Sample size estimation and sampling techniques for selecting a representative sample

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Aamir Omair

2014-01-01

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

Sample size determination for mediation analysis of longitudinal data.

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Pan, Haitao; Liu, Suyu; Miao, Danmin; Yuan, Ying

2018-03-27

Sample size planning for longitudinal data is crucial when designing mediation studies because sufficient statistical power is not only required in grant applications and peer-reviewed publications, but is essential to reliable research results. However, sample size determination is not straightforward for mediation analysis of longitudinal design. To facilitate planning the sample size for longitudinal mediation studies with a multilevel mediation model, this article provides the sample size required to achieve 80% power by simulations under various sizes of the mediation effect, within-subject correlations and numbers of repeated measures. The sample size calculation is based on three commonly used mediation tests: Sobel's method, distribution of product method and the bootstrap method. Among the three methods of testing the mediation effects, Sobel's method required the largest sample size to achieve 80% power. Bootstrapping and the distribution of the product method performed similarly and were more powerful than Sobel's method, as reflected by the relatively smaller sample sizes. For all three methods, the sample size required to achieve 80% power depended on the value of the ICC (i.e., within-subject correlation). A larger value of ICC typically required a larger sample size to achieve 80% power. Simulation results also illustrated the advantage of the longitudinal study design. The sample size tables for most encountered scenarios in practice have also been published for convenient use. Extensive simulations study showed that the distribution of the product method and bootstrapping method have superior performance to the Sobel's method, but the product method was recommended to use in practice in terms of less computation time load compared to the bootstrapping method. A R package has been developed for the product method of sample size determination in mediation longitudinal study design.

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

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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

[Practical aspects regarding sample size in clinical research].

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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.

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

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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.

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...

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

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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

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

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

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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.

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

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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.

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.

Sample size in qualitative interview studies

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

2016-01-01

Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is “saturation.” Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose...... the concept “information power” to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power...... and during data collection of a qualitative study is discussed....

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.

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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 calculation in metabolic phenotyping studies.

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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.

Revisiting sample size: are big trials the answer?

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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.

Concepts in sample size determination

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Umadevi K Rao

2012-01-01

Full Text Available Investigators involved in clinical, epidemiological or translational research, have the drive to publish their results so that they can extrapolate their findings to the population. This begins with the preliminary step of deciding the topic to be studied, the subjects and the type of study design. In this context, the researcher must determine how many subjects would be required for the proposed study. Thus, the number of individuals to be included in the study, i.e., the sample size is an important consideration in the design of many clinical studies. The sample size determination should be based on the difference in the outcome between the two groups studied as in an analytical study, as well as on the accepted p value for statistical significance and the required statistical power to test a hypothesis. The accepted risk of type I error or alpha value, which by convention is set at the 0.05 level in biomedical research defines the cutoff point at which the p value obtained in the study is judged as significant or not. The power in clinical research is the likelihood of finding a statistically significant result when it exists and is typically set to >80%. This is necessary since the most rigorously executed studies may fail to answer the research question if the sample size is too small. Alternatively, a study with too large a sample size will be difficult and will result in waste of time and resources. Thus, the goal of sample size planning is to estimate an appropriate number of subjects for a given study design. This article describes the concepts in estimating the sample size.

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)

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...

Predicting sample size required for classification performance

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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.

Improved sample size determination for attributes and variables sampling

International Nuclear Information System (INIS)

Stirpe, D.; Picard, R.R.

1985-01-01

Earlier INMM papers have addressed the attributes/variables problem and, under conservative/limiting approximations, have reported analytical solutions for the attributes and variables sample sizes. Through computer simulation of this problem, we have calculated attributes and variables sample sizes as a function of falsification, measurement uncertainties, and required detection probability without using approximations. Using realistic assumptions for uncertainty parameters of measurement, the simulation results support the conclusions: (1) previously used conservative approximations can be expensive because they lead to larger sample sizes than needed; and (2) the optimal verification strategy, as well as the falsification strategy, are highly dependent on the underlying uncertainty parameters of the measurement instruments. 1 ref., 3 figs

Experimental determination of size distributions: analyzing proper sample sizes

International Nuclear Information System (INIS)

Buffo, A; Alopaeus, V

2016-01-01

The measurement of various particle size distributions is a crucial aspect for many applications in the process industry. Size distribution is often related to the final product quality, as in crystallization or polymerization. In other cases it is related to the correct evaluation of heat and mass transfer, as well as reaction rates, depending on the interfacial area between the different phases or to the assessment of yield stresses of polycrystalline metals/alloys samples. The experimental determination of such distributions often involves laborious sampling procedures and the statistical significance of the outcome is rarely investigated. In this work, we propose a novel rigorous tool, based on inferential statistics, to determine the number of samples needed to obtain reliable measurements of size distribution, according to specific requirements defined a priori. Such methodology can be adopted regardless of the measurement technique used. (paper)

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

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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.

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

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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.

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.

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

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

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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.

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…

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

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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.

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.

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.

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

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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…

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

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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

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...

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

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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.

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.

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.

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.

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

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.

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

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,

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.

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.

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.

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.

Sample size determination for equivalence assessment with multiple endpoints.

Science.gov (United States)

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.

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.

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.

Sample size for morphological traits of pigeonpea

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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. 

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

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

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.

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

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.

Interpreting and Reporting Effect Sizes in Research Investigations.

Science.gov (United States)

Tapia, Martha; Marsh, George E., II

Since 1994, the American Psychological Association (APA) has advocated the inclusion of effect size indices in reporting research to elucidate the statistical significance of studies based on sample size. In 2001, the fifth edition of the APA "Publication Manual" stressed the importance of including an index of effect size to clarify…

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.

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

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

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.

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…

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.

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.

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

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

Numerical Evaluation of Size Effect on the Stress-Strain Behaviour of Geotextile-Reinforced Sand

DEFF Research Database (Denmark)

Hosseinpour, I.; Mirmoradi, S.H.; Barari, Amin

2010-01-01

This paper studies the effect of sample size on the stress-strain behavior and strength characteristics of geotextile reinforced sand using the finite element numerical analysis. The effect of sample size was investigated by studying the effects of varying the number of geotextile layers, the con......This paper studies the effect of sample size on the stress-strain behavior and strength characteristics of geotextile reinforced sand using the finite element numerical analysis. The effect of sample size was investigated by studying the effects of varying the number of geotextile layers...... on the mechanical behavior of reinforced sand decreases with an increase in the sample size....

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.

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.

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

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 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.

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.

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

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.

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.

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 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.

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.

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

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.

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.

Family Configuration and Achievement: Effects of Birth Order and Family Size in a Sample of Brothers.

Science.gov (United States)

Olneck, Michael R.; Bills, David B.

1979-01-01

Birth order effects in brothers were found to derive from difference in family size. Effects for family size were found even with socioeconomic background controlled. Nor were family size effects explained by parental ability. The importance of unmeasured preferences or economic resources that vary across families was suggested. (Author/RD)

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.

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

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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.

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.

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.

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

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...

Sample size requirements for separating out the effects of combination treatments: randomised controlled trials of combination therapy vs. standard treatment compared to factorial designs for patients with tuberculous meningitis.

Science.gov (United States)

Wolbers, Marcel; Heemskerk, Dorothee; Chau, Tran Thi Hong; Yen, Nguyen Thi Bich; Caws, Maxine; Farrar, Jeremy; Day, Jeremy

2011-02-02

In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 x 2 factorial design. We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 x 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the

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.

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.

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.

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)

What big size you have! Using effect sizes to determine the impact of public health nursing interventions.

Science.gov (United States)

Johnson, K E; McMorris, B J; Raynor, L A; Monsen, K A

2013-01-01

The Omaha System is a standardized interface terminology that is used extensively by public health nurses in community settings to document interventions and client outcomes. Researchers using Omaha System data to analyze the effectiveness of interventions have typically calculated p-values to determine whether significant client changes occurred between admission and discharge. However, p-values are highly dependent on sample size, making it difficult to distinguish statistically significant changes from clinically meaningful changes. Effect sizes can help identify practical differences but have not yet been applied to Omaha System data. We compared p-values and effect sizes (Cohen's d) for mean differences between admission and discharge for 13 client problems documented in the electronic health records of 1,016 young low-income parents. Client problems were documented anywhere from 6 (Health Care Supervision) to 906 (Caretaking/parenting) times. On a scale from 1 to 5, the mean change needed to yield a large effect size (Cohen's d ≥ 0.80) was approximately 0.60 (range = 0.50 - 1.03) regardless of p-value or sample size (i.e., the number of times a client problem was documented in the electronic health record). Researchers using the Omaha System should report effect sizes to help readers determine which differences are practical and meaningful. Such disclosures will allow for increased recognition of effective interventions.

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 ...

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.

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.

Sample size requirements for separating out the effects of combination treatments: Randomised controlled trials of combination therapy vs. standard treatment compared to factorial designs for patients with tuberculous meningitis

Directory of Open Access Journals (Sweden)

Farrar Jeremy

2011-02-01

Full Text Available Abstract Background In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 × 2 factorial design. Methods We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. Results In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Conclusions Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 × 2 factorial design to detect effects of

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.

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.

Sample Size Calculation for Controlling False Discovery Proportion

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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

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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

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...

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

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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.

Atomistic origin of size effects in fatigue behavior of metallic glasses

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Sha, Zhendong; Wong, Wei Hin; Pei, Qingxiang; Branicio, Paulo Sergio; Liu, Zishun; Wang, Tiejun; Guo, Tianfu; Gao, Huajian

2017-07-01

While many experiments and simulations on metallic glasses (MGs) have focused on their tensile ductility under monotonic loading, the fatigue mechanisms of MGs under cyclic loading still remain largely elusive. Here we perform molecular dynamics (MD) and finite element simulations of tension-compression fatigue tests in MGs to elucidate their fatigue mechanisms with focus on the sample size effect. Shear band (SB) thickening is found to be the inherent fatigue mechanism for nanoscale MGs. The difference in fatigue mechanisms between macroscopic and nanoscale MGs originates from whether the SB forms partially or fully through the cross-section of the specimen. Furthermore, a qualitative investigation of the sample size effect suggests that small sample size increases the fatigue life while large sample size promotes cyclic softening and necking. Our observations on the size-dependent fatigue behavior can be rationalized by the Gurson model and the concept of surface tension of the nanovoids. The present study sheds light on the fatigue mechanisms of MGs and can be useful in interpreting previous experimental results.

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

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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.

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

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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.…

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.

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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.

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

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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.

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

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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.

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

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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.

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

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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 sizes and model comparison metrics for species distribution models

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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

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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.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

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Manan Gupta

Full Text Available Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates

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

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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

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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…

What is the optimum sample size for the study of peatland testate amoeba assemblages?

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Mazei, Yuri A; Tsyganov, Andrey N; Esaulov, Anton S; Tychkov, Alexander Yu; Payne, Richard J

2017-10-01

Testate amoebae are widely used in ecological and palaeoecological studies of peatlands, particularly as indicators of surface wetness. To ensure data are robust and comparable it is important to consider methodological factors which may affect results. One significant question which has not been directly addressed in previous studies is how sample size (expressed here as number of Sphagnum stems) affects data quality. In three contrasting locations in a Russian peatland we extracted samples of differing size, analysed testate amoebae and calculated a number of widely-used indices: species richness, Simpson diversity, compositional dissimilarity from the largest sample and transfer function predictions of water table depth. We found that there was a trend for larger samples to contain more species across the range of commonly-used sample sizes in ecological studies. Smaller samples sometimes failed to produce counts of testate amoebae often considered minimally adequate. It seems likely that analyses based on samples of different sizes may not produce consistent data. Decisions about sample size need to reflect trade-offs between logistics, data quality, spatial resolution and the disturbance involved in sample extraction. For most common ecological applications we suggest that samples of more than eight Sphagnum stems are likely to be desirable. Copyright © 2017 Elsevier GmbH. All rights reserved.

Size effects in fcc crystals during the high rate compression test

International Nuclear Information System (INIS)

Yaghoobi, Mohammadreza; Voyiadjis, George Z.

