately represent diversity reveals inadequacies in datasets of domestic dog mitochondrial DNA.

    Science.gov (United States)

    Webb, Kristen; Allard, Marc

    2010-02-01

    Evolutionary and forensic studies commonly choose the mitochondrial control region as the locus for which to evaluate the domestic dog. However, the number of dogs that need to be sampled in order to represent the control region variation present in the worldwide population is yet to be determined. Following the methods of Pereira et al. (2004), we have demonstrated the importance of surveying the complete control region rather than only the popular left domain. We have also evaluated sample saturation in terms of the haplotype number and the number of polymorphisms within the control region. Of the most commonly cited evolutionary research, only a single study has adequately surveyed the domestic dog population, while all forensic studies have failed to meet the minimum values. We recommend that future studies consider dataset size when designing experiments and ideally sample both domains of the control region in an appropriate number of domestic dogs.

  20. How taxonomic diversity, community structure, and sample size determine the reliability of higher taxon surrogates.

    Science.gov (United States)

    Neeson, Thomas M; Van Rijn, Itai; Mandelik, Yael

    2013-07-01

    Ecologists and paleontologists often rely on higher taxon surrogates instead of complete inventories of biological diversity. Despite their intrinsic appeal, the performance of these surrogates has been markedly inconsistent across empirical studies, to the extent that there is no consensus on appropriate taxonomic resolution (i.e., whether genus- or family-level categories are more appropriate) or their overall usefulness. A framework linking the reliability of higher taxon surrogates to biogeographic setting would allow for the interpretation of previously published work and provide some needed guidance regarding the actual application of these surrogates in biodiversity assessments, conservation planning, and the interpretation of the fossil record. We developed a mathematical model to show how taxonomic diversity, community structure, and sampling effort together affect three measures of higher taxon performance: the correlation between species and higher taxon richness, the relative shapes and asymptotes of species and higher taxon accumulation curves, and the efficiency of higher taxa in a complementarity-based reserve-selection algorithm. In our model, higher taxon surrogates performed well in communities in which a few common species were most abundant, and less well in communities with many equally abundant species. Furthermore, higher taxon surrogates performed well when there was a small mean and variance in the number of species per higher taxa. We also show that empirically measured species-higher-taxon correlations can be partly spurious (i.e., a mathematical artifact), except when the species accumulation curve has reached an asymptote. This particular result is of considerable practical interest given the widespread use of rapid survey methods in biodiversity assessment and the application of higher taxon methods to taxa in which species accumulation curves rarely reach an asymptote, e.g., insects.

  1. Prediction errors in learning drug response from gene expression data - influence of labeling, sample size, and machine learning algorithm.

    Directory of Open Access Journals (Sweden)

    Immanuel Bayer

    Full Text Available Model-based prediction is dependent on many choices ranging from the sample collection and prediction endpoint to the choice of algorithm and its parameters. Here we studied the effects of such choices, exemplified by predicting sensitivity (as IC50 of cancer cell lines towards a variety of compounds. For this, we used three independent sample collections and applied several machine learning algorithms for predicting a variety of endpoints for drug response. We compared all possible models for combinations of sample collections, algorithm, drug, and labeling to an identically generated null model. The predictability of treatment effects varies among compounds, i.e. response could be predicted for some but not for all. The choice of sample collection plays a major role towards lowering the prediction error, as does sample size. However, we found that no algorithm was able to consistently outperform the other and there was no significant difference between regression and two- or three class predictors in this experimental setting. These results indicate that response-modeling projects should direct efforts mainly towards sample collection and data quality, rather than method adjustment.

  2. Influence of pH, Temperature and Sample Size on Natural and Enforced Syneresis of Precipitated Silica

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    Sebastian Wilhelm

    2015-12-01

    Full Text Available The production of silica is performed by mixing an inorganic, silicate-based precursor and an acid. Monomeric silicic acid forms and polymerizes to amorphous silica particles. Both further polymerization and agglomeration of the particles lead to a gel network. Since polymerization continues after gelation, the gel network consolidates. This rather slow process is known as “natural syneresis” and strongly influences the product properties (e.g., agglomerate size, porosity or internal surface. “Enforced syneresis” is the superposition of natural syneresis with a mechanical, external force. Enforced syneresis may be used either for analytical or preparative purposes. Hereby, two open key aspects are of particular interest. On the one hand, the question arises whether natural and enforced syneresis are analogous processes with respect to their dependence on the process parameters: pH, temperature and sample size. On the other hand, a method is desirable that allows for correlating natural and enforced syneresis behavior. We can show that the pH-, temperature- and sample size-dependency of natural and enforced syneresis are indeed analogous. It is possible to predict natural syneresis using a correlative model. We found that our model predicts maximum volume shrinkages between 19% and 30% in comparison to measured values of 20% for natural syneresis.

  3. Computing power and sample size for case-control association studies with copy number polymorphism: application of mixture-based likelihood ratio test.

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    Wonkuk Kim

    Full Text Available Recent studies suggest that copy number polymorphisms (CNPs may play an important role in disease susceptibility and onset. Currently, the detection of CNPs mainly depends on microarray technology. For case-control studies, conventionally, subjects are assigned to a specific CNP category based on the continuous quantitative measure produced by microarray experiments, and cases and controls are then compared using a chi-square test of independence. The purpose of this work is to specify the likelihood ratio test statistic (LRTS for case-control sampling design based on the underlying continuous quantitative measurement, and to assess its power and relative efficiency (as compared to the chi-square test of independence on CNP counts. The sample size and power formulas of both methods are given. For the latter, the CNPs are classified using the Bayesian classification rule. The LRTS is more powerful than this chi-square test for the alternatives considered, especially alternatives in which the at-risk CNP categories have low frequencies. An example of the application of the LRTS is given for a comparison of CNP distributions in individuals of Caucasian or Taiwanese ethnicity, where the LRTS appears to be more powerful than the chi-square test, possibly due to misclassification of the most common CNP category into a less common category.

  4. Peer groups splitting in Croatian EQA scheme: a trade-off between homogeneity and sample size number.

    Science.gov (United States)

    Vlašić Tanasković, Jelena; Coucke, Wim; Leniček Krleža, Jasna; Vuković Rodriguez, Jadranka

    2017-03-01

    Laboratory evaluation through external quality assessment (EQA) schemes is often performed as 'peer group' comparison under the assumption that matrix effects influence the comparisons between results of different methods, for analytes where no commutable materials with reference value assignment are available. With EQA schemes that are not large but have many available instruments and reagent options for same analyte, homogenous peer groups must be created with adequate number of results to enable satisfactory statistical evaluation. We proposed a multivariate analysis of variance (MANOVA)-based test to evaluate heterogeneity of peer groups within the Croatian EQA biochemistry scheme and identify groups where further splitting might improve laboratory evaluation. EQA biochemistry results were divided according to instruments used per analyte and the MANOVA test was used to verify statistically significant differences between subgroups. The number of samples was determined by sample size calculation ensuring a power of 90% and allowing the false flagging rate to increase not more than 5%. When statistically significant differences between subgroups were found, clear improvement of laboratory evaluation was assessed before splitting groups. After evaluating 29 peer groups, we found strong evidence for further splitting of six groups. Overall improvement of 6% reported results were observed, with the percentage being as high as 27.4% for one particular method. Defining maximal allowable differences between subgroups based on flagging rate change, followed by sample size planning and MANOVA, identifies heterogeneous peer groups where further splitting improves laboratory evaluation and enables continuous monitoring for peer group heterogeneity within EQA schemes.

  5. Spatial Distribution and Minimum Sample Size for Overwintering Larvae of the Rice Stem Borer Chilo suppressalis (Walker) in Paddy Fields.

    Science.gov (United States)

    Arbab, A

    2014-10-01

    The rice stem borer, Chilo suppressalis (Walker), feeds almost exclusively in paddy fields in most regions of the world. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling procedures, and adopting precise agricultural techniques. Field experiments were conducted during 2011 and 2012 to estimate the spatial distribution pattern of the overwintering larvae. Data were analyzed using five distribution indices and two regression models (Taylor and Iwao). All of the indices and Taylor's model indicated random spatial distribution pattern of the rice stem borer overwintering larvae. Iwao's patchiness regression was inappropriate for our data as shown by the non-homogeneity of variance, whereas Taylor's power law fitted the data well. The coefficients of Taylor's power law for a combined 2 years of data were a = -0.1118, b = 0.9202 ± 0.02, and r (2) = 96.81. Taylor's power law parameters were used to compute minimum sample size needed to estimate populations at three fixed precision levels, 5, 10, and 25% at 0.05 probabilities. Results based on this equation parameters suggesting that minimum sample sizes needed for a precision level of 0.25 were 74 and 20 rice stubble for rice stem borer larvae when the average larvae is near 0.10 and 0.20 larvae per rice stubble, respectively.

  6. Endocranial volume of Australopithecus africanus: new CT-based estimates and the effects of missing data and small sample size.

