(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research

Science.gov (United States)

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: “random chance,” which is based on probability sampling, “minimal information,” which yields at least one new code per sampling step, and “maximum information,” which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario. PMID:28746358

Size Matters: Assessing Optimum Soil Sample Size for Fungal and Bacterial Community Structure Analyses Using High Throughput Sequencing of rRNA Gene Amplicons

Directory of Open Access Journals (Sweden)

Christopher Ryan Penton

2016-06-01

Full Text Available We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5 and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungal community structure, replicate dispersion and the number of operational taxonomic units (OTUs retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation.

Sample size calculations for case-control studies

Science.gov (United States)

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

Science.gov (United States)

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure

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.

Estimating Sample Size for Usability Testing

Directory of Open Access Journals (Sweden)

Alex Cazañas

2017-02-01

Full Text Available One strategy used to assure that an interface meets user requirements is to conduct usability testing. When conducting such testing one of the unknowns is sample size. Since extensive testing is costly, minimizing the number of participants can contribute greatly to successful resource management of a project. Even though a significant number of models have been proposed to estimate sample size in usability testing, there is still not consensus on the optimal size. Several studies claim that 3 to 5 users suffice to uncover 80% of problems in a software interface. However, many other studies challenge this assertion. This study analyzed data collected from the user testing of a web application to verify the rule of thumb, commonly known as the “magic number 5”. The outcomes of the analysis showed that the 5-user rule significantly underestimates the required sample size to achieve reasonable levels of problem detection.

Sample Size Determination for One- and Two-Sample Trimmed Mean Tests

Science.gov (United States)

Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng

2008-01-01

Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…

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.

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.

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.

40 CFR 80.127 - Sample size guidelines.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Sample size guidelines. 80.127 Section 80.127 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Attest Engagements § 80.127 Sample size guidelines. In performing the...

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.

Determination of a representative volume element based on the variability of mechanical properties with sample size in bread.

Science.gov (United States)

Ramírez, Cristian; Young, Ashley; James, Bryony; Aguilera, José M

2010-10-01

Quantitative analysis of food structure is commonly obtained by image analysis of a small portion of the material that may not be the representative of the whole sample. In order to quantify structural parameters (air cells) of 2 types of bread (bread and bagel) the concept of representative volume element (RVE) was employed. The RVE for bread, bagel, and gelatin-gel (used as control) was obtained from the relationship between sample size and the coefficient of variation, calculated from the apparent Young's modulus measured on 25 replicates. The RVE was obtained when the coefficient of variation for different sample sizes converged to a constant value. In the 2 types of bread tested, the tendency of the coefficient of variation was to decrease as the sample size increased, while in the homogeneous gelatin-gel, it remained always constant around 2.3% to 2.4%. The RVE resulted to be cubes with sides of 45 mm for bread, 20 mm for bagels, and 10 mm for gelatin-gel (smallest sample tested). The quantitative image analysis as well as visual observation demonstrated that bread presented the largest dispersion of air-cell sizes. Moreover, both the ratio of maximum air-cell area/image area and maximum air-cell height/image height were greater for bread (values of 0.05 and 0.30, respectively) than for bagels (0.03 and 0.20, respectively). Therefore, the size and the size variation of air cells present in the structure determined the size of the RVE. It was concluded that RVE is highly dependent on the heterogeneity of the structure of the types of baked products.

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

[Practical aspects regarding sample size in clinical research].

Science.gov (United States)

Vega Ramos, B; Peraza Yanes, O; Herrera Correa, G; Saldívar Toraya, S

1996-01-01

The knowledge of the right sample size let us to be sure if the published results in medical papers had a suitable design and a proper conclusion according to the statistics analysis. To estimate the sample size we must consider the type I error, type II error, variance, the size of the effect, significance and power of the test. To decide what kind of mathematics formula will be used, we must define what kind of study we have, it means if its a prevalence study, a means values one or a comparative one. In this paper we explain some basic topics of statistics and we describe four simple samples of estimation of sample size.

Sample size calculation in metabolic phenotyping studies.

Science.gov (United States)

Billoir, Elise; Navratil, Vincent; Blaise, Benjamin J

2015-09-01

The number of samples needed to identify significant effects is a key question in biomedical studies, with consequences on experimental designs, costs and potential discoveries. In metabolic phenotyping studies, sample size determination remains a complex step. This is due particularly to the multiple hypothesis-testing framework and the top-down hypothesis-free approach, with no a priori known metabolic target. Until now, there was no standard procedure available to address this purpose. In this review, we discuss sample size estimation procedures for metabolic phenotyping studies. We release an automated implementation of the Data-driven Sample size Determination (DSD) algorithm for MATLAB and GNU Octave. Original research concerning DSD was published elsewhere. DSD allows the determination of an optimized sample size in metabolic phenotyping studies. The procedure uses analytical data only from a small pilot cohort to generate an expanded data set. The statistical recoupling of variables procedure is used to identify metabolic variables, and their intensity distributions are estimated by Kernel smoothing or log-normal density fitting. Statistically significant metabolic variations are evaluated using the Benjamini-Yekutieli correction and processed for data sets of various sizes. Optimal sample size determination is achieved in a context of biomarker discovery (at least one statistically significant variation) or metabolic exploration (a maximum of statistically significant variations). DSD toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) for Kernel and log-normal estimates, and in GNU Octave for log-normal estimates (Kernel density estimates are not robust enough in GNU octave). It is available at http://www.prabi.fr/redmine/projects/dsd/repository, with a tutorial at http://www.prabi.fr/redmine/projects/dsd/wiki. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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.

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...

Fluctuations in the size of the largest projectile fragment produced in 1 GeV/nucleon Au + C collisions

International Nuclear Information System (INIS)

Warren, P.; Elliott, J.B.; Gilkes, M.L.; Hauger, A.; Hirsch, A.S.

1993-01-01

Large fluctuations in quantities such as density are characteristic of critical phenomena in the neighborhood of the critical point. Using the EOS apparatus at the Bevalac, we have performed an exclusive experiment in which the size of the largest projectile fragment produced in 1 GeV/nucleon Au+C collisions is studied as a function of the charged multiplicity of the event. A peak in the fluctuations is expected at the critical multiplicity. The data are compared to a percolation model and a statistical multifragmentation model

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.

Estimation of sample size and testing power (Part 4).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-01-01

Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.

Discovery of the largest orbweaving spider species: the evolution of gigantism in Nephila.

Science.gov (United States)

Kuntner, Matjaz; Coddington, Jonathan A

2009-10-21

More than 41,000 spider species are known with about 400-500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19(th) century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD) and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa and Madagascar, and review size evolution and SSD in Nephilidae. We formally describe N. komaci sp. nov., the largest web spinning species known, and place the species in phylogenetic context to reconstruct the evolution of mean size (via squared change parsimony). We then test female and male mean size correlation using phylogenetically independent contrasts, and simulate nephilid body size evolution using Monte Carlo statistics. Nephila females increased in size almost monotonically to establish a mostly African clade of true giants. In contrast, Nephila male size is effectively decoupled and hovers around values roughly one fifth of female size. Although N. komaci females are the largest Nephila yet discovered, the males are also large and thus their SSD is not exceptional.

Discovery of the largest orbweaving spider species: the evolution of gigantism in Nephila.

Directory of Open Access Journals (Sweden)

Matjaz Kuntner

2009-10-01

Full Text Available More than 41,000 spider species are known with about 400-500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19(th century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa and Madagascar, and review size evolution and SSD in Nephilidae.We formally describe N. komaci sp. nov., the largest web spinning species known, and place the species in phylogenetic context to reconstruct the evolution of mean size (via squared change parsimony. We then test female and male mean size correlation using phylogenetically independent contrasts, and simulate nephilid body size evolution using Monte Carlo statistics.Nephila females increased in size almost monotonically to establish a mostly African clade of true giants. In contrast, Nephila male size is effectively decoupled and hovers around values roughly one fifth of female size. Although N. komaci females are the largest Nephila yet discovered, the males are also large and thus their SSD is not exceptional.

Preeminence and prerequisites of sample size calculations in clinical trials

OpenAIRE

Richa Singhal; Rakesh Rana

2015-01-01

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 out...

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.

Optimal sample size for probability of detection curves

International Nuclear Information System (INIS)

Annis, Charles; Gandossi, Luca; Martin, Oliver

2013-01-01

Highlights: • We investigate sample size requirement to develop probability of detection curves. • We develop simulations to determine effective inspection target sizes, number and distribution. • We summarize these findings and provide guidelines for the NDE practitioner. -- Abstract: The use of probability of detection curves to quantify the reliability of non-destructive examination (NDE) systems is common in the aeronautical industry, but relatively less so in the nuclear industry, at least in European countries. Due to the nature of the components being inspected, sample sizes tend to be much lower. This makes the manufacturing of test pieces with representative flaws, in sufficient numbers, so to draw statistical conclusions on the reliability of the NDT system under investigation, quite costly. The European Network for Inspection and Qualification (ENIQ) has developed an inspection qualification methodology, referred to as the ENIQ Methodology. It has become widely used in many European countries and provides assurance on the reliability of NDE systems, but only qualitatively. The need to quantify the output of inspection qualification has become more important as structural reliability modelling and quantitative risk-informed in-service inspection methodologies become more widely used. A measure of the NDE reliability is necessary to quantify risk reduction after inspection and probability of detection (POD) curves provide such a metric. The Joint Research Centre, Petten, The Netherlands supported ENIQ by investigating the question of the sample size required to determine a reliable POD curve. As mentioned earlier manufacturing of test pieces with defects that are typically found in nuclear power plants (NPPs) is usually quite expensive. Thus there is a tendency to reduce sample sizes, which in turn increases the uncertainty associated with the resulting POD curve. The main question in conjunction with POS curves is the appropriate sample size. Not

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. 

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.

Revisiting sample size: are big trials the answer?

Science.gov (United States)

Lurati Buse, Giovanna A L; Botto, Fernando; Devereaux, P J

2012-07-18

The superiority of the evidence generated in randomized controlled trials over observational data is not only conditional to randomization. Randomized controlled trials require proper design and implementation to provide a reliable effect estimate. Adequate random sequence generation, allocation implementation, analyses based on the intention-to-treat principle, and sufficient power are crucial to the quality of a randomized controlled trial. Power, or the probability of the trial to detect a difference when a real difference between treatments exists, strongly depends on sample size. The quality of orthopaedic randomized controlled trials is frequently threatened by a limited sample size. This paper reviews basic concepts and pitfalls in sample-size estimation and focuses on the importance of large trials in the generation of valid evidence.

Test of a sample container for shipment of small size plutonium samples with PAT-2

International Nuclear Information System (INIS)

Kuhn, E.; Aigner, H.; Deron, S.

1981-11-01

A light-weight container for the air transport of plutonium, to be designated PAT-2, has been developed in the USA and is presently undergoing licensing. The very limited effective space for bearing plutonium required the design of small size sample canisters to meet the needs of international safeguards for the shipment of plutonium samples. The applicability of a small canister for the sampling of small size powder and solution samples has been tested in an intralaboratory experiment. The results of the experiment, based on the concept of pre-weighed samples, show that the tested canister can successfully be used for the sampling of small size PuO 2 -powder samples of homogeneous source material, as well as for dried aliquands of plutonium nitrate solutions. (author)

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.

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

International Nuclear Information System (INIS)

Taylor, Stephen; Muylem, Alain van; Howarth, Nigel; Gevenois, Pierre Alain; Tack, Denis

2017-01-01

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.)

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.)

Sample-size dependence of diversity indices and the determination of sufficient sample size in a high-diversity deep-sea environment

OpenAIRE

Soetaert, K.; Heip, C.H.R.

1990-01-01

Diversity indices, although designed for comparative purposes, often cannot be used as such, due to their sample-size dependence. It is argued here that this dependence is more pronounced in high diversity than in low diversity assemblages and that indices more sensitive to rarer species require larger sample sizes to estimate diversity with reasonable precision than indices which put more weight on commoner species. This was tested for Hill's diversity number N sub(0) to N sub( proportional ...

Sample size calculation for comparing two negative binomial rates.

Science.gov (United States)

Zhu, Haiyuan; Lakkis, Hassan

2014-02-10

Negative binomial model has been increasingly used to model the count data in recent clinical trials. It is frequently chosen over Poisson model in cases of overdispersed count data that are commonly seen in clinical trials. One of the challenges of applying negative binomial model in clinical trial design is the sample size estimation. In practice, simulation methods have been frequently used for sample size estimation. In this paper, an explicit formula is developed to calculate sample size based on the negative binomial model. Depending on different approaches to estimate the variance under null hypothesis, three variations of the sample size formula are proposed and discussed. Important characteristics of the formula include its accuracy and its ability to explicitly incorporate dispersion parameter and exposure time. The performance of the formula with each variation is assessed using simulations. Copyright © 2013 John Wiley & Sons, Ltd.

Estimation of sample size and testing power (part 5).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-02-01

Estimation of sample size and testing power is an important component of research design. This article introduced methods for sample size and testing power estimation of difference test for quantitative and qualitative data with the single-group design, the paired design or the crossover design. To be specific, this article introduced formulas for sample size and testing power estimation of difference test for quantitative and qualitative data with the above three designs, the realization based on the formulas and the POWER procedure of SAS software and elaborated it with examples, which will benefit researchers for implementing the repetition principle.

Sampling of illicit drugs for quantitative analysis--part II. Study of particle size and its influence on mass reduction.

Science.gov (United States)

Bovens, M; Csesztregi, T; Franc, A; Nagy, J; Dujourdy, L

2014-01-01

The basic goal in sampling for the quantitative analysis of illicit drugs is to maintain the average concentration of the drug in the material from its original seized state (the primary sample) all the way through to the analytical sample, where the effect of particle size is most critical. The size of the largest particles of different authentic illicit drug materials, in their original state and after homogenisation, using manual or mechanical procedures, was measured using a microscope with a camera attachment. The comminution methods employed included pestle and mortar (manual) and various ball and knife mills (mechanical). The drugs investigated were amphetamine, heroin, cocaine and herbal cannabis. It was shown that comminution of illicit drug materials using these techniques reduces the nominal particle size from approximately 600 μm down to between 200 and 300 μm. It was demonstrated that the choice of 1 g increments for the primary samples of powdered drugs and cannabis resin, which were used in the heterogeneity part of our study (Part I) was correct for the routine quantitative analysis of illicit seized drugs. For herbal cannabis we found that the appropriate increment size was larger. Based on the results of this study we can generally state that: An analytical sample weight of between 20 and 35 mg of an illicit powdered drug, with an assumed purity of 5% or higher, would be considered appropriate and would generate an RSDsampling in the same region as the RSDanalysis for a typical quantitative method of analysis for the most common, powdered, illicit drugs. For herbal cannabis, with an assumed purity of 1% THC (tetrahydrocannabinol) or higher, an analytical sample weight of approximately 200 mg would be appropriate. In Part III we will pull together our homogeneity studies and particle size investigations and use them to devise sampling plans and sample preparations suitable for the quantitative instrumental analysis of the most common illicit

Frictional behaviour of sandstone: A sample-size dependent triaxial investigation

Science.gov (United States)

Roshan, Hamid; Masoumi, Hossein; Regenauer-Lieb, Klaus

2017-01-01

Frictional behaviour of rocks from the initial stage of loading to final shear displacement along the formed shear plane has been widely investigated in the past. However the effect of sample size on such frictional behaviour has not attracted much attention. This is mainly related to the limitations in rock testing facilities as well as the complex mechanisms involved in sample-size dependent frictional behaviour of rocks. In this study, a suite of advanced triaxial experiments was performed on Gosford sandstone samples at different sizes and confining pressures. The post-peak response of the rock along the formed shear plane has been captured for the analysis with particular interest in sample-size dependency. Several important phenomena have been observed from the results of this study: a) the rate of transition from brittleness to ductility in rock is sample-size dependent where the relatively smaller samples showed faster transition toward ductility at any confining pressure; b) the sample size influences the angle of formed shear band and c) the friction coefficient of the formed shear plane is sample-size dependent where the relatively smaller sample exhibits lower friction coefficient compared to larger samples. We interpret our results in terms of a thermodynamics approach in which the frictional properties for finite deformation are viewed as encompassing a multitude of ephemeral slipping surfaces prior to the formation of the through going fracture. The final fracture itself is seen as a result of the self-organisation of a sufficiently large ensemble of micro-slip surfaces and therefore consistent in terms of the theory of thermodynamics. This assumption vindicates the use of classical rock mechanics experiments to constrain failure of pressure sensitive rocks and the future imaging of these micro-slips opens an exciting path for research in rock failure mechanisms.

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

Indian Academy of Sciences (India)

the sample size decreases – a result that could be interpreted as a size effect in the order– disorder vortex matter phase transition. However, local magnetic measurements trace this effect to metastable disordered vortex states, revealing the same order–disorder transition induction in samples of different size. Keywords.

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.

Sample Size in Qualitative Interview Studies: Guided by Information Power.

Science.gov (United States)

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

2015-11-27

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 and during data collection of a qualitative study is discussed. © The Author(s) 2015.

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.

The Power of Low Back Pain Trials: A Systematic Review of Power, Sample Size, and Reporting of Sample Size Calculations Over Time, in Trials Published Between 1980 and 2012.

Science.gov (United States)

Froud, Robert; Rajendran, Dévan; Patel, Shilpa; Bright, Philip; Bjørkli, Tom; Eldridge, Sandra; Buchbinder, Rachelle; Underwood, Martin

2017-06-01

A systematic review of nonspecific low back pain trials published between 1980 and 2012. To explore what proportion of trials have been powered to detect different bands of effect size; whether there is evidence that sample size in low back pain trials has been increasing; what proportion of trial reports include a sample size calculation; and whether likelihood of reporting sample size calculations has increased. Clinical trials should have a sample size sufficient to detect a minimally important difference for a given power and type I error rate. An underpowered trial is one within which probability of type II error is too high. Meta-analyses do not mitigate underpowered trials. Reviewers independently abstracted data on sample size at point of analysis, whether a sample size calculation was reported, and year of publication. Descriptive analyses were used to explore ability to detect effect sizes, and regression analyses to explore the relationship between sample size, or reporting sample size calculations, and time. We included 383 trials. One-third were powered to detect a standardized mean difference of less than 0.5, and 5% were powered to detect less than 0.3. The average sample size was 153 people, which increased only slightly (∼4 people/yr) from 1980 to 2000, and declined slightly (∼4.5 people/yr) from 2005 to 2011 (P pain trials and the reporting of sample size calculations may need to be increased. It may be justifiable to power a trial to detect only large effects in the case of novel interventions. 3.

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.

Decision Support on Small size Passive Samples

Directory of Open Access Journals (Sweden)

Vladimir Popukaylo

2018-05-01

Full Text Available A construction technique of adequate mathematical models for small size passive samples, in conditions when classical probabilistic-statis\\-tical methods do not allow obtaining valid conclusions was developed.

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.

The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.

Science.gov (United States)

Shen, Dan; Shen, Haipeng; Zhu, Hongtu; Marron, J S

2016-10-01

The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirections under the spike models with distinguishable (or indistinguishable) eigenvalues, when the sample size and/or the number of variables (or dimension) tend to infinity. The consistency of the sample eigenvectors relative to their population counterparts is determined by the ratio between the dimension and the product of the sample size with the spike size. When this ratio converges to a nonzero constant, the sample eigenvector converges to a cone, with a certain angle to its corresponding population eigenvector. In the High Dimension, Low Sample Size case, the angle between the sample eigenvector and its population counterpart converges to a limiting distribution. Several generalizations of the multi-spike covariance models are also explored, and additional theoretical results are presented.

The attention-weighted sample-size model of visual short-term memory

DEFF Research Database (Denmark)

Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.

2016-01-01

exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items...

Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

Science.gov (United States)

Bacchetti, Peter; Deeks, Steven G.; McCune, Joseph M.

2011-01-01

Innovative clinical and translational research is often delayed or prevented by reviewers’ expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an N of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation. PMID:21677197

Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions.

Science.gov (United States)

Broberg, Per

2013-07-19

One major concern with adaptive designs, such as the sample size adjustable designs, has been the fear of inflating the type I error rate. In (Stat Med 23:1023-1038, 2004) it is however proven that when observations follow a normal distribution and the interim result show promise, meaning that the conditional power exceeds 50%, type I error rate is protected. This bound and the distributional assumptions may seem to impose undesirable restrictions on the use of these designs. In (Stat Med 30:3267-3284, 2011) the possibility of going below 50% is explored and a region that permits an increased sample size without inflation is defined in terms of the conditional power at the interim. A criterion which is implicit in (Stat Med 30:3267-3284, 2011) is derived by elementary methods and expressed in terms of the test statistic at the interim to simplify practical use. Mathematical and computational details concerning this criterion are exhibited. Under very general conditions the type I error rate is preserved under sample size adjustable schemes that permit a raise. The main result states that for normally distributed observations raising the sample size when the result looks promising, where the definition of promising depends on the amount of knowledge gathered so far, guarantees the protection of the type I error rate. Also, in the many situations where the test statistic approximately follows a normal law, the deviation from the main result remains negligible. This article provides details regarding the Weibull and binomial distributions and indicates how one may approach these distributions within the current setting. There is thus reason to consider such designs more often, since they offer a means of adjusting an important design feature at little or no cost in terms of error rate.

Sample Size and Saturation in PhD Studies Using Qualitative Interviews

Directory of Open Access Journals (Sweden)

Mark Mason

2010-08-01

Full Text Available A number of issues can affect sample size in qualitative research; however, the guiding principle should be the concept of saturation. This has been explored in detail by a number of authors but is still hotly debated, and some say little understood. A sample of PhD studies using qualitative approaches, and qualitative interviews as the method of data collection was taken from theses.com and contents analysed for their sample sizes. Five hundred and sixty studies were identified that fitted the inclusion criteria. Results showed that the mean sample size was 31; however, the distribution was non-random, with a statistically significant proportion of studies, presenting sample sizes that were multiples of ten. These results are discussed in relation to saturation. They suggest a pre-meditated approach that is not wholly congruent with the principles of qualitative research. URN: urn:nbn:de:0114-fqs100387

Sample size allocation in multiregional equivalence studies.

Science.gov (United States)

Liao, Jason J Z; Yu, Ziji; Li, Yulan

2018-06-17

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches. Copyright © 2018 John Wiley & Sons, Ltd.

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...

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

Science.gov (United States)

2015-08-01

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...Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal Aluminum Nitride 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

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.

Sample size reassessment for a two-stage design controlling the false discovery rate.

Science.gov (United States)

Zehetmayer, Sonja; Graf, Alexandra C; Posch, Martin

2015-11-01

Sample size calculations for gene expression microarray and NGS-RNA-Seq experiments are challenging because the overall power depends on unknown quantities as the proportion of true null hypotheses and the distribution of the effect sizes under the alternative. We propose a two-stage design with an adaptive interim analysis where these quantities are estimated from the interim data. The second stage sample size is chosen based on these estimates to achieve a specific overall power. The proposed procedure controls the power in all considered scenarios except for very low first stage sample sizes. The false discovery rate (FDR) is controlled despite of the data dependent choice of sample size. The two-stage design can be a useful tool to determine the sample size of high-dimensional studies if in the planning phase there is high uncertainty regarding the expected effect sizes and variability.

Nomogram for sample size calculation on a straightforward basis for the kappa statistic.

Science.gov (United States)

Hong, Hyunsook; Choi, Yunhee; Hahn, Seokyung; Park, Sue Kyung; Park, Byung-Joo

2014-09-01

Kappa is a widely used measure of agreement. However, it may not be straightforward in some situation such as sample size calculation due to the kappa paradox: high agreement but low kappa. Hence, it seems reasonable in sample size calculation that the level of agreement under a certain marginal prevalence is considered in terms of a simple proportion of agreement rather than a kappa value. Therefore, sample size formulae and nomograms using a simple proportion of agreement rather than a kappa under certain marginal prevalences are proposed. A sample size formula was derived using the kappa statistic under the common correlation model and goodness-of-fit statistic. The nomogram for the sample size formula was developed using SAS 9.3. The sample size formulae using a simple proportion of agreement instead of a kappa statistic and nomograms to eliminate the inconvenience of using a mathematical formula were produced. A nomogram for sample size calculation with a simple proportion of agreement should be useful in the planning stages when the focus of interest is on testing the hypothesis of interobserver agreement involving two raters and nominal outcome measures. Copyright © 2014 Elsevier Inc. All rights reserved.

Sample size optimization in nuclear material control. 1

International Nuclear Information System (INIS)

Gladitz, J.

1982-01-01

Equations have been derived and exemplified which allow the determination of the minimum variables sample size for given false alarm and detection probabilities of nuclear material losses and diversions, respectively. (author)

Impact of shoe size in a sample of elderly individuals

Directory of Open Access Journals (Sweden)

Daniel López-López

Full Text Available Summary Introduction: The use of an improper shoe size is common in older people and is believed to have a detrimental effect on the quality of life related to foot health. The objective is to describe and compare, in a sample of participants, the impact of shoes that fit properly or improperly, as well as analyze the scores related to foot health and health overall. Method: A sample of 64 participants, with a mean age of 75.3±7.9 years, attended an outpatient center where self-report data was recorded, the measurements of the size of the feet and footwear were determined and the scores compared between the group that wears the correct size of shoes and another group of individuals who do not wear the correct size of shoes, using the Spanish version of the Foot Health Status Questionnaire. Results: The group wearing an improper shoe size showed poorer quality of life regarding overall health and specifically foot health. Differences between groups were evaluated using a t-test for independent samples resulting statistically significant (p<0.05 for the dimension of pain, function, footwear, overall foot health, and social function. Conclusion: Inadequate shoe size has a significant negative impact on quality of life related to foot health. The degree of negative impact seems to be associated with age, sex, and body mass index (BMI.

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

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

Optimum sample size to estimate mean parasite abundance in fish parasite surveys

Directory of Open Access Journals (Sweden)

Shvydka S.

2018-03-01

Full Text Available To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI was based on the Bag of Little Bootstraps (BLB. The abundance of two species of monogenean parasites Ligophorus cephali and L. mediterraneus from Mugil cephalus across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i based on CIs width a reasonable precision level for the mean abundance in parasitological surveys of Ligophorus spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the CIs width, and ii the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.

Sample size for post-marketing safety studies based on historical controls.

Science.gov (United States)

Wu, Yu-te; Makuch, Robert W

2010-08-01

As part of a drug's entire life cycle, post-marketing studies are an important part in the identification of rare, serious adverse events. Recently, the US Food and Drug Administration (FDA) has begun to implement new post-marketing safety mandates as a consequence of increased emphasis on safety. The purpose of this research is to provide exact sample size formula for the proposed hybrid design, based on a two-group cohort study with incorporation of historical external data. Exact sample size formula based on the Poisson distribution is developed, because the detection of rare events is our outcome of interest. Performance of exact method is compared to its approximate large-sample theory counterpart. The proposed hybrid design requires a smaller sample size compared to the standard, two-group prospective study design. In addition, the exact method reduces the number of subjects required in the treatment group by up to 30% compared to the approximate method for the study scenarios examined. The proposed hybrid design satisfies the advantages and rationale of the two-group design with smaller sample sizes generally required. 2010 John Wiley & Sons, Ltd.

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

Indian Academy of Sciences (India)

ple size needed to reach a given power (Knapp 1999; Schaid. 1999; Chen and Deng 2001; Brown 2004). In their seminal paper, Risch and Merikangas (1996) showed that for a mul- tiplicative mode of inheritance (MOI) for the susceptibility gene, sample size depends on two parameters: the frequency of the risk allele at the ...

Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization

OpenAIRE

Trevelin, Leonardo Carreira; Novaes, Roberto Leonan Morim; Colas-Rosas, Paul François; Benathar, Thayse Cristhina Melo; Peres, Carlos A.

2017-01-01

The advantages of mist-netting, the main technique used in Neotropical bat community studies to date, include logistical implementation, standardization and sampling representativeness. Nonetheless, study designs still have to deal with issues of detectability related to how different species behave and use the environment. Yet there is considerable sampling heterogeneity across available studies in the literature. Here, we approach the problem of sample size optimization. We evaluated the co...

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)

Sample size in psychological research over the past 30 years.

Science.gov (United States)

Marszalek, Jacob M; Barber, Carolyn; Kohlhart, Julie; Holmes, Cooper B

2011-04-01

The American Psychological Association (APA) Task Force on Statistical Inference was formed in 1996 in response to a growing body of research demonstrating methodological issues that threatened the credibility of psychological research, and made recommendations to address them. One issue was the small, even dramatically inadequate, size of samples used in studies published by leading journals. The present study assessed the progress made since the Task Force's final report in 1999. Sample sizes reported in four leading APA journals in 1955, 1977, 1995, and 2006 were compared using nonparametric statistics, while data from the last two waves were fit to a hierarchical generalized linear growth model for more in-depth analysis. Overall, results indicate that the recommendations for increasing sample sizes have not been integrated in core psychological research, although results slightly vary by field. This and other implications are discussed in the context of current methodological critique and practice.

A flexible method for multi-level sample size determination

International Nuclear Information System (INIS)

Lu, Ming-Shih; Sanborn, J.B.; Teichmann, T.

1997-01-01

This paper gives a flexible method to determine sample sizes for both systematic and random error models (this pertains to sampling problems in nuclear safeguard questions). In addition, the method allows different attribute rejection limits. The new method could assist achieving a higher detection probability and enhance inspection effectiveness

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.

The largest Silurian vertebrate and its palaeoecological implications

Science.gov (United States)

Choo, Brian; Zhu, Min; Zhao, Wenjin; Jia, Liaotao; Zhu, You'an

2014-01-01

An apparent absence of Silurian fishes more than half-a-metre in length has been viewed as evidence that gnathostomes were restricted in size and diversity prior to the Devonian. Here we describe the largest pre-Devonian vertebrate (Megamastax amblyodus gen. et sp. nov.), a predatory marine osteichthyan from the Silurian Kuanti Formation (late Ludlow, ~423 million years ago) of Yunnan, China, with an estimated length of about 1 meter. The unusual dentition of the new form suggests a durophagous diet which, combined with its large size, indicates a considerable degree of trophic specialisation among early osteichthyans. The lack of large Silurian vertebrates has recently been used as constraint in palaeoatmospheric modelling, with purported lower oxygen levels imposing a physiological size limit. Regardless of the exact causal relationship between oxygen availability and evolutionary success, this finding refutes the assumption that pre-Emsian vertebrates were restricted to small body sizes. PMID:24921626

Sample Size Calculation for Controlling False Discovery Proportion

Directory of Open Access Journals (Sweden)

Shulian Shang

2012-01-01

Full Text Available The false discovery proportion (FDP, the proportion of incorrect rejections among all rejections, is a direct measure of abundance of false positive findings in multiple testing. Many methods have been proposed to control FDP, but they are too conservative to be useful for power analysis. Study designs for controlling the mean of FDP, which is false discovery rate, have been commonly used. However, there has been little attempt to design study with direct FDP control to achieve certain level of efficiency. We provide a sample size calculation method using the variance formula of the FDP under weak-dependence assumptions to achieve the desired overall power. The relationship between design parameters and sample size is explored. The adequacy of the procedure is assessed by simulation. We illustrate the method using estimated correlations from a prostate cancer dataset.