2016-01-01

The present work studies the different mechanisms of size effects in fcc metallic samples of confined volumes during high rate compression tests using large scale atomistic simulation. Different mechanisms of size effects, including the dislocation starvation, source exhaustion, and dislocation source length effect are investigated for pillars with different sizes. The results show that the controlling mechanisms of size effects depend only on the pillar size and not on the value of applied strain. Dislocation starvation is the governing mechanism for very small pillars, i.e. pillars with diameters less than 30 nm. Increasing the pillar size, the dislocation exhaustion mechanism becomes active and there is no more source-limited activations. Next, the average dislocation source length is obtained and compared for pillars with different sizes. The results show that in the case of high rate deformations, the source length does not depend on the sample size, and the related size effects mechanisms are not active anymore. Also, in the case of high rate deformations, there are no size effects for pristine pillars with the diameters larger than 135 nm. In other words, increasing the strain rate decreases the pillar size at which there is no more size effects in the absence of strain gradient. The governing mechanisms of plastic deformation at high strain rate experiments are also different from those of the quasi-static tests. First, the diameter in which the dislocation nucleation at the free surface becomes the dominant mechanism changes from around 200 nm–30 nm. Next, in the case of the pillars with larger diameters, the plastic deformation is governed by the cross-slip instead of the operation of truncated dislocation sources, which is dominant at slower rates of deformation. In order to study the effects of pillar initial structure on the controlling mechanism of size effects, an initial loading and unloading procedure is conducted on some samples prior to the

[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.

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

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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

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 ...

R2 effect-size measures for mediation analysis.

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Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B

2009-05-01

R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.

R2 effect-size measures for mediation analysis

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Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.

2010-01-01

R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189

Effect of roll hot press temperature on crystallite size of PVDF film

Energy Technology Data Exchange (ETDEWEB)

Hartono, Ambran, E-mail: ambranhartono@yahoo.com; Sanjaya, Edi [Departement of Physics Faculty of Science and Technology, Islamic State University Syarif Hidayatullah , Jl. Juanda 95 Ciputat Jakarta (Indonesia); Djamal, Mitra; Satira, Suparno; Bahar, Herman [Theoretical High Energy Physics and Instrumentation Group Research, Faculty Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesa 10 Bandung (Indonesia); Ramli [Departement of Physics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Padang, Jl.Prof. Hamka, Padang 25131 (Indonesia)

2014-03-24

Fabrication PVDF films have been made using Hot Roll Press. Preparation of samples carried out for nine different temperatures. This condition is carried out to see the effect of Roll Hot Press temperature on the size of the crystallite of PVDF films. To obtain the diffraction pattern of sample characterization is performed using X-Ray Diffraction. Furthermore, from the diffraction pattern is obtained, the calculation to determine the crystallite size of the sample by using the Scherrer equation. From the experimental results and the calculation of crystallite sizes obtained for the samples with temperature 130 °C up to 170 °C respectively increased from 7.2 nm up to 20.54 nm. These results show that increasing temperatures will also increase the size of the crystallite of the sample. This happens because with the increasing temperature causes the higher the degree of crystallization of PVDF film sample is formed, so that the crystallite size also increases. This condition indicates that the specific volume or size of the crystals depends on the magnitude of the temperature as it has been studied by Nakagawa.

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/

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

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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 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.

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.

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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.

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.

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.

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.

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

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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.

A qualitative test for intrinsic size effect on ferroelectric phase transitions

OpenAIRE

Wang, Jin; Tagantsev, Alexander K.; Setter, Nava

2010-01-01

The size effect in ferroelectrics is treated as a competition between the geometrical symmetry of the ferroelectric sample and its crystalline symmetry. The manifestation of this competition is shown to be polarization rotation, which is driven by temperature and/or size variations, thus providing a qualitative indication of intrinsic finite size effect on ferroelectrics. The concept is demonstrated in a simple case of PbTiO3 nanowires having their axis parallel to [111]C direction, where the...

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)

Effect of coal stress on grain size of the gotten

Energy Technology Data Exchange (ETDEWEB)

Sikora, W; Tront, A

1988-09-01

Presents investigation results on the effect of seam stress and strain state on winning as measured by the grain size of the gotten. The investigations were carried out at the Institute of Mining Mechanization of the Silesian Politechnical where the relations between parameters of seams and cutters and their effect on coal grain size and energy consumption have been studied for several years. The effect was examined on coal samples taken from 4 mines in the Upper Silesian coal basin using a model of the system: seam - cutter. Cubic samples (400x400x400 mm) were tested on the CMG KOMAG test stand equipped with the POS-1 cutting apparatus. Two types of coal were distinguished: that particularly sensitive to increased pressure on seam and that only negligibly susceptible. Corresponding graphs of coal grain size versus vertical pressure are shown. A function has been developed that characterizes this sensitivity depending on a material parameter that can be determined by workability tests. The relationship between coal strength and grain size yield greater than 10 mm in the gotten depending on dynamic crushability of coal is shown in graphs. 6 refs.

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 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.

Distinguishing crystallite size effects from those of structural disorder ...

Indian Academy of Sciences (India)

Administrator

Both crystallite size effects and structural disorder contribute to the broadening of lines in .... ple contributions to the peak profiles. ... the fit is then corrected by accounting for sample ... Authors thank the Department of Science and Tech-.

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.

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.

Effect of grain size on corrosion of nanocrystalline copper in NaOH solution

International Nuclear Information System (INIS)

Luo Wei; Xu Yimin; Wang Qiming; Shi Peizhen; Yan Mi

2010-01-01

Research highlights: → Coppers display an active-passive-transpassive behaviour with duplex passive film. → Grain size variation has little effect on the overall corrosion behaviour of Cu. → Little effect on corrosion may be due to duplex passivation in NaOH solution. → Bulk nanocrystalline Cu show bamboo-like flake corrosion structure. - Abstract: Effect of grain size on corrosion of bulk nanocrystalline copper was investigated using potentiodynamic polarization measurements in 0.1 M NaOH solution. Bulk nanocrystalline copper was prepared by inert gas condensation and in situ warm compress (IGCWC) method. The grain sizes of all bulk nanocrystalline samples were determined to be 48, 68 and 92 nm using X-ray diffraction (XRD). Results showed that bulk coppers displayed an active-passive-transpassive behaviour with duplex passive films. From polycrystalline to nanocrystalline, grain size variation showed little effect on the overall corrosion resistance of copper samples.

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)

The effect of grain size and cement content on index properties of weakly solidified artificial sandstones

Science.gov (United States)

Atapour, Hadi; Mortazavi, Ali

2018-04-01

The effects of textural characteristics, especially grain size, on index properties of weakly solidified artificial sandstones are studied. For this purpose, a relatively large number of laboratory tests were carried out on artificial sandstones that were produced in the laboratory. The prepared samples represent fifteen sandstone types consisting of five different median grain sizes and three different cement contents. Indices rock properties including effective porosity, bulk density, point load strength index, and Schmidt hammer values (SHVs) were determined. Experimental results showed that the grain size has significant effects on index properties of weakly solidified sandstones. The porosity of samples is inversely related to the grain size and decreases linearly as grain size increases. While a direct relationship was observed between grain size and dry bulk density, as bulk density increased with increasing median grain size. Furthermore, it was observed that the point load strength index and SHV of samples increased as a result of grain size increase. These observations are indirectly related to the porosity decrease as a function of median grain size.

Effect of model choice and sample size on statistical tolerance limits

International Nuclear Information System (INIS)

Duran, B.S.; Campbell, K.

1980-03-01

Statistical tolerance limits are estimates of large (or small) quantiles of a distribution, quantities which are very sensitive to the shape of the tail of the distribution. The exact nature of this tail behavior cannot be ascertained brom small samples, so statistical tolerance limits are frequently computed using a statistical model chosen on the basis of theoretical considerations or prior experience with similar populations. This report illustrates the effects of such choices on the computations

Effect size calculation in meta-analyses of psychotherapy outcome research.

Science.gov (United States)

Hoyt, William T; Del Re, A C

2018-05-01

Meta-analysis of psychotherapy intervention research normally examines differences between treatment groups and some form of comparison group (e.g., wait list control; alternative treatment group). The effect of treatment is normally quantified as a standardized mean difference (SMD). We describe procedures for computing unbiased estimates of the population SMD from sample data (e.g., group Ms and SDs), and provide guidance about a number of complications that may arise related to effect size computation. These complications include (a) incomplete data in research reports; (b) use of baseline data in computing SMDs and estimating the population standard deviation (σ); (c) combining effect size data from studies using different research designs; and (d) appropriate techniques for analysis of data from studies providing multiple estimates of the effect of interest (i.e., dependent effect sizes). Clinical or Methodological Significance of this article: Meta-analysis is a set of techniques for producing valid summaries of existing research. The initial computational step for meta-analyses of research on intervention outcomes involves computing an effect size quantifying the change attributable to the intervention. We discuss common issues in the computation of effect sizes and provide recommended procedures to address them.

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.

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.

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.

Study of the interaction between the indentation size effect and Hall-Petch effect with spherical indenters on annealed polycrystalline copper

International Nuclear Information System (INIS)

Hou, X D; Bushby, A J; Jennett, N M

2008-01-01

Methods to obtain tensile stress-strain properties of materials from a practically non-destructive indentation test are of great industrial interest. Nanoindentation is a good candidate. However, to do this successfully, indentation size effects must be accounted for. An indentation size effect with spherical indenters has been shown for a range of fcc metals with relatively large grain size (Spary et al 2006 Phil. Mag. 86 5581-93); the increase in yield stress being proportional to the inverse cube root of indenter radius. Here, we investigate these differences further and present results for the indentation size effect with spherical indenters on Cu samples with a range of different grain sizes from 1 μm to single crystal. The important experimental control parameter, of the relative size of the indentation compared with the grain size, is also explored by using indenters of different radii on the different grain sized samples. When the grain size, d, is less than 6 times the radius of the projected contact area, a, a Hall-Petch-like behaviour is observed superimposed on the indentation size effect. For d > 6a the indentation size effect dominates. The two effects may be combined by addition in quadrature. This new parametric function is able to predict the indentation pressure in annealed copper given input values of indenter radius and grain size

Modeling size effects on fatigue life of a zirconium-based bulk metallic glass under bending

International Nuclear Information System (INIS)

Yuan Tao; Wang Gongyao; Feng Qingming; Liaw, Peter K.; Yokoyama, Yoshihiko; Inoue, Akihisa

2013-01-01

A size effect on the fatigue-life cycles of a Zr 50 Cu 30 Al 10 Ni 10 (at.%) bulk metallic glass has been observed in the four-point-bending fatigue experiment. Under the same bending-stress condition, large-sized samples tend to exhibit longer fatigue lives than small-sized samples. This size effect on the fatigue life cannot be satisfactorily explained by the flaw-based Weibull theories. Based on the experimental results, this study explores possible approaches to modeling the size effects on the bending-fatigue life of bulk metallic glasses, and proposes two fatigue-life models based on the Weibull distribution. The first model assumes, empirically, log-linear effects of the sample thickness on the Weibull parameters. The second model incorporates the mechanistic knowledge of the fatigue behavior of metallic glasses, and assumes that the shear-band density, instead of the flaw density, has significant influence on the bending fatigue-life cycles. Promising predictive results provide evidence of the potential validity of the models and their assumptions.

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

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.

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.)

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.

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.

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

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.

Effect Size in Efficacy Trials of Women With Decreased Sexual Desire.