    Science.gov (United States)

    Neubauer, Simon; Gunz, Philipp; Weber, Gerhard W; Hublin, Jean-Jacques

    2012-04-01

    Estimation of endocranial volume in Australopithecus africanus is important in interpreting early hominin brain evolution. However, the number of individuals available for investigation is limited and most of these fossils are, to some degree, incomplete and/or distorted. Uncertainties of the required reconstruction ('missing data uncertainty') and the small sample size ('small sample uncertainty') both potentially bias estimates of the average and within-group variation of endocranial volume in A. africanus. We used CT scans, electronic preparation (segmentation), mirror-imaging and semilandmark-based geometric morphometrics to generate and reconstruct complete endocasts for Sts 5, Sts 60, Sts 71, StW 505, MLD 37/38, and Taung, and measured their endocranial volumes (EV). To get a sense of the reliability of these new EV estimates, we then used simulations based on samples of chimpanzees and humans to: (a) test the accuracy of our approach, (b) assess missing data uncertainty, and (c) appraise small sample uncertainty. Incorporating missing data uncertainty of the five adult individuals, A. africanus was found to have an average adult endocranial volume of 454-461 ml with a standard deviation of 66-75 ml. EV estimates for the juvenile Taung individual range from 402 to 407 ml. Our simulations show that missing data uncertainty is small given the missing portions of the investigated fossils, but that small sample sizes are problematic for estimating species average EV. It is important to take these uncertainties into account when different fossil groups are being compared. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Arecibo Radar Observation of Near-Earth Asteroids: Expanded Sample Size, Determination of Radar Albedos, and Measurements of Polarization Ratios

    Science.gov (United States)

    Lejoly, Cassandra; Howell, Ellen S.; Taylor, Patrick A.; Springmann, Alessondra; Virkki, Anne; Nolan, Michael C.; Rivera-Valentin, Edgard G.; Benner, Lance A. M.; Brozovic, Marina; Giorgini, Jon D.

    2017-10-01

    The Near-Earth Asteroid (NEA) population ranges in size from a few meters to more than 10 kilometers. NEAs have a wide variety of taxonomic classes, surface features, and shapes, including spheroids, binary objects, contact binaries, elongated, as well as irregular bodies. Using the Arecibo Observatory planetary radar system, we have measured apparent rotation rate, radar reflectivity, apparent diameter, and radar albedos for over 350 NEAs. The radar albedo is defined as the radar cross-section divided by the geometric cross-section. If a shape model is available, the actual cross-section is known at the time of the observation. Otherwise we derive a geometric cross-section from a measured diameter. When radar imaging is available, the diameter was measured from the apparent range depth. However, when radar imaging was not available, we used the continuous wave (CW) bandwidth radar measurements in conjunction with the period of the object. The CW bandwidth provides apparent rotation rate, which, given an independent rotation measurement, such as from lightcurves, constrains the size of the object. We assumed an equatorial view unless we knew the pole orientation, which gives a lower limit on the diameter. The CW also provides the polarization ratio, which is the ratio of the SC and OC cross-sections.We confirm the trend found by Benner et al. (2008) that taxonomic types E and V have very high polarization ratios. We have obtained a larger sample and can analyze additional trends with spin, size, rotation rate, taxonomic class, polarization ratio, and radar albedo to interpret the origin of the NEAs and their dynamical processes. The distribution of radar albedo and polarization ratio at the smallest diameters (≤50 m) differs from the distribution of larger objects (>50 m), although the sample size is limited. Additionally, we find more moderate radar albedos for the smallest NEAs when compared to those with diameters 50-150 m. We will present additional trends we

  8. Capture efficiency and size selectivity of sampling gears targeting red-swamp crayfish in several freshwater habitats

    Directory of Open Access Journals (Sweden)

    Paillisson J.-M.

    2011-05-01

    Full Text Available The ecological importance of the red-swamp crayfish (Procambarus clarkii in the functioning of freshwater aquatic ecosystems is becoming more evident. It is important to know the limitations of sampling methods targeting this species, because accurate determination of population characteristics is required for predicting the ecological success of P. clarkii and its potential impacts on invaded ecosystems. In the current study, we addressed the question of trap efficiency by comparing population structure provided by eight trap devices (varying in number and position of entrances, mesh size, trap size and construction materials in three habitats (a pond, a reed bed and a grassland in a French marsh in spring 2010. Based on a large collection of P. clarkii (n = 2091, 272 and 213 respectively in the pond, reed bed and grassland habitats, we found that semi-cylindrical traps made from 5.5 mm mesh galvanized steel wire (SCG were the most efficient in terms of catch probability (96.7–100% compared to 15.7–82.8% depending on trap types and habitats and catch-per-unit effort (CPUE: 15.3, 6.0 and 5.1 crayfish·trap-1·24 h-1 compared to 0.2–4.4, 2.9 and 1.7 crayfish·trap-1·24 h-1 by the other types of fishing gear in the pond, reed bed and grassland respectively. The SCG trap was also the most effective for sampling all size classes, especially small individuals (carapace length \\hbox{$\\leqslant 30$} ⩽ 30 mm. Sex ratio was balanced in all cases. SCG could be considered as appropriate trapping gear to likely give more realistic information about P. clarkii population characteristics than many other trap types. Further investigation is needed to assess the catching effort required for ultimately proposing a standardised sampling method in a large range of habitats.

  9. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Science.gov (United States)

    Vasiliu, Daniel; Clamons, Samuel; McDonough, Molly; Rabe, Brian; Saha, Margaret

    2015-01-01

    Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED). Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  10. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Directory of Open Access Journals (Sweden)

    Daniel Vasiliu

    Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  11. Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic.

    Science.gov (United States)

    Sillett, T Scott; Chandler, Richard B; Royle, J Andrew; Kery, Marc; Morrison, Scott A

    2012-10-01

    Population size and habitat-specific abundance estimates are essential for conservation management. A major impediment to obtaining such estimates is that few statistical models are able to simultaneously account for both spatial variation in abundance and heterogeneity in detection probability, and still be amenable to large-scale applications. The hierarchical distance-sampling model of J. A. Royle, D. K. Dawson, and S. Bates provides a practical solution. Here, we extend this model to estimate habitat-specific abundance and rangewide population size of a bird species of management concern, the Island Scrub-Jay (Aphelocoma insularis), which occurs solely on Santa Cruz Island, California, USA. We surveyed 307 randomly selected, 300 m diameter, point locations throughout the 250-km2 island during October 2008 and April 2009. Population size was estimated to be 2267 (95% CI 1613-3007) and 1705 (1212-2369) during the fall and spring respectively, considerably lower than a previously published but statistically problematic estimate of 12 500. This large discrepancy emphasizes the importance of proper survey design and analysis for obtaining reliable information for management decisions. Jays were most abundant in low-elevation chaparral habitat; the detection function depended primarily on the percent cover of chaparral and forest within count circles. Vegetation change on the island has been dramatic in recent decades, due to release from herbivory following the eradication of feral sheep (Ovis aries) from the majority of the island in the mid-1980s. We applied best-fit fall and spring models of habitat-specific jay abundance to a vegetation map from 1985, and estimated the population size of A. insularis was 1400-1500 at that time. The 20-30% increase in the jay population suggests that the species has benefited from the recovery of native vegetation since sheep removal. Nevertheless, this jay's tiny range and small population size make it vulnerable to natural

  12. Point Counts of Birds in Bottomland Hardwood Forests of the Mississippi Alluvial Valley: Duration, Minimum Sample Size, and Points Versus Visits

    Science.gov (United States)

    Winston Paul Smith; Daniel J. Twedt; David A. Wiedenfeld; Paul B. Hamel; Robert P. Ford; Robert J. Cooper

    1993-01-01

    To compare efficacy of point count sampling in bottomland hardwood forests, duration of point count, number of point counts, number of visits to each point during a breeding season, and minimum sample size are examined.