A normative inference approach for optimal sample sizes in decisions from experience

Science.gov (United States)

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

Rock sampling. [method for controlling particle size distribution

Science.gov (United States)

Blum, P. (Inventor)

1971-01-01

A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.

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 ...

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.

Test of methods for retrospective activity size distribution determination from filter samples

International Nuclear Information System (INIS)

Meisenberg, Oliver; Tschiersch, Jochen

2015-01-01

Determining the activity size distribution of radioactive aerosol particles requires sophisticated and heavy equipment, which makes measurements at large number of sites difficult and expensive. Therefore three methods for a retrospective determination of size distributions from aerosol filter samples in the laboratory were tested for their applicability. Extraction into a carrier liquid with subsequent nebulisation showed size distributions with a slight but correctable bias towards larger diameters compared with the original size distribution. Yields in the order of magnitude of 1% could be achieved. Sonication-assisted extraction into a carrier liquid caused a coagulation mode to appear in the size distribution. Sonication-assisted extraction into the air did not show acceptable results due to small yields. The method of extraction into a carrier liquid without sonication was applied to aerosol samples from Chernobyl in order to calculate inhalation dose coefficients for 137 Cs based on the individual size distribution. The effective dose coefficient is about half of that calculated with a default reference size distribution. - Highlights: • Activity size distributions can be recovered after aerosol sampling on filters. • Extraction into a carrier liquid and subsequent nebulisation is appropriate. • This facilitates the determination of activity size distributions for individuals. • Size distributions from this method can be used for individual dose coefficients. • Dose coefficients were calculated for the workers at the new Chernobyl shelter

Caution regarding the choice of standard deviations to guide sample size calculations in clinical trials.

Science.gov (United States)

Chen, Henian; Zhang, Nanhua; Lu, Xiaosun; Chen, Sophie

2013-08-01

The method used to determine choice of standard deviation (SD) is inadequately reported in clinical trials. Underestimations of the population SD may result in underpowered clinical trials. This study demonstrates how using the wrong method to determine population SD can lead to inaccurate sample sizes and underpowered studies, and offers recommendations to maximize the likelihood of achieving adequate statistical power. We review the practice of reporting sample size and its effect on the power of trials published in major journals. Simulated clinical trials were used to compare the effects of different methods of determining SD on power and sample size calculations. Prior to 1996, sample size calculations were reported in just 1%-42% of clinical trials. This proportion increased from 38% to 54% after the initial Consolidated Standards of Reporting Trials (CONSORT) was published in 1996, and from 64% to 95% after the revised CONSORT was published in 2001. Nevertheless, underpowered clinical trials are still common. Our simulated data showed that all minimal and 25th-percentile SDs fell below 44 (the population SD), regardless of sample size (from 5 to 50). For sample sizes 5 and 50, the minimum sample SDs underestimated the population SD by 90.7% and 29.3%, respectively. If only one sample was available, there was less than 50% chance that the actual power equaled or exceeded the planned power of 80% for detecting a median effect size (Cohen's d = 0.5) when using the sample SD to calculate the sample size. The proportions of studies with actual power of at least 80% were about 95%, 90%, 85%, and 80% when we used the larger SD, 80% upper confidence limit (UCL) of SD, 70% UCL of SD, and 60% UCL of SD to calculate the sample size, respectively. When more than one sample was available, the weighted average SD resulted in about 50% of trials being underpowered; the proportion of trials with power of 80% increased from 90% to 100% when the 75th percentile and the

The largest deep-ocean silicic volcanic eruption of the past century.

Science.gov (United States)

Carey, Rebecca; Soule, S Adam; Manga, Michael; White, James; McPhie, Jocelyn; Wysoczanski, Richard; Jutzeler, Martin; Tani, Kenichiro; Yoerger, Dana; Fornari, Daniel; Caratori-Tontini, Fabio; Houghton, Bruce; Mitchell, Samuel; Ikegami, Fumihiko; Conway, Chris; Murch, Arran; Fauria, Kristen; Jones, Meghan; Cahalan, Ryan; McKenzie, Warren

2018-01-01

The 2012 submarine eruption of Havre volcano in the Kermadec arc, New Zealand, is the largest deep-ocean eruption in history and one of very few recorded submarine eruptions involving rhyolite magma. It was recognized from a gigantic 400-km 2 pumice raft seen in satellite imagery, but the complexity of this event was concealed beneath the sea surface. Mapping, observations, and sampling by submersibles have provided an exceptionally high fidelity record of the seafloor products, which included lava sourced from 14 vents at water depths of 900 to 1220 m, and fragmental deposits including giant pumice clasts up to 9 m in diameter. Most (>75%) of the total erupted volume was partitioned into the pumice raft and transported far from the volcano. The geological record on submarine volcanic edifices in volcanic arcs does not faithfully archive eruption size or magma production.

Sample sizes and model comparison metrics for species distribution models

Science.gov (United States)

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

Influence of Sample Size on Automatic Positional Accuracy Assessment Methods for Urban Areas

Directory of Open Access Journals (Sweden)

Francisco J. Ariza-López

2018-05-01

Full Text Available In recent years, new approaches aimed to increase the automation level of positional accuracy assessment processes for spatial data have been developed. However, in such cases, an aspect as significant as sample size has not yet been addressed. In this paper, we study the influence of sample size when estimating the planimetric positional accuracy of urban databases by means of an automatic assessment using polygon-based methodology. Our study is based on a simulation process, which extracts pairs of homologous polygons from the assessed and reference data sources and applies two buffer-based methods. The parameter used for determining the different sizes (which range from 5 km up to 100 km has been the length of the polygons’ perimeter, and for each sample size 1000 simulations were run. After completing the simulation process, the comparisons between the estimated distribution functions for each sample and population distribution function were carried out by means of the Kolmogorov–Smirnov test. Results show a significant reduction in the variability of estimations when sample size increased from 5 km to 100 km.

Sample size determination for disease prevalence studies with partially validated data.

Science.gov (United States)

Qiu, Shi-Fang; Poon, Wai-Yin; Tang, Man-Lai

2016-02-01

Disease prevalence is an important topic in medical research, and its study is based on data that are obtained by classifying subjects according to whether a disease has been contracted. Classification can be conducted with high-cost gold standard tests or low-cost screening tests, but the latter are subject to the misclassification of subjects. As a compromise between the two, many research studies use partially validated datasets in which all data points are classified by fallible tests, and some of the data points are validated in the sense that they are also classified by the completely accurate gold-standard test. In this article, we investigate the determination of sample sizes for disease prevalence studies with partially validated data. We use two approaches. The first is to find sample sizes that can achieve a pre-specified power of a statistical test at a chosen significance level, and the second is to find sample sizes that can control the width of a confidence interval with a pre-specified confidence level. Empirical studies have been conducted to demonstrate the performance of various testing procedures with the proposed sample sizes. The applicability of the proposed methods are illustrated by a real-data example. © The Author(s) 2012.

Optimal Sample Size for Probability of Detection Curves

International Nuclear Information System (INIS)

Annis, Charles; Gandossi, Luca; Martin, Oliver

2012-01-01

The use of Probability of Detection (POD) curves to quantify NDT reliability is common in the aeronautical industry, but relatively less so in the nuclear industry. The European Network for Inspection Qualification's (ENIQ) Inspection Qualification Methodology is based on the concept of Technical Justification, a document assembling all the evidence to assure that the NDT system in focus is indeed capable of finding the flaws for which it was designed. This methodology has become widely used in many countries, but the assurance it provides is usually of qualitative nature. The need to quantify the output of inspection qualification has become more important, especially as structural reliability modelling and quantitative risk-informed in-service inspection methodologies become more widely used. To credit the inspections in structural reliability evaluations, a measure of the NDT reliability is necessary. A POD curve provides such metric. In 2010 ENIQ developed a technical report on POD curves, reviewing the statistical models used to quantify inspection reliability. Further work was subsequently carried out to investigate the issue of optimal sample size for deriving a POD curve, so that adequate guidance could be given to the practitioners of inspection reliability. Manufacturing of test pieces with cracks that are representative of real defects found in nuclear power plants (NPP) can be very expensive. Thus there is a tendency to reduce sample sizes and in turn reduce the conservatism associated with the POD curve derived. Not much guidance on the correct sample size can be found in the published literature, where often qualitative statements are given with no further justification. The aim of this paper is to summarise the findings of such work. (author)

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…

[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.

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

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

2008-08-28

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. 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. 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.

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 ...

Intrapopulational body size variation and cranial capacity variation in Middle Pleistocene humans: the Sima de los Huesos sample (Sierra de Atapuerca, Spain).

Science.gov (United States)

Lorenzo, C; Carretero, J M; Arsuaga, J L; Gracia, A; Martínez, I

1998-05-01

A sexual dimorphism more marked than in living humans has been claimed for European Middle Pleistocene humans, Neandertals and prehistoric modern humans. In this paper, body size and cranial capacity variation are studied in the Sima de los Huesos Middle Pleistocene sample. This is the largest sample of non-modern humans found to date from one single site, and with all skeletal elements represented. Since the techniques available to estimate the degree of sexual dimorphism in small palaeontological samples are all unsatisfactory, we have used the bootstraping method to asses the magnitude of the variation in the Sima de los Huesos sample compared to modern human intrapopulational variation. We analyze size variation without attempting to sex the specimens a priori. Anatomical regions investigated are scapular glenoid fossa; acetabulum; humeral proximal and distal epiphyses; ulnar proximal epiphysis; radial neck; proximal femur; humeral, femoral, ulnar and tibial shaft; lumbosacral joint; patella; calcaneum; and talar trochlea. In the Sima de los Huesos sample only the humeral midshaft perimeter shows an unusual high variation (only when it is expressed by the maximum ratio, not by the coefficient of variation). In spite of that the cranial capacity range at Sima de los Huesos almost spans the rest of the European and African Middle Pleistocene range. The maximum ratio is in the central part of the distribution of modern human samples. Thus, the hypothesis of a greater sexual dimorphism in Middle Pleistocene populations than in modern populations is not supported by either cranial or postcranial evidence from Sima de los Huesos.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

Science.gov (United States)

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

Science.gov (United States)

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings.

Science.gov (United States)

Lorca-Puls, Diego L; Gajardo-Vidal, Andrea; White, Jitrachote; Seghier, Mohamed L; Leff, Alexander P; Green, David W; Crinion, Jenny T; Ludersdorfer, Philipp; Hope, Thomas M H; Bowman, Howard; Price, Cathy J

2018-07-01

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Does increasing the size of bi-weekly samples of records influence results when using the Global Trigger Tool? An observational study of retrospective record reviews of two different sample sizes.

Science.gov (United States)

Mevik, Kjersti; Griffin, Frances A; Hansen, Tonje E; Deilkås, Ellen T; Vonen, Barthold

2016-04-25

To investigate the impact of increasing sample of records reviewed bi-weekly with the Global Trigger Tool method to identify adverse events in hospitalised patients. Retrospective observational study. A Norwegian 524-bed general hospital trust. 1920 medical records selected from 1 January to 31 December 2010. Rate, type and severity of adverse events identified in two different samples sizes of records selected as 10 and 70 records, bi-weekly. In the large sample, 1.45 (95% CI 1.07 to 1.97) times more adverse events per 1000 patient days (39.3 adverse events/1000 patient days) were identified than in the small sample (27.2 adverse events/1000 patient days). Hospital-acquired infections were the most common category of adverse events in both the samples, and the distributions of the other categories of adverse events did not differ significantly between the samples. The distribution of severity level of adverse events did not differ between the samples. The findings suggest that while the distribution of categories and severity are not dependent on the sample size, the rate of adverse events is. Further studies are needed to conclude if the optimal sample size may need to be adjusted based on the hospital size in order to detect a more accurate rate of adverse events. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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.

Sample size calculation to externally validate scoring systems based on logistic regression models.

Directory of Open Access Journals (Sweden)

Antonio Palazón-Bru

Full Text Available A sample size containing at least 100 events and 100 non-events has been suggested to validate a predictive model, regardless of the model being validated and that certain factors can influence calibration of the predictive model (discrimination, parameterization and incidence. Scoring systems based on binary logistic regression models are a specific type of predictive model.The aim of this study was to develop an algorithm to determine the sample size for validating a scoring system based on a binary logistic regression model and to apply it to a case study.The algorithm was based on bootstrap samples in which the area under the ROC curve, the observed event probabilities through smooth curves, and a measure to determine the lack of calibration (estimated calibration index were calculated. To illustrate its use for interested researchers, the algorithm was applied to a scoring system, based on a binary logistic regression model, to determine mortality in intensive care units.In the case study provided, the algorithm obtained a sample size with 69 events, which is lower than the value suggested in the literature.An algorithm is provided for finding the appropriate sample size to validate scoring systems based on binary logistic regression models. This could be applied to determine the sample size in other similar cases.

Size selective isocyanate aerosols personal air sampling using porous plastic foams

International Nuclear Information System (INIS)

Cong Khanh Huynh; Trinh Vu Duc

2009-01-01

As part of a European project (SMT4-CT96-2137), various European institutions specialized in occupational hygiene (BGIA, HSL, IOM, INRS, IST, Ambiente e Lavoro) have established a program of scientific collaboration to develop one or more prototypes of European personal samplers for the collection of simultaneous three dust fractions: inhalable, thoracic and respirable. These samplers based on existing sampling heads (IOM, GSP and cassettes) use Polyurethane Plastic Foam (PUF) according to their porosity to support sampling and separator size of the particles. In this study, the authors present an original application of size selective personal air sampling using chemical impregnated PUF to perform isocyanate aerosols capturing and derivatizing in industrial spray-painting shops.

An integrated approach for multi-level sample size determination

International Nuclear Information System (INIS)

Lu, M.S.; Teichmann, T.; Sanborn, J.B.

1997-01-01

Inspection procedures involving the sampling of items in a population often require steps of increasingly sensitive measurements, with correspondingly smaller sample sizes; these are referred to as multilevel sampling schemes. In the case of nuclear safeguards inspections verifying that there has been no diversion of Special Nuclear Material (SNM), these procedures have been examined often and increasingly complex algorithms have been developed to implement them. The aim in this paper is to provide an integrated approach, and, in so doing, to describe a systematic, consistent method that proceeds logically from level to level with increasing accuracy. The authors emphasize that the methods discussed are generally consistent with those presented in the references mentioned, and yield comparable results when the error models are the same. However, because of its systematic, integrated approach the proposed method elucidates the conceptual understanding of what goes on, and, in many cases, simplifies the calculations. In nuclear safeguards inspections, an important aspect of verifying nuclear items to detect any possible diversion of nuclear fissile materials is the sampling of such items at various levels of sensitivity. The first step usually is sampling by ''attributes'' involving measurements of relatively low accuracy, followed by further levels of sampling involving greater accuracy. This process is discussed in some detail in the references given; also, the nomenclature is described. Here, the authors outline a coordinated step-by-step procedure for achieving such multilevel sampling, and they develop the relationships between the accuracy of measurement and the sample size required at each stage, i.e., at the various levels. The logic of the underlying procedures is carefully elucidated; the calculations involved and their implications, are clearly described, and the process is put in a form that allows systematic generalization

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications.

Directory of Open Access Journals (Sweden)

Elias Chaibub Neto

Full Text Available In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.

Computing Confidence Bounds for Power and Sample Size of the General Linear Univariate Model

OpenAIRE

Taylor, Douglas J.; Muller, Keith E.

1995-01-01

The power of a test, the probability of rejecting the null hypothesis in favor of an alternative, may be computed using estimates of one or more distributional parameters. Statisticians frequently fix mean values and calculate power or sample size using a variance estimate from an existing study. Hence computed power becomes a random variable for a fixed sample size. Likewise, the sample size necessary to achieve a fixed power varies randomly. Standard statistical practice requires reporting ...

Estimation of sample size and testing power (Part 3).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2011-12-01

This article introduces the definition and sample size estimation of three special tests (namely, non-inferiority test, equivalence test and superiority test) for qualitative data with the design of one factor with two levels having a binary response variable. Non-inferiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is not clinically inferior to that of the positive control drug. Equivalence test refers to the research design of which the objective is to verify that the experimental drug and the control drug have clinically equivalent efficacy. Superiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is clinically superior to that of the control drug. By specific examples, this article introduces formulas of sample size estimation for the three special tests, and their SAS realization in detail.

Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

[Formal sample size calculation and its limited validity in animal studies of medical basic research].

Science.gov (United States)

Mayer, B; Muche, R

2013-01-01

Animal studies are highly relevant for basic medical research, although their usage is discussed controversially in public. Thus, an optimal sample size for these projects should be aimed at from a biometrical point of view. Statistical sample size calculation is usually the appropriate methodology in planning medical research projects. However, required information is often not valid or only available during the course of an animal experiment. This article critically discusses the validity of formal sample size calculation for animal studies. Within the discussion, some requirements are formulated to fundamentally regulate the process of sample size determination for animal experiments.

Discovery of the Largest Orbweaving Spider Species: The Evolution of Gigantism in Nephila

OpenAIRE

Kuntner, Matja?; Coddington, Jonathan A.

2009-01-01

Background More than 41,000 spider species are known with about 400?500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19th century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD) and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa...

Generating Random Samples of a Given Size Using Social Security Numbers.

Science.gov (United States)

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

The purposes of this article are (1) to present a method by which social security numbers may be used to draw cluster samples of a predetermined size and (2) to describe procedures used to validate this method of drawing random samples. (JOW)

THE CHALLENGE OF THE LARGEST STRUCTURES IN THE UNIVERSE TO COSMOLOGY

International Nuclear Information System (INIS)

Park, Changbom; Choi, Yun-Young; Kim, Sungsoo S.; Kim, Kap-Sung; Kim, Juhan; Gott III, J. Richard

2012-01-01

Large galaxy redshift surveys have long been used to constrain cosmological models and structure formation scenarios. In particular, the largest structures discovered observationally are thought to carry critical information on the amplitude of large-scale density fluctuations or homogeneity of the universe, and have often challenged the standard cosmological framework. The Sloan Great Wall (SGW) recently found in the Sloan Digital Sky Survey (SDSS) region casts doubt on the concordance cosmological model with a cosmological constant (i.e., the flat ΛCDM model). Here we show that the existence of the SGW is perfectly consistent with the ΛCDM model, a result that only our very large cosmological N-body simulation (the Horizon Run 2, HR2) could supply. In addition, we report on the discovery of a void complex in the SDSS much larger than the SGW, and show that such size of the largest void is also predicted in the ΛCDM paradigm. Our results demonstrate that an initially homogeneous isotropic universe with primordial Gaussian random phase density fluctuations growing in accordance with the general relativity can explain the richness and size of the observed large-scale structures in the SDSS. Using the HR2 simulation we predict that a future galaxy redshift survey about four times deeper or with 3 mag fainter limit than the SDSS should reveal a largest structure of bright galaxies about twice as big as the SGW.

On sample size and different interpretations of snow stability datasets

Science.gov (United States)

Schirmer, M.; Mitterer, C.; Schweizer, J.

2009-04-01

Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar

Support vector regression to predict porosity and permeability: Effect of sample size

Science.gov (United States)

Al-Anazi, A. F.; Gates, I. D.

2012-02-01

Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function

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.

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.

Differentiating gold nanorod samples using particle size and shape distributions from transmission electron microscope images

Science.gov (United States)

Grulke, Eric A.; Wu, Xiaochun; Ji, Yinglu; Buhr, Egbert; Yamamoto, Kazuhiro; Song, Nam Woong; Stefaniak, Aleksandr B.; Schwegler-Berry, Diane; Burchett, Woodrow W.; Lambert, Joshua; Stromberg, Arnold J.

2018-04-01

Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.

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.

Development of sample size allocation program using hypergeometric distribution

International Nuclear Information System (INIS)

Kim, Hyun Tae; Kwack, Eun Ho; Park, Wan Soo; Min, Kyung Soo; Park, Chan Sik

1996-01-01

The objective of this research is the development of sample allocation program using hypergeometric distribution with objected-oriented method. When IAEA(International Atomic Energy Agency) performs inspection, it simply applies a standard binomial distribution which describes sampling with replacement instead of a hypergeometric distribution which describes sampling without replacement in sample allocation to up to three verification methods. The objective of the IAEA inspection is the timely detection of diversion of significant quantities of nuclear material, therefore game theory is applied to its sampling plan. It is necessary to use hypergeometric distribution directly or approximate distribution to secure statistical accuracy. Improved binomial approximation developed by Mr. J. L. Jaech and correctly applied binomial approximation are more closer to hypergeometric distribution in sample size calculation than the simply applied binomial approximation of the IAEA. Object-oriented programs of 1. sample approximate-allocation with correctly applied standard binomial approximation, 2. sample approximate-allocation with improved binomial approximation, and 3. sample approximate-allocation with hypergeometric distribution were developed with Visual C ++ and corresponding programs were developed with EXCEL(using Visual Basic for Application). 8 tabs., 15 refs. (Author)

Stable Carbon Fractionation In Size Segregated Aerosol Particles Produced By Controlled Biomass Burning

Science.gov (United States)

Masalaite, Agne; Garbaras, Andrius; Garbariene, Inga; Ceburnis, Darius; Martuzevicius, Dainius; Puida, Egidijus; Kvietkus, Kestutis; Remeikis, Vidmantas

2014-05-01

Biomass burning is the largest source of primary fine fraction carbonaceous particles and the second largest source of trace gases in the global atmosphere with a strong effect not only on the regional scale but also in areas distant from the source . Many studies have often assumed no significant carbon isotope fractionation occurring between black carbon and the original vegetation during combustion. However, other studies suggested that stable carbon isotope ratios of char or BC may not reliably reflect carbon isotopic signatures of the source vegetation. Overall, the apparently conflicting results throughout the literature regarding the observed fractionation suggest that combustion conditions may be responsible for the observed effects. The purpose of the present study was to gather more quantitative information on carbonaceous aerosols produced in controlled biomass burning, thereby having a potential impact on interpreting ambient atmospheric observations. Seven different biomass fuel types were burned under controlled conditions to determine the effect of the biomass type on the emitted particulate matter mass and stable carbon isotope composition of bulk and size segregated particles. Size segregated aerosol particles were collected using the total suspended particle (TSP) sampler and a micro-orifice uniform deposit impactor (MOUDI). The results demonstrated that particle emissions were dominated by the submicron particles in all biomass types. However, significant differences in emissions of submicron particles and their dominant sizes were found between different biomass fuels. The largest negative fractionation was obtained for the wood pellet fuel type while the largest positive isotopic fractionation was observed during the buckwheat shells combustion. The carbon isotope composition of MOUDI samples compared very well with isotope composition of TSP samples indicating consistency of the results. The measurements of the stable carbon isotope ratio in

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

2018-03-01

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 H 0 : ES = 0 versus alternative hypotheses H 1 : 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.

Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

Directory of Open Access Journals (Sweden)

Kim Seon-Young

2009-05-01

Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.

Volatile and non-volatile elements in grain-size separated samples of Apollo 17 lunar soils

International Nuclear Information System (INIS)

Giovanoli, R.; Gunten, H.R. von; Kraehenbuehl, U.; Meyer, G.; Wegmueller, F.; Gruetter, A.; Wyttenbach, A.

1977-01-01

Three samples of Apollo 17 lunar soils (75081, 72501 and 72461) were separated into 9 grain-size fractions between 540 and 1 μm mean diameter. In order to detect mineral fractionations caused during the separation procedures major elements were determined by instrumental neutron activation analyses performed on small aliquots of the separated samples. Twenty elements were measured in each size fraction using instrumental and radiochemical neutron activation techniques. The concentration of the main elements in sample 75081 does not change with the grain-size. Exceptions are Fe and Ti which decrease slightly and Al which increases slightly with the decrease in the grain-size. These changes in the composition in main elements suggest a decrease in Ilmenite and an increase in Anorthite with decreasing grain-size. However, it can be concluded that the mineral composition of the fractions changes less than a factor of 2. Samples 72501 and 72461 are not yet analyzed for the main elements. (Auth.)

A modified approach to estimating sample size for simple logistic regression with one continuous covariate.

Science.gov (United States)

Novikov, I; Fund, N; Freedman, L S

2010-01-15

Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.

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.

Sample size methods for estimating HIV incidence from cross-sectional surveys.

Science.gov (United States)

Konikoff, Jacob; Brookmeyer, Ron

2015-12-01

Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this article, we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this article at the Biometrics website on Wiley Online Library. © 2015, The International Biometric Society.

Structural Properties as Proxy for Semantic Relevance in RDF Graph Sampling

NARCIS (Netherlands)

Rietveld, L.; Hoekstra, R.; Schlobach, S.; Guéret, C.; Mika, P.; Tudorache, T.; Bernstein, A.; Welty, C.; Knoblock, C.; Vrandečić, D.; Groth, P.; Noy, N.; Janowicz, K.; Goble, C.

2014-01-01

The Linked Data cloud has grown to become the largest knowledge base ever constructed. Its size is now turning into a major bottleneck for many applications. In order to facilitate access to this structured information, this paper proposes an automatic sampling method targeted at maximizing answer

Sample size calculations for cluster randomised crossover trials in Australian and New Zealand intensive care research.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Pilcher, David; Bellomo, Rinaldo; Forbes, Andrew B

2018-06-01

The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. We show sample size calculations for a two-intervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design). The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design. The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.

Evaluation of pump pulsation in respirable size-selective sampling: part II. Changes in sampling efficiency.

Science.gov (United States)

Lee, Eun Gyung; Lee, Taekhee; Kim, Seung Won; Lee, Larry; Flemmer, Michael M; Harper, Martin

2014-01-01

This second, and concluding, part of this study evaluated changes in sampling efficiency of respirable size-selective samplers due to air pulsations generated by the selected personal sampling pumps characterized in Part I (Lee E, Lee L, Möhlmann C et al. Evaluation of pump pulsation in respirable size-selective sampling: Part I. Pulsation measurements. Ann Occup Hyg 2013). Nine particle sizes of monodisperse ammonium fluorescein (from 1 to 9 μm mass median aerodynamic diameter) were generated individually by a vibrating orifice aerosol generator from dilute solutions of fluorescein in aqueous ammonia and then injected into an environmental chamber. To collect these particles, 10-mm nylon cyclones, also known as Dorr-Oliver (DO) cyclones, were used with five medium volumetric flow rate pumps. Those were the Apex IS, HFS513, GilAir5, Elite5, and Basic5 pumps, which were found in Part I to generate pulsations of 5% (the lowest), 25%, 30%, 56%, and 70% (the highest), respectively. GK2.69 cyclones were used with the Legacy [pump pulsation (PP) = 15%] and Elite12 (PP = 41%) pumps for collection at high flows. The DO cyclone was also used to evaluate changes in sampling efficiency due to pulse shape. The HFS513 pump, which generates a more complex pulse shape, was compared to a single sine wave fluctuation generated by a piston. The luminescent intensity of the fluorescein extracted from each sample was measured with a luminescence spectrometer. Sampling efficiencies were obtained by dividing the intensity of the fluorescein extracted from the filter placed in a cyclone with the intensity obtained from the filter used with a sharp-edged reference sampler. Then, sampling efficiency curves were generated using a sigmoid function with three parameters and each sampling efficiency curve was compared to that of the reference cyclone by constructing bias maps. In general, no change in sampling efficiency (bias under ±10%) was observed until pulsations exceeded 25% for the

Sample-size effects in fast-neutron gamma-ray production measurements: solid-cylinder samples

International Nuclear Information System (INIS)

Smith, D.L.

1975-09-01

The effects of geometry, absorption and multiple scattering in (n,Xγ) reaction measurements with solid-cylinder samples are investigated. Both analytical and Monte-Carlo methods are employed in the analysis. Geometric effects are shown to be relatively insignificant except in definition of the scattering angles. However, absorption and multiple-scattering effects are quite important; accurate microscopic differential cross sections can be extracted from experimental data only after a careful determination of corrections for these processes. The results of measurements performed using several natural iron samples (covering a wide range of sizes) confirm validity of the correction procedures described herein. It is concluded that these procedures are reliable whenever sufficiently accurate neutron and photon cross section and angular distribution information is available for the analysis. (13 figures, 5 tables) (auth)

Subclinical delusional ideation and appreciation of sample size and heterogeneity in statistical judgment.

Science.gov (United States)

Galbraith, Niall D; Manktelow, Ken I; Morris, Neil G

2010-11-01

Previous studies demonstrate that people high in delusional ideation exhibit a data-gathering bias on inductive reasoning tasks. The current study set out to investigate the factors that may underpin such a bias by examining healthy individuals, classified as either high or low scorers on the Peters et al. Delusions Inventory (PDI). More specifically, whether high PDI scorers have a relatively poor appreciation of sample size and heterogeneity when making statistical judgments. In Expt 1, high PDI scorers made higher probability estimates when generalizing from a sample of 1 with regard to the heterogeneous human property of obesity. In Expt 2, this effect was replicated and was also observed in relation to the heterogeneous property of aggression. The findings suggest that delusion-prone individuals are less appreciative of the importance of sample size when making statistical judgments about heterogeneous properties; this may underpin the data gathering bias observed in previous studies. There was some support for the hypothesis that threatening material would exacerbate high PDI scorers' indifference to sample size.

Page sample size in web accessibility testing: how many pages is enough?

NARCIS (Netherlands)

Velleman, Eric Martin; van der Geest, Thea

2013-01-01

Various countries and organizations use a different sampling approach and sample size of web pages in accessibility conformance tests. We are conducting a systematic analysis to determine how many pages is enough for testing whether a website is compliant with standard accessibility guidelines. This

Sensitivity of Mantel Haenszel Model and Rasch Model as Viewed From Sample Size

OpenAIRE

ALWI, IDRUS

2011-01-01

The aims of this research is to study the sensitivity comparison of Mantel Haenszel and Rasch Model for detection differential item functioning, observed from the sample size. These two differential item functioning (DIF) methods were compared using simulate binary item respon data sets of varying sample size,  200 and 400 examinees were used in the analyses, a detection method of differential item functioning (DIF) based on gender difference. These test conditions were replication 4 tim...

Experimental-calculation technique for Ksub(IC) determination using the samples of decreased dimensions

International Nuclear Information System (INIS)

Vinokurov, V.A.; Dymshits, A.V.; Pirusskij, M.V.; Ovsyannikov, B.M.; Kononov, V.V.

1981-01-01

A possibility to decrease the size of samples, which is necessary for the reliable determination of fractUre toughness Ksub(1c), is established. The dependences of crack-resistance caracteristics on the sample dimensions are determined experimentally. The static bending tests are made using the 1251 model of ''Instron'' installation with a specially designed device. The samples of the 20KhNMF steel have been tested. It is shown that the Ksub(1c) value, determined for the samples with the largest netto cross section (50x100 rm), is considerably lower than Ksub(1c) values, determined for the samples with the decreased sizes. it is shown that the developed experimental-calculated method of Ksub(1c) determination can be practically used for the samples of the decreased sizes with the introduction of the corresponding amendment coefficient [ru

Longevity in Calumma parsonii, the World's largest chameleon.