Science.gov (United States)

Pyke, Robert E; Clayton, Anita H

2018-03-22

Regarding hypoactive sexual desire disorder (HSDD) in women, some reviewers judge the effect size small for medications vs placebo, but substantial for cognitive behavior therapy (CBT) or mindfulness meditation training (MMT) vs wait list. However, we lack comparisons of the effect sizes for the active intervention itself, for the control treatment, and for the differential between the two. For efficacy trials of HSDD in women, compare effect sizes for medications (testosterone/testosterone transdermal system, flibanserin, and bremelanotide) and placebo vs effect sizes for psychotherapy and wait-list control. We conducted a literature search for mean changes and SD on main measures of sexual desire and associated distress in trials of medications, CBT, or MMT. Effect size was used as it measures the magnitude of the intervention without confounding by sample size. Cohen d was used to determine effect sizes. For medications, mean (SD) effect size was 1.0 (0.34); for CBT and MMT, 1.0 (0.36); for placebo, 0.55 (0.16); and for wait list, 0.05 (0.26). Recommendations of psychotherapy over medication for treatment of HSDD are premature and not supported by data on effect sizes. Active participation in treatment conveys considerable non-specific benefits. Caregivers should attend to biological and psychosocial elements, and patient preference, to optimize response. Few clinical trials of psychotherapies were substantial in size or utilized adequate control paradigms. Medications and psychotherapies had similar, large effect sizes. Effect size of placebo was moderate. Effect size of wait-list control was very small, about one quarter that of placebo. Thus, a substantial non-specific therapeutic effect is associated with receiving placebo plus active care and evaluation. The difference in effect size between placebo and wait-list controls distorts the value of the subtraction of effect of the control paradigms to estimate intervention effectiveness. Pyke RE, Clayton AH

Size Effect Studies on Tensile Tests for Hot Stamping Steel

Science.gov (United States)

Chen, Xiaodu; Li, Yuanyuan; Han, Xianhong; Zhang, Junbo

2018-02-01

Tensile tests have been widely used to determine basic mechanical properties of materials. However, the properties measured may be related to geometrical factors of the tested samples especially for high-strength steels; this makes the properties' definitions and comparisons difficult. In this study, a series of tensile tests of ultra-high-strength hot-stamped steel were performed; the geometric shapes and sizes as well as the cutting direction were modified. The results demonstrate that the hot-stamped parts were isotropic and the cutting direction had no effect; the measured strengths were practically unrelated to the specimen geometries, including both size and shape. The elongations were slightly related to sample sizes within the studied range but highly depended on the sample shape, represented by the coefficient K. Such phenomena were analyzed and discussed based on microstructural observations and fracture morphologies. Moreover, two widely used elongation conversion equations, the Oliver formula and Barba's law, were introduced to verify their applicability, and a new interpolating function was developed and compared.

Effect size and statistical power in the rodent fear conditioning literature - A systematic review.

Science.gov (United States)

Carneiro, Clarissa F D; Moulin, Thiago C; Macleod, Malcolm R; Amaral, Olavo B

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.

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.

A closer look at the size of the gaze-liking effect: a preregistered replication.

Science.gov (United States)

Tipples, Jason; Pecchinenda, Anna

2018-04-30

This study is a direct replication of gaze-liking effect using the same design, stimuli and procedure. The gaze-liking effect describes the tendency for people to rate objects as more likeable when they have recently seen a person repeatedly gaze toward rather than away from the object. However, as subsequent studies show considerable variability in the size of this effect, we sampled a larger number of participants (N = 98) than the original study (N = 24) to gain a more precise estimate of the gaze-liking effect size. Our results indicate a much smaller standardised effect size (d z  = 0.02) than that of the original study (d z  = 0.94). Our smaller effect size was not due to general insensitivity to eye-gaze effects because the same sample showed a clear (d z  = 1.09) gaze-cuing effect - faster reaction times when eyes looked toward vs away from target objects. We discuss the implications of our findings for future studies wishing to study the gaze-liking effect.

A descriptive study of effect-size reporting in research reviews.

Science.gov (United States)

Floyd, Judith A

2017-06-01

To describe effect-size reporting in research reviews completed in support of evidence-based practice in nursing. Many research reviews report nurses' critical appraisal of level, quality and overall strength of evidence available to address clinical questions. Several studies of research-review quality suggest effect-size information would be useful to include in these reviews, but none focused on reviewers' attention to effect sizes. Descriptive. One hundred and four reviews indexed in CINAHL as systematic reviews and published from July 2012-February 2014 were examined. Papers were required to be peer-reviewed, written in English, contain an abstract and have at least one nurse author. Reviews were excluded if they did not use critical appraisal methods to address evidence of correlation, prediction or effectiveness. Data from remaining papers (N = 73) were extracted by three or more independent coders using a structured coding form and detailed codebook. Data were stored, viewed and analysed using Microsoft Office Excel ® spreadsheet functions. Sixteen percent (n = 12) of the sample contained effect-size information. Of the 12, six included all the effect-size information recommended by APA guidelines. Independent of completeness of reporting, seven contained discussion of effect sizes in the paper, but none included effect-size information in abstracts. Research reviews available to practicing nurses often fail to include information needed to accurately assess how much improvement may result from implementation of evidence-based policies, programs, protocols or practices. Manuscript reviewers are urged to hold authors to APA standards for reporting/discussing effect-size information in both primary research reports and research reviews. © 2016 John Wiley & Sons Ltd.

Effect size, confidence intervals and statistical power in psychological research.

Directory of Open Access Journals (Sweden)

Téllez A.

2015-07-01

Full Text Available Quantitative psychological research is focused on detecting the occurrence of certain population phenomena by analyzing data from a sample, and statistics is a particularly helpful mathematical tool that is used by researchers to evaluate hypotheses and make decisions to accept or reject such hypotheses. In this paper, the various statistical tools in psychological research are reviewed. The limitations of null hypothesis significance testing (NHST and the advantages of using effect size and its respective confidence intervals are explained, as the latter two measurements can provide important information about the results of a study. These measurements also can facilitate data interpretation and easily detect trivial effects, enabling researchers to make decisions in a more clinically relevant fashion. Moreover, it is recommended to establish an appropriate sample size by calculating the optimum statistical power at the moment that the research is designed. Psychological journal editors are encouraged to follow APA recommendations strictly and ask authors of original research studies to report the effect size, its confidence intervals, statistical power and, when required, any measure of clinical significance. Additionally, we must account for the teaching of statistics at the graduate level. At that level, students do not receive sufficient information concerning the importance of using different types of effect sizes and their confidence intervals according to the different types of research designs; instead, most of the information is focused on the various tools of NHST.

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

A methodology to investigate size scale effects in crystalline plasticity using uniaxial compression testing

International Nuclear Information System (INIS)

Uchic, Michael D.; Dimiduk, Dennis M.

2005-01-01

A methodology for performing uniaxial compression tests on samples having micron-size dimensions is presented. Sample fabrication is accomplished using focused ion beam milling to create cylindrical samples of uniform cross-section that remain attached to the bulk substrate at one end. Once fabricated, samples are tested in uniaxial compression using a nanoindentation device outfitted with a flat tip, and a stress-strain curve is obtained. The methodology can be used to examine the plastic response of samples of different sizes that are from the same bulk material. In this manner, dimensional size effects at the micron scale can be explored for single crystals, using a readily interpretable test that minimizes imposed stretch and bending gradients. The methodology was applied to a single-crystal Ni superalloy and a transition from bulk-like to size-affected behavior was observed for samples 5 μm in diameter and smaller

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.

Effect of particle size on degree of inversion in ferrites

International Nuclear Information System (INIS)

Siddique, M.; Butt, N.M.

2012-01-01

Ferrites with the spinel structure are important materials because of their structural, magnetic and electrical properties. The suitability of these materials depends on both the intrinsic behavior of the material and the effects of the grain size. Moessbauer spectroscopy was employed to investigate the cation distribution and degree of inversion in bulk and nano sized particles of CuFe/sub 2/O/sub 4/, MnFe/sub 2/O/sub 4/ and NiFe/sub 2/O/sub 4/ ferrites. The Moessbauer spectra of all bulk ferrites showed complete magnetic behavior, whereas nanoparticle ferrites showed combination of ferromagnetic and superparamagnetic components. Moreover, the cation distribution in nanoparticle materials was also found to be different to that of their bulk counterparts indicating the particle size dependency. The inversion of Cu and Ni ions in bulk sample was greater than that of nanoparticles; whereas the inversion of Mn ions was less in bulk material as compared to the nanoparticles. Hence the degree of inversion decreased in CuFe/sub 2/O/sub 4/ and NiFe/sub 2/O/sub 4/ samples whereas, it increased in MnFe/sub 2/O/sub 4/ as the particle size decreased and thus showed the anomalous behavior in this case. The nanoparticle samples also showed paramagnetic behaviour due to superparamagnetism and this effect is more prominent in MnFe/sub 2/O/sub 4/. Moessbauer spectra of bulk and nanoparticles CuFe/sub 2/O/sub 4/ is shown. (Orig./A.B.)

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

Neutron moderation in a bulk sample and its effects on PGNAA setup geometry

International Nuclear Information System (INIS)

Al-Jarallah, M.I.; Naqvi, A.A.; Fazal-ur-Rehman,; Maselehuddin, M.; Abu-Jarad, F.; Raashid, M.

2003-01-01

In a prompt gamma ray neutron activation analysis (PGNAA) setup, the neutron moderation in the bulk sample also plays a key role. This can even dominate the thermalization effects of the external moderator in some cases. In order to study the neutron moderation effect in the bulk sample, moderators with two different sizes of the sample were tested at the King Fahd University of Petroleum and Minerals (KFUPM) PGNAA facility. In these tests, the thermal neutron relative intensity and prompt gamma ray yield from the two moderators were measured using nuclear track detectors (NTDs) and NaI detector, respectively. As predicted by Monte Carlo simulations, the measured intensity of thermal neutron inside the large sample cavity due to the external moderator was smaller than that from the smaller sample cavity. Due to its larger size, additional thermalization of neutrons will take place in the larger sample. In spite of smaller thermal neutron yield from the external moderator at the large sample location, higher yield of the prompt gamma ray was observed as compared to that from the smaller sample. This confirms the significance of neutron moderation effects in the bulk sample and can thereby affect the PGNAA geometry size. This allows larger samples in conjunction with smaller moderators in the PGNAA setup

Neutron moderation in a bulk sample and its effects on PGNAA setup geometry

Energy Technology Data Exchange (ETDEWEB)

Al-Jarallah, M.I. E-mail: mibrahim@kfupm.edu.sa; Naqvi, A.A.; Fazal-ur-Rehman,; Maselehuddin, M.; Abu-Jarad, F.; Raashid, M

2003-06-01

In a prompt gamma ray neutron activation analysis (PGNAA) setup, the neutron moderation in the bulk sample also plays a key role. This can even dominate the thermalization effects of the external moderator in some cases. In order to study the neutron moderation effect in the bulk sample, moderators with two different sizes of the sample were tested at the King Fahd University of Petroleum and Minerals (KFUPM) PGNAA facility. In these tests, the thermal neutron relative intensity and prompt gamma ray yield from the two moderators were measured using nuclear track detectors (NTDs) and NaI detector, respectively. As predicted by Monte Carlo simulations, the measured intensity of thermal neutron inside the large sample cavity due to the external moderator was smaller than that from the smaller sample cavity. Due to its larger size, additional thermalization of neutrons will take place in the larger sample. In spite of smaller thermal neutron yield from the external moderator at the large sample location, higher yield of the prompt gamma ray was observed as compared to that from the smaller sample. This confirms the significance of neutron moderation effects in the bulk sample and can thereby affect the PGNAA geometry size. This allows larger samples in conjunction with smaller moderators in the PGNAA setup.

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.

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...

Size effects in olivine control strength in low-temperature plasticity regime

Science.gov (United States)

Kumamoto, K. M.; Thom, C.; Wallis, D.; Hansen, L. N.; Armstrong, D. E. J.; Goldsby, D. L.; Warren, J. M.; Wilkinson, A. J.

2017-12-01

The strength of the lithospheric mantle during deformation by low-temperature plasticity controls a range of geological phenomena, including lithospheric-scale strain localization, the evolution of friction on deep seismogenic faults, and the flexure of tectonic plates. However, constraints on the strength of olivine in this deformation regime are difficult to obtain from conventional rock-deformation experiments, and previous results vary considerably. We demonstrate via nanoindentation that the strength of olivine in the low-temperature plasticity regime is dependent on the length-scale of the test, with experiments on smaller volumes of material exhibiting larger yield stresses. This "size effect" has previously been explained in engineering materials as a result of the role of strain gradients and associated geometrically necessary dislocations in modifying plastic behavior. The Hall-Petch effect, in which a material with a small grain size exhibits a higher strength than one with a large grain size, is thought to arise from the same mechanism. The presence of a size effect resolves discrepancies among previous experimental measurements of olivine, which were either conducted using indentation methods or were conducted on polycrystalline samples with small grain sizes. An analysis of different low-temperature plasticity flow laws extrapolated to room temperature reveals a power-law relationship between length-scale (grain size for polycrystalline deformation and contact radius for indentation tests) and yield strength. This suggests that data from samples with large inherent length scales best represent the plastic strength of the coarse-grained lithospheric mantle. Additionally, the plastic deformation of nanometer- to micrometer-sized asperities on fault surfaces may control the evolution of fault roughness due to their size-dependent strength.