  13. Determination of the Molecular Weight of Low-Molecular-Weight Heparins by Using High-Pressure Size Exclusion Chromatography on Line with a Triple Detector Array and Conventional Methods

    Directory of Open Access Journals (Sweden)

    Antonella Bisio

    2015-03-01

    Full Text Available The evaluation of weight average molecular weight (Mw and molecular weight distribution represents one of the most controversial aspects concerning the characterization of low molecular weight heparins (LMWHs. As the most commonly used method for the measurement of such parameters is high performance size exclusion chromatography (HP-SEC, the soundness of results mainly depends on the appropriate calibration of the chromatographic columns used. With the aim of meeting the requirement of proper Mw standards for LMWHs, in the present work the determination of molecular weight parameters (Mw and Mn by HP-SEC combined with a triple detector array (TDA was performed. The HP-SEC/TDA technique permits the evaluation of polymeric samples by exploiting the combined and simultaneous action of three on-line detectors: light scattering detectors (LALLS/RALLS; refractometer and viscometer. Three commercial LMWH samples, enoxaparin, tinzaparin and dalteparin, a γ-ray depolymerized heparin (γ-Hep and its chromatographic fractions, and a synthetic pentasaccharide were analysed by HP-SEC/TDA. The same samples were analysed also with a conventional HP-SEC method employing refractive index (RI and UV detectors and two different chromatographic column set, silica gel and polymeric gel columns. In both chromatographic systems, two different calibration curves were built up by using (i γ-Hep chromatographic fractions and the corresponding Mw parameters obtained via HP-SEC/TDA; (ii the whole γ-Hep preparation with broad Mw dispersion and the corresponding cumulative distribution function calculated via HP-SEC/TDA. In addition, also a chromatographic column calibration according to European Pharmacopoeia indication was built up. By comparing all the obtained results, some important differences among Mw and size distribution values of the three LMWHs were found with the five different calibration methods and with HP-SEC/TDA method. In particular, the detection of

  14. Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa

    Directory of Open Access Journals (Sweden)

    Xiao-ling LI

    2011-03-01

    Full Text Available The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50–225 nested core collections, whose sampling rate was 2.2%–9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions (6.6% could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits (QT1, quantitative traits (QT2 and integrated qualitative and quantitative traits (QTT, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections (225, 200, 175, 150, 125, 100, 75 and 50. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

  15. Organic composition of size segregated atmospheric particulate matter, during summer and winter sampling campaigns at representative sites in Madrid, Spain

    Science.gov (United States)

    Mirante, Fátima; Alves, Célia; Pio, Casimiro; Pindado, Oscar; Perez, Rosa; Revuelta, M.a. Aranzazu; Artiñano, Begoña

    2013-10-01

    Madrid, the largest city of Spain, has some and unique air pollution problems, such as emissions from residential coal burning, a huge vehicle fleet and frequent African dust outbreaks, along with the lack of industrial emissions. The chemical composition of particulate matter (PM) was studied during summer and winter sampling campaigns, conducted in order to obtain size-segregated information at two different urban sites (roadside and urban background). PM was sampled with high volume cascade impactors, with 4 stages: 10-2.5, 2.5-1, 1-0.5 and alcohols and fatty acids were chromatographically resolved. The PM1-2.5 was the fraction with the highest mass percentage of organics. Acids were the organic compounds that dominated all particle size fractions. Different organic compounds presented apparently different seasonal characteristics, reflecting distinct emission sources, such as vehicle exhausts and biogenic sources. The benzo[a]pyrene equivalent concentrations were lower than 1 ng m- 3. The estimated carcinogenic risk is low.

  16. Sample size and repeated measures required in studies of foods in the homes of African-American families.

    Science.gov (United States)

    Stevens, June; Bryant, Maria; Wang, Chin-Hua; Cai, Jianwen; Bentley, Margaret E

    2012-06-01

    Measurement of the home food environment is of interest to researchers because it affects food intake and is a feasible target for nutrition interventions. The objective of this study was to provide estimates to aid the calculation of sample size and number of repeated measures needed in studies of nutrients and foods in the home. We inventoried all foods in the homes of 80 African-American first-time mothers and determined 6 nutrient-related attributes. Sixty-three households were measured 3 times, 11 were measured twice, and 6 were measured once, producing 217 inventories collected at ~2-mo intervals. Following log transformations, number of foods, total energy, dietary fiber, and fat required only one measurement per household to achieve a correlation of 0.8 between the observed and true values. For percent energy from fat and energy density, 3 and 2 repeated measurements, respectively, were needed to achieve a correlation of 0.8. A sample size of 252 was needed to detect a difference of 25% of an SD in total energy with one measurement compared with 213 with 3 repeated measurements. Macronutrient characteristics of household foods appeared relatively stable over a 6-mo period and only 1 or 2 repeated measures of households may be sufficient for an efficient study design.

  17. MRI derived brain atrophy in PSP and MSA-P. Determining sample size to detect treatment effects.

    Science.gov (United States)

    Paviour, Dominic C; Price, Shona L; Lees, Andrew J; Fox, Nick C

    2007-04-01

    Progressive supranuclear palsy (PSP) and multiple system (MSA) atrophy are associated with progressive brain atrophy. Serial MRI can be applied in order to measure this change in brain volume and to calculate atrophy rates. We evaluated MRI derived whole brain and regional atrophy rates as potential markers of progression in PSP and the Parkinsonian variant of multiple system atrophy (MSA-P). 17 patients with PSP, 9 with MSA-P and 18 healthy controls underwent two MRI brain scans. MRI scans were registered, and brain and regional atrophy rates (midbrain, pons, cerebellum, third and lateral ventricles) measured. Sample sizes required to detect the effect of a proposed disease-modifying treatment were estimated. The effect of scan interval on the variance of the atrophy rates and sample size was assessed. Based on the calculated yearly rates of atrophy, for a drug effect equivalent to a 30% reduction in atrophy, fewer PSP subjects are required in each treatment arm when using midbrain rather than whole brain atrophy rates (183 cf. 499). Fewer MSA-P subjects are required, using pontine/cerebellar, rather than whole brain atrophy rates (164/129 cf. 794). A reduction in the variance of measured atrophy rates was observed with a longer scan interval. Regional rather than whole brain atrophy rates calculated from volumetric serial MRI brain scans in PSP and MSA-P provide a more practical and powerful means of monitoring disease progression in clinical trials.

  18. Reduction of sample size requirements by bilateral versus unilateral research designs in animal models for cartilage tissue engineering.

    Science.gov (United States)

    Orth, Patrick; Zurakowski, David; Alini, Mauro; Cucchiarini, Magali; Madry, Henning

    2013-11-01

    Advanced tissue engineering approaches for articular cartilage repair in the knee joint rely on translational animal models. In these investigations, cartilage defects may be established either in one joint (unilateral design) or in both joints of the same animal (bilateral design). We hypothesized that a lower intraindividual variability following the bilateral strategy would reduce the number of required joints. Standardized osteochondral defects were created in the trochlear groove of 18 rabbits. In 12 animals, defects were produced unilaterally (unilateral design; n=12 defects), while defects were created bilaterally in 6 animals (bilateral design; n=12 defects). After 3 weeks, osteochondral repair was evaluated histologically applying an established grading system. Based on intra- and interindividual variabilities, required sample sizes for the detection of discrete differences in the histological score were determined for both study designs (α=0.05, β=0.20). Coefficients of variation (%CV) of the total histological score values were 1.9-fold increased following the unilateral design when compared with the bilateral approach (26 versus 14%CV). The resulting numbers of joints needed to treat were always higher for the unilateral design, resulting in an up to 3.9-fold increase in the required number of experimental animals. This effect was most pronounced for the detection of small-effect sizes and estimating large standard deviations. The data underline the possible benefit of bilateral study designs for the decrease of sample size requirements for certain investigations in articular cartilage research. These findings might also be transferred to other scoring systems, defect types, or translational animal models in the field of cartilage tissue engineering.

  19. Comparison of three analytical methods to measure the size of silver nanoparticles in real environmental water and wastewater samples

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Ying-jie [Department of Agricultural Chemistry, National Taiwan University, Taipei 106, Taiwan (China); Shih, Yang-hsin, E-mail: yhs@ntu.edu.tw [Department of Agricultural Chemistry, National Taiwan University, Taipei 106, Taiwan (China); Su, Chiu-Hun [Material and Chemical Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan (China); Ho, Han-Chen [Department of Anatomy, Tzu-Chi University, Hualien 970, Taiwan (China)

    2017-01-15

    Highlights: • Three emerging techniques to detect NPs in the aquatic environment were evaluated. • The pretreatment of centrifugation to decrease the interference was established. • Asymmetric flow field flow fractionation has a low recovery of NPs. • Hydrodynamic chromatography is recommended to be a low-cost screening tool. • Single particle ICPMS is recommended to accurately measure trace NPs in water. - Abstract: Due to the widespread application of engineered nanoparticles, their potential risk to ecosystems and human health is of growing concern. Silver nanoparticles (Ag NPs) are one of the most extensively produced NPs. Thus, this study aims to develop a method to detect Ag NPs in different aquatic systems. In complex media, three emerging techniques are compared, including hydrodynamic chromatography (HDC), asymmetric flow field flow fractionation (AF4) and single particle inductively coupled plasma-mass spectrometry (SP-ICP-MS). The pre-treatment procedure of centrifugation is evaluated. HDC can estimate the Ag NP sizes, which were consistent with the results obtained from DLS. AF4 can also determine the size of Ag NPs but with lower recoveries, which could result from the interactions between Ag NPs and the working membrane. For the SP-ICP-MS, both the particle size and concentrations can be determined with high Ag NP recoveries. The particle size resulting from SP-ICP-MS also corresponded to the transmission electron microscopy observation (p > 0.05). Therefore, HDC and SP-ICP-MS are recommended for environmental analysis of the samples after our established pre-treatment process. The findings of this study propose a preliminary technique to more accurately determine the Ag NPs in aquatic environments and to use this knowledge to evaluate the environmental impact of manufactured NPs.