Science.gov (United States)

Tessa, Giulia; Glaw, Frank; Andreone, Franco

2017-03-01

Large body size of ectothermic species can be correlated with high life expectancy. We assessed the longevity of the World's largest chameleon, the Parson's chameleon Calumma parsonii from Madagascar by using skeletochronology of phalanges taken from preserved specimens held in European natural history museums. Due to the high bone resorption we can provide only the minimum age of each specimen. The highest minimum age detected was nine years for a male and eight years for a female, confirming that this species is considerably long living among chameleons. Our data also show a strong correlation between snout-vent length and estimated age. Copyright © 2017 Elsevier Inc. All rights reserved.

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 ...

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.

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

African Journals Online (AJOL)

Reports the results of a study conducted to determine an appropriate sample size for a small-quadrat method of botanical survey for application in the Mixed Bushveld of South Africa. Species density and grass density were measured using a small-quadrat method in eight plant communities in the Nylsvley Nature Reserve.

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…

Precision of quantization of the hall conductivity in a finite-size sample: Power law

International Nuclear Information System (INIS)

Greshnov, A. A.; Kolesnikova, E. N.; Zegrya, G. G.

2006-01-01

A microscopic calculation of the conductivity in the integer quantum Hall effect (IQHE) mode is carried out. The precision of quantization is analyzed for finite-size samples. The precision of quantization shows a power-law dependence on the sample size. A new scaling parameter describing this dependence is introduced. It is also demonstrated that the precision of quantization linearly depends on the ratio between the amplitude of the disorder potential and the cyclotron energy. The data obtained are compared with the results of magnetotransport measurements in mesoscopic samples

Sample size for monitoring sirex populations and their natural enemies

Directory of Open Access Journals (Sweden)

Susete do Rocio Chiarello Penteado

2016-09-01

Full Text Available The woodwasp Sirex noctilio Fabricius (Hymenoptera: Siricidae was introduced in Brazil in 1988 and became the main pest in pine plantations. It has spread to about 1.000.000 ha, at different population levels, in the states of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo and Minas Gerais. Control is done mainly by using a nematode, Deladenus siricidicola Bedding (Nematoda: Neothylenchidae. The evaluation of the efficiency of natural enemies has been difficult because there are no appropriate sampling systems. This study tested a hierarchical sampling system to define the sample size to monitor the S. noctilio population and the efficiency of their natural enemies, which was found to be perfectly adequate.

Collection of size fractionated particulate matter sample for neutron activation analysis in Japan

International Nuclear Information System (INIS)

Otoshi, Tsunehiko; Nakamatsu, Hiroaki; Oura, Yasuji; Ebihara, Mitsuru

2004-01-01

According to the decision of the 2001 Workshop on Utilization of Research Reactor (Neutron Activation Analysis (NAA) Section), size fractionated particulate matter collection for NAA was started from 2002 at two sites in Japan. The two monitoring sites, ''Tokyo'' and ''Sakata'', were classified into ''urban'' and ''rural''. In each site, two size fractions, namely PM 2-10 '' and PM 2 '' particles (aerodynamic particle size between 2 to 10 micrometer and less than 2 micrometer, respectively) were collected every month on polycarbonate membrane filters. Average concentrations of PM 10 (sum of PM 2-10 and PM 2 samples) during the common sampling period of August to November 2002 in each site were 0.031mg/m 3 in Tokyo, and 0.022mg/m 3 in Sakata. (author)

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

A two-stage Bayesian design with sample size reestimation and subgroup analysis for phase II binary response trials.

Science.gov (United States)

Zhong, Wei; Koopmeiners, Joseph S; Carlin, Bradley P

2013-11-01

Frequentist sample size determination for binary outcome data in a two-arm clinical trial requires initial guesses of the event probabilities for the two treatments. Misspecification of these event rates may lead to a poor estimate of the necessary sample size. In contrast, the Bayesian approach that considers the treatment effect to be random variable having some distribution may offer a better, more flexible approach. The Bayesian sample size proposed by (Whitehead et al., 2008) for exploratory studies on efficacy justifies the acceptable minimum sample size by a "conclusiveness" condition. In this work, we introduce a new two-stage Bayesian design with sample size reestimation at the interim stage. Our design inherits the properties of good interpretation and easy implementation from Whitehead et al. (2008), generalizes their method to a two-sample setting, and uses a fully Bayesian predictive approach to reduce an overly large initial sample size when necessary. Moreover, our design can be extended to allow patient level covariates via logistic regression, now adjusting sample size within each subgroup based on interim analyses. We illustrate the benefits of our approach with a design in non-Hodgkin lymphoma with a simple binary covariate (patient gender), offering an initial step toward within-trial personalized medicine. Copyright © 2013 Elsevier Inc. All rights reserved.

Effects of sample size and sampling frequency on studies of brown bear home ranges and habitat use

Science.gov (United States)

Arthur, Steve M.; Schwartz, Charles C.

1999-01-01

We equipped 9 brown bears (Ursus arctos) on the Kenai Peninsula, Alaska, with collars containing both conventional very-high-frequency (VHF) transmitters and global positioning system (GPS) receivers programmed to determine an animal's position at 5.75-hr intervals. We calculated minimum convex polygon (MCP) and fixed and adaptive kernel home ranges for randomly-selected subsets of the GPS data to examine the effects of sample size on accuracy and precision of home range estimates. We also compared results obtained by weekly aerial radiotracking versus more frequent GPS locations to test for biases in conventional radiotracking data. Home ranges based on the MCP were 20-606 km2 (x = 201) for aerial radiotracking data (n = 12-16 locations/bear) and 116-1,505 km2 (x = 522) for the complete GPS data sets (n = 245-466 locations/bear). Fixed kernel home ranges were 34-955 km2 (x = 224) for radiotracking data and 16-130 km2 (x = 60) for the GPS data. Differences between means for radiotracking and GPS data were due primarily to the larger samples provided by the GPS data. Means did not differ between radiotracking data and equivalent-sized subsets of GPS data (P > 0.10). For the MCP, home range area increased and variability decreased asymptotically with number of locations. For the kernel models, both area and variability decreased with increasing sample size. Simulations suggested that the MCP and kernel models required >60 and >80 locations, respectively, for estimates to be both accurate (change in area bears. Our results suggest that the usefulness of conventional radiotracking data may be limited by potential biases and variability due to small samples. Investigators that use home range estimates in statistical tests should consider the effects of variability of those estimates. Use of GPS-equipped collars can facilitate obtaining larger samples of unbiased data and improve accuracy and precision of home range estimates.

Modified FlowCAM procedure for quantifying size distribution of zooplankton with sample recycling capacity.

Directory of Open Access Journals (Sweden)

Esther Wong

Full Text Available We have developed a modified FlowCAM procedure for efficiently quantifying the size distribution of zooplankton. The modified method offers the following new features: 1 prevents animals from settling and clogging with constant bubbling in the sample container; 2 prevents damage to sample animals and facilitates recycling by replacing the built-in peristaltic pump with an external syringe pump, in order to generate negative pressure, creates a steady flow by drawing air from the receiving conical flask (i.e. vacuum pump, and transfers plankton from the sample container toward the main flowcell of the imaging system and finally into the receiving flask; 3 aligns samples in advance of imaging and prevents clogging with an additional flowcell placed ahead of the main flowcell. These modifications were designed to overcome the difficulties applying the standard FlowCAM procedure to studies where the number of individuals per sample is small, and since the FlowCAM can only image a subset of a sample. Our effective recycling procedure allows users to pass the same sample through the FlowCAM many times (i.e. bootstrapping the sample in order to generate a good size distribution. Although more advanced FlowCAM models are equipped with syringe pump and Field of View (FOV flowcells which can image all particles passing through the flow field; we note that these advanced setups are very expensive, offer limited syringe and flowcell sizes, and do not guarantee recycling. In contrast, our modifications are inexpensive and flexible. Finally, we compared the biovolumes estimated by automated FlowCAM image analysis versus conventional manual measurements, and found that the size of an individual zooplankter can be estimated by the FlowCAM image system after ground truthing.

Estimation of sample size and testing power (part 6).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-03-01

The design of one factor with k levels (k ≥ 3) refers to the research that only involves one experimental factor with k levels (k ≥ 3), and there is no arrangement for other important non-experimental factors. This paper introduces the estimation of sample size and testing power for quantitative data and qualitative data having a binary response variable with the design of one factor with k levels (k ≥ 3).

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes.

Science.gov (United States)

Vegué, Marina; Perin, Rodrigo; Roxin, Alex

2017-08-30

The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering several distinct classes of network topology, including clustered networks, networks with distance-dependent connectivity, and those with broad degree distributions. To our surprise, we found that all of these qualitatively distinct topologies could account equally well for all reported nonrandom features despite being easily distinguishable from one another at the network level. This apparent paradox was a consequence of estimating network properties given only small sample sizes. In other words, networks that differ markedly in their global structure can look quite similar locally. This makes inferring network structure from small sample sizes, a necessity given the technical difficulty inherent in simultaneous intracellular recordings, problematic. We found that a network statistic called the sample degree correlation (SDC) overcomes this difficulty. The SDC depends only on parameters that can be estimated reliably given small sample sizes and is an accurate fingerprint of every topological family. We applied the SDC criterion to data from rat visual and somatosensory cortex and discovered that the connectivity was not consistent with any of these main topological classes. However, we were able to fit the experimental data with a more general network class, of which all previous topologies were special cases. The resulting network topology could be interpreted as a combination of physical spatial dependence and nonspatial, hierarchical clustering. SIGNIFICANCE STATEMENT The connectivity of cortical microcircuits exhibits features that are inconsistent with a simple random network. Here, we show that several classes of network models can account for this nonrandom structure despite qualitative differences in

Particle Sampling and Real Time Size Distribution Measurement in H2/O2/TEOS Diffusion Flame

International Nuclear Information System (INIS)

Ahn, K.H.; Jung, C.H.; Choi, M.; Lee, J.S.

2001-01-01

Growth characteristics of silica particles have been studied experimentally using in situ particle sampling technique from H 2 /O 2 /Tetraethylorthosilicate (TEOS) diffusion flame with carefully devised sampling probe. The particle morphology and the size comparisons are made between the particles sampled by the local thermophoretic method from the inside of the flame and by the electrostatic collector sampling method after the dilution sampling probe. The Transmission Electron Microscope (TEM) image processed data of these two sampling techniques are compared with Scanning Mobility Particle Sizer (SMPS) measurement. TEM image analysis of two sampling methods showed a good agreement with SMPS measurement. The effects of flame conditions and TEOS flow rates on silica particle size distributions are also investigated using the new particle dilution sampling probe. It is found that the particle size distribution characteristics and morphology are mostly governed by the coagulation process and sintering process in the flame. As the flame temperature increases, the effect of coalescence or sintering becomes an important particle growth mechanism which reduces the coagulation process. However, if the flame temperature is not high enough to sinter the aggregated particles then the coagulation process is a dominant particle growth mechanism. In a certain flame condition a secondary particle formation is observed which results in a bimodal particle size distribution

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.

Loy Yang A - Australia's largest privatisation

International Nuclear Information System (INIS)

Yenckin, C.

1997-01-01

The recent A$4,746 million privatisation of the 2000MW Loy Yang A power station and the Loy Yang coal mine by the Victorian Government is Australia's largest privatisation and one of 1997's largest project financing deals. (author)

Optimal sizing of utility-scale photovoltaic power generation complementarily operating with hydropower: A case study of the world’s largest hydro-photovoltaic plant

International Nuclear Information System (INIS)

Fang, Wei; Huang, Qiang; Huang, Shengzhi; Yang, Jie; Meng, Erhao; Li, Yunyun

2017-01-01

Highlights: • Feasibility of complementary hydro-photovoltaic operation across the world is revealed. • Three scenarios of the novel operation mode are proposed to satisfy different load demand. • A method for optimally sizing a utility-scale photovoltaic plant is developed by maximizing the net revenue during lifetime. • The influence of complementary hydro-photovoltaic operation upon water resources allocation is investigated. - Abstract: The high variability of solar energy makes utility-scale photovoltaic power generation confront huge challenges to penetrate into power system. In this paper, the complementary hydro-photovoltaic operation is explored, aiming at improving the power quality of photovoltaic and promoting the integration of photovoltaic into the system. First, solar-rich and hydro-rich regions across the world are revealed, which are suitable for implementing the complementary hydro-photovoltaic operation. Then, three practical scenarios of the novel operation mode are proposed for better satisfying different types of load demand. Moreover, a method for optimal sizing of a photovoltaic plant integrated into a hydropower plant is developed by maximizing the net revenue during lifetime. Longyangxia complementary hydro-photovoltaic project, the current world’s largest hydro-photovoltaic power plant, is selected as a case study and its optimal photovoltaic capacities of different scenarios are calculated. Results indicate that hydropower installed capacity and annual solar curtailment rate play crucial roles in the size optimization of a photovoltaic plant and complementary hydro-photovoltaic operation exerts little adverse effect upon the water resources allocation of Longyangxia reservoir. The novel operation mode not only improves the penetration of utility-scale photovoltaic power generation but also can provide a valuable reference for the large-scale utilization of other kinds of renewable energy worldwide.

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

Methodology for sample preparation and size measurement of commercial ZnO nanoparticles

Directory of Open Access Journals (Sweden)

Pei-Jia Lu

2018-04-01

Full Text Available This study discusses the strategies on sample preparation to acquire images with sufficient quality for size characterization by scanning electron microscope (SEM using two commercial ZnO nanoparticles of different surface properties as a demonstration. The central idea is that micrometer sized aggregates of ZnO in powdered forms need to firstly be broken down to nanosized particles through an appropriate process to generate nanoparticle dispersion before being deposited on a flat surface for SEM observation. Analytical tools such as contact angle, dynamic light scattering and zeta potential have been utilized to optimize the procedure for sample preparation and to check the quality of the results. Meanwhile, measurements of zeta potential values on flat surfaces also provide critical information and save lots of time and efforts in selection of suitable substrate for particles of different properties to be attracted and kept on the surface without further aggregation. This simple, low-cost methodology can be generally applied on size characterization of commercial ZnO nanoparticles with limited information from vendors. Keywords: Zinc oxide, Nanoparticles, Methodology

Evaluation of Approaches to Analyzing Continuous Correlated Eye Data When Sample Size Is Small.

Science.gov (United States)

Huang, Jing; Huang, Jiayan; Chen, Yong; Ying, Gui-Shuang

2018-02-01

To evaluate the performance of commonly used statistical methods for analyzing continuous correlated eye data when sample size is small. We simulated correlated continuous data from two designs: (1) two eyes of a subject in two comparison groups; (2) two eyes of a subject in the same comparison group, under various sample size (5-50), inter-eye correlation (0-0.75) and effect size (0-0.8). Simulated data were analyzed using paired t-test, two sample t-test, Wald test and score test using the generalized estimating equations (GEE) and F-test using linear mixed effects model (LMM). We compared type I error rates and statistical powers, and demonstrated analysis approaches through analyzing two real datasets. In design 1, paired t-test and LMM perform better than GEE, with nominal type 1 error rate and higher statistical power. In design 2, no test performs uniformly well: two sample t-test (average of two eyes or a random eye) achieves better control of type I error but yields lower statistical power. In both designs, the GEE Wald test inflates type I error rate and GEE score test has lower power. When sample size is small, some commonly used statistical methods do not perform well. Paired t-test and LMM perform best when two eyes of a subject are in two different comparison groups, and t-test using the average of two eyes performs best when the two eyes are in the same comparison group. When selecting the appropriate analysis approach the study design should be considered.

Quicksort, largest bucket, and min-wise hashing with limited independence

DEFF Research Database (Denmark)

Knudsen, Mathias Bæk Tejs; Stöckel, Morten

2015-01-01

Randomized algorithms and data structures are often analyzed under the assumption of access to a perfect source of randomness. The most fundamental metric used to measure how “random” a hash function or a random number generator is, is its independence: a sequence of random variables is said...... to be k-independent if every variable is uniform and every size k subset is independent. In this paper we consider three classic algorithms under limited independence. Besides the theoretical interest in removing the unrealistic assumption of full independence, the work is motivated by lower independence...... being more practical. We provide new bounds for randomized quicksort, min-wise hashing and largest bucket size under limited independence. Our results can be summarized as follows. Randomized Quicksort. When pivot elements are computed using a 5-independent hash function, Karloff and Raghavan, J.ACM’93...

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.

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

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

Science.gov (United States)

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Sample sizing of biological materials analyzed by energy dispersion X-ray fluorescence

International Nuclear Information System (INIS)

Paiva, Jose D.S.; Franca, Elvis J.; Magalhaes, Marcelo R.L.; Almeida, Marcio E.S.; Hazin, Clovis A.

2013-01-01

Analytical portions used in chemical analyses are usually less than 1g. Errors resulting from the sampling are barely evaluated, since this type of study is a time-consuming procedure, with high costs for the chemical analysis of large number of samples. The energy dispersion X-ray fluorescence - EDXRF is a non-destructive and fast analytical technique with the possibility of determining several chemical elements. Therefore, the aim of this study was to provide information on the minimum analytical portion for quantification of chemical elements in biological matrices using EDXRF. Three species were sampled in mangroves from the Pernambuco, Brazil. Tree leaves were washed with distilled water, oven-dried at 60 deg C and milled until 0.5 mm particle size. Ten test-portions of approximately 500 mg for each species were transferred to vials sealed with polypropylene film. The quality of the analytical procedure was evaluated from the reference materials IAEA V10 Hay Powder, SRM 2976 Apple Leaves. After energy calibration, all samples were analyzed under vacuum for 100 seconds for each group of chemical elements. The voltage used was 15 kV and 50 kV for chemical elements of atomic number lower than 22 and the others, respectively. For the best analytical conditions, EDXRF was capable of estimating the sample size uncertainty for further determination of chemical elements in leaves. (author)

Sample sizing of biological materials analyzed by energy dispersion X-ray fluorescence

Energy Technology Data Exchange (ETDEWEB)

Paiva, Jose D.S.; Franca, Elvis J.; Magalhaes, Marcelo R.L.; Almeida, Marcio E.S.; Hazin, Clovis A., E-mail: dan-paiva@hotmail.com, E-mail: ejfranca@cnen.gov.br, E-mail: marcelo_rlm@hotmail.com, E-mail: maensoal@yahoo.com.br, E-mail: chazin@cnen.gov.b [Centro Regional de Ciencias Nucleares do Nordeste (CRCN-NE/CNEN-PE), Recife, PE (Brazil)

2013-07-01

Analytical portions used in chemical analyses are usually less than 1g. Errors resulting from the sampling are barely evaluated, since this type of study is a time-consuming procedure, with high costs for the chemical analysis of large number of samples. The energy dispersion X-ray fluorescence - EDXRF is a non-destructive and fast analytical technique with the possibility of determining several chemical elements. Therefore, the aim of this study was to provide information on the minimum analytical portion for quantification of chemical elements in biological matrices using EDXRF. Three species were sampled in mangroves from the Pernambuco, Brazil. Tree leaves were washed with distilled water, oven-dried at 60 deg C and milled until 0.5 mm particle size. Ten test-portions of approximately 500 mg for each species were transferred to vials sealed with polypropylene film. The quality of the analytical procedure was evaluated from the reference materials IAEA V10 Hay Powder, SRM 2976 Apple Leaves. After energy calibration, all samples were analyzed under vacuum for 100 seconds for each group of chemical elements. The voltage used was 15 kV and 50 kV for chemical elements of atomic number lower than 22 and the others, respectively. For the best analytical conditions, EDXRF was capable of estimating the sample size uncertainty for further determination of chemical elements in leaves. (author)

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 ).

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.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

Science.gov (United States)

Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen

2017-01-01

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

How the largest electric and gas utility companies administer public relations

Energy Technology Data Exchange (ETDEWEB)

Bogart, J.D.

1979-04-12

This article describes the findings of a survey conducted by the author in the second half of 1978 to determine the sizes of the public relations staffs of the nation's largest operating electric and gas utilities, their budgets, organizational differences, and specific functions. Common public relations issues and major public relations problems of the utilities are identified, as well as recent trends or changes in budgeting and organization. Some functional variations of public relations departments among utility companies were detected and described.

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.

Crystallite size variation of TiO_2 samples depending time heat treatment

International Nuclear Information System (INIS)

Galante, A.G.M.; Paula, F.R. de; Montanhera, M.A.; Pereira, E.A.; Spada, E.R.

2016-01-01

Titanium dioxide (TiO_2) is an oxide semiconductor that may be found in mixed phase or in distinct phases: brookite, anatase and rutile. In this work was carried out the study of the residence time influence at a given temperature in the TiO_2 powder physical properties. After the powder synthesis, the samples were divided and heat treated at 650 °C with a ramp up to 3 °C/min and a residence time ranging from 0 to 20 hours and subsequently characterized by x-ray diffraction. Analyzing the obtained diffraction patterns, it was observed that, from 5-hour residence time, began the two-distinct phase coexistence: anatase and rutile. It also calculated the average crystallite size of each sample. The results showed an increase in average crystallite size with increasing residence time of the heat treatment. (author)

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…

Short time-scale optical variability properties of the largest AGN sample observed with Kepler/K2

Science.gov (United States)

Aranzana, E.; Körding, E.; Uttley, P.; Scaringi, S.; Bloemen, S.

2018-05-01

We present the first short time-scale (˜hours to days) optical variability study of a large sample of active galactic nuclei (AGNs) observed with the Kepler/K2 mission. The sample contains 252 AGN observed over four campaigns with ˜30 min cadence selected from the Million Quasar Catalogue with R magnitude <19. We performed time series analysis to determine their variability properties by means of the power spectral densities (PSDs) and applied Monte Carlo techniques to find the best model parameters that fit the observed power spectra. A power-law model is sufficient to describe all the PSDs of our sample. A variety of power-law slopes were found indicating that there is not a universal slope for all AGNs. We find that the rest-frame amplitude variability in the frequency range of 6 × 10-6-10-4 Hz varies from 1to10 per cent with an average of 1.7 per cent. We explore correlations between the variability amplitude and key parameters of the AGN, finding a significant correlation of rest-frame short-term variability amplitude with redshift. We attribute this effect to the known `bluer when brighter' variability of quasars combined with the fixed bandpass of Kepler data. This study also enables us to distinguish between Seyferts and blazars and confirm AGN candidates. For our study, we have compared results obtained from light curves extracted using different aperture sizes and with and without detrending. We find that limited detrending of the optimal photometric precision light curve is the best approach, although some systematic effects still remain present.

Sample Size Requirements for Assessing Statistical Moments of Simulated Crop Yield Distributions

NARCIS (Netherlands)

Lehmann, N.; Finger, R.; Klein, T.; Calanca, P.

2013-01-01

Mechanistic crop growth models are becoming increasingly important in agricultural research and are extensively used in climate change impact assessments. In such studies, statistics of crop yields are usually evaluated without the explicit consideration of sample size requirements. The purpose of

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.

The one-sample PARAFAC approach reveals molecular size distributions of fluorescent components in dissolved organic matter

DEFF Research Database (Denmark)

Wünsch, Urban; Murphy, Kathleen R.; Stedmon, Colin

2017-01-01

Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM...... but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical...... opportunities for elucidating the origins and biogeochemical properties of FDOM...

14CO2 analysis of soil gas: Evaluation of sample size limits and sampling devices

Science.gov (United States)

Wotte, Anja; Wischhöfer, Philipp; Wacker, Lukas; Rethemeyer, Janet

2017-12-01

Radiocarbon (14C) analysis of CO2 respired from soils or sediments is a valuable tool to identify different carbon sources. The collection and processing of the CO2, however, is challenging and prone to contamination. We thus continuously improve our handling procedures and present a refined method for the collection of even small amounts of CO2 in molecular sieve cartridges (MSCs) for accelerator mass spectrometry 14C analysis. Using a modified vacuum rig and an improved desorption procedure, we were able to increase the CO2 recovery from the MSC (95%) as well as the sample throughput compared to our previous study. By processing series of different sample size, we show that our MSCs can be used for CO2 samples of as small as 50 μg C. The contamination by exogenous carbon determined in these laboratory tests, was less than 2.0 μg C from fossil and less than 3.0 μg C from modern sources. Additionally, we tested two sampling devices for the collection of CO2 samples released from soils or sediments, including a respiration chamber and a depth sampler, which are connected to the MSC. We obtained a very promising, low process blank for the entire CO2 sampling and purification procedure of ∼0.004 F14C (equal to 44,000 yrs BP) and ∼0.003 F14C (equal to 47,000 yrs BP). In contrast to previous studies, we observed no isotopic fractionation towards lighter δ13C values during the passive sampling with the depth samplers.

The attention-weighted sample-size model of visual short-term memory: Attention capture predicts resource allocation and memory load.

Science.gov (United States)

Smith, Philip L; Lilburn, Simon D; Corbett, Elaine A; Sewell, David K; Kyllingsbæk, Søren

2016-09-01

We investigated the capacity of visual short-term memory (VSTM) in a phase discrimination task that required judgments about the configural relations between pairs of black and white features. Sewell et al. (2014) previously showed that VSTM capacity in an orientation discrimination task was well described by a sample-size model, which views VSTM as a resource comprised of a finite number of noisy stimulus samples. The model predicts the invariance of [Formula: see text] , the sum of squared sensitivities across items, for displays of different sizes. For phase discrimination, the set-size effect significantly exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items in the display captures attention and receives a disproportionate share of resources. The choice probabilities and response time distributions from the task were well described by a diffusion decision model in which the drift rates embodied the assumptions of the attention-weighted sample-size model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Size dependence of elastic mechanical properties of nanocrystalline aluminum

Energy Technology Data Exchange (ETDEWEB)

Xu, Wenwu; Dávila, Lilian P., E-mail: ldavila@ucmerced.edu

2017-04-24

The effect of grain size on the elastic mechanical properties of nanocrystalline pure metal Al is quantified by molecular dynamics simulation method. In this work, the largest nanocrystalline Al sample has a mean grain size of 29.6 nm and contains over 100 millions atoms in the modeling system. The simulation results show that the elastic properties including elastic modulus and ultimate tensile strength of nanocrystalline Al are relatively insensitive to the variation of mean grain size above 13 nm yet they become distinctly grain size dependent below 13 nm. Moreover, at a grain size <13 nm, the elastic modulus decreases monotonically with decreasing grain size while the ultimate tensile strength of nanocrystalline Al initially decreases with the decrease of the grain size down to 9 nm and then increases with further reduction of grain size. The increase of ultimate tensile strength below 9 nm is believed to be a result of an extended elasticity in the ultrafine grain size nanocrystalline Al. This study can facilitate the prediction of varied mechanical properties for similar nanocrystalline materials and even guide testing and fabrication schemes of such materials.

Statistical characterization of a large geochemical database and effect of sample size

Science.gov (United States)

Zhang, C.; Manheim, F.T.; Hinde, J.; Grossman, J.N.

2005-01-01

smaller numbers of data points showed that few elements passed standard statistical tests for normality or log-normality until sample size decreased to a few hundred data points. Large sample size enhances the power of statistical tests, and leads to rejection of most statistical hypotheses for real data sets. For large sample sizes (e.g., n > 1000), graphical methods such as histogram, stem-and-leaf, and probability plots are recommended for rough judgement of probability distribution if needed. ?? 2005 Elsevier Ltd. All rights reserved.

Sample sufficiency of chinese pink grown in different substrates

Directory of Open Access Journals (Sweden)

Sidinei José lopes

2016-04-01

Full Text Available The cravina is an excellent plant to build up gardens due to its early flowering, abundant flowering and great performance in spring and autumn. The objective was to estimate the sample size for plant chinese pink, grown on different substrates, and check the variability of the sample size between growth parameters and production and substrates. They used seven treatments (substrates: S1 = 50% soil + 50% rice husk ash; S2 = 80% soil + 20% earthworm castings; S3 = 80% rice husk ash + 20% earthworm castings; S4 = 40% soil + 40% rice husk ash + 20% earthworm castings; S5 = 100% peat; S6 = 100% commercial substrate Mecplant®; S7 = 50% peat + 50% rice husk ash, with 56 repetitions each, totaling 392 plants of garden pink, which was evaluated in 17 of growth and production parameters. The methodology used to bootstrap resampling, with replacement, for each character within each substrate with predetermined error: 5, 10, 20 and 40% of the average (D%. To a 95% confidence interval, with D = 20%, the substrate 50% soil and 50% of rice husk ash had the largest sample size 11 characters; when comparing the characters , the number of flower buds had the highest sample size on average 113 plants. Using samples of 44 plant chinese pink for commercial substrate Mecplant® meet the lower precisions or equal to 20% for all variables. There is variation in sample size in relation to the substrate used and the variable evaluated in chinese pink plants.

A note on power and sample size calculations for the Kruskal-Wallis test for ordered categorical data.

Science.gov (United States)

Fan, Chunpeng; Zhang, Donghui

2012-01-01

Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.

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.

Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

Science.gov (United States)

Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

2016-01-01

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

On sample size of the kruskal-wallis test with application to a mouse peritoneal cavity study.

Science.gov (United States)

Fan, Chunpeng; Zhang, Donghui; Zhang, Cun-Hui

2011-03-01

As the nonparametric generalization of the one-way analysis of variance model, the Kruskal-Wallis test applies when the goal is to test the difference between multiple samples and the underlying population distributions are nonnormal or unknown. Although the Kruskal-Wallis test has been widely used for data analysis, power and sample size methods for this test have been investigated to a much lesser extent. This article proposes new power and sample size calculation methods for the Kruskal-Wallis test based on the pilot study in either a completely nonparametric model or a semiparametric location model. No assumption is made on the shape of the underlying population distributions. Simulation results show that, in terms of sample size calculation for the Kruskal-Wallis test, the proposed methods are more reliable and preferable to some more traditional methods. A mouse peritoneal cavity study is used to demonstrate the application of the methods. © 2010, The International Biometric Society.

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.

Atmospheric aerosol sampling campaign in Budapest and K-puszta. Part 1. Elemental concentrations and size distributions

International Nuclear Information System (INIS)

Dobos, E.; Borbely-Kiss, I.; Kertesz, Zs.; Szabo, Gy.; Salma, I.

2004-01-01

Complete text of publication follows. Atmospheric aerosol samples were collected in a sampling campaign from 24 July to 1 Au- gust, 2003 in Hungary. The sampling were performed in two places simultaneously: in Budapest (urban site) and K-puszta (remote area). Two PIXE International 7-stage cascade impactors were used for aerosol sampling with 24 hours duration. These impactors separate the aerosol into 7 size ranges. The elemental concentrations of the samples were obtained by proton-induced X-ray Emission (PIXE) analysis. Size distributions of S, Si, Ca, W, Zn, Pb and Fe elements were investigated in K-puszta and in Budapest. Average rates (shown in Table 1) of the elemental concentrations was calculated for each stage (in %) from the obtained distributions. The elements can be grouped into two parts on the basis of these data. The majority of the particle containing Fe, Si, Ca, (Ti) are in the 2-8 μm size range (first group). These soil origin elements were found usually in higher concentration in Budapest than in K-puszta (Fig.1.). The second group consisted of S, Pb and (W). The majority of these elements was found in the 0.25-1 μm size range and was much higher in Budapest than in K-puszta. W was measured only in samples collected in Budapest. Zn has uniform distribution in Budapest and does not belong to the above mentioned groups. This work was supported by the National Research and Development Program (NRDP 3/005/2001). (author)

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.

Evaluating sampling strategy for DNA barcoding study of coastal and inland halo-tolerant Poaceae and Chenopodiaceae: A case study for increased sample size.

Directory of Open Access Journals (Sweden)

Peng-Cheng Yao

Full Text Available Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P < 0.01. These results suggest that increasing the sample size in specialist habitats can improve measurements of intraspecific genetic diversity, and will have a positive effect on the application of the DNA barcodes in widely distributed species. The results of random sampling showed that when sample size reached 11 for Chloris virgata, Chenopodium glaucum, and Dysphania ambrosioides, 13 for Setaria viridis, and 15 for Eleusine indica, Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11-15.

Adaptive clinical trial designs with pre-specified rules for modifying the sample size: understanding efficient types of adaptation.

Science.gov (United States)

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2013-04-15

Adaptive clinical trial design has been proposed as a promising new approach that may improve the drug discovery process. Proponents of adaptive sample size re-estimation promote its ability to avoid 'up-front' commitment of resources, better address the complicated decisions faced by data monitoring committees, and minimize accrual to studies having delayed ascertainment of outcomes. We investigate aspects of adaptation rules, such as timing of the adaptation analysis and magnitude of sample size adjustment, that lead to greater or lesser statistical efficiency. Owing in part to the recent Food and Drug Administration guidance that promotes the use of pre-specified sampling plans, we evaluate alternative approaches in the context of well-defined, pre-specified adaptation. We quantify the relative costs and benefits of fixed sample, group sequential, and pre-specified adaptive designs with respect to standard operating characteristics such as type I error, maximal sample size, power, and expected sample size under a range of alternatives. Our results build on others' prior research by demonstrating in realistic settings that simple and easily implemented pre-specified adaptive designs provide only very small efficiency gains over group sequential designs with the same number of analyses. In addition, we describe optimal rules for modifying the sample size, providing efficient adaptation boundaries on a variety of scales for the interim test statistic for adaptation analyses occurring at several different stages of the trial. We thus provide insight into what are good and bad choices of adaptive sampling plans when the added flexibility of adaptive designs is desired. Copyright © 2012 John Wiley & Sons, Ltd.

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…

Application of the largest Lyapunov exponent and non-linear fractal extrapolation algorithm to short-term load forecasting

International Nuclear Information System (INIS)

Wang Jianzhou; Jia Ruiling; Zhao Weigang; Wu Jie; Dong Yao

2012-01-01

Highlights: ► The maximal predictive step size is determined by the largest Lyapunov exponent. ► A proper forecasting step size is applied to load demand forecasting. ► The improved approach is validated by the actual load demand data. ► Non-linear fractal extrapolation method is compared with three forecasting models. ► Performance of the models is evaluated by three different error measures. - Abstract: Precise short-term load forecasting (STLF) plays a key role in unit commitment, maintenance and economic dispatch problems. Employing a subjective and arbitrary predictive step size is one of the most important factors causing the low forecasting accuracy. To solve this problem, the largest Lyapunov exponent is adopted to estimate the maximal predictive step size so that the step size in the forecasting is no more than this maximal one. In addition, in this paper a seldom used forecasting model, which is based on the non-linear fractal extrapolation (NLFE) algorithm, is considered to develop the accuracy of predictions. The suitability and superiority of the two solutions are illustrated through an application to real load forecasting using New South Wales electricity load data from the Australian National Electricity Market. Meanwhile, three forecasting models: the gray model, the seasonal autoregressive integrated moving average approach and the support vector machine method, which received high approval in STLF, are selected to compare with the NLFE algorithm. Comparison results also show that the NLFE model is outstanding, effective, practical and feasible.

In Situ Sampling of Relative Dust Devil Particle Loads and Their Vertical Grain Size Distributions.

Science.gov (United States)

Raack, Jan; Reiss, Dennis; Balme, Matthew R; Taj-Eddine, Kamal; Ori, Gian Gabriele

2017-04-19

During a field campaign in the Sahara Desert in southern Morocco, spring 2012, we sampled the vertical grain size distribution of two active dust devils that exhibited different dimensions and intensities. With these in situ samples of grains in the vortices, it was possible to derive detailed vertical grain size distributions and measurements of the lifted relative particle load. Measurements of the two dust devils show that the majority of all lifted particles were only lifted within the first meter (∼46.5% and ∼61% of all particles; ∼76.5 wt % and ∼89 wt % of the relative particle load). Furthermore, ∼69% and ∼82% of all lifted sand grains occurred in the first meter of the dust devils, indicating the occurrence of "sand skirts." Both sampled dust devils were relatively small (∼15 m and ∼4-5 m in diameter) compared to dust devils in surrounding regions; nevertheless, measurements show that ∼58.5% to 73.5% of all lifted particles were small enough to go into suspension (grain size classification). This relatively high amount represents only ∼0.05 to 0.15 wt % of the lifted particle load. Larger dust devils probably entrain larger amounts of fine-grained material into the atmosphere, which can have an influence on the climate. Furthermore, our results indicate that the composition of the surface, on which the dust devils evolved, also had an influence on the particle load composition of the dust devil vortices. The internal particle load structure of both sampled dust devils was comparable related to their vertical grain size distribution and relative particle load, although both dust devils differed in their dimensions and intensities. A general trend of decreasing grain sizes with height was also detected. Key Words: Mars-Dust devils-Planetary science-Desert soils-Atmosphere-Grain sizes. Astrobiology 17, xxx-xxx.

Extreme eigenvalues of sample covariance and correlation matrices

DEFF Research Database (Denmark)

Heiny, Johannes

This thesis is concerned with asymptotic properties of the eigenvalues of high-dimensional sample covariance and correlation matrices under an infinite fourth moment of the entries. In the first part, we study the joint distributional convergence of the largest eigenvalues of the sample covariance...... matrix of a p-dimensional heavy-tailed time series when p converges to infinity together with the sample size n. We generalize the growth rates of p existing in the literature. Assuming a regular variation condition with tail index ... eigenvalues are essentially determined by the extreme order statistics from an array of iid random variables. The asymptotic behavior of the extreme eigenvalues is then derived routinely from classical extreme value theory. The resulting approximations are strikingly simple considering the high dimension...

Sensitivity and specificity of normality tests and consequences on reference interval accuracy at small sample size: a computer-simulation study.

Science.gov (United States)

Le Boedec, Kevin

2016-12-01

According to international guidelines, parametric methods must be chosen for RI construction when the sample size is small and the distribution is Gaussian. However, normality tests may not be accurate at small sample size. The purpose of the study was to evaluate normality test performance to properly identify samples extracted from a Gaussian population at small sample sizes, and assess the consequences on RI accuracy of applying parametric methods to samples that falsely identified the parent population as Gaussian. Samples of n = 60 and n = 30 values were randomly selected 100 times from simulated Gaussian, lognormal, and asymmetric populations of 10,000 values. The sensitivity and specificity of 4 normality tests were compared. Reference intervals were calculated using 6 different statistical methods from samples that falsely identified the parent population as Gaussian, and their accuracy was compared. Shapiro-Wilk and D'Agostino-Pearson tests were the best performing normality tests. However, their specificity was poor at sample size n = 30 (specificity for P Box-Cox transformation) on all samples regardless of their distribution or adjusting, the significance level of normality tests depending on sample size would limit the risk of constructing inaccurate RI. © 2016 American Society for Veterinary Clinical Pathology.

Seasonal body size reductions with warming covary with major body size gradients in arthropod species

DEFF Research Database (Denmark)

Horne, Curtis R.; Hirst, Andrew G.; Atkinson, David

2017-01-01

experience different developmental conditions. Yet, unlike other size patterns, these common seasonal temperature–size gradients have never been collectively analysed. We undertake the largest analysis to date of seasonal temperature-size gradients in multivoltine arthropods, including 102 aquatic...... and terrestrial species from 71 global locations. Adult size declines in warmer seasons in 86% of the species examined. Aquatic species show approximately 2.5-fold greater reduction in size per °C of warming than terrestrial species, supporting the hypothesis that greater oxygen limitation in water than in air...

Method for rapid particle size analysis by hydrosizing and nuclear sensing

International Nuclear Information System (INIS)

Daellenbach, C.B.; Mahan, W.M.

1977-01-01

A method and apparatus to practice the method for rapidly determining the size and mass distribution of a sample of randomly sized particles of a known total mass are described. A series of substantially identical hydrocyclones are connected by conduits to each other and to a temperature controlled water feed. By restricting the cross-sectional areas of these conduits to progressively smaller values, the slurry containing the sample particles is caused to increase its velocity as it moves from hydrocyclone to hydrocyclone. As described by the Stokesian theory which relates particle diameter and settling velocity, the largest sized particles are suspended in the closed apex of the first hydrocyclone with smaller sized particles, in given size ranges, being suspended in the next succeeding hydrocyclone's apexes. In this manner, the particles are separated into discrete fractional sizes with a residual slurry of the very smallest particles being discharged. Before the discrete fractions of particles are suspended in their hydrocyclone apexes, a combined photon source, like a gamma ray source, and detector are calibrated with the water temperature kept constant. When the suspension of particles takes place, an attenuation of the radiation from the source is observed at the detector. This attenuation can be related to the mass or weight of the discrete fractions of suspended particles. Electronic circuitry is used to indicate what this fractional mass or weight is as it relates to the total weight of the sample. 6 claims, 4 figs

Growth and maximum size of tiger sharks (Galeocerdo cuvier) in Hawaii.

Science.gov (United States)

Meyer, Carl G; O'Malley, Joseph M; Papastamatiou, Yannis P; Dale, Jonathan J; Hutchinson, Melanie R; Anderson, James M; Royer, Mark A; Holland, Kim N

2014-01-01

Tiger sharks (Galecerdo cuvier) are apex predators characterized by their broad diet, large size and rapid growth. Tiger shark maximum size is typically between 380 & 450 cm Total Length (TL), with a few individuals reaching 550 cm TL, but the maximum size of tiger sharks in Hawaii waters remains uncertain. A previous study suggested tiger sharks grow rather slowly in Hawaii compared to other regions, but this may have been an artifact of the method used to estimate growth (unvalidated vertebral ring counts) compounded by small sample size and narrow size range. Since 1993, the University of Hawaii has conducted a research program aimed at elucidating tiger shark biology, and to date 420 tiger sharks have been tagged and 50 recaptured. All recaptures were from Hawaii except a single shark recaptured off Isla Jacques Cousteau (24°13'17″N 109°52'14″W), in the southern Gulf of California (minimum distance between tag and recapture sites  =  approximately 5,000 km), after 366 days at liberty (DAL). We used these empirical mark-recapture data to estimate growth rates and maximum size for tiger sharks in Hawaii. We found that tiger sharks in Hawaii grow twice as fast as previously thought, on average reaching 340 cm TL by age 5, and attaining a maximum size of 403 cm TL. Our model indicates the fastest growing individuals attain 400 cm TL by age 5, and the largest reach a maximum size of 444 cm TL. The largest shark captured during our study was 464 cm TL but individuals >450 cm TL were extremely rare (0.005% of sharks captured). We conclude that tiger shark growth rates and maximum sizes in Hawaii are generally consistent with those in other regions, and hypothesize that a broad diet may help them to achieve this rapid growth by maximizing prey consumption rates.

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

and several recent estimators [proposed by Rosenzweig et al. (Conservation Biology, 2003, 17, 864-874), and Ugland et al. (Journal of Animal Ecology, 2003, 72, 888-897)] performed poorly. 3.  Estimations developed using the smaller grain sizes (pair of traps, traps, records and individuals) presented similar....... Data obtained with standardized sampling of 78 transects in natural forest remnants of five islands were aggregated in seven different grains (i.e. ways of defining a single sample): islands, natural areas, transects, pairs of traps, traps, database records and individuals to assess the effect of using...

Considerations for Sample Preparation Using Size-Exclusion Chromatography for Home and Synchrotron Sources.

Science.gov (United States)

Rambo, Robert P

2017-01-01

The success of a SAXS experiment for structural investigations depends on two precise measurements, the sample and the buffer background. Buffer matching between the sample and background can be achieved using dialysis methods but in biological SAXS of monodisperse systems, sample preparation is routinely being performed with size exclusion chromatography (SEC). SEC is the most reliable method for SAXS sample preparation as the method not only purifies the sample for SAXS but also almost guarantees ideal buffer matching. Here, I will highlight the use of SEC for SAXS sample preparation and demonstrate using example proteins that SEC purification does not always provide for ideal samples. Scrutiny of the SEC elution peak using quasi-elastic and multi-angle light scattering techniques can reveal hidden features (heterogeneity) of the sample that should be considered during SAXS data analysis. In some cases, sample heterogeneity can be controlled using a small molecule additive and I outline a simple additive screening method for sample preparation.

Foreign exchange risk management : how are the largest non-financial companies in Norway managing their foreign exchange rate exposure?

OpenAIRE

Eriksen, Krister; Wedøe, Ola

2010-01-01

The purpose of this thesis is to investigate how the largest non-financial companies in Norway manage their foreign exchange rate exposure. This is investigated through the use of a survey distributed to a sample the largest non-financial firms in Norway. According to our results, the largest non-financial companies in Norway have a predefined strategy for managing foreign exchange risk, which is defined by the board of directors or by the management in the organisation. The companies’ mai...

The study of the sample size on the transverse magnetoresistance of bismuth nanowires

International Nuclear Information System (INIS)

Zare, M.; Layeghnejad, R.; Sadeghi, E.

2012-01-01

The effects of sample size on the galvanomagnetice properties of semimetal nanowires are theoretically investigated. Transverse magnetoresistance (TMR) ratios have been calculated within a Boltzmann Transport Equation (BTE) approach by specular reflection approximation. Temperature and radius dependence of the transverse magnetoresistance of cylindrical Bismuth nanowires are given. The obtained values are in good agreement with the experimental results, reported by Heremans et al. - Highlights: ► In this study effects of sample size on the galvanomagnetic properties of Bi. ► Nanowires were explained by Parrott theorem by solving the Boltzmann Transport Equation. ► Transverse magnetoresistance (TMR) ratios have been measured by specular reflection approximation. ► Temperature and radius dependence of the transverse magnetoresistance of cylindrical Bismuth nanowires are given. ► The obtained values are in good agreement with the experimental results, reported by Heremans et al.

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

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...... in 1994-5 by the scientific-ethics committees for Copenhagen and Frederiksberg, Denmark (n=70). MAIN OUTCOME MEASURE: Proportion of protocols and publications that did not provide key information about sample size calculations and statistical methods; proportion of trials with discrepancies between...... 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...

A Web-based Simulator for Sample Size and Power Estimation in Animal Carcinogenicity Studies

Directory of Open Access Journals (Sweden)

Hojin Moon

2002-12-01

Full Text Available A Web-based statistical tool for sample size and power estimation in animal carcinogenicity studies is presented in this paper. It can be used to provide a design with sufficient power for detecting a dose-related trend in the occurrence of a tumor of interest when competing risks are present. The tumors of interest typically are occult tumors for which the time to tumor onset is not directly observable. It is applicable to rodent tumorigenicity assays that have either a single terminal sacrifice or multiple (interval sacrifices. The design is achieved by varying sample size per group, number of sacrifices, number of sacrificed animals at each interval, if any, and scheduled time points for sacrifice. Monte Carlo simulation is carried out in this tool to simulate experiments of rodent bioassays because no closed-form solution is available. It takes design parameters for sample size and power estimation as inputs through the World Wide Web. The core program is written in C and executed in the background. It communicates with the Web front end via a Component Object Model interface passing an Extensible Markup Language string. The proposed statistical tool is illustrated with an animal study in lung cancer prevention research.

Critical Evolution of Damage Toward System-Size Failure in Crystalline Rock

Science.gov (United States)

Renard, François; Weiss, Jérôme; Mathiesen, Joachim; Ben-Zion, Yehuda; Kandula, Neelima; Cordonnier, Benoît

2018-02-01

Rock failure under shear loading conditions controls earthquake and faulting phenomena. We study the dynamics of microscale damage precursory to shear faulting in a quartz-monzonite rock representative of crystalline rocks of the continental crust. Using a triaxial rig that is transparent to X-rays, we image the mechanical evolution of centimeter-size core samples by in situ synchrotron microtomography with a resolution of 6.5 μm. Time-lapse three-dimensional images of the samples inside the rig provide a unique data set of microstructural evolution toward faulting. Above a yield point there is a gradual weakening during which microfractures nucleate and grow until this damage span the whole sample. This leads to shear faults oriented about 30° to the main compressive stress in agreement with Anderson's theory and macroscopic failure. The microfractures can be extracted from the three-dimensional images, and their dynamics and morphology (i.e., number, volume, orientation, shape, and largest cluster) are quantified as a function of increasing stress toward failure. The experimental data show for the first time that the total volume of microfractures, the rate of damage growth, and the size of the largest microfracture all increase and diverge when approaching faulting. The average flatness of the microfractures (i.e., the ratio between the second and third eigenvalues of their covariance matrix) shows a significant decrease near failure. The precursors to faulting developing in the future faulting zone are controlled by the evolving microfracture population. Their divergent dynamics toward failure is reminiscent of a dynamical critical transition.

SDSS-II SUPERNOVA SURVEY: AN ANALYSIS OF THE LARGEST SAMPLE OF TYPE IA SUPERNOVAE AND CORRELATIONS WITH HOST-GALAXY SPECTRAL PROPERTIES

International Nuclear Information System (INIS)

Wolf, Rachel C.; Gupta, Ravi R.; Sako, Masao; Fischer, John A.; March, Marisa C.; Fischer, Johanna-Laina; D’Andrea, Chris B.; Smith, Mathew; Kessler, Rick; Scolnic, Daniel M.; Jha, Saurabh W.; Campbell, Heather; Nichol, Robert C.; Olmstead, Matthew D.; Richmond, Michael; Schneider, Donald P.

2016-01-01

Using the largest single-survey sample of Type Ia supernovae (SNe Ia) to date, we study the relationship between properties of SNe Ia and those of their host galaxies, focusing primarily on correlations with Hubble residuals (HRs). Our sample consists of 345 photometrically classified or spectroscopically confirmed SNe Ia discovered as part of the SDSS-II Supernova Survey (SDSS-SNS). This analysis utilizes host-galaxy spectroscopy obtained during the SDSS-I/II spectroscopic survey and from an ancillary program on the SDSS-III Baryon Oscillation Spectroscopic Survey that obtained spectra for nearly all host galaxies of SDSS-II SN candidates. In addition, we use photometric host-galaxy properties from the SDSS-SNS data release such as host stellar mass and star formation rate. We confirm the well-known relation between HR and host-galaxy mass and find a 3.6 σ significance of a nonzero linear slope. We also recover correlations between HR and host-galaxy gas-phase metallicity and specific star formation rate as they are reported in the literature. With our large data set, we examine correlations between HR and multiple host-galaxy properties simultaneously and find no evidence of a significant correlation. We also independently analyze our spectroscopically confirmed and photometrically classified SNe Ia and comment on the significance of similar combined data sets for future surveys.

Generalized procedures for determining inspection sample sizes (related to quantitative measurements). Vol. 1: Detailed explanations

International Nuclear Information System (INIS)

Jaech, J.L.; Lemaire, R.J.

1986-11-01

Generalized procedures have been developed to determine sample sizes in connection with the planning of inspection activities. These procedures are based on different measurement methods. They are applied mainly to Bulk Handling Facilities and Physical Inventory Verifications. The present report attempts (i) to assign to appropriate statistical testers (viz. testers for gross, partial and small defects) the measurement methods to be used, and (ii) to associate the measurement uncertainties with the sample sizes required for verification. Working papers are also provided to assist in the application of the procedures. This volume contains the detailed explanations concerning the above mentioned procedures

Analysis of femtogram-sized plutonium samples by thermal ionization mass spectrometry

International Nuclear Information System (INIS)

Smith, D.H.; Duckworth, D.C.; Bostick, D.T.; Coleman, R.M.; McPherson, R.L.; McKown, H.S.

1994-01-01

The goal of this investigation was to extend the ability to perform isotopic analysis of plutonium to samples as small as possible. Plutonium ionizes thermally with quite good efficiency (first ionization potential 5.7 eV). Sub-nanogram sized samples can be analyzed on a near-routine basis given the necessary instrumentation. Efforts in this laboratory have been directed at rhenium-carbon systems; solutions of carbon in rhenium provide surfaces with work functions higher than pure rhenium (5.8 vs. ∼ 5.4 eV). Using a single resin bead as a sample loading medium both concentrates the sample nearly to a point and, due to its interaction with rhenium, produces the desired composite surface. Earlier work in this area showed that a layer of rhenium powder slurried in solution containing carbon substantially enhanced precision of isotopic measurements for uranium. Isotopic fractionation was virtually eliminated, and ionization efficiencies 2-5 times better than previously measured were attained for both Pu and U (1.7 and 0.5%, respectively). The other side of this coin should be the ability to analyze smaller samples, which is the subject of this report

Sample Size and Robustness of Inferences from Logistic Regression in the Presence of Nonlinearity and Multicollinearity

OpenAIRE

Bergtold, Jason S.; Yeager, Elizabeth A.; Featherstone, Allen M.

2011-01-01

The logistic regression models has been widely used in the social and natural sciences and results from studies using this model can have significant impact. Thus, confidence in the reliability of inferences drawn from these models is essential. The robustness of such inferences is dependent on sample size. The purpose of this study is to examine the impact of sample size on the mean estimated bias and efficiency of parameter estimation and inference for the logistic regression model. A numbe...

Bias in segmented gamma scans arising from size differences between calibration standards and assay samples

International Nuclear Information System (INIS)

Sampson, T.E.

1991-01-01

Recent advances in segmented gamma scanning have emphasized software corrections for gamma-ray self-adsorption in particulates or lumps of special nuclear material in the sample. another feature of this software is an attenuation correction factor formalism that explicitly accounts for differences in sample container size and composition between the calibration standards and the individual items being measured. Software without this container-size correction produces biases when the unknowns are not packaged in the same containers as the calibration standards. This new software allows the use of different size and composition containers for standards and unknowns, as enormous savings considering the expense of multiple calibration standard sets otherwise needed. This paper presents calculations of the bias resulting from not using this new formalism. These calculations may be used to estimate bias corrections for segmented gamma scanners that do not incorporate these advanced concepts

Sample Size Estimation for Negative Binomial Regression Comparing Rates of Recurrent Events with Unequal Follow-Up Time.

Science.gov (United States)

Tang, Yongqiang

2015-01-01

A sample size formula is derived for negative binomial regression for the analysis of recurrent events, in which subjects can have unequal follow-up time. We obtain sharp lower and upper bounds on the required size, which is easy to compute. The upper bound is generally only slightly larger than the required size, and hence can be used to approximate the sample size. The lower and upper size bounds can be decomposed into two terms. The first term relies on the mean number of events in each group, and the second term depends on two factors that measure, respectively, the extent of between-subject variability in event rates, and follow-up time. Simulation studies are conducted to assess the performance of the proposed method. An application of our formulae to a multiple sclerosis trial is provided.

Rule-of-thumb adjustment of sample sizes to accommodate dropouts in a two-stage analysis of repeated measurements.

Science.gov (United States)

Overall, John E; Tonidandel, Scott; Starbuck, Robert R

2006-01-01

Recent contributions to the statistical literature have provided elegant model-based solutions to the problem of estimating sample sizes for testing the significance of differences in mean rates of change across repeated measures in controlled longitudinal studies with differentially correlated error and missing data due to dropouts. However, the mathematical complexity and model specificity of these solutions make them generally inaccessible to most applied researchers who actually design and undertake treatment evaluation research in psychiatry. In contrast, this article relies on a simple two-stage analysis in which dropout-weighted slope coefficients fitted to the available repeated measurements for each subject separately serve as the dependent variable for a familiar ANCOVA test of significance for differences in mean rates of change. This article is about how a sample of size that is estimated or calculated to provide desired power for testing that hypothesis without considering dropouts can be adjusted appropriately to take dropouts into account. Empirical results support the conclusion that, whatever reasonable level of power would be provided by a given sample size in the absence of dropouts, essentially the same power can be realized in the presence of dropouts simply by adding to the original dropout-free sample size the number of subjects who would be expected to drop from a sample of that original size under conditions of the proposed study.

Uncertainty budget in internal monostandard NAA for small and large size samples analysis

International Nuclear Information System (INIS)

Dasari, K.B.; Acharya, R.

2014-01-01

Total uncertainty budget evaluation on determined concentration value is important under quality assurance programme. Concentration calculation in NAA or carried out by relative NAA and k0 based internal monostandard NAA (IM-NAA) method. IM-NAA method has been used for small and large sample analysis of clay potteries. An attempt was made to identify the uncertainty components in IM-NAA and uncertainty budget for La in both small and large size samples has been evaluated and compared. (author)

A contemporary decennial global Landsat sample of changing agricultural field sizes

Science.gov (United States)

White, Emma; Roy, David

2014-05-01

Agriculture has caused significant human induced Land Cover Land Use (LCLU) change, with dramatic cropland expansion in the last century and significant increases in productivity over the past few decades. Satellite data have been used for agricultural applications including cropland distribution mapping, crop condition monitoring, crop production assessment and yield prediction. Satellite based agricultural applications are less reliable when the sensor spatial resolution is small relative to the field size. However, to date, studies of agricultural field size distributions and their change have been limited, even though this information is needed to inform the design of agricultural satellite monitoring systems. Moreover, the size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLU change. In many parts of the world field sizes may have increased. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, and impacts on the diffusion of herbicides, pesticides, disease pathogens, and pests. The Landsat series of satellites provide the longest record of global land observations, with 30m observations available since 1982. Landsat data are used to examine contemporary field size changes in a period (1980 to 2010) when significant global agricultural changes have occurred. A multi-scale sampling approach is used to locate global hotspots of field size change by examination of a recent global agricultural yield map and literature review. Nine hotspots are selected where significant field size change is apparent and where change has been driven by technological advancements (Argentina and U.S.), abrupt societal changes (Albania and Zimbabwe), government land use and agricultural policy changes (China, Malaysia, Brazil), and/or constrained by

Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

Science.gov (United States)

Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

2018-03-01

In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

Science.gov (United States)

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

Science.gov (United States)

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

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, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

The importance of plot size and the number of sampling seasons on capturing macrofungal species richness.

Science.gov (United States)

Li, Huili; Ostermann, Anne; Karunarathna, Samantha C; Xu, Jianchu; Hyde, Kevin D; Mortimer, Peter E

2018-07-01

The species-area relationship is an important factor in the study of species diversity, conservation biology, and landscape ecology. A deeper understanding of this relationship is necessary, in order to provide recommendations on how to improve the quality of data collection on macrofungal diversity in different land use systems in future studies, a systematic assessment of methodological parameters, in particular optimal plot sizes. The species-area relationship of macrofungi in tropical and temperate climatic zones and four different land use systems were investigated by determining the macrofungal species richness in plot sizes ranging from 100 m 2 to 10 000 m 2 over two sampling seasons. We found that the effect of plot size on recorded species richness significantly differed between land use systems with the exception of monoculture systems. For both climate zones, land use system needs to be considered when determining optimal plot size. Using an optimal plot size was more important than temporal replication (over two sampling seasons) in accurately recording species richness. Copyright © 2018 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Re-estimating sample size in cluster randomized trials with active recruitment within clusters

NARCIS (Netherlands)

van Schie, Sander; Moerbeek, Mirjam

2014-01-01

Often only a limited number of clusters can be obtained in cluster randomised trials, although many potential participants can be recruited within each cluster. Thus, active recruitment is feasible within the clusters. To obtain an efficient sample size in a cluster randomised trial, the cluster

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

Science.gov (United States)

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Largest College Endowments, 2011

Science.gov (United States)

Chronicle of Higher Education, 2012

2012-01-01

Of all endowments valued at more than $250-million, the UCLA Foundation had the highest rate of growth over the previous year, at 49 percent. This article presents a table of the largest college endowments in 2011. The table covers the "rank," "institution," "market value as of June 30, 2011," and "1-year change" of institutions participating in…

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

PURPOSE: For certain cancer indications, the current patient evaluation strategy is a perfect but locally restricted gold standard procedure. If positron emission tomography/computed tomography (PET/CT) can be shown to be reliable within the gold standard region and if it can be argued that PET...... 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....../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...

Percolation under noise: Detecting explosive percolation using the second-largest component

Science.gov (United States)

Viles, Wes; Ginestet, Cedric E.; Tang, Ariana; Kramer, Mark A.; Kolaczyk, Eric D.

2016-05-01

We consider the problem of distinguishing between different rates of percolation under noise. A statistical model of percolation is constructed allowing for the birth and death of edges as well as the presence of noise in the observations. This graph-valued stochastic process is composed of a latent and an observed nonstationary process, where the observed graph process is corrupted by type-I and type-II errors. This produces a hidden Markov graph model. We show that for certain choices of parameters controlling the noise, the classical (Erdős-Rényi) percolation is visually indistinguishable from a more rapid form of percolation. In this setting, we compare two different criteria for discriminating between these two percolation models, based on the interquartile range (IQR) of the first component's size, and on the maximal size of the second-largest component. We show through data simulations that this second criterion outperforms the IQR of the first component's size, in terms of discriminatory power. The maximal size of the second component therefore provides a useful statistic for distinguishing between different rates of percolation, under physically motivated conditions for the birth and death of edges, and under noise. The potential application of the proposed criteria for the detection of clinically relevant percolation in the context of applied neuroscience is also discussed.

Validation Of Intermediate Large Sample Analysis (With Sizes Up to 100 G) and Associated Facility Improvement

International Nuclear Information System (INIS)

Bode, P.; Koster-Ammerlaan, M.J.J.

2018-01-01

Pragmatic rather than physical correction factors for neutron and gamma-ray shielding were studied for samples of intermediate size, i.e. up to the 10-100 gram range. It was found that for most biological and geological materials, the neutron self-shielding is less than 5 % and the gamma-ray self-attenuation can easily be estimated. A trueness control material of 1 kg size was made based on use of left-overs of materials, used in laboratory intercomparisons. A design study for a large sample pool-side facility, handling plate-type volumes, had to be stopped because of a reduction in human resources, available for this CRP. The large sample NAA facilities were made available to guest scientists from Greece and Brazil. The laboratory for neutron activation analysis participated in the world’s first laboratory intercomparison utilizing large samples. (author)

Effect of dislocation pile-up on size-dependent yield strength in finite single-crystal micro-samples

Energy Technology Data Exchange (ETDEWEB)

Pan, Bo; Shibutani, Yoji, E-mail: sibutani@mech.eng.osaka-u.ac.jp [Department of Mechanical Engineering, Osaka University, Suita 565-0871 (Japan); Zhang, Xu [State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi' an Jiaotong University, Xi' an 710049 (China); School of Mechanics and Engineering Science, Zhengzhou University, Zhengzhou 450001 (China); Shang, Fulin [State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi' an Jiaotong University, Xi' an 710049 (China)

2015-07-07

Recent research has explained that the steeply increasing yield strength in metals depends on decreasing sample size. In this work, we derive a statistical physical model of the yield strength of finite single-crystal micro-pillars that depends on single-ended dislocation pile-up inside the micro-pillars. We show that this size effect can be explained almost completely by considering the stochastic lengths of the dislocation source and the dislocation pile-up length in the single-crystal micro-pillars. The Hall–Petch-type relation holds even in a microscale single-crystal, which is characterized by its dislocation source lengths. Our quantitative conclusions suggest that the number of dislocation sources and pile-ups are significant factors for the size effect. They also indicate that starvation of dislocation sources is another reason for the size effect. Moreover, we investigated the explicit relationship between the stacking fault energy and the dislocation “pile-up” effect inside the sample: materials with low stacking fault energy exhibit an obvious dislocation pile-up effect. Our proposed physical model predicts a sample strength that agrees well with experimental data, and our model can give a more precise prediction than the current single arm source model, especially for materials with low stacking fault energy.

The largest glitch observed in the Crab pulsar

Science.gov (United States)

Shaw, B.; Lyne, A. G.; Stappers, B. W.; Weltevrede, P.; Bassa, C. G.; Lien, A. Y.; Mickaliger, M. B.; Breton, R. P.; Jordan, C. A.; Keith, M. J.; Krimm, H. A.

2018-05-01

We have observed a large glitch in the Crab pulsar (PSR B0531+21). The glitch occurred around MJD 58064 (2017 November 8) when the pulsar underwent an increase in the rotation rate of Δν = 1.530 × 10-5 Hz, corresponding to a fractional increase of Δν/ν = 0.516 × 10-6 making this event the largest glitch ever observed in this source. Due to our high-cadence and long-dwell time observations of the Crab pulsar we are able to partially resolve a fraction of the total spin-up of the star. This delayed spin-up occurred over a timescale of ˜1.7 days and is similar to the behaviour seen in the 1989 and 1996 large Crab pulsar glitches. The spin-down rate also increased at the glitch epoch by Δ \\dot{ν } / \\dot{ν } = 7 × 10^{-3}. In addition to being the largest such event observed in the Crab, the glitch occurred after the longest period of glitch inactivity since at least 1984 and we discuss a possible relationship between glitch size and waiting time. No changes to the shape of the pulse profile were observed near the glitch epoch at 610 MHz or 1520 MHz, nor did we identify any changes in the X-ray flux from the pulsar. The long-term recovery from the glitch continues to progress as \\dot{ν } slowly rises towards pre-glitch values. In line with other large Crab glitches, we expect there to be a persistent change to \\dot{ν }. We continue to monitor the long-term recovery with frequent, high quality observations.

Undersampling power-law size distributions: effect on the assessment of extreme natural hazards

Science.gov (United States)

Geist, Eric L.; Parsons, Thomas E.

2014-01-01

The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests using synthetic catalogs indicate that the tail of an empirical size distribution sampled from a pure Pareto probability distribution can range from having one-to-several unusually large events to appearing depleted, relative to the parent distribution. Both of these effects are artifacts caused by limited catalog length. It is more difficult to diagnose the artificially depleted empirical distributions, since one expects that a pure Pareto distribution is physically limited in some way. Using maximum likelihood methods and the method of moments, we estimate the power-law exponent and the corner size parameter of tapered Pareto distributions for several natural hazard examples: tsunamis, floods, and earthquakes. Each of these examples has varying catalog lengths and measurement thresholds, relative to the largest event sizes. In many cases where there are only several orders of magnitude between the measurement threshold and the largest events, joint two-parameter estimation techniques are necessary to account for estimation dependence between the power-law scaling exponent and the corner size parameter. Results indicate that whereas the corner size parameter of a tapered Pareto distribution can be estimated, its upper confidence bound cannot be determined and the estimate itself is often unstable with time. Correspondingly, one cannot statistically reject a pure Pareto null hypothesis using natural hazard catalog data. Although physical limits to the hazard source size and by attenuation mechanisms from source to site constrain the maximum hazard size, historical data alone often cannot reliably determine the corner size parameter. Probabilistic assessments incorporating theoretical constraints on source size and propagation effects are preferred over deterministic assessments of extreme natural hazards based on historic data.

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

A simple sample size formula for analysis of covariance in cluster randomized trials.

NARCIS (Netherlands)

Teerenstra, S.; Eldridge, S.; Graff, M.J.; Hoop, E. de; Borm, G.F.

2012-01-01

For cluster randomized trials with a continuous outcome, the sample size is often calculated as if an analysis of the outcomes at the end of the treatment period (follow-up scores) would be performed. However, often a baseline measurement of the outcome is available or feasible to obtain. An

Grain size distributions and their effects on auto-acoustic compaction

Science.gov (United States)

Taylor, S.; Brodsky, E. E.

2013-12-01

A variety of geophysical and geomorphological processes depend on the response of granular mixtures to shear stress. For example, if shear sliding in a fault zone causes gouge to compact or dilate, this has implications on our understanding of earthquake nucleation and propagation. The behavior of granular flows has previously been found to be strongly dependent on shear rate. At relatively slow shear velocities, a granular flow will support stresses elastically through force chains in what is recognized as the 'quasi-static' regime. At relatively high shear velocities, it will support stresses by transferring momentum in higher velocity grain collisions in the 'grain-inertial' regime, which results in dilation of the flow. Recent experiments conducted using a commercial torsional rheometer found that at intermediate shear velocities, force chain collapse in angular sand samples produced sound waves capable of vibrating the shear zone enough to cause compaction. To expand on the characterization of this newly identified rheological regime, the 'auto-acoustic' regime, we used the same experimental set up to observe how volumetric and acoustic response to shear stress changes with grain size mean and range. Stepped velocity ramp experiments were conducted first on five separate grain size bins, and then on various mixtures of these grain sizes. As expected, larger grain sizes entered the mass-dependent grain-inertial regime at lower shear velocities than smaller grain sizes. Interestingly, smaller grain sizes exhibited more pronounced compaction at slower velocities resulting from the auto-acoustic regime, and the largest grain sizes showed no compaction, implying a grain size threshold for auto-acoustic compaction. In mixtures of different grain size bins, the response of the flow to intermediate shear velocities was consistent with the response of the smallest grain size bin included in the mixture, while the response of the flow to high shear velocities was most

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.

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...

Size-segregated urban aerosol characterization by electron microscopy and dynamic light scattering and influence of sample preparation

Science.gov (United States)

Marvanová, Soňa; Kulich, Pavel; Skoupý, Radim; Hubatka, František; Ciganek, Miroslav; Bendl, Jan; Hovorka, Jan; Machala, Miroslav

2018-04-01

Size-segregated particulate matter (PM) is frequently used in chemical and toxicological studies. Nevertheless, toxicological in vitro studies working with the whole particles often lack a proper evaluation of PM real size distribution and characterization of agglomeration under the experimental conditions. In this study, changes in particle size distributions during the PM sample manipulation and also semiquantitative elemental composition of single particles were evaluated. Coarse (1-10 μm), upper accumulation (0.5-1 μm), lower accumulation (0.17-0.5 μm), and ultrafine (culture media. PM suspension of lower accumulation fraction in water agglomerated after freezing/thawing the sample, and the agglomerates were disrupted by subsequent sonication. Ultrafine fraction did not agglomerate after freezing/thawing the sample. Both lower accumulation and ultrafine fractions were stable in cell culture media with fetal bovine serum, while high agglomeration occurred in media without fetal bovine serum as measured during 24 h.

Clustering for high-dimension, low-sample size data using distance vectors

OpenAIRE

Terada, Yoshikazu

2013-01-01

In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that contain information of the cluster structure in high-dimensional space. Based on this fact, we propose an efficient and simple clustering approach, called distance vector clustering, for HDLSS data. Under the assumptions given in the work of Hall et al. (2005), w...

Annual cycle of size-resolved organic aerosol characterization in an urbanized desert environment

Science.gov (United States)

Cahill, Thomas M.

2013-06-01

Studies of size-resolved organic speciation of aerosols are still relatively rare and are generally only conducted over short durations. However, size-resolved organic data can both suggest possible sources of the aerosols and identify the human exposure to the chemicals since different aerosol sizes have different lung capture efficiencies. The objective of this study was to conduct size-resolved organic aerosol speciation for a calendar year in Phoenix, Arizona to determine the seasonal variations in both chemical concentrations and size profiles. The results showed large seasonal differences in combustion pollutants where the highest concentrations were observed in winter. Summertime aerosols have a greater proportion of biological compounds (e.g. sugars and fatty acids) and the biological compounds represent the largest fraction of the organic compounds detected. These results suggest that standard organic carbon (OC) measurements might be heavily influenced by primary biological compounds particularly if the samples are PM10 and TSP samples. Several large dust storms did not significantly alter the organic aerosol profile since Phoenix resides in a dusty desert environment, so the soil and plant tracer of trehalose was almost always present. The aerosol size profiles showed that PAHs were generally most abundant in the smallest aerosol size fractions, which are most likely to be captured by the lung, while the biological compounds were almost exclusively found in the coarse size fraction.

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.…

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…

Type-II generalized family-wise error rate formulas with application to sample size determination.

Science.gov (United States)

Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie

2016-07-20

Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Largest particle detector nearing completion

CERN Multimedia

2006-01-01

"Construction of another part of the Large Hadron Collider (LHC), the worl's largest particle accelerator at CERN in Switzerland, is nearing completion. The Compact Muon Solenoid (CMS) is oner of the LHC project's four large particle detectors. (1/2 page)

Sample Size Calculation: Inaccurate A Priori Assumptions for Nuisance Parameters Can Greatly Affect the Power of a Randomized Controlled Trial.

Directory of Open Access Journals (Sweden)

Elsa Tavernier

Full Text Available We aimed to examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial (RCT. In a simulation study, we separately considered an RCT with continuous, dichotomous or time-to-event outcomes, with associated nuisance parameters of standard deviation, success rate in the control group and survival rate in the control group at some time point, respectively. For each type of outcome, we calculated a required sample size N for a hypothesized treatment effect, an assumed nuisance parameter and a nominal power of 80%. We then assumed a nuisance parameter associated with a relative error at the design stage. For each type of outcome, we randomly drew 10,000 relative errors of the associated nuisance parameter (from empirical distributions derived from a previously published review. Then, retro-fitting the sample size formula, we derived, for the pre-calculated sample size N, the real power of the RCT, taking into account the relative error for the nuisance parameter. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was 90%. Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. Such findings raise questions about how sample size for RCTs should be determined.

Building predictive models of soil particle-size distribution

Directory of Open Access Journals (Sweden)

Alessandro Samuel-Rosa

2013-04-01

Full Text Available Is it possible to build predictive models (PMs of soil particle-size distribution (psd in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index. The PMs explained more than half of the data variance. This performance is similar to (or even better than that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd of soils in regions of complex geology.

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)

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

International Nuclear Information System (INIS)

Reer, B.

2004-01-01

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)

Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data.

Science.gov (United States)

Bhaskar, Anand; Wang, Y X Rachel; Song, Yun S

2015-02-01

With the recent increase in study sample sizes in human genetics, there has been growing interest in inferring historical population demography from genomic variation data. Here, we present an efficient inference method that can scale up to very large samples, with tens or hundreds of thousands of individuals. Specifically, by utilizing analytic results on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic differentiation, which allows us to compute gradients exactly, we develop a very efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. Our method is orders of magnitude faster than previous demographic inference methods based on the frequency spectrum. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates. We perform extensive validation of our method on simulated data and show that it can accurately infer multiple recent epochs of rapid exponential growth, a signal that is difficult to pick up with small sample sizes. Lastly, we use our method to analyze data from recent sequencing studies, including a large-sample exome-sequencing data set of tens of thousands of individuals assayed at a few hundred genic regions. © 2015 Bhaskar et al.; Published by Cold Spring Harbor Laboratory Press.

Ownership structure and economic and socio-environmental disclosure in the largest Brazilian companies

Directory of Open Access Journals (Sweden)

Tatiana Aquino Almeida

2016-01-01

Full Text Available The disclosure of sustainable practices has become important in the search for competitive advantage, so as to meet the expectations of the various stakeholders. Thus, the study aims to investigate the relationship between the ownership structure and the economic and environmental voluntary disclosure in the largest Brazilian companies, analyzing ownership concentration and the identity of the controlling shareholder. For the analysis, we considered the economic, social and environmental perspectives, addressed both individually and jointly. The sample consists of 47 companies from the 100 largest public companies listed on BM&FBOVESPA, according to the magazine Exame Biggest and Best, edition 2013. The research is descriptive and quantitative, using Multiple Linear Regression for statistical analysis. The descriptive analysis of the prospects of (economic, social, environmental and sustainability disclosure showed lower average disclosure for the environmental aspect. The state control organizations stood out with the highest average in three of the four levels of disclosure: economic, social and sustainability. As regards the application of statistical analysis, the regression models were not statistically significant, indicating that, for the companies in the sample, the ownership structure does not influence the economic and socio-environmental disclosure.

Body Size Distribution of the Dinosaurs

OpenAIRE

O?Gorman, Eoin J.; Hone, David W. E.

2012-01-01

The distribution of species body size is critically important for determining resource use within a group or clade. It is widely known that non-avian dinosaurs were the largest creatures to roam the Earth. There is, however, little understanding of how maximum species body size was distributed among the dinosaurs. Do they share a similar distribution to modern day vertebrate groups in spite of their large size, or did they exhibit fundamentally different distributions due to unique evolutiona...

Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes.

Science.gov (United States)

Moustakas, Aristides; Evans, Matthew R

2015-02-28

Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose. We investigate the survival rates of ten tree species in a dataset designed to monitor growth rates. As some individuals were not included in the census at some time points we use capture-mark-recapture methods both to allow us to account for missing individuals, and to estimate relocation probabilities. Growth rates, size, and light availability were included as covariates in the model predicting survival rates. The study demonstrates that tree mortality is best described as constant between years and size-dependent at early life stages and size independent at later life stages for most species of UK hardwood. We have demonstrated that even with a twenty-year dataset it is possible to discern variability both between individuals and between species. Our work illustrates the potential utility of the method applied here for calculating plant population dynamics parameters in time replicated datasets with small sample sizes and missing individuals without any loss of sample size, and including explanatory covariates.

Development of a sampling strategy and sample size calculation to estimate the distribution of mammographic breast density in Korean women.

Science.gov (United States)

Jun, Jae Kwan; Kim, Mi Jin; Choi, Kui Son; Suh, Mina; Jung, Kyu-Won

2012-01-01

Mammographic breast density is a known risk factor for breast cancer. To conduct a survey to estimate the distribution of mammographic breast density in Korean women, appropriate sampling strategies for representative and efficient sampling design were evaluated through simulation. Using the target population from the National Cancer Screening Programme (NCSP) for breast cancer in 2009, we verified the distribution estimate by repeating the simulation 1,000 times using stratified random sampling to investigate the distribution of breast density of 1,340,362 women. According to the simulation results, using a sampling design stratifying the nation into three groups (metropolitan, urban, and rural), with a total sample size of 4,000, we estimated the distribution of breast density in Korean women at a level of 0.01% tolerance. Based on the results of our study, a nationwide survey for estimating the distribution of mammographic breast density among Korean women can be conducted efficiently.

Diagram Size vs. Layout Flaws: Understanding Quality Factors of UML Diagrams

DEFF Research Database (Denmark)

Störrle, Harald

2016-01-01

, though, is our third goal of extending our analysis aspects of diagram quality. Method: We improve our definition of diagram size and add a (provisional) definition of diagram quality as the number of topographic layout flaws. We apply these metrics on 60 diagrams of the five most commonly used types...... of UML diagram. We carefully analyze the structure of our diagram samples to ensure representativeness. We correlate diagram size and layout quality with modeler performance data obtained in previous experiments. The data set is the largest of its kind (n-156). Results: We replicate earlier findings......, and extend them to two new diagram types. We provide an improved definition of diagram size, and provide a definition of topographic layout quality, which is one more step towards a comprehensive definition of diagram quality as such. Both metrics are shown to be objectively applicable. We quantify...

Sample size calculations based on a difference in medians for positively skewed outcomes in health care studies

Directory of Open Access Journals (Sweden)

Aidan G. O’Keeffe

2017-12-01

Full Text Available Abstract Background In healthcare research, outcomes with skewed probability distributions are common. Sample size calculations for such outcomes are typically based on estimates on a transformed scale (e.g. log which may sometimes be difficult to obtain. In contrast, estimates of median and variance on the untransformed scale are generally easier to pre-specify. The aim of this paper is to describe how to calculate a sample size for a two group comparison of interest based on median and untransformed variance estimates for log-normal outcome data. Methods A log-normal distribution for outcome data is assumed and a sample size calculation approach for a two-sample t-test that compares log-transformed outcome data is demonstrated where the change of interest is specified as difference in median values on the untransformed scale. A simulation study is used to compare the method with a non-parametric alternative (Mann-Whitney U test in a variety of scenarios and the method is applied to a real example in neurosurgery. Results The method attained a nominal power value in simulation studies and was favourable in comparison to a Mann-Whitney U test and a two-sample t-test of untransformed outcomes. In addition, the method can be adjusted and used in some situations where the outcome distribution is not strictly log-normal. Conclusions We recommend the use of this sample size calculation approach for outcome data that are expected to be positively skewed and where a two group comparison on a log-transformed scale is planned. An advantage of this method over usual calculations based on estimates on the log-transformed scale is that it allows clinical efficacy to be specified as a difference in medians and requires a variance estimate on the untransformed scale. Such estimates are often easier to obtain and more interpretable than those for log-transformed outcomes.

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

In vitro rumen feed degradability assessed with DaisyII and batch culture: effect of sample size

Directory of Open Access Journals (Sweden)

Stefano Schiavon

2010-01-01

Full Text Available In vitro degradability with DaisyII (D equipment is commonly performed with 0.5g of feed sample into each filter bag. Literature reported that a reduction of the ratio of sample size to bag surface could facilitate the release of soluble or fine particulate. A reduction of sample size to 0.25 g could improve the correlation between the measurements provided by D and the conventional batch culture (BC. This hypothesis was screened by analysing the results of 2 trials. In trial 1, 7 feeds were incubated for 48h with rumen fluid (3 runs x 4 replications both with D (0.5g/bag and BC; the regressions between the mean values provided for the various feeds in each run by the 2 methods either for NDF (NDFd and in vitro true DM (IVTDMD degradability, had R2 of 0.75 and 0.92 and RSD of 10.9 and 4.8%, respectively. In trial 2, 4 feeds were incubated (2 runs x 8 replications with D (0.25 g/bag and BC; the corresponding regressions for NDFd and IVTDMD showed R2 of 0.94 and 0.98 and RSD of 3.0 and 1.3%, respectively. A sample size of 0.25 g improved the precision of the measurements obtained with D.

Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

Science.gov (United States)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

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

and power when applied to these groups. We propose the use of the variance partition coefficient (VPC), which measures the clustering of infection/disease for individuals with a common risk profile. Sample size estimates are obtained separately for those groups that exhibit markedly different heterogeneity......, thus, optimizing resource allocation. A VPC-based predictive simulation method for sample size estimation to substantiate freedom from disease is presented. To illustrate the benefits of the proposed approach we give two examples with the analysis of data from a risk factor study on Mycobacterium avium...

Analysis of time series and size of equivalent sample

International Nuclear Information System (INIS)

Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge

2004-01-01

In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions

Sample size requirements for studies of treatment effects on beta-cell function in newly diagnosed type 1 diabetes.

Science.gov (United States)

Lachin, John M; McGee, Paula L; Greenbaum, Carla J; Palmer, Jerry; Pescovitz, Mark D; Gottlieb, Peter; Skyler, Jay

2011-01-01

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 accurately

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

Sample size for comparing negative binomial rates in noninferiority and equivalence trials with unequal follow-up times.

Science.gov (United States)

Tang, Yongqiang

2017-05-25

We derive the sample size formulae for comparing two negative binomial rates based on both the relative and absolute rate difference metrics in noninferiority and equivalence trials with unequal follow-up times, and establish an approximate relationship between the sample sizes required for the treatment comparison based on the two treatment effect metrics. The proposed method allows the dispersion parameter to vary by treatment groups. The accuracy of these methods is assessed by simulations. It is demonstrated that ignoring the between-subject variation in the follow-up time by setting the follow-up time for all individuals to be the mean follow-up time may greatly underestimate the required size, resulting in underpowered studies. Methods are provided for back-calculating the dispersion parameter based on the published summary results.

Evaluation of species richness estimators based on quantitative performance measures and sensitivity to patchiness and sample grain size

Science.gov (United States)

Willie, Jacob; Petre, Charles-Albert; Tagg, Nikki; Lens, Luc

2012-11-01

Data from forest herbaceous plants in a site of known species richness in Cameroon were used to test the performance of rarefaction and eight species richness estimators (ACE, ICE, Chao1, Chao2, Jack1, Jack2, Bootstrap and MM). Bias, accuracy, precision and sensitivity to patchiness and sample grain size were the evaluation criteria. An evaluation of the effects of sampling effort and patchiness on diversity estimation is also provided. Stems were identified and counted in linear series of 1-m2 contiguous square plots distributed in six habitat types. Initially, 500 plots were sampled in each habitat type. The sampling process was monitored using rarefaction and a set of richness estimator curves. Curves from the first dataset suggested adequate sampling in riparian forest only. Additional plots ranging from 523 to 2143 were subsequently added in the undersampled habitats until most of the curves stabilized. Jack1 and ICE, the non-parametric richness estimators, performed better, being more accurate and less sensitive to patchiness and sample grain size, and significantly reducing biases that could not be detected by rarefaction and other estimators. This study confirms the usefulness of non-parametric incidence-based estimators, and recommends Jack1 or ICE alongside rarefaction while describing taxon richness and comparing results across areas sampled using similar or different grain sizes. As patchiness varied across habitat types, accurate estimations of diversity did not require the same number of plots. The number of samples needed to fully capture diversity is not necessarily the same across habitats, and can only be known when taxon sampling curves have indicated adequate sampling. Differences in observed species richness between habitats were generally due to differences in patchiness, except between two habitats where they resulted from differences in abundance. We suggest that communities should first be sampled thoroughly using appropriate taxon sampling

Environmental isotope signatures of the largest freshwater lake in Kerala

International Nuclear Information System (INIS)

Unnikrishnan Warrier, C.

2007-01-01

Sasthamkotta lake, the largest freshwater lake in Kerala, serves as a source for drinking water for more than half a million people. Environmental 137 Cs analysis done on undisturbed sediment core samples reveals that the recent rate of sedimentation is not uniform in the lake. The useful life of lake is estimated as about 800 years. The δD and δ 18 O values of the lake waters indicate that the lake is well mixed with a slight variation horizontally. The stable isotope studies on well waters from the catchment indicate hydraulic communication with the lake and lake groundwater system is flow-through type. Analytical model also supports this view. (author)

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

Science.gov (United States)

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

Noninvasive genetics provides insights into the population size and genetic diversity of an Amur tiger population in China.

Science.gov (United States)

Wang, Dan; Hu, Yibo; Ma, Tianxiao; Nie, Yonggang; Xie, Yan; Wei, Fuwen

2016-01-01

Understanding population size and genetic diversity is critical for effective conservation of endangered species. The Amur tiger (Panthera tigris altaica) is the largest felid and a flagship species for wildlife conservation. Due to habitat loss and human activities, available habitat and population size are continuously shrinking. However, little is known about the true population size and genetic diversity of wild tiger populations in China. In this study, we collected 55 fecal samples and 1 hair sample to investigate the population size and genetic diversity of wild Amur tigers in Hunchun National Nature Reserve, Jilin Province, China. From the samples, we determined that 23 fecal samples and 1 hair sample were from 7 Amur tigers: 2 males, 4 females and 1 individual of unknown sex. Interestingly, 2 fecal samples that were presumed to be from tigers were from Amur leopards, highlighting the significant advantages of noninvasive genetics over traditional methods in studying rare and elusive animals. Analyses from this sample suggested that the genetic diversity of wild Amur tigers is much lower than that of Bengal tigers, consistent with previous findings. Furthermore, the genetic diversity of this Hunchun population in China was lower than that of the adjoining subpopulation in southwest Primorye Russia, likely due to sampling bias. Considering the small population size and relatively low genetic diversity, it is urgent to protect this endangered local subpopulation in China. © 2015 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

From damselflies to pterosaurs: how burst and sustainable flight performance scale with size.

Science.gov (United States)

Marden, J H

1994-04-01

Recent empirical data for short-burst lift and power production of flying animals indicate that mass-specific lift and power output scale independently (lift) or slightly positively (power) with increasing size. These results contradict previous theory, as well as simple observation, which argues for degradation of flight performance with increasing size. Here, empirical measures of lift and power during short-burst exertion are combined with empirically based estimates of maximum muscle power output in order to predict how burst and sustainable performance scale with body size. The resulting model is used to estimate performance of the largest extant flying birds and insects, along with the largest flying animals known from fossils. These estimates indicate that burst flight performance capacities of even the largest extinct fliers (estimated mass 250 kg) would allow takeoff from the ground; however, limitations on sustainable power output should constrain capacity for continuous flight at body sizes exceeding 0.003-1.0 kg, depending on relative wing length and flight muscle mass.

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.

A novel approach for small sample size family-based association studies: sequential tests.

Science.gov (United States)

Ilk, Ozlem; Rajabli, Farid; Dungul, Dilay Ciglidag; Ozdag, Hilal; Ilk, Hakki Gokhan

2011-08-01

In this paper, we propose a sequential probability ratio test (SPRT) to overcome the problem of limited samples in studies related to complex genetic diseases. The results of this novel approach are compared with the ones obtained from the traditional transmission disequilibrium test (TDT) on simulated data. Although TDT classifies single-nucleotide polymorphisms (SNPs) to only two groups (SNPs associated with the disease and the others), SPRT has the flexibility of assigning SNPs to a third group, that is, those for which we do not have enough evidence and should keep sampling. It is shown that SPRT results in smaller ratios of false positives and negatives, as well as better accuracy and sensitivity values for classifying SNPs when compared with TDT. By using SPRT, data with small sample size become usable for an accurate association analysis.

Sampling efficiency of modified 37-mm sampling cassettes using computational fluid dynamics.

Science.gov (United States)

Anthony, T Renée; Sleeth, Darrah; Volckens, John

2016-01-01

In the U.S., most industrial hygiene practitioners continue to rely on the closed-face cassette (CFC) to assess worker exposures to hazardous dusts, primarily because ease of use, cost, and familiarity. However, mass concentrations measured with this classic sampler underestimate exposures to larger particles throughout the inhalable particulate mass (IPM) size range (up to aerodynamic diameters of 100 μm). To investigate whether the current 37-mm inlet cap can be redesigned to better meet the IPM sampling criterion, computational fluid dynamics (CFD) models were developed, and particle sampling efficiencies associated with various modifications to the CFC inlet cap were determined. Simulations of fluid flow (standard k-epsilon turbulent model) and particle transport (laminar trajectories, 1-116 μm) were conducted using sampling flow rates of 10 L min(-1) in slow moving air (0.2 m s(-1)) in the facing-the-wind orientation. Combinations of seven inlet shapes and three inlet diameters were evaluated as candidates to replace the current 37-mm inlet cap. For a given inlet geometry, differences in sampler efficiency between inlet diameters averaged less than 1% for particles through 100 μm, but the largest opening was found to increase the efficiency for the 116 μm particles by 14% for the flat inlet cap. A substantial reduction in sampler efficiency was identified for sampler inlets with side walls extending beyond the dimension of the external lip of the current 37-mm CFC. The inlet cap based on the 37-mm CFC dimensions with an expanded 15-mm entry provided the best agreement with facing-the-wind human aspiration efficiency. The sampler efficiency was increased with a flat entry or with a thin central lip adjacent to the new enlarged entry. This work provides a substantial body of sampling efficiency estimates as a function of particle size and inlet geometry for personal aerosol samplers.

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

Science.gov (United States)

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

Science.gov (United States)

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

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...

Reproducibility of 5-HT2A receptor measurements and sample size estimations with [18F]altanserin PET using a bolus/infusion approach

International Nuclear Information System (INIS)

Haugboel, Steven; Pinborg, Lars H.; Arfan, Haroon M.; Froekjaer, Vibe M.; Svarer, Claus; Knudsen, Gitte M.; Madsen, Jacob; Dyrby, Tim B.

2007-01-01

To determine the reproducibility of measurements of brain 5-HT 2A receptors with an [ 18 F]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. For assessment of the variability, six subjects were investigated with [ 18 F]altanserin PET twice, at an interval of less than 2 weeks. The sample size required to detect a 20% difference was estimated from [ 18 F]altanserin PET studies in 84 healthy subjects. Regions of interest were automatically delineated on co-registered MR and PET images. In cortical brain regions with a high density of 5-HT 2A receptors, the outcome parameter (binding potential, BP 1 ) showed high reproducibility, with a median difference between the two group measurements of 6% (range 5-12%), whereas in regions with a low receptor density, BP 1 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 receptor density is approximately 27, whereas for low receptor binding regions the required sample size is substantially higher. This study demonstrates that [ 18 F]altanserin PET with a bolus/infusion design has very low variability, particularly in larger brain regions with high 5-HT 2A receptor density. Moreover, partial volume correction considerably reduces the sample size required to detect regional changes between groups. (orig.)

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.

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

International Nuclear Information System (INIS)

Wagner, Annemarie; Boman, Johan; Gatari, Michael J.

2008-01-01

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 μm 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

Evolution of the Largest Mammalian Genome.

Science.gov (United States)

Evans, Ben J; Upham, Nathan S; Golding, Goeffrey B; Ojeda, Ricardo A; Ojeda, Agustina A

2017-06-01

The genome of the red vizcacha rat (Rodentia, Octodontidae, Tympanoctomys barrerae) is the largest of all mammals, and about double the size of their close relative, the mountain vizcacha rat Octomys mimax, even though the lineages that gave rise to these species diverged from each other only about 5 Ma. The mechanism for this rapid genome expansion is controversial, and hypothesized to be a consequence of whole genome duplication or accumulation of repetitive elements. To test these alternative but nonexclusive hypotheses, we gathered and evaluated evidence from whole transcriptome and whole genome sequences of T. barrerae and O. mimax. We recovered support for genome expansion due to accumulation of a diverse assemblage of repetitive elements, which represent about one half and one fifth of the genomes of T. barrerae and O. mimax, respectively, but we found no strong signal of whole genome duplication. In both species, repetitive sequences were rare in transcribed regions as compared with the rest of the genome, and mostly had no close match to annotated repetitive sequences from other rodents. These findings raise new questions about the genomic dynamics of these repetitive elements, their connection to widespread chromosomal fissions that occurred in the T. barrerae ancestor, and their fitness effects-including during the evolution of hypersaline dietary tolerance in T. barrerae. ©The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in

Science.gov (United States)

North Carolina America's Largest Home Runs on Biodiesel in North Carolina to someone by E-mail Share Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in North Carolina on Facebook Tweet about Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in North

Sampling and chemical analysis by TXRF of size-fractionated ambient aerosols and emissions

International Nuclear Information System (INIS)

John, A.C.; Kuhlbusch, T.A.J.; Fissan, H.; Schmidt, K.-G-; Schmidt, F.; Pfeffer, H.-U.; Gladtke, D.

2000-01-01

Results of recent epidemiological studies led to new European air quality standards which require the monitoring of particles with aerodynamic diameters ≤ 10 μm (PM 10) and ≤ 2.5 μm (PM 2.5) instead of TSP (total suspended particulate matter). As these ambient air limit values will be exceeded most likely at several locations in Europe, so-called 'action plans' have to be set up to reduce particle concentrations, which requires information about sources and processes of PMx aerosols. For chemical characterization of the aerosols, different samplers were used and total reflection x-ray fluorescence analysis (TXRF) was applied beside other methods (elemental and organic carbon analysis, ion chromatography, atomic absorption spectrometry). For TXRF analysis, a specially designed sampling unit was built where the particle size classes 10-2.5 μm and 2.5-1.0 μm were directly impacted on TXRF sample carriers. An electrostatic precipitator (ESP) was used as a back-up filter to collect particles <1 μm directly on a TXRF sample carrier. The sampling unit was calibrated in the laboratory and then used for field measurements to determine the elemental composition of the mentioned particle size fractions. One of the field campaigns was carried out at a measurement site in Duesseldorf, Germany, in November 1999. As the composition of the ambient aerosols may have been influenced by a large construction site directly in the vicinity of the station during the field campaign, not only the aerosol particles, but also construction material was sampled and analyzed by TXRF. As air quality is affected by natural and anthropogenic sources, the emissions of particles ≤ 10 μm and ≤ 2.5 μm, respectively, have to be determined to estimate their contributions to the so called coarse and fine particle modes of ambient air. Therefore, an in-stack particle sampling system was developed according to the new ambient air quality standards. This PM 10/PM 2.5 cascade impactor was

Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals.

Science.gov (United States)

Terry, Leann; Kelley, Ken

2012-11-01

Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.

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...

Reproducibility of R-fMRI metrics on the impact of different strategies for multiple comparison correction and sample sizes.

Science.gov (United States)

Chen, Xiao; Lu, Bin; Yan, Chao-Gan

2018-01-01

Concerns regarding reproducibility of resting-state functional magnetic resonance imaging (R-fMRI) findings have been raised. Little is known about how to operationally define R-fMRI reproducibility and to what extent it is affected by multiple comparison correction strategies and sample size. We comprehensively assessed two aspects of reproducibility, test-retest reliability and replicability, on widely used R-fMRI metrics in both between-subject contrasts of sex differences and within-subject comparisons of eyes-open and eyes-closed (EOEC) conditions. We noted permutation test with Threshold-Free Cluster Enhancement (TFCE), a strict multiple comparison correction strategy, reached the best balance between family-wise error rate (under 5%) and test-retest reliability/replicability (e.g., 0.68 for test-retest reliability and 0.25 for replicability of amplitude of low-frequency fluctuations (ALFF) for between-subject sex differences, 0.49 for replicability of ALFF for within-subject EOEC differences). Although R-fMRI indices attained moderate reliabilities, they replicated poorly in distinct datasets (replicability < 0.3 for between-subject sex differences, < 0.5 for within-subject EOEC differences). By randomly drawing different sample sizes from a single site, we found reliability, sensitivity and positive predictive value (PPV) rose as sample size increased. Small sample sizes (e.g., < 80 [40 per group]) not only minimized power (sensitivity < 2%), but also decreased the likelihood that significant results reflect "true" effects (PPV < 0.26) in sex differences. Our findings have implications for how to select multiple comparison correction strategies and highlight the importance of sufficiently large sample sizes in R-fMRI studies to enhance reproducibility. Hum Brain Mapp 39:300-318, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identifying the node spreading influence with largest k-core values

International Nuclear Information System (INIS)

Lin, Jian-Hong; Guo, Qiang; Dong, Wen-Zhao; Tang, Li-Ying; Liu, Jian-Guo

2014-01-01

Identifying the nodes with largest spreading influence of complex networks is one of the most promising domains. By taking into account the neighbors' k-core values, we present an improved neighbors' k-core (INK) method which is the sum of the neighbors' k-core values with a tunable parameter α to evaluate the node spreading influence with largest k-core values. Comparing with the Susceptible–Infected–Recovered (SIR) results for four real networks, the INK method could identify the node spreading influence with largest k-core values more accurately than the ones generated by the degree k, closeness C, betweenness B and coreness centrality method. - Highlights: • We present an improved neighbors' k-core (INK) method to evaluate the node spreading influence with largest k-core values. • The INK method could identify the node spreading influence with largest k-core values more accurately. • Kendall's tau τ of INK method with α=1 are highly identical to rank the node influence

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.

Effect of Mechanical Impact Energy on the Sorption and Diffusion of Moisture in Reinforced Polymer Composite Samples on Variation of Their Sizes

Science.gov (United States)

Startsev, V. O.; Il'ichev, A. V.

2018-05-01

The effect of mechanical impact energy on the sorption and diffusion of moisture in polymer composite samples on variation of their sizes was investigated. Square samples, with sides of 40, 60, 80, and 100 mm, made of a KMKU-2m-120.E0,1 carbon-fiber and KMKS-2m.120.T10 glass-fiber plastics with different resistances to calibrated impacts, were compared. Impact loading diagrams of the samples in relation to their sizes and impact energy were analyzed. It is shown that the moisture saturation and moisture diffusion coefficient of the impact-damaged materials can be modeled by Fick's second law with account of impact energy and sample sizes.

Size of the great white shark (carcharodon).

Science.gov (United States)

Randall, J E

1973-07-13

The maximum length of 36.5 feet (11.1 meters) attributed to the white shark (Carcharodon carcharias) by Günther and others is a mistake. Examination of the jaws and teeth of the specimen referred to by Günther and comparison with the jaws of white sharks of known length revealed a length of about 17 feet ( approximately 5 meters). The largest white shark reliably measured was a 21-foot (6.4-meter) individual from Cuba. Bites on whale carcasses found off southern Australia suggest that white sharks as long as 25 or 26 feet (7 (1/2) or 8 meters) exist today. The size of extinct Carcharodon has also been grossly exaggerated. Based on a projection of a curve of tooth size of Recent Carcharodon carcharias, the largest fossil Carcharodon were about 43 feet ( approximately 13 meters) long.

Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look.

Science.gov (United States)

Graf, Alexandra C; Bauer, Peter

2011-06-30

We calculate the maximum type 1 error rate of the pre-planned conventional fixed sample size test for comparing the means of independent normal distributions (with common known variance) which can be yielded when sample size and allocation rate to the treatment arms can be modified in an interim analysis. Thereby it is assumed that the experimenter fully exploits knowledge of the unblinded interim estimates of the treatment effects in order to maximize the conditional type 1 error rate. The 'worst-case' strategies require knowledge of the unknown common treatment effect under the null hypothesis. Although this is a rather hypothetical scenario it may be approached in practice when using a standard control treatment for which precise estimates are available from historical data. The maximum inflation of the type 1 error rate is substantially larger than derived by Proschan and Hunsberger (Biometrics 1995; 51:1315-1324) for design modifications applying balanced samples before and after the interim analysis. Corresponding upper limits for the maximum type 1 error rate are calculated for a number of situations arising from practical considerations (e.g. restricting the maximum sample size, not allowing sample size to decrease, allowing only increase in the sample size in the experimental treatment). The application is discussed for a motivating example. Copyright © 2011 John Wiley & Sons, Ltd.

Long-term resource variation and group size: A large-sample field test of the Resource Dispersion Hypothesis

Directory of Open Access Journals (Sweden)

Morecroft Michael D

2001-07-01

Full Text Available Abstract Background The Resource Dispersion Hypothesis (RDH proposes a mechanism for the passive formation of social groups where resources are dispersed, even in the absence of any benefits of group living per se. Despite supportive modelling, it lacks empirical testing. The RDH predicts that, rather than Territory Size (TS increasing monotonically with Group Size (GS to account for increasing metabolic needs, TS is constrained by the dispersion of resource patches, whereas GS is independently limited by their richness. We conducted multiple-year tests of these predictions using data from the long-term study of badgers Meles meles in Wytham Woods, England. The study has long failed to identify direct benefits from group living and, consequently, alternative explanations for their large group sizes have been sought. Results TS was not consistently related to resource dispersion, nor was GS consistently related to resource richness. Results differed according to data groupings and whether territories were mapped using minimum convex polygons or traditional methods. Habitats differed significantly in resource availability, but there was also evidence that food resources may be spatially aggregated within habitat types as well as between them. Conclusions This is, we believe, the largest ever test of the RDH and builds on the long-term project that initiated part of the thinking behind the hypothesis. Support for predictions were mixed and depended on year and the method used to map territory borders. We suggest that within-habitat patchiness, as well as model assumptions, should be further investigated for improved tests of the RDH in the future.

Day and night variation in chemical composition and toxicological responses of size segregated urban air PM samples in a high air pollution situation

Science.gov (United States)

Jalava, P. I.; Wang, Q.; Kuuspalo, K.; Ruusunen, J.; Hao, L.; Fang, D.; Väisänen, O.; Ruuskanen, A.; Sippula, O.; Happo, M. S.; Uski, O.; Kasurinen, S.; Torvela, T.; Koponen, H.; Lehtinen, K. E. J.; Komppula, M.; Gu, C.; Jokiniemi, J.; Hirvonen, M.-R.

2015-11-01

Urban air particulate pollution is a known cause for adverse human health effects worldwide. China has encountered air quality problems in recent years due to rapid industrialization. Toxicological effects induced by particulate air pollution vary with particle sizes and season. However, it is not known how distinctively different photochemical activity and different emission sources during the day and the night affect the chemical composition of the PM size ranges and subsequently how it is reflected to the toxicological properties of the PM exposures. The particulate matter (PM) samples were collected in four different size ranges (PM10-2.5; PM2.5-1; PM1-0.2 and PM0.2) with a high volume cascade impactor. The PM samples were extracted with methanol, dried and thereafter used in the chemical and toxicological analyses. RAW264.7 macrophages were exposed to the particulate samples in four different doses for 24 h. Cytotoxicity, inflammatory parameters, cell cycle and genotoxicity were measured after exposure of the cells to particulate samples. Particles were characterized for their chemical composition, including ions, element and PAH compounds, and transmission electron microscopy (TEM) was used to take images of the PM samples. Chemical composition and the induced toxicological responses of the size segregated PM samples showed considerable size dependent differences as well as day to night variation. The PM10-2.5 and the PM0.2 samples had the highest inflammatory potency among the size ranges. Instead, almost all the PM samples were equally cytotoxic and only minor differences were seen in genotoxicity and cell cycle effects. Overall, the PM0.2 samples had the highest toxic potential among the different size ranges in many parameters. PAH compounds in the samples and were generally more abundant during the night than the day, indicating possible photo-oxidation of the PAH compounds due to solar radiation. This was reflected to different toxicity in the PM

Dental size variation in the Atapuerca-SH Middle Pleistocene hominids.

Science.gov (United States)

Bermúdez de Castro, J M; Sarmiento, S; Cunha, E; Rosas, A; Bastir, M

2001-09-01

The Middle Pleistocene Atapuerca-Sima de los Huesos (SH) site in Spain has yielded the largest sample of fossil hominids so far found from a single site and belonging to the same biological population. The SH dental sample includes a total of 452 permanent and deciduous teeth, representing a minimum of 27 individuals. We present a study of the dental size variation in these hominids, based on the analysis of the mandibular permanent dentition: lateral incisors, n=29; canines, n=27; third premolars, n=30; fourth premolars, n=34; first molars, n=38; second molars, n=38. We have obtained the buccolingual diameter and the crown area (measured on occlusal photographs) of these teeth, and used the bootstrap method to assess the amount of variation in the SH sample compared with the variation of a modern human sample from the Museu Antropologico of the Universidade of Coimbra (Portugal). The SH hominids have, in general terms, a dental size variation higher than that of the modern human sample. The analysis is especially conclusive for the canines. Furthermore, we have estimated the degree of sexual dimorphism of the SH sample by obtaining male and female dental subsamples by means of sexing the large sample of SH mandibular specimens. We obtained the index of sexual dimorphism (ISD=male mean/female mean) and the values were compared with those obtained from the sexed modern human sample from Coimbra, and with data found in the literature concerning several recent human populations. In all tooth classes the ISD of the SH hominids was higher than that of modern humans, but the differences were generally modest, except for the canines, thus suggesting that canine size sexual dimorphism in Homo heidelbergensis was probably greater than that of modern humans. Since the approach of sexing fossil specimens has some obvious limitations, these results should be assessed with caution. Additional data from SH and other European Middle Pleistocene sites would be necessary to test

CERN tests largest superconducting solenoid magnet

CERN Multimedia

2006-01-01

"CERN's Compacts Muon Solenoid (CMS) - the world's largest superconducting solenoid magnet - has reached full field in testing. The instrument is part of the proton-proton Large Hadron Collider (LHC) project, located in a giant subterranean chamber at Cessy on the Franco-Swiss border." (1 page)

Understanding the cluster randomised crossover design: a graphical illustraton of the components of variation and a sample size tutorial.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Hemming, Karla; Pilcher, David; Forbes, Andrew B

2017-08-15

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of

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.

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

Science.gov (United States)

Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A

2013-01-01

Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall pdecrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.

Sauropod dinosaurs evolved moderately sized genomes unrelated to body size.

Science.gov (United States)

Organ, Chris L; Brusatte, Stephen L; Stein, Koen

2009-12-22

Sauropodomorph dinosaurs include the largest land animals to have ever lived, some reaching up to 10 times the mass of an African elephant. Despite their status defining the upper range for body size in land animals, it remains unknown whether sauropodomorphs evolved larger-sized genomes than non-avian theropods, their sister taxon, or whether a relationship exists between genome size and body size in dinosaurs, two questions critical for understanding broad patterns of genome evolution in dinosaurs. Here we report inferences of genome size for 10 sauropodomorph taxa. The estimates are derived from a Bayesian phylogenetic generalized least squares approach that generates posterior distributions of regression models relating genome size to osteocyte lacunae volume in extant tetrapods. We estimate that the average genome size of sauropodomorphs was 2.02 pg (range of species means: 1.77-2.21 pg), a value in the upper range of extant birds (mean = 1.42 pg, range: 0.97-2.16 pg) and near the average for extant non-avian reptiles (mean = 2.24 pg, range: 1.05-5.44 pg). The results suggest that the variation in size and architecture of genomes in extinct dinosaurs was lower than the variation found in mammals. A substantial difference in genome size separates the two major clades within dinosaurs, Ornithischia (large genomes) and Saurischia (moderate to small genomes). We find no relationship between body size and estimated genome size in extinct dinosaurs, which suggests that neutral forces did not dominate the evolution of genome size in this group.

Fruit size and sampling sites affect on dormancy, viability and germination of teak (Tectona grandis L.) seeds

International Nuclear Information System (INIS)

Akram, M.; Aftab, F.

2016-01-01

In the present study, fruits (drupes) were collected from Changa Manga Forest Plus Trees (CMF-PT), Changa Manga Forest Teak Stand (CMF-TS) and Punjab University Botanical Gardens (PUBG) and categorized into very large (= 17 mm dia.), large (12-16 mm dia.), medium (9-11 mm dia.) or small (6-8 mm dia.) fruit size grades. Fresh water as well as mechanical scarification and stratification were tested for breaking seed dormancy. Viability status of seeds was estimated by cutting test, X-rays and In vitro seed germination. Out of 2595 fruits from CMF-PT, 500 fruits were of very large grade. This fruit category also had highest individual fruit weight (0.58 g) with more number of 4-seeded fruits (5.29 percent) and fair germination potential (35.32 percent). Generally, most of the fruits were 1-seeded irrespective of size grades and sampling sites. Fresh water scarification had strong effect on germination (44.30 percent) as compared to mechanical scarification and cold stratification after 40 days of sowing. Similarly, sampling sites and fruit size grades also had significant influence on germination. Highest germination (82.33 percent) was obtained on MS (Murashige and Skoog) agar-solidified medium as compared to Woody Plant Medium (WPM) (69.22 percent). Seedlings from all the media were transferred to ex vitro conditions in the greenhouse and achieved highest survival (28.6 percent) from seedlings previously raised on MS agar-solidified medium after 40 days. There was an association between the studied parameters of teak seeds and the sampling sites and fruit size. (author)

Sample-size resonance, ferromagnetic resonance and magneto-permittivity resonance in multiferroic nano-BiFeO3/paraffin composites at room temperature

International Nuclear Information System (INIS)

Wang, Lei; Li, Zhenyu; Jiang, Jia; An, Taiyu; Qin, Hongwei; Hu, Jifan

2017-01-01

In the present work, we demonstrate that ferromagnetic resonance and magneto-permittivity resonance can be observed in appropriate microwave frequencies at room temperature for multiferroic nano-BiFeO 3 /paraffin composite sample with an appropriate sample-thickness (such as 2 mm). Ferromagnetic resonance originates from the room-temperature weak ferromagnetism of nano-BiFeO 3 . The observed magneto-permittivity resonance in multiferroic nano-BiFeO 3 is connected with the dynamic magnetoelectric coupling through Dzyaloshinskii–Moriya (DM) magnetoelectric interaction or the combination of magnetostriction and piezoelectric effects. In addition, we experimentally observed the resonance of negative imaginary permeability for nano BiFeO 3 /paraffin toroidal samples with longer sample thicknesses D=3.7 and 4.9 mm. Such resonance of negative imaginary permeability belongs to sample-size resonance. - Highlights: • Nano-BiFeO 3 /paraffin composite shows a ferromagnetic resonance. • Nano-BiFeO 3 /paraffin composite shows a magneto-permittivity resonance. • Resonance of negative imaginary permeability in BiFeO 3 is a sample-size resonance. • Nano-BiFeO 3 /paraffin composite with large thickness shows a sample-size resonance.

The Effect of Sterilization on Size and Shape of Fat Globules in Model Processed Cheese Samples

Directory of Open Access Journals (Sweden)

B. Tremlová

2006-01-01

Full Text Available Model cheese samples from 4 independent productions were heat sterilized (117 °C, 20 minutes after the melting process and packing with an aim to prolong their durability. The objective of the study was to assess changes in the size and shape of fat globules due to heat sterilization by using image analysis methods. The study included a selection of suitable methods of preparation mounts, taking microphotographs and making overlays for automatic processing of photographs by image analyser, ascertaining parameters to determine the size and shape of fat globules and statistical analysis of results obtained. The results of the experiment suggest that changes in shape of fat globules due to heat sterilization are not unequivocal. We found that the size of fat globules was significantly increased (p < 0.01 due to heat sterilization (117 °C, 20 min, and the shares of small fat globules (up to 500 μm2, or 100 μm2 in the samples of heat sterilized processed cheese were decreased. The results imply that the image analysis method is very useful when assessing the effect of technological process on the quality of processed cheese quality.

Natural radionuclides in soil profiles surrounding the largest coal-fired power plant in Serbia

OpenAIRE

Tanić Milan N.; Janković-Mandić Ljiljana J.; Gajić Boško A.; Daković Marko Z.; Dragović Snežana D.; Bačić Goran G.

2016-01-01

This study evaluates the influence of the largest Serbian coal-fired power plant on radionuclide concentrations in soil profiles up to 50 cm in depth. Thirty soil profiles were sampled from the plant surroundings (up to 10 km distance) and analyzed using standard methods for soil physicochemical properties and gamma ray spectrometry for specific activities of natural radionuclides (40K, 226Ra and 232Th). Spatial and vertical distribution of radionuclides wa...

Sampling bee communities using pan traps: alternative methods increase sample size

Science.gov (United States)

Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...

Measurements of Plutonium and Americium in Soil Samples from Project 57 using the Suspended Soil Particle Sizing System (SSPSS)

International Nuclear Information System (INIS)

John L. Bowen; Rowena Gonzalez; David S. Shafer

2001-01-01

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

Influence of secular trends and sample size on reference equations for lung function tests.

Science.gov (United States)

Quanjer, P H; Stocks, J; Cole, T J; Hall, G L; Stanojevic, S

2011-03-01

The aim of our study was to determine the contribution of secular trends and sample size to lung function reference equations, and establish the number of local subjects required to validate published reference values. 30 spirometry datasets collected between 1978 and 2009 provided data on healthy, white subjects: 19,291 males and 23,741 females aged 2.5-95 yrs. The best fit for forced expiratory volume in 1 s (FEV(1)), forced vital capacity (FVC) and FEV(1)/FVC as functions of age, height and sex were derived from the entire dataset using GAMLSS. Mean z-scores were calculated for individual datasets to determine inter-centre differences. This was repeated by subdividing one large dataset (3,683 males and 4,759 females) into 36 smaller subsets (comprising 18-227 individuals) to preclude differences due to population/technique. No secular trends were observed and differences between datasets comprising >1,000 subjects were small (maximum difference in FEV(1) and FVC from overall mean: 0.30- -0.22 z-scores). Subdividing one large dataset into smaller subsets reproduced the above sample size-related differences and revealed that at least 150 males and 150 females would be necessary to validate reference values to avoid spurious differences due to sampling error. Use of local controls to validate reference equations will rarely be practical due to the numbers required. Reference equations derived from large or collated datasets are recommended.

Analysis of Human Standing Balance by Largest Lyapunov Exponent

Directory of Open Access Journals (Sweden)

Kun Liu

2015-01-01

Full Text Available The purpose of this research is to analyse the relationship between nonlinear dynamic character and individuals’ standing balance by the largest Lyapunov exponent, which is regarded as a metric for assessing standing balance. According to previous study, the largest Lyapunov exponent from centre of pressure time series could not well quantify the human balance ability. In this research, two improvements were made. Firstly, an external stimulus was applied to feet in the form of continuous horizontal sinusoidal motion by a moving platform. Secondly, a multiaccelerometer subsystem was adopted. Twenty healthy volunteers participated in this experiment. A new metric, coordinated largest Lyapunov exponent was proposed, which reflected the relationship of body segments by integrating multidimensional largest Lyapunov exponent values. By using this metric in actual standing performance under sinusoidal stimulus, an obvious relationship between the new metric and the actual balance ability was found in the majority of the subjects. These results show that the sinusoidal stimulus can make human balance characteristics more obvious, which is beneficial to assess balance, and balance is determined by the ability of coordinating all body segments.

Plasticity in sexual size dimorphism and Rensch's rule in Mediterranean blennies (Blenniidae)

NARCIS (Netherlands)

Lengkeek, W.; Didderen, K.; Cote, I. M.; van der Zee, E. M.; Snoek, R. C.; Reynolds, J. D.

2008-01-01

Comparative analyses of sexual size dimorphism (SSD) across species have led to the discovery of Rensch's rule. This rule states that SSD increases with body size when males are the largest sex, but decreases with increasing size when females are larger. Within-species comparisons of SSD in fish are

On the Importance of Accounting for Competing Risks in Pediatric Brain Cancer: II. Regression Modeling and Sample Size

International Nuclear Information System (INIS)

Tai, Bee-Choo; Grundy, Richard; Machin, David

2011-01-01

Purpose: To accurately model the cumulative need for radiotherapy in trials designed to delay or avoid irradiation among children with malignant brain tumor, it is crucial to account for competing events and evaluate how each contributes to the timing of irradiation. An appropriate choice of statistical model is also important for adequate determination of sample size. Methods and Materials: We describe the statistical modeling of competing events (A, radiotherapy after progression; B, no radiotherapy after progression; and C, elective radiotherapy) using proportional cause-specific and subdistribution hazard functions. The procedures of sample size estimation based on each method are outlined. These are illustrated by use of data comparing children with ependymoma and other malignant brain tumors. The results from these two approaches are compared. Results: The cause-specific hazard analysis showed a reduction in hazards among infants with ependymoma for all event types, including Event A (adjusted cause-specific hazard ratio, 0.76; 95% confidence interval, 0.45-1.28). Conversely, the subdistribution hazard analysis suggested an increase in hazard for Event A (adjusted subdistribution hazard ratio, 1.35; 95% confidence interval, 0.80-2.30), but the reduction in hazards for Events B and C remained. Analysis based on subdistribution hazard requires a larger sample size than the cause-specific hazard approach. Conclusions: Notable differences in effect estimates and anticipated sample size were observed between methods when the main event showed a beneficial effect whereas the competing events showed an adverse effect on the cumulative incidence. The subdistribution hazard is the most appropriate for modeling treatment when its effects on both the main and competing events are of interest.

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

Science.gov (United States)

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

Two to five repeated measurements per patient reduced the required sample size considerably in a randomized clinical trial for patients with inflammatory rheumatic diseases

Directory of Open Access Journals (Sweden)

Smedslund Geir

2013-02-01

Full Text Available Abstract Background Patient reported outcomes are accepted as important outcome measures in rheumatology. The fluctuating symptoms in patients with rheumatic diseases have serious implications for sample size in clinical trials. We estimated the effects of measuring the outcome 1-5 times on the sample size required in a two-armed trial. Findings In a randomized controlled trial that evaluated the effects of a mindfulness-based group intervention for patients with inflammatory arthritis (n=71, the outcome variables Numerical Rating Scales (NRS (pain, fatigue, disease activity, self-care ability, and emotional wellbeing and General Health Questionnaire (GHQ-20 were measured five times before and after the intervention. For each variable we calculated the necessary sample sizes for obtaining 80% power (α=.05 for one up to five measurements. Two, three, and four measures reduced the required sample sizes by 15%, 21%, and 24%, respectively. With three (and five measures, the required sample size per group was reduced from 56 to 39 (32 for the GHQ-20, from 71 to 60 (55 for pain, 96 to 71 (73 for fatigue, 57 to 51 (48 for disease activity, 59 to 44 (45 for self-care, and 47 to 37 (33 for emotional wellbeing. Conclusions Measuring the outcomes five times rather than once reduced the necessary sample size by an average of 27%. When planning a study, researchers should carefully compare the advantages and disadvantages of increasing sample size versus employing three to five repeated measurements in order to obtain the required statistical power.

Sampling considerations when analyzing micrometric-sized particles in a liquid jet using laser induced breakdown spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Faye, C.B.; Amodeo, T.; Fréjafon, E. [Institut National de l' Environnement Industriel et des Risques (INERIS/DRC/CARA/NOVA), Parc Technologique Alata, BP 2, 60550 Verneuil-En-Halatte (France); Delepine-Gilon, N. [Institut des Sciences Analytiques, 5 rue de la Doua, 69100 Villeurbanne (France); Dutouquet, C., E-mail: christophe.dutouquet@ineris.fr [Institut National de l' Environnement Industriel et des Risques (INERIS/DRC/CARA/NOVA), Parc Technologique Alata, BP 2, 60550 Verneuil-En-Halatte (France)

2014-01-01

Pollution of water is a matter of concern all over the earth. Particles are known to play an important role in the transportation of pollutants in this medium. In addition, the emergence of new materials such as NOAA (Nano-Objects, their Aggregates and their Agglomerates) emphasizes the need to develop adapted instruments for their detection. Surveillance of pollutants in particulate form in waste waters in industries involved in nanoparticle manufacturing and processing is a telling example of possible applications of such instrumental development. The LIBS (laser-induced breakdown spectroscopy) technique coupled with the liquid jet as sampling mode for suspensions was deemed as a potential candidate for on-line and real time monitoring. With the final aim in view to obtain the best detection limits, the interaction of nanosecond laser pulses with the liquid jet was examined. The evolution of the volume sampled by laser pulses was estimated as a function of the laser energy applying conditional analysis when analyzing a suspension of micrometric-sized particles of borosilicate glass. An estimation of the sampled depth was made. Along with the estimation of the sampled volume, the evolution of the SNR (signal to noise ratio) as a function of the laser energy was investigated as well. Eventually, the laser energy and the corresponding fluence optimizing both the sampling volume and the SNR were determined. The obtained results highlight intrinsic limitations of the liquid jet sampling mode when using 532 nm nanosecond laser pulses with suspensions. - Highlights: • Micrometric-sized particles in suspensions are analyzed using LIBS and a liquid jet. • The evolution of the sampling volume is estimated as a function of laser energy. • The sampling volume happens to saturate beyond a certain laser fluence. • Its value was found much lower than the beam diameter times the jet thickness. • Particles proved not to be entirely vaporized.

14C-labeled organic amendments: Characterization in different particle size fractions and humic acids in a long-term field experiment.

Science.gov (United States)

Tatzber, Michael; Stemmer, Michael; Spiegel, Heide; Katzlberger, Christian; Landstetter, Claudia; Haberhauer, Georg; Gerzabek, Martin H

2012-05-01

Knowledge about the stabilization of organic matter input to soil is essential for understanding the influence of different agricultural practices on turnover characteristics in agricultural soil systems. In this study, soil samples from a long-term field experiment were separated into silt- and clay-sized particles. In 1967, 14 C labeled farmyard manure was applied to three different cropping systems: crop rotation, monoculture and permanent bare fallow. Humic acids (HAs) were extracted from silt- and clay-sized fractions and characterized using photometry, mid-infrared and fluorescence spectroscopy. Remaining 14 C was determined in size fractions as well as in their extracted HAs. Yields of carbon and remaining 14 C in HAs from silt-sized particles and C org in clay-sized particles decreased significantly in the order: crop rotation > monoculture ≫ bare fallow. Thus, crop rotation not only had the largest overall C-pool in the experiment, but it also best stabilized the added manure. Mid-infrared spectroscopy could distinguish between HAs from different particle size soil fractions. With spectroscopic methods significant differences between the cropping systems were detectable in fewer cases compared to quantitative results of HAs (yields, 14 C, C org and N t ). The trends, however, pointed towards increased humification of HAs from bare fallow systems compared to crop rotation and monoculture as well as of HAs from clay-sized particles compared to silt-sized particles. Our study clearly shows that the largest differences were observed between bare fallow on one hand and monoculture and crop rotation on the other.

Droplet Size-Aware and Error-Correcting Sample Preparation Using Micro-Electrode-Dot-Array Digital Microfluidic Biochips.

Science.gov (United States)

Li, Zipeng; Lai, Kelvin Yi-Tse; Chakrabarty, Krishnendu; Ho, Tsung-Yi; Lee, Chen-Yi

2017-12-01

Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for on-chip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain two major problems associated with sample preparation on a conventional DMFB. First, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. Second, only a limited number of sensors can be integrated on a conventional DMFB; as a result, the latency for error detection during sample preparation is significant. To overcome these drawbacks, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (MEDA), for sample preparation. We propose the first sample-preparation method that exploits the MEDA-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated MEDA biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.

A behavioral Bayes method to determine the sample size of a clinical trial considering efficacy and safety.

Science.gov (United States)

Kikuchi, Takashi; Gittins, John

2009-08-15

It is necessary for the calculation of sample size to achieve the best balance between the cost of a clinical trial and the possible benefits from a new treatment. Gittins and Pezeshk developed an innovative (behavioral Bayes) approach, which assumes that the number of users is an increasing function of the difference in performance between the new treatment and the standard treatment. The better a new treatment, the more the number of patients who want to switch to it. The optimal sample size is calculated in this framework. This BeBay approach takes account of three decision-makers, a pharmaceutical company, the health authority and medical advisers. Kikuchi, Pezeshk and Gittins generalized this approach by introducing a logistic benefit function, and by extending to the more usual unpaired case, and with unknown variance. The expected net benefit in this model is based on the efficacy of the new drug but does not take account of the incidence of adverse reactions. The present paper extends the model to include the costs of treating adverse reactions and focuses on societal cost-effectiveness as the criterion for determining sample size. The main application is likely to be to phase III clinical trials, for which the primary outcome is to compare the costs and benefits of a new drug with a standard drug in relation to national health-care. Copyright 2009 John Wiley & Sons, Ltd.

Approaching the largest ‘API’: extracting information from the Internet with Python

Directory of Open Access Journals (Sweden)

Jonathan E. Germann

2018-02-01

Full Text Available This article explores the need for libraries to algorithmically access and manipulate the world’s largest API: the Internet. The billions of pages on the ‘Internet API’ (HTTP, HTML, CSS, XPath, DOM, etc. are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.

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.

Hospital Prices Increase in California, Especially Among Hospitals in the Largest Multi-hospital Systems

Directory of Open Access Journals (Sweden)

Glenn A. Melnick PhD

2016-06-01

Full Text Available A surge in hospital consolidation is fueling formation of ever larger multi-hospital systems throughout the United States. This article examines hospital prices in California over time with a focus on hospitals in the largest multi-hospital systems. Our data show that hospital prices in California grew substantially (+76% per hospital admission across all hospitals and all services between 2004 and 2013 and that prices at hospitals that are members of the largest, multi-hospital systems grew substantially more (113% than prices paid to all other California hospitals (70%. Prices were similar in both groups at the start of the period (approximately $9200 per admission. By the end of the period, prices at hospitals in the largest systems exceeded prices at other California hospitals by almost $4000 per patient admission. Our study findings are potentially useful to policy makers across the country for several reasons. Our data measure actual prices for a large sample of hospitals over a long period of time in California. California experienced its wave of consolidation much earlier than the rest of the country and as such our findings may provide some insights into what may happen across the United States from hospital consolidation including growth of large, multi-hospital systems now forming in the rest of the rest of the country.

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

The Effects of Test Length and Sample Size on Item Parameters in Item Response Theory

Science.gov (United States)

Sahin, Alper; Anil, Duygu

2017-01-01

This study investigates the effects of sample size and test length on item-parameter estimation in test development utilizing three unidimensional dichotomous models of item response theory (IRT). For this purpose, a real language test comprised of 50 items was administered to 6,288 students. Data from this test was used to obtain data sets of…

Influence of pH, Temperature and Sample Size on Natural and Enforced Syneresis of Precipitated Silica

Directory of Open Access Journals (Sweden)

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.

Optimum sample length for estimating anchovy size distribution and the proportion of juveniles per fishing set for the Peruvian purse-seine fleet

Directory of Open Access Journals (Sweden)

Rocío Joo

2017-04-01

Full Text Available The length distribution of catches represents a fundamental source of information for estimating growth and spatio-temporal dynamics of cohorts. The length distribution of caught is estimated based on samples of catched individuals. This work studies the optimum sample size of individuals at each fishing set in order to obtain a representative sample of the length and the proportion of juveniles in the fishing set. For that matter, we use anchovy (Engraulis ringens length data from different fishing sets recorded by observers at-sea from the On-board Observers Program from the Peruvian Marine Research Institute. Finally, we propose an optimum sample size for obtaining robust size and juvenile estimations. Though the application of this work corresponds to the anchovy fishery, the procedure can be applied to any fishery, either for on board or inland biometric measurements.

(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research

NARCIS (Netherlands)

van Rijnsoever, Frank J.

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in

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

International Nuclear Information System (INIS)

Lisboa-Filho, P N; Deimling, C V; Ortiz, W A

2010-01-01

In this contribution superconducting specimens of YBa 2 Cu 3 O 7-δ 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.

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.

Sample-size resonance, ferromagnetic resonance and magneto-permittivity resonance in multiferroic nano-BiFeO{sub 3}/paraffin composites at room temperature

Energy Technology Data Exchange (ETDEWEB)

Wang, Lei; Li, Zhenyu; Jiang, Jia; An, Taiyu; Qin, Hongwei; Hu, Jifan, E-mail: hujf@sdu.edu.cn

2017-01-01

In the present work, we demonstrate that ferromagnetic resonance and magneto-permittivity resonance can be observed in appropriate microwave frequencies at room temperature for multiferroic nano-BiFeO{sub 3}/paraffin composite sample with an appropriate sample-thickness (such as 2 mm). Ferromagnetic resonance originates from the room-temperature weak ferromagnetism of nano-BiFeO{sub 3}. The observed magneto-permittivity resonance in multiferroic nano-BiFeO{sub 3} is connected with the dynamic magnetoelectric coupling through Dzyaloshinskii–Moriya (DM) magnetoelectric interaction or the combination of magnetostriction and piezoelectric effects. In addition, we experimentally observed the resonance of negative imaginary permeability for nano BiFeO{sub 3}/paraffin toroidal samples with longer sample thicknesses D=3.7 and 4.9 mm. Such resonance of negative imaginary permeability belongs to sample-size resonance. - Highlights: • Nano-BiFeO{sub 3}/paraffin composite shows a ferromagnetic resonance. • Nano-BiFeO{sub 3}/paraffin composite shows a magneto-permittivity resonance. • Resonance of negative imaginary permeability in BiFeO{sub 3} is a sample-size resonance. • Nano-BiFeO{sub 3}/paraffin composite with large thickness shows a sample-size resonance.

Reducing sample size by combining superiority and non-inferiority for two primary endpoints in the Social Fitness study.

Science.gov (United States)

Donkers, Hanneke; Graff, Maud; Vernooij-Dassen, Myrra; Nijhuis-van der Sanden, Maria; Teerenstra, Steven

2017-01-01

In randomized controlled trials, two endpoints may be necessary to capture the multidimensional concept of the intervention and the objectives of the study adequately. We show how to calculate sample size when defining success of a trial by combinations of superiority and/or non-inferiority aims for the endpoints. The randomized controlled trial design of the Social Fitness study uses two primary endpoints, which can be combined into five different scenarios for defining success of the trial. We show how to calculate power and sample size for each scenario and compare these for different settings of power of each endpoint and correlation between them. Compared to a single primary endpoint, using two primary endpoints often gives more power when success is defined as: improvement in one of the two endpoints and no deterioration in the other. This also gives better power than when success is defined as: improvement in one prespecified endpoint and no deterioration in the remaining endpoint. When two primary endpoints are equally important, but a positive effect in both simultaneously is not per se required, the objective of having one superior and the other (at least) non-inferior could make sense and reduce sample size. Copyright © 2016 Elsevier Inc. All rights reserved.

Causes and Consequences of Ownership Concentration among Europe´s Largest Companies: Economic and Systemic Explanations

DEFF Research Database (Denmark)

Pedersen, Torben; Thomsen, Steen

1999-01-01

The paper examines causes and effects of ownership concentration among the largest companies in 12 European countries. As a reference point the paper takes a seminal empirical study on US data by Demsetz and Lehn (1985) and examines to what extent their model is applicable in European countries....... The findings indicate that both general economic effects and system effects are significant. Ownership concentration is found to decrease with firm size and to increase with earnings volatility. But in support of the system theories advocated by Roe (1991), Laporta et al. (1996) and Shleifer and Vishny (1997......) nationality is also found to have a significant effect which is partly attributable to institutional differences between nations such as stock market size and the frequency of large banks. Finally, in line with Demsetz and Lehn (1985), ownership concentration is found to have an insignificant effect...

Effect of the grain size of the soil on the measured activity and variation in activity in surface and subsurface soil samples

International Nuclear Information System (INIS)

Sulaiti, H.A.; Rega, P.H.; Bradley, D.; Dahan, N.A.; Mugren, K.A.; Dosari, M.A.

2014-01-01

Correlation between grain size and activity concentrations of soils and concentrations of various radionuclides in surface and subsurface soils has been measured for samples taken in the State of Qatar by gamma-spectroscopy using a high purity germanium detector. From the obtained gamma-ray spectra, the activity concentrations of the 238U (226Ra) and /sup 232/ Th (/sup 228/ Ac) natural decay series, the long-lived naturally occurring radionuclide 40 K and the fission product radionuclide 137CS have been determined. Gamma dose rate, radium equivalent, radiation hazard index and annual effective dose rates have also been estimated from these data. In order to observe the effect of grain size on the radioactivity of soil, three grain sizes were used i.e., smaller than 0.5 mm; smaller than 1 mm and greater than 0.5 mm; and smaller than 2 mm and greater than 1 mm. The weighted activity concentrations of the 238U series nuclides in 0.5-2 mm grain size of sample numbers was found to vary from 2.5:f:0.2 to 28.5+-0.5 Bq/kg, whereas, the weighted activity concentration of 4 degree K varied from 21+-4 to 188+-10 Bq/kg. The weighted activity concentrations of 238U series and 4 degree K have been found to be higher in the finest grain size. However, for the 232Th series, the activity concentrations in the 1-2 mm grain size of one sample were found to be higher than in the 0.5-1 mm grain size. In the study of surface and subsurface soil samples, the activity concentration levels of 238 U series have been found to range from 15.9+-0.3 to 24.1+-0.9 Bq/kg, in the surface soil samples (0-5 cm) and 14.5+-0.3 to 23.6+-0.5 Bq/kg in the subsurface soil samples (5-25 cm). The activity concentrations of 232Th series have been found to lie in the range 5.7+-0.2 to 13.7+-0.5 Bq/kg, in the surface soil samples (0-5 cm)and 4.1+-0.2 to 15.6+-0.3 Bq/kg in the subsurface soil samples (5-25 cm). The activity concentrations of 4 degree K were in the range 150+-8 to 290+-17 Bq/kg, in the surface

broken magnet highlights largest collider's engineering challenges

CERN Multimedia

Inman, Mason

2007-01-01

"Even at the world's soon-to-be largest particle accelerator - a device that promises to push the boundaries of physics - scientists need to be mindful of one of the most fundamental laws in the universe: Murphy's Law. (2 pages)

Determinants of polyp Size in patients undergoing screening colonoscopy

Directory of Open Access Journals (Sweden)

Maisonneuve Patrick

2011-09-01

Full Text Available Abstract Background Pre-existing polyps, especially large polyps, are known to be the major source for colorectal cancer, but there is limited available information about factors that are associated with polyp size and polyp growth. We aim to determine factors associated with polyp size in different age groups. Methods Colonoscopy data were prospectively collected from 67 adult gastrointestinal practice sites in the United States between 2002 and 2007 using a computer-generated endoscopic report form. Data were transmitted to and stored in a central data repository, where all asymptomatic white (n = 78352 and black (n = 4289 patients who had a polyp finding on screening colonoscopy were identified. Univariate and multivariate analysis of age, gender, performance site, race, polyp location, number of polyps, and family history as risk factors associated with the size of the largest polyp detected at colonoscopy. Results In both genders, size of the largest polyp increased progressively with age in all age groups (P P Conclusions In both genders there is a significant increase in polyp size detected during screening colonoscopy with increasing age. Important additional risk factors associated with increasing polyp size are gender, race, polyp location, and number of polyps, with polyp multiplicity being the strongest risk factor. Previous family history of bowel cancer was not a risk factor.

Temperature-size responses match latitudinal-size clines in arthropods, revealing critical differences between aquatic and terrestrial species

DEFF Research Database (Denmark)

Horne, C.R.; Hirst, Andrew G.; Atkinson, D.

2015-01-01

of these gradients to date, and find that their direction and magnitude co-vary among 12 arthropod orders (r2 = 0.72). Body size in aquatic species generally reduces with both warming and decreasing latitude, whereas terrestrial species have much reduced and even opposite gradients. These patterns support...... the prediction that oxygen limitation is a major controlling factor in water, but not in air. Furthermore, voltinism explains much of the variation in T-S and L-S patterns in terrestrial but not aquatic species. While body size decreases with warming and with decreasing latitude in multivoltine terrestrial......Two major intraspecific patterns of adult size variation are plastic temperature-size (T-S) responses and latitude-size (L-S) clines. Yet, the degree to which these co-vary and share explanatory mechanisms has not been systematically evaluated. We present the largest quantitative comparison...

Effects of Sample Size and Dimensionality on the Performance of Four Algorithms for Inference of Association Networks in Metabonomics

NARCIS (Netherlands)

Suarez Diez, M.; Saccenti, E.

2015-01-01

We investigated the effect of sample size and dimensionality on the performance of four algorithms (ARACNE, CLR, CORR, and PCLRC) when they are used for the inference of metabolite association networks. We report that as many as 100-400 samples may be necessary to obtain stable network estimations,

Dental arch dimensions, form and tooth size ratio among a Saudi sample

Directory of Open Access Journals (Sweden)

Haidi Omar

2018-01-01

Full Text Available Objectives: To determine the dental arch dimensions and arch forms in a sample of Saudi orthodontic patients, to investigate the prevalence of Bolton anterior and overall tooth size discrepancies, and to compare the effect of gender on the measured parameters. Methods: This study is a biometric analysis of dental casts of 149 young adults recruited from different orthodontic centers in Jeddah, Saudi Arabia. The dental arch dimensions were measured. The measured parameters were arch length, arch width, Bolton’s ratio, and arch form. The data were analyzed using IBM SPSS software version 22.0 (IBM Corporation, New York, USA; this cross-sectional study was conducted between April 2015 and May 2016. Results: Dental arch measurements, including inter-canine and inter-molar distance, were found to be significantly greater in males than females (p less than 0.05. The most prevalent dental arch forms were narrow tapered (50.3% and narrow ovoid (34.2%, respectively. The prevalence of tooth size discrepancy in all cases was 43.6% for anterior ratio and 24.8% for overall ratio. The mean Bolton’s anterior ratio in all malocclusion classes was 79.81%, whereas the mean Bolton’s overall ratio was 92.21%. There was no significant difference between males and females regarding Bolton’s ratio. Conclusion: The most prevalent arch form was narrow tapered, followed by narrow ovoid. Males generally had larger dental arch measurements than females, and the prevalence of tooth size discrepancy was more in Bolton’s anterior teeth ratio than in overall ratio.

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

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

Relationships between myonuclear domain size and fibre properties in the muscles of Thoroughbred horses.

Science.gov (United States)

Kawai, M; Kuwano, A; Hiraga, A; Miyata, H

2010-11-01

The myonuclear domain (MND) is the region of cytoplasm governed by a single myonucleus. Myonuclear domain size is an important factor for muscle fibre plasticity because each myonucleus has limitations in the capacity of protein synthesis. Previous studies have demonstrated that differences in MND size exist in different fibre types in several species, including horses. To understand the basic mechanism of muscle plasticity, the relationships between MND size, muscle fibre type population and metabolic properties of skeletal muscles throughout the whole body in Thoroughbred horses were examined. Post mortem samples were taken from 20 muscles in 3 Thoroughbred horses aged 3-5 years of age. Fibre type population was determined on serial cross sections of each muscle sample, stained for monoclonal antibodies to each myosin heavy chain isoform. Oxidative (succinic dehydrogenase; SDH) and glycolytic (phosphofructokinase; PFK) enzyme activities were determined spectrophotometrically in each muscle sample. Furthermore, 30 single fibres were isolated from each muscle under stereomicroscopy and then fibre volume and myonuclear number for a given length analysed under confocal microscopy. The MND size of each single fibre was measured after normalisation of sarcomere length to 2.8 µm by staining with membrane-specific dye. Immunohistochemical staining indicated that soleus, vastus lateralis and gluteus medius muscles had the highest percentage of type I, IIa and IIx muscle fibre, respectively. Biochemical analysis indicated highest activities of SDH and PFK in diaphragm and longissimus lumborum muscles, respectively. MNDs were largest in the splenius muscle and smallest in the soleus and masseter muscles. Myonuclear domain size is significantly related to type I muscle fibre population, but not to SDH activities of the muscles. The MND size of muscle fibre depends on fibre type population rather than mitochondrial enzyme activities. © 2010 EVJ Ltd.

Invertebrate population genetics across Earth's largest habitat: The deep-sea floor.

Science.gov (United States)

Taylor, M L; Roterman, C N

2017-10-01

Despite the deep sea being the largest habitat on Earth, there are just 77 population genetic studies of invertebrates (115 species) inhabiting non-chemosynthetic ecosystems on the deep-sea floor (below 200 m depth). We review and synthesize the results of these papers. Studies reveal levels of genetic diversity comparable to shallow-water species. Generally, populations at similar depths were well connected over 100s-1,000s km, but studies that sampled across depth ranges reveal population structure at much smaller scales (100s-1,000s m) consistent with isolation by adaptation across environmental gradients, or the existence of physical barriers to connectivity with depth. Few studies were ocean-wide (under 4%), and 48% were Atlantic-focused. There is strong emphasis on megafauna and commercial species with research into meiofauna, "ecosystem engineers" and other ecologically important species lacking. Only nine papers account for ~50% of the planet's surface (depths below 3,500 m). Just two species were studied below 5,000 m, a quarter of Earth's seafloor. Most studies used single-locus mitochondrial genes revealing a common pattern of non-neutrality, consistent with demographic instability or selective sweeps; similar to deep-sea hydrothermal vent fauna. The absence of a clear difference between vent and non-vent could signify that demographic instability is common in the deep sea, or that selective sweeps render single-locus mitochondrial studies demographically uninformative. The number of population genetics studies to date is miniscule in relation to the size of the deep sea. The paucity of studies constrains meta-analyses where broad inferences about deep-sea ecology could be made. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

The effects of parameter estimation on minimizing the in-control average sample size for the double sampling X bar chart

Directory of Open Access Journals (Sweden)

Michael B.C. Khoo

2013-11-01

Full Text Available The double sampling (DS X bar chart, one of the most widely-used charting methods, is superior for detecting small and moderate shifts in the process mean. In a right skewed run length distribution, the median run length (MRL provides a more credible representation of the central tendency than the average run length (ARL, as the mean is greater than the median. In this paper, therefore, MRL is used as the performance criterion instead of the traditional ARL. Generally, the performance of the DS X bar chart is investigated under the assumption of known process parameters. In practice, these parameters are usually estimated from an in-control reference Phase-I dataset. Since the performance of the DS X bar chart is significantly affected by estimation errors, we study the effects of parameter estimation on the MRL-based DS X bar chart when the in-control average sample size is minimised. This study reveals that more than 80 samples are required for the MRL-based DS X bar chart with estimated parameters to perform more favourably than the corresponding chart with known parameters.

Linking home ranges to protected area size: The case study of the Mediterranean Sea

DEFF Research Database (Denmark)

Di Franco, Antonio; Plass-Johnson, Jeremiah Grahm; Di Lorenzo, Manfredi

2018-01-01

in the Mediterranean Sea, and related this to the size of 184 Mediterranean fully protected areas. We also investigated the influence of fully protected areas size on fish density in contrast to fished areas with respect to home ranges. Home range estimations were available for 11 species (10 fishes and 1 lobster......). The European spiny lobster Palinurus elephas had the smallest home range (0.0039 ± 0.0014 km2; mean ± 1 SE), while the painted comber Serranus scriba (1.1075 ± 0.2040 km2) had the largest. Approximately 25% of Mediterranean fully protected areas are larger than 2 times the size of the largest home range...

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

Directory of Open Access Journals (Sweden)

Pitchaiah Mandava

Full Text Available OBJECTIVE: Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS, a range of scores ("Shift" is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. METHODS: We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. RESULTS: Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD. Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001. Taking errors into account, SAINT I would have required 24% more subjects than were randomized. CONCLUSION: We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We

Dependence of fracture mechanical and fluid flow properties on fracture roughness and sample size

International Nuclear Information System (INIS)

Tsang, Y.W.; Witherspoon, P.A.

1983-01-01

A parameter study has been carried out to investigate the interdependence of mechanical and fluid flow properties of fractures with fracture roughness and sample size. A rough fracture can be defined mathematically in terms of its aperture density distribution. Correlations were found between the shapes of the aperture density distribution function and the specific fractures of the stress-strain behavior and fluid flow characteristics. Well-matched fractures had peaked aperture distributions that resulted in very nonlinear stress-strain behavior. With an increasing degree of mismatching between the top and bottom of a fracture, the aperture density distribution broadened and the nonlinearity of the stress-strain behavior became less accentuated. The different aperture density distributions also gave rise to qualitatively different fluid flow behavior. Findings from this investigation make it possible to estimate the stress-strain and fluid flow behavior when the roughness characteristics of the fracture are known and, conversely, to estimate the fracture roughness from an examination of the hydraulic and mechanical data. Results from this study showed that both the mechanical and hydraulic properties of the fracture are controlled by the large-scale roughness of the joint surface. This suggests that when the stress-flow behavior of a fracture is being investigated, the size of the rock sample should be larger than the typical wave length of the roughness undulations

Estimated ventricle size using Evans index: reference values from a population-based sample.

Science.gov (United States)

Jaraj, D; Rabiei, K; Marlow, T; Jensen, C; Skoog, I; Wikkelsø, C

2017-03-01

Evans index is an estimate of ventricular size used in the diagnosis of idiopathic normal-pressure hydrocephalus (iNPH). Values >0.3 are considered pathological and are required by guidelines for the diagnosis of iNPH. However, there are no previous epidemiological studies on Evans index, and normal values in adults are thus not precisely known. We examined a representative sample to obtain reference values and descriptive data on Evans index. A population-based sample (n = 1235) of men and women aged ≥70 years was examined. The sample comprised people living in private households and residential care, systematically selected from the Swedish population register. Neuropsychiatric examinations, including head computed tomography, were performed between 1986 and 2000. Evans index ranged from 0.11 to 0.46. The mean value in the total sample was 0.28 (SD, 0.04) and 20.6% (n = 255) had values >0.3. Among men aged ≥80 years, the mean value of Evans index was 0.3 (SD, 0.03). Individuals with dementia had a mean value of Evans index of 0.31 (SD, 0.05) and those with radiological signs of iNPH had a mean value of 0.36 (SD, 0.04). A substantial number of subjects had ventricular enlargement according to current criteria. Clinicians and researchers need to be aware of the range of values among older individuals. © 2017 EAN.

Patterns and trends in food portion sizes, 1977-1998.

Science.gov (United States)

Nielsen, Samara Joy; Popkin, Barry M

While general consensus holds that food portion sizes are increasing, no empirical data have documented actual increases. To determine trends in food portion sizes consumed in the United States, by eating location and food source. Nationally representative data from the Nationwide Food Consumption Survey (1977-1978) and the Continuing Survey of Food Intake by Individuals (1989-1991, 1994-1996, and 1998). The sample consists of 63 380 individuals aged 2 years and older. For each survey year, average portion size consumed from specific food items (salty snacks, desserts, soft drinks, fruit drinks, french fries, hamburgers, cheeseburgers, pizza, and Mexican food) by eating location (home, restaurant, or fast food). Portion sizes vary by food source, with the largest portions consumed at fast food establishments and the smallest at other restaurants. Between 1977 and 1996, food portion sizes increased both inside and outside the home for all categories except pizza. The energy intake and portion size of salty snacks increased by 93 kcal (from 1.0 to 1.6 oz [28.4 to 45.4 g]), soft drinks by 49 kcal (13.1 to 19.9 fl oz [387.4 to 588.4 mL]), hamburgers by 97 kcal (5.7 to 7.0 oz [161.6 to 198.4 g]), french fries by 68 kcal (3.1 to 3.6 oz [87.9 to 102.1 g]), and Mexican food by 133 kcal (6.3 to 8.0 oz [178.6 to 226.8 g]). Portion sizes and energy intake for specific food types have increased markedly with greatest increases for food consumed at fast food establishments and in the home.

Support, shape and number of replicate samples for tree foliage analysis.

Science.gov (United States)

Luyssaert, Sebastiaan; Mertens, Jan; Raitio, Hannu

2003-06-01

Many fundamental features of a sampling program are determined by the heterogeneity of the object under study and the settings for the error (alpha), the power (beta), the effect size (ES), the number of replicate samples, and sample support, which is a feature that is often overlooked. The number of replicates, alpha, beta, ES, and sample support are interconnected. The effect of the sample support and its shape on the required number of replicate samples was investigated by means of a resampling method. The method was applied to a simulated distribution of Cd in the crown of a Salix fragilis L. tree. Increasing the dimensions of the sample support results in a decrease in the variance of the element concentration under study. Analysis of the variance is often the foundation of statistical tests, therefore, valid statistical testing requires the use of a fixed sample support during the experiment. This requirement might be difficult to meet in time-series analyses and long-term monitoring programs. Sample supports have their largest dimension in the direction with the largest heterogeneity, i.e. the direction representing the crown height, and this will give more accurate results than supports with other shapes. Taking the relationships between the sample support and the variance of the element concentrations in tree crowns into account provides guidelines for sampling efficiency in terms of precision and costs. In terms of time, the optimal support to test whether the average Cd concentration of the crown exceeds a threshold value is 0.405 m3 (alpha = 0.05, beta = 0.20, ES = 1.0 mg kg(-1) dry mass). The average weight of this support is 23 g dry mass, and 11 replicate samples need to be taken. It should be noted that in this case the optimal support applies to Cd under conditions similar to those of the simulation, but not necessarily all the examinations for this tree species, element, and hypothesis test.

Collaborative spectrum sensing based on the ratio between largest eigenvalue and Geometric mean of eigenvalues

KAUST Repository

Shakir, Muhammad

2011-12-01

In this paper, we introduce a new detector referred to as Geometric mean detector (GEMD) which is based on the ratio of the largest eigenvalue to the Geometric mean of the eigenvalues for collaborative spectrum sensing. The decision threshold has been derived by employing Gaussian approximation approach. In this approach, the two random variables, i.e. The largest eigenvalue and the Geometric mean of the eigenvalues are considered as independent Gaussian random variables such that their cumulative distribution functions (CDFs) are approximated by a univariate Gaussian distribution function for any number of cooperating secondary users and received samples. The approximation approach is based on the calculation of exact analytical moments of the largest eigenvalue and the Geometric mean of the eigenvalues of the received covariance matrix. The decision threshold has been calculated by exploiting the CDF of the ratio of two Gaussian distributed random variables. In this context, we exchange the analytical moments of the two random variables with the moments of the Gaussian distribution function. The performance of the detector is compared with the performance of the energy detector and eigenvalue ratio detector. Analytical and simulation results show that our newly proposed detector yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, our results based on proposed approximation approach are in perfect agreement with the empirical results. © 2011 IEEE.

Joint Asymptotic Distributions of Smallest and Largest Insurance Claims

Directory of Open Access Journals (Sweden)

Hansjörg Albrecher

2014-07-01

Full Text Available Assume that claims in a portfolio of insurance contracts are described by independent and identically distributed random variables with regularly varying tails and occur according to a near mixed Poisson process. We provide a collection of results pertaining to the joint asymptotic Laplace transforms of the normalised sums of the smallest and largest claims, when the length of the considered time interval tends to infinity. The results crucially depend on the value of the tail index of the claim distribution, as well as on the number of largest claims under consideration.

SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images

International Nuclear Information System (INIS)

Reiser, I; Lu, Z

2014-01-01

Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions included two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task

(I Can’t Get No) Saturation: A Simulation and Guidelines for Minimum Sample Sizes in Qualitative Research

NARCIS (Netherlands)

van Rijnsoever, F.J.

2015-01-01

This paper explores the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the

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.

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.

Is it appropriate to composite fish samples for mercury trend monitoring and consumption advisories?

Science.gov (United States)

Gandhi, Nilima; Bhavsar, Satyendra P; Gewurtz, Sarah B; Drouillard, Ken G; Arhonditsis, George B; Petro, Steve

2016-03-01

Monitoring mercury levels in fish can be costly because variation by space, time, and fish type/size needs to be captured. Here, we explored if compositing fish samples to decrease analytical costs would reduce the effectiveness of the monitoring objectives. Six compositing methods were evaluated by applying them to an existing extensive dataset, and examining their performance in reproducing the fish consumption advisories and temporal trends. The methods resulted in varying amount (average 34-72%) of reductions in samples, but all (except one) reproduced advisories very well (96-97% of the advisories did not change or were one category more restrictive compared to analysis of individual samples). Similarly, the methods performed reasonably well in recreating temporal trends, especially when longer-term and frequent measurements were considered. The results indicate that compositing samples within 5cm fish size bins or retaining the largest/smallest individuals and compositing in-between samples in batches of 5 with decreasing fish size would be the best approaches. Based on the literature, the findings from this study are applicable to fillet, muscle plug and whole fish mercury monitoring studies. The compositing methods may also be suitable for monitoring Persistent Organic Pollutants (POPs) in fish. Overall, compositing fish samples for mercury monitoring could result in a substantial savings (approximately 60% of the analytical cost) and should be considered in fish mercury monitoring, especially in long-term programs or when study cost is a concern. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Airline's choice of aircraft size-explanations and implications

NARCIS (Netherlands)

Rietveld, P.; Givoni, M.

2009-01-01

When facing a growth in demand, airlines tend to respond more by means of increasing frequencies than by increasing aircraft size. At many of the world's largest airports there are fewer than 100 passengers per air transport movement, although congestion and delays are growing. Furthermore, demand

The interrupted power law and the size of shadow banking.

Science.gov (United States)

Fiaschi, Davide; Kondor, Imre; Marsili, Matteo; Volpati, Valerio

2014-01-01

Using public data (Forbes Global 2000) we show that the asset sizes for the largest global firms follow a Pareto distribution in an intermediate range, that is "interrupted" by a sharp cut-off in its upper tail, where it is totally dominated by financial firms. This flattening of the distribution contrasts with a large body of empirical literature which finds a Pareto distribution for firm sizes both across countries and over time. Pareto distributions are generally traced back to a mechanism of proportional random growth, based on a regime of constant returns to scale. This makes our findings of an "interrupted" Pareto distribution all the more puzzling, because we provide evidence that financial firms in our sample should operate in such a regime. We claim that the missing mass from the upper tail of the asset size distribution is a consequence of shadow banking activity and that it provides an (upper) estimate of the size of the shadow banking system. This estimate-which we propose as a shadow banking index-compares well with estimates of the Financial Stability Board until 2009, but it shows a sharper rise in shadow banking activity after 2010. Finally, we propose a proportional random growth model that reproduces the observed distribution, thereby providing a quantitative estimate of the intensity of shadow banking activity.

Self-navigation of a scanning tunneling microscope tip toward a micron-sized graphene sample.

Science.gov (United States)

Li, Guohong; Luican, Adina; Andrei, Eva Y

2011-07-01

We demonstrate a simple capacitance-based method to quickly and efficiently locate micron-sized conductive samples, such as graphene flakes, on insulating substrates in a scanning tunneling microscope (STM). By using edge recognition, the method is designed to locate and to identify small features when the STM tip is far above the surface, allowing for crash-free search and navigation. The method can be implemented in any STM environment, even at low temperatures and in strong magnetic field, with minimal or no hardware modifications.

A Systematic Review of Surgical Randomized Controlled Trials: Part 2. Funding Source, Conflict of Interest, and Sample Size in Plastic Surgery.

Science.gov (United States)

Voineskos, Sophocles H; Coroneos, Christopher J; Ziolkowski, Natalia I; Kaur, Manraj N; Banfield, Laura; Meade, Maureen O; Chung, Kevin C; Thoma, Achilleas; Bhandari, Mohit

2016-02-01

The authors examined industry support, conflict of interest, and sample size in plastic surgery randomized controlled trials that compared surgical interventions. They hypothesized that industry-funded trials demonstrate statistically significant outcomes more often, and randomized controlled trials with small sample sizes report statistically significant results more frequently. An electronic search identified randomized controlled trials published between 2000 and 2013. Independent reviewers assessed manuscripts and performed data extraction. Funding source, conflict of interest, primary outcome direction, and sample size were examined. Chi-squared and independent-samples t tests were used in the analysis. The search identified 173 randomized controlled trials, of which 100 (58 percent) did not acknowledge funding status. A relationship between funding source and trial outcome direction was not observed. Both funding status and conflict of interest reporting improved over time. Only 24 percent (six of 25) of industry-funded randomized controlled trials reported authors to have independent control of data and manuscript contents. The mean number of patients randomized was 73 per trial (median, 43, minimum, 3, maximum, 936). Small trials were not found to be positive more often than large trials (p = 0.87). Randomized controlled trials with small sample size were common; however, this provides great opportunity for the field to engage in further collaboration and produce larger, more definitive trials. Reporting of trial funding and conflict of interest is historically poor, but it greatly improved over the study period. Underreporting at author and journal levels remains a limitation when assessing the relationship between funding source and trial outcomes. Improved reporting and manuscript control should be goals that both authors and journals can actively achieve.

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.

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study.

Science.gov (United States)

Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

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.

Influence of crystallite size on the magnetic properties of Fe{sub 3}O{sub 4} nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Upadhyay, Sneha [Dept of Applied Science, Symbiosis Institute of Technology, SIU, Lavale, Mulshi, Pune 412 115 (India); Parekh, Kinnari [K C Patel R & D Center, Charotar University of Science & Technology, Changa 388421 (India); Pandey, Brajesh, E-mail: bpandey@gmail.com [Dept of Applied Science, Symbiosis Institute of Technology, SIU, Lavale, Mulshi, Pune 412 115 (India)

2016-09-05

Structural and magnetic properties of chemically synthesized magnetite nanoparticles have been studied using X-ray diffraction, Transmission Electron Microscopy and Vibrating Sample Magnetometer. Magnetically the synthesized nanoparticles are ranging from superparamagnetic to multi domain state. Average crystallite size of the synthesized magnetite nanoparticles were determined using X-ray line broadening and are found to be in the range of 9–53 nm. On the other hand, the TEM images show that the size is ranging between 7.9 and 200 nm with the transition from spherical superparamagnetic particles to faceted cubic multi domain particles. Magnetic parameters of the samples show a strong dependence on average crystallite size. The ratio of coercive field at 20 K to that at 300 K (H{sub c} (20 K)/H{sub c} (300 K)) increased sharply with decrease in crystallite size. A critical crystallite diameter of order 36 nm may be inferred as boundary between single domain to multi domain transition. Zero-field-cooled (ZFC) and field-cooled (FC) measurements at 10 Oe field validate the same for smallest and largest size samples, confirming that the anisotropy energy is greater than thermal energy upto 300 K temperature. For 9 nm sample broad ZFC curve with overlapping of FC curve is observed just at 300 K, indicating the effect of strong dipolar field in superparamagnetic system. - Graphical abstract: We present our study on magnetite nanoparticles. We observed that the synthesized nanoparticles behave like single domain particles in the range of 14 nm–36 nm. They show superparamagnetic properties if particles are smaller than 14 nm and multi-domain properties when the particles are bigger than 36 nm. - Highlights: • Magnetite nanoparticles have been synthesized using chemical precipitation method. • Smaller magnetite particles below 14 nm in size are in super-paramagnetic state. • Bigger particles show multi-domain character. • Magnetite in the size range 14–36 is

Sample size effect on the determination of the irreversibility line of high-Tc superconductors

International Nuclear Information System (INIS)

Li, Q.; Suenaga, M.; Li, Q.; Freltoft, T.

1994-01-01

The irreversibility lines of a high-J c superconducting Bi 2 Sr 2 Ca 2 Cu 3 O x /Ag tape were systematically measured upon a sequence of subdivisions of the sample. The irreversibility field H r (T) (parallel to the c axis) was found to change approximately as L 0.13 , where L is the effective dimension of the superconducting tape. Furthermore, it was found that the irreversibility line for a grain-aligned Bi 2 Sr 2 Ca 2 Cu 3 O x specimen can be approximately reproduced by the extrapolation of this relation down to a grain size of a few tens of micrometers. The observed size effect could significantly obscure the real physical meaning of the irreversibility lines. In addition, this finding surprisingly indicated that the Bi 2 Sr 2 Ca 2 Cu 2 O x /Ag tape and grain-aligned specimen may have similar flux line pinning strength

Speciation and leachability of copper in mine tailings from porphyry copper mining: influence of particle size.

Science.gov (United States)

Hansen, Henrik K; Yianatos, Juan B; Ottosen, Lisbeth M

2005-09-01

Mine tailing from the El Teniente-Codelco copper mine situated in VI Region of Chile was analysed in order to evaluate the mobility and speciation of copper in the solid material. Mine tailing was sampled after the rougher flotation circuits, and the copper content was measured to 1150 mg kg (-1) dry matter. This tailing was segmented into fractions of different size intervals: 0-38, 38-45, 45-53, 53-75, 75-106, 106-150, 150-212, and >212 microm, respectively. Copper content determination, sequential chemical extraction, and desorption experiments were carried out for each size interval in order to evaluate the speciation of copper. It was found that the particles of smallest size contained 50-60% weak acid leachable copper, whereas only 32% of the copper found in largest particles could be leached in weak acid. Copper oxides and carbonates were the dominating species in the smaller particles, and the larger particles contained considerable amounts of sulphides.

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

2018-01-01

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.

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

Science.gov (United States)

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

Guaranteeing uptime at worl's largest particle physics lab

CERN Multimedia

Brodkin, Jon

2007-01-01

"As the European agency CERN was gearing up to build the world's largest particle accelerator, officials there knew they could not afford to have problems in their technical infrastructure cause any downtime." (1 page)

Size-distributions of n-alkanes, PAHs and hopanes and their sources in the urban, mountain and marine atmospheres over East Asia

Directory of Open Access Journals (Sweden)

Z. Wang

2009-11-01

Full Text Available Size-segregated (9 stages n-alkanes, polycyclic aromatic hydrocarbons (PAHs and hopanes in the urban (Baoji city in inland China, mountain (Mt. Tai in east coastal China and marine (Okinawa Island, Japan atmospheres over East Asia were studied using a GC/MS technique. Ambient concentrations of n-alkanes (1698±568 ng m−3 in winter and 487±145 ng m−3 in spring, PAHs (536±80 and 161±39 ng m−3, and hopanes (65±24 and 20±2.4 ng m−3 in the urban air are 1–2 orders of magnitude higher than those in the mountain aerosols and 2–3 orders of magnitude higher than those in the marine samples. Mass ratios of n-alkanes, PAHs and hopanes clearly demonstrate coal-burning emissions as their major source. Size distributions of fossil fuel derived n-alkane, PAHs and hopanes were found to be unimodal in most cases, peaking at 0.7–1.1 μm size. In contrast, plant wax derived n-alkanes presented a bimodal distribution with two peaks at the sizes of 0.7–1.1 μm and >4.7 μm in the summer mountain and spring marine samples. Among the three types of samples, geometric mean diameter (GMD of the organics in fine mode (<2.1 μm was found to be smallest (av. 0.63 μm in spring for the urban samples and largest (1.01 μm for the marine samples, whereas the GMD in coarse mode (≥2.1 μm was found to be smallest (3.48 μm for the marine aerosols and largest (4.04 μm for the urban aerosols. The fine mode GMDs of the urban and mountain samples were larger in winter than in spring and summer. Moreover, GMDs of 3- and 4-ring PAHs were larger than those of 5- and 6-ring PAHs in the three types of atmospheres. Such differences in GMDs can be interpreted by the repartitioning of organic compounds and the coagulation and hygroscopic growth of particles during a long-range transport from the inland continent to the marine area, as well as the difference in their sources among the three regions.

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

OpenAIRE

Heckmann, Mark; Burk, Lukas

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...

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....... Regions of interest were automatically delineated on co-registered MR and PET images. RESULTS: In cortical brain regions with a high density of 5-HT2A receptors, the outcome parameter (binding potential, BP1) showed high reproducibility, with a median difference between the two group measurements of 6...

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

Science.gov (United States)

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

Habitat area and climate stability determine geographical variation in plant species range sizes

DEFF Research Database (Denmark)

Morueta-Holme, Naia; Enquist, Brian J.; McGill, Brian J.

2013-01-01

Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest botanical data set assembled to date to quantify geographical variation in range size for ~85,000 ...

EFFECT OF GRAIN SIZE AND ACTIVATION TIME OF ZEOLITE TO ADSORPTION AND DESORPTION OF NH4OH AND KCL AS MODEL OF FERTILIZER-ZEOLITE MIX

Directory of Open Access Journals (Sweden)

Muhammad Prasantio Bimantio

2017-10-01

Full Text Available Zeolites can be used as adsorbent, ion exchange, catalyst, or catalyst carrier. Application of fertilizer use in the zeolite also be one of the interesting topic. Zeolites in a mixture of fertilizer can use to control the release of nutrients. The purpose of this research is to study the effect of grain size and time of the activation of zeolite to adsorption and desorption of NH4OH and KCl as modeling of ZA and KCl fertilizer, to obtain the value of adsorption rate constant (ka and desorption rate constant (kd. This research procedure include: the process of adsorption by adding zeolite with various size and time of activation into a sealed beaker glass and let the adsorption process occurs for 24 hours. After 24 hours, the solution was filtered, the zeolite then put in 100 ml of aquadest into a sealed beaker glass and let the desorption process happened for another 24 hours. Three samples with the largest difference solution concentrations looked for the value of the ka and kd. Zeolite configuration with the largest ka is trialed with fertilizer and compared with the value of ka obtained from modeling. The result for NH4OH adsorbate, -50+60 mesh 2 hours configuration zeolite give the largest ka. For KCl adsorbate, -30+40 mesh 4 hours configuration zeolite give the largest ka. The value between modeling and trials with fertilizers are not much different.

STAR FORMATION LAWS: THE EFFECTS OF GAS CLOUD SAMPLING

International Nuclear Information System (INIS)

Calzetti, D.; Liu, G.; Koda, J.

2012-01-01

Recent observational results indicate that the functional shape of the spatially resolved star formation-molecular gas density relation depends on the spatial scale considered. These results may indicate a fundamental role of sampling effects on scales that are typically only a few times larger than those of the largest molecular clouds. To investigate the impact of this effect, we construct simple models for the distribution of molecular clouds in a typical star-forming spiral galaxy and, assuming a power-law relation between star formation rate (SFR) and cloud mass, explore a range of input parameters. We confirm that the slope and the scatter of the simulated SFR-molecular gas surface density relation depend on the size of the sub-galactic region considered, due to stochastic sampling of the molecular cloud mass function, and the effect is larger for steeper relations between SFR and molecular gas. There is a general trend for all slope values to tend to ∼unity for region sizes larger than 1-2 kpc, irrespective of the input SFR-cloud relation. The region size of 1-2 kpc corresponds to the area where the cloud mass function becomes fully sampled. We quantify the effects of selection biases in data tracing the SFR, either as thresholds (i.e., clouds smaller than a given mass value do not form stars) or as backgrounds (e.g., diffuse emission unrelated to current star formation is counted toward the SFR). Apparently discordant observational results are brought into agreement via this simple model, and the comparison of our simulations with data for a few galaxies supports a steep (>1) power-law index between SFR and molecular gas.

Size-exclusion chromatography-based enrichment of extracellular vesicles from urine samples

Directory of Open Access Journals (Sweden)

Inés Lozano-Ramos

2015-05-01

Full Text Available Renal biopsy is the gold-standard procedure to diagnose most of renal pathologies. However, this invasive method is of limited repeatability and often describes an irreversible renal damage. Urine is an easily accessible fluid and urinary extracellular vesicles (EVs may be ideal to describe new biomarkers associated with renal pathologies. Several methods to enrich EVs have been described. Most of them contain a mixture of proteins, lipoproteins and cell debris that may be masking relevant biomarkers. Here, we evaluated size-exclusion chromatography (SEC as a suitable method to isolate urinary EVs. Following a conventional centrifugation to eliminate cell debris and apoptotic bodies, urine samples were concentrated using ultrafiltration and loaded on a SEC column. Collected fractions were analysed by protein content and flow cytometry to determine the presence of tetraspanin markers (CD63 and CD9. The highest tetraspanin content was routinely detected in fractions well before the bulk of proteins eluted. These tetraspanin-peak fractions were analysed by cryo-electron microscopy (cryo-EM and nanoparticle tracking analysis revealing the presence of EVs.When analysed by sodium dodecyl sulphate–polyacrylamide gel electrophoresis, tetraspanin-peak fractions from urine concentrated samples contained multiple bands but the main urine proteins (such as Tamm–Horsfall protein were absent. Furthermore, a preliminary proteomic study of these fractions revealed the presence of EV-related proteins, suggesting their enrichment in concentrated samples. In addition, RNA profiling also showed the presence of vesicular small RNA species.To summarize, our results demonstrated that concentrated urine followed by SEC is a suitable option to isolate EVs with low presence of soluble contaminants. This methodology could permit more accurate analyses of EV-related biomarkers when further characterized by -omics technologies compared with other approaches.

Species and Size Composition of Seahorses (Genus Hippocampus, Family Syngnathidae) in the Coastal Waters and Local Market of Kota Kinabalu, Sabah, Malaysia.

Science.gov (United States)

Shapawi, Rossita; Anyie, Adrian Leslie; Hussien, Muhammad Ali Syed; Zuldin, Wahidatul Husna

2015-12-01

Seahorse diversity (genus Hippocampus, Family Syngnathidae), species identification, size composition and sexual dimorphism were studied from November 2012 to March 2013 in selected coastal waters around Kota Kinabalu, Sabah and the local market trade. Six species of seahorses were identified in the study: (1) Hippocampus barbouri, (2) Hippocampus comes, (3) Hippocampus kelloggi, (4) Hippocampus kuda, (5) Hippocampus spinosissimus and (6) Hippocampus trimaculatus. All six species were sold at the local market, and the dried seahorses were obtained mainly by local fishermen using trawl by-catch method and traded as traditional medicine, souvenirs and other uses. Four species were identified by direct samplings in various different habitats of Kota Kinabalu coastal waters: (1) H. barbouri, (2) H. comes, (3) H. kuda, and (4) H. spinosissimus. Based on the results, H. comes was the largest in size among the four fresh/live species found (mean standard length [SL]: 148.25±1.26 mm), whereas H. barbouri was the smallest species (mean SL: 129±7.81 mm). For the dried samples, H. kelloggi was the largest (mean SL: 245.25±14.55 mm) and H. barbouri was the smallest (mean SL: 127.21±10.01 mm). No significant difference (p>0.05) was observed between the lengths of males and females in every seahorse species, and there was no sexual size dimorphism in any of the species. The findings from the study are significant to provide baseline data for the conservation efforts of these unique marine teleost.

Matching Ge detector element geometry to sample size and shape: One does not fit all exclamation point

International Nuclear Information System (INIS)

Keyser, R.M.; Twomey, T.R.; Sangsingkeow, P.

1998-01-01

For 25 yr, coaxial germanium detector performance has been specified using the methods and values specified in Ref. 1. These specifications are the full-width at half-maximum (FWHM), FW.1M, FW.02M, peak-to-Compton ratio, and relative efficiency. All of these measurements are made with a 60 Co source 25 cm from the cryostat endcap and centered on the axis of the detector. These measurements are easy to reproduce, both because they are simple to set up and use a common source. These standard tests have been useful in guiding the user to an appropriate detector choice for the intended measurement. Most users of germanium gamma-ray detectors do not make measurements in this simple geometry. Germanium detector manufacturers have worked over the years to make detectors with better resolution, better peak-to-Compton ratios, and higher efficiency--but all based on measurements using the IEEE standard. Advances in germanium crystal growth techniques have made it relatively easy to provide detector elements of different shapes and sizes. Many of these different shapes and sizes can give better results for a specific application than other shapes and sizes. But, the detector specifications must be changed to correspond to the actual application. Both the expected values and the actual parameters to be specified should be changed. In many cases, detection efficiency, peak shape, and minimum detectable limit for a particular detector/sample combination are valuable specifications of detector performance. For other situations, other parameters are important, such as peak shape as a function of count rate. In this work, different sample geometries were considered. The results show the variation in efficiency with energy for all of these sample and detector geometries. The point source at 25 cm from the endcap measurement allows the results to be compared with the currently given IEEE criteria. The best sample/detector configuration for a specific measurement requires more and

The world's largest LNG producer's next market

International Nuclear Information System (INIS)

Fuller, R.; Isworo Suharno; Simandjuntak, W.M.P.

1996-01-01

The development of the domestic gas market in Indonesia, the world's largest liquefied natural gas producing country, is described as part of the overall impact of the country's oil and gas production. The first large scale use of natural gas in Indonesia was established in 1968 when a fertiliser plant using gas as the feedstock was built. Ultimately, through increased yields, this has enabled Indonesia to be self-sufficient in rice and an exporter of fertiliser. Problems which stand in the way of further developments include: capital, though Pertamina and PGN are perceived as attractive for foreign investment; the lack of a regulatory framework for gas; geographical constraints, among them the fact that the gas deposits are remote from the largest population concentrations; lack of infrastructure. There are nevertheless plans for expansion and the provision of an integrated gas pipeline system. Pertamina, which has responsibility for all oil and gas developments, and PGN, whose primary role has been as a manufacturer and distributor of gas, are now working together in the coordination of all gas activities. (10 figures). (UK)

Weighted piecewise LDA for solving the small sample size problem in face verification.

Science.gov (United States)

Kyperountas, Marios; Tefas, Anastasios; Pitas, Ioannis

2007-03-01

A novel algorithm that can be used to boost the performance of face-verification methods that utilize Fisher's criterion is presented and evaluated. The algorithm is applied to similarity, or matching error, data and provides a general solution for overcoming the "small sample size" (SSS) problem, where the lack of sufficient training samples causes improper estimation of a linear separation hyperplane between the classes. Two independent phases constitute the proposed method. Initially, a set of weighted piecewise discriminant hyperplanes are used in order to provide a more accurate discriminant decision than the one produced by the traditional linear discriminant analysis (LDA) methodology. The expected classification ability of this method is investigated throughout a series of simulations. The second phase defines proper combinations for person-specific similarity scores and describes an outlier removal process that further enhances the classification ability. The proposed technique has been tested on the M2VTS and XM2VTS frontal face databases. Experimental results indicate that the proposed framework greatly improves the face-verification performance.

Worlds Largest Wave Energy Project 2007 in Wales

DEFF Research Database (Denmark)

Christensen, Lars; Friis-Madsen, Erik; Kofoed, Jens Peter

2006-01-01

This paper introduces world largest wave energy project being developed in Wales and based on one of the leading wave energy technologies. The background for the development of wave energy, the total resource ands its distribution around the world is described. In contrast to wind energy turbines...... Dragon has to be scaled in accordance with the wave climate at the deployment site, which makes the Welch demonstrator device the worlds largest WEC so far with a total width of 300 meters. The project budget, the construction methods and the deployment site are also given....... a large number of fundamentally different technologies are utilised to harvest wave energy. The Wave Dragon belongs to the wave overtopping class of converters and the paper describes the fundamentals and the technical solutions used in this wave energy converter. An offshore floating WEC like the Wave...

Evaluating sampling strategy for DNA barcoding study of coastal and inland halo-tolerant Poaceae and Chenopodiaceae: A case study for increased sample size.

Science.gov (United States)

Yao, Peng-Cheng; Gao, Hai-Yan; Wei, Ya-Nan; Zhang, Jian-Hang; Chen, Xiao-Yong; Li, Hong-Qing

2017-01-01

Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11-15.

First Experience from the World Largest fully commercial Solar Heating Plant

DEFF Research Database (Denmark)

Heller, Alfred; Furbo, Simon

1997-01-01

The first experience from the largest solar heating plant in the world is given. The plant is situated in Marstal and is has a total area of 8000 square m.......The first experience from the largest solar heating plant in the world is given. The plant is situated in Marstal and is has a total area of 8000 square m....

Decision-making and sampling size effect

OpenAIRE

Ismariah Ahmad; Rohana Abd Rahman; Roda Jean-Marc; Lim Hin Fui; Mohd Parid Mamat

2010-01-01

Sound decision-making requires quality information. Poor information does not help in decision making. Among the sources of low quality information, an important cause is inadequate and inappropriate sampling. In this paper we illustrate the case of information collected on timber prices.

A Volume-Limited Sample of L and T Dwarfs Defined by Parallaxes

Science.gov (United States)

Best, William M. J.; Liu, Michael C.; Magnier, Eugene; Dupuy, Trent

2018-01-01

Volume-limited samples are the gold standard for stellar population studies, as they enable unbiased measurements of space densities and luminosity functions. Parallaxes are the most direct measures of distance and are therefore essential for defining high-confidence volume limited samples. Previous efforts to model the local brown dwarf population were hampered by samples based on a small number of parallaxes. We are using UKIRT/WFCAM to conduct the largest near-infrared program to date to measure parallaxes and proper motions of L and T dwarfs. For the past 3+ years we have monitored over 350 targets, ≈90% of which are too faint to be observed by Gaia. We present preliminary results from our observations. Our program more than doubles the number of known L and T dwarf parallaxes, defining a volume-limited sample of ≈400 L0-T6 dwarfs out to 25 parsecs, the first L and T dwarf sample of this size and depth based entirely on parallaxes. Our sample will combine with the upcoming stellar census from Gaia DR2 parallaxes to form a complete volume-limited sample of nearby stars and brown dwarfs.

Dissolved Oxygen Dynamics in Backwaters of North America's Largest River Swamp

Science.gov (United States)

Bueche, S. M.; Xu, Y. J.; Reiman, J. H.

2017-12-01

The Atchafalaya River (AR) is the largest distributary of the Mississippi River flowing through south-central Louisiana, creating North America's largest river swamp basin - the Atchafalaya River Basin (ARB). Prior to human settlement, the AR's main channel was highly connected to this large wetland ecosystem. However, due to constructed levee systems and other human modifications, much of the ARB is now hydrologically disconnected from the AR's main channel except during high flow events. This lack of regular inputs of fresh, oxygenated water to these wetlands, paired with high levels of organic matter decomposition in wetlands, has caused low oxygen-deprived hypoxic conditions in the ARB's back waters. In addition, due to the incredibly nutrient-rich and warm nature of the ARB, microbial decomposition in backwater areas with limited flow often results in potentially stressful, if not lethal, levels of DO for organisms during and after flood pulses. This study aims to investigate dynamics of dissolved oxygen in backwaters of the Atchafalaya River Basin, intending to answer a crucial question about hydrological and water quality connectivity between the river's mainstem and its floodplain. Specifically, the study will 1) conduct field water quality measurements, 2) collect composite water samples for chemical analysis of nutrients and carbon, 3) investigate DO dynamics over different seasons for one year, and 4) determine the major factors that affect DO dynamics in this unique swamp ecosystem. The study is currently underway; therefore, in this presentation we will share the major findings gained in the past several months and discuss backwater effects on river chemistry.

Association between different phases of menstrual cycle and body image measures of perceived size, ideal size, and body dissatisfaction.

Science.gov (United States)

Teixeira, André Luiz S; Dias, Marcelo Ricardo C; Damasceno, Vinícius O; Lamounier, Joel A; Gardner, Rick M

2013-12-01

The association between phases of the menstrual cycle and body image was investigated. 44 university women (M age = 23.3 yr., SD = 4.7) judged their perceived and ideal body size, and body dissatisfaction was calculated at each phase of the menstrual cycle, including premenstrual, menstrual, and intermenstrual. Participants selected one of nine figural drawings ranging from very thin to obese that represented their perceived size and ideal size. Body dissatisfaction was measured as the absolute difference between scores on perceived and ideal figural drawings. During each menstrual phase, anthropometric measures of weight, height, body mass index, circumference of waist and abdomen, and body composition were taken. There were no significant differences in any anthropometric measures between the three menstrual cycle phases. Perceived body size and body dissatisfaction were significantly different between menstrual phases, with the largest perceived body size and highest body dissatisfaction occurring during the menstrual phase. Ideal body size did not differ between menstrual phases, although participants desired a significantly smaller ideal size as compared to the perceived size.

A contemporary decennial global sample of changing agricultural field sizes

Science.gov (United States)

White, E.; Roy, D. P.

2011-12-01

In the last several hundred years agriculture has caused significant human induced Land Cover Land Use Change (LCLUC) with dramatic cropland expansion and a marked increase in agricultural productivity. The size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLUC. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, diffusion of disease pathogens and pests, and loss or degradation in buffers to nutrient, herbicide and pesticide flows. In this study, globally distributed locations with significant contemporary field size change were selected guided by a global map of agricultural yield and literature review and were selected to be representative of different driving forces of field size change (associated with technological innovation, socio-economic conditions, government policy, historic patterns of land cover land use, and environmental setting). Seasonal Landsat data acquired on a decadal basis (for 1980, 1990, 2000 and 2010) were used to extract field boundaries and the temporal changes in field size quantified and their causes discussed.

The effects of preparation, shipment and ageing on the Pu elemental assay results of milligram-sized samples

International Nuclear Information System (INIS)

Berger, J.; Doubek, N.; Jammet, G.; Aigner, H.; Bagliano, G.; Donohue, D.; Kuhn, E.

1994-02-01

Specialized procedures have been implemented for the sampling of Pu-containing materials such as Pu nitrate, oxide or mixed oxide in States which have not yet approved type B(U) shipment containers for the air-shipment of gram-sized quantities of Pu. In such cases, it it necessary to prepare samples for shipment which contain only milligram quantities of Pu dried from solution in penicillin vials. Potential problems due to flaking-off during shipment could affect the recovery of Pu at the analytical laboratory. Therefore, a series of tests was performed with synthetic Pu nitrated, and mixed U, Pu nitrated samples to test the effectiveness of the evaporation and recovery procedures. Results of these tests as well as experience with actual inspection samples are presented, showing conclusively that the existing procedures are satisfactory. (author). 11 refs, 6 figs, 8 tabs

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

Dinosaurs, dragons, and dwarfs: The evolution of maximal body size

Science.gov (United States)

Burness, Gary P.; Diamond, Jared; Flannery, Timothy

2001-01-01

Among local faunas, the maximum body size and taxonomic affiliation of the top terrestrial vertebrate vary greatly. Does this variation reflect how food requirements differ between trophic levels (herbivores vs. carnivores) and with taxonomic affiliation (mammals and birds vs. reptiles)? We gathered data on the body size and food requirements of the top terrestrial herbivores and carnivores, over the past 65,000 years, from oceanic islands and continents. The body mass of the top species was found to increase with increasing land area, with a slope similar to that of the relation between body mass and home range area, suggesting that maximum body size is determined by the number of home ranges that can fit into a given land area. For a given land area, the body size of the top species decreased in the sequence: ectothermic herbivore > endothermic herbivore > ectothermic carnivore > endothermic carnivore. When we converted body mass to food requirements, the food consumption of a top herbivore was about 8 times that of a top carnivore, in accord with the factor expected from the trophic pyramid. Although top ectotherms were heavier than top endotherms at a given trophic level, lower metabolic rates per gram of body mass in ectotherms resulted in endotherms and ectotherms having the same food consumption. These patterns explain the size of the largest-ever extinct mammal, but the size of the largest dinosaurs exceeds that predicted from land areas and remains unexplained. PMID:11724953

Challenges with the largest commercial hydrogen station in the world

Energy Technology Data Exchange (ETDEWEB)

Charbonneau, Thomas; Gauthier, Pierre [Air Liquide Canada (Canada)

2010-07-01

This abstract's objective is to share with the participants the story of the largest hydrogen fueling station made to this date and to kick-start the story, we will cover the challenges; first the technical ones; the operational ones; the distribution ones and; the financial ones. We will then move on to review the logistic (geographic) issues raised by the project and conclude our presentation by sharing the output values of the largest fueling station built so far in the world. (orig.)

Investigating effects of sample pretreatment on protein stability using size-exclusion chromatography and high-resolution continuum source atomic absorption spectrometry.

Science.gov (United States)

Rakow, Tobias; El Deeb, Sami; Hahne, Thomas; El-Hady, Deia Abd; AlBishri, Hassan M; Wätzig, Hermann

2014-09-01

In this study, size-exclusion chromatography and high-resolution atomic absorption spectrometry methods have been developed and evaluated to test the stability of proteins during sample pretreatment. This especially includes different storage conditions but also adsorption before or even during the chromatographic process. For the development of the size exclusion method, a Biosep S3000 5 μm column was used for investigating a series of representative model proteins, namely bovine serum albumin, ovalbumin, monoclonal immunoglobulin G antibody, and myoglobin. Ambient temperature storage was found to be harmful to all model proteins, whereas short-term storage up to 14 days could be done in an ordinary refrigerator. Freezing the protein solutions was always complicated and had to be evaluated for each protein in the corresponding solvent. To keep the proteins in their native state a gentle freezing temperature should be chosen, hence liquid nitrogen should be avoided. Furthermore, a high-resolution continuum source atomic absorption spectrometry method was developed to observe the adsorption of proteins on container material and chromatographic columns. Adsorption to any container led to a sample loss and lowered the recovery rates. During the pretreatment and high-performance size-exclusion chromatography, adsorption caused sample losses of up to 33%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatially Resolved Hα Maps and Sizes of 57 Strongly Star-forming Galaxies at z ~ 1 from 3D-HST: Evidence for Rapid Inside-out Assembly of Disk Galaxies

Science.gov (United States)

Nelson, Erica June; van Dokkum, Pieter G.; Brammer, Gabriel; Förster Schreiber, Natascha; Franx, Marijn; Fumagalli, Mattia; Patel, Shannon; Rix, Hans-Walter; Skelton, Rosalind E.; Bezanson, Rachel; Da Cunha, Elisabete; Kriek, Mariska; Labbe, Ivo; Lundgren, Britt; Quadri, Ryan; Schmidt, Kasper B.

2012-03-01

We investigate the buildup of galaxies at z ~ 1 using maps of Hα and stellar continuum emission for a sample of 57 galaxies with rest-frame Hα equivalent widths >100 Å in the 3D-HST grism survey. We find that the Hα emission broadly follows the rest-frame R-band light but that it is typically somewhat more extended and clumpy. We quantify the spatial distribution with the half-light radius. The median Hα effective radius re (Hα) is 4.2 ± 0.1 kpc but the sizes span a large range, from compact objects with re (Hα) ~ 1.0 kpc to extended disks with re (Hα) ~ 15 kpc. Comparing Hα sizes to continuum sizes, we find =1.3 ± 0.1 for the full sample. That is, star formation, as traced by Hα, typically occurs out to larger radii than the rest-frame R-band stellar continuum; galaxies are growing their radii and building up from the inside out. This effect appears to be somewhat more pronounced for the largest galaxies. Using the measured Hα sizes, we derive star formation rate surface densities, ΣSFR. We find that ΣSFR ranges from ~0.05 M ⊙ yr-1 kpc-2 for the largest galaxies to ~5 M ⊙ yr-1 kpc-2 for the smallest galaxies, implying a large range in physical conditions in rapidly star-forming z ~ 1 galaxies. Finally, we infer that all galaxies in the sample have very high gas mass fractions and stellar mass doubling times <500 Myr. Although other explanations are also possible, a straightforward interpretation is that we are simultaneously witnessing the rapid formation of compact bulges and large disks at z ~ 1.

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…

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)

The influence of nitrogen inputs on biomass and trophic structure of ocean plankton: a study using biomass and stable isotope size-spectra

KAUST Repository

Mompeán, Carmen

2016-08-18