The pack size effect: Influence on consumer perceptions of portion sizes

NARCIS (Netherlands)

Hieke, Sophie; Palascha, Aikaterini; Jola, Corinne; Wills, Josephine; Raats, Monique M.

2016-01-01

Larger portions as well as larger packs can lead to larger prospective consumption estimates, larger servings and increased consumption, described as 'portion-size effects' and 'pack size effects'. Although related, the effects of pack sizes on portion estimates have received less attention. While

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 ...

Finite-size effects on band structure of CdS nanocrystallites studied by positron annihilation

International Nuclear Information System (INIS)

Kar, Soumitra; Biswas, Subhajit; Chaudhuri, Subhadra; Nambissan, P.M.G.

2005-01-01

Quantum confinement effects in nanocrystalline CdS were studied using positrons as spectroscopic probes to explore the defect characteristics. The lifetime of positrons annihilating at the vacancy clusters on nanocrystalline grain surfaces increased remarkably consequent to the onset of such finite-size effects. The Doppler broadened line shape was also found to reflect rather sensitively such distinct changes in the electron momentum redistribution scanned by the positrons, owing to the widening of the band gap. The nanocrystalline sizes of the samples used were confirmed from x-ray diffraction and high resolution transmission electron microscopy and the optical absorption results supported the quantum size effects. Positron annihilation results indicated distinct qualitative changes between CdS nanorods and the bulk sample, notwithstanding the identical x-ray diffraction pattern and close resemblance of the optical absorption spectra. The results are promising in the event of positron annihilation being proved to be a very successful tool for the study of such finite-size effects in semiconductor nanoparticles

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

Science.gov (United States)

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.

Science.gov (United States)

Diaz, Francisco J; Berg, Michel J; Krebill, Ron; Welty, Timothy; Gidal, Barry E; Alloway, Rita; Privitera, Michael

2013-12-01

Due to concern and debate in the epilepsy medical community and to the current interest of the US Food and Drug Administration (FDA) in revising approaches to the approval of generic drugs, the FDA is currently supporting ongoing bioequivalence studies of antiepileptic drugs, the EQUIGEN studies. During the design of these crossover studies, the researchers could not find commercial or non-commercial statistical software that quickly allowed computation of sample sizes for their designs, particularly software implementing the FDA requirement of using random-effects linear models for the analyses of bioequivalence studies. This article presents tables for sample-size evaluations of average bioequivalence studies based on the two crossover designs used in the EQUIGEN studies: the four-period, two-sequence, two-formulation design, and the six-period, three-sequence, three-formulation design. Sample-size computations assume that random-effects linear models are used in bioequivalence analyses with crossover designs. Random-effects linear models have been traditionally viewed by many pharmacologists and clinical researchers as just mathematical devices to analyze repeated-measures data. In contrast, a modern view of these models attributes an important mathematical role in theoretical formulations in personalized medicine to them, because these models not only have parameters that represent average patients, but also have parameters that represent individual patients. Moreover, the notation and language of random-effects linear models have evolved over the years. Thus, another goal of this article is to provide a presentation of the statistical modeling of data from bioequivalence studies that highlights the modern view of these models, with special emphasis on power analyses and sample-size computations.

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…

Crystallite size effects in stacking faulted nickel hydroxide and its electrochemical behaviour

International Nuclear Information System (INIS)

Ramesh, T.N.

2009-01-01

β-Nickel hydroxide comprises a long range periodic arrangement of atoms with a stacking sequence of AC AC AC-having an ideal composition Ni(OH) 2 . Variation in the preparative conditions can lead to the changes in the stacking sequence (AC AC BA CB AC AC or AC AC AB AC AC). This type of variation in stacking sequence can result in the formation of stacking fault in nickel hydroxide. The stability of the stacking fault depends on the free energy content of the sample. Stacking faults in nickel hydroxide is essential for better electrochemical activity. Also there are reports correlating particle size to the better electrochemical activity. Here we present the effect of crystallite size on the stacking faulted nickel hydroxide samples. The electrochemical performance of stacking faulted nickel hydroxide with small crystallite size exchanges 0.8e/Ni, while the samples with larger crystallite size exchange 0.4e/Ni. Hence a right combination of crystallite size and stacking fault content has to be controlled for good electrochemical activity of nickel hydroxide

Sample size for monitoring sirex populations and their natural enemies

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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.

Significant Effect of Pore Sizes on Energy Storage in Nanoporous Carbon Supercapacitors.

Science.gov (United States)

Young, Christine; Lin, Jianjian; Wang, Jie; Ding, Bing; Zhang, Xiaogang; Alshehri, Saad M; Ahamad, Tansir; Salunkhe, Rahul R; Hossain, Shahriar A; Khan, Junayet Hossain; Ide, Yusuke; Kim, Jeonghun; Henzie, Joel; Wu, Kevin C-W; Kobayashi, Naoya; Yamauchi, Yusuke

2018-04-20

Mesoporous carbon can be synthesized with good control of surface area, pore-size distribution, and porous architecture. Although the relationship between porosity and supercapacitor performance is well known, there are no thorough reports that compare the performance of numerous types of carbon samples side by side. In this manuscript, we describe the performance of 13 porous carbon samples in supercapacitor devices. We suggest that there is a "critical pore size" at which guest molecules can pass through the pores effectively. In this context, the specific surface area (SSA) and pore-size distribution (PSD) are used to show the point at which the pore size crosses the threshold of critical size. These measurements provide a guide for the development of new kinds of carbon materials for supercapacitor devices. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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)

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).

Effect size and statistical power in the rodent fear conditioning literature – A systematic review

Science.gov (United States)

Macleod, Malcolm R.

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science. PMID:29698451

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

Effect of colour and relative product size (RPS) on consumer attitudes

OpenAIRE

Varsha Jain; Subhadip Roy; Adwita Pant

2013-01-01

Colour and visuals are used extensively by the advertisers of different product categories to attract consumer attention and create favourable attitude. Based on this premise, the present study aimed to explore the effect of colour and relative product size on the consumer attitudes incorporating the moderating role of product familiarity. An experimental design was used, with a sample size of 420 respondents of 18-25 years in a 3 (Product Size: Large/Med/Small) X 2 (Ad Colour: CL/BW) X 2 (Ge...

Zn incorporation in CuInSe2: Particle size and strain effects on ...

Indian Academy of Sciences (India)

Administrator

Zn incorporation in CuInSe2: Particle size and strain effects on microstructural ... size as well as tensile strain. The calculated ... X-ray diffraction analysis of CuInSe2 samples reported in figure 2 ... To estimate qualitative information regarding ...

Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

Science.gov (United States)

Boessen, Ruud; van der Baan, Frederieke; Groenwold, Rolf; Egberts, Antoine; Klungel, Olaf; Grobbee, Diederick; Knol, Mirjam; Roes, Kit

2013-01-01

Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design. Copyright © 2013 John Wiley & Sons, Ltd.

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

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

Hit size effectiveness in relation to the microdosimetric site size

International Nuclear Information System (INIS)

Varma, M.N.; Wuu, C.S.; Zaider, M.

1994-01-01

This paper examines the effect of site size (that is, the diameter of the microdosimetric volume) on the hit size effectiveness function (HSEF), q(y), for several endpoints relevant in radiation protection. A Bayesian and maximum entropy approach is used to solve the integral equations that determine, given microdosimetric spectra and measured initial slopes, the function q(y). All microdosimetric spectra have been calculated de novo. The somewhat surprising conclusion of this analysis is that site size plays only a minor role in selecting the hit size effectiveness function q(y). It thus appears that practical means (e.g. conventional proportional counters) are already at hand to actually implement the HSEF as a radiation protection tool. (Author)

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.

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.

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

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.

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.

Size effects in foams : Experiments and modeling

NARCIS (Netherlands)

Tekoglu, C.; Gibson, L. J.; Pardoen, T.; Onck, P. R.

Mechanical properties of cellular solids depend on the ratio of the sample size to the cell size at length scales where the two are of the same order of magnitude. Considering that the cell size of many cellular solids used in engineering applications is between 1 and 10 mm, it is not uncommon to

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.

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

Strong crystal size effect on deformation twinning

DEFF Research Database (Denmark)

Yu, Qian; Shan, Zhi-Wei; Li, Ju

2010-01-01

plasticity. Accompanying the transition in deformation mechanism, the maximum flow stress of the submicrometre-sized pillars was observed to saturate at a value close to titanium’s ideal strength9, 10. We develop a ‘stimulated slip’ model to explain the strong size dependence of deformation twinning......Deformation twinning1, 2, 3, 4, 5, 6 in crystals is a highly coherent inelastic shearing process that controls the mechanical behaviour of many materials, but its origin and spatio-temporal features are shrouded in mystery. Using micro-compression and in situ nano-compression experiments, here we...... find that the stress required for deformation twinning increases drastically with decreasing sample size of a titanium alloy single crystal7, 8, until the sample size is reduced to one micrometre, below which the deformation twinning is entirely replaced by less correlated, ordinary dislocation...

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 Effect on Acoustic Emission Characteristics of Coal-Rock Damage Evolution

Directory of Open Access Journals (Sweden)

Zhijie Wen

2017-01-01

Full Text Available Coal-gas outburst, rock burst, and other mine dynamic disasters are closely related to the instability and failure of coal-rock. Coal-rock is the assemblies of mineral particles of varying sizes and shapes bonded together by cementing materials. The damage and rupture process of coal-rock is accompanied by acoustic emission (AE, which can be used as an effective means to monitor and predict the instability of coal-rock body. In this manuscript, considering the size effect of coal-rock, the influence of different height to diameter ratio on the acoustic emission characteristics of coal-rock damage evolution was discussed by microparticle flow PFC2D software platform. The results show that coal-rock size influences the uniaxial compressive strength, peak strain, and elastic modulus of itself; the size effect has little effect on the acoustic emission law of coal-rock damage and the effects of the size of coal-rock samples on acoustic emission characteristics are mainly reflected in three aspects: the triggering time of acoustic emission, the strain range of strong acoustic emission, and the intensity of acoustic emission; the damage evolution of coal-rock specimen can be divided into 4 stages: initial damage, stable development, accelerated development, and damage.

Effect Sizes in Gifted Education Research

Science.gov (United States)

Gentry, Marcia; Peters, Scott J.

2009-01-01

Recent calls for reporting and interpreting effect sizes have been numerous, with the 5th edition of the "Publication Manual of the American Psychological Association" (2001) calling for the inclusion of effect sizes to interpret quantitative findings. Many top journals have required that effect sizes accompany claims of statistical significance.…

Information overload or search-amplified risk? Set size and order effects on decisions from experience.

Science.gov (United States)

Hills, Thomas T; Noguchi, Takao; Gibbert, Michael

2013-10-01

How do changes in choice-set size influence information search and subsequent decisions? Moreover, does information overload influence information processing with larger choice sets? We investigated these questions by letting people freely explore sets of gambles before choosing one of them, with the choice sets either increasing or decreasing in number for each participant (from two to 32 gambles). Set size influenced information search, with participants taking more samples overall, but sampling a smaller proportion of gambles and taking fewer samples per gamble, when set sizes were larger. The order of choice sets also influenced search, with participants sampling from more gambles and taking more samples overall if they started with smaller as opposed to larger choice sets. Inconsistent with information overload, information processing appeared consistent across set sizes and choice order conditions, reliably favoring gambles with higher sample means. Despite the lack of evidence for information overload, changes in information search did lead to systematic changes in choice: People who started with smaller choice sets were more likely to choose gambles with the highest expected values, but only for small set sizes. For large set sizes, the increase in total samples increased the likelihood of encountering rare events at the same time that the reduction in samples per gamble amplified the effect of these rare events when they occurred-what we call search-amplified risk. This led to riskier choices for individuals whose choices most closely followed the sample mean.