  20. Porous iron pellets for AMS C-14 analysis of small samples down to ultra-microscale size (10-25 mu gC)

    NARCIS (Netherlands)

    de Rooij, M.; van der Plicht, J.; Meijer, H. A. J.

    We developed the use of a porous iron pellet as a catalyst for AMS C-14 analysis of small samples down to ultra-microscale size (10-25 mu gC). It resulted in increased and more stable beam currents through our HVEE 4130 C-14 AMS system, which depend smoothly on the sample size. We find that both the

  1. Sampling

    CERN Document Server

    Thompson, Steven K

    2012-01-01

    Praise for the Second Edition "This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book." —Technometrics "Well-written . . . an excellent book on an important subject. Highly recommended." —Choice "An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treat

  2. Determining the sample size required to establish whether a medical device is non-inferior to an external benchmark.

    Science.gov (United States)

    Sayers, Adrian; Crowther, Michael J; Judge, Andrew; Whitehouse, Michael R; Blom, Ashley W

    2017-08-28

    The use of benchmarks to assess the performance of implants such as those used in arthroplasty surgery is a widespread practice. It provides surgeons, patients and regulatory authorities with the reassurance that implants used are safe and effective. However, it is not currently clear how or how many implants should be statistically compared with a benchmark to assess whether or not that implant is superior, equivalent, non-inferior or inferior to the performance benchmark of interest.We aim to describe the methods and sample size required to conduct a one-sample non-inferiority study of a medical device for the purposes of benchmarking. Simulation study. Simulation study of a national register of medical devices. We simulated data, with and without a non-informative competing risk, to represent an arthroplasty population and describe three methods of analysis (z-test, 1-Kaplan-Meier and competing risks) commonly used in surgical research. We evaluate the performance of each method using power, bias, root-mean-square error, coverage and CI width. 1-Kaplan-Meier provides an unbiased estimate of implant net failure, which can be used to assess if a surgical device is non-inferior to an external benchmark. Small non-inferiority margins require significantly more individuals to be at risk compared with current benchmarking standards. A non-inferiority testing paradigm provides a useful framework for determining if an implant meets the required performance defined by an external benchmark. Current contemporary benchmarking standards have limited power to detect non-inferiority, and substantially larger samples sizes, in excess of 3200 procedures, are required to achieve a power greater than 60%. It is clear when benchmarking implant performance, net failure estimated using 1-KM is preferential to crude failure estimated by competing risk models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No

  3. Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches.

    Science.gov (United States)

    Skrbinšek, Tomaž; Jelenčič, Maja; Waits, Lisette; Kos, Ivan; Jerina, Klemen; Trontelj, Peter

    2012-02-01

    The effective population size (N(e) ) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating N(e) from a single sample of genotypes to trace temporal change in N(e) for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both N(e) and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (N(b) ) using linkage disequilibrium, sibship assignment and approximate Bayesian computation methods and extrapolated these estimates to N(e) using the generation interval. The N(e) estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of N(e) > 50 but short of the long-term minimum viable population goal of N(e) > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in N(e) probably in the late 1990s and early 2000s. The new single-sample approaches to the estimation of N(e) provide efficient means for including N(e) in monitoring frameworks and will be of great importance for future management and conservation. © 2012 Blackwell Publishing Ltd.

  4. The effects of composition, temperature and sample size on the sintering of chem-prep high field varistors.

    Energy Technology Data Exchange (ETDEWEB)

    Garino, Terry J.

    2007-09-01

    The sintering behavior of Sandia chem-prep high field varistor materials was studied using techniques including in situ shrinkage measurements, optical and scanning electron microscopy and x-ray diffraction. A thorough literature review of phase behavior, sintering and microstructure in Bi{sub 2}O{sub 3}-ZnO varistor systems is included. The effects of Bi{sub 2}O{sub 3} content (from 0.25 to 0.56 mol%) and of sodium doping level (0 to 600 ppm) on the isothermal densification kinetics was determined between 650 and 825 C. At {ge} 750 C samples with {ge}0.41 mol% Bi{sub 2}O{sub 3} have very similar densification kinetics, whereas samples with {le}0.33 mol% begin to densify only after a period of hours at low temperatures. The effect of the sodium content was greatest at {approx}700 C for standard 0.56 mol% Bi{sub 2}O{sub 3} and was greater in samples with 0.30 mol% Bi{sub 2}O{sub 3} than for those with 0.56 mol%. Sintering experiments on samples of differing size and shape found that densification decreases and mass loss increases with increasing surface area to volume ratio. However, these two effects have different causes: the enhancement in densification as samples increase in size appears to be caused by a low oxygen internal atmosphere that develops whereas the mass loss is due to the evaporation of bismuth oxide. In situ XRD experiments showed that the bismuth is initially present as an oxycarbonate that transforms to metastable {beta}-Bi{sub 2}O{sub 3} by 400 C. At {approx}650 C, coincident with the onset of densification, the cubic binary phase, Bi{sub 38}ZnO{sub 58} forms and remains stable to >800 C, indicating that a eutectic liquid does not form during normal varistor sintering ({approx}730 C). Finally, the formation and morphology of bismuth oxide phase regions that form on the varistors surfaces during slow cooling were studied.

  5. Reversible phospholipid nanogels for deoxyribonucleic acid fragment size determinations up to 1500 base pairs and integrated sample stacking.

    Science.gov (United States)

    Durney, Brandon C; Bachert, Beth A; Sloane, Hillary S; Lukomski, Slawomir; Landers, James P; Holland, Lisa A

    2015-06-23

    Phospholipid additives are a cost-effective medium to separate deoxyribonucleic acid (DNA) fragments and possess a thermally-responsive viscosity. This provides a mechanism to easily create and replace a highly viscous nanogel in a narrow bore capillary with only a 10°C change in temperature. Preparations composed of dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and 1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) self-assemble, forming structures such as nanodisks and wormlike micelles. Factors that influence the morphology of a particular DMPC-DHPC preparation include the concentration of lipid in solution, the temperature, and the ratio of DMPC and DHPC. It has previously been established that an aqueous solution containing 10% phospholipid with a ratio of [DMPC]/[DHPC]=2.5 separates DNA fragments with nearly single base resolution for DNA fragments up to 500 base pairs in length, but beyond this size the resolution decreases dramatically. A new DMPC-DHPC medium is developed to effectively separate and size DNA fragments up to 1500 base pairs by decreasing the total lipid concentration to 2.5%. A 2.5% phospholipid nanogel generates a resolution of 1% of the DNA fragment size up to 1500 base pairs. This increase in the upper size limit is accomplished using commercially available phospholipids at an even lower material cost than is achieved with the 10% preparation. The separation additive is used to evaluate size markers ranging between 200 and 1500 base pairs in order to distinguish invasive strains of Streptococcus pyogenes and Aspergillus species by harnessing differences in gene sequences of collagen-like proteins in these organisms. For the first time, a reversible stacking gel is integrated in a capillary sieving separation by utilizing the thermally-responsive viscosity of these self-assembled phospholipid preparations. A discontinuous matrix is created that is composed of a cartridge of highly viscous phospholipid assimilated into a separation matrix

  6. Transgender Population Size in the United States: a Meta-Regression of Population-Based Probability Samples.

    Science.gov (United States)

    Meerwijk, Esther L; Sevelius, Jae M

    2017-02-01

    Transgender individuals have a gender identity that differs from the sex they were assigned at birth. The population size of transgender individuals in the United States is not well-known, in part because official records, including the US Census, do not include data on gender identity. Population surveys today more often collect transgender-inclusive gender-identity data, and secular trends in culture and the media have created a somewhat more favorable environment for transgender people. To estimate the current population size of transgender individuals in the United States and evaluate any trend over time. In June and July 2016, we searched PubMed, Cumulative Index to Nursing and Allied Health Literature, and Web of Science for national surveys, as well as "gray" literature, through an Internet search. We limited the search to 2006 through 2016. We selected population-based surveys that used probability sampling and included self-reported transgender-identity data. We used random-effects meta-analysis to pool eligible surveys and used meta-regression to address our hypothesis that the transgender population size estimate would increase over time. We used subsample and leave-one-out analysis to assess for bias. Our meta-regression model, based on 12 surveys covering 2007 to 2015, explained 62.5% of model heterogeneity, with a significant effect for each unit increase in survey year (F = 17.122; df = 1,10; b = 0.026%; P = .002). Extrapolating these results to 2016 suggested a current US population size of 390 adults per 100 000, or almost 1 million adults nationally. This estimate may be more indicative for younger adults, who represented more than 50% of the respondents in our analysis. Future national surveys are likely to observe higher numbers of transgender people. The large variety in questions used to ask about transgender identity may account for residual heterogeneity in our models. Public health implications. Under- or nonrepresentation

  7. Transgender Population Size in the United States: a Meta-Regression of Population-Based Probability Samples

    Science.gov (United States)

    Sevelius, Jae M.

    2017-01-01

    Background. Transgender individuals have a gender identity that differs from the sex they were assigned at birth. The population size of transgender individuals in the United States is not well-known, in part because official records, including the US Census, do not include data on gender identity. Population surveys today more often collect transgender-inclusive gender-identity data, and secular trends in culture and the media have created a somewhat more favorable environment for transgender people. Objectives. To estimate the current population size of transgender individuals in the United States and evaluate any trend over time. Search methods. In June and July 2016, we searched PubMed, Cumulative Index to Nursing and Allied Health Literature, and Web of Science for national surveys, as well as “gray” literature, through an Internet search. We limited the search to 2006 through 2016. Selection criteria. We selected population-based surveys that used probability sampling and included self-reported transgender-identity data. Data collection and analysis. We used random-effects meta-analysis to pool eligible surveys and used meta-regression to address our hypothesis that the transgender population size estimate would increase over time. We used subsample and leave-one-out analysis to assess for bias. Main results. Our meta-regression model, based on 12 surveys covering 2007 to 2015, explained 62.5% of model heterogeneity, with a significant effect for each unit increase in survey year (F = 17.122; df = 1,10; b = 0.026%; P = .002). Extrapolating these results to 2016 suggested a current US population size of 390 adults per 100 000, or almost 1 million adults nationally. This estimate may be more indicative for younger adults, who represented more than 50% of the respondents in our analysis. Authors’ conclusions. Future national surveys are likely to observe higher numbers of transgender people. The large variety in questions used to ask

  8. Reflex fluorescent in situ hybridization testing for unsuccessful product of conception cultures: a retrospective analysis of 5555 samples attempted by conventional cytogenetics and fluorescent in situ hybridization.

    Science.gov (United States)

    Shearer, Brandon M; Thorland, Erik C; Carlson, Austin W; Jalal, Syed M; Ketterling, Rhett P

    2011-06-01

    The use of chromosome analysis on products of conception from spontaneous abortions is recommended to identify a genetic etiology. However, 20% of products of conception cultures are unsuccessful due to microbial contamination or lack of viable dividing cells. Our laboratory implemented a reflex fluorescent in situ hybridization (FISH) assay to detect numeric chromosome abnormalities for unsuccessful cultures. All products of conception samples were simultaneously processed for both chromosome analysis and FISH analysis. If the chromosome analysis was unsuccessful, interphase FISH was performed for chromosomes 13, 16, 18, 21, 22, X, and Y. To assess the performance of the FISH assay, a 3-year retrospective comparative analysis of the FISH results versus chromosome results was performed. Of 5555 total specimens, 4189 (75%) represented chorionic villi/fetal tissue and 1366 (25%) represented tissue of unidentified origin. Of the 1189 tissues of unidentified origin with chromosome or FISH results, 1096 (92%) were XX, indicating that the majority of these tissues are likely maternal in origin. Of the 3361 successful chromosome studies on the chorionic villi/fetal tissue specimens, 1734 (52%) samples had a chromosome abnormality. Of the 762 successful FISH studies on chorionic villi/fetal tissue specimens that were unsuccessful by chromosome studies, 181 (25%) had an abnormal result with the targeted FISH panel. Overall, the FISH panel detected approximately 70% of the chromosome abnormalities in products of conception detectable by karyotype. When the FISH panel results were combined with chromosome analysis for the 4189 chorionic villi/fetal tissue specimens, the overall abnormality rate is 47%. Our reflex FISH assay proved useful for the detection of common chromosome aneuploidies in products of conception samples that failed conventional chromosome analysis. Because of its limited view of the genome, cautious interpretation of FISH results is required for all samples

  9. The Examination of Model Fit Indexes with Different Estimation Methods under Different Sample Sizes in Confirmatory Factor Analysis

    Directory of Open Access Journals (Sweden)

    Ayfer SAYIN

    2016-12-01

    Full Text Available In adjustment studies of scales and in terms of cross validity at scale development, confirmatory factor analysis is conducted. Confirmatory factor analysis, multivariate statistics, is estimated via various parameter estimation methods and utilizes several fit indexes for evaluating the model fit. In this study, model fit indexes utilized in confirmatory factor analysis are examined with different parameter estimation methods under different sample sizes. For the purpose of this study, answers of 60, 100, 250, 500 and 1000 students who attended PISA 2012 program were pulled from the answers to two dimensional “thoughts on the importance of mathematics” dimension. Estimations were based on methods of maximum likelihood (ML, unweighted least squares (ULS and generalized least squares (GLS. As a result of the study, it was found that model fit indexes were affected by the conditions, however some fit indexes were affected less than others and vice versa. In order to analyze these, some suggestions were made.

  10. Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

    Science.gov (United States)

    Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

    2017-01-01

    Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

  11. Delineamento experimental e tamanho de amostra para alface cultivada em hidroponia Experimental design and sample size for hydroponic lettuce crop

    Directory of Open Access Journals (Sweden)

    Valéria Schimitz Marodim

    2000-10-01

    Full Text Available Este estudo visa a estabelecer o delineamento experimental e o tamanho de amostra para a cultura da alface (Lactuca sativa em hidroponia, pelo sistema NFT (Nutrient film technique. O experimento foi conduzido no Laboratório de Cultivos Sem Solo/Hidroponia, no Departamento de Fitotecnia da Universidade Federal de Santa Maria e baseou-se em dados de massa de plantas. Os resultados obtidos mostraram que, usando estrutura de cultivo de alface em hidroponia sobre bancadas de fibrocimento com seis canais, o delineamento experimental adequado é blocos ao acaso se a unidade experimental for constituída de faixas transversais aos canais das bancadas, e deve ser inteiramente casualizado se a bancada for a unidade experimental; para a variável massa de plantas, o tamanho da amostra é de 40 plantas para uma semi-amplitude do intervalo de confiança em percentagem da média (d igual a 5% e de 7 plantas para um d igual a 20%.This study was carried out to establish the experimental design and sample size for hydroponic lettuce (Lactuca sativa crop under nutrient film technique. The experiment was conducted in the Laboratory of Hydroponic Crops of the Horticulture Department of the Federal University of Santa Maria. The evaluated traits were plant weight. Under hydroponic conditions on concrete bench with six ducts, the most indicated experimental design for lettuce is randomised blocks for duct transversal plots or completely randomised for bench plot. The sample size for plant weight should be 40 and 7 plants, respectively, for a confidence interval of mean percentage (d equal to 5% and 20%.

  12. Accuracy of Tumor Sizing in Breast Cancer: A Comparison of Strain Elastography, 3-D Ultrasound and Conventional B-Mode Ultrasound with and without Compound Imaging.

    Science.gov (United States)

    Stachs, Angrit; Pandjaitan, Alexander; Martin, Annett; Stubert, Johannes; Hartmann, Steffi; Gerber, Bernd; Glass, Änne

    2016-12-01

    The objective of this study was to compare the accuracy of strain elastography (SE), 3-D ultrasound (US), B-mode US with compound imaging (CI) and B-mode US without compound imaging for lesion sizing in breast cancer. The prospective study included 93 patients with invasive breast cancer. The largest tumor diameters measured by B-mode US, B-mode US with CI, SE and 3-D US were compared in Bland-Altman plots versus pathology as reference. A general linear model repeated measures (GLM Rep) was applied to investigate factors influencing tumor sizing. All methods underestimated pathologic size, with SE (-0.08 ± 7.7 mm) and 3-D US (-1.4 ± 6.5 mm) having the smallest mean differences from pathology. Bland-Altman plots revealed that B-mode US, B-mode US with CI and 3-D US systematically underestimated large tumor sizes, and only SE was technically comparable to pathology. The study indicates that sonographic underestimation of tumor size occurs mainly in tumors >20 mm; in this subgroup, SE is superior to other ultrasound methods. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  13. Time-integrated passive sampling as a complement to conventional point-in-time sampling for investigating drinking-water quality, McKenzie River Basin, Oregon, 2007 and 2010-11

    Science.gov (United States)

    McCarthy, Kathleen A.; Alvarez, David A.

    2014-01-01

    The Eugene Water & Electric Board (EWEB) supplies drinking water to approximately 200,000 people in Eugene, Oregon. The sole source of this water is the McKenzie River, which has consistently excellent water quality relative to established drinking-water standards. To ensure that this quality is maintained as land use in the source basin changes and water demands increase, EWEB has developed a proactive management strategy that includes a combination of conventional point-in-time discrete water sampling and time‑integrated passive sampling with a combination of chemical analyses and bioassays to explore water quality and identify where vulnerabilities may lie. In this report, we present the results from six passive‑sampling deployments at six sites in the basin, including the intake and outflow from the EWEB drinking‑water treatment plant (DWTP). This is the first known use of passive samplers to investigate both the source and finished water of a municipal DWTP. Results indicate that low concentrations of several polycyclic aromatic hydrocarbons and organohalogen compounds are consistently present in source waters, and that many of these compounds are also present in finished drinking water. The nature and patterns of compounds detected suggest that land-surface runoff and atmospheric deposition act as ongoing sources of polycyclic aromatic hydrocarbons, some currently used pesticides, and several legacy organochlorine pesticides. Comparison of results from point-in-time and time-integrated sampling indicate that these two methods are complementary and, when used together, provide a clearer understanding of contaminant sources than either method alone.