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

Sonographically guided fine-needle biopsy of thyroid nodules: the effects of nodule characteristics, sampling technique, and needle size on the adequacy of cytological material

International Nuclear Information System (INIS)

Degirmenci, B.; Haktanir, A.; Albayrak, R.; Acar, M.; Sahin, D.A.; Sahin, O.; Yucel, A.; Caliskan, G.

2007-01-01

Aim: To evaluate the effects of sonographic characteristics of thyroid nodules, the diameter of needle used for sampling, and sampling technique on obtaining sufficient cytological material (SCM). Materials and methods: We performed sonography-guided fine-needle biopsy (FNB) in 232 solid thyroid nodules. Size-, echogenicity, vascularity, and localization of all nodules were evaluated by Doppler sonography before the biopsy. Needles of size 20, 22, and 24 G were used for biopsy. The biopsy specimen was acquired using two different methods after localisation. In first method, the needle tip was advanced into the nodule in various positions using a to-and-fro motion whilst in the nodule, along with concurrent aspiration. In the second method, the needle was advanced vigorously using a to-and-fro motion within the nodule whilst being rotated on its axis (capillary-action technique). Results: The mean nodule size was 2.1 ± 1.3 cm (range 0.4-7.2 cm). SCM was acquired from 154 (66.4%) nodules by sonography-guided FNB. In 78 (33.6%) nodules, SCM could not be collected. There was no significant difference between nodules with different echogenicity and vascularity for SCM. Regarding the needle size, the lowest rate of SCM was obtained using 20 G needles (56.6%) and the highest rate of adequate material was obtained using 24 G needles (82.5%; p = 0.001). The SCM rate was 76.9% with the capillary-action technique versus 49.4% with the aspiration technique (p < 0.001). Conclusion: Selecting finer needles (24-25 G) for sonography-guided FNB of thyroid nodules and using the capillary-action technique decreased the rate of inadequate material in cytological examination

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.

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)

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 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 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.

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.

Size effects in shear interfaces

OpenAIRE

GARNIER, J

2001-01-01

In physical modelling (centrifuge tests, calibration chambers, laboratory tests), the size of the soil particles may not be negligible when compared to the dimensions of the models. Size effects may so disturb the response of the models and the experimental data obtained on these cannot be extended to true scale conditions. Different tests have been performed to study and quantify the size effects that may happen in shear interfaces between soils and structures : modified shear box tests, pul...

Size effect on deformation twinning in face-centred cubic single crystals: Experiments and modelling

International Nuclear Information System (INIS)

Liang, Z.Y.; De Hosson, J.T.M.; Huang, M.X.

2017-01-01

In addition to slip by dislocation glide, deformation twinning in small-sized metallic crystals also exhibits size effect, namely the twinning stress increases with decreasing sample size. In order to understand the underpinning mechanisms responsible for such effect, systematic experiments were carried out on the small-sized single-crystalline pillars of a twinning-induced plasticity steel with a face-centred cubic structure. The flow stress increases considerably with decreasing pillar diameter from 3 to 0.5 μm, demonstrating a substantial size effect with a power exponent of 0.43. Detailed microstructural characterization reveals that the plastic deformation of the present pillars is dominant by twinning, primarily via twin growth, indicating that the size effect should be related to deformation twinning instead of slip by dislocation glide. Subsequent modelling works indicate that twinning can be accomplished by the dissociation of the ion-radiation-induced vacancy Frank loops in the damaged subsurface layer of the pillars, and the size effect is attributed to the ion-radiation-induced compressive stress in the subsurface layer, which decreases with pillar diameter.

A Primer on Basic Effect Size Concepts.

Science.gov (United States)

Elmore, Patricia B.; Rotou, Ourania

The increased interest in reporting effect sizes means that it is necessary to consider what should be included in a primer on effect sizes. A review of papers on effect sizes and commonly repeated statistical analyses suggests that it is important to discuss effect sizes relative to bivariate correlation, t-tests, analysis of variance/covariance,…

ANALYSIS OF COMPANY SIZE, FINANCIAL LEVERAGE, AND PROFITABILITY AND ITS EFFECT TO CSR DISCLOSURE

Directory of Open Access Journals (Sweden)

Suskim Riantani

2015-09-01

Full Text Available This study aims to analyze and recognize the effect of financial performance measured through company size, financial leverage and profitability to Corporate Social Responsibility Disclosure (CSRD. The research was done in Tobacco Company listed in Indonesia Stock Exchange during period of 2007-2011. Descriptive analysis and verification method was used as the research method. The purposive sampling method was used to obtain the sample and there are three cigarette companies as the sample. Multiple linear regression and correlation analysis using t test and F test were applied as a technique of analysis. The test of the classical assumption such as the normality, multicollinearity, heteroscedasticity, and autocorrelation applied before the multiple linear regression. The result shows that the company size had positive and significant effect to the CSR disclosure, financial leverage does not show significant effect to the CSR disclosure, profitability does not have significant effect to the CSR disclosure during the investigation.

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)

Sparse feature learning for instrument identification: Effects of sampling and pooling methods.

Science.gov (United States)

Han, Yoonchang; Lee, Subin; Nam, Juhan; Lee, Kyogu

2016-05-01

Feature learning for music applications has recently received considerable attention from many researchers. This paper reports on the sparse feature learning algorithm for musical instrument identification, and in particular, focuses on the effects of the frame sampling techniques for dictionary learning and the pooling methods for feature aggregation. To this end, two frame sampling techniques are examined that are fixed and proportional random sampling. Furthermore, the effect of using onset frame was analyzed for both of proposed sampling methods. Regarding summarization of the feature activation, a standard deviation pooling method is used and compared with the commonly used max- and average-pooling techniques. Using more than 47 000 recordings of 24 instruments from various performers, playing styles, and dynamics, a number of tuning parameters are experimented including the analysis frame size, the dictionary size, and the type of frequency scaling as well as the different sampling and pooling methods. The results show that the combination of proportional sampling and standard deviation pooling achieve the best overall performance of 95.62% while the optimal parameter set varies among the instrument classes.

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.

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…

Size effects on electrical properties of chemically grown zinc oxide nanoparticles

Science.gov (United States)

Rathod, K. N.; Joshi, Zalak; Dhruv, Davit; Gadani, Keval; Boricha, Hetal; Joshi, A. D.; Solanki, P. S.; Shah, N. A.

2018-03-01

In the present article, we study ZnO nanoparticles grown by cost effective sol–gel technique for various electrical properties. Structural studies performed by x-ray diffraction (XRD) revealed hexagonal unit cell phase with no observed impurities. Transmission electron microscopy (TEM) and particle size analyzer showed increased average particle size due to agglomeration effect with higher sintering. Dielectric constant (ε‧) decreases with increase in frequency because of the disability of dipoles to follow higher electric field. With higher sintering, dielectric constant reduced owing to the important role of increased formation of oxygen vacancy defects. Universal dielectric response (UDR) was verified by straight line fitting of log (fε‧) versus log (f) plots. All samples exhibit UDR behavior and with higher sintering more contribution from crystal cores. Impedance studies suggest an important role of boundary density while Cole–Cole (Z″ versus Z‧) plots have been studied for the relaxation behavior of the samples. Average normalized change (ANC) in impedance has been studied for all the samples wherein boundaries play an important role. Frequency dependent electrical conductivity has been understood on the basis of Jonscher’s universal power law. Jonscher’s law fits suggest that conduction of charge carrier is possible in the context of correlated barrier hopping (CBH) mechanism for lower temperature sintered sample while for higher temperature sintered ZnO samples, Maxwell–Wagner (M–W) relaxation process has been determined.

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

The Effect of Sample Size and Data Numbering on Precision of Calibration Model to predict Soil Properties

Directory of Open Access Journals (Sweden)

H Mohamadi Monavar

2017-10-01

Full Text Available Introduction Precision agriculture (PA is a technology that measures and manages within-field variability, such as physical and chemical properties of soil. The nondestructive and rapid VIS-NIR technology detected a significant correlation between reflectance spectra and the physical and chemical properties of soil. On the other hand, quantitatively predict of soil factors such as nitrogen, carbon, cation exchange capacity and the amount of clay in precision farming is very important. The emphasis of this paper is comparing different techniques of choosing calibration samples such as randomly selected method, chemical data and also based on PCA. Since increasing the number of samples is usually time-consuming and costly, then in this study, the best sampling way -in available methods- was predicted for calibration models. In addition, the effect of sample size on the accuracy of the calibration and validation models was analyzed. Materials and Methods Two hundred and ten soil samples were collected from cultivated farm located in Avarzaman in Hamedan province, Iran. The crop rotation was mostly potato and wheat. Samples were collected from a depth of 20 cm above ground and passed through a 2 mm sieve and air dried at room temperature. Chemical analysis was performed in the soil science laboratory, faculty of agriculture engineering, Bu-ali Sina University, Hamadan, Iran. Two Spectrometer (AvaSpec-ULS 2048- UV-VIS and (FT-NIR100N were used to measure the spectral bands which cover the UV-Vis and NIR region (220-2200 nm. Each soil sample was uniformly tiled in a petri dish and was scanned 20 times. Then the pre-processing methods of multivariate scatter correction (MSC and base line correction (BC were applied on the raw signals using Unscrambler software. The samples were divided into two groups: one group for calibration 105 and the second group was used for validation. Each time, 15 samples were selected randomly and tested the accuracy of

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...

Size effects in manufacturing of metallic components

DEFF Research Database (Denmark)

Vollertsen, F; Biermann, D; Hansen, Hans Nørgaard

2009-01-01

In manufacturing of metallic components, the size of the part plays an important role for the process behaviour. This is due to so called size effects, which lead to changes in the process behaviour even if the relationship between the main geometrical features is kept constant. The aim...... of this paper is to give a systematic review on Such effects and their potential use or remedy. First, the typology of size effects will be explained, followed by a description of size effects on strength and tribology. The last three sections describe size effects on formability, forming processes and cutting...... processes. (C) 2009 CIRP....

Modelling the effect of size-asymmetric competition on size inequality

DEFF Research Database (Denmark)

Rasmussen, Camilla Ruø; Weiner, Jacob

2017-01-01

Abstract The concept of size asymmetry in resource competition among plants, in which larger individuals obtain a disproportionate share of contested resources, appears to be very straightforward, but the effects of size asymmetry on growth and size variation among individuals have proved...... to be controversial. It has often been assumed that competition among individual plants in a population has to be size-asymmetric to result in higher size inequality than in the absence of competition, but here we question this inference. Using very simple, individual-based models, we investigate how size symmetry...... of competition affects the development in size inequality between two competing plants and show that increased size inequality due to competition is not always strong evidence for size-asymmetric competition. Even absolute symmetric competition, in which all plants receive the same amount of resources...

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.

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 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.

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.

Effect size estimates: current use, calculations, and interpretation.

Science.gov (United States)

Fritz, Catherine O; Morris, Peter E; Richler, Jennifer J

2012-02-01

The Publication Manual of the American Psychological Association (American Psychological Association, 2001, American Psychological Association, 2010) calls for the reporting of effect sizes and their confidence intervals. Estimates of effect size are useful for determining the practical or theoretical importance of an effect, the relative contributions of factors, and the power of an analysis. We surveyed articles published in 2009 and 2010 in the Journal of Experimental Psychology: General, noting the statistical analyses reported and the associated reporting of effect size estimates. Effect sizes were reported for fewer than half of the analyses; no article reported a confidence interval for an effect size. The most often reported analysis was analysis of variance, and almost half of these reports were not accompanied by effect sizes. Partial η2 was the most commonly reported effect size estimate for analysis of variance. For t tests, 2/3 of the articles did not report an associated effect size estimate; Cohen's d was the most often reported. We provide a straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis.

Effect of microfluidization on casein micelle size of bovine milk

Science.gov (United States)

Sinaga, H.; Deeth, H.; Bhandari, B.