  14. Sample Preparation of Nano-sized Inorganic Materials for Scanning Electron Microscopy or Transmission Electron Microscopy: Scientific Operating Procedure SOP-P-2

    Science.gov (United States)

    2015-07-01

    sample. Nano- sized particles have a tendency to agglomerate during sample preparation. ERDC/GSL SR-15-1 4 3 Scope This SOP is used to determine the...conductive vs. nonconductive samples. The preparation of nanomaterial samples for imaging can be challenging as these materials tend to agglomerate or...aggregated or agglomerated samples. Another way is to extract the material from the liquid. In selected cases, imaging of the nanoparticles is aided

  15. Identification of chemicals relevant to the Chemical Weapons Convention using the novel sample-preparation methods and strategies of the Mobile Laboratory of the Organization for the Prohibition of Chemical Weapons

    NARCIS (Netherlands)

    Terzic, O.; Gregg, H.; de Voogt, P.

    2015-01-01

    The standard approach to on-site sample preparation for gas chromatography-mass spectrometry analysis of chemicals relevant to the Chemical Weapons Convention provides relatively good coverage of the target analytes, but it suffers from a number of drawbacks, such as low sample throughput, use of

  16. A systematic study on extraction of total arsenic from down-scaled sample sizes of plant tissues and implications for arsenic species analysis.

    Science.gov (United States)

    Schmidt, Anne-Christine; Haufe, Nora; Otto, Matthias

    2008-09-15

    An easily feasible, species-conserving and inexpensive protocol for the extraction of total arsenic and arsenic species from terrestrial plants was designed and applied to the investigation of accumulation and metabolization of arsenite (As(III)), arsenate (As(V)), monomethylarsonate (MMA(V)), and dimethylarsinate (DMA(V)) by the model plant Tropaeolum majus. In contrast to existing extraction methods hazardous additives and elaborate procedures to enhance the extraction yields were omitted. The proposed protocol is suited to down-scale the sample sizes used for the extractions and to promote a compartmentally resolved analysis of the arsenic distribution within individual leaves, leaf stalks, and stems instead of the conventional extraction of pooled samples. In a two-step extraction, the high extraction efficiencies (85-92%) for arsenic achieved by phosphate buffer from larger amounts (200mg) of homogenized leaf material in a one-step extraction, could be enhanced to 94-100% in a second extraction step. A strong dependence of the arsenic extractability on the type of arsenic species accumulated in the tissue as well as on the type of the tissue (leaf, leaf stalk, stem) was found. For the extraction of 5mm long segments cut from individual leaves without previous homogenization of the plant parts yields between 75 and 93% depending on arsenic species prevailing in the cells were obtained using 1 or 10mM phosphate buffer. The total extraction and analysis protocol was validated using a standard reference material as well as by spiking experiments. The arsenic species analysis by IC/ICPMS revealed a number of nine unidentified metabolites in the plant extracts in addition to the species MMA(V), DMA(V), As(III), and As(V) that were provided to the plants during their growth phase.

  17. Reproducibility of 5-HT2A receptor measurements and sample size estimations with [18F]altanserin PET using a bolus/infusion approach

    DEFF Research Database (Denmark)

    Haugbøl, Steven; Pinborg, Lars H; Arfan, Haroon M

    2006-01-01

    PURPOSE: To determine the reproducibility of measurements of brain 5-HT2A receptors with an [18F]altanserin PET bolus/infusion approach. Further, to estimate the sample size needed to detect regional differences between two groups and, finally, to evaluate how partial volume correction affects...... reproducibility and the required sample size. METHODS: For assessment of the variability, six subjects were investigated with [18F]altanserin PET twice, at an interval of less than 2 weeks. The sample size required to detect a 20% difference was estimated from [18F]altanserin PET studies in 84 healthy subjects......% (range 5-12%), whereas in regions with a low receptor density, BP1 reproducibility was lower, with a median difference of 17% (range 11-39%). Partial volume correction reduced the variability in the sample considerably. The sample size required to detect a 20% difference in brain regions with high...

  18. Accurate and equitable medical genomic analysis requires an understanding of demography and its influence on sample size and ratio.

    Science.gov (United States)

    Kessler, Michael D; O'Connor, Timothy D

    2017-02-27

    In a recent study, Petrovski and Goldstein reported that (non-Finnish) Europeans have significantly fewer nonsynonymous singletons in Online Mendelian Inheritance in Man (OMIM) disease genes compared with Africans, Latinos, South Asians, East Asians, and other unassigned non-Europeans. We use simulations of Exome Aggregation Consortium (ExAC) data to show that sample size and ratio interact to influence the number of these singletons identified in a cohort. These interactions are different across ancestries and can lead to the same number of identified singletons in both Europeans and non-Europeans without an equal number of samples. We conclude that there is a need to account for the ancestry-specific influence of demography on genomic architecture and rare variant analysis in order to address inequalities in medical genomic analysis.The authors of the original article were invited to submit a response, but declined to do so. Please see related Open Letter: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1016-y.

  19. Test results of the first 50 kA NbTi full size sample for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Ciazynski, D.; Zani, L. [Association Euratom-CEA Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee; Ciotti, M.; Gislon, P.; Spadoni, M. [Association Euratom-ENEA sulla Fusione Centro Ricerche Energia Frascati (Italy); Huber, S.; Stepanov, B. [Association Euratom-Confederation Suisse, EPFL, CRPP-TF, Villigen (Switzerland); Karlemo, B. [European Fusion Development Agreement - Close Support Unit (EFDA/CSU), Max-Planck-Institut fuer Plasmaphysik, Garching (Germany)

    2003-07-01

    Within the framework of the research studies for the International Thermonuclear Experimental Reactor (ITER) project, the first full size NbTi conductor sample was fabricated in industry and tested in the SULTAN facility (Villigen, Switzerland). This sample (PF-FSJS), which is relevant to the Poloidal Field coils of ITER, is composed of two parallel straight bars of conductor, connected at bottom through a joint designed according to the Cea twin-box concept. The two conductor legs are identical except for the use of different strands: a nickel plated NbTi strand with a pure copper matrix in one leg, and a bare NbTi strand with copper matrix and internal CuNi barrier in the other leg. The two conductors and the joint were extensively tested regarding DC (direct current) and AC (alternative current) properties. This paper reports on the tests results and analysis, stressing the differences between the two conductor legs and discussing the impact of the test results on the ITER design criteria for conductor and joint. While joint DC resistance, conductors and joint AC losses, fulfilled the ITER requirements, neither conductor could reach its current sharing temperature at relevant ITER currents, due to instabilities. Although the drop in temperature is slight for the CuNi strand cable, it is more significant for the Ni plated strand cable. (authors)

  20. Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

    Science.gov (United States)

    Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

    2012-01-01

    The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

  1. Comparative study of manual liquid-based cytology (MLBC technique and direct smear technique (conventional on fine-needle cytology/fine-needle aspiration cytology samples

    Directory of Open Access Journals (Sweden)

    Prajkta Suresh Pawar

    2014-01-01

    Conclusion: This MLBC technique gives results comparable to the conventional technique with better morphology. In a set up where aspirators are learners, this technique will ensure adequacy due to remnant in needle hub getting processed

  2. Sediment Grain Size Measurements: Is There a Differenc Between Digested and Un-digested Samples? And Does the Organic Carbon of the Sample Play a Role

    Science.gov (United States)

    Grain size is a physical measurement commonly made in the analysis of many benthic systems. Grain size influences benthic community composition, can influence contaminant loading and can indicate the energy regime of a system. We have recently investigated the relationship betw...

  3. Archive of sediment physical properties and grain-size data for sediment samples collected offshore of Assateague Island, Maryland and Virginia

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland...

  4. The Effect of Sample Size and Data Numbering on Precision of Calibration Model to predict Soil Properties

    Directory of Open Access Journals (Sweden)

    H Mohamadi Monavar

    2017-10-01

    Full Text Available Introduction Precision agriculture (PA is a technology that measures and manages within-field variability, such as physical and chemical properties of soil. The nondestructive and rapid VIS-NIR technology detected a significant correlation between reflectance spectra and the physical and chemical properties of soil. On the other hand, quantitatively predict of soil factors such as nitrogen, carbon, cation exchange capacity and the amount of clay in precision farming is very important. The emphasis of this paper is comparing different techniques of choosing calibration samples such as randomly selected method, chemical data and also based on PCA. Since increasing the number of samples is usually time-consuming and costly, then in this study, the best sampling way -in available methods- was predicted for calibration models. In addition, the effect of sample size on the accuracy of the calibration and validation models was analyzed. Materials and Methods Two hundred and ten soil samples were collected from cultivated farm located in Avarzaman in Hamedan province, Iran. The crop rotation was mostly potato and wheat. Samples were collected from a depth of 20 cm above ground and passed through a 2 mm sieve and air dried at room temperature. Chemical analysis was performed in the soil science laboratory, faculty of agriculture engineering, Bu-ali Sina University, Hamadan, Iran. Two Spectrometer (AvaSpec-ULS 2048- UV-VIS and (FT-NIR100N were used to measure the spectral bands which cover the UV-Vis and NIR region (220-2200 nm. Each soil sample was uniformly tiled in a petri dish and was scanned 20 times. Then the pre-processing methods of multivariate scatter correction (MSC and base line correction (BC were applied on the raw signals using Unscrambler software. The samples were divided into two groups: one group for calibration 105 and the second group was used for validation. Each time, 15 samples were selected randomly and tested the accuracy of

  5. Sampling surface and subsurface particle-size distributions in wadable gravel-and cobble-bed streams for analyses in sediment transport, hydraulics, and streambed monitoring

    Science.gov (United States)

    Kristin Bunte; Steven R. Abt

    2001-01-01

    This document provides guidance for sampling surface and subsurface sediment from wadable gravel-and cobble-bed streams. After a short introduction to streams types and classifications in gravel-bed rivers, the document explains the field and laboratory measurement of particle sizes and the statistical analysis of particle-size distributions. Analysis of particle...

  6. Pb isotope analysis of ng size samples by TIMS equipped with a 1013 Ω resistor using a 207Pb-204Pb double spike

    NARCIS (Netherlands)

    Klaver, M.; Smeets, R.J.; Koornneef, J.M.; Davies, G.R.; Vroon, P.Z.

    2016-01-01

    The use of the double spike technique to correct for instrumental mass fractionation has yielded high precision results for lead isotope measurements by thermal ionisation mass spectrometry (TIMS), but the applicability to ng size Pb samples is hampered by the small size of the

  7. Characterization of Dissolved Organic Matter in River Water by Conventional Methods and Direct Sample Analysis-Time of Flight-Mass Spectrometry

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    T. Garrido Reyes

    2016-01-01

    Full Text Available The dissolved organic matter in surface waters is composed of fractions of different molecular weight and polarity, characteristics that determine their capacity for complexing different types of pollutants and their environmental impact. In this study, the dissolved organic matter in the surface water of the Bio-Bio River (Central Region of Chile was characterized chemically and spectroscopically after fractionating by molecular weight and polarity. The technique of direct sample analysis-time of flight-mass spectrometry (DSA-TOF-MS was used to obtain more information on the composition of dissolved organic matter. It is concluded that dissolved organic matter found in the water of the river from the site of minor human impact (Rucalhue has a predominantly natural origin, with a high content of aromatic carbon, in contrast to dissolved organic matter found in the waters of the sites that have higher human impact (Laja and Concepción, characterized by a greater molecular size and higher organic carbon content. These results are consistent with those obtained from DSA-TOF-MS, where higher correlation was observed between the mass spectrum of the standard commercial humic acid and dissolved organic matter found in the sectors of Laja and Concepción, unlike the spectrum mass of lignin which is more like dissolved organic matter found in the sector Rucalhue.

  8. Sample size matters in dietary gene expression studies—A case study in the gilthead sea bream (Sparus aurata L.

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    Fotini Kokou

    2016-05-01

    Full Text Available One of the main concerns in gene expression studies is the calculation of statistical significance which in most cases remains low due to limited sample size. Increasing biological replicates translates into more effective gains in power which, especially in nutritional experiments, is of great importance as individual variation of growth performance parameters and feed conversion is high. The present study investigates in the gilthead sea bream Sparus aurata, one of the most important Mediterranean aquaculture species. For 24 gilthead sea bream individuals (biological replicates the effects of gradual substitution of fish meal by plant ingredients (0% (control, 25%, 50% and 75% in the diets were studied by looking at expression levels of four immune-and stress-related genes in intestine, head kidney and liver. The present results showed that only the lowest substitution percentage is tolerated and that liver is the most sensitive tissue to detect gene expression variations in relation to fish meal substituted diets. Additionally the usage of three independent biological replicates were evaluated by calculating the averages of all possible triplets in order to assess the suitability of selected genes for stress indication as well as the impact of the experimental set up, thus in the present work the impact of FM substitution. Gene expression was altered depending of the selected biological triplicate. Only for two genes in liver (hsp70 and tgf significant differential expression was assured independently of the triplicates used. These results underlined the importance of choosing the adequate sample number especially when significant, but minor differences in gene expression levels are observed.

  9. Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes

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    Kropf Siegfried

    2008-01-01

    Full Text Available Abstract Background In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio is biologically meaningless. A relevant difference or ratio is sought in such cases. Results This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. Conclusion The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

  10. Focal spot size reduction using asymmetric collimation to enable reduced anode angles with a conventional angiographic x-ray tube for use with high resolution detectors

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    Russ, M.; Shankar, A.; Setlur Nagesh, S. V.; Ionita, C. N.; Bednarek, D. R.; Rudin, S.

    2017-03-01

    The high-resolution requirements for neuro-endovascular image-guided interventions (EIGIs) necessitate the use of a small focal-spot size; however, the maximum tube output limits for such small focal-spot sizes may not enable sufficient x-ray fluence after attenuation through the human head to support the desired image quality. This may necessitate the use of a larger focal spot, thus contributing to the overall reduction in resolution. A method for creating a higher-output small effective focal spot based on the line-focus principle has been demonstrated and characterized. By tilting the C-arm gantry, the anode-side of the x-ray field-of-view is accessible using a detector placed off-axis. This tilted central axis diminishes the resultant focal spot size in the anode-cathode direction by the tangent of the effective anode angle, allowing a medium focal spot to be used in place of a small focal spot with minimal losses in resolution but with increased tube output. Images were acquired of two different objects at the central axis, and with the C-arm tilted away from the central axis at 1° increments from 0°-7°. With standard collimation settings, only 6° was accessible, but using asymmetric extended collimation a maximum of 7° was accessed for enhanced comparisons. All objects were positioned perpendicular to the anode-cathode direction and images were compared qualitatively. The increasing advantage of the off-axis focal spots was quantitatively evidenced at each subsequent angle using the Generalized Measured-Relative Object Detectability metric (GM-ROD). This anode-tilt method is a simple and robust way of increasing tube output for a small field-of-view detector without diminishing the overall apparent resolution for neuro-EIGIs.

  11. Statistical process control charts for attribute data involving very large sample sizes: a review of problems and solutions.

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    Mohammed, Mohammed A; Panesar, Jagdeep S; Laney, David B; Wilson, Richard

    2013-04-01

    The use of statistical process control (SPC) charts in healthcare is increasing. The primary purpose of SPC is to distinguish between common-cause variation which is attributable to the underlying process, and special-cause variation which is extrinsic to the underlying process. This is important because improvement under common-cause variation requires action on the process, whereas special-cause variation merits an investigation to first find the cause. Nonetheless, when dealing with attribute or count data (eg, number of emergency admissions) involving very large sample sizes, traditional SPC charts often produce tight control limits with most of the data points appearing outside the control limits. This can give a false impression of common and special-cause variation, and potentially misguide the user into taking the wrong actions. Given the growing availability of large datasets from routinely collected databases in healthcare, there is a need to present a review of this problem (which arises because traditional attribute charts only consider within-subgroup variation) and its solutions (which consider within and between-subgroup variation), which involve the use of the well-established measurements chart and the more recently developed attribute charts based on Laney's innovative approach. We close by making some suggestions for practice.

  12. Bayesian principal component regression model with spatial effects for forest inventory variables under small field sample size

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    Junttila, Virpi; Laine, Marko

    2017-04-01

    Remote sensing observations are extensively used for analysis of environmental variables. These variables often exhibit spatial correlation, which has to be accounted for in the calibration models used in predictions, either by direct modelling of the dependencies or by allowing for spatially correlated stochastic effects. Another feature in many remote sensing instruments is that the derived predictor variables are highly correlated, which can lead to unnecessary model over-training and at worst, singularities in the estimates. Both of these affect the prediction accuracy, especially when the training set for model calibration is small. To overcome these modelling challenges, we present a general model calibration procedure for remotely sensed data and apply it to airborne laser scanning data for forest inventory. We use a linear regression model that accounts for multicollinearity in the predictors by principal components and Bayesian regularization. It has a spatial random effect component for the spatial correlations that are not explained by a simple linear model. An efficient Markov chain Monte Carlo sampling scheme is used to account for the uncertainty in all the model parameters. We tested the proposed model against several alternatives and it outperformed the other linear calibration models, especially when there were spatial effects, multicollinearity and the training set size was small.

  13. Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data.