2018-02-01

The properties of milk are likely to be dependent on the casein micelle size, and various processing technologies produce particular change in the average size of casein micelles. The main objective of this study was to manipulate casein micelle size by subjecting milk to microfluidizer. The experiment was performed as a complete block randomised design with three replications. The sample was passed through the microfluidizer at the set pressure of 83, 97, 112 and 126 MPa for one, two, three, four, five and six cycles, except for the 112 MPa. The results showed that microfluidized milk has smaller size by 3% with pressure up to 126 MPa. However, at each pressure, no further reduction was observed after increasing the passed up to 6 cycles. Although the average casein micelle size was similar, elevating pressure resulted in narrower size distribution. In contrast, increasing the number of cycles had little effect on casein micelle distribution. The finding from this study can be applied for future work to characterize the fundamental and functional properties of the treated milk.

A Generalized Least Squares Regression Approach for Computing Effect Sizes in Single-Case Research: Application Examples

Science.gov (United States)

Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.

2011-01-01

A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…

Brain vs behavior: an effect size comparison of neuroimaging and cognitive studies of genetic risk for schizophrenia.

LENUS (Irish Health Repository)

Rose, Emma Jane

2013-05-01

Genetic variants associated with increased risk for schizophrenia (SZ) are hypothesized to be more penetrant at the level of brain structure and function than at the level of behavior. However, to date the relative sensitivity of imaging vs cognitive measures of these variants has not been quantified. We considered effect sizes associated with cognitive and imaging studies of 9 robust SZ risk genes (DAOA, DISC1, DTNBP1, NRG1, RGS4, NRGN, CACNA1C, TCF4, and ZNF804A) published between January 2005-November 2011. Summary data was used to calculate estimates of effect size for each significant finding. The mean effect size for each study was categorized as small, medium, or large and the relative frequency of each category was compared between modalities and across genes. Random effects meta-analysis was used to consider the impact of experimental methodology on effect size. Imaging studies reported mostly medium or large effects, whereas cognitive investigations commonly reported small effects. Meta-analysis confirmed that imaging studies were associated with larger effects. Effect size estimates were negatively correlated with sample size but did not differ as a function of gene nor imaging modality. These observations support the notion that SZ risk variants show larger effects, and hence greater penetrance, when characterized using indices of brain structure and function than when indexed by cognitive measures. However, it remains to be established whether this holds true for individual risk variants, imaging modalities, or cognitive functions, and how such effects may be mediated by a relationship with sample size and other aspects of experimental variability.

Effect of the critical size of initial voids on stress-induced migration

International Nuclear Information System (INIS)

Aoyagi, Minoru

2004-01-01

The stress-induced migration phenomenon is one of the problems related to the reliability of metal interconnections in semiconductor devices. This phenomenon causes voids and fractures in interconnections. The basic feature of this phenomenon is vacancy migration to minute initial voids. Expanding initial voids grow into larger voids and fractures. The purpose of this work is to theoretically clarify the effects of residual thermal stress and void surface stress on the behavior of the initial voids which exist immediately after a passivation process. Using a spherical metal sample with a spherical void under external stress, vacancy absorption or emission was investigated between the void surface and the sample surface. The behavior of vacancies and atoms was also investigated in interconnections under residual thermal stress. We show that the void or sample surface becomes a vacancy sink or source, depending on the mutual relationship between the surface stress due to the surface-free energy and the residual thermal stress. We also reveal that the initial voids, which exist immediately after a passivation process, grow into larger voids and fractures when the size of the initial voids exceeds the critical size. If the size of the initial void can be controlled to below the critical size, voids and fractures do not occur

Effective population sizes of a major vector of human diseases, Aedes aegypti.

Science.gov (United States)

Saarman, Norah P; Gloria-Soria, Andrea; Anderson, Eric C; Evans, Benjamin R; Pless, Evlyn; Cosme, Luciano V; Gonzalez-Acosta, Cassandra; Kamgang, Basile; Wesson, Dawn M; Powell, Jeffrey R

2017-12-01

The effective population size ( N e ) is a fundamental parameter in population genetics that determines the relative strength of selection and random genetic drift, the effect of migration, levels of inbreeding, and linkage disequilibrium. In many cases where it has been estimated in animals, N e is on the order of 10%-20% of the census size. In this study, we use 12 microsatellite markers and 14,888 single nucleotide polymorphisms (SNPs) to empirically estimate N e in Aedes aegypti , the major vector of yellow fever, dengue, chikungunya, and Zika viruses. We used the method of temporal sampling to estimate N e on a global dataset made up of 46 samples of Ae. aegypti that included multiple time points from 17 widely distributed geographic localities. Our N e estimates for Ae. aegypti fell within a broad range (~25-3,000) and averaged between 400 and 600 across all localities and time points sampled. Adult census size (N c ) estimates for this species range between one and five thousand, so the N e / N c ratio is about the same as for most animals. These N e values are lower than estimates available for other insects and have important implications for the design of genetic control strategies to reduce the impact of this species of mosquito on human health.

The Effect of pH and High-Pressure Homogenization on Droplet Size

Directory of Open Access Journals (Sweden)

Ah Pis Yong

2017-12-01

Full Text Available The aims of this study are to revisit the effect of high pressure on homogenization and the influence of pH on the emulsion droplet sizes. The high-pressure homogenization (HPH involves two stages of processing, where the first stage involves in blending the coarse emulsion by a blender, and the second stage requires disruption of the coarse emulsion into smaller droplets by a high-pressure homogenizer. The pressure range in this review is in between 10-500 MPa. The homogenised droplet sizes can be reduced by increasing the homogenization recirculation, and there is a threshold point beyond that by applying pressure only, the size cannot be further reduced. Normally, homogenised emulsions are classified by their degree of kinetic stability. Dispersed phase present in the form of droplets while continuous phase also known as suspended droplets. With a proper homogenization recirculation and pressure, a more kinetically stable emulsion can be produced. The side effects of increasing homogenization pressure are that it can cause overprocessing of the emulsion droplets where the droplet sizes become larger rather than the expected smaller size. This can cause kinetic instability in the emulsion. The droplet size is usually measured by dynamic light scattering or by laser light scattering technique. The type of samples used in this reviews are such as chocolate and vanilla based powders; mean droplet sizes samples; basil oil; tomato; lupin protein; oil; skim milk, soymilk; coconut milk; tomato homogenate; corn; egg-yolk, rapeseed and sunflower; Poly(4-vinylpyridine/silica; and Complex 1 until complex 4 approaches from author case study. A relationship is developed between emulsion size and pH. Results clearly show that lower pH offers smaller droplet of emulsion and the opposite occurs when the pH is increased.

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.

Sample size requirements for one-year treatment effects using deep gray matter volume from 3T MRI in progressive forms of multiple sclerosis.

Science.gov (United States)

Kim, Gloria; Chu, Renxin; Yousuf, Fawad; Tauhid, Shahamat; Stazzone, Lynn; Houtchens, Maria K; Stankiewicz, James M; Severson, Christopher; Kimbrough, Dorlan; Quintana, Francisco J; Chitnis, Tanuja; Weiner, Howard L; Healy, Brian C; Bakshi, Rohit

2017-11-01

The subcortical deep gray matter (DGM) develops selective, progressive, and clinically relevant atrophy in progressive forms of multiple sclerosis (PMS). This patient population is the target of active neurotherapeutic development, requiring the availability of outcome measures. We tested a fully automated MRI analysis pipeline to assess DGM atrophy in PMS. Consistent 3D T1-weighted high-resolution 3T brain MRI was obtained over one year in 19 consecutive patients with PMS [15 secondary progressive, 4 primary progressive, 53% women, age (mean±SD) 50.8±8.0 years, Expanded Disability Status Scale (median, range) 5.0, 2.0-6.5)]. DGM segmentation applied the fully automated FSL-FIRST pipeline ( http://fsl.fmrib.ox.ac.uk ). Total DGM volume was the sum of the caudate, putamen, globus pallidus, and thalamus. On-study change was calculated using a random-effects linear regression model. We detected one-year decreases in raw [mean (95% confidence interval): -0.749 ml (-1.455, -0.043), p = 0.039] and annualized [-0.754 ml/year (-1.492, -0.016), p = 0.046] total DGM volumes. A treatment trial for an intervention that would show a 50% reduction in DGM brain atrophy would require a sample size of 123 patients for a single-arm study (one-year run-in followed by one-year on-treatment). For a two-arm placebo-controlled one-year study, 242 patients would be required per arm. The use of DGM fraction required more patients. The thalamus, putamen, and globus pallidus, showed smaller effect sizes in their on-study changes than the total DGM; however, for the caudate, the effect sizes were somewhat larger. DGM atrophy may prove efficient as a short-term outcome for proof-of-concept neurotherapeutic trials in PMS.

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)

Do class size effects differ across grades?

DEFF Research Database (Denmark)

Nandrup, Anne Brink

size cap that creates exogenous variation in class sizes. Significant (albeit modest) negative effects of class size increases are found for children on primary school levels. The effects on math abilities are statistically different across primary and secondary school. Larger classes do not affect......This paper contributes to the class size literature by analyzing whether short-run class size effects are constant across grade levels in compulsory school. Results are based on administrative data on all pupils enroled in Danish public schools. Identification is based on a government-imposed class...

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.

Size Effects on the Strength of Metals

DEFF Research Database (Denmark)

Huang, Xiaoxu

2014-01-01

The grain size effect and the specimen size effect on the strength of metals are briefly reviewed with respect to their history and current status of research. It is revealed that the fundamental strengthening mechanisms responsible for these two types of size effect are to increase the resistanc...

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.

A re-examination of the effect of contextual group size on people's attitude to risk

Directory of Open Access Journals (Sweden)

Kazumi Shimizu

2011-02-01

Full Text Available Using Kahneman and Tversky's life-death decision paradigm, Wang and colleagues (e.g., Wang and Johnston, 1995; Wang, 1996a, 1996b, 1996c, 2008; Wang et al., 2001 have shown two characteristic phenomena regarding people's attitude to risk when the contextual group size is manipulated. In both positive and negative frames, people tend to take greater risks in life-death decisions as the contextual group size becomes smaller; this risk-seeking attitude is greater when framed positively than negatively. (This second characteristic often leads to the disappearance of the framing effect in small group contexts comprising of 6 or 60 people. Their results could shed new light on the effect of contextual group size on people's risk choice. However these results are usually observed in laboratory experiments with university student samples. This study aims to examine the external validity of these results through different ways of experimentation and with a different sample base. The first characteristic was replicated in both a face-to-face interview with a randomly selected sample of the Japanese general public, and a web-based experiment with a non-student sample, but not the second.

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.

Using e-mail recruitment and an online questionnaire to establish effect size: A worked example.

Science.gov (United States)

Kirkby, Helen M; Wilson, Sue; Calvert, Melanie; Draper, Heather

2011-06-09

Sample size calculations require effect size estimations. Sometimes, effect size estimations and standard deviation may not be readily available, particularly if efficacy is unknown because the intervention is new or developing, or the trial targets a new population. In such cases, one way to estimate the effect size is to gather expert opinion. This paper reports the use of a simple strategy to gather expert opinion to estimate a suitable effect size to use in a sample size calculation. Researchers involved in the design and analysis of clinical trials were identified at the University of Birmingham and via the MRC Hubs for Trials Methodology Research. An email invited them to participate.An online questionnaire was developed using the free online tool 'Survey Monkey©'. The questionnaire described an intervention, an electronic participant information sheet (e-PIS), which may increase recruitment rates to a trial. Respondents were asked how much they would need to see recruitment rates increased by, based on 90%. 70%, 50% and 30% baseline rates, (in a hypothetical study) before they would consider using an e-PIS in their research.Analyses comprised simple descriptive statistics. The invitation to participate was sent to 122 people; 7 responded to say they were not involved in trial design and could not complete the questionnaire, 64 attempted it, 26 failed to complete it. Thirty-eight people completed the questionnaire and were included in the analysis (response rate 33%; 38/115). Of those who completed the questionnaire 44.7% (17/38) were at the academic grade of research fellow 26.3% (10/38) senior research fellow, and 28.9% (11/38) professor. Dependent upon the baseline recruitment rates presented in the questionnaire, participants wanted recruitment rate to increase from 6.9% to 28.9% before they would consider using the intervention. This paper has shown that in situations where effect size estimations cannot be collected from previous research, opinions

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.

Sample design effects in landscape genetics

Science.gov (United States)

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Effect of granulation of geological samples in neutron transport measurements

International Nuclear Information System (INIS)

Woznicka, Urszula; Drozdowicz, Krzysztof; Gabanska, Barbara; Krynicka, Ewa; Igielski, Andrzej

2001-01-01

The thermal neutron absorption cross section is one of the parameters describing the transport of thermal neutrons in a medium. Theoretical descriptions and experiments which determine the absorption cross section have a wide literature for homogeneous media. The situation comes true e.g. for fluids or amorphous solids. There are many other media which should be treated as heterogeneous. Among others - geological materials. The material heterogeneity for the thermal neutron transport in a considered volume is understood here as an existence of many small regions which differ significantly in their macroscopic neutron diffusion parameters (defined by the absorption and transport cross sections). The final difference, which influences the neutron transport, comes from a combination of the absolute differences between the parameters and of sizes of regions (related to the neutron mean free paths). A rock can be naturally heterogeneous in the above meaning. Besides, it can happen that a preparation of the rock sample for a neutron measurement can increase its natural heterogeneity. (For example, when the rock material is crushed and the measured sample consists of the obtained grains). The question is which granulation is allowed to treat the sample material as still homogeneous, and from which size of the rock grains we have to consider a two-component medium. It has been experimentally proved that the effective absorption of thermal neutrons in a heterogeneous two-component material can significantly differ from the absorption in a homogeneous one which consists of the same elements. The final effect is dependent on a few factors: the macroscopic absorption cross sections of the components, their total mass contributions, and the size of the grains. The ratio of the effective absorption cross section of the heterogeneous material to the cross section of the equivalent homogeneous, is a measure of the heterogeneity effect on the thermal neutron absorption

Effects of grain size on the corrosion resistance of pure magnesium by cooling rate-controlled solidification

Science.gov (United States)

Liu, Yichi; Liu, Debao; You, Chen; Chen, Minfang

2015-09-01

The aim of this study was to investigate the effect of grain size on the corrosion resistance of pure magnesium developed for biomedical applications. High-purity magnesium samples with different grain size were prepared by the cooling rate-controlled solidification. Electrochemical and immersion tests were employed to measure the corrosion resistance of pure magnesium with different grain size. The electrochemical polarization curves indicated that the corrosion susceptibility increased as the grain size decrease. However, the electrochemical impedance spectroscopy (EIS) and immersion tests indicated that the corrosion resistance of pure magnesium is improved as the grain size decreases. The improvement in the corrosion resistance is attributed to refine grain can produce more uniform and density film on the surface of sample.

Deconstruction of Vulnerability to Complex Diseases: Enhanced Effect Sizes and Power of Intermediate Phenotypes

Directory of Open Access Journals (Sweden)

David Goldman

2007-01-01

Full Text Available The deconstruction of vulnerability to complex disease with the help of intermediate phenotypes, including the heritable and disease-associated endophenotypes, is a legacy of Henri Begleiter. Systematic searches for genes influencing complex disorders, including bipolar disorder, have recently been completed using whole genome association (WGA, identifying a series of validated loci. Using this information, it is possible to compare effect sizes of disease loci discovered in very large samples to the effect sizes of replicated functional loci determining intermediate phenotypes that are of essential interest in psychiatric disorders. It is shown that the genes influencing intermediate phenotypes tend to have a larger effect size. Furthermore, the WGA results reveal that the number of loci of large effect size for complex diseases is limited, and yet multiple functional loci have already been identified for intermediate phenotypes relevant to psychiatric diseases, and without the benefit of WGA.

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.

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.

Effects of Al(OH)O nanoparticle agglomerate size in epoxy resin on tension, bending, and fracture properties

Energy Technology Data Exchange (ETDEWEB)

Jux, Maximilian, E-mail: maximilian.jux@dlr.de [TU Braunschweig, Institute of Adaptronic and Functional Integration (IAF) (Germany); Finke, Benedikt [TU Braunschweig, Institute for Particle Technology (IPAT) (Germany); Mahrholz, Thorsten [DLR Braunschweig, Institute of Composite Structures and Adaptive Systems (FA) (Germany); Sinapius, Michael [TU Braunschweig, Institute of Adaptronic and Functional Integration (IAF) (Germany); Kwade, Arno; Schilde, Carsten [TU Braunschweig, Institute for Particle Technology (IPAT) (Germany)

2017-04-15

Several epoxy Al(OH)O (boehmite) dispersions in an epoxy resin are produced in a kneader to study the mechanistic correlation between the nanoparticle size and mechanical properties of the prepared nanocomposites. The agglomerate size is set by a targeted variation in solid content and temperature during dispersion, resulting in a different level of stress intensity and thus a different final agglomerate size during the process. The suspension viscosity was used for the estimation of stress energy in laminar shear flow. Agglomerate size measurements are executed via dynamic light scattering to ensure the quality of the produced dispersions. Furthermore, various nanocomposite samples are prepared for three-point bending, tension, and fracture toughness tests. The screening of the size effect is executed with at least seven samples per agglomerate size and test method. The variation of solid content is found to be a reliable method to adjust the agglomerate size between 138–354 nm during dispersion. The size effect on the Young’s modulus and the critical stress intensity is only marginal. Nevertheless, there is a statistically relevant trend showing a linear increase with a decrease in agglomerate size. In contrast, the size effect is more dominant to the sample’s strain and stress at failure. Unlike microscaled agglomerates or particles, which lead to embrittlement of the composite material, nanoscaled agglomerates or particles cause the composite elongation to be nearly of the same level as the base material. The observed effect is valid for agglomerate sizes between 138–354 nm and a particle mass fraction of 10 wt%.

Effects of Al(OH)O nanoparticle agglomerate size in epoxy resin on tension, bending, and fracture properties

International Nuclear Information System (INIS)

Jux, Maximilian; Finke, Benedikt; Mahrholz, Thorsten; Sinapius, Michael; Kwade, Arno; Schilde, Carsten

2017-01-01

Several epoxy Al(OH)O (boehmite) dispersions in an epoxy resin are produced in a kneader to study the mechanistic correlation between the nanoparticle size and mechanical properties of the prepared nanocomposites. The agglomerate size is set by a targeted variation in solid content and temperature during dispersion, resulting in a different level of stress intensity and thus a different final agglomerate size during the process. The suspension viscosity was used for the estimation of stress energy in laminar shear flow. Agglomerate size measurements are executed via dynamic light scattering to ensure the quality of the produced dispersions. Furthermore, various nanocomposite samples are prepared for three-point bending, tension, and fracture toughness tests. The screening of the size effect is executed with at least seven samples per agglomerate size and test method. The variation of solid content is found to be a reliable method to adjust the agglomerate size between 138–354 nm during dispersion. The size effect on the Young’s modulus and the critical stress intensity is only marginal. Nevertheless, there is a statistically relevant trend showing a linear increase with a decrease in agglomerate size. In contrast, the size effect is more dominant to the sample’s strain and stress at failure. Unlike microscaled agglomerates or particles, which lead to embrittlement of the composite material, nanoscaled agglomerates or particles cause the composite elongation to be nearly of the same level as the base material. The observed effect is valid for agglomerate sizes between 138–354 nm and a particle mass fraction of 10 wt%.

Modelling of Size Effect with Regularised Continua

Directory of Open Access Journals (Sweden)

H. Askes

2004-01-01

Full Text Available A nonlocal damage continuum and a viscoplastic damage continuum are used to model size effects. Three-point bending specimens are analysed, whereby a distinction is made between unnotched specimens, specimens with a constant notch and specimens with a proportionally scaled notch. Numerical finite element simulations have been performed for specimen sizes in a range of 1:64. Size effects are established in terms of nominal strength and compared to existing size effect models from the literature. 

The effect of journal impact factor, reporting conflicts, and reporting funding sources, on standardized effect sizes in back pain trials: a systematic review and meta-regression.

Science.gov (United States)

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

2015-11-30

Low back pain is a common and costly health complaint for which there are several moderately effective treatments. In some fields there is evidence that funder and financial conflicts are associated with trial outcomes. It is not clear whether effect sizes in back pain trials relate to journal impact factor, reporting conflicts of interest, or reporting funding. We performed a systematic review of English-language papers reporting randomised controlled trials of treatments for non-specific low back pain, published between 2006-2012. We modelled the relationship using 5-year journal impact factor, and categories of reported of conflicts of interest, and categories of reported funding (reported none and reported some, compared to not reporting these) using meta-regression, adjusting for sample size, and publication year. We also considered whether impact factor could be predicted by the direction of outcome, or trial sample size. We could abstract data to calculate effect size in 99 of 146 trials that met our inclusion criteria. Effect size is not associated with impact factor, reporting of funding source, or reporting of conflicts of interest. However, explicitly reporting 'no trial funding' is strongly associated with larger absolute values of effect size (adjusted β=1.02 (95 % CI 0.44 to 1.59), P=0.001). Impact factor increases by 0.008 (0.004 to 0.012) per unit increase in trial sample size (Psources of funding, and conflicts of interest reflects positively on research and publisher conduct in the field. Strong evidence of a large association between absolute magnitude of effect size and explicit reporting of 'no funding' suggests authors of unfunded trials are likely to report larger effect sizes, notwithstanding direction. This could relate in part to quality, resources, and/or how pragmatic a trial is.

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

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

Science.gov (United States)

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 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.

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.

Nanocoatings size effect in nanostructured films

CERN Document Server

Aliofkhazraei, Mahmood

2014-01-01

Size effect in structures has been taken into consideration over the last years. In comparison with coatings with micrometer-ranged thickness, nanostructured coatings usually enjoy better and appropriate properties, such as strength and resistance. These coatings enjoy unique magnetic properties and are used with the aim of producing surfaces resistant against erosion, lubricant system, cutting tools, manufacturing hardened sporadic alloys, being resistant against oxidation and corrosion. This book reviews researches on fabrication and classification of nanostructured coatings with focus on size effect in nanometric scale. Size effect on electrochemical, mechanical and physical properties of nanocoatings are presented.

Size effect for phase stability on Au–Cd–Ag of phase boundary composition

International Nuclear Information System (INIS)

Matsuoka, Yuki; Suzuki, Keiko; Kudo, Natsuko

2013-01-01

Highlights: ► Size and heat treatment effects of phase boundary composition Au 52.5−x Cd 47.5 Ag x were studied. ► The transformation temperature T 0 increases by quench. It is investigated that disordering of atoms and lattice defects make β-phase unstable. ► Downsizing sample decreased T 0 in β-phase, showed a tendency of increase in coexistent phase. ► Downsizing is supposed to make difficult nucleation for martensitic transformation. ► Increasing of surface ratio by downsizing of powder sample is estimated to make easy to transform from unstable β-phase to martensite phase. -- Abstract: Size and heat treatment effects on martensitic transformation of phase boundary composition Au 52.5−x Cd 47.5 Ag x were studied. Au 52.5−x Cd 47.5 Ag x has coexistent phase of β-phase and α-phase of fcc structure at x > 42 at.%. The transformation temperature T 0 decreases as Au is substituted on Ag over phase boundary. T 0 increases by quench in both case of bulk and powder. This behavior is investigated that disordering of atoms and lattice defects make β-phase (L2 1 , B2 or bcc) unstable. Size effect was also inspected. Downsizing sample decreased the transformation temperature in β-phase. On the contrary, the transformation temperature of the coexistent phase showed a tendency of increase. Downsizing is supposed to make difficult nucleation for martensitic transformation because of reduction of β-phase ordered volume. Increasing of surface (disorder structure) ratio by downsizing of powder sample is estimated to make easy to transform from unstable β-phase to martensite phase

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

Scale and size effects in dynamic fracture of concretes and rocks

Directory of Open Access Journals (Sweden)

Petrov Y.

2015-01-01

Full Text Available Structural-temporal approach based on the notion of incubation time is used for interpretation of strain-rate effects in the fracture process of concretes and rocks. It is established that temporal dependences of concretes and rocks are calculated by the incubation time criterion. Experimentally observed different relations between ultimate stresses of concrete and mortar in static and dynamic conditions are explained. It is obtained that compressive strength of mortar at a low strain rate is greater than that of concrete, but at a high strain rate the opposite is true. Influence of confinement pressure on the mechanism of dynamic strength for concretes and rocks is discussed. Both size effect and scale effect for concrete and rocks samples subjected to impact loading are analyzed. Statistical nature of a size effect contrasts to a scale effect that is related to the definition of a spatio-temporal representative volume determining the fracture event on the given scale level.

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.

Structural effect of size on interracial friendship.

Science.gov (United States)

Cheng, Siwei; Xie, Yu

2013-04-30

Social contexts exert structural effects on individuals' social relationships, including interracial friendships. In this study, we posit that, net of group composition, total context size has a distinct effect on interracial friendship. Under the assumptions of (i) maximization of preference in choosing a friend, (ii) multidimensionality of preference, and (iii) preference for same-race friends, we conducted analyses using microsimulation that yielded three main findings. First, increased context size decreases the likelihood of forming an interracial friendship. Second, the size effect increases with the number of preference dimensions. Third, the size effect is diluted by noise, i.e., the random component affecting friendship formation. Analysis of actual friendship data among 4,745 American high school students yielded results consistent with the main conclusion that increased context size promotes racial segregation and discourages interracial friendship.

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

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

Investigation of size-temperature effects in thin f;.lms of transition metals

International Nuclear Information System (INIS)

Loboda, V.B.; Protsenko, I.E.; Smolin, M.D.; Yaremenko, A.V.

1985-01-01

The temperature and size dependences are studied for specific rho and temperature coeficients of resistance of transition metal films obtained and annealed in the 10 -6 - 5x10 -7 Pa vacuum. The size dependence of lambda sub(g)(1-p), rho sub(db), R, r and rhosub(db)sup(v) parameters was calculated using the Tellier, Tosser and Pichard theory. The temperature dependence of the conductivity was investigated in the 80-700 K range. A conclusion is made that all differences between dependences rho(T) for thin and bulk samples may be explained by effects specific for films but presenting no class of new physical effects. The size dependence of the electron-phonon interaction near T>THETAsub(D) and proportionality factors in the approximating equation rho approximately Asub(1.2)xTsup(2) is obtained for Ni films

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.

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.

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.

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...

Size effect in the strength of concrete structures

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

The fracture mechanics size effect, as opposed to the Weibull statistical size effect, is a .... Solutions for TPB beam and a typical wedge-splitting geometry have been ..... Bazant Z P 1984 Size effect in blunt fracture: Concrete, rock, metal. J. Eng.

ANALYSIS OF COMPANY SIZE, FINANCIAL LEVERAGE, AND PROFITABILITY AND ITS EFFECT TO CSR DISCLOSURE

OpenAIRE

Suskim Riantani; Hafidz Nurzamzam

2015-01-01

This study aims to analyze and recognize the effect of financial performance measured through company size, financial leverage and profitability to Corporate Social Responsibility Disclosure (CSRD). The research was done in Tobacco Company listed in Indonesia Stock Exchange during period of 2007-2011. Descriptive analysis and verification method was used as the research method. The purposive sampling method was used to obtain the sample and there are three cigarette companies as the sample. M...

(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

Prevention of the Portion Size Effect

NARCIS (Netherlands)

I. Versluis (Iris)

2016-01-01

markdownabstractAn increase in the portion size leads to an increase in energy intake, a phenomenon which is also referred to as the portion size effect. The increase in portion sizes in recent years is regarded as an important contributor to the increase in the prevalence of obesity. Hence, the aim

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)

Estimation of the ancestral effective population sizes of African great apes under different selection regimes.

Science.gov (United States)

Schrago, Carlos G

2014-08-01

Reliable estimates of ancestral effective population sizes are necessary to unveil the population-level phenomena that shaped the phylogeny and molecular evolution of the African great apes. Although several methods have previously been applied to infer ancestral effective population sizes, an analysis of the influence of the selective regime on the estimates of ancestral demography has not been thoroughly conducted. In this study, three independent data sets under different selective regimes were used were composed to tackle this issue. The results showed that selection had a significant impact on the estimates of ancestral effective population sizes of the African great apes. The inference of the ancestral demography of African great apes was affected by the selection regime. The effects, however, were not homogeneous along the ancestral populations of great apes. The effective population size of the ancestor of humans and chimpanzees was more impacted by the selection regime when compared to the same parameter in the ancestor of humans, chimpanzees and gorillas. Because the selection regime influenced the estimates of ancestral effective population size, it is reasonable to assume that a portion of the discrepancy found in previous studies that inferred the ancestral effective population size may be attributable to the differential action of selection on the genes sampled.

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)

Effect of nano-oxide particle size on radiation resistance of iron–chromium alloys

Energy Technology Data Exchange (ETDEWEB)

Xu, Weizong; Li, Lulu [Department of Materials Science and Engineering, North Carolina State University, Raleigh, NC 27695 (United States); Valdez, James A. [Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Saber, Mostafa [Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97201 (United States); Zhu, Yuntian, E-mail: ytzhu@ncsu.edu [Department of Materials Science and Engineering, North Carolina State University, Raleigh, NC 27695 (United States); Koch, Carl C.; Scattergood, Ronald O. [Department of Materials Science and Engineering, North Carolina State University, Raleigh, NC 27695 (United States)

2016-02-15

Radiation resistance of Fe–14Cr alloys under 200 keV He irradiation at 500 °C was systematically investigated with varying sizes of nano oxide Zr, Hf and Cr particles. It is found that these nano oxide particles acted as effective sites for He bubble formation. By statistically analyzing 700–1500 He bubbles at the depth of about 150–700 nm from a series of HRTEM images for each sample, we established the variation of average He bubble size, He bubble density, and swelling percentage along the depth, and found them to be consistent with the He concentration profile calculated from the SIRM program. Oxide particles with sizes less than 3.5–4 nm are found most effective for enhancing radiation resistance in the studied alloy systems.

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

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.

The quantification of specimen size effects in the ductile-brittle transition for C-Mn steel

International Nuclear Information System (INIS)

Knee, N.; Worthington, P.J.; Moskovic, R.

1989-02-01

It is now generally accepted that the temperature range of the brittle to ductile transition, determined using fracture mechanics specimens, is dependent of the specimen size for ferritic steels. This size effect arises through increasing constraint at the crack tip as the specimen thickness increases together with an increasing volume of material sampled. The size effect can be quantified in terms of a shift in temperature for a given toughness level. This was determined in the present work from fracture toughness/temperature curves obtained by performing fracture toughness tests on eight 100 mm thick compact tension specimens and 40 25 mm thick compact tension specimens over the ductile-brittle transition range of a C-Mn steel. The emphasis is on the development of a practical methodology to quantify the size effect from a limited but still appreciable number of tests. (author)

Optimal sample size for predicting viability of cabbage and radish seeds based on near infrared spectra of single seeds

DEFF Research Database (Denmark)

Shetty, Nisha; Min, Tai-Gi; Gislum, René

2011-01-01

The effects of the number of seeds in a training sample set on the ability to predict the viability of cabbage or radish seeds are presented and discussed. The supervised classification method extended canonical variates analysis (ECVA) was used to develop a classification model. Calibration sub......-sets of different sizes were chosen randomly with several iterations and using the spectral-based sample selection algorithms DUPLEX and CADEX. An independent test set was used to validate the developed classification models. The results showed that 200 seeds were optimal in a calibration set for both cabbage...... using all 600 seeds in the calibration set. Thus, the number of seeds in the calibration set can be reduced by up to 67% without significant loss of classification accuracy, which will effectively enhance the cost-effectiveness of NIR spectral analysis. Wavelength regions important...

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...

Children's accuracy of portion size estimation using digital food images: effects of interface design and size of image on computer screen.

Science.gov (United States)

Baranowski, Tom; Baranowski, Janice C; Watson, Kathleen B; Martin, Shelby; Beltran, Alicia; Islam, Noemi; Dadabhoy, Hafza; Adame, Su-heyla; Cullen, Karen; Thompson, Debbe; Buday, Richard; Subar, Amy

2011-03-01

To test the effect of image size and presence of size cues on the accuracy of portion size estimation by children. Children were randomly assigned to seeing images with or without food size cues (utensils and checked tablecloth) and were presented with sixteen food models (foods commonly eaten by children) in varying portion sizes, one at a time. They estimated each food model's portion size by selecting a digital food image. The same food images were presented in two ways: (i) as small, graduated portion size images all on one screen or (ii) by scrolling across large, graduated portion size images, one per sequential screen. Laboratory-based with computer and food models. Volunteer multi-ethnic sample of 120 children, equally distributed by gender and ages (8 to 13 years) in 2008-2009. Average percentage of correctly classified foods was 60·3 %. There were no differences in accuracy by any design factor or demographic characteristic. Multiple small pictures on the screen at once took half the time to estimate portion size compared with scrolling through large pictures. Larger pictures had more overestimation of size. Multiple images of successively larger portion sizes of a food on one computer screen facilitated quicker portion size responses with no decrease in accuracy. This is the method of choice for portion size estimation on a computer.

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...

The influence of tube voltage and phantom size in computed tomography on the dose-response relationship of dicentrics in human blood samples

International Nuclear Information System (INIS)

Jost, G; Pietsch, H; Lengsfeld, P; Voth, M; Schmid, E

2010-01-01

The aim of this study was to investigate the dose response relationship of dicentrics in human lymphocytes after CT scans at tube voltages of 80 and 140 kV. Blood samples from a healthy donor placed in tissue equivalent abdomen phantoms of standard, pediatric and adipose sizes were exposed at dose levels up to 0.1 Gy using a 64-slice CT scanner. It was found that both the tube voltage and the phantom size significantly influenced the CT scan-induced linear dose-response relationship of dicentrics in human lymphocytes. Using the same phantom (standard abdomen), 80 kV CT x-rays were biologically more effective than 140 kV CT x-rays. However, it could also be determined that the applied phantom size had much more influence on the biological effectiveness. Obviously, the increasing slopes of the CT scan-induced dose response relationships of dicentrics in human lymphocytes obtained in a pediatric, a standard and an adipose abdomen have been induced by scattering effects of photons, which strongly increase with increasing phantom size.

The influence of tube voltage and phantom size in computed tomography on the dose-response relationship of dicentrics in human blood samples

Energy Technology Data Exchange (ETDEWEB)

Jost, G; Pietsch, H [TRG Diagnostic Imaging, Bayer Schering Pharma AG, Berlin (Germany); Lengsfeld, P; Voth, M [Global Medical Affairs Diagnostic Imaging, Bayer Schering Pharma AG, Berlin (Germany); Schmid, E, E-mail: Ernst.Schmid@lrz.uni-muenchen.d [Institute for Cell Biology, Center for Integrated Protein Science, University of Munich (Germany)

2010-06-07

The aim of this study was to investigate the dose response relationship of dicentrics in human lymphocytes after CT scans at tube voltages of 80 and 140 kV. Blood samples from a healthy donor placed in tissue equivalent abdomen phantoms of standard, pediatric and adipose sizes were exposed at dose levels up to 0.1 Gy using a 64-slice CT scanner. It was found that both the tube voltage and the phantom size significantly influenced the CT scan-induced linear dose-response relationship of dicentrics in human lymphocytes. Using the same phantom (standard abdomen), 80 kV CT x-rays were biologically more effective than 140 kV CT x-rays. However, it could also be determined that the applied phantom size had much more influence on the biological effectiveness. Obviously, the increasing slopes of the CT scan-induced dose response relationships of dicentrics in human lymphocytes obtained in a pediatric, a standard and an adipose abdomen have been induced by scattering effects of photons, which strongly increase with increasing phantom size.

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

Science.gov (United States)

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

2016-06-01

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

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…

Do Between-Culture Differences Really Mean that People Are Different? A Look at Some Measures of Culture Effect Size.

Science.gov (United States)

Matsumoto, David; Grissom, Robert J.; Dinnel, Dale L.

2001-01-01

Recommends four measures of cultural effect size appropriate for cross-cultural research (standardized difference between two sample means, probabilistic superiority effect size measure, Cohen's U1, and point biserial correlation), demonstrating their efficacy on two data sets from previously published studies and arguing for their use in future…

How to Estimate and Interpret Various Effect Sizes