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    Yılmaz Isıkhan, Selen; Karabulut, Erdem; Alpar, Celal Reha

    2016-01-01

    Background/Aim. Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques. Materials and Methods. Eleven real gene expression datasets containing dose values were included. First, important genes for dose prediction were selected using iterative sure independence screening. Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined. Results. The results demonstrated that a regression-based feature selection method substantially reduced the number of irrelevant genes from raw datasets. Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM). Conclusion. Analysis of various dose values based on microarray gene expression data identified common genes found in our study and the referenced studies. According to our findings, SVR and GBM can be good predictors of dose-gene datasets. Another result of the study was to identify the sample size of n = 25 as a cutoff point for RT bagging to outperform a single RT.

  14. Sample size determination for a specific region in multiregional clinical trials with multiple co-primary endpoints.

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    Wong-Shian Huang

    Full Text Available Recently, multi-regional clinical trials (MRCTs, which incorporate subjects from many countries/regions around the world under the same protocol, have been widely conducted by many global pharmaceutical companies. The objective of such trials is to accelerate the development process for a drug and shorten the drug's approval time in key markets. Several statistical methods have been purposed for the design and evaluation of MRCTs, as well as for assessing the consistency of treatment effects across all regions with one primary endpoint. However, in some therapeutic areas (e.g., Alzheimer's disease, the clinical efficacy of a new treatment may be characterized by a set of possibly correlated endpoints, known as multiple co-primary endpoints. In this paper, we focus on a specific region and establish three statistical criteria for evaluating consistency between the specific region and overall results in MRCTs with multiple co-primary endpoints. More specifically, two of those criteria are used to assess whether the treatment effect in the region of interest is as large as that of the other regions or of the regions overall, while the other criterion is used to assess the consistency of the treatment effect of the specific region achieving a pre-specified threshold. The sample size required for the region of interest can also be evaluated based on these three criteria.

  15. Conditional and Unconditional Tests (and Sample Size Based on Multiple Comparisons for Stratified 2 × 2 Tables

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    A. Martín Andrés

    2015-01-01

    Full Text Available The Mantel-Haenszel test is the most frequent asymptotic test used for analyzing stratified 2 × 2 tables. Its exact alternative is the test of Birch, which has recently been reconsidered by Jung. Both tests have a conditional origin: Pearson’s chi-squared test and Fisher’s exact test, respectively. But both tests have the same drawback that the result of global test (the stratified test may not be compatible with the result of individual tests (the test for each stratum. In this paper, we propose to carry out the global test using a multiple comparisons method (MC method which does not have this disadvantage. By refining the method (MCB method an alternative to the Mantel-Haenszel and Birch tests may be obtained. The new MC and MCB methods have the advantage that they may be applied from an unconditional view, a methodology which until now has not been applied to this problem. We also propose some sample size calculation methods.

  16. Theoretical basis, application, reliability, and sample size estimates of a Meridian Energy Analysis Device for Traditional Chinese Medicine Research.

    Science.gov (United States)

    Tsai, Ming-Yen; Chen, Shih-Yu; Lin, Chung-Chun

    2017-04-01

    The Meridian Energy Analysis Device is currently a popular tool in the scientific research of meridian electrophysiology. In this field, it is generally believed that measuring the electrical conductivity of meridians provides information about the balance of bioenergy or Qi-blood in the body. PubMed database based on some original articles from 1956 to 2014 and the authoŕs clinical experience. In this short communication, we provide clinical examples of Meridian Energy Analysis Device application, especially in the field of traditional Chinese medicine, discuss the reliability of the measurements, and put the values obtained into context by considering items of considerable variability and by estimating sample size. The Meridian Energy Analysis Device is making a valuable contribution to the diagnosis of Qi-blood dysfunction. It can be assessed from short-term and long-term meridian bioenergy recordings. It is one of the few methods that allow outpatient traditional Chinese medicine diagnosis, monitoring the progress, therapeutic effect and evaluation of patient prognosis. The holistic approaches underlying the practice of traditional Chinese medicine and new trends in modern medicine toward the use of objective instruments require in-depth knowledge of the mechanisms of meridian energy, and the Meridian Energy Analysis Device can feasibly be used for understanding and interpreting traditional Chinese medicine theory, especially in view of its expansion in Western countries.

  17. Current practice in methodology and reporting of the sample size calculation in randomised trials of hip and knee osteoarthritis: a protocol for a systematic review.

    Science.gov (United States)

    Copsey, Bethan; Dutton, Susan; Fitzpatrick, Ray; Lamb, Sarah E; Cook, Jonathan A

    2017-10-10

    A key aspect of the design of randomised controlled trials (RCTs) is determining the sample size. It is important that the trial sample size is appropriately calculated. The required sample size will differ by clinical area, for instance, due to the prevalence of the condition and the choice of primary outcome. Additionally, it will depend upon the choice of target difference assumed in the calculation. Focussing upon the hip and knee osteoarthritis population, this study aims to systematically review how the trial size was determined for trials of osteoarthritis, on what basis, and how well these aspects are reported. Several electronic databases (Medline, Cochrane library, CINAHL, EMBASE, PsycINFO, PEDro and AMED) will be searched to identify articles on RCTs of hip and knee osteoarthritis published in 2016. Articles will be screened for eligibility and data extracted independently by two reviewers. Data will be extracted on study characteristics (design, population, intervention and control treatments), primary outcome, chosen sample size and justification, parameters used to calculate the sample size (including treatment effect in control arm, level of variability in primary outcome, loss to follow-up rates). Data will be summarised across the studies using appropriate summary statistics (e.g. n and %, median and interquartile range). The proportion of studies which report each key component of the sample size calculation will be presented. The reproducibility of the sample size calculation will be tested. The findings of this systematic review will summarise the current practice for sample size calculation in trials of hip and knee osteoarthritis. It will also provide evidence on the completeness of the reporting of the sample size calculation, reproducibility of the chosen sample size and the basis for the values used in the calculation. As this review was not eligible to be registered on PROSPERO, the summary information was uploaded to Figshare to make it

  18. Estimates of genetic differentiation measured by F(ST do not necessarily require large sample sizes when using many SNP markers.

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    Eva-Maria Willing

    Full Text Available Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. F(ST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer F(ST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating F(ST. We tested the behavior of three different estimators that infer F(ST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4-6 when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000. Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.

  19. Development of the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method for recruiting urban nightlife-goers in an entire city

    NARCIS (Netherlands)

    Labhart, F.; Santani, D.; Truong, J.; Tarsetti, F.; Bornet, O.; Landolt, S.; Gatica-Perez, D.; Kuntsche, E.N.

    2017-01-01

    We developed the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method in order to obtain a sample of nightlife-goers which accounted for the diversity of spaces, patrons and locations within two Swiss cities. Popular nightlife zones were identified and quantified using social

  20. Diet- and Body Size-Related Attitudes and Behaviors Associated with Vitamin Supplement Use in a Representative Sample of Fourth-Grade Students in Texas

    Science.gov (United States)

    George, Goldy C.; Hoelscher, Deanna M.; Nicklas, Theresa A.; Kelder, Steven H.

    2009-01-01

    Objective: To examine diet- and body size-related attitudes and behaviors associated with supplement use in a representative sample of fourth-grade students in Texas. Design: Cross-sectional data from the School Physical Activity and Nutrition study, a probability-based sample of schoolchildren. Children completed a questionnaire that assessed…

  1. Diffuse myocardial fibrosis evaluation using cardiac magnetic resonance T1 mapping: sample size considerations for clinical trials

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    Liu Songtao

    2012-12-01

    Full Text Available Abstract Background Cardiac magnetic resonance (CMR T1 mapping has been used to characterize myocardial diffuse fibrosis. The aim of this study is to determine the reproducibility and sample size of CMR fibrosis measurements that would be applicable in clinical trials. Methods A modified Look-Locker with inversion recovery (MOLLI sequence was used to determine myocardial T1 values pre-, and 12 and 25min post-administration of a gadolinium-based contrast agent at 3 Tesla. For 24 healthy subjects (8 men; 29 ± 6 years, two separate scans were obtained a with a bolus of 0.15mmol/kg of gadopentate dimeglumine and b 0.1mmol/kg of gadobenate dimeglumine, respectively, with averaged of 51 ± 34 days between two scans. Separately, 25 heart failure subjects (12 men; 63 ± 14 years, were evaluated after a bolus of 0.15mmol/kg of gadopentate dimeglumine. Myocardial partition coefficient (λ was calculated according to (ΔR1myocardium/ΔR1blood, and ECV was derived from λ by adjusting (1-hematocrit. Results Mean ECV and λ were both significantly higher in HF subjects than healthy (ECV: 0.287 ± 0.034 vs. 0.267 ± 0.028, p=0.002; λ: 0.481 ± 0.052 vs. 442 ± 0.037, p Conclusion ECV and λ quantification have a low variability across scans, and could be a viable tool for evaluating clinical trial outcome.

  2. Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    Science.gov (United States)

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2017-08-01

    Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple as