Sample size requirements for indirect association studies of gene-environment interactions (G x E).

PubMed

Hein, Rebecca; Beckmann, Lars; Chang-Claude, Jenny

2008-04-01

Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only.

Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes

PubMed Central

Wason, James M. S.; Mander, Adrian P.

2012-01-01

Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The proposed design performs well for a wider range of treatment effects and so is useful for Phase II trials. We compare the design to a previously used optimal design and show it has superior expected sample size properties. PMID:22651118

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jomekian, A.; Faculty of Chemical Engineering, Iran University of Science and Technology; Behbahani, R.M., E-mail: behbahani@put.ac.ir

Ultra porous ZIF-8 particles synthesized using PEO/PA6 based poly(ether-block-amide) (Pebax 1657) as structure directing agent. Structural properties of ZIF-8 samples prepared under different synthesis parameters were investigated by laser particle size analysis, XRD, N{sub 2} adsorption analysis, BJH and BET tests. The overall results showed that: (1) The mean pore size of all ZIF-8 samples increased remarkably (from 0.34 nm to 1.1–2.5 nm) compared to conventionally synthesized ZIF-8 samples. (2) Exceptional BET surface area of 1869 m{sup 2}/g was obtained for a ZIF-8 sample with mean pore size of 2.5 nm. (3) Applying high concentrations of Pebax 1657 to themore » synthesis solution lead to higher surface area, larger pore size and smaller particle size for ZIF-8 samples. (4) Both, Increase in temperature and decrease in molar ratio of MeIM/Zn{sup 2+} had increasing effect on ZIF-8 particle size, pore size, pore volume, crystallinity and BET surface area of all investigated samples. - Highlights: • The pore size of ZIF-8 samples synthesized with Pebax 1657 increased remarkably. • The BET surface area of 1869 m{sup 2}/gr obtained for a ZIF-8 synthesized sample with Pebax. • Increase in temperature had increasing effect on textural properties of ZIF-8 samples. • Decrease in MeIM/Zn{sup 2+} had increasing effect on textural properties of ZIF-8 samples.« less

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

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2016-01-01

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

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

ERIC Educational Resources Information Center

Dong, Nianbo; Maynard, Rebecca

2013-01-01

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

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

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

PubMed

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

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

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

PubMed

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 maximum SD from 10 samples were used. Greater sample size is needed to achieve a higher proportion of studies having actual power of 80%. This study only addressed sample size calculation for continuous outcome variables. We recommend using the 60% UCL of SD, maximum SD, 80th-percentile SD, and 75th-percentile SD to calculate sample size when 1 or 2 samples, 3 samples, 4-5 samples, and more than 5 samples of data are available, respectively. Using the sample SD or average SD to calculate sample size should be avoided.

Generalized SAMPLE SIZE Determination Formulas for Investigating Contextual Effects by a Three-Level Random Intercept Model.

PubMed

Usami, Satoshi

2017-03-01

Behavioral and psychological researchers have shown strong interests in investigating contextual effects (i.e., the influences of combinations of individual- and group-level predictors on individual-level outcomes). The present research provides generalized formulas for determining the sample size needed in investigating contextual effects according to the desired level of statistical power as well as width of confidence interval. These formulas are derived within a three-level random intercept model that includes one predictor/contextual variable at each level to simultaneously cover various kinds of contextual effects that researchers can show interest. The relative influences of indices included in the formulas on the standard errors of contextual effects estimates are investigated with the aim of further simplifying sample size determination procedures. In addition, simulation studies are performed to investigate finite sample behavior of calculated statistical power, showing that estimated sample sizes based on derived formulas can be both positively and negatively biased due to complex effects of unreliability of contextual variables, multicollinearity, and violation of assumption regarding the known variances. Thus, it is advisable to compare estimated sample sizes under various specifications of indices and to evaluate its potential bias, as illustrated in the example.

Sample size determination for mediation analysis of longitudinal data.

PubMed

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.

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

PubMed

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 calculations for randomized clinical trials published in anesthesiology journals: a comparison of 2010 versus 2016.

PubMed

Chow, Jeffrey T Y; Turkstra, Timothy P; Yim, Edmund; Jones, Philip M

2018-06-01

Although every randomized clinical trial (RCT) needs participants, determining the ideal number of participants that balances limited resources and the ability to detect a real effect is difficult. Focussing on two-arm, parallel group, superiority RCTs published in six general anesthesiology journals, the objective of this study was to compare the quality of sample size calculations for RCTs published in 2010 vs 2016. Each RCT's full text was searched for the presence of a sample size calculation, and the assumptions made by the investigators were compared with the actual values observed in the results. Analyses were only performed for sample size calculations that were amenable to replication, defined as using a clearly identified outcome that was continuous or binary in a standard sample size calculation procedure. The percentage of RCTs reporting all sample size calculation assumptions increased from 51% in 2010 to 84% in 2016. The difference between the values observed in the study and the expected values used for the sample size calculation for most RCTs was usually > 10% of the expected value, with negligible improvement from 2010 to 2016. While the reporting of sample size calculations improved from 2010 to 2016, the expected values in these sample size calculations often assumed effect sizes larger than those actually observed in the study. Since overly optimistic assumptions may systematically lead to underpowered RCTs, improvements in how to calculate and report sample sizes in anesthesiology research are needed.

Sampling strategies for estimating brook trout effective population size

Treesearch

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

2012-01-01

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

Sample Size Calculations for Precise Interval Estimation of the Eta-Squared Effect Size

ERIC Educational Resources Information Center

Shieh, Gwowen

2015-01-01

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Analysis of Sample Size, Counting Time, and Plot Size from an Avian Point Count Survey on Hoosier National Forest, Indiana

Treesearch

Frank R. Thompson; Monica J. Schwalbach

1995-01-01

We report results of a point count survey of breeding birds on Hoosier National Forest in Indiana. We determined sample size requirements to detect differences in means and the effects of count duration and plot size on individual detection rates. Sample size requirements ranged from 100 to >1000 points with Type I and II error rates of <0.1 and 0.2. Sample...

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

PubMed

Bergh, Daniel

2015-01-01

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

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

PubMed

Cui, Zaixu; Gong, Gaolang

2018-06-02

Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accuracies. However, the effects of the ML regression algorithm and sample size on individualized behavioral/cognitive prediction performance have not been comprehensively assessed. To address this issue, the present study included six commonly used ML regression algorithms: ordinary least squares (OLS) regression, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic-net regression, linear support vector regression (LSVR), and relevance vector regression (RVR), to perform specific behavioral/cognitive predictions based on different sample sizes. Specifically, the publicly available resting-state functional MRI (rs-fMRI) dataset from the Human Connectome Project (HCP) was used, and whole-brain resting-state functional connectivity (rsFC) or rsFC strength (rsFCS) were extracted as prediction features. Twenty-five sample sizes (ranged from 20 to 700) were studied by sub-sampling from the entire HCP cohort. The analyses showed that rsFC-based LASSO regression performed remarkably worse than the other algorithms, and rsFCS-based OLS regression performed markedly worse than the other algorithms. Regardless of the algorithm and feature type, both the prediction accuracy and its stability exponentially increased with increasing sample size. The specific patterns of the observed algorithm and sample size effects were well replicated in the prediction using re-testing fMRI data, data processed by different imaging preprocessing schemes, and different behavioral/cognitive scores, thus indicating excellent robustness/generalization of the effects. The current findings provide critical insight into how the selected ML regression algorithm and sample size influence individualized predictions of behavior/cognition and offer important guidance for choosing the ML regression algorithm or sample size in relevant investigations. Copyright © 2018 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

PubMed

Herzog, Sereina A; Low, Nicola; Berghold, Andrea

2015-06-19

The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis

PubMed Central

Adnan, Tassha Hilda

2016-01-01

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

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference

PubMed Central

Karcher, Michael D.; Palacios, Julia A.; Bedford, Trevor; Suchard, Marc A.; Minin, Vladimir N.

2016-01-01

Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals’ genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples. PMID:26938243

Reproducibility of preclinical animal research improves with heterogeneity of study samples

PubMed Central

Vogt, Lucile; Sena, Emily S.; Würbel, Hanno

2018-01-01

Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research. PMID:29470495

Atomistic origin of size effects in fatigue behavior of metallic glasses

NASA Astrophysics Data System (ADS)

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 and Allocation of Effort in Point Count Sampling of Birds in Bottomland Hardwood Forests

Treesearch

Winston P. Smith; Daniel J. Twedt; Robert J. Cooper; David A. Wiedenfeld; Paul B. Hamel; Robert P. Ford

1995-01-01

To examine sample size requirements and optimum allocation of effort in point count sampling of bottomland hardwood forests, we computed minimum sample sizes from variation recorded during 82 point counts (May 7-May 16, 1992) from three localities containing three habitat types across three regions of the Mississippi Alluvial Valley (MAV). Also, we estimated the effect...

Monitoring Species of Concern Using Noninvasive Genetic Sampling and Capture-Recapture Methods

DTIC Science & Technology

2016-11-01

ABBREVIATIONS AICc Akaike’s Information Criterion with small sample size correction AZGFD Arizona Game and Fish Department BMGR Barry M. Goldwater...MNKA Minimum Number Known Alive N Abundance Ne Effective Population Size NGS Noninvasive Genetic Sampling NGS-CR Noninvasive Genetic...parameter estimates from capture-recapture models require sufficient sample sizes , capture probabilities and low capture biases. For NGS-CR, sample

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

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

NASA Astrophysics Data System (ADS)

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.

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the principles are long known, historically, sample size determination has been difficult, because of relatively complex mathematical considerations and numerous different formulas. However, of late, there has been remarkable improvement in the availability, capability, and user-friendliness of power and sample size determination software. Many can execute routines for determination of sample size and power for a wide variety of research designs and statistical tests. With the drudgery of mathematical calculation gone, researchers must now concentrate on determining appropriate sample size and achieving these targets, so that study conclusions can be accepted as meaningful. PMID:27688437

Meta-analysis of multiple outcomes: a multilevel approach.

PubMed

Van den Noortgate, Wim; López-López, José Antonio; Marín-Martínez, Fulgencio; Sánchez-Meca, Julio

2015-12-01

In meta-analysis, dependent effect sizes are very common. An example is where in one or more studies the effect of an intervention is evaluated on multiple outcome variables for the same sample of participants. In this paper, we evaluate a three-level meta-analytic model to account for this kind of dependence, extending the simulation results of Van den Noortgate, López-López, Marín-Martínez, and Sánchez-Meca Behavior Research Methods, 45, 576-594 (2013) by allowing for a variation in the number of effect sizes per study, in the between-study variance, in the correlations between pairs of outcomes, and in the sample size of the studies. At the same time, we explore the performance of the approach if the outcomes used in a study can be regarded as a random sample from a population of outcomes. We conclude that although this approach is relatively simple and does not require prior estimates of the sampling covariances between effect sizes, it gives appropriate mean effect size estimates, standard error estimates, and confidence interval coverage proportions in a variety of realistic situations.

Accounting for missing data in the estimation of contemporary genetic effective population size (N(e) ).

PubMed

Peel, D; Waples, R S; Macbeth, G M; Do, C; Ovenden, J R

2013-03-01

Theoretical models are often applied to population genetic data sets without fully considering the effect of missing data. Researchers can deal with missing data by removing individuals that have failed to yield genotypes and/or by removing loci that have failed to yield allelic determinations, but despite their best efforts, most data sets still contain some missing data. As a consequence, realized sample size differs among loci, and this poses a problem for unbiased methods that must explicitly account for random sampling error. One commonly used solution for the calculation of contemporary effective population size (N(e) ) is to calculate the effective sample size as an unweighted mean or harmonic mean across loci. This is not ideal because it fails to account for the fact that loci with different numbers of alleles have different information content. Here we consider this problem for genetic estimators of contemporary effective population size (N(e) ). To evaluate bias and precision of several statistical approaches for dealing with missing data, we simulated populations with known N(e) and various degrees of missing data. Across all scenarios, one method of correcting for missing data (fixed-inverse variance-weighted harmonic mean) consistently performed the best for both single-sample and two-sample (temporal) methods of estimating N(e) and outperformed some methods currently in widespread use. The approach adopted here may be a starting point to adjust other population genetics methods that include per-locus sample size components. © 2012 Blackwell Publishing Ltd.

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

PubMed Central

Vavrek, Matthew J.

2015-01-01

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes. PMID:25780770

Sampling Theory and Confidence Intervals for Effect Sizes: Using ESCI To Illustrate "Bouncing"; Confidence Intervals.

ERIC Educational Resources Information Center

Du, Yunfei

This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartono, Ambran, E-mail: ambranhartono@yahoo.com; Sanjaya, Edi; Djamal, Mitra

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 respectivelymore » 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.« less

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

PubMed Central

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.; Hoffmann, Udo; Douglas, Pamela S.; Einstein, Andrew J.

2014-01-01

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample size required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence. PMID:24694150

Treatment Trials for Neonatal Seizures: The Effect of Design on Sample Size

PubMed Central

Stevenson, Nathan J.; Boylan, Geraldine B.; Hellström-Westas, Lena; Vanhatalo, Sampsa

2016-01-01

Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (Td) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, Td and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in Td between groups in analysis will be valid and minimise sample size. PMID:27824913

Investigation of the Specht density estimator

NASA Technical Reports Server (NTRS)

Speed, F. M.; Rydl, L. M.

1971-01-01

The feasibility of using the Specht density estimator function on the IBM 360/44 computer is investigated. Factors such as storage, speed, amount of calculations, size of the smoothing parameter and sample size have an effect on the results. The reliability of the Specht estimator for normal and uniform distributions and the effects of the smoothing parameter and sample size are investigated.

Effect of sample area and sieve size on benthic macrofaunal community condition assessments in California enclosed bays and estuaries.

PubMed

Hammerstrom, Kamille K; Ranasinghe, J Ananda; Weisberg, Stephen B; Oliver, John S; Fairey, W Russell; Slattery, Peter N; Oakden, James M

2012-10-01

Benthic macrofauna are used extensively for environmental assessment, but the area sampled and sieve sizes used to capture animals often differ among studies. Here, we sampled 80 sites using 3 different sized sampling areas (0.1, 0.05, 0.0071 m(2)) and sieved those sediments through each of 2 screen sizes (0.5, 1 mm) to evaluate their effect on number of individuals, number of species, dominance, nonmetric multidimensional scaling (MDS) ordination, and benthic community condition indices that are used to assess sediment quality in California. Sample area had little effect on abundance but substantially affected numbers of species, which are not easily scaled to a standard area. Sieve size had a substantial effect on both measures, with the 1-mm screen capturing only 74% of the species and 68% of the individuals collected in the 0.5-mm screen. These differences, though, had little effect on the ability to differentiate samples along gradients in ordination space. Benthic indices generally ranked sample condition in the same order regardless of gear, although the absolute scoring of condition was affected by gear type. The largest differences in condition assessment were observed for the 0.0071-m(2) gear. Benthic indices based on numbers of species were more affected than those based on relative abundance, primarily because we were unable to scale species number to a common area as we did for abundance. Copyright © 2010 SETAC.

Sampling the structure and chemical order in assemblies of ferromagnetic nanoparticles by nuclear magnetic resonance

PubMed Central

Liu, Yuefeng; Luo, Jingjie; Shin, Yooleemi; Moldovan, Simona; Ersen, Ovidiu; Hébraud, Anne; Schlatter, Guy; Pham-Huu, Cuong; Meny, Christian

2016-01-01

Assemblies of nanoparticles are studied in many research fields from physics to medicine. However, as it is often difficult to produce mono-dispersed particles, investigating the key parameters enhancing their efficiency is blurred by wide size distributions. Indeed, near-field methods analyse a part of the sample that might not be representative of the full size distribution and macroscopic methods give average information including all particle sizes. Here, we introduce temperature differential ferromagnetic nuclear resonance spectra that allow sampling the crystallographic structure, the chemical composition and the chemical order of non-interacting ferromagnetic nanoparticles for specific size ranges within their size distribution. The method is applied to cobalt nanoparticles for catalysis and allows extracting the size effect from the crystallographic structure effect on their catalytic activity. It also allows sampling of the chemical composition and chemical order within the size distribution of alloyed nanoparticles and can thus be useful in many research fields. PMID:27156575

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

PubMed

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.

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

PubMed

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

2008-08-28

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

Long-term effective population size dynamics of an intensively monitored vertebrate population

PubMed Central

Mueller, A-K; Chakarov, N; Krüger, O; Hoffman, J I

2016-01-01

Long-term genetic data from intensively monitored natural populations are important for understanding how effective population sizes (Ne) can vary over time. We therefore genotyped 1622 common buzzard (Buteo buteo) chicks sampled over 12 consecutive years (2002–2013 inclusive) at 15 microsatellite loci. This data set allowed us to both compare single-sample with temporal approaches and explore temporal patterns in the effective number of parents that produced each cohort in relation to the observed population dynamics. We found reasonable consistency between linkage disequilibrium-based single-sample and temporal estimators, particularly during the latter half of the study, but no clear relationship between annual Ne estimates () and census sizes. We also documented a 14-fold increase in between 2008 and 2011, a period during which the census size doubled, probably reflecting a combination of higher adult survival and immigration from further afield. Our study thus reveals appreciable temporal heterogeneity in the effective population size of a natural vertebrate population, confirms the need for long-term studies and cautions against drawing conclusions from a single sample. PMID:27553455

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

Background: The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. Methods: We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. Results: We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. Conclusions: There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. PMID:26174515

A single test for rejecting the null hypothesis in subgroups and in the overall sample.

PubMed

Lin, Yunzhi; Zhou, Kefei; Ganju, Jitendra

2017-01-01

In clinical trials, some patient subgroups are likely to demonstrate larger effect sizes than other subgroups. For example, the effect size, or informally the benefit with treatment, is often greater in patients with a moderate condition of a disease than in those with a mild condition. A limitation of the usual method of analysis is that it does not incorporate this ordering of effect size by patient subgroup. We propose a test statistic which supplements the conventional test by including this information and simultaneously tests the null hypothesis in pre-specified subgroups and in the overall sample. It results in more power than the conventional test when the differences in effect sizes across subgroups are at least moderately large; otherwise it loses power. The method involves combining p-values from models fit to pre-specified subgroups and the overall sample in a manner that assigns greater weight to subgroups in which a larger effect size is expected. Results are presented for randomized trials with two and three subgroups.

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.

PubMed

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 combination trial. Current Controlled Trials ISRCTN61649292.

Effect of Microstructural Interfaces on the Mechanical Response of Crystalline Metallic Materials

NASA Astrophysics Data System (ADS)

Aitken, Zachary H.

Advances in nano-scale mechanical testing have brought about progress in the understanding of physical phenomena in materials and a measure of control in the fabrication of novel materials. In contrast to bulk materials that display size-invariant mechanical properties, sub-micron metallic samples show a critical dependence on sample size. The strength of nano-scale single crystalline metals is well-described by a power-law function, sigma ∝ D-n, where D is a critical sample size and n is a experimentally-fit positive exponent. This relationship is attributed to source-driven plasticity and demonstrates a strengthening as the decreasing sample size begins to limit the size and number of dislocation sources. A full understanding of this size-dependence is complicated by the presence of microstructural features such as interfaces that can compete with the dominant dislocation-based deformation mechanisms. In this thesis, the effects of microstructural features such as grain boundaries and anisotropic crystallinity on nano-scale metals are investigated through uniaxial compression testing. We find that nano-sized Cu covered by a hard coating displays a Bauschinger effect and the emergence of this behavior can be explained through a simple dislocation-based analytic model. Al nano-pillars containing a single vertically-oriented coincident site lattice grain boundary are found to show similar deformation to single-crystalline nano-pillars with slip traces passing through the grain boundary. With increasing tilt angle of the grain boundary from the pillar axis, we observe a transition from dislocation-dominated deformation to grain boundary sliding. Crystallites are observed to shear along the grain boundary and molecular dynamics simulations reveal a mechanism of atomic migration that accommodates boundary sliding. We conclude with an analysis of the effects of inherent crystal anisotropy and alloying on the mechanical behavior of the Mg alloy, AZ31. Through comparison to pure Mg, we show that the size effect dominates the strength of samples below 10 microm, that differences in the size effect between hexagonal slip systems is due to the inherent crystal anisotropy, suggesting that the fundamental mechanism of the size effect in these slip systems is the same.

Interpreting and Reporting Effect Sizes in Research Investigations.

ERIC Educational Resources Information Center

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…

An opportunity cost approach to sample size calculation in cost-effectiveness analysis.

PubMed

Gafni, A; Walter, S D; Birch, S; Sendi, P

2008-01-01

The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers. Copyright (c) 2007 John Wiley & Sons, Ltd.

Blinded and unblinded internal pilot study designs for clinical trials with count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-07-01

Internal pilot studies are a popular design feature to address uncertainties in the sample size calculations caused by vague information on nuisance parameters. Despite their popularity, only very recently blinded sample size reestimation procedures for trials with count data were proposed and their properties systematically investigated. Although blinded procedures are favored by regulatory authorities, practical application is somewhat limited by fears that blinded procedures are prone to bias if the treatment effect was misspecified in the planning. Here, we compare unblinded and blinded procedures with respect to bias, error rates, and sample size distribution. We find that both procedures maintain the desired power and that the unblinded procedure is slightly liberal whereas the actual significance level of the blinded procedure is close to the nominal level. Furthermore, we show that in situations where uncertainty about the assumed treatment effect exists, the blinded estimator of the control event rate is biased in contrast to the unblinded estimator, which results in differences in mean sample sizes in favor of the unblinded procedure. However, these differences are rather small compared to the deviations of the mean sample sizes from the sample size required to detect the true, but unknown effect. We demonstrate that the variation of the sample size resulting from the blinded procedure is in many practically relevant situations considerably smaller than the one of the unblinded procedures. The methods are extended to overdispersed counts using a quasi-likelihood approach and are illustrated by trials in relapsing multiple sclerosis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Practical aspects regarding sample size in clinical research].

PubMed

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.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Size Effect on the Mechanical Properties of CF Winding Composite

NASA Astrophysics Data System (ADS)

Cui, Yuqing; Yin, Zhongwei

2017-12-01

Mechanical properties of filament winding composites are usually tested by NOL ring samples. Few people have studied the size effect of winding composite samples on the testing result of mechanical property. In this research, winding composite thickness, diameter, and geometry of NOL ring samples were prepared to investigate the size effect on the mechanical strength of carbon fiber (CF) winding composite. The CF T700, T1000, M40, and M50 were adopted for the winding composite, while the matrix was epoxy resin. Test results show that the tensile strength and ILSS of composites decreases monotonically with an increase of thickness from 1 mm to 4 mm. The mechanical strength of composite samples increases monotonically with the increase in diameter from 100 mm to 189 mm. The mechanical strength of composite samples with two flat sides are higher than those of cyclic annular samples.

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Tests of Independence in Contingency Tables with Small Samples: A Comparison of Statistical Power.

ERIC Educational Resources Information Center

Parshall, Cynthia G.; Kromrey, Jeffrey D.

1996-01-01

Power and Type I error rates were estimated for contingency tables with small sample sizes for the following four types of tests: (1) Pearson's chi-square; (2) chi-square with Yates's continuity correction; (3) the likelihood ratio test; and (4) Fisher's Exact Test. Various marginal distributions, sample sizes, and effect sizes were examined. (SLD)

An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Bo; Shibutani, Yoji, E-mail: sibutani@mech.eng.osaka-u.ac.jp; Zhang, Xu

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 andmore » 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.« less

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

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

ERIC Educational Resources Information Center

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)

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.

2014-04-15

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample sizemore » required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence.« less

You Cannot Step Into the Same River Twice: When Power Analyses Are Optimistic.

PubMed

McShane, Blakeley B; Böckenholt, Ulf

2014-11-01

Statistical power depends on the size of the effect of interest. However, effect sizes are rarely fixed in psychological research: Study design choices, such as the operationalization of the dependent variable or the treatment manipulation, the social context, the subject pool, or the time of day, typically cause systematic variation in the effect size. Ignoring this between-study variation, as standard power formulae do, results in assessments of power that are too optimistic. Consequently, when researchers attempting replication set sample sizes using these formulae, their studies will be underpowered and will thus fail at a greater than expected rate. We illustrate this with both hypothetical examples and data on several well-studied phenomena in psychology. We provide formulae that account for between-study variation and suggest that researchers set sample sizes with respect to our generally more conservative formulae. Our formulae generalize to settings in which there are multiple effects of interest. We also introduce an easy-to-use website that implements our approach to setting sample sizes. Finally, we conclude with recommendations for quantifying between-study variation. © The Author(s) 2014.

Statistical power analysis in wildlife research

USGS Publications Warehouse

Steidl, R.J.; Hayes, J.P.

1997-01-01

Statistical power analysis can be used to increase the efficiency of research efforts and to clarify research results. Power analysis is most valuable in the design or planning phases of research efforts. Such prospective (a priori) power analyses can be used to guide research design and to estimate the number of samples necessary to achieve a high probability of detecting biologically significant effects. Retrospective (a posteriori) power analysis has been advocated as a method to increase information about hypothesis tests that were not rejected. However, estimating power for tests of null hypotheses that were not rejected with the effect size observed in the study is incorrect; these power estimates will always be a??0.50 when bias adjusted and have no relation to true power. Therefore, retrospective power estimates based on the observed effect size for hypothesis tests that were not rejected are misleading; retrospective power estimates are only meaningful when based on effect sizes other than the observed effect size, such as those effect sizes hypothesized to be biologically significant. Retrospective power analysis can be used effectively to estimate the number of samples or effect size that would have been necessary for a completed study to have rejected a specific null hypothesis. Simply presenting confidence intervals can provide additional information about null hypotheses that were not rejected, including information about the size of the true effect and whether or not there is adequate evidence to 'accept' a null hypothesis as true. We suggest that (1) statistical power analyses be routinely incorporated into research planning efforts to increase their efficiency, (2) confidence intervals be used in lieu of retrospective power analyses for null hypotheses that were not rejected to assess the likely size of the true effect, (3) minimum biologically significant effect sizes be used for all power analyses, and (4) if retrospective power estimates are to be reported, then the I?-level, effect sizes, and sample sizes used in calculations must also be reported.

A novel measure of effect size for mediation analysis.

PubMed

Lachowicz, Mark J; Preacher, Kristopher J; Kelley, Ken

2018-06-01

Mediation analysis has become one of the most popular statistical methods in the social sciences. However, many currently available effect size measures for mediation have limitations that restrict their use to specific mediation models. In this article, we develop a measure of effect size that addresses these limitations. We show how modification of a currently existing effect size measure results in a novel effect size measure with many desirable properties. We also derive an expression for the bias of the sample estimator for the proposed effect size measure and propose an adjusted version of the estimator. We present a Monte Carlo simulation study conducted to examine the finite sampling properties of the adjusted and unadjusted estimators, which shows that the adjusted estimator is effective at recovering the true value it estimates. Finally, we demonstrate the use of the effect size measure with an empirical example. We provide freely available software so that researchers can immediately implement the methods we discuss. Our developments here extend the existing literature on effect sizes and mediation by developing a potentially useful method of communicating the magnitude of mediation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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%.

Investigation of specimen size effects by in-situ microcompression of equal channel angular pressed copper

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howard, C.; Frazer, D.; Lupinacci, A.

Here, micropillar compression testing was implemented on Equal Channel Angular Pressed copper samples ranging from 200 nm to 10 µm in side length in order to measure the mechanical properties yield strength, first load drop during plastic deformation at which there was a subsequent stress decrease with increasing strain, work hardening, and strain hardening exponent. Several micropillars containing multiple grains were investigated in a 200 nm grain sample. The effective pillar diameter to grain size ratios, D/d, were measured to be between 1.9 and 27.2. Specimens having D/d ratios between 0.2 and 5 were investigated in a second sample thatmore » was annealed at 200 °C for 2 h with an average grain size of 1.3 µm. No yield strength or elastic modulus size effects were observed in specimens in the 200 nm grain size sample. However work hardening increases with a decrease in critical ratios and first stress drops occur at much lower stresses for specimens with D/d ratios less than 5. For comparison, bulk tensile testing of both samples was performed, and the yield strength values of all micropillar compression tests for the 200 nm grained sample are in good agreement with the yield strength values of the tensile tests.« less

Investigation of specimen size effects by in-situ microcompression of equal channel angular pressed copper

DOE PAGES

Howard, C.; Frazer, D.; Lupinacci, A.; ...

2015-09-30

Here, micropillar compression testing was implemented on Equal Channel Angular Pressed copper samples ranging from 200 nm to 10 µm in side length in order to measure the mechanical properties yield strength, first load drop during plastic deformation at which there was a subsequent stress decrease with increasing strain, work hardening, and strain hardening exponent. Several micropillars containing multiple grains were investigated in a 200 nm grain sample. The effective pillar diameter to grain size ratios, D/d, were measured to be between 1.9 and 27.2. Specimens having D/d ratios between 0.2 and 5 were investigated in a second sample thatmore » was annealed at 200 °C for 2 h with an average grain size of 1.3 µm. No yield strength or elastic modulus size effects were observed in specimens in the 200 nm grain size sample. However work hardening increases with a decrease in critical ratios and first stress drops occur at much lower stresses for specimens with D/d ratios less than 5. For comparison, bulk tensile testing of both samples was performed, and the yield strength values of all micropillar compression tests for the 200 nm grained sample are in good agreement with the yield strength values of the tensile tests.« less

Relationships fade with time: a meta-analysis of temporal trends in publication in ecology and evolution.

PubMed Central

Jennions, Michael D; Møller, Anders P

2002-01-01

Both significant positive and negative relationships between the magnitude of research findings (their 'effect size') and their year of publication have been reported in a few areas of biology. These trends have been attributed to Kuhnian paradigm shifts, scientific fads and bias in the choice of study systems. Here we test whether or not these isolated cases reflect a more general trend. We examined the relationship using effect sizes extracted from 44 peer-reviewed meta-analyses covering a wide range of topics in ecological and evolutionary biology. On average, there was a small but significant decline in effect size with year of publication. For the original empirical studies there was also a significant decrease in effect size as sample size increased. However, the effect of year of publication remained even after we controlled for sampling effort. Although these results have several possible explanations, it is suggested that a publication bias against non-significant or weaker findings offers the most parsimonious explanation. As in the medical sciences, non-significant results may take longer to publish and studies with both small sample sizes and non-significant results may be less likely to be published. PMID:11788035

Upward counterfactual thinking and depression: A meta-analysis.

PubMed

Broomhall, Anne Gene; Phillips, Wendy J; Hine, Donald W; Loi, Natasha M

2017-07-01

This meta-analysis examined the strength of association between upward counterfactual thinking and depressive symptoms. Forty-two effect sizes from a pooled sample of 13,168 respondents produced a weighted average effect size of r=.26, p<.001. Moderator analyses using an expanded set of 96 effect sizes indicated that upward counterfactuals and regret produced significant positive effects that were similar in strength. Effects also did not vary as a function of the theme of the counterfactual-inducing situation or study design (cross-sectional versus longitudinal). Significant effect size heterogeneity was observed across sample types, methods of assessing upward counterfactual thinking, and types of depression scale. Significant positive effects were found in studies that employed samples of bereaved individuals, older adults, terminally ill patients, or university students, but not adolescent mothers or mixed samples. Both number-based and Likert-based upward counterfactual thinking assessments produced significant positive effects, with the latter generating a larger effect. All depression scales produced significant positive effects, except for the Psychiatric Epidemiology Research Interview. Research and theoretical implications are discussed in relation to cognitive theories of depression and the functional theory of upward counterfactual thinking, and important gaps in the extant research literature are identified. Copyright © 2017 Elsevier Ltd. All rights reserved.

What is a species? A new universal method to measure differentiation and assess the taxonomic rank of allopatric populations, using continuous variables

PubMed Central

Donegan, Thomas M.

2018-01-01

Abstract Existing models for assigning species, subspecies, or no taxonomic rank to populations which are geographically separated from one another were analyzed. This was done by subjecting over 3,000 pairwise comparisons of vocal or biometric data based on birds to a variety of statistical tests that have been proposed as measures of differentiation. One current model which aims to test diagnosability (Isler et al. 1998) is highly conservative, applying a hard cut-off, which excludes from consideration differentiation below diagnosis. It also includes non-overlap as a requirement, a measure which penalizes increases to sample size. The “species scoring” model of Tobias et al. (2010) involves less drastic cut-offs, but unlike Isler et al. (1998), does not control adequately for sample size and attributes scores in many cases to differentiation which is not statistically significant. Four different models of assessing effect sizes were analyzed: using both pooled and unpooled standard deviations and controlling for sample size using t-distributions or omitting to do so. Pooled standard deviations produced more conservative effect sizes when uncontrolled for sample size but less conservative effect sizes when so controlled. Pooled models require assumptions to be made that are typically elusive or unsupported for taxonomic studies. Modifications to improving these frameworks are proposed, including: (i) introducing statistical significance as a gateway to attributing any weighting to findings of differentiation; (ii) abandoning non-overlap as a test; (iii) recalibrating Tobias et al. (2010) scores based on effect sizes controlled for sample size using t-distributions. A new universal method is proposed for measuring differentiation in taxonomy using continuous variables and a formula is proposed for ranking allopatric populations. This is based first on calculating effect sizes using unpooled standard deviations, controlled for sample size using t-distributions, for a series of different variables. All non-significant results are excluded by scoring them as zero. Distance between any two populations is calculated using Euclidian summation of non-zeroed effect size scores. If the score of an allopatric pair exceeds that of a related sympatric pair, then the allopatric population can be ranked as species and, if not, then at most subspecies rank should be assigned. A spreadsheet has been programmed and is being made available which allows this and other tests of differentiation and rank studied in this paper to be rapidly analyzed. PMID:29780266

Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM).

PubMed

Haverkamp, Nicolas; Beauducel, André

2017-01-01

We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach. In contrast to previous simulation studies on this topic, up to nine measurement occasions were considered. Effects of the level of inter-correlations between measurement occasions on Type I error rates were considered for the first time. Two populations with non-violation of the sphericity assumption, one with uncorrelated measurement occasions and one with moderately correlated measurement occasions, were generated. One population with violation of the sphericity assumption combines uncorrelated with highly correlated measurement occasions. A second population with violation of the sphericity assumption combines moderately correlated and highly correlated measurement occasions. From these four populations without any between-group effect or within-subject effect 5,000 random samples were drawn. Finally, the mean Type I error rates for Multilevel linear models (MLM) with an unstructured covariance matrix (MLM-UN), MLM with compound-symmetry (MLM-CS) and for repeated measures analysis of variance (rANOVA) models (without correction, with Greenhouse-Geisser-correction, and Huynh-Feldt-correction) were computed. To examine the effect of both the sample size and the number of measurement occasions, sample sizes of n = 20, 40, 60, 80, and 100 were considered as well as measurement occasions of m = 3, 6, and 9. With respect to rANOVA, the results plead for a use of rANOVA with Huynh-Feldt-correction, especially when the sphericity assumption is violated, the sample size is rather small and the number of measurement occasions is large. For MLM-UN, the results illustrate a massive progressive bias for small sample sizes ( n = 20) and m = 6 or more measurement occasions. This effect could not be found in previous simulation studies with a smaller number of measurement occasions. The proportionality of bias and number of measurement occasions should be considered when MLM-UN is used. The good news is that this proportionality can be compensated by means of large sample sizes. Accordingly, MLM-UN can be recommended even for small sample sizes for about three measurement occasions and for large sample sizes for about nine measurement occasions.

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

NASA Astrophysics Data System (ADS)

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 samples. Some of the day to night difference may have been caused also by differing wind directions transporting air masses from different emission sources during the day and the night. The present findings indicate the important role of the local particle sources and atmospheric processes on the health related toxicological properties of the PM. The varying toxicological responses evoked by the PM samples showed the importance of examining various particle sizes. Especially the detected considerable toxicological activity by PM0.2 size range suggests they're attributable to combustion sources, new particle formation and atmospheric processes.

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

ERIC Educational Resources Information Center

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…

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.

PubMed

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).

Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials

PubMed Central

Martin, James; Taljaard, Monica; Girling, Alan; Hemming, Karla

2016-01-01

Background Stepped-wedge cluster randomised trials (SW-CRT) are increasingly being used in health policy and services research, but unless they are conducted and reported to the highest methodological standards, they are unlikely to be useful to decision-makers. Sample size calculations for these designs require allowance for clustering, time effects and repeated measures. Methods We carried out a methodological review of SW-CRTs up to October 2014. We assessed adherence to reporting each of the 9 sample size calculation items recommended in the 2012 extension of the CONSORT statement to cluster trials. Results We identified 32 completed trials and 28 independent protocols published between 1987 and 2014. Of these, 45 (75%) reported a sample size calculation, with a median of 5.0 (IQR 2.5–6.0) of the 9 CONSORT items reported. Of those that reported a sample size calculation, the majority, 33 (73%), allowed for clustering, but just 15 (33%) allowed for time effects. There was a small increase in the proportions reporting a sample size calculation (from 64% before to 84% after publication of the CONSORT extension, p=0.07). The type of design (cohort or cross-sectional) was not reported clearly in the majority of studies, but cohort designs seemed to be most prevalent. Sample size calculations in cohort designs were particularly poor with only 3 out of 24 (13%) of these studies allowing for repeated measures. Discussion The quality of reporting of sample size items in stepped-wedge trials is suboptimal. There is an urgent need for dissemination of the appropriate guidelines for reporting and methodological development to match the proliferation of the use of this design in practice. Time effects and repeated measures should be considered in all SW-CRT power calculations, and there should be clarity in reporting trials as cohort or cross-sectional designs. PMID:26846897

The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements.

PubMed

Daszkiewicz, Karol; Maquer, Ghislain; Zysset, Philippe K

2017-06-01

Boundary conditions (BCs) and sample size affect the measured elastic properties of cancellous bone. Samples too small to be representative appear stiffer under kinematic uniform BCs (KUBCs) than under periodicity-compatible mixed uniform BCs (PMUBCs). To avoid those effects, we propose to determine the effective properties of trabecular bone using an embedded configuration. Cubic samples of various sizes (2.63, 5.29, 7.96, 10.58 and 15.87 mm) were cropped from [Formula: see text] scans of femoral heads and vertebral bodies. They were converted into [Formula: see text] models and their stiffness tensor was established via six uniaxial and shear load cases. PMUBCs- and KUBCs-based tensors were determined for each sample. "In situ" stiffness tensors were also evaluated for the embedded configuration, i.e. when the loads were transmitted to the samples via a layer of trabecular bone. The Zysset-Curnier model accounting for bone volume fraction and fabric anisotropy was fitted to those stiffness tensors, and model parameters [Formula: see text] (Poisson's ratio) [Formula: see text] and [Formula: see text] (elastic and shear moduli) were compared between sizes. BCs and sample size had little impact on [Formula: see text]. However, KUBCs- and PMUBCs-based [Formula: see text] and [Formula: see text], respectively, decreased and increased with growing size, though convergence was not reached even for our largest samples. Both BCs produced upper and lower bounds for the in situ values that were almost constant across samples dimensions, thus appearing as an approximation of the effective properties. PMUBCs seem also appropriate for mimicking the trabecular core, but they still underestimate its elastic properties (especially in shear) even for nearly orthotropic samples.

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach. [Kansas

NASA Technical Reports Server (NTRS)

Hixson, M. M.; Bauer, M. E.; Davis, B. J.

1979-01-01

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

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

PubMed Central

2011-01-01

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 individual drugs would require at least 8-fold the sample size of the combination trial. Trial registration Current Controlled Trials ISRCTN61649292 PMID:21288326

The albatross plot: A novel graphical tool for presenting results of diversely reported studies in a systematic review

PubMed Central

Jones, Hayley E.; Martin, Richard M.; Lewis, Sarah J.; Higgins, Julian P.T.

2017-01-01

Abstract Meta‐analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies were done or limitations in how their results were reported. Other methods, such as vote counting, are then used to summarize the results of these studies, but most of these methods are limited in that they do not provide any indication of the magnitude of effect. We propose a novel plot, the albatross plot, which requires only a 1‐sided P value and a total sample size from each study (or equivalently a 2‐sided P value, direction of effect and total sample size). The plot allows an approximate examination of underlying effect sizes and the potential to identify sources of heterogeneity across studies. This is achieved by drawing contours showing the range of effect sizes that might lead to each P value for given sample sizes, under simple study designs. We provide examples of albatross plots using data from previous meta‐analyses, allowing for comparison of results, and an example from when a meta‐analysis was not possible. PMID:28453179

Infrared reflectance spectra: Effects of particle size, provenance and preparation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Yin-Fong; Myers, Tanya L.; Brauer, Carolyn S.

2014-09-22

We have recently developed methods for making more accurate infrared total and diffuse directional - hemispherical reflectance measurements using an integrating sphere. We have found that reflectance spectra of solids, especially powders, are influenced by a number of factors including the sample preparation method, the particle size and morphology, as well as the sample origin. On a quantitative basis we have investigated some of these parameters and the effects they have on reflectance spectra, particularly in the longwave infrared. In the IR the spectral features may be observed as either maxima or minima: In general, upward-going peaks in the reflectancemore » spectrum result from strong surface scattering, i.e. rays that are reflected from the surface without bulk penetration, whereas downward-going peaks are due to either absorption or volume scattering, i.e. rays that have penetrated or refracted into the sample interior and are not reflected. The light signals reflected from solids usually encompass all such effects, but with strong dependencies on particle size and preparation. This paper measures the reflectance spectra in the 1.3 – 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to observe the effects on the spectral features: Bulk materials were ground with a mortar and pestle and sieved to separate the samples into various size fractions between 5 and 500 microns. The median particle size is demonstrated to have large effects on the reflectance spectra. For certain minerals we also observe significant spectral change depending on the geologic origin of the sample. All three such effects (particle size, preparation and provenance) result in substantial change in the reflectance spectra for solid materials; successful identification algorithms will require sufficient flexibility to account for these parameters.« less

Infrared reflectance spectra: effects of particle size, provenance and preparation

NASA Astrophysics Data System (ADS)

Su, Yin-Fong; Myers, Tanya L.; Brauer, Carolyn S.; Blake, Thomas A.; Forland, Brenda M.; Szecsody, J. E.; Johnson, Timothy J.

2014-10-01

We have recently developed methods for making more accurate infrared total and diffuse directional - hemispherical reflectance measurements using an integrating sphere. We have found that reflectance spectra of solids, especially powders, are influenced by a number of factors including the sample preparation method, the particle size and morphology, as well as the sample origin. On a quantitative basis we have investigated some of these parameters and the effects they have on reflectance spectra, particularly in the longwave infrared. In the IR the spectral features may be observed as either maxima or minima: In general, upward-going peaks in the reflectance spectrum result from strong surface scattering, i.e. rays that are reflected from the surface without bulk penetration, whereas downward-going peaks are due to either absorption or volume scattering, i.e. rays that have penetrated or refracted into the sample interior and are not reflected. The light signals reflected from solids usually encompass all such effects, but with strong dependencies on particle size and preparation. This paper measures the reflectance spectra in the 1.3 - 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to observe the effects on the spectral features: Bulk materials were ground with a mortar and pestle and sieved to separate the samples into various size fractions between 5 and 500 microns. The median particle size is demonstrated to have large effects on the reflectance spectra. For certain minerals we also observe significant spectral change depending on the geologic origin of the sample. All three such effects (particle size, preparation and provenance) result in substantial change in the reflectance spectra for solid materials; successful identification algorithms will require sufficient flexibility to account for these parameters.

Experimental Effects on IR Reflectance Spectra: Particle Size and Morphology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beiswenger, Toya N.; Myers, Tanya L.; Brauer, Carolyn S.

For geologic and extraterrestrial samples it is known that both particle size and morphology can have strong effects on the species’ infrared reflectance spectra. Due to such effects, the reflectance spectra cannot be predicted from the absorption coefficients alone. This is because reflectance is both a surface as well as a bulk phenomenon, incorporating both dispersion as well as absorption effects. The same spectral features can even be observed as either a maximum or minimum. The complex effects depend on particle size and preparation, as well as the relative amplitudes of the optical constants n and k, i.e. the realmore » and imaginary components of the complex refractive index. While somewhat oversimplified, upward-going amplitude in the reflectance spectrum usually result from surface scattering, i.e. rays that have been reflected from the surface without penetration, whereas downward-going peaks are due to either absorption or volume scattering, i.e. rays that have penetrated or refracted into the sample interior and are not reflected. While the effects are well known, we report seminal measurements of reflectance along with quantified particle size of the samples, the sizing obtained from optical microscopy measurements. The size measurements are correlated with the reflectance spectra in the 1.3 – 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to understand the effects on the spectral features as a function of the mean grain size of the sample. We report results for both sodium sulfate Na2SO4 as well as ammonium sulfate (NH4)2SO4; the optical constants have been measured for (NH4)2SO4. To go a step further from the field to the laboratory we explore our understanding of particle size effects on reflectance spectra in the field using standoff detection. This has helped identify weaknesses and strengths in detection using standoff distances of up 160 meters away from the Target. The studies have shown that particle size has an enormous influence on the measured reflectance spectra of such materials; successful identification requires sufficient, representative reflectance data to include the particle sizes of interest.« less

Sample size calculation in economic evaluations.

PubMed

Al, M J; van Hout, B A; Michel, B C; Rutten, F F

1998-06-01

A simulation method is presented for sample size calculation in economic evaluations. As input the method requires: the expected difference and variance of costs and effects, their correlation, the significance level (alpha) and the power of the testing method and the maximum acceptable ratio of incremental effectiveness to incremental costs. The method is illustrated with data from two trials. The first compares primary coronary angioplasty with streptokinase in the treatment of acute myocardial infarction, in the second trial, lansoprazole is compared with omeprazole in the treatment of reflux oesophagitis. These case studies show how the various parameters influence the sample size. Given the large number of parameters that have to be specified in advance, the lack of knowledge about costs and their standard deviation, and the difficulty of specifying the maximum acceptable ratio of incremental effectiveness to incremental costs, the conclusion of the study is that from a technical point of view it is possible to perform a sample size calculation for an economic evaluation, but one should wonder how useful it is.

Experimental and numerical modeling research of rubber material during microwave heating process

NASA Astrophysics Data System (ADS)

Chen, Hailong; Li, Tao; Li, Kunling; Li, Qingling

2018-05-01

This paper aims to investigate the heating behaviors of block rubber by experimental and simulated method. The COMSOL Multiphysics 5.0 software was utilized in numerical simulation work. The effects of microwave frequency, power and sample size on temperature distribution are examined. The effect of frequency on temperature distribution is obvious. The maximum and minimum temperatures of block rubber increase first and then decrease with frequency increasing. The microwave heating efficiency is maximum in the microwave frequency of 2450 MHz. However, more uniform temperature distribution is presented in other microwave frequencies. The influence of microwave power on temperature distribution is also remarkable. The smaller the power, the more uniform the temperature distribution on the block rubber. The effect of power on microwave heating efficiency is not obvious. The effect of sample size on temperature distribution is evidently found. The smaller the sample size, the more uniform the temperature distribution on the block rubber. However, the smaller the sample size, the lower the microwave heating efficiency. The results can serve as references for the research on heating rubber material by microwave technology.

Thermal conductivity of graphene mediated by strain and size

DOE PAGES

Kuang, Youdi; Shi, Sanqiang; Wang, Xinjiang; ...

2016-06-09

Based on first-principles calculations and full iterative solution of the linearized Boltzmann–Peierls transport equation for phonons, we systematically investigate effects of strain, size and temperature on the thermal conductivity k of suspended graphene. The calculated size-dependent and temperature-dependent k for finite samples agree well with experimental data. The results show that, contrast to the convergent room-temperature k = 5450 W/m-K of unstrained graphene at a sample size ~8 cm, k of strained graphene diverges with increasing the sample size even at high temperature. Out-of-plane acoustic phonons are responsible for the significant size effect in unstrained and strained graphene due tomore » their ultralong mean free path and acoustic phonons with wavelength smaller than 10 nm contribute 80% to the intrinsic room temperature k of unstrained graphene. Tensile strain hardens the flexural modes and increases their lifetimes, causing interesting dependence of k on sample size and strain due to the competition between boundary scattering and intrinsic phonon–phonon scattering. k of graphene can be tuned within a large range by strain for the size larger than 500 μm. These findings shed light on the nature of thermal transport in two-dimensional materials and may guide predicting and engineering k of graphene by varying strain and size.« less

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

PubMed

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.

Replication Validity of Initial Association Studies: A Comparison between Psychiatry, Neurology and Four Somatic Diseases.

PubMed

Dumas-Mallet, Estelle; Button, Katherine; Boraud, Thomas; Munafo, Marcus; Gonon, François

2016-01-01

There are growing concerns about effect size inflation and replication validity of association studies, but few observational investigations have explored the extent of these problems. Using meta-analyses to measure the reliability of initial studies and explore whether this varies across biomedical domains and study types (cognitive/behavioral, brain imaging, genetic and "others"). We analyzed 663 meta-analyses describing associations between markers or risk factors and 12 pathologies within three biomedical domains (psychiatry, neurology and four somatic diseases). We collected the effect size, sample size, publication year and Impact Factor of initial studies, largest studies (i.e., with the largest sample size) and the corresponding meta-analyses. Initial studies were considered as replicated if they were in nominal agreement with meta-analyses and if their effect size inflation was below 100%. Nominal agreement between initial studies and meta-analyses regarding the presence of a significant effect was not better than chance in psychiatry, whereas it was somewhat better in neurology and somatic diseases. Whereas effect sizes reported by largest studies and meta-analyses were similar, most of those reported by initial studies were inflated. Among the 256 initial studies reporting a significant effect (p<0.05) and paired with significant meta-analyses, 97 effect sizes were inflated by more than 100%. Nominal agreement and effect size inflation varied with the biomedical domain and study type. Indeed, the replication rate of initial studies reporting a significant effect ranged from 6.3% for genetic studies in psychiatry to 86.4% for cognitive/behavioral studies. Comparison between eight subgroups shows that replication rate decreases with sample size and "true" effect size. We observed no evidence of association between replication rate and publication year or Impact Factor. The differences in reliability between biological psychiatry, neurology and somatic diseases suggest that there is room for improvement, at least in some subdomains.

Replication Validity of Initial Association Studies: A Comparison between Psychiatry, Neurology and Four Somatic Diseases

PubMed Central

Dumas-Mallet, Estelle; Button, Katherine; Boraud, Thomas; Munafo, Marcus; Gonon, François

2016-01-01

Context There are growing concerns about effect size inflation and replication validity of association studies, but few observational investigations have explored the extent of these problems. Objective Using meta-analyses to measure the reliability of initial studies and explore whether this varies across biomedical domains and study types (cognitive/behavioral, brain imaging, genetic and “others”). Methods We analyzed 663 meta-analyses describing associations between markers or risk factors and 12 pathologies within three biomedical domains (psychiatry, neurology and four somatic diseases). We collected the effect size, sample size, publication year and Impact Factor of initial studies, largest studies (i.e., with the largest sample size) and the corresponding meta-analyses. Initial studies were considered as replicated if they were in nominal agreement with meta-analyses and if their effect size inflation was below 100%. Results Nominal agreement between initial studies and meta-analyses regarding the presence of a significant effect was not better than chance in psychiatry, whereas it was somewhat better in neurology and somatic diseases. Whereas effect sizes reported by largest studies and meta-analyses were similar, most of those reported by initial studies were inflated. Among the 256 initial studies reporting a significant effect (p<0.05) and paired with significant meta-analyses, 97 effect sizes were inflated by more than 100%. Nominal agreement and effect size inflation varied with the biomedical domain and study type. Indeed, the replication rate of initial studies reporting a significant effect ranged from 6.3% for genetic studies in psychiatry to 86.4% for cognitive/behavioral studies. Comparison between eight subgroups shows that replication rate decreases with sample size and “true” effect size. We observed no evidence of association between replication rate and publication year or Impact Factor. Conclusion The differences in reliability between biological psychiatry, neurology and somatic diseases suggest that there is room for improvement, at least in some subdomains. PMID:27336301

Meta-analysis of genome-wide association from genomic prediction models

USDA-ARS?s Scientific Manuscript database

A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

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

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

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

The Precision Efficacy Analysis for Regression Sample Size Method.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…

Effect of the three-dimensional microstructure on the sound absorption of foams: A parametric study.

PubMed

Chevillotte, Fabien; Perrot, Camille

2017-08-01

The purpose of this work is to systematically study the effect of the throat and the pore sizes on the sound absorbing properties of open-cell foams. The three-dimensional idealized unit cell used in this work enables to mimic the acoustical macro-behavior of a large class of cellular solid foams. This study is carried out for a normal incidence and also for a diffuse field excitation, with a relatively large range of sample thicknesses. The transport and sound absorbing properties are numerically studied as a function of the throat size, the pore size, and the sample thickness. The resulting diagrams show the ranges of the specific throat sizes and pore sizes where the sound absorption grading is maximized due to the pore morphology as a function of the sample thickness, and how it correlates with the corresponding transport parameters. These charts demonstrate, together with typical examples, how the morphological characteristics of foam could be modified in order to increase the visco-thermal dissipation effects.

Estimation of the bottleneck size in Florida panthers

USGS Publications Warehouse

Culver, M.; Hedrick, P.W.; Murphy, K.; O'Brien, S.; Hornocker, M.G.

2008-01-01

We have estimated the extent of genetic variation in museum (1890s) and contemporary (1980s) samples of Florida panthers Puma concolor coryi for both nuclear loci and mtDNA. The microsatellite heterozygosity in the contemporary sample was only 0.325 that in the museum samples although our sample size and number of loci are limited. Support for this estimate is provided by a sample of 84 microsatellite loci in contemporary Florida panthers and Idaho pumas Puma concolor hippolestes in which the contemporary Florida panther sample had only 0.442 the heterozygosity of Idaho pumas. The estimated diversities in mtDNA in the museum and contemporary samples were 0.600 and 0.000, respectively. Using a population genetics approach, we have estimated that to reduce either the microsatellite heterozygosity or the mtDNA diversity this much (in a period of c. 80years during the 20th century when the numbers were thought to be low) that a very small bottleneck size of c. 2 for several generations and a small effective population size in other generations is necessary. Using demographic data from Yellowstone pumas, we estimated the ratio of effective to census population size to be 0.315. Using this ratio, the census population size in the Florida panthers necessary to explain the loss of microsatellite variation was c .41 for the non-bottleneck generations and 6.2 for the two bottleneck generations. These low bottleneck population sizes and the concomitant reduced effectiveness of selection are probably responsible for the high frequency of several detrimental traits in Florida panthers, namely undescended testicles and poor sperm quality. The recent intensive monitoring both before and after the introduction of Texas pumas in 1995 will make the recovery and genetic restoration of Florida panthers a classic study of an endangered species. Our estimates of the bottleneck size responsible for the loss of genetic variation in the Florida panther completes an unknown aspect of this account. ?? 2008 The Authors. Journal compilation ?? 2008 The Zoological Society of London.

Scale-dependent effect sizes of ecological drivers on biodiversity: why standardised sampling is not enough.

PubMed

Chase, Jonathan M; Knight, Tiffany M

2013-05-01

There is little consensus about how natural (e.g. productivity, disturbance) and anthropogenic (e.g. invasive species, habitat destruction) ecological drivers influence biodiversity. Here, we show that when sampling is standardised by area (species density) or individuals (rarefied species richness), the measured effect sizes depend critically on the spatial grain and extent of sampling, as well as the size of the species pool. This compromises comparisons of effects sizes within studies using standard statistics, as well as among studies using meta-analysis. To derive an unambiguous effect size, we advocate that comparisons need to be made on a scale-independent metric, such as Hurlbert's Probability of Interspecific Encounter. Analyses of this metric can be used to disentangle the relative influence of changes in the absolute and relative abundances of individuals, as well as their intraspecific aggregations, in driving differences in biodiversity among communities. This and related approaches are necessary to achieve generality in understanding how biodiversity responds to ecological drivers and will necessitate a change in the way many ecologists collect and analyse their data. © 2013 John Wiley & Sons Ltd/CNRS.

Effects of Sample Preparation on the Infrared Reflectance Spectra of Powders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.

2015-05-22

While reflectance spectroscopy is a useful tool in identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-packedmore » as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.« less

Effects of sample preparation on the infrared reflectance spectra of powders

NASA Astrophysics Data System (ADS)

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.; Su, Yin-Fong; Blake, Thomas A.; Forland, Brenda M.

2015-05-01

While reflectance spectroscopy is a useful tool for identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-loaded as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample can have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.

Sample Size Requirements and Study Duration for Testing Main Effects and Interactions in Completely Randomized Factorial Designs When Time to Event is the Outcome

PubMed Central

Moser, Barry Kurt; Halabi, Susan

2013-01-01

In this paper we develop the methodology for designing clinical trials with any factorial arrangement when the primary outcome is time to event. We provide a matrix formulation for calculating the sample size and study duration necessary to test any effect with a pre-specified type I error rate and power. Assuming that a time to event follows an exponential distribution, we describe the relationships between the effect size, the power, and the sample size. We present examples for illustration purposes. We provide a simulation study to verify the numerical calculations of the expected number of events and the duration of the trial. The change in the power produced by a reduced number of observations or by accruing no patients to certain factorial combinations is also described. PMID:25530661

Sample size considerations when groups are the appropriate unit of analyses

PubMed Central

Sadler, Georgia Robins; Ko, Celine Marie; Alisangco, Jennifer; Rosbrook, Bradley P.; Miller, Eric; Fullerton, Judith

2007-01-01

This paper discusses issues to be considered by nurse researchers when groups should be used as a unit of randomization. Advantages and disadvantages are presented, with statistical calculations needed to determine effective sample size. Examples of these concepts are presented using data from the Black Cosmetologists Promoting Health Program. Different hypothetical scenarios and their impact on sample size are presented. Given the complexity of calculating sample size when using groups as a unit of randomization, it’s advantageous for researchers to work closely with statisticians when designing and implementing studies that anticipate the use of groups as the unit of randomization. PMID:17693219

Damage Accumulation in Silica Glass Nanofibers.

PubMed

Bonfanti, Silvia; Ferrero, Ezequiel E; Sellerio, Alessandro L; Guerra, Roberto; Zapperi, Stefano

2018-06-06

The origin of the brittle-to-ductile transition, experimentally observed in amorphous silica nanofibers as the sample size is reduced, is still debated. Here we investigate the issue by extensive molecular dynamics simulations at low and room temperatures for a broad range of sample sizes, with open and periodic boundary conditions. Our results show that small sample-size enhanced ductility is primarily due to diffuse damage accumulation, that for larger samples leads to brittle catastrophic failure. Surface effects such as boundary fluidization contribute to ductility at room temperature by promoting necking, but are not the main driver of the transition. Our results suggest that the experimentally observed size-induced ductility of silica nanofibers is a manifestation of finite-size criticality, as expected in general for quasi-brittle disordered networks.

Finite element and analytical solutions for van der Pauw and four-point probe correction factors when multiple non-ideal measurement conditions coexist

NASA Astrophysics Data System (ADS)

Reveil, Mardochee; Sorg, Victoria C.; Cheng, Emily R.; Ezzyat, Taha; Clancy, Paulette; Thompson, Michael O.

2017-09-01

This paper presents an extensive collection of calculated correction factors that account for the combined effects of a wide range of non-ideal conditions often encountered in realistic four-point probe and van der Pauw experiments. In this context, "non-ideal conditions" refer to conditions that deviate from the assumptions on sample and probe characteristics made in the development of these two techniques. We examine the combined effects of contact size and sample thickness on van der Pauw measurements. In the four-point probe configuration, we examine the combined effects of varying the sample's lateral dimensions, probe placement, and sample thickness. We derive an analytical expression to calculate correction factors that account, simultaneously, for finite sample size and asymmetric probe placement in four-point probe experiments. We provide experimental validation of the analytical solution via four-point probe measurements on a thin film rectangular sample with arbitrary probe placement. The finite sample size effect is very significant in four-point probe measurements (especially for a narrow sample) and asymmetric probe placement only worsens such effects. The contribution of conduction in multilayer samples is also studied and found to be substantial; hence, we provide a map of the necessary correction factors. This library of correction factors will enable the design of resistivity measurements with improved accuracy and reproducibility over a wide range of experimental conditions.

Finite element and analytical solutions for van der Pauw and four-point probe correction factors when multiple non-ideal measurement conditions coexist.

PubMed

Reveil, Mardochee; Sorg, Victoria C; Cheng, Emily R; Ezzyat, Taha; Clancy, Paulette; Thompson, Michael O

2017-09-01

This paper presents an extensive collection of calculated correction factors that account for the combined effects of a wide range of non-ideal conditions often encountered in realistic four-point probe and van der Pauw experiments. In this context, "non-ideal conditions" refer to conditions that deviate from the assumptions on sample and probe characteristics made in the development of these two techniques. We examine the combined effects of contact size and sample thickness on van der Pauw measurements. In the four-point probe configuration, we examine the combined effects of varying the sample's lateral dimensions, probe placement, and sample thickness. We derive an analytical expression to calculate correction factors that account, simultaneously, for finite sample size and asymmetric probe placement in four-point probe experiments. We provide experimental validation of the analytical solution via four-point probe measurements on a thin film rectangular sample with arbitrary probe placement. The finite sample size effect is very significant in four-point probe measurements (especially for a narrow sample) and asymmetric probe placement only worsens such effects. The contribution of conduction in multilayer samples is also studied and found to be substantial; hence, we provide a map of the necessary correction factors. This library of correction factors will enable the design of resistivity measurements with improved accuracy and reproducibility over a wide range of experimental conditions.

Effect of sample inhomogeneity in KAr dating

USGS Publications Warehouse

Engels, J.C.; Ingamells, C.O.

1970-01-01

Error in K-Ar ages is often due more to deficiencies in the splitting process, whereby portions of the sample are taken for potassium and for argon determination, than to imprecision in the analytical methods. The effect of the grain size of a sample and of the composition of a contaminating mineral can be evaluated, and this provides a useful guide in attempts to minimize error. Rocks and minerals should be prepared for age determination with the effects of contaminants and grain size in mind. The magnitude of such effects can be much larger than intuitive estimates might indicate. ?? 1970.

Influence of multidroplet size distribution on icing collection efficiency

NASA Technical Reports Server (NTRS)

Chang, H.-P.; Kimble, K. R.; Frost, W.; Shaw, R. J.

1983-01-01

Calculation of collection efficiencies of two-dimensional airfoils for a monodispersed droplet icing cloud and a multidispersed droplet is carried out. Comparison is made with the experimental results reported in the NACA Technical Note series. The results of the study show considerably improved agreement with experiment when multidroplet size distributions are employed. The study then investigates the effect of collection efficiency on airborne particle droplet size sampling instruments. The biased effect introduced due to sampling from different collection volumes is predicted.

The albatross plot: A novel graphical tool for presenting results of diversely reported studies in a systematic review.

PubMed

Harrison, Sean; Jones, Hayley E; Martin, Richard M; Lewis, Sarah J; Higgins, Julian P T

2017-09-01

Meta-analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies were done or limitations in how their results were reported. Other methods, such as vote counting, are then used to summarize the results of these studies, but most of these methods are limited in that they do not provide any indication of the magnitude of effect. We propose a novel plot, the albatross plot, which requires only a 1-sided P value and a total sample size from each study (or equivalently a 2-sided P value, direction of effect and total sample size). The plot allows an approximate examination of underlying effect sizes and the potential to identify sources of heterogeneity across studies. This is achieved by drawing contours showing the range of effect sizes that might lead to each P value for given sample sizes, under simple study designs. We provide examples of albatross plots using data from previous meta-analyses, allowing for comparison of results, and an example from when a meta-analysis was not possible. Copyright © 2017 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd.

Automated sampling assessment for molecular simulations using the effective sample size

PubMed Central

Zhang, Xin; Bhatt, Divesh; Zuckerman, Daniel M.

2010-01-01

To quantify the progress in the development of algorithms and forcefields used in molecular simulations, a general method for the assessment of the sampling quality is needed. Statistical mechanics principles suggest the populations of physical states characterize equilibrium sampling in a fundamental way. We therefore develop an approach for analyzing the variances in state populations, which quantifies the degree of sampling in terms of the effective sample size (ESS). The ESS estimates the number of statistically independent configurations contained in a simulated ensemble. The method is applicable to both traditional dynamics simulations as well as more modern (e.g., multi–canonical) approaches. Our procedure is tested in a variety of systems from toy models to atomistic protein simulations. We also introduce a simple automated procedure to obtain approximate physical states from dynamic trajectories: this allows sample–size estimation in systems for which physical states are not known in advance. PMID:21221418

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

PubMed

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.

Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling

PubMed Central

2006-01-01

Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling. PMID:16937083

Estimation of Effect Size from a Series of Experiments Involving Paired Comparisons.

ERIC Educational Resources Information Center

Gibbons, Robert D.; And Others

1993-01-01

A distribution theory is derived for a G. V. Glass-type (1976) estimator of effect size from studies involving paired comparisons. The possibility of combining effect sizes from studies involving a mixture of related and unrelated samples is also explored. Resulting estimates are illustrated using data from previous psychiatric research. (SLD)

Using sieving and pretreatment to separate plastics during end-of-life vehicle recycling.

PubMed

Stagner, Jacqueline A; Sagan, Barsha; Tam, Edwin Kl

2013-09-01

Plastics continue to be a challenge for recovering materials at the end-of-life for vehicles. However, it may be possible to improve the recovery of plastics by exploiting material characteristics, such as shape, or by altering their behavior, such as through temperature changes, in relation to recovery processes and handling. Samples of a 2009 Dodge Challenger front fascia were shredded in a laboratory-scale hammer mill shredder. A 2 × 2 factorial design study was performed to determine the effect of sample shape (flat versus curved) and sample temperature (room temperature versus cryogenic temperature) on the size of the particles exiting from the shredder. It was determined that sample shape does not affect the particle size; however, sample temperature does affect the particle size. At cryogenic temperatures, the distribution of particle sizes is much narrower than at room temperature. Having a more uniform particle size could make recovery of plastic particles, such as these more efficient during the recycling of end-of-life vehicles. Samples of Chrysler minivan headlights were also shredded at room temperature and at cryogenic temperatures. The size of the particles of the two different plastics in the headlights is statistically different both at room temperature and at cryogenic temperature, and the particles are distributed narrowly. The research suggests that incremental changes in end-of-life vehicle processing could be effective in aiding materials recovery.

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

PubMed

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.

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.

PubMed

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 (P<0.001), but does not differ by reported direction of the LBP trial outcome (P=0.270). The absence of associations between effect size and impact factor, reporting sources 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.

Sample Size in Clinical Cardioprotection Trials Using Myocardial Salvage Index, Infarct Size, or Biochemical Markers as Endpoint.

PubMed

Engblom, Henrik; Heiberg, Einar; Erlinge, David; Jensen, Svend Eggert; Nordrehaug, Jan Erik; Dubois-Randé, Jean-Luc; Halvorsen, Sigrun; Hoffmann, Pavel; Koul, Sasha; Carlsson, Marcus; Atar, Dan; Arheden, Håkan

2016-03-09

Cardiac magnetic resonance (CMR) can quantify myocardial infarct (MI) size and myocardium at risk (MaR), enabling assessment of myocardial salvage index (MSI). We assessed how MSI impacts the number of patients needed to reach statistical power in relation to MI size alone and levels of biochemical markers in clinical cardioprotection trials and how scan day affect sample size. Controls (n=90) from the recent CHILL-MI and MITOCARE trials were included. MI size, MaR, and MSI were assessed from CMR. High-sensitivity troponin T (hsTnT) and creatine kinase isoenzyme MB (CKMB) levels were assessed in CHILL-MI patients (n=50). Utilizing distribution of these variables, 100 000 clinical trials were simulated for calculation of sample size required to reach sufficient power. For a treatment effect of 25% decrease in outcome variables, 50 patients were required in each arm using MSI compared to 93, 98, 120, 141, and 143 for MI size alone, hsTnT (area under the curve [AUC] and peak), and CKMB (AUC and peak) in order to reach a power of 90%. If average CMR scan day between treatment and control arms differed by 1 day, sample size needs to be increased by 54% (77 vs 50) to avoid scan day bias masking a treatment effect of 25%. Sample size in cardioprotection trials can be reduced 46% to 65% without compromising statistical power when using MSI by CMR as an outcome variable instead of MI size alone or biochemical markers. It is essential to ensure lack of bias in scan day between treatment and control arms to avoid compromising statistical power. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

Cook, David A.; Hatala, Rose

2015-01-01

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

A new method for estimating the demographic history from DNA sequences: an importance sampling approach

PubMed Central

Ait Kaci Azzou, Sadoune; Larribe, Fabrice; Froda, Sorana

2015-01-01

The effective population size over time (demographic history) can be retraced from a sample of contemporary DNA sequences. In this paper, we propose a novel methodology based on importance sampling (IS) for exploring such demographic histories. Our starting point is the generalized skyline plot with the main difference being that our procedure, skywis plot, uses a large number of genealogies. The information provided by these genealogies is combined according to the IS weights. Thus, we compute a weighted average of the effective population sizes on specific time intervals (epochs), where the genealogies that agree more with the data are given more weight. We illustrate by a simulation study that the skywis plot correctly reconstructs the recent demographic history under the scenarios most commonly considered in the literature. In particular, our method can capture a change point in the effective population size, and its overall performance is comparable with the one of the bayesian skyline plot. We also introduce the case of serially sampled sequences and illustrate that it is possible to improve the performance of the skywis plot in the case of an exponential expansion of the effective population size. PMID:26300910

Variable percentage sampler

DOEpatents

Miller, Jr., William H.

1976-01-01

A remotely operable sampler is provided for obtaining variable percentage samples of nuclear fuel particles and the like for analyses. The sampler has a rotating cup for a sample collection chamber designed so that the effective size of the sample inlet opening to the cup varies with rotational speed. Samples of a desired size are withdrawn from a flowing stream of particles without a deterrent to the flow of remaining particles.

Large exchange bias effect in NiFe2O4/CoO nanocomposites

NASA Astrophysics Data System (ADS)

Mohan, Rajendra; Prasad Ghosh, Mritunjoy; Mukherjee, Samrat

2018-03-01

In this work, we report the exchange bias effect of NiFe2O4/CoO nanocomposites, synthesized via chemical co-precipitation method. Four samples of different particle size ranging from 4 nm to 31 nm were prepared with the annealing temperature varying from 200 °C to 800 °C. X-ray diffraction analysis of all the samples confirmed the presence of cubic spinel phase of Nickel ferrite along with CoO phase without trace of any impurity. Sizes of the particles were studied from transmission electron micrographs and were found to be in agreement with those estimated from x-ray diffraction. Field cooled (FC) hysteresis loops at 5 K revealed an exchange bias (HE) of 2.2 kOe for the sample heated at 200 °C which decreased with the increase of particle size. Exchange bias expectedly vanished at 300 K due to high thermal energy (kBT) and low effective surface anisotropy. M-T curves revealed a blocking temperature of 135 K for the sample with smaller particle size.

The Effect of Game-Assisted Mathematics Education on Academic Achievement in Turkey: A Meta-Analysis Study

ERIC Educational Resources Information Center

Turgut, Sedat; Temur, Özlem Dogan

2017-01-01

In this research, the effects of using game in mathematics teaching process on academic achievement in Turkey were examined by metaanalysis method. For this purpose, the average effect size value and the average effect size values of the moderator variables (education level, the field of education, game type, implementation period and sample size)…

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

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

PubMed

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.

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

PubMed Central

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

Modeling ultrasound propagation through material of increasing geometrical complexity.

PubMed

Odabaee, Maryam; Odabaee, Mostafa; Pelekanos, Matthew; Leinenga, Gerhard; Götz, Jürgen

2018-06-01

Ultrasound is increasingly being recognized as a neuromodulatory and therapeutic tool, inducing a broad range of bio-effects in the tissue of experimental animals and humans. To achieve these effects in a predictable manner in the human brain, the thick cancellous skull presents a problem, causing attenuation. In order to overcome this challenge, as a first step, the acoustic properties of a set of simple bone-modeling resin samples that displayed an increasing geometrical complexity (increasing step sizes) were analyzed. Using two Non-Destructive Testing (NDT) transducers, we found that Wiener deconvolution predicted the Ultrasound Acoustic Response (UAR) and attenuation caused by the samples. However, whereas the UAR of samples with step sizes larger than the wavelength could be accurately estimated, the prediction was not accurate when the sample had a smaller step size. Furthermore, a Finite Element Analysis (FEA) performed in ANSYS determined that the scattering and refraction of sound waves was significantly higher in complex samples with smaller step sizes compared to simple samples with a larger step size. Together, this reveals an interaction of frequency and geometrical complexity in predicting the UAR and attenuation. These findings could in future be applied to poro-visco-elastic materials that better model the human skull. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Rapid detection of soils contaminated with heavy metals and oils by laser induced breakdown spectroscopy (LIBS).

PubMed

Kim, Gibaek; Kwak, Jihyun; Kim, Ki-Rak; Lee, Heesung; Kim, Kyoung-Woong; Yang, Hyeon; Park, Kihong

2013-12-15

A laser induced breakdown spectroscopy (LIBS) coupled with the chemometric method was applied to rapidly discriminate between soils contaminated with heavy metals or oils and clean soils. The effects of the water contents and grain sizes of soil samples on LIBS emissions were also investigated. The LIBS emission lines decreased by 59-75% when the water content increased from 1.2% to 7.8%, and soil samples with a grain size of 75 μm displayed higher LIBS emission lines with lower relative standard deviations than those with a 2mm grain size. The water content was found to have a more pronounced effect on the LIBS emission lines than the grain size. Pelletizing and sieving were conducted for all samples collected from abandoned mining areas and military camp to have similar water contents and grain sizes before being analyzed by the LIBS with the chemometric analysis. The data show that three types of soil samples were clearly discerned by using the first three principal components from the spectral data of soil samples. A blind test was conducted with a 100% correction rate for soil samples contaminated with heavy metals and oil residues. Copyright © 2013 Elsevier B.V. All rights reserved.

Size and modal analyses of fines and ultrafines from some Apollo 17 samples

NASA Technical Reports Server (NTRS)

Greene, G. M.; King, D. T., Jr.; Banholzer, G. S., Jr.; King, E. A.

1975-01-01

Scanning electron and optical microscopy techniques have been used to determine the grain-size frequency distributions and morphology-based modal analyses of fine and ultrafine fractions of some Apollo 17 regolith samples. There are significant and large differences between the grain-size frequency distributions of the less than 10-micron size fraction of Apollo 17 samples, but there are no clear relations to the local geologic setting from which individual samples have been collected. This may be due to effective lateral mixing of regolith particles in this size range by micrometeoroid impacts. None of the properties of the frequency distributions support the idea of selective transport of any fine grain-size fraction, as has been proposed by other workers. All of the particle types found in the coarser size fractions also occur in the less than 10-micron particles. In the size range from 105 to 10 microns there is a strong tendency for the percentage of regularly shaped glass to increase as the graphic mean grain size of the less than 1-mm size fraction decreases, both probably being controlled by exposure age.

Vitamin D receptor gene and osteoporosis - author`s response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Looney, J.E.; Yoon, Hyun Koo; Fischer, M.

1996-04-01

We appreciate the comments of Dr. Nguyen et al. about our recent study, but we disagree with their suggestion that the lack of an association between low bone density and the BB VDR genotype, which we reported, is an artifact generated by the small sample size. Furthermore, our results are consistent with similar conclusions reached by a number of other investigators, as recently reported by Peacock. Peacock states {open_quotes}Taken as a whole, the results of studies outlined ... indicate that VDR alleles, cannot account for the major part of the heritable component of bone density as indicated by Morrison etmore » al.{close_quotes}. The majority of the 17 studies cited in this editorial could not confirm an association between the VDR genotype and the bone phenotype. Surely one cannot criticize this combined work as representing an artifact because of a too small sample size. We do not dispute the suggestion by Nguyen et al. that large sample sizes are required to analyze small biological effects. This is evident in both Peacock`s summary and in their own bone density studies. We did not design our study with a larger sample size because, based on the work of Morrison et al., we had hypothesized a large biological effect; large sample sizes are only needed for small biological effects. 4 refs.« less

On the repeated measures designs and sample sizes for randomized controlled trials.

PubMed

Tango, Toshiro

2016-04-01

For the analysis of longitudinal or repeated measures data, generalized linear mixed-effects models provide a flexible and powerful tool to deal with heterogeneity among subject response profiles. However, the typical statistical design adopted in usual randomized controlled trials is an analysis of covariance type analysis using a pre-defined pair of "pre-post" data, in which pre-(baseline) data are used as a covariate for adjustment together with other covariates. Then, the major design issue is to calculate the sample size or the number of subjects allocated to each treatment group. In this paper, we propose a new repeated measures design and sample size calculations combined with generalized linear mixed-effects models that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for the analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size, compared with the simple pre-post design. The proposed designs and the sample size calculations are illustrated with real data arising from randomized controlled trials. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

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.

Conditional Optimal Design in Three- and Four-Level Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.; Borenstein, Michael

2014-01-01

The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to…

Characterization of Raman Scattering in Solid Samples with Different Particle Sizes and Elucidation on the Trends of Particle Size-Dependent Intensity Variations in Relation to Changes in the Sizes of Laser Illumination and Detection Area.

PubMed

Duy, Pham K; Chun, Seulah; Chung, Hoeil

2017-11-21

We have systematically characterized Raman scatterings in solid samples with different particle sizes and investigated subsequent trends of particle size-induced intensity variations. For this purpose, both lactose powders and pellets composed of five different particle sizes were prepared. Uniquely in this study, three spectral acquisition schemes with different sizes of laser illuminations and detection windows were employed for the evaluation, since it was expected that the experimental configuration would be another factor potentially influencing the intensity of the lactose peak, along with the particle size itself. In both samples, the distribution of Raman photons became broader with the increase in particle size, as the mean free path of laser photons, the average photon travel distance between consecutive scattering locations, became longer under this situation. When the particle size was the same, the Raman photon distribution was narrower in the pellets since the individual particles were more densely packed in a given volume (the shorter mean free path). When the size of the detection window was small, the number of photons reaching the detector decreased as the photon distribution was larger. Meanwhile, a large-window detector was able to collect the widely distributed Raman photons more effectively; therefore, the trends of intensity change with the variation in particle size were dissimilar depending on the employed spectral acquisition schemes. Overall, the Monte Carlo simulation was effective at probing the photon distribution inside the samples and helped to support the experimental observations.

Investigating the effect of sputtering conditions on the physical properties of aluminum thin film and the resulting alumina template

NASA Astrophysics Data System (ADS)

Taheriniya, Shabnam; Parhizgar, Sara Sadat; Sari, Amir Hossein

2018-06-01

To study the alumina template pore size distribution as a function of Al thin film grain size distribution, porous alumina templates were prepared by anodizing sputtered aluminum thin films. To control the grain size the aluminum samples were sputtered with the rate of 0.5, 1 and 2 Å/s and the substrate temperature was either 25, 75 or 125 °C. All samples were anodized for 120 s in 1 M sulfuric acid solution kept at 1 °C while a 15 V potential was being applied. The standard deviation value for samples deposited at room temperature but with different rates is roughly 2 nm in both thin film and porous template form but it rises to approximately 4 nm with substrate temperature. Samples with the average grain size of 13, 14, 18.5 and 21 nm respectively produce alumina templates with an average pore size of 8.5, 10, 15 and 16 nm in that order which shows the average grain size limits the average pore diameter in the resulting template. Lateral correlation length and grain boundary effect are other factors that affect the pore formation process and pore size distribution by limiting the initial current density.

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

ERIC Educational Resources Information Center

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…

Study on extrusion process of SiC ceramic matrix

NASA Astrophysics Data System (ADS)

Dai, Xiao-Yuan; Shen, Fan; Ji, Jia-You; Wang, Shu-Ling; Xu, Man

2017-11-01

In this thesis, the extrusion process of SiC ceramic matrix has been systematically studied.The effect of different cellulose content on the flexural strength and pore size distribution of SiC matrix was discussed.Reselts show that with the increase of cellulose content, the flexural strength decreased.The pore size distribution in the sample was 1um-4um, and the 1um-2um concentration was more concentrated. It is found that the cellulose content has little effect on the pore size distribution.When the cellulose content is 7%, the flexural strength of the sample is 40.9Mpa. At this time, the mechanical properties of the sample are the strongest.

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

PubMed

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 of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

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

PubMed

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.

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

PubMed

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.

Effects of sampling techniques on physical parameters and concentrations of selected persistent organic pollutants in suspended matter.

PubMed

Pohlert, Thorsten; Hillebrand, Gudrun; Breitung, Vera

2011-06-01

This study focusses on the effect of sampling techniques for suspended matter in stream water on subsequent particle-size distribution and concentrations of total organic carbon and selected persistent organic pollutants. The key questions are whether differences between the sampling techniques are due to the separation principle of the devices or due to the difference between time-proportional versus integral sampling. Several multivariate homogeneity tests were conducted on an extensive set of field-data that covers the period from 2002 to 2007, when up to three different sampling techniques were deployed in parallel at four monitoring stations of the River Rhine. The results indicate homogeneity for polychlorinated biphenyls, but significant effects due to the sampling techniques on particle-size, organic carbon and hexachlorobenzene. The effects can be amplified depending on the site characteristics of the monitoring stations.

[An investigation of the statistical power of the effect size in randomized controlled trials for the treatment of patients with type 2 diabetes mellitus using Chinese medicine].

PubMed

Ma, Li-Xin; Liu, Jian-Ping

2012-01-01

To investigate whether the power of the effect size was based on adequate sample size in randomized controlled trials (RCTs) for the treatment of patients with type 2 diabetes mellitus (T2DM) using Chinese medicine. China Knowledge Resource Integrated Database (CNKI), VIP Database for Chinese Technical Periodicals (VIP), Chinese Biomedical Database (CBM), and Wangfang Data were systematically recruited using terms like "Xiaoke" or diabetes, Chinese herbal medicine, patent medicine, traditional Chinese medicine, randomized, controlled, blinded, and placebo-controlled. Limitation was set on the intervention course > or = 3 months in order to identify the information of outcome assessement and the sample size. Data collection forms were made according to the checking lists found in the CONSORT statement. Independent double data extractions were performed on all included trials. The statistical power of the effects size for each RCT study was assessed using sample size calculation equations. (1) A total of 207 RCTs were included, including 111 superiority trials and 96 non-inferiority trials. (2) Among the 111 superiority trials, fasting plasma glucose (FPG) and glycosylated hemoglobin HbA1c (HbA1c) outcome measure were reported in 9% and 12% of the RCTs respectively with the sample size > 150 in each trial. For the outcome of HbA1c, only 10% of the RCTs had more than 80% power. For FPG, 23% of the RCTs had more than 80% power. (3) In the 96 non-inferiority trials, the outcomes FPG and HbA1c were reported as 31% and 36% respectively. These RCTs had a samples size > 150. For HbA1c only 36% of the RCTs had more than 80% power. For FPG, only 27% of the studies had more than 80% power. The sample size for statistical analysis was distressingly low and most RCTs did not achieve 80% power. In order to obtain a sufficient statistic power, it is recommended that clinical trials should establish clear research objective and hypothesis first, and choose scientific and evidence-based study design and outcome measurements. At the same time, calculate required sample size to ensure a precise research conclusion.

Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models.

PubMed

Liu, Jingxia; Colditz, Graham A

2018-05-01

There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two-group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs-exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

How Methodological Features Affect Effect Sizes in Education

ERIC Educational Resources Information Center

Cheung, Alan; Slavin, Robert

2016-01-01

As evidence-based reform becomes increasingly important in educational policy, it is becoming essential to understand how research design might contribute to reported effect sizes in experiments evaluating educational programs. The purpose of this study was to examine how methodological features such as types of publication, sample sizes, and…

Effects of pore-scale dispersion, degree of heterogeneity, sampling size, and source volume on the concentration moments of conservative solutes in heterogeneous formations

Treesearch

Daniele Tonina; Alberto Bellin

2008-01-01

Pore-scale dispersion (PSD), aquifer heterogeneity, sampling volume, and source size influence solute concentrations of conservative tracers transported in heterogeneous porous formations. In this work, we developed a new set of analytical solutions for the concentration ensemble mean, variance, and coefficient of variation (CV), which consider the effects of all these...

Particle size and surface area effects on the thin-pulse shock initiation of Diaminoazoxyfurazan (DAAF)

NASA Astrophysics Data System (ADS)

Burritt, Rosemary; Francois, Elizabeth; Windler, Gary; Chavez, David

2017-06-01

Diaminoazoxyfurazan (DAAF) has many of the safety characteristics of an insensitive high explosive (IHE): it is extremely insensitive to impact and friction and is comparable to triaminotrinitrobezene (TATB) in this way. Conversely, it demonstrates many performance characteristics of a Conventional High Explosive (CHE). DAAF has a small failure diameter of about 1.25 mm and can be sensitive to shock under the right conditions. Large particle sized DAAF will not initiate in a typical exploding foil initiator (EFI) configuration but smaller particle sizes will. Large particle sized DAAF, of 40 μm, was crash precipitated and ball milled into six distinct samples and pressed into pellets with a density of 1.60 g/cc (91% TMD). To investigate the effect of particle size and surface area on the direct initiation on DAAF multiple threshold tests were preformed on each sample of DAAF in different EFI configurations, which varied in flyer thickness and/or bridge size. Comparative tests were performed examining threshold voltage and correlated to Photon Doppler Velocimetry (PDV) results. The samples with larger particle sizes and surface area required more energy to initiate while the smaller particle sizes required less energy and could be initiated with smaller diameter flyers.

Sample size calculations for comparative clinical trials with over-dispersed Poisson process data.

PubMed

Matsui, Shigeyuki

2005-05-15

This paper develops a new formula for sample size calculations for comparative clinical trials with Poisson or over-dispersed Poisson process data. The criteria for sample size calculations is developed on the basis of asymptotic approximations for a two-sample non-parametric test to compare the empirical event rate function between treatment groups. This formula can accommodate time heterogeneity, inter-patient heterogeneity in event rate, and also, time-varying treatment effects. An application of the formula to a trial for chronic granulomatous disease is provided. Copyright 2004 John Wiley & Sons, Ltd.

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

PubMed

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.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

PubMed Central

Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric

2016-01-01

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. PMID:26943927

How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study.

PubMed

Hittner, James B; May, Kim

2012-01-01

The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.

Influence of pore size distributions on decomposition of maize leaf residue: evidence from X-ray computed micro-tomography

NASA Astrophysics Data System (ADS)

Negassa, Wakene; Guber, Andrey; Kravchenko, Alexandra; Rivers, Mark

2014-05-01

Soil's potential to sequester carbon (C) depends not only on quality and quantity of organic inputs to soil but also on the residence time of the applied organic inputs within the soil. Soil pore structure is one of the main factors that influence residence time of soil organic matter by controlling gas exchange, soil moisture and microbial activities, thereby soil C sequestration capacity. Previous attempts to investigate the fate of organic inputs added to soil did not allow examining their decomposition in situ; the drawback that can now be remediated by application of X-ray computed micro-tomography (µ-CT). The non-destructive and non-invasive nature of µ-CT gives an opportunity to investigate the effect of soil pore size distributions on decomposition of plant residues at a new quantitative level. The objective of this study is to examine the influence of pore size distributions on the decomposition of plant residue added to soil. Samples with contrasting pore size distributions were created using aggregate fractions of five different sizes (<0.05, 0.05-0.1, 0.10-05, 0.5-1.0 and 1.0-2.0 mm). Weighted average pore diameters ranged from 10 µm (<0.05 mm fraction) to 104 µm (1-2 mm fraction), while maximum pore diameter were in a range from 29 µm (<0.05 mm fraction) to 568 µm (1-2 mm fraction) in the created soil samples. Dried pieces of maize leaves 2.5 mg in size (equivalent to 1.71 mg C g-1 soil) were added to half of the studied samples. Samples with and without maize leaves were incubated for 120 days. CO2 emission from the samples was measured at regular time intervals. In order to ensure that the observed differences are due to differences in pore structure and not due to differences in inherent properties of the studied aggregate fractions, we repeated the whole experiment using soil from the same aggregate size fractions but ground to <0.05 mm size. Five to six replicated samples were used for intact and ground samples of all sizes with and without leaves. Two replications of the intact aggregate fractions of all sizes with leaves were subjected to µ-CT scanning before and after incubation, whereas all the remaining replications of both intact and ground aggregate fractions of <0.05, 0.05-0.1, and 1.0-2.0 mm sizes with leaves were scanned with µ-CT after the incubation. The µ-CT image showed that approximately 80% of the leaves in the intact samples of large aggregate fractions (0.5-1.0 and 1.0-2.0 mm) was decomposed during the incubation, while only 50-60% of the leaves were decomposed in the intact samples of smaller sized fractions. Even lower percent of leaves (40-50%) was decomposed in the ground samples, with very similar leaf decomposition observed in all ground samples regardless of the aggregate fraction size. Consistent with µ-CT results, the proportion of decomposed leaf estimated with the conventional mass loss method was 48% and 60% for the <0.05 mm and 1.0-2.0 mm soil size fractions of intact aggregates, and 40-50% in ground samples, respectively. The results of the incubation experiment demonstrated that, while greater C mineralization was observed in samples of all size fractions amended with leaf, the effect of leaf presence was most pronounced in the smaller aggregate fractions (0.05-0.1 mm and 0.05 mm) of intact aggregates. The results of the present study unequivocally demonstrate that differences in pore size distributions have a major effect on the decomposition of plant residues added to soil. Moreover, in presence of plant residues, differences in pore size distributions appear to also influence the rates of decomposition of the intrinsic soil organic material.

Standardized mean differences cause funnel plot distortion in publication bias assessments.

PubMed

Zwetsloot, Peter-Paul; Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris Ah; Chamuleau, Steven Aj; MacLeod, Malcolm R; Wever, Kimberley E

2017-09-08

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.

Standardized mean differences cause funnel plot distortion in publication bias assessments

PubMed Central

Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris AH; Chamuleau, Steven AJ; MacLeod, Malcolm R

2017-01-01

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results. PMID:28884685

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

PubMed

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.

ZnFe2O4 nanoparticles dispersed in a highly porous silica aerogel matrix: a magnetic study.

PubMed

Bullita, S; Casu, A; Casula, M F; Concas, G; Congiu, F; Corrias, A; Falqui, A; Loche, D; Marras, C

2014-03-14

We report the detailed structural characterization and magnetic investigation of nanocrystalline zinc ferrite nanoparticles supported on a silica aerogel porous matrix which differ in size (in the range 4-11 nm) and the inversion degree (from 0.4 to 0.2) as compared to bulk zinc ferrite which has a normal spinel structure. The samples were investigated by zero-field-cooling-field-cooling, thermo-remnant DC magnetization measurements, AC magnetization investigation and Mössbauer spectroscopy. The nanocomposites are superparamagnetic at room temperature; the temperature of the superparamagnetic transition in the samples decreases with the particle size and therefore it is mainly determined by the inversion degree rather than by the particle size, which would give an opposite effect on the blocking temperature. The contribution of particle interaction to the magnetic behavior of the nanocomposites decreases significantly in the sample with the largest particle size. The values of the anisotropy constant give evidence that the anisotropy constant decreases upon increasing the particle size of the samples. All these results clearly indicate that, even when dispersed with low concentration in a non-magnetic and highly porous and insulating matrix, the zinc ferrite nanoparticles show a magnetic behavior similar to that displayed when they are unsupported or dispersed in a similar but denser matrix, and with higher loading. The effective anisotropy measured for our samples appears to be systematically higher than that measured for supported zinc ferrite nanoparticles of similar size, indicating that this effect probably occurs as a consequence of the high inversion degree.

Accounting for treatment by center interaction in sample size determinations and the use of surrogate outcomes in the pessary for the prevention of preterm birth trial: a simulation study.

PubMed

Willan, Andrew R

2016-07-05

The Pessary for the Prevention of Preterm Birth Study (PS3) is an international, multicenter, randomized clinical trial designed to examine the effectiveness of the Arabin pessary in preventing preterm birth in pregnant women with a short cervix. During the design of the study two methodological issues regarding power and sample size were raised. Since treatment in the Standard Arm will vary between centers, it is anticipated that so too will the probability of preterm birth in that arm. This will likely result in a treatment by center interaction, and the issue of how this will affect the sample size requirements was raised. The sample size requirements to examine the effect of the pessary on the baby's clinical outcome was prohibitively high, so the second issue is how best to examine the effect on clinical outcome. The approaches taken to address these issues are presented. Simulation and sensitivity analysis were used to address the sample size issue. The probability of preterm birth in the Standard Arm was assumed to vary between centers following a Beta distribution with a mean of 0.3 and a coefficient of variation of 0.3. To address the second issue a Bayesian decision model is proposed that combines the information regarding the between-treatment difference in the probability of preterm birth from PS3 with the data from the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study that relate preterm birth and perinatal mortality/morbidity. The approach provides a between-treatment comparison with respect to the probability of a bad clinical outcome. The performance of the approach was assessed using simulation and sensitivity analysis. Accounting for a possible treatment by center interaction increased the sample size from 540 to 700 patients per arm for the base case. The sample size requirements increase with the coefficient of variation and decrease with the number of centers. Under the same assumptions used for determining the sample size requirements, the simulated mean probability that pessary reduces the risk of perinatal mortality/morbidity is 0.98. The simulated mean decreased with coefficient of variation and increased with the number of clinical sites. Employing simulation and sensitivity analysis is a useful approach for determining sample size requirements while accounting for the additional uncertainty due to a treatment by center interaction. Using a surrogate outcome in conjunction with a Bayesian decision model is an efficient way to compare important clinical outcomes in a randomized clinical trial in situations where the direct approach requires a prohibitively high sample size.

Effect of Study Design on Sample Size in Studies Intended to Evaluate Bioequivalence of Inhaled Short‐Acting β‐Agonist Formulations

PubMed Central

Zeng, Yaohui; Singh, Sachinkumar; Wang, Kai

2017-01-01

Abstract Pharmacodynamic studies that use methacholine challenge to assess bioequivalence of generic and innovator albuterol formulations are generally designed per published Food and Drug Administration guidance, with 3 reference doses and 1 test dose (3‐by‐1 design). These studies are challenging and expensive to conduct, typically requiring large sample sizes. We proposed 14 modified study designs as alternatives to the Food and Drug Administration–recommended 3‐by‐1 design, hypothesizing that adding reference and/or test doses would reduce sample size and cost. We used Monte Carlo simulation to estimate sample size. Simulation inputs were selected based on published studies and our own experience with this type of trial. We also estimated effects of these modified study designs on study cost. Most of these altered designs reduced sample size and cost relative to the 3‐by‐1 design, some decreasing cost by more than 40%. The most effective single study dose to add was 180 μg of test formulation, which resulted in an estimated 30% relative cost reduction. Adding a single test dose of 90 μg was less effective, producing only a 13% cost reduction. Adding a lone reference dose of either 180, 270, or 360 μg yielded little benefit (less than 10% cost reduction), whereas adding 720 μg resulted in a 19% cost reduction. Of the 14 study design modifications we evaluated, the most effective was addition of both a 90‐μg test dose and a 720‐μg reference dose (42% cost reduction). Combining a 180‐μg test dose and a 720‐μg reference dose produced an estimated 36% cost reduction. PMID:29281130

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.

PubMed

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.

Size Effects in the Resistivity of Kondo and Spin-Glass Wires

NASA Astrophysics Data System (ADS)

van Haesendonck, Chris

1998-03-01

Recently, several experiments have focused on possible size effects for the Kondo scattering in thin-film structures of very dilute magnetic alloys (concentration ~ 100 ppm) (For an overview, see M.A. Blachly and N. Giordano, Phys. Rev. B 51), 12537 (1995).. Intuitively, one expects size effects to occur as soon as the sample dimensions become smaller than the size of the Kondo screening cloud which induces a compensation of the local magnetic moments below the Kondo temperature. Since the size of the Kondo cloud is predicted to be of the order of 1 μ m, one should be able to observe pronounced size effects in thin-film Kondo alloys which have been patterned by standard electron beam lithography. Experiments performed by other groups have indeed revealed an important reduction of the slope of the Kondo resistivity for samples with micrometer dimensions. These experiments also show that the size effects are affected by disorder. On the other hand, our experiments on AuFe wires, which have been prepared by flash evaporation as well as by ion implantation, indicate the absence of size effects for the Kondo scattering down to a width of 38 nm. Therefore, the existence of the Kondo cloud remains a controversial issue. The size effects have also been investigated for more concentrated spin-glass alloys (concentration ~ 1 at.%). The resistivity measurements of thin-film spin glasses indicate that intrinsic size effects may be present for length scales below 100 nm (K.R. Lane et al., Phys. Rev. B 51), 945 (1995); G. Neuttiens et al., Europhys. Lett. 34, 617 (1996).. Due to the damping of the RKKY interaction by elastic defect scattering, size effects in the spin-glass regime can be strongly affected by disorder.

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

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

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

Effects of crystallite size on the structure and magnetism of ferrihydrite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xiaoming; Zhu, Mengqiang; Koopal, Luuk K.

2015-12-15

The structure and magnetic properties of nano-sized (1.6 to 4.4 nm) ferrihydrite samples are systematically investigated through a combination of X-ray diffraction (XRD), X-ray pair distribution function (PDF), X-ray absorption spectroscopy (XAS) and magnetic analyses. The XRD, PDF and Fe K-edge XAS data of the ferrihydrite samples are all fitted well with the Michel ferrihydrite model, indicating similar local-, medium- and long-range ordered structures. PDF and XAS fitting results indicate that, with increasing crystallite size, the average coordination numbers of Fe–Fe and the unit cell parameter c increase, while Fe2 and Fe3 vacancies and the unit cell parameter a decrease.more » Mössbauer results indicate that the surface layer is relatively disordered, which might have been caused by the random distribution of Fe vacancies. These results support Hiemstra's surface-depletion model in terms of the location of disorder and the variations of Fe2 and Fe3 occupancies with size. Magnetic data indicate that the ferrihydrite samples show antiferromagnetism superimposed with a ferromagnetic-like moment at lower temperatures (100 K and 10 K), but ferrihydrite is paramagnetic at room temperature. In addition, both the magnetization and coercivity decrease with increasing ferrihydrite crystallite size due to strong surface effects in fine-grained ferrihydrites. Smaller ferrihydrite samples show less magnetic hyperfine splitting and a lower unblocking temperature (T B) than larger samples. The dependence of magnetic properties on grain size for nano-sized ferrihydrite provides a practical way to determine the crystallite size of ferrihydrite quantitatively in natural environments or artificial systems.« less

Size-selective separation of polydisperse gold nanoparticles in supercritical ethane.

PubMed

Williams, Dylan P; Satherley, John

2009-04-09

The aim of this study was to use supercritical ethane to selectively disperse alkanethiol-stabilized gold nanoparticles of one size from a polydisperse sample in order to recover a monodisperse fraction of the nanoparticles. A disperse sample of metal nanoparticles with diameters in the range of 1-5 nm was prepared using established techniques then further purified by Soxhlet extraction. The purified sample was subjected to supercritical ethane at a temperature of 318 K in the pressure range 50-276 bar. Particles were characterized by UV-vis absorption spectroscopy, TEM, and MALDI-TOF mass spectroscopy. The results show that with increasing pressure the dispersibility of the nanoparticles increases, this effect is most pronounced for smaller nanoparticles. At the highest pressure investigated a sample of the particles was effectively stripped of all the smaller particles leaving a monodisperse sample. The relationship between dispersibility and supercritical fluid density for two different size samples of alkanethiol-stabilized gold nanoparticles was considered using the Chrastil chemical equilibrium model.

Revisiting sample size: are big trials the answer?

PubMed

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.

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

ERIC Educational Resources Information Center

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…

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

PubMed

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.

Numerical modeling of the tensile strength of a biological granular aggregate: Effect of the particle size distribution

NASA Astrophysics Data System (ADS)

Heinze, Karsta; Frank, Xavier; Lullien-Pellerin, Valérie; George, Matthieu; Radjai, Farhang; Delenne, Jean-Yves

2017-06-01

Wheat grains can be considered as a natural cemented granular material. They are milled under high forces to produce food products such as flour. The major part of the grain is the so-called starchy endosperm. It contains stiff starch granules, which show a multi-modal size distribution, and a softer protein matrix that surrounds the granules. Experimental milling studies and numerical simulations are going hand in hand to better understand the fragmentation behavior of this biological material and to improve milling performance. We present a numerical study of the effect of granule size distribution on the strength of such a cemented granular material. Samples of bi-modal starch granule size distribution were created and submitted to uniaxial tension, using a peridynamics method. We show that, when compared to the effects of starch-protein interface adhesion and voids, the granule size distribution has a limited effect on the samples' yield stress.

Using known map category marginal frequencies to improve estimates of thematic map accuracy

NASA Technical Reports Server (NTRS)

Card, D. H.

1982-01-01

By means of two simple sampling plans suggested in the accuracy-assessment literature, it is shown how one can use knowledge of map-category relative sizes to improve estimates of various probabilities. The fact that maximum likelihood estimates of cell probabilities for the simple random sampling and map category-stratified sampling were identical has permitted a unified treatment of the contingency-table analysis. A rigorous analysis of the effect of sampling independently within map categories is made possible by results for the stratified case. It is noted that such matters as optimal sample size selection for the achievement of a desired level of precision in various estimators are irrelevant, since the estimators derived are valid irrespective of how sample sizes are chosen.

Sample size requirements for the design of reliability studies: precision consideration.

PubMed

Shieh, Gwowen

2014-09-01

In multilevel modeling, the intraclass correlation coefficient based on the one-way random-effects model is routinely employed to measure the reliability or degree of resemblance among group members. To facilitate the advocated practice of reporting confidence intervals in future reliability studies, this article presents exact sample size procedures for precise interval estimation of the intraclass correlation coefficient under various allocation and cost structures. Although the suggested approaches do not admit explicit sample size formulas and require special algorithms for carrying out iterative computations, they are more accurate than the closed-form formulas constructed from large-sample approximations with respect to the expected width and assurance probability criteria. This investigation notes the deficiency of existing methods and expands the sample size methodology for the design of reliability studies that have not previously been discussed in the literature.

Are power calculations useful? A multicentre neuroimaging study

PubMed Central

Suckling, John; Henty, Julian; Ecker, Christine; Deoni, Sean C; Lombardo, Michael V; Baron-Cohen, Simon; Jezzard, Peter; Barnes, Anna; Chakrabarti, Bhismadev; Ooi, Cinly; Lai, Meng-Chuan; Williams, Steven C; Murphy, Declan GM; Bullmore, Edward

2014-01-01

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources. PMID:24644267

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Estimating the size of hidden populations using respondent-driven sampling data: Case examples from Morocco

PubMed Central

Johnston, Lisa G; McLaughlin, Katherine R; Rhilani, Houssine El; Latifi, Amina; Toufik, Abdalla; Bennani, Aziza; Alami, Kamal; Elomari, Boutaina; Handcock, Mark S

2015-01-01

Background Respondent-driven sampling is used worldwide to estimate the population prevalence of characteristics such as HIV/AIDS and associated risk factors in hard-to-reach populations. Estimating the total size of these populations is of great interest to national and international organizations, however reliable measures of population size often do not exist. Methods Successive Sampling-Population Size Estimation (SS-PSE) along with network size imputation allows population size estimates to be made without relying on separate studies or additional data (as in network scale-up, multiplier and capture-recapture methods), which may be biased. Results Ten population size estimates were calculated for people who inject drugs, female sex workers, men who have sex with other men, and migrants from sub-Sahara Africa in six different cities in Morocco. SS-PSE estimates fell within or very close to the likely values provided by experts and the estimates from previous studies using other methods. Conclusions SS-PSE is an effective method for estimating the size of hard-to-reach populations that leverages important information within respondent-driven sampling studies. The addition of a network size imputation method helps to smooth network sizes allowing for more accurate results. However, caution should be used particularly when there is reason to believe that clustered subgroups may exist within the population of interest or when the sample size is small in relation to the population. PMID:26258908

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

NASA Astrophysics Data System (ADS)

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.

Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs

PubMed Central

Lakens, Daniël

2013-01-01

Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists themselves, effect sizes are most useful because they facilitate cumulative science. Effect sizes can be used to determine the sample size for follow-up studies, or examining effects across studies. This article aims to provide a practical primer on how to calculate and report effect sizes for t-tests and ANOVA's such that effect sizes can be used in a-priori power analyses and meta-analyses. Whereas many articles about effect sizes focus on between-subjects designs and address within-subjects designs only briefly, I provide a detailed overview of the similarities and differences between within- and between-subjects designs. I suggest that some research questions in experimental psychology examine inherently intra-individual effects, which makes effect sizes that incorporate the correlation between measures the best summary of the results. Finally, a supplementary spreadsheet is provided to make it as easy as possible for researchers to incorporate effect size calculations into their workflow. PMID:24324449

Guiding of Plasmons and Phonons in Complex Three Dimensional Structures

DTIC Science & Technology

2013-01-01

typical sample. We employed X - ray diffraction (XRD) to measure the average grain size across the entire depth of the sample over spot sizes Figure...propagation distance L as the 1/e decay length of the field intensity along x ...as well as the network layout with subwavelegth gap size and internode distance on the order of the effective wavelength, a small 2 x 2 resonant

Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure.

PubMed

Ciarleglio, Maria M; Arendt, Christopher D; Peduzzi, Peter N

2016-06-01

When designing studies that have a continuous outcome as the primary endpoint, the hypothesized effect size ([Formula: see text]), that is, the hypothesized difference in means ([Formula: see text]) relative to the assumed variability of the endpoint ([Formula: see text]), plays an important role in sample size and power calculations. Point estimates for [Formula: see text] and [Formula: see text] are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed. This article presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of [Formula: see text] and [Formula: see text] into the study's power calculation. Conditional expected power, which averages the traditional power curve using the prior distributions of [Formula: see text] and [Formula: see text] as the averaging weight, is used, and the value of [Formula: see text] is found that equates the prespecified frequentist power ([Formula: see text]) and the conditional expected power of the trial. This hypothesized effect size is then used in traditional sample size calculations when determining sample size for the study. The value of [Formula: see text] found using this method may be expressed as a function of the prior means of [Formula: see text] and [Formula: see text], [Formula: see text], and their prior standard deviations, [Formula: see text]. We show that the "naïve" estimate of the effect size, that is, the ratio of prior means, should be down-weighted to account for the variability in the parameters. An example is presented for designing a placebo-controlled clinical trial testing the antidepressant effect of alprazolam as monotherapy for major depression. Through this method, we are able to formally integrate prior information on the uncertainty and variability of both the treatment effect and the common standard deviation into the design of the study while maintaining a frequentist framework for the final analysis. Solving for the effect size which the study has a high probability of correctly detecting based on the available prior information on the difference [Formula: see text] and the standard deviation [Formula: see text] provides a valuable, substantiated estimate that can form the basis for discussion about the study's feasibility during the design phase. © The Author(s) 2016.

Sample-size needs for forestry herbicide trials

Treesearch

S.M. Zedaker; T.G. Gregoire; James H. Miller

1994-01-01

Forest herbicide experiments are increasingly being designed to evaluate smaller treatment differences when comparing existing effective treatments, tank mix ratios, surfactants, and new low-rate products. The ability to detect small differences in efficacy is dependent upon the relationship among sample size. type I and II error probabilities, and the coefficients of...

The Effects of Model Misspecification and Sample Size on LISREL Maximum Likelihood Estimates.

ERIC Educational Resources Information Center

Baldwin, Beatrice

The robustness of LISREL computer program maximum likelihood estimates under specific conditions of model misspecification and sample size was examined. The population model used in this study contains one exogenous variable; three endogenous variables; and eight indicator variables, two for each latent variable. Conditions of model…

Effects of storage time and temperature on pH, specific gravity, and crystal formation in urine samples from dogs and cats.

PubMed

Albasan, Hasan; Lulich, Jody P; Osborne, Carl A; Lekcharoensuk, Chalermpol; Ulrich, Lisa K; Carpenter, Kathleen A

2003-01-15

To determine effects of storage temperature and time on pH and specific gravity of and number and size of crystals in urine samples from dogs and cats. Randomized complete block design. 31 dogs and 8 cats. Aliquots of each urine sample were analyzed within 60 minutes of collection or after storage at room or refrigeration temperatures (20 vs 6 degrees C [68 vs 43 degrees F]) for 6 or 24 hours. Crystals formed in samples from 11 of 39 (28%) animals. Calcium oxalate (CaOx) crystals formed in vitro in samples from 1 cat and 8 dogs. Magnesium ammonium phosphate (MAP) crystals formed in vitro in samples from 2 dogs. Compared with aliquots stored at room temperature, refrigeration increased the number and size of crystals that formed in vitro; however, the increase in number and size of MAP crystals in stored urine samples was not significant. Increased storage time and decreased storage temperature were associated with a significant increase in number of CaOx crystals formed. Greater numbers of crystals formed in urine aliquots stored for 24 hours than in aliquots stored for 6 hours. Storage time and temperature did not have a significant effect on pH or specific gravity. Urine samples should be analyzed within 60 minutes of collection to minimize temperature- and time-dependent effects on in vitro crystal formation. Presence of crystals observed in stored samples should be validated by reevaluation of fresh urine.

Inflammation response and cytotoxic effects in human THP-1 cells of size-fractionated PM10 extracts in a polluted urban site.

PubMed

Schilirò, T; Alessandria, L; Bonetta, S; Carraro, E; Gilli, G

2016-02-01

To contribute to a greater characterization of the airborne particulate matter's toxicity, size-fractionated PM10 was sampled during different seasons in a polluted urban site in Torino, a northern Italian city. Three main size fractions (PM10 - 3 μm; PM3 - 0.95 μm; PM < 0.95 μm) extracts (organic and aqueous) were assayed with THP-1 cells to evaluate their effects on cell proliferation, LDH activity, TNFα, IL-8 and CYP1A1 expression. The mean PM10 concentrations were statistically different in summer and in winter and the finest fraction PM<0.95 was always higher than the others. Size-fractionated PM10 extracts, sampled in an urban traffic meteorological-chemical station produced size-related toxicological effects in relation to season and particles extraction. The PM summer extracts induced a significant release of LDH compared to winter and produced a size-related effect, with higher values measured with PM10-3. Exposure to size-fractionated PM10 extracts did not induce significant expression of TNFα. IL-8 expression was influenced by exposure to size-fractionated PM10 extracts and statistically significant differences were found between kind of extracts for both seasons. The mean fold increases in CYP1A1 expression were statistically different in summer and in winter; winter fraction extracts produced a size-related effect, in particular for organic samples with higher values measured with PM<0.95 extracts. Our results confirm that the only measure of PM can be misleading for the assessment of air quality moreover we support efforts toward identifying potential effect-based tools (e.g. in vitro test) that could be used in the context of the different monitoring programs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review

PubMed Central

Morris, Tom; Gray, Laura

2017-01-01

Objectives To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Setting Any, not limited to healthcare settings. Participants Any taking part in an SW-CRT published up to March 2016. Primary and secondary outcome measures The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Results Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22–0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Conclusions Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. PMID:29146637

The relationship between national-level carbon dioxide emissions and population size: an assessment of regional and temporal variation, 1960-2005.

PubMed

Jorgenson, Andrew K; Clark, Brett

2013-01-01

This study examines the regional and temporal differences in the statistical relationship between national-level carbon dioxide emissions and national-level population size. The authors analyze panel data from 1960 to 2005 for a diverse sample of nations, and employ descriptive statistics and rigorous panel regression modeling techniques. Initial descriptive analyses indicate that all regions experienced overall increases in carbon emissions and population size during the 45-year period of investigation, but with notable differences. For carbon emissions, the sample of countries in Asia experienced the largest percent increase, followed by countries in Latin America, Africa, and lastly the sample of relatively affluent countries in Europe, North America, and Oceania combined. For population size, the sample of countries in Africa experienced the largest percent increase, followed countries in Latin America, Asia, and the combined sample of countries in Europe, North America, and Oceania. Findings for two-way fixed effects panel regression elasticity models of national-level carbon emissions indicate that the estimated elasticity coefficient for population size is much smaller for nations in Africa than for nations in other regions of the world. Regarding potential temporal changes, from 1960 to 2005 the estimated elasticity coefficient for population size decreased by 25% for the sample of Africa countries, 14% for the sample of Asia countries, 6.5% for the sample of Latin America countries, but remained the same in size for the sample of countries in Europe, North America, and Oceania. Overall, while population size continues to be the primary driver of total national-level anthropogenic carbon dioxide emissions, the findings for this study highlight the need for future research and policies to recognize that the actual impacts of population size on national-level carbon emissions differ across both time and region.

Sampling methods, dispersion patterns, and fixed precision sequential sampling plans for western flower thrips (Thysanoptera: Thripidae) and cotton fleahoppers (Hemiptera: Miridae) in cotton.

PubMed

Parajulee, M N; Shrestha, R B; Leser, J F

2006-04-01

A 2-yr field study was conducted to examine the effectiveness of two sampling methods (visual and plant washing techniques) for western flower thrips, Frankliniella occidentalis (Pergande), and five sampling methods (visual, beat bucket, drop cloth, sweep net, and vacuum) for cotton fleahopper, Pseudatomoscelis seriatus (Reuter), in Texas cotton, Gossypium hirsutum (L.), and to develop sequential sampling plans for each pest. The plant washing technique gave similar results to the visual method in detecting adult thrips, but the washing technique detected significantly higher number of thrips larvae compared with the visual sampling. Visual sampling detected the highest number of fleahoppers followed by beat bucket, drop cloth, vacuum, and sweep net sampling, with no significant difference in catch efficiency between vacuum and sweep net methods. However, based on fixed precision cost reliability, the sweep net sampling was the most cost-effective method followed by vacuum, beat bucket, drop cloth, and visual sampling. Taylor's Power Law analysis revealed that the field dispersion patterns of both thrips and fleahoppers were aggregated throughout the crop growing season. For thrips management decision based on visual sampling (0.25 precision), 15 plants were estimated to be the minimum sample size when the estimated population density was one thrips per plant, whereas the minimum sample size was nine plants when thrips density approached 10 thrips per plant. The minimum visual sample size for cotton fleahoppers was 16 plants when the density was one fleahopper per plant, but the sample size decreased rapidly with an increase in fleahopper density, requiring only four plants to be sampled when the density was 10 fleahoppers per plant. Sequential sampling plans were developed and validated with independent data for both thrips and cotton fleahoppers.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, Eric; Cai, Jing; Benson, David; Nesterenko, Vitali

2007-06-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed (CIP) composites of polytetrafluoroethylene (PTFE), tungsten and aluminum powders show significant differences depending on the size of metallic particles. PTFE and aluminum mixtures are known to be energetic under dynamic and thermal loading. The addition of tungsten increases density and overall strength of the sample. Multi-material Eulerian and arbitrary Lagrangian-Eulerian methods were used for the investigation due to the complexity of the microstructure, relatively large deformations and the ability to handle the formation of free surfaces in a natural manner. The calculations indicate that the observed dependence of sample strength on particle size is due to the formation of force chains under dynamic loading in samples with small particle sizes even at larger porosity in comparison with samples with large grain size and larger density.

A standardized sampling protocol for channel catfish in prairie streams

USGS Publications Warehouse

Vokoun, Jason C.; Rabeni, Charles F.

2001-01-01

Three alternative gears—an AC electrofishing raft, bankpoles, and a 15-hoop-net set—were used in a standardized manner to sample channel catfish Ictalurus punctatus in three prairie streams of varying size in three seasons. We compared these gears as to time required per sample, size selectivity, mean catch per unit effort (CPUE) among months, mean CPUE within months, effect of fluctuating stream stage, and sensitivity to population size. According to these comparisons, the 15-hoop-net set used during stable water levels in October had the most desirable characteristics. Using our catch data, we estimated the precision of CPUE and size structure by varying sample sizes for the 15-hoop-net set. We recommend that 11–15 repetitions of the 15-hoop-net set be used for most management activities. This standardized basic unit of effort will increase the precision of estimates and allow better comparisons among samples as well as increased confidence in management decisions.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

The use of group sequential, information-based sample size re-estimation in the design of the PRIMO study of chronic kidney disease.

PubMed

Pritchett, Yili; Jemiai, Yannis; Chang, Yuchiao; Bhan, Ishir; Agarwal, Rajiv; Zoccali, Carmine; Wanner, Christoph; Lloyd-Jones, Donald; Cannata-Andía, Jorge B; Thompson, Taylor; Appelbaum, Evan; Audhya, Paul; Andress, Dennis; Zhang, Wuyan; Solomon, Scott; Manning, Warren J; Thadhani, Ravi

2011-04-01

Chronic kidney disease is associated with a marked increase in risk for left ventricular hypertrophy and cardiovascular mortality compared with the general population. Therapy with vitamin D receptor activators has been linked with reduced mortality in chronic kidney disease and an improvement in left ventricular hypertrophy in animal studies. PRIMO (Paricalcitol capsules benefits in Renal failure Induced cardia MOrbidity) is a multinational, multicenter randomized controlled trial to assess the effects of paricalcitol (a selective vitamin D receptor activator) on mild to moderate left ventricular hypertrophy in patients with chronic kidney disease. Subjects with mild-moderate chronic kidney disease are randomized to paricalcitol or placebo after confirming left ventricular hypertrophy using a cardiac echocardiogram. Cardiac magnetic resonance imaging is then used to assess left ventricular mass index at baseline, 24 and 48 weeks, which is the primary efficacy endpoint of the study. Because of limited prior data to estimate sample size, a maximum information group sequential design with sample size re-estimation is implemented to allow sample size adjustment based on the nuisance parameter estimated using the interim data. An interim efficacy analysis is planned at a pre-specified time point conditioned on the status of enrollment. The decision to increase sample size depends on the observed treatment effect. A repeated measures analysis model, using available data at Week 24 and 48 with a backup model of an ANCOVA analyzing change from baseline to the final nonmissing observation, are pre-specified to evaluate the treatment effect. Gamma-family of spending function is employed to control family-wise Type I error rate as stopping for success is planned in the interim efficacy analysis. If enrollment is slower than anticipated, the smaller sample size used in the interim efficacy analysis and the greater percent of missing week 48 data might decrease the parameter estimation accuracy, either for the nuisance parameter or for the treatment effect, which might in turn affect the interim decision-making. The application of combining a group sequential design with a sample-size re-estimation in clinical trial design has the potential to improve efficiency and to increase the probability of trial success while ensuring integrity of the study.

Effects of grain size, mineralogy, and acid-extractable grain coatings on the distribution of the fallout radionuclides 7Be, 10Be, 137Cs, and 210Pb in river sediment

NASA Astrophysics Data System (ADS)

Singleton, Adrian A.; Schmidt, Amanda H.; Bierman, Paul R.; Rood, Dylan H.; Neilson, Thomas B.; Greene, Emily Sophie; Bower, Jennifer A.; Perdrial, Nicolas

2017-01-01

Grain-size dependencies in fallout radionuclide activity have been attributed to either increase in specific surface area in finer grain sizes or differing mineralogical abundances in different grain sizes. Here, we consider a third possibility, that the concentration and composition of grain coatings, where fallout radionuclides reside, controls their activity in fluvial sediment. We evaluated these three possible explanations in two experiments: (1) we examined the effect of sediment grain size, mineralogy, and composition of the acid-extractable materials on the distribution of 7Be, 10Be, 137Cs, and unsupported 210Pb in detrital sediment samples collected from rivers in China and the United States, and (2) we periodically monitored 7Be, 137Cs, and 210Pb retention in samples of known composition exposed to natural fallout in Ohio, USA for 294 days. Acid-extractable materials (made up predominately of Fe, Mn, Al, and Ca from secondary minerals and grain coatings produced during pedogenesis) are positively related to the abundance of fallout radionuclides in our sediment samples. Grain-size dependency of fallout radionuclide concentrations was significant in detrital sediment samples, but not in samples exposed to fallout under controlled conditions. Mineralogy had a large effect on 7Be and 210Pb retention in samples exposed to fallout, suggesting that sieving sediments to a single grain size or using specific surface area-based correction terms may not completely control for preferential distribution of these nuclides. We conclude that time-dependent geochemical, pedogenic, and sedimentary processes together result in the observed differences in nuclide distribution between different grain sizes and substrate compositions. These findings likely explain variability of measured nuclide activities in river networks that exceeds the variability introduced by analytical techniques as well as spatial and temporal differences in erosion rates and processes. In short, we suggest that presence and amount of pedogenic grain coatings is more important than either specific surface area or surface charge in setting the distribution of fallout radionuclides.

Effects of particle size on magnetostrictive properties of magnetostrictive composites with low particulate volume fraction

NASA Astrophysics Data System (ADS)

Dong, Xufeng; Guan, Xinchun; Ou, Jinping

2009-03-01

In the past ten years, there have been several investigations on the effects of particle size on magnetostrictive properties of polymer-bonded Terfenol-D composites, but they didn't get an agreement. To solve the conflict among them, Terfenol-D/unsaturated polyester resin composite samples were prepared from Tb0.3Dy0.7Fe2 powder with 20% volume fraction in six particle-size ranges (30-53, 53-150, 150-300, 300-450, 450-500 and 30-500μm). Then their magnetostrictive properties were tested. The results indicate the 53-150μm distribution presents the largest static and dynamic magnetostriction among the five monodispersed distribution samples. But the 30-500μm (polydispersed) distribution shows even larger response than 53-150μm distribution. It indicates the particle size level plays a doubleedged sword on magnetostrictive properties of magnetostrictive composites. The existence of the optimal particle size to prepare polymer-bonded Terfenol-D, whose composition is Tb0.3Dy0.7Fe2, is resulted from the competition between the positive effects and negative effects of increasing particle size. At small particle size level, the voids and the demagnetization effect decrease significantly with increasing particle size and leads to the increase of magnetostriction; while at lager particle size level, the percentage of single-crystal particles and packing density becomes increasingly smaller with increasing particle size and results in the decrease of magnetostriction. The reason for the other scholars got different results is analyzed.

Use of randomised controlled trials for producing cost-effectiveness evidence: potential impact of design choices on sample size and study duration.

PubMed

Backhouse, Martin E

2002-01-01

A number of approaches to conducting economic evaluations could be adopted. However, some decision makers have a preference for wholly stochastic cost-effectiveness analyses, particularly if the sampled data are derived from randomised controlled trials (RCTs). Formal requirements for cost-effectiveness evidence have heightened concerns in the pharmaceutical industry that development costs and times might be increased if formal requirements increase the number, duration or costs of RCTs. Whether this proves to be the case or not will depend upon the timing, nature and extent of the cost-effectiveness evidence required. To illustrate how different requirements for wholly stochastic cost-effectiveness evidence could have a significant impact on two of the major determinants of new drug development costs and times, namely RCT sample size and study duration. Using data collected prospectively in a clinical evaluation, sample sizes were calculated for a number of hypothetical cost-effectiveness study design scenarios. The results were compared with a baseline clinical trial design. The sample sizes required for the cost-effectiveness study scenarios were mostly larger than those for the baseline clinical trial design. Circumstances can be such that a wholly stochastic cost-effectiveness analysis might not be a practical proposition even though its clinical counterpart is. In such situations, alternative research methodologies would be required. For wholly stochastic cost-effectiveness analyses, the importance of prior specification of the different components of study design is emphasised. However, it is doubtful whether all the information necessary for doing this will typically be available when product registration trials are being designed. Formal requirements for wholly stochastic cost-effectiveness evidence based on the standard frequentist paradigm have the potential to increase the size, duration and number of RCTs significantly and hence the costs and timelines associated with new product development. Moreover, it is possible to envisage situations where such an approach would be impossible to adopt. Clearly, further research is required into the issue of how to appraise the economic consequences of alternative economic evaluation research strategies.

Small studies may overestimate the effect sizes in critical care meta-analyses: a meta-epidemiological study

PubMed Central

2013-01-01

Introduction Small-study effects refer to the fact that trials with limited sample sizes are more likely to report larger beneficial effects than large trials. However, this has never been investigated in critical care medicine. Thus, the present study aimed to examine the presence and extent of small-study effects in critical care medicine. Methods Critical care meta-analyses involving randomized controlled trials and reported mortality as an outcome measure were considered eligible for the study. Component trials were classified as large (≥100 patients per arm) and small (<100 patients per arm) according to their sample sizes. Ratio of odds ratio (ROR) was calculated for each meta-analysis and then RORs were combined using a meta-analytic approach. ROR<1 indicated larger beneficial effect in small trials. Small and large trials were compared in methodological qualities including sequence generating, blinding, allocation concealment, intention to treat and sample size calculation. Results A total of 27 critical care meta-analyses involving 317 trials were included. Of them, five meta-analyses showed statistically significant RORs <1, and other meta-analyses did not reach a statistical significance. Overall, the pooled ROR was 0.60 (95% CI: 0.53 to 0.68); the heterogeneity was moderate with an I2 of 50.3% (chi-squared = 52.30; P = 0.002). Large trials showed significantly better reporting quality than small trials in terms of sequence generating, allocation concealment, blinding, intention to treat, sample size calculation and incomplete follow-up data. Conclusions Small trials are more likely to report larger beneficial effects than large trials in critical care medicine, which could be partly explained by the lower methodological quality in small trials. Caution should be practiced in the interpretation of meta-analyses involving small trials. PMID:23302257

Synthesis and characterization of nanocrystalline mesoporous zirconia using supercritical drying.

PubMed

Tyagi, Beena; Sidhpuria, Kalpesh; Shaik, Basha; Jasra, Raksh Vir

2006-06-01

Synthesis of nano-crystalline zirconia aerogel was done by sol-gel technique and supercritical drying using n-propanol solvent at and above supercritical temperature (235-280 degrees C) and pressure (48-52 bar) of n-propanol. Zirconia xerogel samples have also been prepared by conventional thermal drying method to compare with the super critically dried samples. Crystalline phase, crystallite size, surface area, pore volume, and pore size distribution were determined for all the samples in detail to understand the effect of gel drying methods on these properties. Supercritical drying of zirconia gel was observed to give thermally stable, nano-crystalline, tetragonal zirconia aerogels having high specific surface area and porosity with narrow and uniform pore size distribution as compared to thermally dried zirconia. With supercritical drying, zirconia samples show the formation of only mesopores whereas in thermally dried samples, substantial amount of micropores are observed along with mesopores. The samples prepared using supercritical drying yield nano-crystalline zirconia with smaller crystallite size (4-6 nm) as compared to higher crystallite size (13-20 nm) observed with thermally dried zirconia.

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

PubMed

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.

Stoichiometry of Cd(S,Se) nanocrystals by anomalous small-angle x-ray scattering

NASA Astrophysics Data System (ADS)

Ramos, Aline; Lyon, Olivier; Levelut, Claire

1995-12-01

In Cd(S,Se)-doped glasses the optical properties are strongly dependent on the size of the nanocrystals, but can be also largely modified by changes in the crystal stoichiometry; however, the information on both stoichiometry and size is difficult to obtain in crystals smaller than 10 nm. The intensity scattered at small angles is classically used to get information about nanoparticles sizes. Moreover the variation of amplitude of this intensity with the energy of the x ray—``the anomalous effect''—near the selenium edge is related to stoichiometry. Anomalous small-angle x-ray scattering has been used as a tentative method to get information about stoichiometry in nanocrystals with size lower than 10 nm. Experiments have been performed on samples treated for 2 days at temperatures in the range 540-650 °C. The samples treated at temperatures above 580 °C contain crystals with size larger than 4 nm. For all these samples the anomalous effect has nearly the same amplitude, and we found the stoichiometry x=0.4 for the CdSxSe1-x nanocrystals. This agrees with the previous results obtained by scanning electron microscopy and Raman spectroscopy. The results are also confirmed by measurements of the position of the optical absorption edge and by wide-angle x-ray scattering experiments. For the sample treated at 560 °C, the nanocrystal size is 3 nm and the stoichiometry x=0.6 is deduced from the anomalous effect. For samples treated at lower temperatures the anomalous effect is not observable, indicating an even lower selenium content in the nanocrystals (x≳0.7). We observed differences in the Se content of nanocrystals for different heat treatments of the same initial glass. These results may be very helpful to interpret the change in the optical properties when the temperature of the treatments decreases in the range 560-590 °C. In this temperature range, compositional effects seem to be of the same order of magnitude as the effects of the quantum confinement.

[Ultra-Fine Pressed Powder Pellet Sample Preparation XRF Determination of Multi-Elements and Carbon Dioxide in Carbonate].

PubMed

Li, Xiao-li; An, Shu-qing; Xu, Tie-min; Liu, Yi-bo; Zhang, Li-juan; Zeng, Jiang-ping; Wang, Na

2015-06-01

The main analysis error of pressed powder pellet of carbonate comes from particle-size effect and mineral effect. So in the article in order to eliminate the particle-size effect, the ultrafine pressed powder pellet sample preparation is used to the determination of multi-elements and carbon-dioxide in carbonate. To prepare the ultrafine powder the FRITSCH planetary Micro Mill machine and tungsten carbide media is utilized. To conquer the conglomeration during the process of grinding, the wet grinding is preferred. The surface morphology of the pellet is more smooth and neat, the Compton scatter effect is reduced with the decrease in particle size. The intensity of the spectral line is varied with the change of the particle size, generally the intensity of the spectral line is increased with the decrease in the particle size. But when the particle size of more than one component of the material is decreased, the intensity of the spectral line may increase for S, Si, Mg, or decrease for Ca, Al, Ti, K, which depend on the respective mass absorption coefficient . The change of the composition of the phase with milling is also researched. The incident depth of respective element is given from theoretical calculation. When the sample is grounded to the particle size of less than the penetration depth of all the analyte, the effect of the particle size on the intensity of the spectral line is much reduced. In the experiment, when grounded the sample to less than 8 μm(d95), the particle-size effect is much eliminated, with the correction method of theoretical α coefficient and the empirical coefficient, 14 major, minor and trace element in the carbonate can be determined accurately. And the precision of the method is much improved with RSD < 2%, except Na2O. Carbon is ultra-light element, the fluorescence yield is low and the interference is serious. With the manual multi-layer crystal PX4, coarse collimator, empirical correction, X-ray spectrometer can be used to determine the carbon dioxide in the carbonate quantitatively. The intensity of the carbon is increase with the times of the measurement and the time delay even the pellet is stored in the dessicator. So employing the latest pressed powder pellet is suggested.

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

ERIC Educational Resources Information Center

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.…

An Investigation of Sample Size Splitting on ATFIND and DIMTEST

ERIC Educational Resources Information Center

Socha, Alan; DeMars, Christine E.

2013-01-01

Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…

Power and Precision in Confirmatory Factor Analytic Tests of Measurement Invariance

ERIC Educational Resources Information Center

Meade, Adam W.; Bauer, Daniel J.

2007-01-01

This study investigates the effects of sample size, factor overdetermination, and communality on the precision of factor loading estimates and the power of the likelihood ratio test of factorial invariance in multigroup confirmatory factor analysis. Although sample sizes are typically thought to be the primary determinant of precision and power,…

Multi-passes warm rolling of AZ31 magnesium alloy, effect on evaluation of texture, microstructure, grain size and hardness

NASA Astrophysics Data System (ADS)

Kamran, J.; Hasan, B. A.; Tariq, N. H.; Izhar, S.; Sarwar, M.

2014-06-01

In this study the effect of multi-passes warm rolling of AZ31 magnesium alloy on texture, microstructure, grain size variation and hardness of as cast sample (A) and two rolled samples (B & C) taken from different locations of the as-cast ingot was investigated. The purpose was to enhance the formability of AZ31 alloy in order to help manufacturability. It was observed that multi-passes warm rolling (250°C to 350°C) of samples B & C with initial thickness 7.76mm and 7.73 mm was successfully achieved up to 85% reduction without any edge or surface cracks in ten steps with a total of 26 passes. The step numbers 1 to 4 consist of 5, 2, 11 and 3 passes respectively, the remaining steps 5 to 10 were single pass rolls. In each discrete step a fixed roll gap is used in a way that true strain per step increases very slowly from 0.0067 in the first step to 0.7118 in the 26th step. Both samples B & C showed very similar behavior after 26th pass and were successfully rolled up to 85% thickness reduction. However, during 10th step (27th pass) with a true strain value of 0.772 the sample B experienced very severe surface as well as edge cracks. Sample C was therefore not rolled for the 10th step and retained after 26 passes. Both samples were studied in terms of their basal texture, microstructure, grain size and hardness. Sample C showed an equiaxed grain structure after 85% total reduction. The equiaxed grain structure of sample C may be due to the effective involvement of dynamic recrystallization (DRX) which led to formation of these grains with relatively low misorientations with respect to the parent as cast grains. The sample B on the other hand showed a microstructure in which all the grains were elongated along the rolling direction (RD) after 90 % total reduction and DRX could not effectively play its role due to heavy strain and lack of plastic deformation systems. The microstructure of as cast sample showed a near-random texture (mrd 4.3), with average grain size of 44 & micro-hardness of 52 Hv. The grain size of sample B and C was 14μm and 27μm respectively and mrd intensity of basal texture was 5.34 and 5.46 respectively. The hardness of sample B and C came out to be 91 and 66 Hv respectively due to reduction in grain size and followed the well known Hall-Petch relationship.

Size effect on atomic structure in low-dimensional Cu-Zr amorphous systems.

PubMed

Zhang, W B; Liu, J; Lu, S H; Zhang, H; Wang, H; Wang, X D; Cao, Q P; Zhang, D X; Jiang, J Z

2017-08-04

The size effect on atomic structure of a Cu 64 Zr 36 amorphous system, including zero-dimensional small-size amorphous particles (SSAPs) and two-dimensional small-size amorphous films (SSAFs) together with bulk sample was investigated by molecular dynamics simulations. We revealed that sample size strongly affects local atomic structure in both Cu 64 Zr 36 SSAPs and SSAFs, which are composed of core and shell (surface) components. Compared with core component, the shell component of SSAPs has lower average coordination number and average bond length, higher degree of ordering, and lower packing density due to the segregation of Cu atoms on the shell of Cu 64 Zr 36 SSAPs. These atomic structure differences in SSAPs with various sizes result in different glass transition temperatures, in which the glass transition temperature for the shell component is found to be 577 K, which is much lower than 910 K for the core component. We further extended the size effect on the structure and glasses transition temperature to Cu 64 Zr 36 SSAFs, and revealed that the T g decreases when SSAFs becomes thinner due to the following factors: different dynamic motion (mean square displacement), different density of core and surface and Cu segregation on the surface of SSAFs. The obtained results here are different from the results for the size effect on atomic structure of nanometer-sized crystalline metallic alloys.

Effect of Sampling Plans on the Risk of Escherichia coli O157 Illness.

PubMed

Kiermeier, Andreas; Sumner, John; Jenson, Ian

2015-07-01

Australia exports about 150,000 to 200,000 tons of manufacturing beef to the United States annually. Each lot is tested for Escherichia coli O157 using the N-60 sampling protocol, where 60 small pieces of surface meat from each lot of production are tested. A risk assessment of E. coli O157 illness from the consumption of hamburgers made from Australian manufacturing meat formed the basis to evaluate the effect of sample size and amount on the number of illnesses predicted. The sampling plans evaluated included no sampling (resulting in an estimated 55.2 illnesses per annum), the current N-60 plan (50.2 illnesses), N-90 (49.6 illnesses), N-120 (48.4 illnesses), and a more stringent N-60 sampling plan taking five 25-g samples from each of 12 cartons (47.4 illnesses per annum). While sampling may detect some highly contaminated lots, it does not guarantee that all such lots are removed from commerce. It is concluded that increasing the sample size or sample amount from the current N-60 plan would have a very small public health effect.

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

PubMed

Mütze, Tobias; Friede, Tim

2017-10-15

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

The effects of sample size on population genomic analyses--implications for the tests of neutrality.

PubMed

Subramanian, Sankar

2016-02-20

One of the fundamental measures of molecular genetic variation is the Watterson's estimator (θ), which is based on the number of segregating sites. The estimation of θ is unbiased only under neutrality and constant population growth. It is well known that the estimation of θ is biased when these assumptions are violated. However, the effects of sample size in modulating the bias was not well appreciated. We examined this issue in detail based on large-scale exome data and robust simulations. Our investigation revealed that sample size appreciably influences θ estimation and this effect was much higher for constrained genomic regions than that of neutral regions. For instance, θ estimated for synonymous sites using 512 human exomes was 1.9 times higher than that obtained using 16 exomes. However, this difference was 2.5 times for the nonsynonymous sites of the same data. We observed a positive correlation between the rate of increase in θ estimates (with respect to the sample size) and the magnitude of selection pressure. For example, θ estimated for the nonsynonymous sites of highly constrained genes (dN/dS < 0.1) using 512 exomes was 3.6 times higher than that estimated using 16 exomes. In contrast this difference was only 2 times for the less constrained genes (dN/dS > 0.9). The results of this study reveal the extent of underestimation owing to small sample sizes and thus emphasize the importance of sample size in estimating a number of population genomic parameters. Our results have serious implications for neutrality tests such as Tajima D, Fu-Li D and those based on the McDonald and Kreitman test: Neutrality Index and the fraction of adaptive substitutions. For instance, use of 16 exomes produced 2.4 times higher proportion of adaptive substitutions compared to that obtained using 512 exomes (24% vs 10 %).

Interventions to Improve Medication Adherence in Hypertensive Patients: Systematic Review and Meta-analysis.

PubMed

Conn, Vicki S; Ruppar, Todd M; Chase, Jo-Ana D; Enriquez, Maithe; Cooper, Pamela S

2015-12-01

This systematic review applied meta-analytic procedures to synthesize medication adherence interventions that focus on adults with hypertension. Comprehensive searching located trials with medication adherence behavior outcomes. Study sample, design, intervention characteristics, and outcomes were coded. Random-effects models were used in calculating standardized mean difference effect sizes. Moderator analyses were conducted using meta-analytic analogues of ANOVA and regression to explore associations between effect sizes and sample, design, and intervention characteristics. Effect sizes were calculated for 112 eligible treatment-vs.-control group outcome comparisons of 34,272 subjects. The overall standardized mean difference effect size between treatment and control subjects was 0.300. Exploratory moderator analyses revealed interventions were most effective among female, older, and moderate- or high-income participants. The most promising intervention components were those linking adherence behavior with habits, giving adherence feedback to patients, self-monitoring of blood pressure, using pill boxes and other special packaging, and motivational interviewing. The most effective interventions employed multiple components and were delivered over many days. Future research should strive for minimizing risks of bias common in this literature, especially avoiding self-report adherence measures.

Mesh-size effects on drift sample composition as determined with a triple net sampler

USGS Publications Warehouse

Slack, K.V.; Tilley, L.J.; Kennelly, S.S.

1991-01-01

Nested nets of three different mesh apertures were used to study mesh-size effects on drift collected in a small mountain stream. The innermost, middle, and outermost nets had, respectively, 425 ??m, 209 ??m and 106 ??m openings, a design that reduced clogging while partitioning collections into three size groups. The open area of mesh in each net, from largest to smallest mesh opening, was 3.7, 5.7 and 8.0 times the area of the net mouth. Volumes of filtered water were determined with a flowmeter. The results are expressed as (1) drift retained by each net, (2) drift that would have been collected by a single net of given mesh size, and (3) the percentage of total drift (the sum of the catches from all three nets) that passed through the 425 ??m and 209 ??m nets. During a two day period in August 1986, Chironomidae larvae were dominant numerically in all 209 ??m and 106 ??m samples and midday 425 ??m samples. Large drifters (Ephemerellidae) occurred only in 425 ??m or 209 ??m nets, but the general pattern was an increase in abundance and number of taxa with decreasing mesh size. Relatively more individuals occurred in the larger mesh nets at night than during the day. The two larger mesh sizes retained 70% of the total sediment/detritus in the drift collections, and this decreased the rate of clogging of the 106 ??m net. If an objective of a sampling program is to compare drift density or drift rate between areas or sampling dates, the same mesh size should be used for all sample collection and processing. The mesh aperture used for drift collection should retain all species and life stages of significance in a study. The nested net design enables an investigator to test the adequacy of drift samples. ?? 1991 Kluwer Academic Publishers.

Effect of finite sample size on feature selection and classification: a simulation study.

PubMed

Way, Ted W; Sahiner, Berkman; Hadjiiski, Lubomir M; Chan, Heang-Ping

2010-02-01

The small number of samples available for training and testing is often the limiting factor in finding the most effective features and designing an optimal computer-aided diagnosis (CAD) system. Training on a limited set of samples introduces bias and variance in the performance of a CAD system relative to that trained with an infinite sample size. In this work, the authors conducted a simulation study to evaluate the performances of various combinations of classifiers and feature selection techniques and their dependence on the class distribution, dimensionality, and the training sample size. The understanding of these relationships will facilitate development of effective CAD systems under the constraint of limited available samples. Three feature selection techniques, the stepwise feature selection (SFS), sequential floating forward search (SFFS), and principal component analysis (PCA), and two commonly used classifiers, Fisher's linear discriminant analysis (LDA) and support vector machine (SVM), were investigated. Samples were drawn from multidimensional feature spaces of multivariate Gaussian distributions with equal or unequal covariance matrices and unequal means, and with equal covariance matrices and unequal means estimated from a clinical data set. Classifier performance was quantified by the area under the receiver operating characteristic curve Az. The mean Az values obtained by resubstitution and hold-out methods were evaluated for training sample sizes ranging from 15 to 100 per class. The number of simulated features available for selection was chosen to be 50, 100, and 200. It was found that the relative performance of the different combinations of classifier and feature selection method depends on the feature space distributions, the dimensionality, and the available training sample sizes. The LDA and SVM with radial kernel performed similarly for most of the conditions evaluated in this study, although the SVM classifier showed a slightly higher hold-out performance than LDA for some conditions and vice versa for other conditions. PCA was comparable to or better than SFS and SFFS for LDA at small samples sizes, but inferior for SVM with polynomial kernel. For the class distributions simulated from clinical data, PCA did not show advantages over the other two feature selection methods. Under this condition, the SVM with radial kernel performed better than the LDA when few training samples were available, while LDA performed better when a large number of training samples were available. None of the investigated feature selection-classifier combinations provided consistently superior performance under the studied conditions for different sample sizes and feature space distributions. In general, the SFFS method was comparable to the SFS method while PCA may have an advantage for Gaussian feature spaces with unequal covariance matrices. The performance of the SVM with radial kernel was better than, or comparable to, that of the SVM with polynomial kernel under most conditions studied.

Researchers’ Intuitions About Power in Psychological Research

PubMed Central

Bakker, Marjan; Hartgerink, Chris H. J.; Wicherts, Jelte M.; van der Maas, Han L. J.

2016-01-01

Many psychology studies are statistically underpowered. In part, this may be because many researchers rely on intuition, rules of thumb, and prior practice (along with practical considerations) to determine the number of subjects to test. In Study 1, we surveyed 291 published research psychologists and found large discrepancies between their reports of their preferred amount of power and the actual power of their studies (calculated from their reported typical cell size, typical effect size, and acceptable alpha). Furthermore, in Study 2, 89% of the 214 respondents overestimated the power of specific research designs with a small expected effect size, and 95% underestimated the sample size needed to obtain .80 power for detecting a small effect. Neither researchers’ experience nor their knowledge predicted the bias in their self-reported power intuitions. Because many respondents reported that they based their sample sizes on rules of thumb or common practice in the field, we recommend that researchers conduct and report formal power analyses for their studies. PMID:27354203

Researchers' Intuitions About Power in Psychological Research.

PubMed

Bakker, Marjan; Hartgerink, Chris H J; Wicherts, Jelte M; van der Maas, Han L J

2016-08-01

Many psychology studies are statistically underpowered. In part, this may be because many researchers rely on intuition, rules of thumb, and prior practice (along with practical considerations) to determine the number of subjects to test. In Study 1, we surveyed 291 published research psychologists and found large discrepancies between their reports of their preferred amount of power and the actual power of their studies (calculated from their reported typical cell size, typical effect size, and acceptable alpha). Furthermore, in Study 2, 89% of the 214 respondents overestimated the power of specific research designs with a small expected effect size, and 95% underestimated the sample size needed to obtain .80 power for detecting a small effect. Neither researchers' experience nor their knowledge predicted the bias in their self-reported power intuitions. Because many respondents reported that they based their sample sizes on rules of thumb or common practice in the field, we recommend that researchers conduct and report formal power analyses for their studies. © The Author(s) 2016.

Evaluation of Confluence Model Variables on IQ and Achievement Test Scores in a Sample of 6- to 11-Year-Old Children.

ERIC Educational Resources Information Center

Svanum, Soren; Bringle, Robert G.

1980-01-01

The confluence model of cognitive development was tested on 7,060 children. Family size, sibling order within family sizes, and hypothesized age-dependent effects were tested. Findings indicated an inverse relationship between family size and the cognitive measures; age-dependent effects and other confluence variables were found to be…

Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

USDA-ARS?s Scientific Manuscript database

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...

Analysis of YBCO high temperature superconductor doped with silver nanoparticles and carbon nanotubes using Williamson-Hall and size-strain plot

NASA Astrophysics Data System (ADS)

Dadras, Sedigheh; Davoudiniya, Masoumeh

2018-05-01

This paper sets out to investigate and compare the effects of Ag nanoparticles and carbon nanotubes (CNTs) doping on the mechanical properties of Y1Ba2Cu3O7-δ (YBCO) high temperature superconductor. For this purpose, the pure and doped YBCO samples were synthesized by sol-gel method. The microstructural analysis of the samples is performed using X-ray diffraction (XRD). The crystalline size, lattice strain and stress of the pure and doped YBCO samples were estimated by modified forms of Williamson-Hall analysis (W-H), namely, uniform deformation model (UDM), uniform deformation stress model (UDSM) and the size-strain plot method (SSP). These results show that the crystalline size, lattice strain and stress of the YBCO samples declined by Ag nanoparticles and CNTs doping.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, E. B.; Cai, J.; Benson, D. J.; Nesterenko, V. F.

2007-12-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed composites of polytetrafluoroethylene (PTFE), tungsten (W) and aluminum (Al) powders show significant differences depending on the size of metallic particles. The addition of W increases the density and changes the overall strength of the sample depending on the size of W particles. To investigate relatively large deformations, multi-material Eulerian and arbitrary Lagrangian-Eulerian methods, which have the ability to efficiently handle the formation of free surfaces, were used. The calculations indicate that the increased sample strength with fine metallic particles is due to the dynamic formation of force chains. This phenomenon occurs for samples with a higher porosity of the PTFE matrix compared to samples with larger particle size of W and a higher density PTFE matrix.

The impact of hypnotic suggestibility in clinical care settings.

PubMed

Montgomery, Guy H; Schnur, Julie B; David, Daniel

2011-07-01

Hypnotic suggestibility has been described as a powerful predictor of outcomes associated with hypnotic interventions. However, there have been no systematic approaches to quantifying this effect across the literature. This meta-analysis evaluates the magnitude of the effect of hypnotic suggestibility on hypnotic outcomes in clinical settings. PsycINFO and PubMed were searched from their inception through July 2009. Thirty-four effects from 10 studies and 283 participants are reported. Results revealed a statistically significant overall effect size in the small to medium range (r = .24; 95% Confidence Interval = -0.28 to 0.75), indicating that greater hypnotic suggestibility led to greater effects of hypnosis interventions. Hypnotic suggestibility accounted for 6% of the variance in outcomes. Smaller sample size studies, use of the SHCS, and pediatric samples tended to result in larger effect sizes. The authors question the usefulness of assessing hypnotic suggestibility in clinical contexts.

The impact of hypnotic suggestibility in clinical care settings

PubMed Central

Montgomery, Guy H.; Schnur, Julie B.; David, Daniel

2013-01-01

Hypnotic suggestibility has been described as a powerful predictor of outcomes associated with hypnotic interventions. However, there have been no systematic approaches to quantifying this effect across the literature. The present meta-analysis evaluates the magnitude of the effect of hypnotic suggestibility on hypnotic outcomes in clinical settings. PsycINFO and PubMed were searched from their inception through July 2009. Thirty-four effects from ten studies and 283 participants are reported. Results revealed a statistically significant overall effect size in the small to medium range (r = 0.24; 95% Confidence Interval = −0.28 to 0.75), indicating that greater hypnotic suggestibility led to greater effects of hypnosis interventions. Hypnotic suggestibility accounted for 6% of the variance in outcomes. Smaller sample size studies, use of the SHCS, and pediatric samples tended to result in larger effect sizes. Results question the usefulness of assessing hypnotic suggestibility in clinical contexts. PMID:21644122

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

PubMed Central

2013-01-01

Background 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. Results 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. Conclusions 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. PMID:24160725

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

PubMed

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.

Samples in applied psychology: over a decade of research in review.

PubMed

Shen, Winny; Kiger, Thomas B; Davies, Stacy E; Rasch, Rena L; Simon, Kara M; Ones, Deniz S

2011-09-01

This study examines sample characteristics of articles published in Journal of Applied Psychology (JAP) from 1995 to 2008. At the individual level, the overall median sample size over the period examined was approximately 173, which is generally adequate for detecting the average magnitude of effects of primary interest to researchers who publish in JAP. Samples using higher units of analyses (e.g., teams, departments/work units, and organizations) had lower median sample sizes (Mdn ≈ 65), yet were arguably robust given typical multilevel design choices of JAP authors despite the practical constraints of collecting data at higher units of analysis. A substantial proportion of studies used student samples (~40%); surprisingly, median sample sizes for student samples were smaller than working adult samples. Samples were more commonly occupationally homogeneous (~70%) than occupationally heterogeneous. U.S. and English-speaking participants made up the vast majority of samples, whereas Middle Eastern, African, and Latin American samples were largely unrepresented. On the basis of study results, recommendations are provided for authors, editors, and readers, which converge on 3 themes: (a) appropriateness and match between sample characteristics and research questions, (b) careful consideration of statistical power, and (c) the increased popularity of quantitative synthesis. Implications are discussed in terms of theory building, generalizability of research findings, and statistical power to detect effects. PsycINFO Database Record (c) 2011 APA, all rights reserved

Discrete element method (DEM) simulations of stratified sampling during solid dosage form manufacturing.

PubMed

Hancock, Bruno C; Ketterhagen, William R

2011-10-14

Discrete element model (DEM) simulations of the discharge of powders from hoppers under gravity were analyzed to provide estimates of dosage form content uniformity during the manufacture of solid dosage forms (tablets and capsules). For a system that exhibits moderate segregation the effects of sample size, number, and location within the batch were determined. The various sampling approaches were compared to current best-practices for sampling described in the Product Quality Research Institute (PQRI) Blend Uniformity Working Group (BUWG) guidelines. Sampling uniformly across the discharge process gave the most accurate results with respect to identifying segregation trends. Sigmoidal sampling (as recommended in the PQRI BUWG guidelines) tended to overestimate potential segregation issues, whereas truncated sampling (common in industrial practice) tended to underestimate them. The size of the sample had a major effect on the absolute potency RSD. The number of sampling locations (10 vs. 20) had very little effect on the trends in the data, and the number of samples analyzed at each location (1 vs. 3 vs. 7) had only a small effect for the sampling conditions examined. The results of this work provide greater understanding of the effect of different sampling approaches on the measured content uniformity of real dosage forms, and can help to guide the choice of appropriate sampling protocols. Copyright © 2011 Elsevier B.V. All rights reserved.

Rectification of depth measurement using pulsed thermography with logarithmic peak second derivative method

NASA Astrophysics Data System (ADS)

Li, Xiaoli; Zeng, Zhi; Shen, Jingling; Zhang, Cunlin; Zhao, Yuejin

2018-03-01

Logarithmic peak second derivative (LPSD) method is the most popular method for depth prediction in pulsed thermography. It is widely accepted that this method is independent of defect size. The theoretical model for LPSD method is based on the one-dimensional solution of heat conduction without considering the effect of defect size. When a decay term considering defect aspect ratio is introduced into the solution to correct the three-dimensional thermal diffusion effect, we found that LPSD method is affected by defect size by analytical model. Furthermore, we constructed the relation between the characteristic time of LPSD method and defect aspect ratio, which was verified with the experimental results of stainless steel and glass fiber reinforced plate (GFRP) samples. We also proposed an improved LPSD method for depth prediction when the effect of defect size was considered, and the rectification results of stainless steel and GFRP samples were presented and discussed.

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

NASA Astrophysics Data System (ADS)

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 type and loss functions used.

Effect of Study Design on Sample Size in Studies Intended to Evaluate Bioequivalence of Inhaled Short-Acting β-Agonist Formulations.

PubMed

Zeng, Yaohui; Singh, Sachinkumar; Wang, Kai; Ahrens, Richard C

2018-04-01

Pharmacodynamic studies that use methacholine challenge to assess bioequivalence of generic and innovator albuterol formulations are generally designed per published Food and Drug Administration guidance, with 3 reference doses and 1 test dose (3-by-1 design). These studies are challenging and expensive to conduct, typically requiring large sample sizes. We proposed 14 modified study designs as alternatives to the Food and Drug Administration-recommended 3-by-1 design, hypothesizing that adding reference and/or test doses would reduce sample size and cost. We used Monte Carlo simulation to estimate sample size. Simulation inputs were selected based on published studies and our own experience with this type of trial. We also estimated effects of these modified study designs on study cost. Most of these altered designs reduced sample size and cost relative to the 3-by-1 design, some decreasing cost by more than 40%. The most effective single study dose to add was 180 μg of test formulation, which resulted in an estimated 30% relative cost reduction. Adding a single test dose of 90 μg was less effective, producing only a 13% cost reduction. Adding a lone reference dose of either 180, 270, or 360 μg yielded little benefit (less than 10% cost reduction), whereas adding 720 μg resulted in a 19% cost reduction. Of the 14 study design modifications we evaluated, the most effective was addition of both a 90-μg test dose and a 720-μg reference dose (42% cost reduction). Combining a 180-μg test dose and a 720-μg reference dose produced an estimated 36% cost reduction. © 2017, The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.

Critical appraisal of arguments for the delayed-start design proposed as alternative to the parallel-group randomized clinical trial design in the field of rare disease.

PubMed

Spineli, Loukia M; Jenz, Eva; Großhennig, Anika; Koch, Armin

2017-08-17

A number of papers have proposed or evaluated the delayed-start design as an alternative to the standard two-arm parallel group randomized clinical trial (RCT) design in the field of rare disease. However the discussion is felt to lack a sufficient degree of consideration devoted to the true virtues of the delayed start design and the implications either in terms of required sample-size, overall information, or interpretation of the estimate in the context of small populations. To evaluate whether there are real advantages of the delayed-start design particularly in terms of overall efficacy and sample size requirements as a proposed alternative to the standard parallel group RCT in the field of rare disease. We used a real-life example to compare the delayed-start design with the standard RCT in terms of sample size requirements. Then, based on three scenarios regarding the development of the treatment effect over time, the advantages, limitations and potential costs of the delayed-start design are discussed. We clarify that delayed-start design is not suitable for drugs that establish an immediate treatment effect, but for drugs with effects developing over time, instead. In addition, the sample size will always increase as an implication for a reduced time on placebo resulting in a decreased treatment effect. A number of papers have repeated well-known arguments to justify the delayed-start design as appropriate alternative to the standard parallel group RCT in the field of rare disease and do not discuss the specific needs of research methodology in this field. The main point is that a limited time on placebo will result in an underestimated treatment effect and, in consequence, in larger sample size requirements compared to those expected under a standard parallel-group design. This also impacts on benefit-risk assessment.

Extraction of citral oil from lemongrass (Cymbopogon Citratus) by steam-water distillation technique

NASA Astrophysics Data System (ADS)

Alam, P. N.; Husin, H.; Asnawi, T. M.; Adisalamun

2018-04-01

In Indonesia, production of citral oil from lemon grass (Cymbopogon Cytratus) is done by a traditional technique whereby a low yield results. To improve the yield, an appropriate extraction technology is required. In this research, a steam-water distillation technique was applied to extract the essential oil from the lemongrass. The effects of sample particle size and bed volume on yield and quality of citral oil produced were investigated. The drying and refining time of 2 hours were used as fixed variables. This research results that minimum citral oil yield of 0.53% was obtained on sample particle size of 3 cm and bed volume of 80%, whereas the maximum yield of 1.95% on sample particle size of 15 cm and bed volume of 40%. The lowest specific gravity of 0.80 and the highest specific gravity of 0.905 were obtained on sample particle size of 8 cm with bed volume of 80% and particle size of 12 cm with bed volume of 70%, respectively. The lowest refractive index of 1.480 and the highest refractive index of 1.495 were obtained on sample particle size of 8 cm with bed volume of 70% and sample particle size of 15 cm with bed volume of 40%, respectively. The solubility of the produced citral oil in alcohol was 70% in ratio of 1:1, and the citral oil concentration obtained was around 79%.

Laboratory hydraulic calibration of the Helley-Smith bedload sediment sampler

USGS Publications Warehouse

Druffel, Leroy; Emmett, W.W.; Schneider, V.R.; Skinner, J.V.

1976-01-01

Filling the sample bag to 40 percent capacity with a sediment larger in diameter than the mesh size of the bag had no effect on the hydraulic efficiency. Particles close to the 0.2 mm mesh size of the sample bag plugged the openings and caused the efficiency to decrease in an undetermined manner.

Planning Community-Based Assessments of HIV Educational Intervention Programs in Sub-Saharan Africa

ERIC Educational Resources Information Center

Kelcey, Ben; Shen, Zuchao

2017-01-01

A key consideration in planning studies of community-based HIV education programs is identifying a sample size large enough to ensure a reasonable probability of detecting program effects if they exist. Sufficient sample sizes for community- or group-based designs are proportional to the correlation or similarity of individuals within communities.…

Bootstrapping Results of Exercise Therapy and Education for Patients with Congestive Heart Failure

ERIC Educational Resources Information Center

Witta, E. Lea; Brubaker, Craig

2003-01-01

When studies are conducted over a period of time, the sample size typically decreases. In a study of the effects of exercise therapy and education with recovering congestive heart failure (CHF) patients (Brubaker, Witta, & Angelopoulus, 2003), the sample size decreased from over 40 to 9 participants after an 18-month time span. Although the…

Laser Diffraction Techniques Replace Sieving for Lunar Soil Particle Size Distribution Data

NASA Technical Reports Server (NTRS)

Cooper, Bonnie L.; Gonzalez, C. P.; McKay, D. S.; Fruland, R. L.

2012-01-01

Sieving was used extensively until 1999 to determine the particle size distribution of lunar samples. This method is time-consuming, and requires more than a gram of material in order to obtain a result in which one may have confidence. This is demonstrated by the difference in geometric mean and median for samples measured by [1], in which a 14-gram sample produced a geometric mean of approx.52 micrometers, whereas two other samples of 1.5 grams resulted in gave means of approx.63 and approx.69 micrometers. Sample allocations for sieving are typically much smaller than a gram, and many of the sample allocations received by our lab are 0.5 to 0.25 grams in mass. Basu [2] has described how the finest fraction of the soil is easily lost in the sieving process, and this effect is compounded when sample sizes are small.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Sample Size Estimation for Alzheimer's Disease Trials from Japanese ADNI Serial Magnetic Resonance Imaging.

PubMed

Fujishima, Motonobu; Kawaguchi, Atsushi; Maikusa, Norihide; Kuwano, Ryozo; Iwatsubo, Takeshi; Matsuda, Hiroshi

2017-01-01

Little is known about the sample sizes required for clinical trials of Alzheimer's disease (AD)-modifying treatments using atrophy measures from serial brain magnetic resonance imaging (MRI) in the Japanese population. The primary objective of the present study was to estimate how large a sample size would be needed for future clinical trials for AD-modifying treatments in Japan using atrophy measures of the brain as a surrogate biomarker. Sample sizes were estimated from the rates of change of the whole brain and hippocampus by the k-means normalized boundary shift integral (KN-BSI) and cognitive measures using the data of 537 Japanese Alzheimer's Neuroimaging Initiative (J-ADNI) participants with a linear mixed-effects model. We also examined the potential use of ApoE status as a trial enrichment strategy. The hippocampal atrophy rate required smaller sample sizes than cognitive measures of AD and mild cognitive impairment (MCI). Inclusion of ApoE status reduced sample sizes for AD and MCI patients in the atrophy measures. These results show the potential use of longitudinal hippocampal atrophy measurement using automated image analysis as a progression biomarker and ApoE status as a trial enrichment strategy in a clinical trial of AD-modifying treatment in Japanese people.

Orphan therapies: making best use of postmarket data.

PubMed

Maro, Judith C; Brown, Jeffrey S; Dal Pan, Gerald J; Li, Lingling

2014-08-01

Postmarket surveillance of the comparative safety and efficacy of orphan therapeutics is challenging, particularly when multiple therapeutics are licensed for the same orphan indication. To make best use of product-specific registry data collected to fulfill regulatory requirements, we propose the creation of a distributed electronic health data network among registries. Such a network could support sequential statistical analyses designed to detect early warnings of excess risks. We use a simulated example to explore the circumstances under which a distributed network may prove advantageous. We perform sample size calculations for sequential and non-sequential statistical studies aimed at comparing the incidence of hepatotoxicity following initiation of two newly licensed therapies for homozygous familial hypercholesterolemia. We calculate the sample size savings ratio, or the proportion of sample size saved if one conducted a sequential study as compared to a non-sequential study. Then, using models to describe the adoption and utilization of these therapies, we simulate when these sample sizes are attainable in calendar years. We then calculate the analytic calendar time savings ratio, analogous to the sample size savings ratio. We repeat these analyses for numerous scenarios. Sequential analyses detect effect sizes earlier or at the same time as non-sequential analyses. The most substantial potential savings occur when the market share is more imbalanced (i.e., 90% for therapy A) and the effect size is closest to the null hypothesis. However, due to low exposure prevalence, these savings are difficult to realize within the 30-year time frame of this simulation for scenarios in which the outcome of interest occurs at or more frequently than one event/100 person-years. We illustrate a process to assess whether sequential statistical analyses of registry data performed via distributed networks may prove a worthwhile infrastructure investment for pharmacovigilance.

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

PubMed

Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

2016-07-01

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. © 2016 Institute of Food Technologists®

A size-dependent constitutive model of bulk metallic glasses in the supercooled liquid region

PubMed Central

Yao, Di; Deng, Lei; Zhang, Mao; Wang, Xinyun; Tang, Na; Li, Jianjun

2015-01-01

Size effect is of great importance in micro forming processes. In this paper, micro cylinder compression was conducted to investigate the deformation behavior of bulk metallic glasses (BMGs) in supercooled liquid region with different deformation variables including sample size, temperature and strain rate. It was found that the elastic and plastic behaviors of BMGs have a strong dependence on the sample size. The free volume and defect concentration were introduced to explain the size effect. In order to demonstrate the influence of deformation variables on steady stress, elastic modulus and overshoot phenomenon, four size-dependent factors were proposed to construct a size-dependent constitutive model based on the Maxwell-pulse type model previously presented by the authors according to viscosity theory and free volume model. The proposed constitutive model was then adopted in finite element method simulations, and validated by comparing the micro cylinder compression and micro double cup extrusion experimental data with the numerical results. Furthermore, the model provides a new approach to understanding the size-dependent plastic deformation behavior of BMGs. PMID:25626690

The N-Pact Factor: Evaluating the Quality of Empirical Journals with Respect to Sample Size and Statistical Power

PubMed Central

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

Addressing the "Replication Crisis": Using Original Studies to Design Replication Studies with Appropriate Statistical Power.

PubMed

Anderson, Samantha F; Maxwell, Scott E

2017-01-01

Psychology is undergoing a replication crisis. The discussion surrounding this crisis has centered on mistrust of previous findings. Researchers planning replication studies often use the original study sample effect size as the basis for sample size planning. However, this strategy ignores uncertainty and publication bias in estimated effect sizes, resulting in overly optimistic calculations. A psychologist who intends to obtain power of .80 in the replication study, and performs calculations accordingly, may have an actual power lower than .80. We performed simulations to reveal the magnitude of the difference between actual and intended power based on common sample size planning strategies and assessed the performance of methods that aim to correct for effect size uncertainty and/or bias. Our results imply that even if original studies reflect actual phenomena and were conducted in the absence of questionable research practices, popular approaches to designing replication studies may result in a low success rate, especially if the original study is underpowered. Methods correcting for bias and/or uncertainty generally had higher actual power, but were not a panacea for an underpowered original study. Thus, it becomes imperative that 1) original studies are adequately powered and 2) replication studies are designed with methods that are more likely to yield the intended level of power.

Overlap between treatment and control distributions as an effect size measure in experiments.

PubMed

Hedges, Larry V; Olkin, Ingram

2016-03-01

The proportion π of treatment group observations that exceed the control group mean has been proposed as an effect size measure for experiments that randomly assign independent units into 2 groups. We give the exact distribution of a simple estimator of π based on the standardized mean difference and use it to study the small sample bias of this estimator. We also give the minimum variance unbiased estimator of π under 2 models, one in which the variance of the mean difference is known and one in which the variance is unknown. We show how to use the relation between the standardized mean difference and the overlap measure to compute confidence intervals for π and show that these results can be used to obtain unbiased estimators, large sample variances, and confidence intervals for 3 related effect size measures based on the overlap. Finally, we show how the effect size π can be used in a meta-analysis. (c) 2016 APA, all rights reserved).

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

PubMed

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparing Single Case Design Overlap-Based Effect Size Metrics From Studies Examining Speech Generating Device Interventions

PubMed Central

Chen, Mo; Hyppa-Martin, Jolene K.; Reichle, Joe E.; Symons, Frank J.

2017-01-01

Meaningfully synthesizing single case experimental data from intervention studies comprised of individuals with low incidence conditions and generating effect size estimates remains challenging. Seven effect size metrics were compared for single case design (SCD) data focused on teaching speech generating device use to individuals with intellectual and developmental disabilities (IDD) with moderate to profound levels of impairment. The effect size metrics included percent of data points exceeding the median (PEM), percent of nonoverlapping data (PND), improvement rate difference (IRD), percent of all nonoverlapping data (PAND), Phi, nonoverlap of all pairs (NAP), and Taunovlap. Results showed that among the seven effect size metrics, PAND, Phi, IRD, and PND were more effective in quantifying intervention effects for the data sample (N = 285 phase or condition contrasts). Results are discussed with respect to issues concerning extracting and calculating effect sizes, visual analysis, and SCD intervention research in IDD. PMID:27119210

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

PubMed

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.

The Relationship between National-Level Carbon Dioxide Emissions and Population Size: An Assessment of Regional and Temporal Variation, 1960–2005

PubMed Central

Jorgenson, Andrew K.; Clark, Brett

2013-01-01

This study examines the regional and temporal differences in the statistical relationship between national-level carbon dioxide emissions and national-level population size. The authors analyze panel data from 1960 to 2005 for a diverse sample of nations, and employ descriptive statistics and rigorous panel regression modeling techniques. Initial descriptive analyses indicate that all regions experienced overall increases in carbon emissions and population size during the 45-year period of investigation, but with notable differences. For carbon emissions, the sample of countries in Asia experienced the largest percent increase, followed by countries in Latin America, Africa, and lastly the sample of relatively affluent countries in Europe, North America, and Oceania combined. For population size, the sample of countries in Africa experienced the largest percent increase, followed countries in Latin America, Asia, and the combined sample of countries in Europe, North America, and Oceania. Findings for two-way fixed effects panel regression elasticity models of national-level carbon emissions indicate that the estimated elasticity coefficient for population size is much smaller for nations in Africa than for nations in other regions of the world. Regarding potential temporal changes, from 1960 to 2005 the estimated elasticity coefficient for population size decreased by 25% for the sample of Africa countries, 14% for the sample of Asia countries, 6.5% for the sample of Latin America countries, but remained the same in size for the sample of countries in Europe, North America, and Oceania. Overall, while population size continues to be the primary driver of total national-level anthropogenic carbon dioxide emissions, the findings for this study highlight the need for future research and policies to recognize that the actual impacts of population size on national-level carbon emissions differ across both time and region. PMID:23437323

Rock sampling. [method for controlling particle size distribution

NASA Technical Reports Server (NTRS)

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.

Effect of synthesis methods with different annealing temperatures on micro structure, cations distribution and magnetic properties of nano-nickel ferrite

NASA Astrophysics Data System (ADS)

El-Sayed, Karimat; Mohamed, Mohamed Bakr; Hamdy, Sh.; Ata-Allah, S. S.

2017-02-01

Nano-crystalline NiFe2O4 was synthesized by citrate and sol-gel methods at different annealing temperatures and the results were compared with a bulk sample prepared by ceramic method. The effect of methods of preparation and different annealing temperatures on the crystallize size, strain, bond lengths, bond angles, cations distribution and degree of inversions were investigated by X-ray powder diffraction, high resolution transmission electron microscope, Mössbauer effect spectrometer and vibrating sample magnetometer. The cations distributions were determined at both octahedral and tetrahedral sites using both Mössbauer effect spectroscopy and a modified Bertaut method using Rietveld method. The Mössbauer effect spectra showed a regular decrease in the hyperfine field with decreasing particle size. Saturation magnetization and coercivity are found to be affected by the particle size and the cations distribution.

Influence of calcium carbonate and charcoal application on aggregation processes and organic matter retention at the silt-size scale

NASA Astrophysics Data System (ADS)

Asefaw Berhe, Asmeret; Kaiser, Michael; Ghezzehei, Teamrat; Myrold, David; Kleber, Markus

2013-04-01

The effectiveness of charcoal and calcium carbonate applications to improve soil conditions has been well documented. However, their influence on the formation of silt-sized aggregates and the amount and protection of associated organic matter (OM) against microbial decomposition is still largely unknown. For sustainable management of agricultural soils, silt-sized aggregates (2-53 µm) are of particularly large importance because they store up to 60% of soil organic carbon with mean residence times between 70 and 400 years. The objectives are i) to analyze the ability of CaCO3 and/or charcoal application to increase the amount of silt-sized aggregates and associated OM, ii) vary soil mineral conditions to establish relevant boundary conditions for amendment-induced aggregation processes, iii) to determine how amendment-induced changes in formation of silt-sized aggregates relate to microbial decomposition of OM. We set up artificial high reactive (HR, clay: 40%, sand: 57%, OM: 3%) and low reactive soils (LR, clay: 10%, sand: 89%, OM: 1%) and mixed them with charcoal (CC, 1%) and/or calcium carbonate (Ca, 0.2%). The samples were adjusted to a water potential of 0.3 bar and sub samples were incubated with microbial inoculum (MO). After a 16-weeks aggregation experiment, size fractions were separated by wet-sieving and sedimentation. Since we did not use mineral compounds in the artificial mixtures within the size range of 2 to 53 µm, we consider material recovered in this fraction as silt-sized aggregates, which was confirmed by SEM analyses. For the LR mixtures, we detected increasing N concentrations within the 2-53 µm fractions of the charcoal amended samples (CC, CC+Ca, and CC+Ca+MO) as compared to the Control sample with the strongest effect for the CC+Ca+MO sample. This indicates an association of N-containing microbial derived OM with silt-sized aggregates. For the charcoal amended LR and HR mixtures, the C concentrations of the 2-53 µm fractions are larger than those of the respective fractions of the Control samples but the effect is several times stronger for the LR mixtures. The C concentrations of the 2-53 µm fractions relative to the total C amount of the LR and HR mixtures are between 30 and 50%. The charcoal amended samples show generally larger relative C amounts associated with the 2-53 µm fractions than the Control samples. Benefits for aggregate formation and OM storage were larger for sand (LR) than for clay soil (HR). The gained data are similar to respective data for natural soils. Consequently, the suggested microcosm experiments are suitable to analyze mechanisms within soil aggregation processes.

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-Means Cluster Analysis

ERIC Educational Resources Information Center

de Craen, Saskia; Commandeur, Jacques J. F.; Frank, Laurence E.; Heiser, Willem J.

2006-01-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these…

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

PubMed

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 from researchers and trialists can be quickly and easily collected by conducting a simple study using email recruitment and an online questionnaire. The results collected from the survey were successfully used in sample size calculations for a PhD research study protocol.

Methodological quality of behavioural weight loss studies: a systematic review

PubMed Central

Lemon, S. C.; Wang, M. L.; Haughton, C. F.; Estabrook, D. P.; Frisard, C. F.; Pagoto, S. L.

2018-01-01

Summary This systematic review assessed the methodological quality of behavioural weight loss intervention studies conducted among adults and associations between quality and statistically significant weight loss outcome, strength of intervention effectiveness and sample size. Searches for trials published between January, 2009 and December, 2014 were conducted using PUBMED, MEDLINE and PSYCINFO and identified ninety studies. Methodological quality indicators included study design, anthropometric measurement approach, sample size calculations, intent-to-treat (ITT) analysis, loss to follow-up rate, missing data strategy, sampling strategy, report of treatment receipt and report of intervention fidelity (mean = 6.3). Indicators most commonly utilized included randomized design (100%), objectively measured anthropometrics (96.7%), ITT analysis (86.7%) and reporting treatment adherence (76.7%). Most studies (62.2%) had a follow-up rate >75% and reported a loss to follow-up analytic strategy or minimal missing data (69.9%). Describing intervention fidelity (34.4%) and sampling from a known population (41.1%) were least common. Methodological quality was not associated with reporting a statistically significant result, effect size or sample size. This review found the published literature of behavioural weight loss trials to be of high quality for specific indicators, including study design and measurement. Identified for improvement include utilization of more rigorous statistical approaches to loss to follow up and better fidelity reporting. PMID:27071775

Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis.

PubMed

Amlung, M; Petker, T; Jackson, J; Balodis, I; MacKillop, J

2016-08-01

An increasing number of studies have investigated delay discounting (DD) in relation to obesity, but with mixed findings. This meta-analysis synthesized the literature on the relationship between monetary and food DD and obesity, with three objectives: (1) to characterize the relationship between DD and obesity in both case-control comparisons and continuous designs; (2) to examine potential moderators, including case-control v. continuous design, money v. food rewards, sample sex distribution, and sample age (18 years); and (3) to evaluate publication bias. From 134 candidate articles, 39 independent investigations yielded 29 case-control and 30 continuous comparisons (total n = 10 278). Random-effects meta-analysis was conducted using Cohen's d as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger tests, meta-regression of publication year and effect size, and imputation of missing studies. The primary analysis revealed a medium effect size across studies that was highly statistically significant (d = 0.43, p < 10-14). None of the moderators examined yielded statistically significant differences, although notably larger effect sizes were found for studies with case-control designs, food rewards and child/adolescent samples. Limited evidence of publication bias was present, although the Begg-Mazumdar test and meta-regression suggested a slightly diminishing effect size over time. Steep DD of food and money appears to be a robust feature of obesity that is relatively consistent across the DD assessment methodologies and study designs examined. These findings are discussed in the context of research on DD in drug addiction, the neural bases of DD in obesity, and potential clinical applications.

Effect of biomimetic non-smooth unit morphology on thermal fatigue behavior of H13 hot-work tool steel

NASA Astrophysics Data System (ADS)

Meng, Chao; Zhou, Hong; Cong, Dalong; Wang, Chuanwei; Zhang, Peng; Zhang, Zhihui; Ren, Luquan

2012-06-01

The thermal fatigue behavior of hot-work tool steel processed by a biomimetic coupled laser remelting process gets a remarkable improvement compared to untreated sample. The 'dowel pin effect', the 'dam effect' and the 'fence effect' of non-smooth units are the main reason of the conspicuous improvement of the thermal fatigue behavior. In order to get a further enhancement of the 'dowel pin effect', the 'dam effect' and the 'fence effect', this study investigated the effect of different unit morphologies (including 'prolate', 'U' and 'V' morphology) and the same unit morphology in different sizes on the thermal fatigue behavior of H13 hot-work tool steel. The results showed that the 'U' morphology unit had the optimum thermal fatigue behavior, then the 'V' morphology which was better than the 'prolate' morphology unit; when the unit morphology was identical, the thermal fatigue behavior of the sample with large unit sizes was better than that of the small sizes.

Optimal sample sizes for the design of reliability studies: power consideration.

PubMed

Shieh, Gwowen

2014-09-01

Intraclass correlation coefficients are used extensively to measure the reliability or degree of resemblance among group members in multilevel research. This study concerns the problem of the necessary sample size to ensure adequate statistical power for hypothesis tests concerning the intraclass correlation coefficient in the one-way random-effects model. In view of the incomplete and problematic numerical results in the literature, the approximate sample size formula constructed from Fisher's transformation is reevaluated and compared with an exact approach across a wide range of model configurations. These comprehensive examinations showed that the Fisher transformation method is appropriate only under limited circumstances, and therefore it is not recommended as a general method in practice. For advance design planning of reliability studies, the exact sample size procedures are fully described and illustrated for various allocation and cost schemes. Corresponding computer programs are also developed to implement the suggested algorithms.

The Effect of Brain Based Learning on Academic Achievement: A Meta-Analytical Study

ERIC Educational Resources Information Center

Gozuyesil, Eda; Dikici, Ayhan

2014-01-01

This study's aim is to measure the effect sizes of the quantitative studies that examined the effectiveness of brain-based learning on students' academic achievement and to examine with the meta-analytical method if there is a significant difference in effect in terms of the factors of education level, subject matter, sampling size, and the…

Effect of Co doping on structural and mechanical properties of CeO2

NASA Astrophysics Data System (ADS)

Tiwari, Saurabh; Balasubramanian, Nivedha; Biring, Sajal; Sen, Somaditya

2018-05-01

Sol-gel synthesized nanocrystalline Co doped CeO2 powders [(Ce1-xCoxO2; x=0, 0.03)] were made into cylindrical discs by uniaxial pressing and sintered at 1500°C for 24h to measure mechanical properties. The pure phase formation of undoped and Co doped samples were confirmed by X-ray diffraction and Raman analysis. The scanning electron microscopy (SEM) was used for observing the microstructure of sintered samples to investigate density, porosity, and grain size. The grains size observed for 1500°C sintered samples 5-8 µm. Vickers indentation method used for investigating the micro-hardness. For undoped CeO2 micro-hardness was found 6.2 GPa which decreased with Co doping. It was found that samples follow indentation size effect (ISE) and follow elastic than plastic deformation. Enhanced ductile nature with Co doping in CeO2 made it more promising material for optoelectronic device applications.

A Meta-Analysis on Antecedents and Outcomes of Detachment from Work.

PubMed

Wendsche, Johannes; Lohmann-Haislah, Andrea

2016-01-01

Detachment from work has been proposed as an important non-work experience helping employees to recover from work demands. This meta-analysis (86 publications, k = 91 independent study samples, N = 38,124 employees) examined core antecedents and outcomes of detachment in employee samples. With regard to outcomes, results indicated average positive correlations between detachment and self-reported mental (i.e., less exhaustion, higher life satisfaction, more well-being, better sleep) and physical (i.e., lower physical discomfort) health, state well-being (i.e., less fatigue, higher positive affect, more intensive state of recovery), and task performance (small to medium sized effects). However, average relationships between detachment and physiological stress indicators and work motivation were not significant while associations with contextual performance and creativity were significant, but negative. Concerning work characteristics, as expected, job demands were negatively related and job resources were positively related to detachment (small sized effects). Further, analyses revealed that person characteristics such as negative affectivity/neuroticism (small sized effect) and heavy work investment (medium sized effect) were negatively related to detachment whereas detachment and demographic variables (i.e., age and gender) were not related. Moreover, we found a medium sized average negative relationship between engagement in work-related activities during non-work time and detachment. For most of the examined relationships heterogeneity of effect sizes was moderate to high. We identified study design, samples' gender distribution, and affective valence of work-related thoughts as moderators for some of these aforementioned relationships. The results of this meta-analysis point to detachment as a non-work (recovery) experience that is influenced by work-related and personal characteristics which in turn is relevant for a range of employee outcomes.

A Meta-Analysis on Antecedents and Outcomes of Detachment from Work

PubMed Central

Wendsche, Johannes; Lohmann-Haislah, Andrea

2017-01-01

Detachment from work has been proposed as an important non-work experience helping employees to recover from work demands. This meta-analysis (86 publications, k = 91 independent study samples, N = 38,124 employees) examined core antecedents and outcomes of detachment in employee samples. With regard to outcomes, results indicated average positive correlations between detachment and self-reported mental (i.e., less exhaustion, higher life satisfaction, more well-being, better sleep) and physical (i.e., lower physical discomfort) health, state well-being (i.e., less fatigue, higher positive affect, more intensive state of recovery), and task performance (small to medium sized effects). However, average relationships between detachment and physiological stress indicators and work motivation were not significant while associations with contextual performance and creativity were significant, but negative. Concerning work characteristics, as expected, job demands were negatively related and job resources were positively related to detachment (small sized effects). Further, analyses revealed that person characteristics such as negative affectivity/neuroticism (small sized effect) and heavy work investment (medium sized effect) were negatively related to detachment whereas detachment and demographic variables (i.e., age and gender) were not related. Moreover, we found a medium sized average negative relationship between engagement in work-related activities during non-work time and detachment. For most of the examined relationships heterogeneity of effect sizes was moderate to high. We identified study design, samples' gender distribution, and affective valence of work-related thoughts as moderators for some of these aforementioned relationships. The results of this meta-analysis point to detachment as a non-work (recovery) experience that is influenced by work-related and personal characteristics which in turn is relevant for a range of employee outcomes. PMID:28133454

Comparative analyses of basal rate of metabolism in mammals: data selection does matter.

PubMed

Genoud, Michel; Isler, Karin; Martin, Robert D

2018-02-01

Basal rate of metabolism (BMR) is a physiological parameter that should be measured under strictly defined experimental conditions. In comparative analyses among mammals BMR is widely used as an index of the intensity of the metabolic machinery or as a proxy for energy expenditure. Many databases with BMR values for mammals are available, but the criteria used to select metabolic data as BMR estimates have often varied and the potential effect of this variability has rarely been questioned. We provide a new, expanded BMR database reflecting compliance with standard criteria (resting, postabsorptive state; thermal neutrality; adult, non-reproductive status for females) and examine potential effects of differential selectivity on the results of comparative analyses. The database includes 1739 different entries for 817 species of mammals, compiled from the original sources. It provides information permitting assessment of the validity of each estimate and presents the value closest to a proper BMR for each entry. Using different selection criteria, several alternative data sets were extracted and used in comparative analyses of (i) the scaling of BMR to body mass and (ii) the relationship between brain mass and BMR. It was expected that results would be especially dependent on selection criteria with small sample sizes and with relatively weak relationships. Phylogenetically informed regression (phylogenetic generalized least squares, PGLS) was applied to the alternative data sets for several different clades (Mammalia, Eutheria, Metatheria, or individual orders). For Mammalia, a 'subsampling procedure' was also applied, in which random subsamples of different sample sizes were taken from each original data set and successively analysed. In each case, two data sets with identical sample size and species, but comprising BMR data with different degrees of reliability, were compared. Selection criteria had minor effects on scaling equations computed for large clades (Mammalia, Eutheria, Metatheria), although less-reliable estimates of BMR were generally about 12-20% larger than more-reliable ones. Larger effects were found with more-limited clades, such as sciuromorph rodents. For the relationship between BMR and brain mass the results of comparative analyses were found to depend strongly on the data set used, especially with more-limited, order-level clades. In fact, with small sample sizes (e.g. <100) results often appeared erratic. Subsampling revealed that sample size has a non-linear effect on the probability of a zero slope for a given relationship. Depending on the species included, results could differ dramatically, especially with small sample sizes. Overall, our findings indicate a need for due diligence when selecting BMR estimates and caution regarding results (even if seemingly significant) with small sample sizes. © 2017 Cambridge Philosophical Society.

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

Treesearch

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...

Chance-corrected classification for use in discriminant analysis: Ecological applications

USGS Publications Warehouse

Titus, K.; Mosher, J.A.; Williams, B.K.

1984-01-01

A method for evaluating the classification table from a discriminant analysis is described. The statistic, kappa, is useful to ecologists in that it removes the effects of chance. It is useful even with equal group sample sizes although the need for a chance-corrected measure of prediction becomes greater with more dissimilar group sample sizes. Examples are presented.

Sample Size Bias in Judgments of Perceptual Averages

ERIC Educational Resources Information Center

Price, Paul C.; Kimura, Nicole M.; Smith, Andrew R.; Marshall, Lindsay D.

2014-01-01

Previous research has shown that people exhibit a sample size bias when judging the average of a set of stimuli on a single dimension. The more stimuli there are in the set, the greater people judge the average to be. This effect has been demonstrated reliably for judgments of the average likelihood that groups of people will experience negative,…

Oil-water separation property of polymer-contained wastewater from polymer-flooding oilfields in Bohai Bay, China.

PubMed

Chen, Hua-xing; Tang, Hong-ming; Duan, Ming; Liu, Yi-gang; Liu, Min; Zhao, Feng

2015-01-01

In this study, the effects of gravitational settling time, temperature, speed and time of centrifugation, flocculant type and dosage, bubble size and gas amount were investigated. The results show that the simple increase in settling time and temperature is of no use for oil-water separation of the three wastewater samples. As far as oil-water separation efficiency is concerned, increasing centrifugal speed and centrifugal time is highly effective for L sample, and has a certain effect on J sample, but is not valid for S sample. The flocculants are highly effective for S and L samples, and the oil-water separation efficiency increases with an increase in the concentration of inorganic cationic flocculants. There exist critical reagent concentrations for the organic cationic and the nonionic flocculants, wherein a higher or lower concentration of flocculant would cause a decrease in the treatment efficiency. Flotation is an effective approach for oil-water separation of polymer-contained wastewater from the three oilfields. The oil-water separation efficiency can be enhanced by increasing floatation agent concentration, flotation time and gas amount, and by decreasing bubble size.

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

PubMed

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.

Self-objectification and disordered eating: A meta-analysis.

PubMed

Schaefer, Lauren M; Thompson, J Kevin

2018-06-01

Objectification theory posits that self-objectification increases risk for disordered eating. The current study sought to examine the relationship between self-objectification and disordered eating using meta-analytic techniques. Data from 53 cross-sectional studies (73 effect sizes) revealed a significant moderate positive overall effect (r = .39), which was moderated by gender, ethnicity, sexual orientation, and measurement of self-objectification. Specifically, larger effect sizes were associated with female samples and the Objectified Body Consciousness Scale. Effect sizes were smaller among heterosexual men and African American samples. Age, body mass index, country of origin, measurement of disordered eating, sample type and publication type were not significant moderators. Overall, results from the first meta-analysis to examine the relationship between self-objectification and disordered eating provide support for one of the major tenets of objectification theory and suggest that self-objectification may be a meaningful target in eating disorder interventions, though further work is needed to establish temporal and causal relationships. Findings highlight current gaps in the literature (e.g., limited representation of males, and ethnic and sexual minorities) with implications for guiding future research. © 2018 Wiley Periodicals, Inc.

Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for narrow confidence intervals.

PubMed

Lai, Keke; Kelley, Ken

2011-06-01

In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about the magnitude of the population targeted effects. With the goal of obtaining sufficiently narrow confidence intervals for the model parameters of interest, sample size planning methods for SEM are developed from the accuracy in parameter estimation approach. One method plans for the sample size so that the expected confidence interval width is sufficiently narrow. An extended procedure ensures that the obtained confidence interval will be no wider than desired, with some specified degree of assurance. A Monte Carlo simulation study was conducted that verified the effectiveness of the procedures in realistic situations. The methods developed have been implemented in the MBESS package in R so that they can be easily applied by researchers. © 2011 American Psychological Association

Numerical calculations of spectral turnover and synchrotron self-absorption in CSS and GPS radio sources

NASA Astrophysics Data System (ADS)

Jeyakumar, S.

2016-06-01

The dependence of the turnover frequency on the linear size is presented for a sample of Giga-hertz Peaked Spectrum and Compact Steep Spectrum radio sources derived from complete samples. The dependence of the luminosity of the emission at the peak frequency with the linear size and the peak frequency is also presented for the galaxies in the sample. The luminosity of the smaller sources evolve strongly with the linear size. Optical depth effects have been included to the 3D model for the radio source of Kaiser to study the spectral turnover. Using this model, the observed trend can be explained by synchrotron self-absorption. The observed trend in the peak-frequency-linear-size plane is not affected by the luminosity evolution of the sources.

Monitoring the impact of Bt maize on butterflies in the field: estimation of required sample sizes.

PubMed

Lang, Andreas

2004-01-01

The monitoring of genetically modified organisms (GMOs) after deliberate release is important in order to assess and evaluate possible environmental effects. Concerns have been raised that the transgenic crop, Bt maize, may affect butterflies occurring in field margins. Therefore, a monitoring of butterflies was suggested accompanying the commercial cultivation of Bt maize. In this study, baseline data on the butterfly species and their abundance in maize field margins is presented together with implications for butterfly monitoring. The study was conducted in Bavaria, South Germany, between 2000-2002. A total of 33 butterfly species was recorded in field margins. A small number of species dominated the community, and butterflies observed were mostly common species. Observation duration was the most important factor influencing the monitoring results. Field margin size affected the butterfly abundance, and habitat diversity had a tendency to influence species richness. Sample size and statistical power analyses indicated that a sample size in the range of 75 to 150 field margins for treatment (transgenic maize) and control (conventional maize) would detect (power of 80%) effects larger than 15% in species richness and the butterfly abundance pooled across species. However, a much higher number of field margins must be sampled in order to achieve a higher statistical power, to detect smaller effects, and to monitor single butterfly species.

Effect of carbon source on the morphology and electrochemical performances of LiFePO4/C nanocomposites.

PubMed

Liu, Shuxin; Wang, Haibin; Yin, Hengbo; Wang, Hong; He, Jichuan

2014-03-01

The carbon coated LiFePO4 (LiFePO4/C) nanocomposites materials were successfully synthesized by sol-gel method. The microstructure and morphology of LiFePO4/C nanocomposites were characterized by X-ray diffraction, Raman spectroscopy and scanning electron microscopy. The results showed that the carbon layers decomposed by different dispersant and carbon source had different graphitization degree, and the sugar could decompose to form more graphite-like structure carbon. The carbon source and heat-treatment temperature had some effect on the particle size and morphology, the sample LFP-S700 synthesized by adding sugar as carbon source at 700 degrees C had smaller particle size, uniform size distribution and spherical shape. The electrochemical behavior of LiFePO4/C nanocomposites was analyzed using galvanostatic measurements and cyclic voltammetry (CV). The results showed that the sample LFP-S700 had higher discharge specific capacities, higher apparent lithium ion diffusion coefficient and lower charge transfer resistance. The excellent electrochemical performance of sample LFP-S700 could be attributed to its high graphitization degree of carbon, smaller particle size and uniform size distribution.

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

PubMed

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.

High energy ball milling study of Fe{sub 2}MnSn Heusler alloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, Vivek Kumar, E-mail: vivek.jain129@gmail.com; Lakshmi, N.; Jain, Vishal

The structural and magnetic properties of as-melted and high energy ball milled alloy samples have been studied by X-ray diffraction, DC magnetization and electronic structure calculations by means of density functional theory. The observed properties are compared to that of the bulk sample. There is a very good enhancement of saturation magnetization and coercivity in the nano-sized samples as compared to bulk which is explained in terms of structural disordering and size effect.

Inherent size effects on XANES of nanometer metal clusters: Size-selected platinum clusters on silica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Yang; Gorey, Timothy J.; Anderson, Scott L.

2016-12-12

X-ray absorption near-edge structure (XANES) is commonly used to probe the oxidation state of metal-containing nanomaterials, however, as the particle size in the material drops below a few nanometers, it becomes important to consider inherent size effects on the electronic structure of the materials. In this paper, we analyze a series of size-selected Pt n/SiO 2 samples, using X-ray photoelectron spectroscopy (XPS), low energy ion scattering, grazing-incidence small angle X-ray scattering, and XANES. The oxidation state and morphology are characterized both as-deposited in UHV, and after air/O 2 exposure and annealing in H 2. Here, the clusters are found tomore » be stable during deposition and upon air exposure, but sinter if heated above ~150 °C. XANES shows shifts in the Pt L 3 edge, relative to bulk Pt, that increase with decreasing cluster size, and the cluster samples show high white line intensity. Reference to bulk standards would suggest that the clusters are oxidized, however, XPS shows that they are not. Instead, the XANES effects are attributable to development of a band gap and localization of empty state wavefunctions in small clusters.« less

Effect of charcoal doping on the superconducting properties of MgB 2 bulk

NASA Astrophysics Data System (ADS)

Kim, N. K.; Tan, K. S.; Jun, B.-H.; Park, H. W.; Joo, J.; Kim, C.-J.

2008-09-01

The effect of charcoal doping on the superconducting properties of in situ processed MgB 2 bulk samples was investigated. To understand the size effect of the dopant the charcoal powder was attrition milled for 1 h, 3 h and 6 h using ZrO 2 balls. The milled charcoal powders were mixed with magnesium and boron powders to a nominal composition of Mg(B 0.975C 0.025) 2. The Mg(B 0.975C 0.025) 2 compacts were heat-treated at 900 °C for 0.5 h in flowing Ar atmosphere. Magnetic susceptibility for the samples showed that the superconducting transition temperature ( Tc) decreased as the size of the charcoal powder decreased. The critical current density ( Jc) of Mg(B 0.975C 0.025) 2 prepared using large size charcoal powder was lower than that of the undoped MgB 2. However, a crossover of Jc value was observed at high magnetic fields of about 4 T in Mg(B 0.975C 0.025) 2 prepared using small size charcoal powder. Carbon diffusion into the boron site was easier and gave the Jc increase effect when the small size charcoal was used as a dopant.

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

USGS Publications Warehouse

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 <1%/additional location) and precise (CV < 50%). Although the radiotracking data appeared unbiased, except for the relationship between area and sample size, these data failed to indicate some areas that likely were important to 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.

(Sample) Size Matters: Best Practices for Defining Error in Planktic Foraminiferal Proxy Records

NASA Astrophysics Data System (ADS)

Lowery, C.; Fraass, A. J.

2016-02-01

Paleoceanographic research is a vital tool to extend modern observational datasets and to study the impact of climate events for which there is no modern analog. Foraminifera are one of the most widely used tools for this type of work, both as paleoecological indicators and as carriers for geochemical proxies. However, the use of microfossils as proxies for paleoceanographic conditions brings about a unique set of problems. This is primarily due to the fact that groups of individual foraminifera, which usually live about a month, are used to infer average conditions for time periods ranging from hundreds to tens of thousands of years. Because of this, adequate sample size is very important for generating statistically robust datasets, particularly for stable isotopes. In the early days of stable isotope geochemistry, instrumental limitations required hundreds of individual foraminiferal tests to return a value. This had the fortunate side-effect of smoothing any seasonal to decadal changes within the planktic foram population. With the advent of more sensitive mass spectrometers, smaller sample sizes have now become standard. While this has many advantages, the use of smaller numbers of individuals to generate a data point has lessened the amount of time averaging in the isotopic analysis and decreased precision in paleoceanographic datasets. With fewer individuals per sample, the differences between individual specimens will result in larger variation, and therefore error, and less precise values for each sample. Unfortunately, most (the authors included) do not make a habit of reporting the error associated with their sample size. We have created an open-source model in R to quantify the effect of sample sizes under various realistic and highly modifiable parameters (calcification depth, diagenesis in a subset of the population, improper identification, vital effects, mass, etc.). For example, a sample in which only 1 in 10 specimens is diagenetically altered can be off by >0.3‰ δ18O VPDB, or 1°C. Here, we demonstrate the use of this tool to quantify error in micropaleontological datasets, and suggest best practices for minimizing error when generating stable isotope data with foraminifera.

Grain size dependence of dynamic mechanical behavior of AZ31B magnesium alloy sheet under compressive shock loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asgari, H., E-mail: hamed.asgari@usask.ca; Odeshi, A.G.; Szpunar, J.A.

2015-08-15

The effects of grain size on the dynamic deformation behavior of rolled AZ31B alloy at high strain rates were investigated. Rolled AZ31B alloy samples with grain sizes of 6, 18 and 37 μm, were subjected to shock loading tests using Split Hopkinson Pressure Bar at room temperature and at a strain rate of 1100 s{sup −} {sup 1}. It was found that a double-peak basal texture formed in the shock loaded samples. The strength and ductility of the alloy under the high strain-rate compressive loading increased with decreasing grain size. However, twinning fraction and strain hardening rate were found tomore » decrease with decreasing grain size. In addition, orientation imaging microscopy showed a higher contribution of double and contraction twins in the deformation process of the coarse-grained samples. Using transmission electron microscopy, pyramidal dislocations were detected in the shock loaded sample, proving the activation of pyramidal slip system under dynamic impact loading. - Highlights: • A double-peak basal texture developed in all shock loaded samples. • Both strength and ductility increased with decreasing grain size. • Twinning fraction and strain hardening rate decreased with decreasing grain size. • ‘g.b’ analysis confirmed the presence of dislocations in shock loaded alloy.« less

The Discovery of Single-Nucleotide Polymorphisms—and Inferences about Human Demographic History

PubMed Central

Wakeley, John; Nielsen, Rasmus; Liu-Cordero, Shau Neen; Ardlie, Kristin

2001-01-01

A method of historical inference that accounts for ascertainment bias is developed and applied to single-nucleotide polymorphism (SNP) data in humans. The data consist of 84 short fragments of the genome that were selected, from three recent SNP surveys, to contain at least two polymorphisms in their respective ascertainment samples and that were then fully resequenced in 47 globally distributed individuals. Ascertainment bias is the deviation, from what would be observed in a random sample, caused either by discovery of polymorphisms in small samples or by locus selection based on levels or patterns of polymorphism. The three SNP surveys from which the present data were derived differ both in their protocols for ascertainment and in the size of the samples used for discovery. We implemented a Monte Carlo maximum-likelihood method to fit a subdivided-population model that includes a possible change in effective size at some time in the past. Incorrectly assuming that ascertainment bias does not exist causes errors in inference, affecting both estimates of migration rates and historical changes in size. Migration rates are overestimated when ascertainment bias is ignored. However, the direction of error in inferences about changes in effective population size (whether the population is inferred to be shrinking or growing) depends on whether either the numbers of SNPs per fragment or the SNP-allele frequencies are analyzed. We use the abbreviation “SDL,” for “SNP-discovered locus,” in recognition of the genomic-discovery context of SNPs. When ascertainment bias is modeled fully, both the number of SNPs per SDL and their allele frequencies support a scenario of growth in effective size in the context of a subdivided population. If subdivision is ignored, however, the hypothesis of constant effective population size cannot be rejected. An important conclusion of this work is that, in demographic or other studies, SNP data are useful only to the extent that their ascertainment can be modeled. PMID:11704929

Effect of laser irradiation on surface hardness and structural parameters of 7178 aluminium alloy

NASA Astrophysics Data System (ADS)

Maryam, Siddra; Bashir, Farooq

2018-04-01

Aluminium 7178 samples were prepared and irradiated with Nd:YAG laser. The surfaces of exposed samples were investigated using optical microscopy, which revealed that the surface morphology of the samples is changed drastically as a function of laser shots. It is revealed from the micrographs that the laser heat effected area increases with the increase in the number of the laser pulses. Furthermore morphological and mechanical properties were studied using XRD and Vickers hardness testing. XRD study shows an increasing trend in Grain size with the increasing number of laser shots. And the hardness of the samples as a function of the laser shots shows that the hardness first increases and then it decreases gradually. It was observed that the grain size has no pronouncing effect on the hardness. Hardness profile has a decreasing trend with the increase in linear distance from the boundary of the laser heat affected area.

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.

PubMed

Gupta, Manan; Joshi, Amitabh; Vidya, T N C

2017-01-01

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. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.

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

PubMed Central

Joshi, Amitabh; Vidya, T. N. C.

2017-01-01

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. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species. PMID:28306735

An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

PubMed

Dodd, Lori E; Korn, Edward L; Freidlin, Boris; Gu, Wenjuan; Abrams, Jeffrey S; Bushnell, William D; Canetta, Renzo; Doroshow, James H; Gray, Robert J; Sridhara, Rajeshwari

2013-10-01

Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-means Cluster Analysis.

PubMed

Craen, Saskia de; Commandeur, Jacques J F; Frank, Laurence E; Heiser, Willem J

2006-06-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these populations showed a significant effect of lack of sphericity and group size. This effect was, however, not as large as expected, with still a recovery index of more than 0.5 in the "worst case scenario." An interaction effect between the two data aspects was also found. The decreasing trend in the recovery of clusters for increasing departures from sphericity is different for equal and unequal group sizes.

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

DOE PAGES

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong; ...

2015-05-19

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Quantitative Reflectance Spectra of Solid Powders as a Function of Particle Size

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, Tanya L.; Brauer, Carolyn S.; Su, Yin-Fong

We have recently developed vetted methods for obtaining quantitative infrared directional-hemispherical reflectance spectra using a commercial integrating sphere. In this paper, the effects of particle size on the spectral properties are analyzed for several samples such as ammonium sulfate, calcium carbonate, and sodium sulfate as well as one organic compound, lactose. We prepared multiple size fractions for each sample and confirmed the mean sizes using optical microscopy. Most species displayed a wide range of spectral behavior depending on the mean particle size. General trends of reflectance vs. particle size are observed such as increased albedo for smaller particles: for mostmore » wavelengths, the reflectivity drops with increased size, sometimes displaying a factor of 4 or more drop in reflectivity along with a loss of spectral contrast. In the longwave infrared, several species with symmetric anions or cations exhibited reststrahlen features whose amplitude was nearly invariant with particle size, at least for intermediate- and large-sized sample fractions; that is, > ~150 microns. Trends of other types of bands (Christiansen minima, transparency features) are also investigated as well as quantitative analysis of the observed relationship between reflectance vs. particle diameter.« less

Sample Size Requirements for Studies of Treatment Effects on Beta-Cell Function in Newly Diagnosed Type 1 Diabetes

PubMed Central

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

2011-01-01

Preservation of -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(), log(+1) and square-root 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(+1) and 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 evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes. PMID:22102862

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

PubMed

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 evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes.

Characterization of the enhancement effect of Na2CO3 on the sulfur capture capacity of limestones.

PubMed

Laursen, Karin; Kern, Arnt A; Grace, John R; Lim, C Jim

2003-08-15

It has been known for a long time that certain additives (e.g., NaCl, CaCl2, Na2CO3, Fe2O3) can increase the sulfur dioxide capture-capacity of limestones. In a recent study we demonstrated that very small amounts of Na2CO3 can be very beneficial for producing sorbents of very high sorption capacities. This paper explores what contributes to these significant increases. Mercury porosimetry measurements of calcined limestone samples reveal a change in the pore-size from 0.04-0.2 microm in untreated samples to 2-10 microm in samples treated with Na2CO3--a pore-size more favorable for penetration of sulfur into the particles. The change in pore-size facilitates reaction with lime grains throughout the whole particle without rapid plugging of pores, avoiding premature change from a fast chemical reaction to a slow solid-state diffusion controlled process, as seen for untreated samples. Calcination in a thermogravimetric reactor showed that Na2CO3 increased the rate of calcination of CaCO3 to CaO, an effect which was slightly larger at 825 degrees C than at 900 degrees C. Peak broadening analysis of powder X-ray diffraction data of the raw, calcined, and sulfated samples revealed an unaffected calcite size (approximately 125-170 nm) but a significant increase in the crystallite size for lime (approximately 60-90 nm to approximately 250-300 nm) and less for anhydrite (approximately 125-150 nm to approximately 225-250 nm). The increase in the crystallite and pore-size of the treated limestones is attributed to an increase in ionic mobility in the crystal lattice due to formation of vacancies in the crystals when Ca is partly replaced by Na.

Motion mitigation for lung cancer patients treated with active scanning proton therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grassberger, Clemens, E-mail: Grassberger.Clemens@mgh.harvard.edu; Dowdell, Stephen; Sharp, Greg

2015-05-15

Purpose: Motion interplay can affect the tumor dose in scanned proton beam therapy. This study assesses the ability of rescanning and gating to mitigate interplay effects during lung treatments. Methods: The treatments of five lung cancer patients [48 Gy(RBE)/4fx] with varying tumor size (21.1–82.3 cm{sup 3}) and motion amplitude (2.9–30.6 mm) were simulated employing 4D Monte Carlo. The authors investigated two spot sizes (σ ∼ 12 and ∼3 mm), three rescanning techniques (layered, volumetric, breath-sampled volumetric) and respiratory gating with a 30% duty cycle. Results: For 4/5 patients, layered rescanning 6/2 times (for the small/large spot size) maintains equivalent uniformmore » dose within the target >98% for a single fraction. Breath sampling the timing of rescanning is ∼2 times more effective than the same number of continuous rescans. Volumetric rescanning is sensitive to synchronization effects, which was observed in 3/5 patients, though not for layered rescanning. For the large spot size, rescanning compared favorably with gating in terms of time requirements, i.e., 2x-rescanning is on average a factor ∼2.6 faster than gating for this scenario. For the small spot size however, 6x-rescanning takes on average 65% longer compared to gating. Rescanning has no effect on normal lung V{sub 20} and mean lung dose (MLD), though it reduces the maximum lung dose by on average 6.9 ± 2.4/16.7 ± 12.2 Gy(RBE) for the large and small spot sizes, respectively. Gating leads to a similar reduction in maximum dose and additionally reduces V{sub 20} and MLD. Breath-sampled rescanning is most successful in reducing the maximum dose to the normal lung. Conclusions: Both rescanning (2–6 times, depending on the beam size) as well as gating was able to mitigate interplay effects in the target for 4/5 patients studied. Layered rescanning is superior to volumetric rescanning, as the latter suffers from synchronization effects in 3/5 patients studied. Gating minimizes the irradiated volume of normal lung more efficiently, while breath-sampled rescanning is superior in reducing maximum doses to organs at risk.« less

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

PubMed Central

Song, Rui; Kosorok, Michael R.; Cai, Jianwen

2009-01-01

Summary Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847–862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do not contain significant information about event times, it reduces to the same form as that of Schoenfeld (1983, Biometrics 39, 499–503) for cases of a single event or independent event times within a subject. We carry out simulations to study the control of type I error and the comparison of powers between several methods in finite samples. The proposed sample size formula is illustrated using data from an rhDNase study. PMID:18162107

The Relation of Empathy and Defending in Bullying: A Meta-Analytic Investigation

ERIC Educational Resources Information Center

Nickerson, Amanda B.; Aloe, Ariel M.; Werth, Jilynn M.

2015-01-01

This meta-analysis synthesized results about the association between empathy and defending in bullying. A total of 20 studies were included, with 22 effect sizes from 6 studies that separated findings by the defender's gender, and 31 effect sizes from 18 studies that provided effects for the total sample were included in the analysis. The weighted…

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

PubMed

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

2016-01-01

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

Investigation of the annealing temperature effect on structural, morphology, dielectric and magnetic properties of BiFeO3 nanoparticles

NASA Astrophysics Data System (ADS)

Ranjbar, M.; Ghazi, M. E.; Izadifard, M.

2018-06-01

In this paper we have investigated the annealing temperature effect on the structure, morphology, dielectric and magnetic properties of sol-gel synthesized multiferroic BiFeO3 nanoparticles. X-ray diffraction spectroscopy revealed that all the samples have rhombohedrally distorted perovskite structure and the most pure BFO phase is obtained on the sample annealed at 800 °C. Field emission scanning electron microscopy (FESEM) revealed that increasing annealing temperature would increase the particle size. Decrease in dielectric constant was also observed by increasing annealing temperature. Vibrating sample method (VSM) analysis confirmed that samples annealed at 500-700 °C with particle size below the BFO's spiral spin structure length, have well saturated M-H curve and show ferromagnetic behavior.

75 FR 39200 - Periodic Reporting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... using an alternative sample frame. Establishing this docket will allow the Commission to consider the... Information System/Revenue Pieces and Weight (ODIS/RPW) data by 20 percent. Id. at 3. In effect, Proposal Two... sample size to a special study utilizing an alternative sample frame. The alternative sample frame that...

Ratio of Cut Surface Area to Leaf Sample Volume for Water Potential Measurements by Thermocouple Psychrometers

PubMed Central

Walker, Sue; Oosterhuis, Derrick M.; Wiebe, Herman H.

1984-01-01

Evaporative losses from the cut edge of leaf samples are of considerable importance in measurements of leaf water potential using thermocouple psychrometers. The ratio of cut surface area to leaf sample volume (area to volume ratio) has been used to give an estimate of possible effects of evaporative loss in relation to sample size. A wide range of sample sizes with different area to volume ratios has been used. Our results using Glycine max L. Merr. cv Bragg indicate that leaf samples with area to volume values less than 0.2 square millimeter per cubic millimeter give psychrometric leaf water potential measurements that compare favorably with pressure chamber measurements. PMID:16663578

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saxena, Shailendra K., E-mail: phd1211512@iiti.ac.in; Sahu, Gayatri; Sagdeo, Pankaj R.

Quantum confinement effect has been studied in cheese like silicon nano-structures (Ch-SiNS) fabricated by metal induced chemical etching using different etching times. Scanning electron microscopy is used for the morphological study of these Ch-SiNS. A visible photoluminescence (PL) emission is observed from the samples under UV excitation at room temperature due to quantum confinement effect. The average size of Silicon Nanostructures (SiNS) present in the samples has been estimated by bond polarizability model using Raman Spectroscopy from the red-shift observed from SiNSs as compared to its bulk counterpart. The sizes of SiNS present in the samples decreases as etching timemore » increase from 45 to 75 mintunes.« less

Facile Synthesis of Calcium Borate Nanoparticles and the Annealing Effect on Their Structure and Size

PubMed Central

Erfani, Maryam; Saion, Elias; Soltani, Nayereh; Hashim, Mansor; Wan Abdullah, Wan Saffiey B.; Navasery, Manizheh

2012-01-01

Calcium borate nanoparticles have been synthesized by a thermal treatment method via facile co-precipitation. Differences of annealing temperature and annealing time and their effects on crystal structure, particle size, size distribution and thermal stability of nanoparticles were investigated. The formation of calcium borate compound was characterized by X-ray diffraction (XRD) and Fourier Transform Infrared spectroscopy (FTIR), Transmission electron microscopy (TEM), and Thermogravimetry (TGA). The XRD patterns revealed that the co-precipitated samples annealed at 700 °C for 3 h annealing time formed an amorphous structure and the transformation into a crystalline structure only occurred after 5 h annealing time. It was found that the samples annealed at 900 °C are mostly metaborate (CaB2O4) nanoparticles and tetraborate (CaB4O7) nanoparticles only observed at 970 °C, which was confirmed by FTIR. The TEM images indicated that with increasing the annealing time and temperature, the average particle size increases. TGA analysis confirmed the thermal stability of the annealed samples at higher temperatures. PMID:23203073

Processing and Characterization of Porous Ti2AlC with Controlled Porosity and Pore Size

DTIC Science & Technology

2012-09-11

fabricated by spark plasma sintering , were also characterized. The effects of porosity and/or pore size on the room temperature elastic moduli...pressureless- sintered without NaCl pore former, or fabricated by spark plasma sintering , were also characterized. The effects of porosity and/or pore size...as well as several samples sintered using spark plasma sintering (SPS). Furthermore, we demon- strate that the developed methodology can be implemented

Longitudinal Effects of Class Size Reductions on Attainment: Results from Hong Kong Primary Classrooms

ERIC Educational Resources Information Center

Galton, Maurice; Pell, Tony

2012-01-01

In a four-year study of the effect of class size on pupil outcomes in a sample of 36 primary schools in Hong Kong, it has been found that there are few positive differences in attainment between classes set at less than 25 pupils and those of normal size averaging 38. Three cohorts of pupils were studied. In Cohort 1 pupils spent 3 years in small…

The Effect of Composition, Size, and Solubility on Acute Pulmonary Injury in Rats Following Exposure to Mexico City Ambient Particulate Matter Samples

EPA Science Inventory

Particulate matter (PM) associated metals contribute to the adverse cardiopulmonary effects following exposure to air pollution. Here, we investigated how variation in the composition and size of ambient PM collected from two distinct regions in Mexico City relates to toxicity d...

How Thinking About the Donor Influences Post-traumatic Growth in Liver Transplant Recipients.

PubMed

Martín-Rodríguez, A; Pérez-San-Gregorio, M Á; Avargues-Navarro, M L; Borda-Mas, M; Pérez-Bernal, J; Gómez-Bravo, M Á

2018-03-01

The aim of this work was to find out whether thinking frequently about the donor influences post-traumatic growth of liver transplant recipients. The sample of 240 patients selected was made up of 185 men and 55 women with an overall mean age of 60.21 (SD 9.3) years. All of them had received liver transplants from cadaver donors. Transplant recipients were asked whether they thought frequently about the donor (yes or no) and filled out the Post-traumatic Growth Inventory. The t test for unpaired samples was applied to analyze how thinking frequently about the donor or not influenced post-traumatic growth. We also calculated the effect sizes by means of Cohen d or Cohen w depending on the nature of the variables analyzed (quantitative or qualitative). The liver transplant recipients who thought frequently about the donor, compared with those who did not, had higher total scores on post-traumatic growth (P = .000; d = 0.57; medium effect size). Furthermore, considering the effect sizes, the differences between the subgroups were more relevant on the following subscales: new possibilities (P = .000; d = 0.53; medium effect size), appreciation of life (P = .000; d = 0.60; medium effect size), and spiritual change (P = .000; d = 0.54; medium effect size). Patients who think frequently about the donor have more post-traumatic growth than those who do not. Copyright © 2017 Elsevier Inc. All rights reserved.

An Investigation of the Sampling Distribution of the Congruence Coefficient.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.; Elmore, Patricia B.

This study developed and investigated an empirical sampling distribution of the congruence coefficient. The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model and…

Synthesis, structure and magnetic properties of nanostructured La1-xAxFe0.5Mn0.5O3 (A = Ca, Sr and Pb; x = 0 & 0.25) perovskites

NASA Astrophysics Data System (ADS)

Hossain, Aslam; Ghosh, Debamalya; Dutta, Uma; Walke, Pravin S.; Mordvinova, Natalia E.; Lebedev, Oleg I.; Sinha, Bhavesh; Pal, Kamalesh; Gayen, Arup; Kundu, Asish K.; Seikh, Md. Motin

2017-12-01

The effect of hole doping on magnetic properties of LaFe0.5Mn0.5O3 have been investigated. All the ceramics samples La1-xAxFe0.5Mn0.5O3 (A = Ca, Sr and Pb; x = 0 & 0.25) were synthesized at 500 °C by sol-gel method and the particles size were found to be in nanodimension. The samples were characterized by X-ray and electron diffraction, HRTEM and both dc and ac-magnetization measurements. The X-ray and electron diffraction patterns were indexed by cubic Pm-3m space group. The particle size of the LaFe0.5Mn0.5O3 is ∼100 nm, whereas the Pb-doped sample is ∼50 nm and for Ca or Sr doped samples the size is ∼10-30 nm. Both dc and ac-susceptibility measurements suggest that the effect of hole doping and A-site cationic radius in LaFe0.5Mn0.5O3 have no significant role on magnetic properties. However, the particle size plays an important role on magnetic property due to the development of surface ferromagnetic cluster at nanoscale. The competing interactions lead to magnetic phase separation where local ferromagnetic clusters coexist within the antiferromagentic matrix in all the samples.

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Are There Scenarios When the Use of Non-Placebo-Control Groups in Experimental Trial Designs Increase Expected Value to Society?

PubMed

Uyei, Jennifer; Braithwaite, R Scott

2016-01-01

Despite the benefits of the placebo-controlled trial design, it is limited by its inability to quantify total benefits and harms. Such trials, for example, are not designed to detect an intervention's placebo or nocebo effects, which if detected could alter the benefit-to-harm balance and change a decision to adopt or reject an intervention. In this article, we explore scenarios in which alternative experimental trial designs, which differ in the type of control used, influence expected value across a range of pretest assumptions and study sample sizes. We developed a decision model to compare 3 trial designs and their implications for decision making: 2-arm placebo-controlled trial ("placebo-control"), 2-arm intervention v. do nothing trial ("null-control"), and an innovative 3-arm trial design: intervention v. do nothing v. placebo trial ("novel design"). Four scenarios were explored regarding particular attributes of a hypothetical intervention: 1) all benefits and no harm, 2) no biological effect, 3) only biological effects, and 4) surreptitious harm (no biological benefit or nocebo effect). Scenario 1: When sample sizes were very small, the null-control was preferred, but as sample sizes increased, expected value of all 3 designs converged. Scenario 2: The null-control was preferred regardless of sample size when the ratio of placebo to nocebo effect was >1; otherwise, the placebo-control was preferred. Scenario 3: When sample size was very small, the placebo-control was preferred when benefits outweighed harms, but the novel design was preferred when harms outweighed benefits. Scenario 4: The placebo-control was preferred when harms outweighed placebo benefits; otherwise, preference went to the null-control. Scenarios are hypothetical, study designs have not been tested in a real-world setting, blinding is not possible in all designs, and some may argue the novel design poses ethical concerns. We identified scenarios in which alternative experimental study designs would confer greater expected value than the placebo-controlled trial design. The likelihood and prevalence of such situations warrant further study. © The Author(s) 2015.

The effects of neutralized particles on the sampling efficiency of polyurethane foam used to estimate the extrathoracic deposition fraction.

PubMed

Tomyn, Ronald L; Sleeth, Darrah K; Thiese, Matthew S; Larson, Rodney R

2016-01-01

In addition to chemical composition, the site of deposition of inhaled particles is important for determining the potential health effects from an exposure. As a result, the International Organization for Standardization adopted a particle deposition sampling convention. This includes extrathoracic particle deposition sampling conventions for the anterior nasal passages (ET1) and the posterior nasal and oral passages (ET2). This study assessed how well a polyurethane foam insert placed in an Institute of Occupational Medicine (IOM) sampler can match an extrathoracic deposition sampling convention, while accounting for possible static buildup in the test particles. In this way, the study aimed to assess whether neutralized particles affected the performance of this sampler for estimating extrathoracic particle deposition. A total of three different particle sizes (4.9, 9.5, and 12.8 µm) were used. For each trial, one particle size was introduced into a low-speed wind tunnel with a wind speed set a 0.2 m/s (∼40 ft/min). This wind speed was chosen to closely match the conditions of most indoor working environments. Each particle size was tested twice either neutralized, using a high voltage neutralizer, or left in its normal (non neutralized) state as standard particles. IOM samplers were fitted with a polyurethane foam insert and placed on a rotating mannequin inside the wind tunnel. Foam sampling efficiencies were calculated for all trials to compare against the normalized ET1 sampling deposition convention. The foam sampling efficiencies matched well to the ET1 deposition convention for the larger particle sizes, but had a general trend of underestimating for all three particle sizes. The results of a Wilcoxon Rank Sum Test also showed that only at 4.9 µm was there a statistically significant difference (p-value = 0.03) between the foam sampling efficiency using the standard particles and the neutralized particles. This is interpreted to mean that static buildup may be occurring and neutralizing the particles that are 4.9 µm diameter in size did affect the performance of the foam sampler when estimating extrathoracic particle deposition.

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity.

PubMed

Khan, Bilal; Lee, Hsuan-Wei; Fellows, Ian; Dombrowski, Kirk

2018-01-01

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section.

Lowering sample size in comparative analyses can indicate a correlation where there is none: example from Rensch's rule in primates.

PubMed

Lindenfors, P; Tullberg, B S

2006-07-01

The fact that characters may co-vary in organism groups because of shared ancestry and not always because of functional correlations was the initial rationale for developing phylogenetic comparative methods. Here we point out a case where similarity due to shared ancestry can produce an undesired effect when conducting an independent contrasts analysis. Under special circumstances, using a low sample size will produce results indicating an evolutionary correlation between characters where an analysis of the same pattern utilizing a larger sample size will show that this correlation does not exist. This is the opposite effect of increased sample size to that expected; normally an increased sample size increases the chance of finding a correlation. The situation where the problem occurs is when co-variation between the two continuous characters analysed is clumped in clades; e.g. when some phylogenetically conservative factors affect both characters simultaneously. In such a case, the correlation between the two characters becomes contingent on the number of clades sharing this conservative factor that are included in the analysis, in relation to the number of species contained within these clades. Removing species scattered evenly over the phylogeny will in this case remove the exact variation that diffuses the evolutionary correlation between the two characters - the variation contained within the clades sharing the conservative factor. We exemplify this problem by discussing a parallel in nature where the described problem may be of importance. This concerns the question of the presence or absence of Rensch's rule in primates.

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

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

PubMed Central

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

2015-01-01

Motivation: 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. Results: 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. Availability and implementation: http://github.com/brendankelly/micropower. Contact: brendank@mail.med.upenn.edu or hongzhe@upenn.edu PMID:25819674

Got power? A systematic review of sample size adequacy in health professions education research.

PubMed

Cook, David A; Hatala, Rose

2015-03-01

Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011, and included all studies evaluating simulation-based education for health professionals in comparison with no intervention or another simulation intervention. Reviewers working in duplicate abstracted information to calculate standardized mean differences (SMD's). We included 897 original research studies. Among the 627 no-intervention-comparison studies the median sample size was 25. Only two studies (0.3%) had ≥80% power to detect a small difference (SMD > 0.2 standard deviations) and 136 (22%) had power to detect a large difference (SMD > 0.8). 110 no-intervention-comparison studies failed to find a statistically significant difference, but none excluded a small difference and only 47 (43%) excluded a large difference. Among 297 studies comparing alternate simulation approaches the median sample size was 30. Only one study (0.3%) had ≥80% power to detect a small difference and 79 (27%) had power to detect a large difference. Of the 128 studies that did not detect a statistically significant effect, 4 (3%) excluded a small difference and 91 (71%) excluded a large difference. In conclusion, most education research studies are powered only to detect effects of large magnitude. For most studies that do not reach statistical significance, the possibility of large and important differences still exists.

A statistical analysis of seat belt effectiveness in 1973-1975 model cars involved in towaway crashes. Volume 1

DOT National Transportation Integrated Search

1976-09-01

Standardized injury rates and seat belt effectiveness measures are derived from a probability sample of towaway accidents involving 1973-1975 model cars. The data were collected in five different geographic regions. Weighted sample size available for...

Evaluating the Impact of Guessing and Its Interactions With Other Test Characteristics on Confidence Interval Procedures for Coefficient Alpha

PubMed Central

Paek, Insu

2015-01-01

The effect of guessing on the point estimate of coefficient alpha has been studied in the literature, but the impact of guessing and its interactions with other test characteristics on the interval estimators for coefficient alpha has not been fully investigated. This study examined the impact of guessing and its interactions with other test characteristics on four confidence interval (CI) procedures for coefficient alpha in terms of coverage rate (CR), length, and the degree of asymmetry of CI estimates. In addition, interval estimates of coefficient alpha when data follow the essentially tau-equivalent condition were investigated as a supplement to the case of dichotomous data with examinee guessing. For dichotomous data with guessing, the results did not reveal salient negative effects of guessing and its interactions with other test characteristics (sample size, test length, coefficient alpha levels) on CR and the degree of asymmetry, but the effect of guessing was salient as a main effect and an interaction effect with sample size on the length of the CI estimates, making longer CI estimates as guessing increases, especially when combined with a small sample size. Other important effects (e.g., CI procedures on CR) are also discussed. PMID:29795863

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

PubMed

Seto, Mayumi; Uriu, Koichiro

2015-03-01

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

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

PubMed

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.

Intra-class correlation estimates for assessment of vitamin A intake in children.

PubMed

Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

2005-03-01

In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

Effect of field view size and lighting on unique-hue selection using Natural Color System object colors.

PubMed

Shamey, Renzo; Zubair, Muhammad; Cheema, Hammad

2015-08-01

The aim of this study was twofold, first to determine the effect of field view size and second of illumination conditions on the selection of unique hue samples (UHs: R, Y, G and B) from two rotatable trays, each containing forty highly chromatic Natural Color System (NCS) samples, on one tray corresponding to 1.4° and on the other to 5.7° field of view size. UH selections were made by 25 color-normal observers who repeated assessments three times with a gap of at least 24h between trials. Observers separately assessed UHs under four illumination conditions simulating illuminants D65, A, F2 and F11. An apparent hue shift (statistically significant for UR) was noted for UH selections at 5.7° field of view compared to those at 1.4°. Observers' overall variability was found to be higher for UH stimuli selections at the larger field of view. Intra-observer variability was found to be approximately 18.7% of inter-observer variability in selection of samples for both sample sizes. The highest intra-observer variability was under simulated illuminant D65, followed by A, F11, and F2. Copyright © 2015 Elsevier Ltd. All rights reserved.

Storage effects on quantity and composition of dissolved organic carbon and nitrogen of lake water, leaf leachate and peat soil water.

PubMed

Heinz, Marlen; Zak, Dominik

2018-03-01

This study aimed to evaluate the effects of freezing and cold storage at 4 °C on bulk dissolved organic carbon (DOC) and nitrogen (DON) concentration and SEC fractions determined with size exclusion chromatography (SEC), as well as on spectral properties of dissolved organic matter (DOM) analyzed with fluorescence spectroscopy. In order to account for differences in DOM composition and source we analyzed storage effects for three different sample types, including a lake water sample representing freshwater DOM, a leaf litter leachate of Phragmites australis representing a terrestrial, 'fresh' DOM source and peatland porewater samples. According to our findings one week of cold storage can bias DOC and DON determination. Overall, the determination of DOC and DON concentration with SEC analysis for all three sample types were little susceptible to alterations due to freezing. The findings derived for the sampling locations investigated here may not apply for other sampling locations and/or sample types. However, DOC size fractions and DON concentration of formerly frozen samples should be interpreted with caution when sample concentrations are high. Alteration of some optical properties (HIX and SUVA 254 ) due to freezing were evident, and therefore we recommend immediate analysis of samples for spectral analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Synthesis and magnetic characterization of nickel ferrite nanoparticles prepared by co-precipitation route

NASA Astrophysics Data System (ADS)

Maaz, K.; Karim, S.; Mumtaz, A.; Hasanain, S. K.; Liu, J.; Duan, J. L.

2009-06-01

Magnetic nanoparticles of nickel ferrite (NiFe 2O 4) have been synthesized by co-precipitation route using stable ferric and nickel salts with sodium hydroxide as the precipitating agent and oleic acid as the surfactant. X-ray diffraction (XRD) and transmission electron microscope (TEM) analyses confirmed the formation of single-phase nickel ferrite nanoparticles in the range 8-28 nm depending upon the annealing temperature of the samples during the synthesis. The size of the particles ( d) was observed to be increasing linearly with annealing temperature of the sample while the coercivity with particle size goes through a maximum, peaking at ˜11 nm and then decreases for larger particles. Typical blocking effects were observed below ˜225 K for all the prepared samples. The superparamagnetic blocking temperature ( T B) was found to be increasing with increasing particle size that has been attributed to the increased effective anisotropy energy of the nanoparticles. The saturation moment of all the samples was found much below the bulk value of nickel ferrite that has been attributed to the disordered surface spins or dead/inert layer in these nanoparticles.

Mesoporous carbon synthesized from different pore sizes of SBA-15 for high density electrode supercapacitor application

NASA Astrophysics Data System (ADS)

Jamil, Farinaa Md; Sulaiman, Mohd Ali; Ibrahim, Suhaina Mohd; Masrom, Abdul Kadir; Yahya, Muhd Zu Azhan

2017-12-01

A series of mesoporous carbon sample was synthesized using silica template, SBA-15 with two different pore sizes. Impregnation method was applied using glucose as a precursor for converting it into carbon. An appropriate carbonization and silica removal process were carried out to produce a series of mesoporous carbon with different pore sizes and surface areas. Mesoporous carbon sample was then assembled as electrode and its performance was tested using cyclic voltammetry and impedance spectroscopy to study the effect of ion transportation into several pore sizes on electric double layer capacitor (EDLC) system. 6M KOH was used as electrolyte at various scan rates of 10, 20, 30 and 50 mVs-1. The results showed that the pore size of carbon increased as the pore size of template increased and the specific capacitance improved as the increasing of the pore size of carbon.

Brain size growth in wild and captive chimpanzees (Pan troglodytes).

PubMed

Cofran, Zachary

2018-05-24

Despite many studies of chimpanzee brain size growth, intraspecific variation is under-explored. Brain size data from chimpanzees of the Taï Forest and the Yerkes Primate Research Center enable a unique glimpse into brain growth variation as age at death is known for individuals, allowing cross-sectional growth curves to be estimated. Because Taï chimpanzees are from the wild but Yerkes apes are captive, potential environmental effects on neural development can also be explored. Previous research has revealed differences in growth and health between wild and captive primates, but such habitat effects have yet to be investigated for brain growth. Here, I use an iterative curve fitting procedure to estimate brain growth and regression parameters for each population, statistically comparing growth models using bootstrapped confidence intervals. Yerkes and Taï brain sizes overlap at all ages, although the sole Taï newborn is at the low end of captive neonatal variation. Growth rate and duration are statistically indistinguishable between the two populations. Resampling the Yerkes sample to match the Taï sample size and age group composition shows that ontogenetic variation in the two groups are remarkably similar despite the latter's limited size. Best fit growth curves for each sample indicate cessation of brain size growth at around 2 years, earlier than has previously been reported. The overall similarity between wild and captive chimpanzees points to the canalization of brain growth in this species. © 2018 Wiley Periodicals, Inc.

Characterization of the Particle Size and Polydispersity of Dicumarol Using Solid-State NMR Spectroscopy.

PubMed

Dempah, Kassibla Elodie; Lubach, Joseph W; Munson, Eric J

2017-03-06

A variety of particle sizes of a model compound, dicumarol, were prepared and characterized in order to investigate the correlation between particle size and solid-state NMR (SSNMR) proton spin-lattice relaxation ( 1 H T 1 ) times. Conventional laser diffraction and scanning electron microscopy were used as particle size measurement techniques and showed crystalline dicumarol samples with sizes ranging from tens of micrometers to a few micrometers. Dicumarol samples were prepared using both bottom-up and top-down particle size control approaches, via antisolvent microprecipitation and cryogrinding. It was observed that smaller particles of dicumarol generally had shorter 1 H T 1 times than larger ones. Additionally, cryomilled particles had the shortest 1 H T 1 times encountered (8 s). SSNMR 1 H T 1 times of all the samples were measured and showed as-received dicumarol to have a T 1 of 1500 s, whereas the 1 H T 1 times of the precipitated samples ranged from 20 to 80 s, with no apparent change in the physical form of dicumarol. Physical mixtures of different sized particles were also analyzed to determine the effect of sample inhomogeneity on 1 H T 1 values. Mixtures of cryoground and as-received dicumarol were clearly inhomogeneous as they did not fit well to a one-component relaxation model, but could be fit much better to a two-component model with both fast-and slow-relaxing regimes. Results indicate that samples of crystalline dicumarol containing two significantly different particle size populations could be deconvoluted solely based on their differences in 1 H T 1 times. Relative populations of each particle size regime could also be approximated using two-component fitting models. Using NMR theory on spin diffusion as a reference, and taking into account the presence of crystal defects, a model for the correlation between the particle size of dicumarol and its 1 H T 1 time was proposed.

R2 effect-size measures for mediation analysis

PubMed Central

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

R2 effect-size measures for mediation analysis.

PubMed

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.

Detection of linkage between a quantitative trait and a marker locus by the lod score method: sample size and sampling considerations.

PubMed

Demenais, F; Lathrop, G M; Lalouel, J M

1988-07-01

A simulation study is here conducted to measure the power of the lod score method to detect linkage between a quantitative trait and a marker locus in various situations. The number of families necessary to detect such linkage with 80% power is assessed for different sets of parameters at the trait locus and different values of the recombination fraction. The effects of varying the mode of sampling families and the sibship size are also evaluated.

Effect of Pore Size and Porosity on the Biomechanical Properties and Cytocompatibility of Porous NiTi Alloys

PubMed Central

Jian, Yu-Tao; Yang, Yue; Tian, Tian; Stanford, Clark; Zhang, Xin-Ping; Zhao, Ke

2015-01-01

Five types of porous Nickel-Titanium (NiTi) alloy samples of different porosities and pore sizes were fabricated. According to compressive and fracture strengths, three groups of porous NiTi alloy samples underwent further cytocompatibility experiments. Porous NiTi alloys exhibited a lower Young’s modulus (2.0 GPa ~ 0.8 GPa). Both compressive strength (108.8 MPa ~ 56.2 MPa) and fracture strength (64.6 MPa ~ 41.6 MPa) decreased gradually with increasing mean pore size (MPS). Cells grew and spread well on all porous NiTi alloy samples. Cells attached more strongly on control group and blank group than on all porous NiTi alloy samples (p < 0.05). Cell adhesion on porous NiTi alloys was correlated negatively to MPS (277.2 μm ~ 566.5 μm; p < 0.05). More cells proliferated on control group and blank group than on all porous NiTi alloy samples (p < 0.05). Cellular ALP activity on all porous NiTi alloy samples was higher than on control group and blank group (p < 0.05). The porous NiTi alloys with optimized pore size could be a potential orthopedic material. PMID:26047515

A comparative appraisal of two equivalence tests for multiple standardized effects.

PubMed

Shieh, Gwowen

2016-04-01

Equivalence testing is recommended as a better alternative to the traditional difference-based methods for demonstrating the comparability of two or more treatment effects. Although equivalent tests of two groups are widely discussed, the natural extensions for assessing equivalence between several groups have not been well examined. This article provides a detailed and schematic comparison of the ANOVA F and the studentized range tests for evaluating the comparability of several standardized effects. Power and sample size appraisals of the two grossly distinct approaches are conducted in terms of a constraint on the range of the standardized means when the standard deviation of the standardized means is fixed. Although neither method is uniformly more powerful, the studentized range test has a clear advantage in sample size requirements necessary to achieve a given power when the underlying effect configurations are close to the priori minimum difference for determining equivalence. For actual application of equivalence tests and advance planning of equivalence studies, both SAS and R computer codes are available as supplementary files to implement the calculations of critical values, p-values, power levels, and sample sizes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

In vitro inflammatory and cytotoxic effects of size-segregated particulate samples collected during long-range transport of wildfire smoke to Helsinki.

PubMed

Jalava, Pasi I; Salonen, Raimo O; Hälinen, Arja I; Penttinen, Piia; Pennanen, Arto S; Sillanpää, Markus; Sandell, Erik; Hillamo, Risto; Hirvonen, Maija-Riitta

2006-09-15

The impact of long-range transport (LRT) episodes of wildfire smoke on the inflammogenic and cytotoxic activity of urban air particles was investigated in the mouse RAW 264.7 macrophages. The particles were sampled in four size ranges using a modified Harvard high-volume cascade impactor, and the samples were chemically characterized for identification of different emission sources. The particulate mass concentration in the accumulation size range (PM(1-0.2)) was highly increased during two LRT episodes, but the contents of total and genotoxic polycyclic aromatic hydrocarbons (PAH) in collected particulate samples were only 10-25% of those in the seasonal average sample. The ability of coarse (PM(10-2.5)), intermodal size range (PM(2.5-1)), PM(1-0.2) and ultrafine (PM(0.2)) particles to cause cytokine production (TNFalpha, IL-6, MIP-2) reduced along with smaller particle size, but the size range had a much smaller impact on induced nitric oxide (NO) production and cytotoxicity or apoptosis. The aerosol particles collected during LRT episodes had a substantially lower activity in cytokine production than the corresponding particles of the seasonal average period, which is suggested to be due to chemical transformation of the organic fraction during aging. However, the episode events were associated with enhanced inflammogenic and cytotoxic activities per inhaled cubic meter of air due to the greatly increased particulate mass concentration in the accumulation size range, which may have public health implications.

Effect of resin infiltration on the thermal and mechanical properties of nano-sized silica-based thermal insulation.

PubMed

Lee, Jae Chun; Kim, Yun-Il; Lee, Dong-Hun; Kim, Won-Jun; Park, Sung; Lee, Dong Bok

2011-08-01

Several kinds of nano-sized silica-based thermal insulation were prepared by dry processing of mixtures consisting of fumed silica, ceramic fiber, and a SiC opacifier. Infiltration of phenolic resin solution into the insulation, followed by hot-pressing, was attempted to improve the mechanical strength of the insulation. More than 22% resin content was necessary to increase the strength of the insulation by a factor of two or more. The structural integrity of the resin-infiltrated samples could be maintained, even after resin burn-out, presumably due to reinforcement from ceramic fibers. For all temperature ranges and similar sample bulk density values, the thermal conductivities of the samples after resin burn-out were consistently higher than those of the samples obtained from the dry process. Mercury intrusion curves indicated that the median size of the nanopores formed by primary silica aggregates in the samples after resin burn-out is consistently larger than that of the sample without resin infiltration.

Mating System and Effective Population Size of the Overexploited Neotropical Tree (Myroxylon peruiferum L.f.) and Their Impact on Seedling Production.

PubMed

Silvestre, Ellida de Aguiar; Schwarcz, Kaiser Dias; Grando, Carolina; de Campos, Jaqueline Bueno; Sujii, Patricia Sanae; Tambarussi, Evandro Vagner; Macrini, Camila Menezes Trindade; Pinheiro, José Baldin; Brancalion, Pedro Henrique Santin; Zucchi, Maria Imaculada

2018-03-16

The reproductive system of a tree species has substantial impact on genetic diversity and structure within and among natural populations. Such information, should be considered when planning tree planting for forest restoration. Here, we describe the mating system and genetic diversity of an overexploited Neotropical tree, Myroxylon peruiferum L.f. (Fabaceae) sampled from a forest remnant (10 seed trees and 200 seeds) and assess whether the effective population size of nursery-grown seedlings (148 seedlings) is sufficient to prevent inbreeding depression in reintroduced populations. Genetic analyses were performed based on 8 microsatellite loci. M. peruiferum presented a mixed mating system with evidence of biparental inbreeding (t^m-t^s = 0.118). We found low levels of genetic diversity for M. peruiferum species (allelic richness: 1.40 to 4.82; expected heterozygosity: 0.29 to 0.52). Based on Ne(v) within progeny, we suggest a sample size of 47 seed trees to achieve an effective population size of 100. The effective population sizes for the nursery-grown seedlings were much smaller Ne = 27.54-34.86) than that recommended for short term Ne ≥ 100) population conservation. Therefore, to obtain a reasonable genetic representation of native tree species and prevent problems associated with inbreeding depression, seedling production for restoration purposes may require a much larger sampling effort than is currently used, a problem that is further complicated by species with a mixed mating system. This study emphasizes the need to integrate species reproductive biology into seedling production programs and connect conservation genetics with ecological restoration.

Experiments with central-limit properties of spatial samples from locally covariant random fields

USGS Publications Warehouse

Barringer, T.H.; Smith, T.E.

1992-01-01

When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

Only pick the right grains: Modelling the bias due to subjective grain-size interval selection for chronometric and fingerprinting approaches.

NASA Astrophysics Data System (ADS)

Dietze, Michael; Fuchs, Margret; Kreutzer, Sebastian

2016-04-01

Many modern approaches of radiometric dating or geochemical fingerprinting rely on sampling sedimentary deposits. A key assumption of most concepts is that the extracted grain-size fraction of the sampled sediment adequately represents the actual process to be dated or the source area to be fingerprinted. However, these assumptions are not always well constrained. Rather, they have to align with arbitrary, method-determined size intervals, such as "coarse grain" or "fine grain" with partly even different definitions. Such arbitrary intervals violate principal process-based concepts of sediment transport and can thus introduce significant bias to the analysis outcome (i.e., a deviation of the measured from the true value). We present a flexible numerical framework (numOlum) for the statistical programming language R that allows quantifying the bias due to any given analysis size interval for different types of sediment deposits. This framework is applied to synthetic samples from the realms of luminescence dating and geochemical fingerprinting, i.e. a virtual reworked loess section. We show independent validation data from artificially dosed and subsequently mixed grain-size proportions and we present a statistical approach (end-member modelling analysis, EMMA) that allows accounting for the effect of measuring the compound dosimetric history or geochemical composition of a sample. EMMA separates polymodal grain-size distributions into the underlying transport process-related distributions and their contribution to each sample. These underlying distributions can then be used to adjust grain-size preparation intervals to minimise the incorporation of "undesired" grain-size fractions.

Are Parents' Gender Schemas Related to Their Children's Gender-Related Cognitions? A Meta-Analysis.

ERIC Educational Resources Information Center

Tenenbaum, Harriet R.; Leaper, Campbell

2002-01-01

Used meta-analysis to examine relationship of parents' gender schemas and their offspring's gender-related cognitions, with samples ranging in age from infancy through early adulthood. Found a small but meaningful effect size (r=.16) indicating a positive correlation between parent gender schema and offspring measures. Effect sizes were influenced…

Researchers' choice of the number and range of levels in experiments affects the resultant variance-accounted-for effect size.

PubMed

Okada, Kensuke; Hoshino, Takahiro

2017-04-01

In psychology, the reporting of variance-accounted-for effect size indices has been recommended and widely accepted through the movement away from null hypothesis significance testing. However, most researchers have paid insufficient attention to the fact that effect sizes depend on the choice of the number of levels and their ranges in experiments. Moreover, the functional form of how and how much this choice affects the resultant effect size has not thus far been studied. We show that the relationship between the population effect size and number and range of levels is given as an explicit function under reasonable assumptions. Counterintuitively, it is found that researchers may affect the resultant effect size to be either double or half simply by suitably choosing the number of levels and their ranges. Through a simulation study, we confirm that this relation also applies to sample effect size indices in much the same way. Therefore, the variance-accounted-for effect size would be substantially affected by the basic research design such as the number of levels. Simple cross-study comparisons and a meta-analysis of variance-accounted-for effect sizes would generally be irrational unless differences in research designs are explicitly considered.

Sample size calculations for stepped wedge and cluster randomised trials: a unified approach

PubMed Central

Hemming, Karla; Taljaard, Monica

2016-01-01

Objectives To clarify and illustrate sample size calculations for the cross-sectional stepped wedge cluster randomized trial (SW-CRT) and to present a simple approach for comparing the efficiencies of competing designs within a unified framework. Study Design and Setting We summarize design effects for the SW-CRT, the parallel cluster randomized trial (CRT), and the parallel cluster randomized trial with before and after observations (CRT-BA), assuming cross-sectional samples are selected over time. We present new formulas that enable trialists to determine the required cluster size for a given number of clusters. We illustrate by example how to implement the presented design effects and give practical guidance on the design of stepped wedge studies. Results For a fixed total cluster size, the choice of study design that provides the greatest power depends on the intracluster correlation coefficient (ICC) and the cluster size. When the ICC is small, the CRT tends to be more efficient; when the ICC is large, the SW-CRT tends to be more efficient and can serve as an alternative design when the CRT is an infeasible design. Conclusion Our unified approach allows trialists to easily compare the efficiencies of three competing designs to inform the decision about the most efficient design in a given scenario. PMID:26344808

Naltrexone and Cognitive Behavioral Therapy for the Treatment of Alcohol Dependence

PubMed Central

Baros, AM; Latham, PK; Anton, RF

2008-01-01

Background Sex differences in regards to pharmacotherapy for alcoholism is a topic of concern following publications suggesting naltrexone, one of the longest approved treatments of alcoholism, is not as effective in women as in men. This study was conducted by combining two randomized placebo controlled clinical trials utilizing similar methodologies and personnel in which the data was amalgamated to evaluate sex effects in a reasonable sized sample. Methods 211 alcoholics (57 female; 154 male) were randomized to the naltrexone/CBT or placebo/CBT arm of the two clinical trials analyzed. Baseline variables were examined for differences between sex and treatment groups via analysis of variance (ANOVA) for continuous variable or chi-square test for categorical variables. All initial outcome analysis was conducted under an intent-to-treat analysis plan. Effect sizes for naltrexone over placebo were determined by Cohen’s D (d). Results The effect size of naltrexone over placebo for the following outcome variables was similar in men and women (%days abstinent (PDA) d=0.36, %heavy drinking days (PHDD) d=0.36 and total standard drinks (TSD) d=0.36). Only for men were the differences significant secondary to the larger sample size (PDA p=0.03; PHDD p=0.03; TSD p=0.04). There were a few variables (GGT at wk-12 change from baseline to week-12: men d=0.36, p=0.05; women d=0.20, p=0.45 and drinks per drinking day: men d=0.36, p=0.05; women d=0.28, p=0.34) where the naltrexone effect size for men was greater than women. In women, naltrexone tended to increase continuous abstinent days before a first drink (women d-0.46, p=0.09; men d=0.00, p=0.44). Conclusions The effect size of naltrexone over placebo appeared similar in women and men in our hands suggesting the findings of sex differences in naltrexone response might have to do with sample size and/or endpoint drinking variables rather than any inherent pharmacological or biological differences in response. PMID:18336635

Size effects on electrical properties of chemically grown zinc oxide nanoparticles

NASA Astrophysics Data System (ADS)

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.

Reading comprehension and its underlying components in second-language learners: A meta-analysis of studies comparing first- and second-language learners.

PubMed

Melby-Lervåg, Monica; Lervåg, Arne

2014-03-01

We report a systematic meta-analytic review of studies comparing reading comprehension and its underlying components (language comprehension, decoding, and phonological awareness) in first- and second-language learners. The review included 82 studies, and 576 effect sizes were calculated for reading comprehension and underlying components. Key findings were that, compared to first-language learners, second-language learners display a medium-sized deficit in reading comprehension (pooled effect size d = -0.62), a large deficit in language comprehension (pooled effect size d = -1.12), but only small differences in phonological awareness (pooled effect size d = -0.08) and decoding (pooled effect size d = -0.12). A moderator analysis showed that characteristics related to the type of reading comprehension test reliably explained the variation in the differences in reading comprehension between first- and second-language learners. For language comprehension, studies of samples from low socioeconomic backgrounds and samples where only the first language was used at home generated the largest group differences in favor of first-language learners. Test characteristics and study origin reliably contributed to the variations between the studies of language comprehension. For decoding, Canadian studies showed group differences in favor of second-language learners, whereas the opposite was the case for U.S. studies. Regarding implications, unless specific decoding problems are detected, interventions that aim to ameliorate reading comprehension problems among second-language learners should focus on language comprehension skills.

The size-reduced Eudragit® RS microparticles prepared by solvent evaporation method - monitoring the effect of selected variables on tested parameters.

PubMed

Vasileiou, Kalliopi; Vysloužil, Jakub; Pavelková, Miroslava; Vysloužil, Jan; Kubová, Kateřina

2018-01-01

Size-reduced microparticles were successfully obtained by solvent evaporation method. Different parameters were applied in each sample and their influence on microparticles was evaluated. As a model drug the insoluble ibuprofen was selected for the encapsulation process with Eudragit® RS. The obtained microparticles were inspected by optical microscopy and scanning electron microscopy. The effect of aqueous phase volume (600, 400, 200 ml) and the concentration of polyvinyl alcohol (PVA; 1.0% and 0.1%) were studied. It was evaluated how those variations and also size can affect microparticle characteristics such as encapsulation efficiency, drug loading, burst effect and microparticle morphology. It was observed that the sample prepared with 600 ml aqueous phase and 1% concentration of polyvinyl alcohol gave the most favorable results.Key words: microparticles solvent evaporation sustained drug release Eudragit RS®.

Effect on the grain size of single-mode microwave sintered NiCuZn ferrite and zinc titanate dielectric resonator ceramics.

PubMed

Sirugudu, Roopas Kiran; Vemuri, Rama Krishna Murthy; Venkatachalam, Subramanian; Gopalakrishnan, Anisha; Budaraju, Srinivasa Murty

2011-01-01

Microwave sintering of materials significantly depends on dielectric, magnetic and conductive Losses. Samples with high dielectric and magnetic loss such as ferrites could be sintered easily. But low dielectric loss material such as dielectric resonators (paraelectrics) finds difficulty in generation of heat during microwave interaction. Microwave sintering of materials of these two classes helps in understanding the variation in dielectric and magnetic characteristics with respect to the change in grain size. High-energy ball milled Ni0.6Cu0.2Zn0.2Fe1.98O4-delta and ZnTiO3 are sintered in conventional and microwave methods and characterized for respective dielectric and magnetic characteristics. The grain size variation with higher copper content is also observed with conventional and microwave sintering. The grain size in microwave sintered Ni0.6Cu0.2Zn0.2Fe1.98O4-delta is found to be much small and uniform in comparison with conventional sintered sample. However, the grain size of microwave sintered sample is almost equal to that of conventional sintered sample of Ni0.3Cu0.5Zn0.2Fe1.98O4-delta. In contrast to these high dielectric and magnetic loss ferrites, the paraelectric materials are observed to sinter in presence of microwaves. Although microwave sintered zinc titanate sample showed finer and uniform grains with respect to conventional samples, the dielectric characteristics of microwave sintered sample are found to be less than that of conventional sample. Low dielectric constant is attributed to the low density. Smaller grain size is found to be responsible for low quality factor and the presence of small percentage of TiO2 is observed to achieve the temperature stable resonant frequency.

Measurements of Regolith Simulant Thermal Conductivity Under Asteroid and Mars Surface Conditions

NASA Astrophysics Data System (ADS)

Ryan, A. J.; Christensen, P. R.

2017-12-01

Laboratory measurements have been necessary to interpret thermal data of planetary surfaces for decades. We present a novel radiometric laboratory method to determine temperature-dependent thermal conductivity of complex regolith simulants under rough to high vacuum and across a wide range of temperatures. This method relies on radiometric temperature measurements instead of contact measurements, eliminating the need to disturb the sample with thermal probes. We intend to determine the conductivity of grains that are up to 2 cm in diameter and to parameterize the effects of angularity, sorting, layering, composition, and eventually cementation. We present the experimental data and model results for a suite of samples that were selected to isolate and address regolith physical parameters that affect bulk conductivity. Spherical glass beads of various sizes were used to measure the effect of size frequency distribution. Spherical beads of polypropylene and well-rounded quartz sand have respectively lower and higher solid phase thermal conductivities than the glass beads and thus provide the opportunity to test the sensitivity of bulk conductivity to differences in solid phase conductivity. Gas pressure in our asteroid experimental chambers is held at 10^-6 torr, which is sufficient to negate gas thermal conduction in even our coarsest of samples. On Mars, the atmospheric pressure is such that the mean free path of the gas molecules is comparable to the pore size for many regolith particulates. Thus, subtle variations in pore size and/or atmospheric pressure can produce large changes in bulk regolith conductivity. For each sample measured in our martian environmental chamber, we repeat thermal measurement runs at multiple pressures to observe this behavior. Finally, we present conductivity measurements of angular basaltic simulant that is physically analogous to sand and gravel that may be present on Bennu. This simulant was used for OSIRIS-REx TAGSAM Sample Return Arm engineering tests. We measure the original size frequency distribution as well as several sorted size fractions. These results will support the efforts of the OSIRIS-REx team in selecting a site on asteroid Bennu that is safe for the spacecraft and meets grain size requirements for sampling.

Size effects on the magnetic properties of LaCoO3 nanoparticles

NASA Astrophysics Data System (ADS)

Wei, Q.; Zhang, T.; Wang, X. P.; Fang, Q. F.

2012-02-01

Magnetic properties of LaCoO3 nanoparticles prepared by a sol-gel method with average particle size (D) ranging from 20 to 500 nm are investigated. All samples exhibit obvious ferromagnetic transition. With decreasing particle size from 500 to 120 nm, the transition temperature Tc decreases slightly from 85 K, however Tc decreases dramatically when D ≤ 85 nm. Low-field magnetic moment at 10 K decreases with reduction of particle size, while the high-field magnetization exhibits a converse behavior, which is different with previous reports. The coercivity Hc decreases as the particle size is reduced. It is different with other nanosystems that no exchange bias effect is observed in nanosized LaCoO3 particles. These interesting results arise from the surface effect induced by sized effect and the structure change in LaCoO3 nanoparticles.

Monitoring landscape metrics by point sampling: accuracy in estimating Shannon's diversity and edge density.

PubMed

Ramezani, Habib; Holm, Sören; Allard, Anna; Ståhl, Göran

2010-05-01

Environmental monitoring of landscapes is of increasing interest. To quantify landscape patterns, a number of metrics are used, of which Shannon's diversity, edge length, and density are studied here. As an alternative to complete mapping, point sampling was applied to estimate the metrics for already mapped landscapes selected from the National Inventory of Landscapes in Sweden (NILS). Monte-Carlo simulation was applied to study the performance of different designs. Random and systematic samplings were applied for four sample sizes and five buffer widths. The latter feature was relevant for edge length, since length was estimated through the number of points falling in buffer areas around edges. In addition, two landscape complexities were tested by applying two classification schemes with seven or 20 land cover classes to the NILS data. As expected, the root mean square error (RMSE) of the estimators decreased with increasing sample size. The estimators of both metrics were slightly biased, but the bias of Shannon's diversity estimator was shown to decrease when sample size increased. In the edge length case, an increasing buffer width resulted in larger bias due to the increased impact of boundary conditions; this effect was shown to be independent of sample size. However, we also developed adjusted estimators that eliminate the bias of the edge length estimator. The rates of decrease of RMSE with increasing sample size and buffer width were quantified by a regression model. Finally, indicative cost-accuracy relationships were derived showing that point sampling could be a competitive alternative to complete wall-to-wall mapping.

Effects of sample size on KERNEL home range estimates

USGS Publications Warehouse

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

1999-01-01

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

A Bayesian Perspective on the Reproducibility Project: Psychology

PubMed Central

Etz, Alexander; Vandekerckhove, Joachim

2016-01-01

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors—a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis—for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable. PMID:26919473

A Bayesian Perspective on the Reproducibility Project: Psychology.

PubMed

Etz, Alexander; Vandekerckhove, Joachim

2016-01-01

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors-a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis-for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable.

Socioeconomic status, urbanicity and risk behaviors in Mexican youth: an analysis of three cross-sectional surveys

PubMed Central

2011-01-01

Background The relationship between urbanicity and adolescent health is a critical issue for which little empirical evidence has been reported. Although an association has been suggested, a dichotomous rural versus urban comparison may not succeed in identifying differences between adolescent contexts. This study aims to assess the influence of locality size on risk behaviors in a national sample of young Mexicans living in low-income households, while considering the moderating effect of socioeconomic status (SES). Methods This is a secondary analysis of three national surveys of low-income households in Mexico in different settings: rural, semi-urban and urban areas. We analyzed risk behaviors in 15-21-year-olds and their potential relation to urbanicity. The risk behaviors explored were: tobacco and alcohol consumption, sexual initiation and condom use. The adolescents' localities of residence were classified according to the number of inhabitants in each locality. We used a logistical model to identify an association between locality size and risk behaviors, including an interaction term with SES. Results The final sample included 17,974 adolescents from 704 localities in Mexico. Locality size was associated with tobacco and alcohol consumption, showing a similar effect throughout all SES levels: the larger the size of the locality, the lower the risk of consuming tobacco or alcohol compared with rural settings. The effect of locality size on sexual behavior was more complex. The odds of adolescent condom use were higher in larger localities only among adolescents in the lowest SES levels. We found no statically significant association between locality size and sexual initiation. Conclusions The results suggest that in this sample of adolescents from low-income areas in Mexico, risk behaviors are related to locality size (number of inhabitants). Furthermore, for condom use, this relation is moderated by SES. Such heterogeneity suggests the need for more detailed analyses of both the effects of urbanicity on behavior, and the responses--which are also heterogeneous--required to address this situation. PMID:22129110

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

PubMed

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.

A pilot randomized trial of two cognitive rehabilitation interventions for mild cognitive impairment: caregiver outcomes.

PubMed

Cuc, Andrea V; Locke, Dona E C; Duncan, Noah; Fields, Julie A; Snyder, Charlene Hoffman; Hanna, Sherrie; Lunde, Angela; Smith, Glenn E; Chandler, Melanie

2017-12-01

This study aims to provide effect size estimates of the impact of two cognitive rehabilitation interventions provided to patients with mild cognitive impairment: computerized brain fitness exercise and memory support system on support partners' outcomes of depression, anxiety, quality of life, and partner burden. A randomized controlled pilot trial was performed. At 6 months, the partners from both treatment groups showed stable to improved depression scores, while partners in an untreated control group showed worsening depression over 6 months. There were no statistically significant differences on anxiety, quality of life, or burden outcomes in this small pilot trial; however, effect sizes were moderate, suggesting that the sample sizes in this pilot study were not adequate to detect statistical significance. Either form of cognitive rehabilitation may help partners' mood, compared with providing no treatment. However, effect size estimates related to other partner outcomes (i.e., burden, quality of life, and anxiety) suggest that follow-up efficacy trials will need sample sizes of at least 30-100 people per group to accurately determine significance. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The Response of Simple Polymer Structures Under Dynamic Loading

NASA Astrophysics Data System (ADS)

Proud, William; Ellison, Kay; Yapp, Su; Cole, Cloe; Galimberti, Stefano; Institute of Shock Physics Team

2017-06-01

The dynamic response of polymeric materials has been widely studied with the effects of degree of crystallinity, strain rate, temperature and sample size being commonly reported. This study uses a simple PMMA structure, a right cylindrical sample, with structural features such as holes. The features are added an varied in a systematic fashion. Samples were dynamically loaded using a Split Hopkinson Pressure Bar up to failure. The resulting stress-strain curves are presented showing the change in sample response. The strain to failure is shown to increase initially with the presence of holes, while failure stress is relatively unaffected. The fracture patterns seen in the failed samples change, with tensile cracks, Hertzian cones, shear effects being dominant for different holes sizes and geometries. The sample were prepared by laser cutting and checked for residual stress before experiment. The data is used to validate predictive model predictions where material, structure and damage are included.. The Institute of Shock Physics acknowledges the support of Imperial College London and the Atomic Weapons Establishment.

Facultative adjustment of the offspring sex ratio and male attractiveness: a systematic review and meta-analysis.

PubMed

Booksmythe, Isobel; Mautz, Brian; Davis, Jacqueline; Nakagawa, Shinichi; Jennions, Michael D

2017-02-01

Females can benefit from mate choice for male traits (e.g. sexual ornaments or body condition) that reliably signal the effect that mating will have on mean offspring fitness. These male-derived benefits can be due to material and/or genetic effects. The latter include an increase in the attractiveness, hence likely mating success, of sons. Females can potentially enhance any sex-biased benefits of mating with certain males by adjusting the offspring sex ratio depending on their mate's phenotype. One hypothesis is that females should produce mainly sons when mating with more attractive or higher quality males. Here we perform a meta-analysis of the empirical literature that has accumulated to test this hypothesis. The mean effect size was small (r = 0.064-0.095; i.e. explaining <1% of variation in offspring sex ratios) but statistically significant in the predicted direction. It was, however, not robust to correction for an apparent publication bias towards significantly positive results. We also examined the strength of the relationship using different indices of male attractiveness/quality that have been invoked by researchers (ornaments, behavioural displays, female preference scores, body condition, male age, body size, and whether a male is a within-pair or extra-pair mate). Only ornamentation and body size significantly predicted the proportion of sons produced. We obtained similar results regardless of whether we ran a standard random-effects meta-analysis, or a multi-level, Bayesian model that included a correction for phylogenetic non-independence. A moderate proportion of the variance in effect sizes (51.6-56.2%) was due to variation that was not attributable to sampling error (i.e. sample size). Much of this non-sampling error variance was not attributable to phylogenetic effects or high repeatability of effect sizes among species. It was approximately equally attributable to differences (occurring for unknown reasons) in effect sizes among and within studies (25.3, 22.9% of the total variance). There were no significant effects of year of publication or two aspects of study design (experimental/observational or field/laboratory) on reported effect sizes. We discuss various practical reasons and theoretical arguments as to why small effect sizes should be expected, and why there might be relatively high variation among studies. Currently, there are no species where replicated, experimental studies show that mothers adjust the offspring sex ratio in response to a generally preferred male phenotype. Ultimately, we need more experimental studies that test directly whether females produce more sons when mated to relatively more attractive males, and that provide the requisite evidence that their sons have higher mean fitness than their daughters. © 2015 Cambridge Philosophical Society.

Calibrating the Ordovician Radiation of marine life: implications for Phanerozoic diversity trends

NASA Technical Reports Server (NTRS)

Miller, A. I.; Foote, M.

1996-01-01

It has long been suspected that trends in global marine biodiversity calibrated for the Phanerozoic may be affected by sampling problems. However, this possibility has not been evaluated definitively, and raw diversity trends are generally accepted at face value in macroevolutionary investigations. Here, we analyze a global-scale sample of fossil occurrences that allows us to determine directly the effects of sample size on the calibration of what is generally thought to be among the most significant global biodiversity increases in the history of life: the Ordovician Radiation. Utilizing a composite database that includes trilobites, brachiopods, and three classes of molluscs, we conduct rarefaction analyses to demonstrate that the diversification trajectory for the Radiation was considerably different than suggested by raw diversity time-series. Our analyses suggest that a substantial portion of the increase recognized in raw diversity depictions for the last three Ordovician epochs (the Llandeilian, Caradocian, and Ashgillian) is a consequence of increased sample size of the preserved and catalogued fossil record. We also use biometric data for a global sample of Ordovician trilobites, along with methods of measuring morphological diversity that are not biased by sample size, to show that morphological diversification in this major clade had leveled off by the Llanvirnian. The discordance between raw diversity depictions and more robust taxonomic and morphological diversity metrics suggests that sampling effects may strongly influence our perception of biodiversity trends throughout the Phanerozoic.

Modeling the transport of engineered nanoparticles in saturated porous media - an experimental setup

NASA Astrophysics Data System (ADS)

Braun, A.; Neukum, C.; Azzam, R.

2011-12-01

The accelerating production and application of engineered nanoparticles is causing concerns regarding their release and fate in the environment. For assessing the risk that is posed to drinking water resources it is important to understand the transport and retention mechanisms of engineered nanoparticles in soil and groundwater. In this study an experimental setup for analyzing the mobility of silver and titanium dioxide nanoparticles in saturated porous media is presented. Batch and column experiments with glass beads and two different soils as matrices are carried out under varied conditions to study the impact of electrolyte concentration and pore water velocities. The analysis of nanoparticles implies several challenges, such as the detection and characterization and the preparation of a well dispersed sample with defined properties, as nanoparticles tend to form agglomerates when suspended in an aqueous medium. The analytical part of the experiments is mainly undertaken with Flow Field-Flow Fractionation (FlFFF). This chromatography like technique separates a particulate sample according to size. It is coupled to a UV/Vis and a light scattering detector for analyzing concentration and size distribution of the sample. The advantage of this technique is the ability to analyze also complex environmental samples, such as the effluent of column experiments including soil components, and the gentle sample treatment. For optimization of the sample preparation and for getting a first idea of the aggregation behavior in soil solutions, in sedimentation experiments the effect of ionic strength, sample concentration and addition of a surfactant on particle or aggregate size and temporal dispersion stability was investigated. In general the samples are more stable the lower the concentration of particles is. For TiO2 nanoparticles, the addition of a surfactant yielded the most stable samples with smallest aggregate sizes. Furthermore the suspension stability is increasing with electrolyte concentration. Depending on the dispersing medium the results show that TiO2 nanoparticles tend to form aggregates between 100-200 nm in diameter while the primary particle size is given as 21 nm by the manufacturer. Aggregate sizes are increasing with time. The particle size distribution of the silver nanoparticle samples is quite uniform in each medium. The fresh samples show aggregate sizes between 40 and 45 nm while the primary particle size is 15 nm according to the manufacturer. Aggregate size is only slightly increasing with time during the sedimentation experiments. These results are used as a reference when analyzing the effluent of column experiments.

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

NASA Astrophysics Data System (ADS)

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.

Pore-scale simulations of drainage in granular materials: Finite size effects and the representative elementary volume

NASA Astrophysics Data System (ADS)

Yuan, Chao; Chareyre, Bruno; Darve, Félix

2016-09-01

A pore-scale model is introduced for two-phase flow in dense packings of polydisperse spheres. The model is developed as a component of a more general hydromechanical coupling framework based on the discrete element method, which will be elaborated in future papers and will apply to various processes of interest in soil science, in geomechanics and in oil and gas production. Here the emphasis is on the generation of a network of pores mapping the void space between spherical grains, and the definition of local criteria governing the primary drainage process. The pore space is decomposed by Regular Triangulation, from which a set of pores connected by throats are identified. A local entry capillary pressure is evaluated for each throat, based on the balance of capillary pressure and surface tension at equilibrium. The model reflects the possible entrapment of disconnected patches of the receding wetting phase. It is validated by a comparison with drainage experiments. In the last part of the paper, a series of simulations are reported to illustrate size and boundary effects, key questions when studying small samples made of spherical particles be it in simulations or experiments. Repeated tests on samples of different sizes give evolution of water content which are not only scattered but also strongly biased for small sample sizes. More than 20,000 spheres are needed to reduce the bias on saturation below 0.02. Additional statistics are generated by subsampling a large sample of 64,000 spheres. They suggest that the minimal sampling volume for evaluating saturation is one hundred times greater that the sampling volume needed for measuring porosity with the same accuracy. This requirement in terms of sample size induces a need for efficient computer codes. The method described herein has a low algorithmic complexity in order to satisfy this requirement. It will be well suited to further developments toward coupled flow-deformation problems in which evolution of the microstructure require frequent updates of the pore network.

A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Method for normalization

NASA Astrophysics Data System (ADS)

Harudin, N.; Jamaludin, K. R.; Muhtazaruddin, M. Nabil; Ramlie, F.; Muhamad, Wan Zuki Azman Wan

2018-03-01

T-Method is one of the techniques governed under Mahalanobis Taguchi System that developed specifically for multivariate data predictions. Prediction using T-Method is always possible even with very limited sample size. The user of T-Method required to clearly understanding the population data trend since this method is not considering the effect of outliers within it. Outliers may cause apparent non-normality and the entire classical methods breakdown. There exist robust parameter estimate that provide satisfactory results when the data contain outliers, as well as when the data are free of them. The robust parameter estimates of location and scale measure called Shamos Bickel (SB) and Hodges Lehman (HL) which are used as a comparable method to calculate the mean and standard deviation of classical statistic is part of it. Embedding these into T-Method normalize stage feasibly help in enhancing the accuracy of the T-Method as well as analysing the robustness of T-method itself. However, the result of higher sample size case study shows that T-method is having lowest average error percentages (3.09%) on data with extreme outliers. HL and SB is having lowest error percentages (4.67%) for data without extreme outliers with minimum error differences compared to T-Method. The error percentages prediction trend is vice versa for lower sample size case study. The result shows that with minimum sample size, which outliers always be at low risk, T-Method is much better on that, while higher sample size with extreme outliers, T-Method as well show better prediction compared to others. For the case studies conducted in this research, it shows that normalization of T-Method is showing satisfactory results and it is not feasible to adapt HL and SB or normal mean and standard deviation into it since it’s only provide minimum effect of percentages errors. Normalization using T-method is still considered having lower risk towards outlier’s effect.

Using simulation to aid trial design: Ring-vaccination trials.

PubMed

Hitchings, Matt David Thomas; Grais, Rebecca Freeman; Lipsitch, Marc

2017-03-01

The 2014-6 West African Ebola epidemic highlights the need for rigorous, rapid clinical trial methods for vaccines. A challenge for trial design is making sample size calculations based on incidence within the trial, total vaccine effect, and intracluster correlation, when these parameters are uncertain in the presence of indirect effects of vaccination. We present a stochastic, compartmental model for a ring vaccination trial. After identification of an index case, a ring of contacts is recruited and either vaccinated immediately or after 21 days. The primary outcome of the trial is total vaccine effect, counting cases only from a pre-specified window in which the immediate arm is assumed to be fully protected and the delayed arm is not protected. Simulation results are used to calculate necessary sample size and estimated vaccine effect. Under baseline assumptions about vaccine properties, monthly incidence in unvaccinated rings and trial design, a standard sample-size calculation neglecting dynamic effects estimated that 7,100 participants would be needed to achieve 80% power to detect a difference in attack rate between arms, while incorporating dynamic considerations in the model increased the estimate to 8,900. This approach replaces assumptions about parameters at the ring level with assumptions about disease dynamics and vaccine characteristics at the individual level, so within this framework we were able to describe the sensitivity of the trial power and estimated effect to various parameters. We found that both of these quantities are sensitive to properties of the vaccine, to setting-specific parameters over which investigators have little control, and to parameters that are determined by the study design. Incorporating simulation into the trial design process can improve robustness of sample size calculations. For this specific trial design, vaccine effectiveness depends on properties of the ring vaccination design and on the measurement window, as well as the epidemiologic setting.

A Bayesian sequential design using alpha spending function to control type I error.

PubMed

Zhu, Han; Yu, Qingzhao

2017-10-01

We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

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

PubMed

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.

Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials.

PubMed

Wu, Zhichao; Medeiros, Felipe A

2018-03-20

Visual field testing is an important endpoint in glaucoma clinical trials, and the testing paradigm used can have a significant impact on the sample size requirements. To investigate this, this study included 353 eyes of 247 glaucoma patients seen over a 3-year period to extract real-world visual field rates of change and variability estimates to provide sample size estimates from computer simulations. The clinical trial scenario assumed that a new treatment was added to one of two groups that were both under routine clinical care, with various treatment effects examined. Three different visual field testing paradigms were evaluated: a) evenly spaced testing, b) United Kingdom Glaucoma Treatment Study (UKGTS) follow-up scheme, which adds clustered tests at the beginning and end of follow-up in addition to evenly spaced testing, and c) clustered testing paradigm, with clusters of tests at the beginning and end of the trial period and two intermediary visits. The sample size requirements were reduced by 17-19% and 39-40% using the UKGTS and clustered testing paradigms, respectively, when compared to the evenly spaced approach. These findings highlight how the clustered testing paradigm can substantially reduce sample size requirements and improve the feasibility of future glaucoma clinical trials.

Evidence from a Large Sample on the Effects of Group Size and Decision-Making Time on Performance in a Marketing Simulation Game

ERIC Educational Resources Information Center

Treen, Emily; Atanasova, Christina; Pitt, Leyland; Johnson, Michael

2016-01-01

Marketing instructors using simulation games as a way of inducing some realism into a marketing course are faced with many dilemmas. Two important quandaries are the optimal size of groups and how much of the students' time should ideally be devoted to the game. Using evidence from a very large sample of teams playing a simulation game, the study…

Magnetic hyperthermia in water based ferrofluids: Effects of initial susceptibility and size polydispersity on heating efficiency

NASA Astrophysics Data System (ADS)

Lahiri, B. B.; Ranoo, Surojit; Muthukumaran, T.; Philip, John

2018-04-01

The effects of initial susceptibility and size polydispersity on magnetic hyperthermia efficiency in two water based ferrofluids containing phosphate and TMAOH coated superparamagnetic Fe3O4 nanoparticles were studied. Experiments were performed at a fixed frequency of 126 kHz on four different concentrations of both samples and under different external field amplitudes. It was observed that for field amplitudes beyond 45.0 kAm-1, the maximum temperature rise was in the vicinity of 42°C (hyperthermia limit) which indicated the suitability of the water based ferrofluids for hyperthermia applications. The maximum temperature rise and specific absorption rate were found to vary linearly with square of the applied field amplitudes, in accordance with theoretical predictions. It was further observed that for a fixed sample concentration, specific absorption rate was higher for the phosphate coated samples which was attributed to the higher initial static susceptibility and lower size polydispersity of phosphate coated Fe3O4.

Effect of CNT as a Nucleating Agent on Cell Morphology and Thermal Insulation Property of the Rigid Polyurethane Foams.

PubMed

Ahn, WonSool; Lee, Joon-Man

2015-11-01

The effects of MWCNT on the cell sizes, cell uniformities, thermal conductivities, bulk densities, foaming kinetics, and compressive mechanical properties of the rigid PUFs were investigated. To obtain the better uniform dispersed state of MWCNT, grease-type master batch of MWCNT/surfactant was prepared by three-roll mill. Average cell size of the PUF samples decreased from 185.1 for the neat PUF to 162.9 μm for the sample of 0.01 phr of MWCNT concentration. Cell uniformity was also enhanced showing the standard cell-size deviation of 61.7 and 35.2, respectively. While the thermal conductivity of the neat PUF was 0.0222 W/m(o)K, that of the sample with 0.01 phr of MWCNT showed 0.0204 W/m(o)K, resulting 8.2% reduction of the thermal conductivity. Bulk density of the PUF samples was observed as nearly the same values as 30.0 ± 1.0 g/cm3 regardless of MWCNT. Temperature profiles during foaming process showed that an indirect indication of the nucleation effect of MWCNT for the PUF foaming system, showing faster and higher temperature rising with time. The compressive yield stress is nearly the same as 0.030 x 10(5) Pa regardless of MWCNT.

Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared.

PubMed

Nixon, Richard M; Wonderling, David; Grieve, Richard D

2010-03-01

Cost-effectiveness analyses (CEA) alongside randomised controlled trials commonly estimate incremental net benefits (INB), with 95% confidence intervals, and compute cost-effectiveness acceptability curves and confidence ellipses. Two alternative non-parametric methods for estimating INB are to apply the central limit theorem (CLT) or to use the non-parametric bootstrap method, although it is unclear which method is preferable. This paper describes the statistical rationale underlying each of these methods and illustrates their application with a trial-based CEA. It compares the sampling uncertainty from using either technique in a Monte Carlo simulation. The experiments are repeated varying the sample size and the skewness of costs in the population. The results showed that, even when data were highly skewed, both methods accurately estimated the true standard errors (SEs) when sample sizes were moderate to large (n>50), and also gave good estimates for small data sets with low skewness. However, when sample sizes were relatively small and the data highly skewed, using the CLT rather than the bootstrap led to slightly more accurate SEs. We conclude that while in general using either method is appropriate, the CLT is easier to implement, and provides SEs that are at least as accurate as the bootstrap. (c) 2009 John Wiley & Sons, Ltd.

Family Characteristics and Achievement: Effects of Birth Order and Family Size of the Kalamazoo Brothers Sample. Discussion Papers No. 431-77.

ERIC Educational Resources Information Center

Olneck, Michael R.; Bills, David B.

Research on the effects of birth order on cognitive ability often fails to control relevant variables related to family background and does not usually investigate the effects of birth order among members of the same family. Consequently, apparently significant birth order effects may in fact be spurious. This study uses a sample of brothers…

Power analysis to detect treatment effects in longitudinal clinical trials for Alzheimer's disease.

PubMed

Huang, Zhiyue; Muniz-Terrera, Graciela; Tom, Brian D M

2017-09-01

Assessing cognitive and functional changes at the early stage of Alzheimer's disease (AD) and detecting treatment effects in clinical trials for early AD are challenging. Under the assumption that transformed versions of the Mini-Mental State Examination, the Clinical Dementia Rating Scale-Sum of Boxes, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale tests'/components' scores are from a multivariate linear mixed-effects model, we calculated the sample sizes required to detect treatment effects on the annual rates of change in these three components in clinical trials for participants with mild cognitive impairment. Our results suggest that a large number of participants would be required to detect a clinically meaningful treatment effect in a population with preclinical or prodromal Alzheimer's disease. We found that the transformed Mini-Mental State Examination is more sensitive for detecting treatment effects in early AD than the transformed Clinical Dementia Rating Scale-Sum of Boxes and Alzheimer's Disease Assessment Scale-Cognitive Subscale. The use of optimal weights to construct powerful test statistics or sensitive composite scores/endpoints can reduce the required sample sizes needed for clinical trials. Consideration of the multivariate/joint distribution of components' scores rather than the distribution of a single composite score when designing clinical trials can lead to an increase in power and reduced sample sizes for detecting treatment effects in clinical trials for early AD.

Microstructural and mechanical evolution during deformation and annealing of poly-phase marbles - constraints from laboratory experiments and field observations

NASA Astrophysics Data System (ADS)

Austin, N. J.; Evans, B.; Dresen, G. H.; Rybacki, E.

2009-12-01

Deformed rocks commonly consist of several mineral phases, each with dramatically different mechanical properties. In both naturally and experimentally deformed rocks, deformation mechanisms and, in turn, strength, are commonly investigated by analyzing microstructural elements such as crystallographic preferred orientation (CPO) and recrystallized grain size. Here, we investigated the effect of variations in the volume fraction and the geometry of rigid second phases on the strength and evolution of CPO and grain size of synthetic calcite rocks. Experiments using triaxial compression and torsional loading were conducted at 1023 K and equivalent strain rates between ~2e-6 and 1e-3 s-1. The second phases in these synthetic assemblages are rigid carbon spheres or splinters with known particle size distributions and geometries, which are chemically inert at our experimental conditions. Under hydrostatic conditions, the addition of as little as 1 vol.% carbon spheres poisons normal grain growth. Shape is also important: for an equivalent volume fraction and grain dimension, carbon splinters result in a finer calcite grain size than carbon spheres. In samples deformed at “high” strain rates, or which have “large” mean free spacing of the pinning phase, the final recrystallized grain size is well explained by competing grain growth and grain size reduction processes, where the grain-size reduction rate is determined by the rate that mechanical work is done during deformation. In these samples, the final grain size is finer than in samples heat-treated hydrostatically for equivalent durations. The addition of 1 vol.% spheres to calcite has little effect on either the strength or CPO development. Adding 10 vol.% splinters increases the strength at low strains and low strain rates, but has little effect on the strength at high strains and/or high strain rates, compared to pure samples. A CPO similar to that in pure samples is observed, although the intensity is reduced in samples containing 10 vol.% splinters. When 10 vol.% spheres are added to calcite, the strength of the aggregate is reduced, and a distinct and strong CPO develops. Viscoplastic self consistent calculations were used to model the evolution of CPO in these materials, and these suggest a variation in the activity of the various slip systems within pure samples and those containing 10 vol.% spheres. The applicability of these laboratory observations has been tested with field-based observations made in the Morcles Nappe (Swiss Helvetic Alps). In the Morcles Nappe, calcite grain size becomes progressively finer as the thrust contact is approached, and there is a concomitant increase in CPO intensity, with the strongest CPO’s in the finest-grained, quartz-rich limestones, nearest the thrust contact, which are interpreted to have been deformed to the highest strains. Thus, our laboratory results may be used to provide insight into the distribution of strain observed in natural shear zones.

The widespread misuse of effect sizes.

PubMed

Dankel, Scott J; Mouser, J Grant; Mattocks, Kevin T; Counts, Brittany R; Jessee, Matthew B; Buckner, Samuel L; Loprinzi, Paul D; Loenneke, Jeremy P

2017-05-01

Studies comparing multiple groups (i.e., experimental and control) often examine the efficacy of an intervention by calculating within group effect sizes using Cohen's d. This method is inappropriate and largely impacted by the pre-test variability as opposed to the variability in the intervention itself. Furthermore, the percentage change is often analyzed, but this is highly impacted by the baseline values and can be potentially misleading. Thus, the objective of this study was to illustrate the common misuse of the effect size and percent change measures. Here we provide a realistic sample data set comparing two resistance training groups with the same pre-test to post-test change. Statistical tests that are commonly performed within the literature were computed. Analyzing the within group effect size favors the control group, while the percent change favors the experimental group. The most appropriate way to present the data would be to plot the individual responses or, for larger samples, provide the mean change and 95% confidence intervals of the mean change. This details the magnitude and variability within the response to the intervention itself in units that are easily interpretable. This manuscript demonstrates the common misuse of the effect size and details the importance for investigators to always report raw values, even when alternative statistics are performed. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Alcohol marketing research: the need for a new agenda.

PubMed

Meier, Petra S

2011-03-01

This paper aims to contribute to a rethink of marketing research priorities to address policy makers' evidence needs in relation to alcohol marketing. Discussion paper reviewing evidence gaps identified during an appraisal of policy options to restrict alcohol marketing. Evidence requirements can be categorized as follows: (i) the size of marketing effects for the whole population and for policy-relevant population subgroups, (ii) the balance between immediate and long-term effects and the time lag, duration and cumulative build-up of effects and (iii) comparative effects of partial versus comprehensive marketing restrictions on consumption and harm. These knowledge gaps impede the appraisal and evaluation of existing and new interventions, because without understanding the size and timing of expected effects, researchers may choose inadequate time-frames, samples or sample sizes. To date, research has tended to rely on simplified models of marketing and has focused disproportionately on youth populations. The effects of cumulative exposure across multiple marketing channels, targeting of messages at certain population groups and indirect effects of advertising on consumption remain unclear. It is essential that studies into marketing effect sizes are geared towards informing policy decision-makers, anchored strongly in theory, use measures of effect that are well-justified and recognize fully the complexities of alcohol marketing efforts. © 2010 The Author, Addiction © 2010 Society for the Study of Addiction.

Can a Toy Encourage Lower Calorie Meal Bundle Selection in Children? A Field Experiment on the Reinforcing Effects of Toys on Food Choice.

PubMed

Reimann, Martin; Lane, Kristen

2017-01-01

The goal of this research was to test whether including an inexpensive nonfood item (toy) with a smaller-sized meal bundle (420 calories), but not with the regular-sized meal bundle version (580 calories), would incentivize children to choose the smaller-sized meal bundle, even among children with overweight and obesity. Logistic regression was used to evaluate the effect in a between-subjects field experiment of a toy on smaller-sized meal choice (here, a binary choice between a smaller-sized or regular-sized meal bundles). A random sample of 109 elementary school children from two schools in the Tucson, Arizona metropolitan area (55 females; Mage = 8.53 years, SDage = 2.14; MBMI = 18.30, SDBMI = 4.42) participated. Children's height and weight were measured and body-mass-index (BMI) was calculated, adjusting for age and sex. In our sample, 21 children were considered to be either overweight or obese. Logistic regression was used to evaluate the effect of a toy on smaller-sized meal choice. Results revealed that the inclusion of a toy with a smaller-sized meal, but not with the regular-sized version, predicted smaller-sized meal choice (P < .001), suggesting that children can be incentivized to choose less food when such is paired with a toy. BMI neither moderated nor nullified the effect of toy on smaller-sized meal choice (P = .125), suggesting that children with overweight and obesity can also be incentivized to choose less. This article is the first to suggest that fast-food restaurant chains may well utilize toys to motivate children to choose smaller-sized meal bundles. Our findings may be relevant for consumers, health advocates, policy makers, and marketers who would benefit from a strategy that presents healthier, but still desirable, meal bundle options.

Can a Toy Encourage Lower Calorie Meal Bundle Selection in Children? A Field Experiment on the Reinforcing Effects of Toys on Food Choice

PubMed Central

2017-01-01

The goal of this research was to test whether including an inexpensive nonfood item (toy) with a smaller-sized meal bundle (420 calories), but not with the regular-sized meal bundle version (580 calories), would incentivize children to choose the smaller-sized meal bundle, even among children with overweight and obesity. Logistic regression was used to evaluate the effect in a between-subjects field experiment of a toy on smaller-sized meal choice (here, a binary choice between a smaller-sized or regular-sized meal bundles). A random sample of 109 elementary school children from two schools in the Tucson, Arizona metropolitan area (55 females; Mage = 8.53 years, SDage = 2.14; MBMI = 18.30, SDBMI = 4.42) participated. Children’s height and weight were measured and body-mass-index (BMI) was calculated, adjusting for age and sex. In our sample, 21 children were considered to be either overweight or obese. Logistic regression was used to evaluate the effect of a toy on smaller-sized meal choice. Results revealed that the inclusion of a toy with a smaller-sized meal, but not with the regular-sized version, predicted smaller-sized meal choice (P < .001), suggesting that children can be incentivized to choose less food when such is paired with a toy. BMI neither moderated nor nullified the effect of toy on smaller-sized meal choice (P = .125), suggesting that children with overweight and obesity can also be incentivized to choose less. This article is the first to suggest that fast-food restaurant chains may well utilize toys to motivate children to choose smaller-sized meal bundles. Our findings may be relevant for consumers, health advocates, policy makers, and marketers who would benefit from a strategy that presents healthier, but still desirable, meal bundle options. PMID:28085904

Geometrical characteristics of sandstone with different sample sizes

NASA Astrophysics Data System (ADS)

Cheon, D. S.; Takahashi, M., , Dr

2017-12-01

In many rock engineering projects such as CO2 underground storage, engineering geothermal system, it is important things to understand the fluid flow behavior in the deep geological conditions. This fluid flow is generally affected by the geometrical characteristics of rock, especially porous media. Furthermore, physical properties in rock may depend on the existence of voids space in rock. Total porosity and pore size distribution can be measured by Mercury Intrusion Porosimetry and the other geometrical and spatial information of pores can be obtained through micro-focus X-ray CT. Using the micro-focus X-ray CT, we obtained the extracted void space and transparent image from the original CT voxel images of with different sample sizes like 1 mm, 2 mm, 3 mm cubes. The test samples are Berea sandstone and Otway sandstone. The former is well-known sandstone and it is used for the standard sample to compared to the result from the Otway sandstone. Otway sandstone was obtained from the CO2CRC Otway pilot site for the CO2 geosequestraion project. From the X-ray scan and ExFACT software, we get the informations including effective pore radii, coordination number, tortuosity and effective throat/pore radius ratio etc. The geometrical information analysis showed that for Berea sandstone and Otway sandstone, there is rarely differences with different sample sizes and total value of coordination number show high porosity, the tortuosity of Berea sandstone is higher than the Otway sandstone. In the future, these information will be used for the permeability of the samples.

The Consideration of Future Consequences and Health Behaviour: A Meta-Analysis.

PubMed

Murphy, Lisa; Dockray, Samantha

2018-06-14

The aim of this meta-analysis was to quantify the direction and strength of associations between the Consideration of Future Consequences (CFC) scale and intended and actual engagement in three categories of health-related behaviour: health risk, health promotive, and illness preventative/detective behaviour. A systematic literature search was conducted to identify studies that measured CFC and health behaviour. In total, sixty-four effect sizes were extracted from 53 independent samples. Effect sizes were synthesised using a random-effects model. Aggregate effect sizes for all behaviour categories were significant, albeit small in magnitude. There were no significant moderating effects of the length of CFC scale (long vs. short), population type (college students vs. non-college students), mean age, or sex proportion of study samples. CFC reliability and study quality score significantly moderated the overall association between CFC and health risk behaviour only. The magnitude of effect sizes is comparable to associations between health behaviour and other individual difference variables, such as the Big Five personality traits. The findings indicate that CFC is an important construct to consider in research on engagement in health risk behaviour in particular. Future research is needed to examine the optimal approach by which to apply the findings to behavioural interventions.

The Effect of Hypnosis on Anxiety in Patients With Cancer: A Meta-Analysis.

PubMed

Chen, Pei-Ying; Liu, Ying-Mei; Chen, Mei-Ling

2017-06-01

Anxiety is a common form of psychological distress in patients with cancer. One recognized nonpharmacological intervention to reduce anxiety for various populations is hypnotherapy or hypnosis. However, its effect in reducing anxiety in cancer patients has not been systematically evaluated. This meta-analysis was designed to synthesize the immediate and sustained effects of hypnosis on anxiety of cancer patients and to identify moderators for these hypnosis effects. Qualified studies including randomized controlled trials (RCT) and pre-post design studies were identified by searching seven electronic databases: Scopus, Medline Ovidsp, PubMed, PsycInfo-Ovid, Academic Search Premier, CINAHL Plus with FT-EBSCO, and SDOL. Effect size (Hedges' g) was computed for each study. Random-effect modeling was used to combine effect sizes across studies. All statistical analyses were conducted with Comprehensive Meta-Analysis, version 2 (Biostat, Inc., Englewood, NJ, USA). Our meta-analysis of 20 studies found that hypnosis had a significant immediate effect on anxiety in cancer patients (Hedges' g: 0.70-1.41, p < .01) and the effect was sustained (Hedges' g: 0.61-2.77, p < .01). The adjusted mean effect size (determined by Duvan and Tweedie's trim-and-fill method) was 0.46. RCTs had a significantly higher effect size than non-RCT studies. Higher mean effect sizes were also found with pediatric study samples, hematological malignancy, studies on procedure-related stressors, and with mixed-gender samples. Hypnosis delivered by a therapist was significantly more effective than self-hypnosis. Hypnosis can reduce anxiety of cancer patients, especially for pediatric cancer patients who experience procedure-related stress. We recommend therapist-delivered hypnosis should be preferred until more effective self-hypnosis strategies are developed. © 2017 Sigma Theta Tau International.

A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.

PubMed

Khondoker, Mizanur; Dobson, Richard; Skirrow, Caroline; Simmons, Andrew; Stahl, Daniel

2016-10-01

Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the major sources of bias in such comparisons. Better performance in one or a few instances does not necessarily imply so on an average or on a population level and simulation studies may be a better alternative for objectively comparing the performances of machine learning algorithms. We compare the classification performance of a number of important and widely used machine learning algorithms, namely the Random Forests (RF), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbour (kNN). Using massively parallel processing on high-performance supercomputers, we compare the generalisation errors at various combinations of levels of several factors: number of features, training sample size, biological variation, experimental variation, effect size, replication and correlation between features. For smaller number of correlated features, number of features not exceeding approximately half the sample size, LDA was found to be the method of choice in terms of average generalisation errors as well as stability (precision) of error estimates. SVM (with RBF kernel) outperforms LDA as well as RF and kNN by a clear margin as the feature set gets larger provided the sample size is not too small (at least 20). The performance of kNN also improves as the number of features grows and outplays that of LDA and RF unless the data variability is too high and/or effect sizes are too small. RF was found to outperform only kNN in some instances where the data are more variable and have smaller effect sizes, in which cases it also provide more stable error estimates than kNN and LDA. Applications to a number of real datasets supported the findings from the simulation study. © The Author(s) 2013.

Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

Normalization procedures are widely used in high-throughput genomic data analyses to remove various technological noise and variations. They are known to have profound impact to the subsequent gene differential expression analysis. Although there has been some research in evaluating different normalization procedures, few attempts have been made to systematically evaluate the gene detection performances of normalization procedures from the bias-variance trade-off point of view, especially with strong gene differentiation effects and large sample size. In this paper, we conduct a thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size. We conduct theoretical evaluation based on a random effect model, as well as simulation and biological data analyses to verify the results. Based on our findings, we provide some practical guidance for selecting a suitable normalization procedure under different scenarios. PMID:24941114

Diagnosing hyperuniformity in two-dimensional, disordered, jammed packings of soft spheres.

PubMed

Dreyfus, Remi; Xu, Ye; Still, Tim; Hough, L A; Yodh, A G; Torquato, Salvatore

2015-01-01

Hyperuniformity characterizes a state of matter for which (scaled) density fluctuations diminish towards zero at the largest length scales. However, the task of determining whether or not an image of an experimental system is hyperuniform is experimentally challenging due to finite-resolution, noise, and sample-size effects that influence characterization measurements. Here we explore these issues, employing video optical microscopy to study hyperuniformity phenomena in disordered two-dimensional jammed packings of soft spheres. Using a combination of experiment and simulation we characterize the possible adverse effects of particle polydispersity, image noise, and finite-size effects on the assignment of hyperuniformity, and we develop a methodology that permits improved diagnosis of hyperuniformity from real-space measurements. The key to this improvement is a simple packing reconstruction algorithm that incorporates particle polydispersity to minimize the free volume. In addition, simulations show that hyperuniformity in finite-sized samples can be ascertained more accurately in direct space than in reciprocal space. Finally, our experimental colloidal packings of soft polymeric spheres are shown to be effectively hyperuniform.

Diagnosing hyperuniformity in two-dimensional, disordered, jammed packings of soft spheres

NASA Astrophysics Data System (ADS)

Dreyfus, Remi; Xu, Ye; Still, Tim; Hough, L. A.; Yodh, A. G.; Torquato, Salvatore

2015-01-01

Hyperuniformity characterizes a state of matter for which (scaled) density fluctuations diminish towards zero at the largest length scales. However, the task of determining whether or not an image of an experimental system is hyperuniform is experimentally challenging due to finite-resolution, noise, and sample-size effects that influence characterization measurements. Here we explore these issues, employing video optical microscopy to study hyperuniformity phenomena in disordered two-dimensional jammed packings of soft spheres. Using a combination of experiment and simulation we characterize the possible adverse effects of particle polydispersity, image noise, and finite-size effects on the assignment of hyperuniformity, and we develop a methodology that permits improved diagnosis of hyperuniformity from real-space measurements. The key to this improvement is a simple packing reconstruction algorithm that incorporates particle polydispersity to minimize the free volume. In addition, simulations show that hyperuniformity in finite-sized samples can be ascertained more accurately in direct space than in reciprocal space. Finally, our experimental colloidal packings of soft polymeric spheres are shown to be effectively hyperuniform.

MUDMASTER: A Program for Calculating Crystalline Size Distributions and Strain from the Shapes of X-Ray Diffraction Peaks

USGS Publications Warehouse

Eberl, D.D.; Drits, V.A.; Środoń, Jan; Nüesch, R.

1996-01-01

Particle size may strongly influence the physical and chemical properties of a substance (e.g. its rheology, surface area, cation exchange capacity, solubility, etc.), and its measurement in rocks may yield geological information about ancient environments (sediment provenance, degree of metamorphism, degree of weathering, current directions, distance to shore, etc.). Therefore mineralogists, geologists, chemists, soil scientists, and others who deal with clay-size material would like to have a convenient method for measuring particle size distributions. Nano-size crystals generally are too fine to be measured by light microscopy. Laser scattering methods give only average particle sizes; therefore particle size can not be measured in a particular crystallographic direction. Also, the particles measured by laser techniques may be composed of several different minerals, and may be agglomerations of individual crystals. Measurement by electron and atomic force microscopy is tedious, expensive, and time consuming. It is difficult to measure more than a few hundred particles per sample by these methods. This many measurements, often taking several days of intensive effort, may yield an accurate mean size for a sample, but may be too few to determine an accurate distribution of sizes. Measurement of size distributions by X-ray diffraction (XRD) solves these shortcomings. An X-ray scan of a sample occurs automatically, taking a few minutes to a few hours. The resulting XRD peaks average diffraction effects from billions of individual nano-size crystals. The size that is measured by XRD may be related to the size of the individual crystals of the mineral in the sample, rather than to the size of particles formed from the agglomeration of these crystals. Therefore one can determine the size of a particular mineral in a mixture of minerals, and the sizes in a particular crystallographic direction of that mineral.

The relation between statistical power and inference in fMRI

PubMed Central

Wager, Tor D.; Yarkoni, Tal

2017-01-01

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches. PMID:29155843

Cognitive Behavioral Therapy: A Meta-Analysis of Race and Substance Use Outcomes

PubMed Central

Windsor, Liliane Cambraia; Jemal, Alexis; Alessi, Edward

2015-01-01

Cognitive behavioral therapy (CBT) is an effective intervention for reducing substance use. However, because CBT trials have included predominantly White samples caution must be used when generalizing these effects to Blacks and Hispanics. This meta-analysis compared the impact of CBT in reducing substance use between studies with a predominantly non-Hispanic White sample (hereafter NHW studies) and studies with a predominantly Black and/or Hispanic sample (hereafter BH studies). From 322 manuscripts identified in the literature, 17 met criteria for inclusion. Effect sizes between CBT and comparison group at posttest had similar effects on substance abuse across NHW and BH studies. However, when comparing pre-posttest effect sizes from groups receiving CBT between NHW and BH studies, CBT’s impact was significantly stronger in NHW studies. T-test comparisons indicated reduced retention/engagement in BH studies, albeit failing to reach statistical significance. Results highlight the need for further research testing CBT’s impact on substance use among Blacks and Hispanics. PMID:25285527

Water quality monitoring: A comparative case study of municipal and Curtin Sarawak's lake samples

NASA Astrophysics Data System (ADS)

Anand Kumar, A.; Jaison, J.; Prabakaran, K.; Nagarajan, R.; Chan, Y. S.

2016-03-01

In this study, particle size distribution and zeta potential of the suspended particles in municipal water and lake surface water of Curtin Sarawak's lake were compared and the samples were analysed using dynamic light scattering method. High concentration of suspended particles affects the water quality as well as suppresses the aquatic photosynthetic systems. A new approach has been carried out in the current work to determine the particle size distribution and zeta potential of the suspended particles present in the water samples. The results for the lake samples showed that the particle size ranges from 180nm to 1345nm and the zeta potential values ranges from -8.58 mV to -26.1 mV. High zeta potential value was observed in the surface water samples of Curtin Sarawak's lake compared to the municipal water. The zeta potential values represent that the suspended particles are stable and chances of agglomeration is lower in lake water samples. Moreover, the effects of physico-chemical parameters on zeta potential of the water samples were also discussed.

Do adults show a curse of knowledge in false-belief reasoning? A robust estimate of the true effect size.

PubMed

Ryskin, Rachel A; Brown-Schmidt, Sarah

2014-01-01

Seven experiments use large sample sizes to robustly estimate the effect size of a previous finding that adults are more likely to commit egocentric errors in a false-belief task when the egocentric response is plausible in light of their prior knowledge. We estimate the true effect size to be less than half of that reported in the original findings. Even though we found effects in the same direction as the original, they were substantively smaller; the original study would have had less than 33% power to detect an effect of this magnitude. The influence of plausibility on the curse of knowledge in adults appears to be small enough that its impact on real-life perspective-taking may need to be reevaluated.

Tungsten Carbide Grain Size Computation for WC-Co Dissimilar Welds

NASA Astrophysics Data System (ADS)

Zhou, Dongran; Cui, Haichao; Xu, Peiquan; Lu, Fenggui

2016-06-01

A "two-step" image processing method based on electron backscatter diffraction in scanning electron microscopy was used to compute the tungsten carbide (WC) grain size distribution for tungsten inert gas (TIG) welds and laser welds. Twenty-four images were collected on randomly set fields per sample located at the top, middle, and bottom of a cross-sectional micrograph. Each field contained 500 to 1500 WC grains. The images were recognized through clustering-based image segmentation and WC grain growth recognition. According to the WC grain size computation and experiments, a simple WC-WC interaction model was developed to explain the WC dissolution, grain growth, and aggregation in welded joints. The WC-WC interaction and blunt corners were characterized using scanning and transmission electron microscopy. The WC grain size distribution and the effects of heat input E on grain size distribution for the laser samples were discussed. The results indicate that (1) the grain size distribution follows a Gaussian distribution. Grain sizes at the top of the weld were larger than those near the middle and weld root because of power attenuation. (2) Significant WC grain growth occurred during welding as observed in the as-welded micrographs. The average grain size was 11.47 μm in the TIG samples, which was much larger than that in base metal 1 (BM1 2.13 μm). The grain size distribution curves for the TIG samples revealed a broad particle size distribution without fine grains. The average grain size (1.59 μm) in laser samples was larger than that in base metal 2 (BM2 1.01 μm). (3) WC-WC interaction exhibited complex plane, edge, and blunt corner characteristics during grain growth. A WC ( { 1 {bar{{1}}}00} ) to WC ( {0 1 1 {bar{{0}}}} ) edge disappeared and became a blunt plane WC ( { 10 1 {bar{{0}}}} ) , several grains with two- or three-sided planes and edges disappeared into a multi-edge, and a WC-WC merged.

A pretreatment method for grain size analysis of red mudstones

NASA Astrophysics Data System (ADS)

Jiang, Zaixing; Liu, Li'an

2011-11-01

Traditional sediment disaggregation methods work well for loose mud sediments, but not for tightly cemented mudstones by ferric oxide minerals. In this paper, a new pretreatment method for analyzing the grain size of red mudstones is presented. The experimental samples are Eocene red mudstones from the Dongying Depression, Bohai Bay Basin. The red mudstones are composed mainly of clay minerals, clastic sediments and ferric oxides that make the mudstones red and tightly compacted. The procedure of the method is as follows. Firstly, samples of the red mudstones were crushed into fragments with a diameter of 0.6-0.8 mm in size; secondly, the CBD (citrate-bicarbonate-dithionite) treatment was used to remove ferric oxides so that the cementation of intra-aggregates and inter-aggregates became weakened, and then 5% dilute hydrochloric acid was added to further remove the cements; thirdly, the fragments were further ground with a rubber pestle; lastly, an ultrasonicator was used to disaggregate the samples. After the treatment, the samples could then be used for grain size analysis or for other geological analyses of sedimentary grains. Compared with other pretreatment methods for size analysis of mudstones, this proposed method is more effective and has higher repeatability.

A time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes with applications in substance abuse research.

PubMed

Yang, Songshan; Cranford, James A; Jester, Jennifer M; Li, Runze; Zucker, Robert A; Buu, Anne

2017-02-28

This study proposes a time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes. The motivating example demonstrates that this zero-inflated Poisson model allows investigators to study group differences in different aspects of substance use (e.g., the probability of abstinence and the quantity of alcohol use) simultaneously. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size increases; the accuracy under equal group sizes is only higher when the sample size is small (100). In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all settings. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size is larger. Moreover, the hypothesis test for the group difference in the zero component tends to be less powerful than the test for the group difference in the Poisson component. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

EPR investigation of UV light effect on calcium carbonate powders with different grain sizes.

PubMed

Kabacińska, Zuzanna; Krzyminiewski, Ryszard; Dobosz, Bernadeta

2014-06-01

This study is based on investigation of calcium carbonate powders with different grain sizes exposed to UV light. Calcium carbonate is widely used in many branches of industry, e.g. as a filler for polymer materials; therefore, knowing its properties, among them also its reaction to UV light, is essential. Samples of powdered calcium carbonate with average grain sizes of 69 and 300 nm and 2.1, 6, 16, 25 µm were used in this investigation. Measurements were performed at room temperature using EPR X-band spectrometer, and they have shown the additional signals induced by the light from Hg lamp. The effect of annealing of the micro-grain samples was also studied. The spectra of four micro-grain samples after irradiation are similar, but there are differences between them and the other two powders, which could be related to the different sizes of their grains. Further studies based on these preliminary results may prove useful in research of photodegradation of CaCO3-filled materials, as well as helpful in increasing the accuracy of dating of archaeological and geological objects. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Ethnicity and Body Dissatisfaction among Women in the United States: A Meta-Analysis

ERIC Educational Resources Information Center

Grabe, Shelly; Hyde, Janet Shibley

2005-01-01

The prevailing view in popular culture and the psychological literature is that White women have greater body dissatisfaction than women of color. In this meta-analysis, 6 main effect sizes were obtained for differences among Asian American, Black, Hispanic, and White women with a sample of 98 studies, yielding 222 effect sizes. The average d for…

Behavioral and Emotional Problems Reported by Parents of Children Ages 6 to 16 in 31 Societies

ERIC Educational Resources Information Center

Rescorla, Leslie; Achenbach, Thomas; Ivanova, Masha Y.; Dumenci, Levent; Almqvist, Fredrik; Bilenberg, Niels; Bird, Hector; Chen, Wei; Dobrean, Anca; Dopfner, Manfred; Erol, Nese; Fombonne, Eric; Fonseca, Antonio; Frigerio, Alessandra; Grietens, Hans; Hannesdottir, Helga; Kanbayashi, Yasuko; Lambert, Michael; Larsson, Bo; Leung, Patrick; Liu, Xianchen; Minaei, Asghar; Mulatu, Mesfin S.; Novik, Torunn S.; Oh, Kyung-Ja; Roussos, Alexandra; Sawyer, Michael; Simsek, Zeynep; Steinhausen, Hans-Christoph; Weintraub, Sheila; Weisz, John; Metzke, Christa Winkler; Wolanczyk, Tomasz; Yang, Hao-Jan; Zilber, Nelly; Zukauskiene, Rita; Verhulst, Frank

2007-01-01

This study compared parents' ratings of behavioral and emotional problems on the "Child Behavior Checklist" (Achenbach, 1991; Achenbach & Rescorla, 2001) for general population samples of children ages 6 to 16 from 31 societies (N = 55,508). Effect sizes for society ranged from 0.03 to 0.14. Effect sizes for gender were less than or…

Effective Ice Particle Densities for Cold Anvil Cirrus

NASA Technical Reports Server (NTRS)

Heymsfield, Andrew J.; Schmitt, Carl G.; Bansemer, Aaron; Baumgardner, Darrel; Weinstock, Elliot M.; Smith, Jessica

2002-01-01

This study derives effective ice particle densities from data collected from the NASA WB-57F aircraft near the tops of anvils during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) in southern Florida in July 2002. The effective density, defined as the ice particle mass divided by the volume of an equivalent diameter liquid sphere, is obtained for particle populations and single sizes containing mixed particle habits using measurements of condensed water content and particle size distributions. The mean effective densities for populations decrease with increasing slopes of the gamma size distributions fitted to the size distributions. The population-mean densities range from near 0.91 g/cu m to 0.15 g/cu m. Effective densities for single sizes obey a power-law with an exponent of about -0.55, somewhat less steep than found from earlier studies. Our interpretations apply to samples where particle sizes are generally below 200-300 microns in maximum dimension because of probe limitations.

Effect of capping and particle size on Raman laser-induced degradation of {gamma}-Fe{sub 2}O{sub 3} nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varadwaj, K.S.K.; Panigrahi, M.K.; Ghose, J.

2004-11-01

Diol capped {gamma}-Fe{sub 2}O{sub 3} nanoparticles are prepared from ferric nitrate by refluxing in 1,4-butanediol (9.5nm) and 1,5-pentanediol (15nm) and uncapped particles are prepared by refluxing in 1,2-propanediol followed by sintering the alkoxide formed. X-ray diffraction (XRD) shows that all the samples have the spinel phase. Raman spectroscopy shows that the samples prepared in 1,4-butanediol and 1,5-pentanediol and 1,2-propanediol (sintered at 573 and 673K) are {gamma}-Fe{sub 2}O{sub 3} and the 773K-sintered sample is Fe{sub 3}O{sub 4}. Raman laser studies carried out at various laser powers show that all the samples undergo laser-induced degradation to {alpha}-Fe{sub 2}O{sub 3} at higher lasermore » power. The capped samples are however, found more stable to degradation than the uncapped samples. The stability of {gamma}-Fe{sub 2}O{sub 3} sample with large particle size (15.4nm) is more than the sample with small particle size (10.2nm). Fe{sub 3}O{sub 4} having a particle size of 48nm is however less stable than the smaller {gamma}-Fe{sub 2}O{sub 3} nanoparticles.« less

A comparative study of the physical properties of Cu-Zn ferrites annealed under different atmospheres and temperatures: Magnetic enhancement of Cu0.5Zn0.5Fe2O4 nanoparticles by a reducing atmosphere

NASA Astrophysics Data System (ADS)

Gholizadeh, Ahmad

2018-04-01

In the present work, the influence of different sintering atmospheres and temperatures on physical properties of the Cu0.5Zn0.5Fe2O4 nanoparticles including the redistribution of Zn2+ and Fe3+ ions, the oxidation of Fe atoms in the lattice, crystallite sizes, IR bands, saturation magnetization and magnetic core sizes have been investigated. The fitting of XRD patterns by using Fullprof program and also FT-IR measurement show the formation of a cubic structure with no presence of impurity phase for all the samples. The unit cell parameter of the samples sintered at the air- and inert-ambient atmospheres trend to decrease with sintering temperature, but for the samples sintered under carbon monoxide-ambient atmosphere increase. The magnetization curves versus the applied magnetic field, indicate different behaviour for the samples sintered at 700 °C with the respect to the samples sintered at 300 °C. Also, the saturation magnetization increases with the sintering temperature and reach a maximum 61.68 emu/g in the sample sintered under reducing atmosphere at 600 °C. The magnetic particle size distributions of samples have been calculated by fitting the M-H curves with the size distributed Langevin function. The results obtained from the XRD and FTIR measurements suggest that the magnetic core size has the dominant effect in variation of the saturation magnetization of the samples.

The Effects of Maternal Social Phobia on Mother-Infant Interactions and Infant Social Responsiveness

ERIC Educational Resources Information Center

Murray, Lynne; Cooper, Peter; Creswell, Cathy; Schofield, Elizabeth; Sack, Caroline

2007-01-01

Background: Social phobia aggregates in families. The genetic contribution to intergenerational transmission is modest, and parenting is considered important. Research on the effects of social phobia on parenting has been subject to problems of small sample size, heterogeneity of samples and lack of specificity of observational frameworks. We…

The effectiveness of increased apical enlargement in reducing intracanal bacteria.

PubMed

Card, Steven J; Sigurdsson, Asgeir; Orstavik, Dag; Trope, Martin

2002-11-01

It has been suggested that the apical portion of a root canal is not adequately disinfected by typical instrumentation regimens. The purpose of this study was to determine whether instrumentation to sizes larger than typically used would more effectively remove culturable bacteria from the canal. Forty patients with clinical and radiographic evidence of apical periodontitis were recruited from the endodontic clinic. Mandibular cuspids (n = 2), bicuspids (n = 11), and molars (mesial roots) (n = 27) were selected for the study. Bacterial sampling was performed upon access and after each of two consecutive instrumentations. The first instrumentation utilized 1% NaOCI and 0.04 taper ProFile rotary files. The cuspid and bicuspid canals were instrumented to a #8 size and the molar canals to a #7 size. The second instrumentation utilized LightSpeed files and 1% NaOCl irrigation for further enlargement of the apical third. Typically, molars were instrumented to size 60 and cuspid/bicuspid canals to size 80. Our findings show that 100% of the cuspid/bicuspid canals and 81.5% of the molar canals were rendered bacteria-free after the first instrumentation sizes. The molar results improved to 89% after the second instrumentation. Of the (59.3%) molar mesial canals without a clinically detectable communication, 93% were rendered bacteria-free with the first instrumentation. Using a Wilcoxon rank sum test, statistically significant differences (p < 0.0001) were found between the initial sample and the samples after the first and second instrumentations. The differences between the samples that followed the two instrumentation regimens were not significant (p = 0.0617). It is concluded that simple root canal systems (without multiple canal communications) may be rendered bacteria-free when preparation of this type is utilized.

Family Characteristics and Elementary School Achievement in an Urban Ghetto

ERIC Educational Resources Information Center

Solomon, Daniel; And Others

1972-01-01

The relationships of sex, father absence, family size, and birth order to factor scores representing general academic achievement'' were investigated in a sample of urban black ghetto fifth-grade children. Significant main effects were found for sex and family size. (Author)

Measuring the specific surface area of natural and manmade glasses: effects of formation process, morphology, and particle size

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papelis, Charalambos; Um, Wooyong; Russel, Charles E.

2003-03-28

The specific surface area of natural and manmade solid materials is a key parameter controlling important interfacial processes in natural environments and engineered systems, including dissolution reactions and sorption processes at solid-fluid interfaces. To improve our ability to quantify the release of trace elements trapped in natural glasses, the release of hazardous compounds trapped in manmade glasses, or the release of radionuclides from nuclear melt glass, we measured the specific surface area of natural and manmade glasses as a function of particle size, morphology, and composition. Volcanic ash, volcanic tuff, tektites, obsidian glass, and in situ vitrified rock were analyzed.more » Specific surface area estimates were obtained using krypton as gas adsorbent and the BET model. The range of surface areas measured exceeded three orders of magnitude. A tektite sample had the highest surface area (1.65 m2/g), while one of the samples of in situ vitrified rock had the lowest surf ace area (0.0016 m2/g). The specific surface area of the samples was a function of particle size, decreasing with increasing particle size. Different types of materials, however, showed variable dependence on particle size, and could be assigned to one of three distinct groups: (1) samples with low surface area dependence on particle size and surface areas approximately two orders of magnitude higher than the surface area of smooth spheres of equivalent size. The specific surface area of these materials was attributed mostly to internal porosity and surface roughness. (2) samples that showed a trend of decreasing surface area dependence on particle size as the particle size increased. The minimum specific surface area of these materials was between 0.1 and 0.01 m2/g and was also attributed to internal porosity and surface roughness. (3) samples whose surface area showed a monotonic decrease with increasing particle size, never reaching an ultimate surface area limit within the particle size range examined. The surface area results were consistent with particle morphology, examined by scanning electron microscopy, and have significant implications for the release of radionuclides and toxic metals in the environment.« less

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests.

PubMed

Tan, Lingzhao; Fan, Chunyu; Zhang, Chunyu; von Gadow, Klaus; Fan, Xiuhua

2017-12-01

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem-mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best-explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad-leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

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

PubMed

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.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

PubMed

Alegana, Victor A; Wright, Jim; Bosco, Claudio; Okiro, Emelda A; Atkinson, Peter M; Snow, Robert W; Tatem, Andrew J; Noor, Abdisalan M

2017-11-21

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

The effect of doped zinc on the structural properties of nano-crystalline (Se0.8Te0.2)100-xZnx

NASA Astrophysics Data System (ADS)

Kumar, Arun; Singh, Harkawal; Gill, P. S.; Goyal, Navdeep

2016-05-01

The effect of metallic zinc (Zn) on the structural properties of (Se0.8Te0.2)1-XZnX (x=0, 2, 6, 8, 10) samples analyzed by X-ray Diffraction (XRD). The presence of sharp peaks in XRD patterns confirmed the crystalline nature of the samples and is indexed in orthorhombic crystal structure. XRD studies predicts that the average particle size of all the samples are about 46.29 nm, which is less than 100 nm and hence have strong tendency of agglomeration. Williamson-Hall plot method was used to evaluate the lattice strain. The dislocation density and no. of unit cells of the samples were calculated which show the inverse relation with each other. Morphology index derived from FWHM of XRD data explains the direct relationship with the particle size.

Big assumptions for small samples in crop insurance

Treesearch

Ashley Elaine Hungerford; Barry Goodwin

2014-01-01

The purpose of this paper is to investigate the effects of crop insurance premiums being determined by small samples of yields that are spatially correlated. If spatial autocorrelation and small sample size are not properly accounted for in premium ratings, the premium rates may inaccurately reflect the risk of a loss.

In vitro inflammatory and cytotoxic effects of size-segregated particulate samples collected during long-range transport of wildfire smoke to Helsinki

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jalava, Pasi I.; Salonen, Raimo O.; Haelinen, Arja I.

2006-09-15

The impact of long-range transport (LRT) episodes of wildfire smoke on the inflammogenic and cytotoxic activity of urban air particles was investigated in the mouse RAW 264.7 macrophages. The particles were sampled in four size ranges using a modified Harvard high-volume cascade impactor, and the samples were chemically characterized for identification of different emission sources. The particulate mass concentration in the accumulation size range (PM{sub 1-0.2}) was highly increased during two LRT episodes, but the contents of total and genotoxic polycyclic aromatic hydrocarbons (PAH) in collected particulate samples were only 10-25% of those in the seasonal average sample. The abilitymore » of coarse (PM{sub 10-2.5}), intermodal size range (PM{sub 2.5-1}), PM{sub 1-0.2} and ultrafine (PM{sub 0.2}) particles to cause cytokine production (TNF{alpha}, IL-6, MIP-2) reduced along with smaller particle size, but the size range had a much smaller impact on induced nitric oxide (NO) production and cytotoxicity or apoptosis. The aerosol particles collected during LRT episodes had a substantially lower activity in cytokine production than the corresponding particles of the seasonal average period, which is suggested to be due to chemical transformation of the organic fraction during aging. However, the episode events were associated with enhanced inflammogenic and cytotoxic activities per inhaled cubic meter of air due to the greatly increased particulate mass concentration in the accumulation size range, which may have public health implications.« less

Grain size effect on the electrical and magneto-transport properties of nanosized Pr0.67Sr0.33MnO3

NASA Astrophysics Data System (ADS)

Ng, S. W.; Lim, K. P.; Halim, S. A.; Jumiah, H.

2018-06-01

In this study, nanosized of Pr0.67Sr0.33MnO3 prepared via sol-gel method followed by heat treatment at 600-1000 °C in intervals of 100 °C were synthesized. The structure, surface morphology, electrical, magneto-transport and magnetic properties of the samples were investigated. Rietveld refinements of X-ray diffraction patterns confirm that single phase orthorhombic crystal structure with the space group of Pnma (62) is formed at 600 °C. A strong dependence of surface morphology, electrical and magneto-transport properties on grain size have been observed in this manganites system. Both grain size and crystallite size are increases with the sintering temperature due to the congregation effect. Upon increasing grain size, the paramagnetic-ferromagnetic transition temperature increases from 278 K to 295 K. The resistivity drops and the metal-insulator transition temperature shifted from 184 K to 248 K with increases of grain size due to the grain growth and reduction of grain boundary. Below metal-insulator transition temperature, the samples fit well to the combination of resistivity due to grain or domain boundaries, electron-electron scattering process and electron-phonon interaction. The resistivity data above the metal-insulator transition temperature is well described using small polaron hopping and variable range hopping models. It is found that the negative magnetoresistance also increases with larger grain size where the highest %MR of - 26% can be observed for sample sintered at 1000 °C (245 nm).

Elastic moduli in nano-size samples of amorphous solids: System size dependence

NASA Astrophysics Data System (ADS)

Cohen, Yossi; Procaccia, Itamar

2012-08-01

This letter is motivated by some recent experiments on pan-cake-shaped nano-samples of metallic glass that indicate a decline in the measured shear modulus upon decreasing the sample radius. Similar measurements on crystalline samples of the same dimensions showed a much more modest change. In this letter we offer a theory of this phenomenon; we argue that such results are generically expected for any amorphous solid, with the main effect being related to the increased contribution of surfaces with respect to the bulk when the samples get smaller. We employ exact relations between the shear modulus and the eigenvalues of the system's Hessian matrix to explore the role of surface modes in affecting the elastic moduli.

Drying regimes in homogeneous porous media from macro- to nanoscale

NASA Astrophysics Data System (ADS)

Thiery, J.; Rodts, S.; Weitz, D. A.; Coussot, P.

2017-07-01

Magnetic resonance imaging visualization down to nanometric liquid films in model porous media with pore sizes from micro- to nanometers enables one to fully characterize the physical mechanisms of drying. For pore size larger than a few tens of nanometers, we identify an initial constant drying rate period, probing homogeneous desaturation, followed by a falling drying rate period. This second period is associated with the development of a gradient in saturation underneath the sample free surface that initiates the inward recession of the contact line. During this latter stage, the drying rate varies in accordance with vapor diffusion through the dry porous region, possibly affected by the Knudsen effect for small pore size. However, we show that for sufficiently small pore size and/or saturation the drying rate is increasingly reduced by the Kelvin effect. Subsequently, we demonstrate that this effect governs the kinetics of evaporation in nanopores as a homogeneous desaturation occurs. Eventually, under our experimental conditions, we show that the saturation unceasingly decreases in a homogeneous manner throughout the wet regions of the medium regardless of pore size or drying regime considered. This finding suggests the existence of continuous liquid flow towards the interface of higher evaporation, down to very low saturation or very small pore size. Paradoxically, even if this net flow is unidirectional and capillary driven, it corresponds to a series of diffused local capillary equilibrations over the full height of the sample, which might explain that a simple Darcy's law model does not predict the effect of scaling of the net flow rate on the pore size observed in our tests.

An integrated approach to piezoactuator positioning in high-speed atomic force microscope imaging

NASA Astrophysics Data System (ADS)

Yan, Yan; Wu, Ying; Zou, Qingze; Su, Chanmin

2008-07-01

In this paper, an integrated approach to achieve high-speed atomic force microscope (AFM) imaging of large-size samples is proposed, which combines the enhanced inversion-based iterative control technique to drive the piezotube actuator control for lateral x-y axis positioning with the use of a dual-stage piezoactuator for vertical z-axis positioning. High-speed, large-size AFM imaging is challenging because in high-speed lateral scanning of the AFM imaging at large size, large positioning error of the AFM probe relative to the sample can be generated due to the adverse effects—the nonlinear hysteresis and the vibrational dynamics of the piezotube actuator. In addition, vertical precision positioning of the AFM probe is even more challenging (than the lateral scanning) because the desired trajectory (i.e., the sample topography profile) is unknown in general, and the probe positioning is also effected by and sensitive to the probe-sample interaction. The main contribution of this article is the development of an integrated approach that combines advanced control algorithm with an advanced hardware platform. The proposed approach is demonstrated in experiments by imaging a large-size (50μm ) calibration sample at high-speed (50Hz scan rate).

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

USGS Publications Warehouse

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

Effect of microstructure on the thermoelectric performance of La{sub 1−x}Sr{sub x}CoO{sub 3}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Viskadourakis, Z.; Department of Mechanical and Manufacturing Engineering, University of Cypruss, 75 Kallipoleos Avenue, P.O. Box 20537, 1678 Nicosia; Athanasopoulos, G.I.

We present a case where the microstructure has a profound effect on the thermoelectric properties of oxide compounds. Specifically, we have investigated the effect of different sintering treatments on La{sub 1−x}Sr{sub x}CoO{sub 3} samples synthesized using the Pechini method. We found that the samples, which are dense and consist of inhomogeneously-mixed grains of different size, exhibit both higher Seebeck coefficient and thermoelectric figure of merit than the samples, which are porous and consist of grains with almost identical size. The enhancement of Seebeck coefficient in the dense samples is attributed to the so-called “energy-filtering” mechanism that is related to themore » energy barrier of the grain boundary. On the other hand, the thermal conductivity for the porous compounds is significantly reduced in comparison to the dense compounds. It is suggested that a fine-manipulation of grain size ratio combined with a fine-tuning of porosity could considerably enhance the thermoelectric performance of oxides. - Graphical abstract: The enhancement of the dimensionless thermoelectric figure ZT of merit is presented for two equally Sr-doped LaCoO3 compounds, possessing different microstructure, indicating the effect of the latter to the thermoelectric performance of the La{sub 1−x}Sr{sub x}CoO{sub 3} solid solution. - Highlights: • Electrical and thermal transport properties are affected by the microstructure in La{sub 1−x}Sr{sub x}CoO{sub 3} polycrystalline materials. • Coarse/fine grain size distribution enhances the Seebeck coefficient. • Porosity reduces the thermal conductivity in La{sub 1−x}Sr{sub x}CoO{sub 3} polycrystalline samples. • The combination of large/small grain ratio distribution with the high porosity may result to the enhancement of the thermoelectric performance of the material.« less

Multipinhole SPECT helical scan parameters and imaging volume

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Rutao, E-mail: rutaoyao@buffalo.edu; Deng, Xiao; Wei, Qingyang

Purpose: The authors developed SPECT imaging capability on an animal PET scanner using a multiple-pinhole collimator and step-and-shoot helical data acquisition protocols. The objective of this work was to determine the preferred helical scan parameters, i.e., the angular and axial step sizes, and the imaging volume, that provide optimal imaging performance. Methods: The authors studied nine helical scan protocols formed by permuting three rotational and three axial step sizes. These step sizes were chosen around the reference values analytically calculated from the estimated spatial resolution of the SPECT system and the Nyquist sampling theorem. The nine helical protocols were evaluatedmore » by two figures-of-merit: the sampling completeness percentage (SCP) and the root-mean-square (RMS) resolution. SCP was an analytically calculated numerical index based on projection sampling. RMS resolution was derived from the reconstructed images of a sphere-grid phantom. Results: The RMS resolution results show that (1) the start and end pinhole planes of the helical scheme determine the axial extent of the effective field of view (EFOV), and (2) the diameter of the transverse EFOV is adequately calculated from the geometry of the pinhole opening, since the peripheral region beyond EFOV would introduce projection multiplexing and consequent effects. The RMS resolution results of the nine helical scan schemes show optimal resolution is achieved when the axial step size is the half, and the angular step size is about twice the corresponding values derived from the Nyquist theorem. The SCP results agree in general with that of RMS resolution but are less critical in assessing the effects of helical parameters and EFOV. Conclusions: The authors quantitatively validated the effective FOV of multiple pinhole helical scan protocols and proposed a simple method to calculate optimal helical scan parameters.« less

Physical capital and the embodied nature of income inequality: gender differences in the effect of body size on workers' incomes in Canada.

PubMed

Perks, Thomas

2012-02-01

This study assesses the effects of body size--measured using the body mass index--on the income attainment of female and male workers in Canada. Using data from a national representative sample of Canadians, multivariate analyses show that, for female workers, the body size-income relationship is negative. However, for male workers, the body size-income relationship is positive and nonlinear. Using Bourdieu's conceptualization of physical capital, and Shilling's extension of it, it is argued that these results are suggestive of the relative importance of body size to the production and continuation of gender income inequality in Canada.

Radiographic analysis of vocal tract length and its relation to overall body size in two canid species.

PubMed

Plotsky, K; Rendall, D; Riede, T; Chase, K

2013-09-01

Body size is an important determinant of resource and mate competition in many species. Competition is often mediated by conspicuous vocal displays, which may help to intimidate rivals and attract mates by providing honest cues to signaler size. Fitch proposed that vocal tract resonances (or formants) should provide particularly good, or honest, acoustic cues to signaler size because they are determined by the length of the vocal tract, which in turn, is hypothesized to scale reliably with overall body size. There is some empirical support for this hypothesis, but to date, many of the effects have been either mixed for males compared with females, weaker than expected in one or the other sex, or complicated by sampling issues. In this paper, we undertake a direct test of Fitch's hypothesis in two canid species using large samples that control for age- and sex-related variation. The samples involved radiographic images of 120 Portuguese water dogs Canis lupus familiaris and 121 Russian silver foxes Vulpes vulpes . Direct measurements were made of vocal tract length from X-ray images and compared against independent measures of body size. In adults of both species, and within both sexes, overall vocal tract length was strongly and significantly correlated with body size. Effects were strongest for the oral component of the vocal tract. By contrast, the length of the pharyngeal component was not as consistently related to body size. These outcomes are some of the clearest evidence to date in support of Fitch's hypothesis. At the same time, they highlight the potential for elements of both honest and deceptive body signaling to occur simultaneously via differential acoustic cues provided by the oral versus pharyngeal components of the vocal tract.

Radiographic analysis of vocal tract length and its relation to overall body size in two canid species

PubMed Central

Plotsky, K.; Rendall, D.; Riede, T.; Chase, K.

2013-01-01

Body size is an important determinant of resource and mate competition in many species. Competition is often mediated by conspicuous vocal displays, which may help to intimidate rivals and attract mates by providing honest cues to signaler size. Fitch proposed that vocal tract resonances (or formants) should provide particularly good, or honest, acoustic cues to signaler size because they are determined by the length of the vocal tract, which in turn, is hypothesized to scale reliably with overall body size. There is some empirical support for this hypothesis, but to date, many of the effects have been either mixed for males compared with females, weaker than expected in one or the other sex, or complicated by sampling issues. In this paper, we undertake a direct test of Fitch’s hypothesis in two canid species using large samples that control for age- and sex-related variation. The samples involved radiographic images of 120 Portuguese water dogs Canis lupus familiaris and 121 Russian silver foxes Vulpes vulpes. Direct measurements were made of vocal tract length from X-ray images and compared against independent measures of body size. In adults of both species, and within both sexes, overall vocal tract length was strongly and significantly correlated with body size. Effects were strongest for the oral component of the vocal tract. By contrast, the length of the pharyngeal component was not as consistently related to body size. These outcomes are some of the clearest evidence to date in support of Fitch’s hypothesis. At the same time, they highlight the potential for elements of both honest and deceptive body signaling to occur simultaneously via differential acoustic cues provided by the oral versus pharyngeal components of the vocal tract. PMID:24363497

Gear and seasonal bias associated with abundance and size structure estimates for lentic freshwater fishes

USGS Publications Warehouse

Fischer, Jesse R.; Quist, Michael C.

2014-01-01

All freshwater fish sampling methods are biased toward particular species, sizes, and sexes and are further influenced by season, habitat, and fish behavior changes over time. However, little is known about gear-specific biases for many common fish species because few multiple-gear comparison studies exist that have incorporated seasonal dynamics. We sampled six lakes and impoundments representing a diversity of trophic and physical conditions in Iowa, USA, using multiple gear types (i.e., standard modified fyke net, mini-modified fyke net, sinking experimental gill net, bag seine, benthic trawl, boat-mounted electrofisher used diurnally and nocturnally) to determine the influence of sampling methodology and season on fisheries assessments. Specifically, we describe the influence of season on catch per unit effort, proportional size distribution, and the number of samples required to obtain 125 stock-length individuals for 12 species of recreational and ecological importance. Mean catch per unit effort generally peaked in the spring and fall as a result of increased sampling effectiveness in shallow areas and seasonal changes in habitat use (e.g., movement offshore during summer). Mean proportional size distribution decreased from spring to fall for white bass Morone chrysops, largemouth bass Micropterus salmoides, bluegill Lepomis macrochirus, and black crappie Pomoxis nigromaculatus, suggesting selectivity for large and presumably sexually mature individuals in the spring and summer. Overall, the mean number of samples required to sample 125 stock-length individuals was minimized in the fall with sinking experimental gill nets, a boat-mounted electrofisher used at night, and standard modified nets for 11 of the 12 species evaluated. Our results provide fisheries scientists with relative comparisons between several recommended standard sampling methods and illustrate the effects of seasonal variation on estimates of population indices that will be critical to the future development of standardized sampling methods for freshwater fish in lentic ecosystems.

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

PubMed

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.

Effect of grain size on structural and dielectric properties of barium titanate piezoceramics synthesized by high energy ball milling

NASA Astrophysics Data System (ADS)

Verma, Narendra Kumar; Patel, Sandeep Kumar Singh; Kumar, Dinesh; Singh, Chandra Bhal; Singh, Akhilesh Kumar

2018-05-01

We have investigated the effect of sintering temperature on the densification behaviour, grain size, structural and dielectric properties of BaTiO3 ceramics, prepared by high energy ball milling method. The Powder x-ray diffraction reveals the tetragonal structure with space group P4mm for all the samples. The samples were sintered at four different temperatures, (T = 900°C, 1000°C, 1100°C, 1200°C and 1300°C). Density increased with increasing sintering temperature, reaching up to 97% at 1300°C. A grain growth was observed with increasing sintering temperature. Impedance analyses of the sintered samples at various temperatures were performed. Increase in dielectric constant and Curie temperature is observed with increasing sintering temperature.

Seasonal variation in size-dependent survival of juvenile Atlantic salmon (Salmo salar): Performance of multistate capture-mark-recapture models

USGS Publications Warehouse

Letcher, B.H.; Horton, G.E.

2008-01-01

We estimated the magnitude and shape of size-dependent survival (SDS) across multiple sampling intervals for two cohorts of stream-dwelling Atlantic salmon (Salmo salar) juveniles using multistate capture-mark-recapture (CMR) models. Simulations designed to test the effectiveness of multistate models for detecting SDS in our system indicated that error in SDS estimates was low and that both time-invariant and time-varying SDS could be detected with sample sizes of >250, average survival of >0.6, and average probability of capture of >0.6, except for cases of very strong SDS. In the field (N ??? 750, survival 0.6-0.8 among sampling intervals, probability of capture 0.6-0.8 among sampling occasions), about one-third of the sampling intervals showed evidence of SDS, with poorer survival of larger fish during the age-2+ autumn and quadratic survival (opposite direction between cohorts) during age-1+ spring. The varying magnitude and shape of SDS among sampling intervals suggest a potential mechanism for the maintenance of the very wide observed size distributions. Estimating SDS using multistate CMR models appears complementary to established approaches, can provide estimates with low error, and can be used to detect intermittent SDS. ?? 2008 NRC Canada.

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

PubMed

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.

Interventions targeting substance abuse among women survivors of intimate partner abuse: a meta-analysis.

PubMed

Fowler, Dawnovise N; Faulkner, Monica

2011-12-01

In this article, meta-analytic techniques are used to examine existing intervention studies (n = 11) to determine their effects on substance abuse among female samples of intimate partner abuse (IPA) survivors. This research serves as a starting point for greater attention in research and practice to the implementation of evidence-based, integrated services to address co-occurring substance abuse and IPA victimization among women as major intersecting public health problems. The results show greater effects in three main areas. First, greater effect sizes exist in studies where larger numbers of women experienced current IPA. Second, studies with a lower mean age also showed greater effect sizes than studies with a higher mean age. Lastly, studies with smaller sample sizes have greater effects. This research helps to facilitate cohesion in the knowledge base on this topic, and the findings of this meta-analysis, in particular, contribute needed information to gaps in the literature on the level of promise of existing interventions to impact substance abuse in this underserved population. Published by Elsevier Inc.

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

PubMed

van Schie, S; Moerbeek, M

2014-08-30

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 level and individual level variance should be known before the study starts, but this is often not the case. We suggest using an internal pilot study design to address this problem of unknown variances. A pilot can be useful to re-estimate the variances and re-calculate the sample size during the trial. Using simulated data, it is shown that an initially low or high power can be adjusted using an internal pilot with the type I error rate remaining within an acceptable range. The intracluster correlation coefficient can be re-estimated with more precision, which has a positive effect on the sample size. We conclude that an internal pilot study design may be used if active recruitment is feasible within a limited number of clusters. Copyright © 2014 John Wiley & Sons, Ltd.

Grain size effect on the permittivity of La1.5Sr0.5NiO4 nanoparticles

NASA Astrophysics Data System (ADS)

Dang Thanh, Tran; Van Hong, Le

2009-09-01

Using the annealing at different temperatures the La1.5Sr0.5NiO4 ceramic samples with different mean grain size were manufactured. Mean grain size () of the samples was evaluated by Warren-Averbach method and their SEM images. The obtained results of both methods are almost the same, changing from 16.2 to 95 nm in dependence on the annealing temperature. The frequency dependence of dielectric constant in the frequency range of (1-13 MHz) was recorded for all samples. The real (ɛ') and the imaginary parts (ɛ") of the permittivity of La1.5Sr0.5NiO4 samples abnormally depend on the frequency, exhibiting a dielectric resonance around 500 kHz. R-L-C in series equivalent-circuit fitted well for the obtained result. It was supposed that there exists magnetic contribution in material that suggests the material is a multiferroic one. Dependence of the (ɛ') on the mean grain size supposed that the colossal dielectric property is an intrinsic behaviour of La1.5Sr0.5NiO4 material.

In Situ Balloon-Borne Ice Particle Imaging in High-Latitude Cirrus

NASA Astrophysics Data System (ADS)

Kuhn, Thomas; Heymsfield, Andrew J.

2016-09-01

Cirrus clouds reflect incoming solar radiation, creating a cooling effect. At the same time, these clouds absorb the infrared radiation from the Earth, creating a greenhouse effect. The net effect, crucial for radiative transfer, depends on the cirrus microphysical properties, such as particle size distributions and particle shapes. Knowledge of these cloud properties is also needed for calibrating and validating passive and active remote sensors. Ice particles of sizes below 100 µm are inherently difficult to measure with aircraft-mounted probes due to issues with resolution, sizing, and size-dependent sampling volume. Furthermore, artefacts are produced by shattering of particles on the leading surfaces of the aircraft probes when particles several hundred microns or larger are present. Here, we report on a series of balloon-borne in situ measurements that were carried out at a high-latitude location, Kiruna in northern Sweden (68N 21E). The method used here avoids these issues experienced with the aircraft probes. Furthermore, with a balloon-borne instrument, data are collected as vertical profiles, more useful for calibrating or evaluating remote sensing measurements than data collected along horizontal traverses. Particles are collected on an oil-coated film at a sampling speed given directly by the ascending rate of the balloon, 4 m s-1. The collecting film is advanced uniformly inside the instrument so that an always unused section of the film is exposed to ice particles, which are measured by imaging shortly after sampling. The high optical resolution of about 4 µm together with a pixel resolution of 1.65 µm allows particle detection at sizes of 10 µm and larger. For particles that are 20 µm (12 pixel) in size or larger, the shape can be recognized. The sampling volume, 130 cm3 s-1, is well defined and independent of particle size. With the encountered number concentrations of between 4 and 400 L-1, this required about 90- to 4-s sampling times to determine particle size distributions of cloud layers. Depending on how ice particles vary through the cloud, several layers per cloud with relatively uniform properties have been analysed. Preliminary results of the balloon campaign, targeting upper tropospheric, cold cirrus clouds, are presented here. Ice particles in these clouds were predominantly very small, with a median size of measured particles of around 50 µm and about 80 % of all particles below 100 µm in size. The properties of the particle size distributions at temperatures between -36 and -67 °C have been studied, as well as particle areas, extinction coefficients, and their shapes (area ratios). Gamma and log-normal distribution functions could be fitted to all measured particle size distributions achieving very good correlation with coefficients R of up to 0.95. Each distribution features one distinct mode. With decreasing temperature, the mode diameter decreases exponentially, whereas the total number concentration increases by two orders of magnitude with decreasing temperature in the same range. The high concentrations at cold temperatures also caused larger extinction coefficients, directly determined from cross-sectional areas of single ice particles, than at warmer temperatures. The mass of particles has been estimated from area and size. Ice water content (IWC) and effective diameters are then determined from the data. IWC did vary only between 1 × 10-3 and 5 × 10-3 g m-3 at temperatures below -40 °C and did not show a clear temperature trend. These measurements are part of an ongoing study.

The Statistical Power of Planned Comparisons.

ERIC Educational Resources Information Center

Benton, Roberta L.

Basic principles underlying statistical power are examined; and issues pertaining to effect size, sample size, error variance, and significance level are highlighted via the use of specific hypothetical examples. Analysis of variance (ANOVA) and related methods remain popular, although other procedures sometimes have more statistical power against…

Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions.

PubMed

Choi, Yoonha; Liu, Tiffany Ting; Pankratz, Daniel G; Colby, Thomas V; Barth, Neil M; Lynch, David A; Walsh, P Sean; Raghu, Ganesh; Kennedy, Giulia C; Huang, Jing

2018-05-09

We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects. We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~ 0.9 in cross-validation. Using in silico mixed samples in training, we prospectively defined a decision boundary to optimize specificity at ≥85%. The penalized logistic regression model showed greater reproducibility across technical replicates and was chosen as the final model. The final model showed sensitivity of 70% and specificity of 88% in the test set. We demonstrated that the suggested methodologies appropriately addressed challenges of the sample size, disease heterogeneity and technical batch effects and developed a highly accurate and robust classifier leveraging RNA sequencing for the classification of UIP.

A Meta-Analysis of the Long-Term Effects of Phonemic Awareness, Phonics, Fluency, and Reading Comprehension Interventions.

PubMed

Suggate, Sebastian P

2016-01-01

Much is known about short-term--but very little about the long-term--effects of reading interventions. To rectify this, a detailed analysis of follow-up effects as a function of intervention, sample, and methodological variables was conducted. A total of 71 intervention-control groups were selected (N = 8,161 at posttest) from studies reporting posttest and follow-up data (M = 11.17 months) for previously established reading interventions. The posttest effect sizes indicated effects (dw = 0.37) that decreased to follow-up (dw = 0.22). Overall, comprehension and phonemic awareness interventions showed good maintenance of effect that transferred to nontargeted skills, whereas phonics and fluency interventions, and those for preschool and kindergarten children, tended not to. Several methodological features also related to effect sizes at follow-up, namely experimental design and dosage, and sample attrition, risk status, and gender balance. © Hammill Institute on Disabilities 2014.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

The effect of size, orientation and alloying on the deformation of AZ31 nanopillars

NASA Astrophysics Data System (ADS)

Aitken, Zachary H.; Fan, Haidong; El-Awady, Jaafar A.; Greer, Julia R.

2015-03-01

We conducted uniaxial compression of single crystalline Mg alloy, AZ31 (Al 3 wt% and Zn 1 wt%) nanopillars with diameters between 300 and 5000 nm with two distinct crystallographic orientations: (1) along the [0001] c-axis and (2) at an acute angle away from the c-axis, nominally oriented for basal slip. We observe single slip deformation for sub-micron samples nominally oriented for basal slip with the deformation commencing via a single set of parallel shear offsets. Samples compressed along the c-axis display an increase in yield strength compared to basal samples as well as significant hardening with the deformation being mostly homogeneous. We find that the "smaller is stronger" size effect in single crystals dominates any improvement in strength that may have arisen from solid solution strengthening. We employ 3D-discrete dislocation dynamics (DDD) to simulate compression along the [0001] and [ 11 2 bar 2 ] directions to elucidate the mechanisms of slip and evolution of dislocation microstructure. These simulations show qualitatively similar stress-strain signatures to the experimentally obtained stress-strain data. Simulations of compression parallel to the [ 11 2 bar 2 ] direction reveal the activation and motion of only -type dislocations and virtually no dislocation junction formation. Computations of compression along [0001] show the activation and motion of both and dislocations along with a significant increase in the formation of junctions corresponding to the interaction of intersecting pyramidal planes. Both experiments and simulation show a size effect, with a differing exponent for basal and pyramidal slip. We postulate that this anisotropy in size effect is a result of the underlying anisotropic material properties only. We discuss these findings in the context of the effective resolved shear stress relative to the unit Burgers vector for each type of slip, which reveal that the mechanism that governs size effect in this Mg-alloy is equivalent in both orientations.

Carbon Nanotube and Nanofiber Exposure Assessments: An Analysis of 14 Site Visits.

PubMed

Dahm, Matthew M; Schubauer-Berigan, Mary K; Evans, Douglas E; Birch, M Eileen; Fernback, Joseph E; Deddens, James A

2015-07-01

Recent evidence has suggested the potential for wide-ranging health effects that could result from exposure to carbon nanotubes (CNT) and carbon nanofibers (CNF). In response, the National Institute for Occupational Safety and Health (NIOSH) set a recommended exposure limit (REL) for CNT and CNF: 1 µg m(-3) as an 8-h time weighted average (TWA) of elemental carbon (EC) for the respirable size fraction. The purpose of this study was to conduct an industrywide exposure assessment among US CNT and CNF manufacturers and users. Fourteen total sites were visited to assess exposures to CNT (13 sites) and CNF (1 site). Personal breathing zone (PBZ) and area samples were collected for both the inhalable and respirable mass concentration of EC, using NIOSH Method 5040. Inhalable PBZ samples were collected at nine sites while at the remaining five sites both respirable and inhalable PBZ samples were collected side-by-side. Transmission electron microscopy (TEM) PBZ and area samples were also collected at the inhalable size fraction and analyzed to quantify and size CNT and CNF agglomerate and fibrous exposures. Respirable EC PBZ concentrations ranged from 0.02 to 2.94 µg m(-3) with a geometric mean (GM) of 0.34 µg m(-3) and an 8-h TWA of 0.16 µg m(-3). PBZ samples at the inhalable size fraction for EC ranged from 0.01 to 79.57 µg m(-3) with a GM of 1.21 µg m(-3). PBZ samples analyzed by TEM showed concentrations ranging from 0.0001 to 1.613 CNT or CNF-structures per cm(3) with a GM of 0.008 and an 8-h TWA concentration of 0.003. The most common CNT structure sizes were found to be larger agglomerates in the 2-5 µm range as well as agglomerates >5 µm. A statistically significant correlation was observed between the inhalable samples for the mass of EC and structure counts by TEM (Spearman ρ = 0.39, P < 0.0001). Overall, EC PBZ and area TWA samples were below the NIOSH REL (96% were <1 μg m(-3) at the respirable size fraction), while 30% of the inhalable PBZ EC samples were found to be >1 μg m(-3). Until more information is known about health effects associated with larger agglomerates, it seems prudent to assess worker exposure to airborne CNT and CNF materials by monitoring EC at both the respirable and inhalable size fractions. Concurrent TEM samples should be collected to confirm the presence of CNT and CNF. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2015.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size

PubMed Central

Yu, P.; Sun, J.; Wolz, R.; Stephenson, D.; Brewer, J.; Fox, N.C.; Cole, P.E.; Jack, C.R.; Hill, D.L.G.; Schwarz, A.J.

2014-01-01

Objective To evaluate the effect of computational algorithm, measurement variability and cut-point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). Methods We used normal control and amnestic MCI subjects from ADNI-1 as normative reference and screening cohorts. We evaluated the enrichment performance of four widely-used hippocampal segmentation algorithms (FreeSurfer, HMAPS, LEAP and NeuroQuant) in terms of two-year changes in MMSE, ADAS-Cog and CDR-SB. We modeled the effect of algorithm, test-retest variability and cut-point on sample size, screen fail rates and trial cost and duration. Results HCV-based patient selection yielded not only reduced sample sizes (by ~40–60%) but also lower trial costs (by ~30–40%) across a wide range of cut-points. Overall, the dependence on the cut-point value was similar for the three clinical instruments considered. Conclusion These results provide a guide to the choice of HCV cut-point for aMCI clinical trials, allowing an informed trade-off between statistical and practical considerations. PMID:24211008

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

PubMed

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.

Effects of sources of variability on sample sizes required for RCTs, applied to trials of lipid-altering therapies on carotid artery intima-media thickness.

PubMed

Gould, A Lawrence; Koglin, Joerg; Bain, Raymond P; Pinto, Cathy-Anne; Mitchel, Yale B; Pasternak, Richard C; Sapre, Aditi

2009-08-01

Studies measuring progression of carotid artery intima-media thickness (cIMT) have been used to estimate the effect of lipid-modifying therapies cardiovascular event risk. The likelihood that future cIMT clinical trials will detect a true treatment effect is estimated by leveraging results from prior studies. The present analyses assess the impact of between- and within-study variability based on currently published data from prior clinical studies on the likelihood that ongoing or future cIMT trials will detect the true treatment effect of lipid-modifying therapies. Published data from six contemporary cIMT studies (ASAP, ARBITER 2, RADIANCE 1, RADIANCE 2, ENHANCE, and METEOR) including data from a total of 3563 patients were examined. Bayesian and frequentist methods were used to assess the impact of between study variability on the likelihood of detecting true treatment effects on 1-year cIMT progression/regression and to provide a sample size estimate that would specifically compensate for the effect of between-study variability. In addition to the well-described within-study variability, there is considerable between-study variability associated with the measurement of annualized change in cIMT. Accounting for the additional between-study variability decreases the power for existing study designs. In order to account for the added between-study variability, it is likely that future cIMT studies would require a large increase in sample size in order to provide substantial probability (> or =90%) to have 90% power of detecting a true treatment effect.Limitation Analyses are based on study level data. Future meta-analyses incorporating patient-level data would be useful for confirmation. Due to substantial within- and between-study variability in the measure of 1-year change of cIMT, as well as uncertainty about progression rates in contemporary populations, future study designs evaluating the effect of new lipid-modifying therapies on atherosclerotic disease progression are likely to be challenged by large sample sizes in order to demonstrate a true treatment effect.

Shrinking of silicon nanocrystals embedded in an amorphous silicon oxide matrix during rapid thermal annealing in a forming gas atmosphere

NASA Astrophysics Data System (ADS)

van Sebille, M.; Fusi, A.; Xie, L.; Ali, H.; van Swaaij, R. A. C. M. M.; Leifer, K.; Zeman, M.

2016-09-01

We report the effect of hydrogen on the crystallization process of silicon nanocrystals embedded in a silicon oxide matrix. We show that hydrogen gas during annealing leads to a lower sub-band gap absorption, indicating passivation of defects created during annealing. Samples annealed in pure nitrogen show expected trends according to crystallization theory. Samples annealed in forming gas, however, deviate from this trend. Their crystallinity decreases for increased annealing time. Furthermore, we observe a decrease in the mean nanocrystal size and the size distribution broadens, indicating that hydrogen causes a size reduction of the silicon nanocrystals.

Size separation of analytes using monomeric surfactants

DOEpatents

Yeung, Edward S.; Wei, Wei

2005-04-12

A sieving medium for use in the separation of analytes in a sample containing at least one such analyte comprises a monomeric non-ionic surfactant of the of the general formula, B-A, wherein A is a hydrophilic moiety and B is a hydrophobic moiety, present in a solvent at a concentration forming a self-assembled micelle configuration under selected conditions and having an aggregation number providing an equivalent weight capable of effecting the size separation of the sample solution so as to resolve a target analyte(s) in a solution containing the same, the size separation taking place in a chromatography or electrophoresis separation system.

Effect of milling atmosphere on structural and magnetic properties of Ni-Zn ferrite nanocrystalline

NASA Astrophysics Data System (ADS)

Hajalilou, Abdollah; Hashim, Mansor; Ebrahimi-Kahrizsangi, Reza; Masoudi Mohamad, Taghi

2015-04-01

Powder mixtures of Zn, NiO, and Fe2O3 are mechanically alloyed by high energy ball milling to produce Ni-Zn ferrite with a nominal composition of Ni0.36Zn0.64Fe2O4. The effects of milling atmospheres (argon, air, and oxygen), milling time (from 0 to 30 h) and heat treatment are studied. The products are characterized using x-ray diffractometry, field emission scanning electron microscopy equipped with energy-dispersive x-ray spectroscopy, and transmitted electron microscopy. The results indicate that the desired ferrite is not produced during the milling in the samples milled under either air or oxygen atmospheres. In those samples milled under argon, however, Zn/NiO/Fe2O3 reacts with a solid-state diffusion mode to produce Ni-Zn ferrite nanocrystalline in a size of 8 nm after 30-h-milling. The average crystallite sizes decrease to 9 nm and 10 nm in 30-h-milling samples under air and oxygen atmospheres, respectively. Annealing the 30-h-milling samples at 600 °C for 2 h leads to the formation of a single phase of Ni-Zn ferrite, an increase of crystallite size, and a reduction of internal lattice strain. Finally, the effects of the milling atmosphere and heating temperature on the magnetic properties of the 30-h-milling samples are investigated. Project supported by the University Putra Malaysia Graduate Research Fellowship Section.

The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

NASA Astrophysics Data System (ADS)

Wake, David A.; Bundy, Kevin; Diamond-Stanic, Aleksandar M.; Yan, Renbin; Blanton, Michael R.; Bershady, Matthew A.; Sánchez-Gallego, José R.; Drory, Niv; Jones, Amy; Kauffmann, Guinevere; Law, David R.; Li, Cheng; MacDonald, Nicholas; Masters, Karen; Thomas, Daniel; Tinker, Jeremy; Weijmans, Anne-Marie; Brownstein, Joel R.

2017-09-01

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing signal-to-noise ratio, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on I-band absolute magnitude (M I ), or, for a small subset of our sample, M I and color (NUV - I). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to M I and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (R e ), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color-magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range 5× {10}8≤slant {M}* ≤slant 3× {10}11 {M}⊙ {h}-2 and are sampled at median physical resolutions of 1.37 and 2.5 kpc for the Primary and Secondary samples, respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume-limited sample.

Using the Sampling Margin of Error to Assess the Interpretative Validity of Student Evaluations of Teaching

ERIC Educational Resources Information Center

James, David E.; Schraw, Gregory; Kuch, Fred

2015-01-01

We present an equation, derived from standard statistical theory, that can be used to estimate sampling margin of error for student evaluations of teaching (SETs). We use the equation to examine the effect of sample size, response rates and sample variability on the estimated sampling margin of error, and present results in four tables that allow…

Microstructure as a function of the grain size distribution for packings of frictionless disks: Effects of the size span and the shape of the distribution.

PubMed

Estrada, Nicolas; Oquendo, W F

2017-10-01

This article presents a numerical study of the effects of grain size distribution (GSD) on the microstructure of two-dimensional packings of frictionless disks. The GSD is described by a power law with two parameters controlling the size span and the shape of the distribution. First, several samples are built for each combination of these parameters. Then, by means of contact dynamics simulations, the samples are densified in oedometric conditions and sheared in a simple shear configuration. The microstructure is analyzed in terms of packing fraction, local ordering, connectivity, and force transmission properties. It is shown that the microstructure is notoriously affected by both the size span and the shape of the GSD. These findings confirm recent observations regarding the size span of the GSD and extend previous works by describing the effects of the GSD shape. Specifically, we find that if the GSD shape is varied by increasing the proportion of small grains by a certain amount, it is possible to increase the packing fraction, increase coordination, and decrease the proportion of floating particles. Thus, by carefully controlling the GSD shape, it is possible to obtain systems that are denser and better connected, probably increasing the system's robustness and optimizing important strength properties such as stiffness, cohesion, and fragmentation susceptibility.

Effect of bait and gear type on channel catfish catch and turtle bycatch in a reservoir

USGS Publications Warehouse

Cartabiano, Evan C.; Stewart, David R.; Long, James M.

2014-01-01

Hoop nets have become the preferred gear choice to sample channel catfish Ictalurus punctatus but the degree of bycatch can be high, especially due to the incidental capture of aquatic turtles. While exclusion and escapement devices have been developed and evaluated, few have examined bait choice as a method to reduce turtle bycatch. The use of Zote™ soap has shown considerable promise to reduce bycatch of aquatic turtles when used with trotlines but its effectiveness in hoop nets has not been evaluated. We sought to determine the effectiveness of hoop nets baited with cheese bait or Zote™ soap and trotlines baited with shad or Zote™ soap as a way to sample channel catfish and prevent capture of aquatic turtles. We used a repeated-measures experimental design and treatment combinations were randomly assigned using a Latin-square arrangement. Eight sampling locations were systematically selected and then sampled with either hoop nets or trotlines using Zote™ soap (both gears), waste cheese (hoop nets), or cut shad (trotlines). Catch rates did not statistically differ among the gear–bait-type combinations. Size bias was evident with trotlines consistently capturing larger sized channel catfish compared to hoop nets. Results from a Monte Carlo bootstrapping procedure estimated the number of samples needed to reach predetermined levels of sampling precision to be lowest for trotlines baited with soap. Moreover, trotlines baited with soap caught no aquatic turtles, while hoop nets captured many turtles and had high mortality rates. We suggest that Zote™ soap used in combination with multiple hook sizes on trotlines may be a viable alternative to sample channel catfish and reduce bycatch of aquatic turtles.

Replication and contradiction of highly cited research papers in psychiatry: 10-year follow-up.

PubMed

Tajika, Aran; Ogawa, Yusuke; Takeshima, Nozomi; Hayasaka, Yu; Furukawa, Toshi A

2015-10-01

Contradictions and initial overestimates are not unusual among highly cited studies. However, this issue has not been researched in psychiatry. Aims: To assess how highly cited studies in psychiatry are replicated by subsequent studies. We selected highly cited studies claiming effective psychiatric treatments in the years 2000 through 2002. For each of these studies we searched for subsequent studies with a better-controlled design, or with a similar design but a larger sample. Among 83 articles recommending effective interventions, 40 had not been subject to any attempt at replication, 16 were contradicted, 11 were found to have substantially smaller effects and only 16 were replicated. The standardised mean differences of the initial studies were overestimated by 132%. Studies with a total sample size of 100 or more tended to produce replicable results. Caution is needed when a study with a small sample size reports a large effect. © The Royal College of Psychiatrists 2015.

Optical properties of mineral dust aerosol including analysis of particle size, composition, and shape effects, and the impact of physical and chemical processing

NASA Astrophysics Data System (ADS)

Alexander, Jennifer Mary

Atmospheric mineral dust has a large impact on the earth's radiation balance and climate. The radiative effects of mineral dust depend on factors including, particle size, shape, and composition which can all be extremely complex. Mineral dust particles are typically irregular in shape and can include sharp edges, voids, and fine scale surface roughness. Particle shape can also depend on the type of mineral and can vary as a function of particle size. In addition, atmospheric mineral dust is a complex mixture of different minerals as well as other, possibly organic, components that have been mixed in while these particles are suspended in the atmosphere. Aerosol optical properties are investigated in this work, including studies of the effect of particle size, shape, and composition on the infrared (IR) extinction and visible scattering properties in order to achieve more accurate modeling methods. Studies of particle shape effects on dust optical properties for single component mineral samples of silicate clay and diatomaceous earth are carried out here first. Experimental measurements are modeled using T-matrix theory in a uniform spheroid approximation. Previous efforts to simulate the measured optical properties of silicate clay, using models that assumed particle shape was independent of particle size, have achieved only limited success. However, a model which accounts for a correlation between particle size and shape for the silicate clays offers a large improvement over earlier modeling approaches. Diatomaceous earth is also studied as an example of a single component mineral dust aerosol with extreme particle shapes. A particle shape distribution, determined by fitting the experimental IR extinction data, used as a basis for modeling the visible light scattering properties. While the visible simulations show only modestly good agreement with the scattering data, the fits are generally better than those obtained using more commonly invoked particle shape distributions. The next goal of this work is to investigate if modeling methods developed in the studies of single mineral components can be generalized to predict the optical properties of more authentic aerosol samples which are complex mixtures of different minerals. Samples of Saharan sand, Iowa loess, and Arizona road dust are used here as test cases. T-matrix based simulations of the authentic samples, using measured particle size distributions, empirical mineralogies, and a priori particle shape models for each mineral component are directly compared with the measured IR extinction spectra and visible scattering profiles. This modeling approach offers a significant improvement over more commonly applied models that ignore variations in particle shape with size or mineralogy and include only a moderate range of shape parameters. Mineral dust samples processed with organic acids and humic material are also studied in order to explore how the optical properties of dust can change after being aged in the atmosphere. Processed samples include quartz mixed with humic material, and calcite reacted with acetic and oxalic acid. Clear differences in the light scattering properties are observed for all three processed mineral dust samples when compared to the unprocessed mineral dust or organic salt products. These interactions result in both internal and external mixtures depending on the sample. In addition, the presence of these organic materials can alter the mineral dust particle shape. Overall, however, these results demonstrate the need to account for the effects of atmospheric aging of mineral dust on aerosol optical properties. Particle shape can also affect the aerodynamic properties of mineral dust aerosol. In order to account for these effects, the dynamic shape factor is used to give a measure of particle asphericity. Dynamic shape factors of quartz are measured by mass and mobility selecting particles and measuring their vacuum aerodynamic diameter. From this, dynamic shape factors in both the transition and vacuum regime can be derived. The measured dynamic shape factors of quartz agree quite well with the spheroidal shape distributions derived through studies of the optical properties.

The Effect of Grouping by Formal Reasoning Ability, Formal Reasoning Ability Levels, Group Size, and Gender on Achievement in Laboratory Chemistry.

ERIC Educational Resources Information Center

Moody, Judith D.; Gifford, Vernon D.

This study investigated the grouping effect on student achievement in a chemistry laboratory when homogeneous and heterogeneous formal reasoning ability, high and low levels of formal reasoning ability, group sizes of two and four, and homogeneous and heterogeneous gender were used for grouping factors. The sample consisted of all eight intact…

The Risk of Adverse Impact in Selections Based on a Test with Known Effect Size

ERIC Educational Resources Information Center

De Corte, Wilfried; Lievens, Filip

2005-01-01

The authors derive the exact sampling distribution function of the adverse impact (AI) ratio for single-stage, top-down selections using tests with known effect sizes. Subsequently, it is shown how this distribution function can be used to determine the risk that a future selection decision on the basis of such tests will result in an outcome that…

Confidence crisis of results in biomechanics research.

PubMed

Knudson, Duane

2017-11-01

Many biomechanics studies have small sample sizes and incorrect statistical analyses, so reporting of inaccurate inferences and inflated magnitude of effects are common in the field. This review examines these issues in biomechanics research and summarises potential solutions from research in other fields to increase the confidence in the experimental effects reported in biomechanics. Authors, reviewers and editors of biomechanics research reports are encouraged to improve sample sizes and the resulting statistical power, improve reporting transparency, improve the rigour of statistical analyses used, and increase the acceptance of replication studies to improve the validity of inferences from data in biomechanics research. The application of sports biomechanics research results would also improve if a larger percentage of unbiased effects and their uncertainty were reported in the literature.

The Differential Victimization Associated With Depression and Anxiety in Cross-Cultural Perspective: A Meta-Analysis.

PubMed

Yuchang, Jin; Junyi, Li; Junxiu, An; Jing, Wu; Mingcheng, He

2017-01-01

Traditional bullying and cyberbullying have become serious worldwide issues. The meta-analysis in this article took a cross-cultural perspective to explore whether there were any differences between the effects of cyber victimization and traditional victimization on the presence of depression and anxiety in children and adolescents and to examine the effects of moderators in explaining these differences/similarities. Fifty-six empirical studies (generating 148 independent samples) were included with a total sample size of 214,819 participants. The results indicated that the effects of cyber victimization and the subtypes of traditional victimization on anxiety were significantly different, and there was a marginally significant difference for depression. The moderating effects of country of origin were found to be significant for depression, with the mean effect size in North America being significantly higher than in China and Europe, which suggested that culture was an important factor. The moderating effects of age were also found to be significant for the relationships between traditional victimization and depression, traditional victimization and anxiety, cyber victimization and depression, and cyber victimization and anxiety. In addition, the effect size for cyber victimization and depression has increased in more recent publication years.

Some radiation effects on organic binders in X-ray fluorescence spectrometry

NASA Astrophysics Data System (ADS)

Novosel-Radović, Vj.; MaljkoviĆ, Da.; NenadiĆ, N.

The paper deals with diminished wear resistance of standard samples in X-ray fluorescence spectrometry. The effect of X-ray irradiation on pellet samples, pressed with starch as organic binder, was investigated by sieve analysis and scanning electron microscopy. A change in the starch grain size was found as a result of swelling and cracking.

Reversing the Signaled Magnitude Effect in Delayed Matching to Sample: Delay-Specific Remembering?

ERIC Educational Resources Information Center

White, K. Geoffrey; Brown, Glenn S.

2011-01-01

Pigeons performed a delayed matching-to-sample task in which large or small reinforcers for correct remembering were signaled during the retention interval. Accuracy was low when small reinforcers were signaled, and high when large reinforcers were signaled (the signaled magnitude effect). When the reinforcer-size cue was switched from small to…

Bias and Precision of Measures of Association for a Fixed-Effect Multivariate Analysis of Variance Model

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

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

PubMed Central

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

2017-01-01

Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V, E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K, and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios. PMID:28867924

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

PubMed

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

2016-01-01

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

Confidence intervals and sample size calculations for the standardized mean difference effect size between two normal populations under heteroscedasticity.

PubMed

Shieh, G

2013-12-01

The use of effect sizes and associated confidence intervals in all empirical research has been strongly emphasized by journal publication guidelines. To help advance theory and practice in the social sciences, this article describes an improved procedure for constructing confidence intervals of the standardized mean difference effect size between two independent normal populations with unknown and possibly unequal variances. The presented approach has advantages over the existing formula in both theoretical justification and computational simplicity. In addition, simulation results show that the suggested one- and two-sided confidence intervals are more accurate in achieving the nominal coverage probability. The proposed estimation method provides a feasible alternative to the most commonly used measure of Cohen's d and the corresponding interval procedure when the assumption of homogeneous variances is not tenable. To further improve the potential applicability of the suggested methodology, the sample size procedures for precise interval estimation of the standardized mean difference are also delineated. The desired precision of a confidence interval is assessed with respect to the control of expected width and to the assurance probability of interval width within a designated value. Supplementary computer programs are developed to aid in the usefulness and implementation of the introduced techniques.

Suspended sediments from upstream tributaries as the source of downstream river sites

NASA Astrophysics Data System (ADS)

Haddadchi, Arman; Olley, Jon

2014-05-01

Understanding the efficiency with which sediment eroded from different sources is transported to the catchment outlet is a key knowledge gap that is critical to our ability to accurately target and prioritise management actions to reduce sediment delivery. Sediment fingerprinting has proven to be an efficient approach to determine the sources of sediment. This study examines the suspended sediment sources from Emu Creek catchment, south eastern Queensland, Australia. In addition to collect suspended sediments from different sites of the streams after the confluence of tributaries and outlet of the catchment, time integrated suspended samples from upper tributaries were used as the source of sediment, instead of using hillslope and channel bank samples. Totally, 35 time-integrated samplers were used to compute the contribution of suspended sediments from different upstream waterways to the downstream sediment sites. Three size fractions of materials including fine sand (63-210 μm), silt (10-63 μm) and fine silt and clay (<10 μm) were used to find the effect of particle size on the contribution of upper sediments as the sources of sediment after river confluences. And then samples were analysed by ICP-MS and -OES to find 41 sediment fingerprints. According to the results of Student's T-distribution mixing model, small creeks in the middle and lower part of the catchment were major source in different size fractions, especially in silt (10-63 μm) samples. Gowrie Creek as covers southern-upstream part of the catchment was a major contributor at the outlet of the catchment in finest size fraction (<10 μm) Large differences between the contributions of suspended sediments from upper tributaries in different size fractions necessitate the selection of appropriate size fraction on sediment tracing in the catchment and also major effect of particle size on the movement and deposition of sediments.

COMPARATIVE TOXICITY OF SIZE FRACTIONATED AIRBORNE PARTICULATE MATTER OBTAINED FROM DIFFERENT CITIES IN THE USA

EPA Science Inventory

This paper is the result of a collaboration to assess effects of size fractionated PM from different locations on murine pulmonary inflammatory responses. In the course of this, they also determined the chemical makeup of each of the samples.

Confidence Interval Coverage for Cohen's Effect Size Statistic

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2006-01-01

Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population…

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

NASA Astrophysics Data System (ADS)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Micro-computed tomography characterization of tissue engineering scaffolds: effects of pixel size and rotation step.

PubMed

Cengiz, Ibrahim Fatih; Oliveira, Joaquim Miguel; Reis, Rui L

2017-08-01

Quantitative assessment of micro-structure of materials is of key importance in many fields including tissue engineering, biology, and dentistry. Micro-computed tomography (µ-CT) is an intensively used non-destructive technique. However, the acquisition parameters such as pixel size and rotation step may have significant effects on the obtained results. In this study, a set of tissue engineering scaffolds including examples of natural and synthetic polymers, and ceramics were analyzed. We comprehensively compared the quantitative results of µ-CT characterization using 15 acquisition scenarios that differ in the combination of the pixel size and rotation step. The results showed that the acquisition parameters could statistically significantly affect the quantified mean porosity, mean pore size, and mean wall thickness of the scaffolds. The effects are also practically important since the differences can be as high as 24% regarding the mean porosity in average, and 19.5 h and 166 GB regarding the characterization time and data storage per sample with a relatively small volume. This study showed in a quantitative manner the effects of such a wide range of acquisition scenarios on the final data, as well as the characterization time and data storage per sample. Herein, a clear picture of the effects of the pixel size and rotation step on the results is provided which can notably be useful to refine the practice of µ-CT characterization of scaffolds and economize the related resources.

Power and sample size for multivariate logistic modeling of unmatched case-control studies.

PubMed

Gail, Mitchell H; Haneuse, Sebastien

2017-01-01

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

Effect of magnetic anisotropy and particle size distribution on temperature dependent magnetic hyperthermia in Fe3O4 ferrofluids

NASA Astrophysics Data System (ADS)

Palihawadana Arachchige, Maheshika; Nemala, Humeshkar; Naik, Vaman; Naik, Ratna

Magnetic hyperthermia (MHT) has a great potential as a non-invasive cancer therapy technique. Specific absorption rate (SAR) which measures the efficiency of heat generation, mainly depends on magnetic properties of nanoparticles such as saturation magnetization (Ms) and magnetic anisotropy (K) which depend on the size and shape. Therefore, MHT applications of magnetic nanoparticles often require a controllable synthesis to achieve desirable magnetic properties. We have synthesized Fe3O4 nanoparticles using two different methods, co-precipitation (CP) and hydrothermal (HT) techniques to produce similar XRD crystallite size of 12 nm, and subsequently coated with dextran to prepare ferrofluids for MHT. However, TEM measurements show average particle sizes of 13.8 +/-3.6 nm and 14.6 +/-3.6 nm for HT and CP samples, implying the existence of an amorphous surface layer for both. The MHT data show the two samples have very different SAR values of 110 W/g (CP) and 40W/g (HT) at room temperature, although they have similar Ms of 70 +/-4 emu/g regardless of their different TEM sizes. We fitted the temperature dependent SAR using linear response theory to explain the observed results. CP sample shows a larger magnetic core with a narrow size distribution and a higher K value compared to that of HT sample.

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

PubMed Central

Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian; Tiedje, James M.

2016-01-01

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. PMID:27313569

Topological Analysis and Gaussian Decision Tree: Effective Representation and Classification of Biosignals of Small Sample Size.

PubMed

Zhang, Zhifei; Song, Yang; Cui, Haochen; Wu, Jayne; Schwartz, Fernando; Qi, Hairong

2017-09-01

Bucking the trend of big data, in microdevice engineering, small sample size is common, especially when the device is still at the proof-of-concept stage. The small sample size, small interclass variation, and large intraclass variation, have brought biosignal analysis new challenges. Novel representation and classification approaches need to be developed to effectively recognize targets of interests with the absence of a large training set. Moving away from the traditional signal analysis in the spatiotemporal domain, we exploit the biosignal representation in the topological domain that would reveal the intrinsic structure of point clouds generated from the biosignal. Additionally, we propose a Gaussian-based decision tree (GDT), which can efficiently classify the biosignals even when the sample size is extremely small. This study is motivated by the application of mastitis detection using low-voltage alternating current electrokinetics (ACEK) where five categories of bisignals need to be recognized with only two samples in each class. Experimental results demonstrate the robustness of the topological features as well as the advantage of GDT over some conventional classifiers in handling small dataset. Our method reduces the voltage of ACEK to a safe level and still yields high-fidelity results with a short assay time. This paper makes two distinctive contributions to the field of biosignal analysis, including performing signal processing in the topological domain and handling extremely small dataset. Currently, there have been no related works that can efficiently tackle the dilemma between avoiding electrochemical reaction and accelerating assay process using ACEK.

Constraining Ω0 with the Angular Size-Redshift Relation of Double-lobed Quasars in the FIRST Survey

NASA Astrophysics Data System (ADS)

Buchalter, Ari; Helfand, David J.; Becker, Robert H.; White, Richard L.

1998-02-01

In previous attempts to measure cosmological parameters from the angular size-redshift (θ-z) relation of double-lobed radio sources, the observed data have generally been consistent with a static Euclidean universe rather than with standard Friedmann models, and past authors have disagreed significantly as to what effects are responsible for this observation. These results and different interpretations may be due largely to a variety of selection effects and differences in the sample definitions destroying the integrity of the data sets, and inconsistencies in the analysis undermining the results. Using the VLA FIRST survey, we investigate the θ-z relation for a new sample of double-lobed quasars. We define a set of 103 sources, carefully addressing the various potential problems that, we believe, have compromised past work, including a robust definition of size and the completeness and homogeneity of the sample, and further devise a self-consistent method to assure accurate morphological classification and account for finite resolution effects in the analysis. Before focusing on cosmological constraints, we investigate the possible impact of correlations among the intrinsic properties of these sources over the entire assumed range of allowed cosmological parameter values. For all cases, we find apparent size evolution of the form l ~ (1 + z)c, with c ~ -0.8 +/- 0.4, which is found to arise mainly from a power-size correlation of the form l ~ Pβ (β ~ - 0.13 +/- 0.06) coupled with a power-redshift correlation. Intrinsic size evolution is consistent with zero. We also find that in all cases, a subsample with c ~ 0 can be defined, whose θ-z relation should therefore arise primarily from cosmological effects. These results are found to be independent of orientation effects, although other evidence indicates that orientation effects are present and consistent with predictions of the unified scheme for radio-loud active galactic nuclei. The above results are all confirmed by nonparametric analysis. Contrary to past work, we find that the observed θ-z relation for our sample is more consistent with standard Friedmann models than with a static Euclidean universe. Though the current data cannot distinguish with high significance between various Friedmann models, significant constraints on the cosmological parameters within a given model are obtained. In particular, we find that a flat, matter-dominated universe (Ω0 = 1), a flat universe with a cosmological constant, and an open universe all provide comparably good fits to the data, with the latter two models both yielding Ω0 ~ 0.35 with 1 σ ranges including values between ~0.25 and 1.0; the c ~ 0 subsamples yield values of Ω0 near unity in these models, though with even greater error ranges. We also examine the values of H0 implied by the data, using plausible assumptions about the intrinsic source sizes, and find these to be consistent with the currently accepted range of values. We determine the sample size needed to improve significantly the results and outline future strategies for such work.

Beneficial effects of polyethylene packages containing micrometer-sized silver particles on the quality and shelf life of dried barberry (Berberis vulgaris).

PubMed

Motlagh, N Valipoor; Mosavian, M T Hamed; Mortazavi, S A; Tamizi, A

2012-01-01

In this research, the effects of low-density polyethylene (LDPE) packages containing micrometer-sized silver particles (LDPE-Ag) on microbial and sensory factors of dried barberry were investigated in comparison with the pure LDPE packages. LDPE-Ag packages with 1% and 2% concentrations of silver particles statistically caused a decrease in the microbial growth of barberry, especially in the case of mold and total bacteria count, compared with the pure LDPE packages. The taste, aroma, appearance, and total acceptance were evaluated by trained panelists using the 9-point hedonic scale. This test showed improvement of all these factors in the samples related to packages containing 1% and 2% concentrations of silver particles in comparison with other samples. Low-density polyethylene package containing micrometer-sized silver particles had beneficial effects on the sensory and microbial quality of barberry when compared with normal packing material. © 2011 Institute of Food Technologists®

Are catchment-wide erosion rates really "Catchment-Wide"? Effects of grain size on erosion rates determined from 10Be

NASA Astrophysics Data System (ADS)

Reitz, M. A.; Seeber, L.; Schaefer, J. M.; Ferguson, E. K.

2012-12-01

Early studies pioneering the method for catchment wide erosion rates by measuring 10Be in alluvial sediment were taken at river mouths and used the sand size grain fraction from the riverbeds in order to average upstream erosion rates and measure erosion patterns. Finer particles (<0.0625 mm) were excluded to reduce the possibility of a wind-blown component of sediment and coarser particles (>2 mm) were excluded to better approximate erosion from the entire upstream catchment area (coarse grains are generally found near the source). Now that the sensitivity of 10Be measurements is rapidly increasing, we can precisely measure erosion rates from rivers eroding active tectonic regions. These active regions create higher energy drainage systems that erode faster and carry coarser sediment. In these settings, does the sand-sized fraction fully capture the average erosion of the upstream drainage area? Or does a different grain size fraction provide a more accurate measure of upstream erosion? During a study of the Neto River in Calabria, southern Italy, we took 8 samples along the length of the river, focusing on collecting samples just below confluences with major tributaries, in order to use the high-resolution erosion rate data to constrain tectonic motion. The samples we measured were sieved to either a 0.125 mm - 0.710 mm fraction or the 0.125 mm - 4 mm fraction (depending on how much of the former was available). After measuring these 8 samples for 10Be and determining erosion rates, we used the approach by Granger et al. [1996] to calculate the subcatchment erosion rates between each sample point. In the subcatchments of the river where we used grain sizes up to 4 mm, we measured very low 10Be concentrations (corresponding to high erosion rates) and calculated nonsensical subcatchment erosion rates (i.e. negative rates). We, therefore, hypothesize that the coarser grain sizes we included are preferentially sampling a smaller upstream area, and not the entire upstream catchment, which is assumed when measurements are based solely on the sand sized fraction. To test this hypothesis, we used samples with a variety of grain sizes from the Shillong Plateau. We sieved 5 samples into three grain size fractions: 0.125 mm - 710 mm, 710 mm - 4 mm, and >4 mm and measured 10Be concentrations in each fraction. Although there is some variation in the grain size fraction that yields the highest erosion rate, generally, the coarser grain size fractions have higher erosion rates. More significant are the results when calculating the subcatchment erosion rates, which suggest that even medium sized grains (710 mm - 4 mm) are sampling an area smaller than the entire upstream area; this finding is consistent with the nonsensical results from the Neto River study. This result has numerous implications for the interpretations of 10Be erosion rates: most importantly, an alluvial sample may not be averaging the entire upstream area, even when using the sand size fraction - resulting erosion rates more pertinent for that sample point rather than the entire catchment.

Effects of grain size on the properties of bulk nanocrystalline Co-Ni alloys

NASA Astrophysics Data System (ADS)

Qiao, Gui-Ying; Xiao, Fu-Ren

2017-08-01

Bulk nanocrystalline Co78Ni22 alloys with grain size ranging from 5 nm to 35 nm were prepared by high-speed jet electrodeposition (HSJED) and annealing. Microhardness and magnetic properties of these alloys were investigated by microhardness tester and vibrating sample magnetometer. Effects of grain size on these characteristics were also discussed. Results show that the microhardness of nanocrystalline Co78Ni22 alloys increases following a d -1/2-power law with decreasing grain size d. This phenomenon fits the Hall-Petch law when the grain size ranges from 5 nm to 35 nm. However, coercivity H c increases following a 1/d-power law with increasing grain size when the grain size ranges from 5 nm to 15.9 nm. Coercivity H c decreases again for grain sizes above 16.6 nm according to the d 6-power law.

Variability in group size and the evolution of collective action.

PubMed

Peña, Jorge; Nöldeke, Georg

2016-01-21

Models of the evolution of collective action typically assume that interactions occur in groups of identical size. In contrast, social interactions between animals occur in groups of widely dispersed size. This paper models collective action problems as two-strategy multiplayer games and studies the effect of variability in group size on the evolution of cooperative behavior under the replicator dynamics. The analysis identifies elementary conditions on the payoff structure of the game implying that the evolution of cooperative behavior is promoted or inhibited when the group size experienced by a focal player is more or less variable. Similar but more stringent conditions are applicable when the confounding effect of size-biased sampling, which causes the group-size distribution experienced by a focal player to differ from the statistical distribution of group sizes, is taken into account. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of a Multidisciplinary Approach to Improve Volume of Diagnostic Material in CT-Guided Lung Biopsies.

PubMed

Ferguson, Philip E; Sales, Catherine M; Hodges, Dalton C; Sales, Elizabeth W

2015-01-01

Recent publications have emphasized the importance of a multidisciplinary strategy for maximum conservation and utilization of lung biopsy material for advanced testing, which may determine therapy. This paper quantifies the effect of a multidisciplinary strategy implemented to optimize and increase tissue volume in CT-guided transthoracic needle core lung biopsies. The strategy was three-pronged: (1) once there was confidence diagnostic tissue had been obtained and if safe for the patient, additional biopsy passes were performed to further increase volume of biopsy material, (2) biopsy material was placed in multiple cassettes for processing, and (3) all tissue ribbons were conserved when cutting blocks in the histology laboratory. This study quantifies the effects of strategies #1 and #2. This retrospective analysis comparing CT-guided lung biopsies from 2007 and 2012 (before and after multidisciplinary approach implementation) was performed at a single institution. Patient medical records were reviewed and main variables analyzed include biopsy sample size, radiologist, number of blocks submitted, diagnosis, and complications. The biopsy sample size measured was considered to be directly proportional to tissue volume in the block. Biopsy sample size increased 2.5 fold with the average total biopsy sample size increasing from 1.0 cm (0.9-1.1 cm) in 2007 to 2.5 cm (2.3-2.8 cm) in 2012 (P<0.0001). The improvement was statistically significant for each individual radiologist. During the same time, the rate of pneumothorax requiring chest tube placement decreased from 15% to 7% (P = 0.065). No other major complications were identified. The proportion of tumor within the biopsy material was similar at 28% (23%-33%) and 35% (30%-40%) for 2007 and 2012, respectively. The number of cases with at least two blocks available for testing increased from 10.7% to 96.4% (P<0.0001). The effect of this multidisciplinary strategy to CT-guided lung biopsies was effective in significantly increasing tissue volume and number of blocks available for advanced diagnostic testing.

Zooplankton Grazing Effects on Particle Size Spectra under Different Seasonal Conditions

NASA Astrophysics Data System (ADS)

Stamieszkin, K.; Poulton, N.; Pershing, A. J.

2016-02-01

Oceanic particle size spectra can be used to explain and predict variability in carbon export efficiency, since larger particles are more likely to sink to depth than small particles. The distribution of biogenic particle size in the surface ocean is the result of many variables and processes, including nutrient availability, primary productivity, aggregation, remineralization, and grazing. We conducted a series of grazing experiments to test the hypothesis that mesozooplankton shift particle size spectra toward larger particles, via grazing and egestion of relatively large fecal pellets. These experiments were carried out over several months, and used natural communities of mesozooplankton and their microbial prey, collected offshore of the Damariscotta River in the Gulf of Maine. We analyzed the samples using Fluid Imaging Technologies' FlowCam®, a particle imaging system. With this equipment, we processed live samples, decreasing the likelihood of losing or damaging fragile particles, and thereby lessening sources of error in commonly used preservation and enumeration protocols. Our results show how the plankton size spectrum changes as the Gulf of Maine progresses through a seasonal cycle. We explore the relationship of grazing community size structure to its effect on the overall biogenic particle size spectrum. At some times of year, mesozooplankton grazing does not alter the particle size spectrum, while at others it significantly does, affecting the potential for biogenic flux. We also examine prey selectivity, and find that chain diatoms are the only prey group preferentially consumed. Otherwise, we find that complete mesozooplankton communities are "evolved" to fit their prey such that most prey groups are grazed evenly. We discuss a metabolic numerical model which could be used to universalize the relationships between whole gazer and whole microbial communities, with respect to effects on particle size spectra.

USE OF EXPERT RATINGS AS SAMPLING STRATA FOR A MORE COST-EFFECTIVE PROBABILITY SAMPLE OF A RARE POPULATION

PubMed Central

McCaffrey, Daniel; Perlman, Judith; Marshall, Grant N.; Hambarsoomians, Katrin

2010-01-01

We consider situations in which externally observable characteristics allow experts to quickly categorize individual households as likely or unlikely to contain a member of a rare target population. This classification can form the basis of disproportionate stratified sampling such that households classified as “unlikely” are sampled at a lower rate than those classified as “likely,” thereby reducing screening costs. Design weights account for this approach and allow unbiased estimates for the target population. We demonstrate that with sensitivity and specificity of expert classification at least 70%, and ideally at least 80%, our approach can economically increase effective sample size for a rare population. We develop heuristics for implementing this approach and demonstrate that sensitivity drives design effects and screening costs whereas specificity only drives the latter. We demonstrate that the potential gains from this approach increase as the target population becomes rarer. We further show that for most applications, unlikely strata should be sampled at 1/6 to ½ the rate of likely strata. This approach was applied to a survey of Cambodian immigrants in which the 82% of households rated “unlikely” were sampled at ¼ the rate as “likely” households, reducing screening from 9.4 to 4.0 approaches per complete. Sensitivity and specificity were 86% and 91% respectively. Weighted estimation had a design effect of 1.26 so screening costs per effective sample size were reduced 47%. We also note that in this instance, expert classification appeared to be uncorrelated with survey outcomes of interest among eligibles. PMID:20936050

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

PubMed

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.

Effect of flaw size and temperature on the matrix cracking behavior of a brittle ceramic matrix composite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anandakumar, U.; Webb, J.E.; Singh, R.N.

The matrix cracking behavior of a zircon matrix - uniaxial SCS 6 fiber composite was studied as a function of initial flaw size and temperature. The composites were fabricated by a tape casting and hot pressing technique. Surface flaws of controlled size were introduced using a vicker`s indenter. The composite samples were tested in three point flexure at three different temperatures to study the non steady state and steady state matrix cracking behavior. The composite samples exhibited steady state and non steady matrix cracking behavior at all temperatures. The steady state matrix cracking stress and steady state crack size increasedmore » with increasing temperature. The results of the study correlated well with the results predicted by the matrix cracking models.« less

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

PubMed

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.

Bivariate mass-size relation as a function of morphology as determined by Galaxy Zoo 2 crowdsourced visual classifications

NASA Astrophysics Data System (ADS)

Beck, Melanie; Scarlata, Claudia; Fortson, Lucy; Willett, Kyle; Galloway, Melanie

2016-01-01

It is well known that the mass-size distribution evolves as a function of cosmic time and that this evolution is different between passive and star-forming galaxy populations. However, the devil is in the details and the precise evolution is still a matter of debate since this requires careful comparison between similar galaxy populations over cosmic time while simultaneously taking into account changes in image resolution, rest-frame wavelength, and surface brightness dimming in addition to properly selecting representative morphological samples.Here we present the first step in an ambitious undertaking to calculate the bivariate mass-size distribution as a function of time and morphology. We begin with a large sample (~3 x 105) of SDSS galaxies at z ~ 0.1. Morphologies for this sample have been determined by Galaxy Zoo crowdsourced visual classifications and we split the sample not only by disk- and bulge-dominated galaxies but also in finer morphology bins such as bulge strength. Bivariate distribution functions are the only way to properly account for biases and selection effects. In particular, we quantify the mass-size distribution with a version of the parametric Maximum Likelihood estimator which has been modified to account for measurement errors as well as upper limits on galaxy sizes.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

PubMed

Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Investigation of the effects of the macrophysical and microphysical properties of cirrus clouds on the retrieval of optical properties: Results for FIRE 2

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Stephens, Graeme L.

1993-01-01

Due to the prevalence and persistence of cirrus cloudiness across the globe, cirrus clouds are believed to have an important effect on the climate. Stephens et al., (1990) among others have shown that the important factor determining how cirrus clouds modulate the climate is the balance between the albedo and emittance effect of the cloud systems. This factor was shown to depend in part upon the effective sizes of the cirrus cloud particles. Since effective sizes of cirrus cloud microphysical distributions are used as a basis of parameterizations in climate models, it is crucial that the relationships between effective sizes and radiative properties be clearly established. In this preliminary study, the retrieval of cirrus cloud effective sizes are examined using a two dimensional radiative transfer model for a cirrus cloud case sampled during FIRE Cirrus 11. The purpose of this paper is to present preliminary results from the SHSG model demonstrating the sensitivity of the bispectral relationships of reflected radiances and thus the retrieval of effective sizes to phase function and dimensionality.

Phase Composition, Crystallite Size and Physical Properties of B2O3-added Forsterite Nano-ceramics

NASA Astrophysics Data System (ADS)

Pratapa, S.; Chairunnisa, A.; Nurbaiti, U.; Handoko, W. D.

2018-05-01

This study was aimed to know the effect of B2O3 addition on the phase composition, crystallite size and dielectric properties of forsterite (Mg2SiO4) nano-ceramics. It utilized a purified silica sand from Tanah Laut, South Kalimantan as the source of (amorphous) silica and a magnesium oxide (MgO) powder. They were thoroughly mixed and milled prior to calcination. The addition of 1, 2, 3, and 4 wt% B2O3 to the calcined powder was done before uniaxial pressing and then sintering at 950 °C for 4 h. The phase composition and forsterite crystallite size, the microstructure and the dielectric constant of the sintered samples were characterized using X-ray diffractometer (XRD), Scanning Electron Microscope (SEM) and Vector Network Analyzer (VNA), respectively. Results showed that all samples contained forsterite, periclase (MgO) and proto enstatite (MgSiO3) with different weight fractions and forsterite crystallite size. In general, the weight fraction and crystallite size of forsterite increased with increasing B2O3 addition. The weight fraction and crystallite size of forsterite in the 4%-added sample reached 99% wt and 164 nm. Furthermore, the SEM images showed that the average grain size became slightly larger and the ceramics also became slightly denser as more B2O3 was added. The results are in accordance with density measurements using the Archimedes method which showed that the 4% ceramic exhibited 1.845 g/cm3 apparent density, while the 1% ceramic 1.681 g/cm3. We also found that the higher the density, the higher the average dielectric constant, i.e. it was 4.6 for the 1%-added sample and 6.4 for the 4%-added sample.

Repopulation of calibrations with samples from the target site: effect of the size of the calibration.

NASA Astrophysics Data System (ADS)

Guerrero, C.; Zornoza, R.; Gómez, I.; Mataix-Solera, J.; Navarro-Pedreño, J.; Mataix-Beneyto, J.; García-Orenes, F.

2009-04-01

Near infrared (NIR) reflectance spectroscopy offers important advantages because is a non-destructive technique, the pre-treatments needed in samples are minimal, and the spectrum of the sample is obtained in less than 1 minute without the needs of chemical reagents. For these reasons, NIR is a fast and cost-effective method. Moreover, NIR allows the analysis of several constituents or parameters simultaneously from the same spectrum once it is obtained. For this, a needed steep is the development of soil spectral libraries (set of samples analysed and scanned) and calibrations (using multivariate techniques). The calibrations should contain the variability of the target site soils in which the calibration is to be used. Many times this premise is not easy to fulfil, especially in libraries recently developed. A classical way to solve this problem is through the repopulation of libraries and the subsequent recalibration of the models. In this work we studied the changes in the accuracy of the predictions as a consequence of the successive addition of samples to repopulation. In general, calibrations with high number of samples and high diversity are desired. But we hypothesized that calibrations with lower quantities of samples (lower size) will absorb more easily the spectral characteristics of the target site. Thus, we suspect that the size of the calibration (model) that will be repopulated could be important. For this reason we also studied this effect in the accuracy of predictions of the repopulated models. In this study we used those spectra of our library which contained data of soil Kjeldahl Nitrogen (NKj) content (near to 1500 samples). First, those spectra from the target site were removed from the spectral library. Then, different quantities of samples of the library were selected (representing the 5, 10, 25, 50, 75 and 100% of the total library). These samples were used to develop calibrations with different sizes (%) of samples. We used partial least squares regression, and leave-one-out cross validation as methods of calibration. Two methods were used to select the different quantities (size of models) of samples: (1) Based on Characteristics of Spectra (BCS), and (2) Based on NKj Values of Samples (BVS). Both methods tried to select representative samples. Each of the calibrations (containing the 5, 10, 25, 50, 75 or 100% of the total samples of the library) was repopulated with samples from the target site and then recalibrated (by leave-one-out cross validation). This procedure was sequential. In each step, 2 samples from the target site were added to the models, and then recalibrated. This process was repeated successively 10 times, being 20 the total number of samples added. A local model was also created with the 20 samples used for repopulation. The repopulated, non-repopulated and local calibrations were used to predict the NKj content in those samples from the target site not included in repopulations. For the measurement of the accuracy of the predictions, the r2, RMSEP and slopes were calculated comparing predicted with analysed NKj values. This scheme was repeated for each of the four target sites studied. In general, scarce differences can be found between results obtained with BCS and BVS models. We observed that the repopulation of models increased the r2 of the predictions in sites 1 and 3. The repopulation caused scarce changes of the r2 of the predictions in sites 2 and 4, maybe due to the high initial values (using non-repopulated models r2 >0.90). As consequence of repopulation, the RMSEP decreased in all the sites except in site 2, where a very low RMESP was obtained before the repopulation (0.4 g×kg-1). The slopes trended to approximate to 1, but this value was reached only in site 4 and after the repopulation with 20 samples. In sites 3 and 4, accurate predictions were obtained using the local models. Predictions obtained with models using similar size of samples (similar %) were averaged with the aim to describe the main patterns. The r2 of predictions obtained with models of higher size were not more accurate than those obtained with models of lower size. After repopulation, the RMSEP of predictions using models with lower sizes (5, 10 and 25% of samples of the library) were lower than RMSEP obtained with higher sizes (75 and 100%), indicating that small models can easily integrate the variability of the soils from the target site. The results suggest that calibrations of small size could be repopulated and "converted" in local calibrations. According to this, we can focus most of the efforts in the obtainment of highly accurate analytical values in a reduced set of samples (including some samples from the target sites). The patterns observed here are in opposition with the idea of global models. These results could encourage the expansion of this technique, because very large data based seems not to be needed. Future studies with very different samples will help to confirm the robustness of the patterns observed. Authors acknowledge to "Bancaja-UMH" for the financial support of the project "NIRPROS".

Zinc-Nucleated D 2 and H 2 Crystal Formation from Their Liquids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernat, T. P.; Petta, N.; Kozioziemski, B.

Calorimetric measurements at University of Rochester Laboratory for Laser Energetics of D 2 crystallization from the melt indicate that zinc can act as a heterogeneous nucleation seed with suppressed supercooling. We further studied in this paper this effect for a variety of zinc substrates using the optical-access cryogenic sample cell at Lawrence Livermore National Laboratory. Small supercoolings are observed, some as low as 5 mK, but results depend on the zinc history and sample preparation. In general, thin samples prepared by physical vapor deposition were not effective in nucleating crystal formation. Larger (several-millimeter) granules showed greater supercooling suppression, depending onmore » surface modification and granule size. Surfaces of these granules are morphologically varied and not uniform. Scanning electron microscope images were not able to correlate any particular surface feature with enhanced nucleation. Finally, application of classical nucleation theory to the observed variation of supercooling level with granule size is consistent with nucleation features with sizes <100 nm and with wetting angles of a few degrees.« less

Effect sizes and cut-off points: a meta-analytical review of burnout in latin American countries.

PubMed

García-Arroyo, Jose; Osca Segovia, Amparo

2018-05-02

Burnout is a highly prevalent globalized health issue that causes significant physical and psychological health problems. In Latin America research on this topic has increased in recent years, however there are no studies comparing results across countries, nor normative reference cut-offs. The present meta-analysis examines the intensity of burnout (emotional exhaustion, cynicism and personal accomplishment) in 58 adult nonclinical samples from 8 countries (Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru and Venezuela). We found low intensity of burnout but there are significant differences between countries in emotional exhaustion explained by occupation and language. Social and human service professionals (police officers, social workers, public administration staff) are more exhausted than health professionals (physicians, nurses) or teachers. The samples with Portuguese language score higher in emotional exhaustion than Spanish, supporting the theory of cultural relativism. Demographics (sex, age) and study variables (sample size, instrument), were not found significant to predict burnout. The effect size and confidence intervals found are proposed as a useful baseline for research and medical diagnosis of burnout in Latin American countries.

The effect of exit beam phase aberrations on parallel beam coherent x-ray reconstructions

NASA Astrophysics Data System (ADS)

Hruszkewycz, S. O.; Harder, R.; Xiao, X.; Fuoss, P. H.

2010-12-01

Diffraction artifacts from imperfect x-ray windows near the sample are an important consideration in the design of coherent x-ray diffraction measurements. In this study, we used simulated and experimental diffraction patterns in two and three dimensions to explore the effect of phase imperfections in a beryllium window (such as a void or inclusion) on the convergence behavior of phasing algorithms and on the ultimate reconstruction. A predictive relationship between beam wavelength, sample size, and window position was derived to explain the dependence of reconstruction quality on beryllium defect size. Defects corresponding to this prediction cause the most damage to the sample exit wave and induce signature error oscillations during phasing that can be used as a fingerprint of experimental x-ray window artifacts. The relationship between x-ray window imperfection size and coherent x-ray diffractive imaging reconstruction quality explored in this work can play an important role in designing high-resolution in situ coherent imaging instrumentation and will help interpret the phasing behavior of coherent diffraction measured in these in situ environments.

The effect of exit beam phase aberrations on parallel beam coherent x-ray reconstructions.

PubMed

Hruszkewycz, S O; Harder, R; Xiao, X; Fuoss, P H

2010-12-01

Diffraction artifacts from imperfect x-ray windows near the sample are an important consideration in the design of coherent x-ray diffraction measurements. In this study, we used simulated and experimental diffraction patterns in two and three dimensions to explore the effect of phase imperfections in a beryllium window (such as a void or inclusion) on the convergence behavior of phasing algorithms and on the ultimate reconstruction. A predictive relationship between beam wavelength, sample size, and window position was derived to explain the dependence of reconstruction quality on beryllium defect size. Defects corresponding to this prediction cause the most damage to the sample exit wave and induce signature error oscillations during phasing that can be used as a fingerprint of experimental x-ray window artifacts. The relationship between x-ray window imperfection size and coherent x-ray diffractive imaging reconstruction quality explored in this work can play an important role in designing high-resolution in situ coherent imaging instrumentation and will help interpret the phasing behavior of coherent diffraction measured in these in situ environments.

Factors Associated with the Performance and Cost-Effectiveness of Using Lymphatic Filariasis Transmission Assessment Surveys for Monitoring Soil-Transmitted Helminths: A Case Study in Kenya

PubMed Central

Smith, Jennifer L.; Sturrock, Hugh J. W.; Assefa, Liya; Nikolay, Birgit; Njenga, Sammy M.; Kihara, Jimmy; Mwandawiro, Charles S.; Brooker, Simon J.

2015-01-01

Transmission assessment surveys (TAS) for lymphatic filariasis have been proposed as a platform to assess the impact of mass drug administration (MDA) on soil-transmitted helminths (STHs). This study used computer simulation and field data from pre- and post-MDA settings across Kenya to evaluate the performance and cost-effectiveness of the TAS design for STH assessment compared with alternative survey designs. Variations in the TAS design and different sample sizes and diagnostic methods were also evaluated. The district-level TAS design correctly classified more districts compared with standard STH designs in pre-MDA settings. Aggregating districts into larger evaluation units in a TAS design decreased performance, whereas age group sampled and sample size had minimal impact. The low diagnostic sensitivity of Kato-Katz and mini-FLOTAC methods was found to increase misclassification. We recommend using a district-level TAS among children 8–10 years of age to assess STH but suggest that key consideration is given to evaluation unit size. PMID:25487730

Zinc-Nucleated D 2 and H 2 Crystal Formation from Their Liquids

DOE PAGES

Bernat, T. P.; Petta, N.; Kozioziemski, B.; ...

2016-09-01

Calorimetric measurements at University of Rochester Laboratory for Laser Energetics of D 2 crystallization from the melt indicate that zinc can act as a heterogeneous nucleation seed with suppressed supercooling. We further studied in this paper this effect for a variety of zinc substrates using the optical-access cryogenic sample cell at Lawrence Livermore National Laboratory. Small supercoolings are observed, some as low as 5 mK, but results depend on the zinc history and sample preparation. In general, thin samples prepared by physical vapor deposition were not effective in nucleating crystal formation. Larger (several-millimeter) granules showed greater supercooling suppression, depending onmore » surface modification and granule size. Surfaces of these granules are morphologically varied and not uniform. Scanning electron microscope images were not able to correlate any particular surface feature with enhanced nucleation. Finally, application of classical nucleation theory to the observed variation of supercooling level with granule size is consistent with nucleation features with sizes <100 nm and with wetting angles of a few degrees.« less

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

PubMed

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. Effect Size in Efficacy Trials of Women With Decreased Sexual Desire. Sex Med Rev 2018;XX:XXX-XXX. Copyright © 2018 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Effects of lint cleaning on lint trash particle size distribution

USDA-ARS?s Scientific Manuscript database

Cotton quality trash measurements used today typically yield a single value for trash parameters for a lint sample (i.e. High Volume Instrument – percent area; Advanced Fiber Information System – total count, trash size, dust count, trash count, and visible foreign matter). A Cotton Trash Identifica...

A Systematic Review of the Relationship between Familism and Mental Health Outcomes in Latino Population

PubMed Central

Valdivieso-Mora, Esmeralda; Peet, Casie L.; Garnier-Villarreal, Mauricio; Salazar-Villanea, Monica; Johnson, David K.

2016-01-01

Background: Familismo or familism is a cultural value frequently seen in Hispanic cultures, in which a higher emphasis is placed on the family unit in terms of respect, support, obligation, and reference. Familism has been implicated as a protective factor against mental health problems and may foster the growth and development of children. This study aims at measuring the size of the relationship between familism and mental health outcomes of depression, suicide, substance abuse, internalizing, and externalizing behaviors. Methods: Thirty-nine studies were systematically reviewed to assess the relationship between familism and mental health outcomes. Data from the studies were comprised and organized into five categories: depression, suicide, internalizing symptoms, externalizing symptoms, and substance use. The Cohen's d of each value (dependent variable in comparison to familism) was calculated. Results were weighted based on sample sizes (n) and total effect sizes were then calculated. It was hypothesized that there would be a large effect size in the relationship between familism and depression, suicide, internalizing, and externalizing symptoms and substance use in Hispanics. Results: The meta-analysis showed small effect sizes in the relationship between familism and depression, suicide and internalizing behaviors. And no significant effects for substance abuse and externalizing behaviors. Discussion: The small effects found in this study may be explained by the presence of moderator variables between familism and mental health outcomes (e.g., communication within the family). In addition, variability in the Latino samples and in the measurements used might explain the small and non-significant effects found. PMID:27826269

Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature.

PubMed

Szucs, Denes; Ioannidis, John P A

2017-03-01

We have empirically assessed the distribution of published effect sizes and estimated power by analyzing 26,841 statistical records from 3,801 cognitive neuroscience and psychology papers published recently. The reported median effect size was D = 0.93 (interquartile range: 0.64-1.46) for nominally statistically significant results and D = 0.24 (0.11-0.42) for nonsignificant results. Median power to detect small, medium, and large effects was 0.12, 0.44, and 0.73, reflecting no improvement through the past half-century. This is so because sample sizes have remained small. Assuming similar true effect sizes in both disciplines, power was lower in cognitive neuroscience than in psychology. Journal impact factors negatively correlated with power. Assuming a realistic range of prior probabilities for null hypotheses, false report probability is likely to exceed 50% for the whole literature. In light of our findings, the recently reported low replication success in psychology is realistic, and worse performance may be expected for cognitive neuroscience.

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

PubMed

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

The Impact of Accelerating Faster than Exponential Population Growth on Genetic Variation

PubMed Central

Reppell, Mark; Boehnke, Michael; Zöllner, Sebastian

2014-01-01

Current human sequencing projects observe an abundance of extremely rare genetic variation, suggesting recent acceleration of population growth. To better understand the impact of such accelerating growth on the quantity and nature of genetic variation, we present a new class of models capable of incorporating faster than exponential growth in a coalescent framework. Our work shows that such accelerated growth affects only the population size in the recent past and thus large samples are required to detect the models’ effects on patterns of variation. When we compare models with fixed initial growth rate, models with accelerating growth achieve very large current population sizes and large samples from these populations contain more variation than samples from populations with constant growth. This increase is driven almost entirely by an increase in singleton variation. Moreover, linkage disequilibrium decays faster in populations with accelerating growth. When we instead condition on current population size, models with accelerating growth result in less overall variation and slower linkage disequilibrium decay compared to models with exponential growth. We also find that pairwise linkage disequilibrium of very rare variants contains information about growth rates in the recent past. Finally, we demonstrate that models of accelerating growth may substantially change estimates of present-day effective population sizes and growth times. PMID:24381333

The impact of accelerating faster than exponential population growth on genetic variation.

PubMed

Reppell, Mark; Boehnke, Michael; Zöllner, Sebastian

2014-03-01

Current human sequencing projects observe an abundance of extremely rare genetic variation, suggesting recent acceleration of population growth. To better understand the impact of such accelerating growth on the quantity and nature of genetic variation, we present a new class of models capable of incorporating faster than exponential growth in a coalescent framework. Our work shows that such accelerated growth affects only the population size in the recent past and thus large samples are required to detect the models' effects on patterns of variation. When we compare models with fixed initial growth rate, models with accelerating growth achieve very large current population sizes and large samples from these populations contain more variation than samples from populations with constant growth. This increase is driven almost entirely by an increase in singleton variation. Moreover, linkage disequilibrium decays faster in populations with accelerating growth. When we instead condition on current population size, models with accelerating growth result in less overall variation and slower linkage disequilibrium decay compared to models with exponential growth. We also find that pairwise linkage disequilibrium of very rare variants contains information about growth rates in the recent past. Finally, we demonstrate that models of accelerating growth may substantially change estimates of present-day effective population sizes and growth times.

Failure to Report Effect Sizes: The Handling of Quantitative Results in Published Health Education and Behavior Research.

PubMed

Barry, Adam E; Szucs, Leigh E; Reyes, Jovanni V; Ji, Qian; Wilson, Kelly L; Thompson, Bruce

2016-10-01

Given the American Psychological Association's strong recommendation to always report effect sizes in research, scholars have a responsibility to provide complete information regarding their findings. The purposes of this study were to (a) determine the frequencies with which different effect sizes were reported in published, peer-reviewed articles in health education, promotion, and behavior journals and (b) discuss implications for reporting effect size in social science research. Across a 4-year time period (2010-2013), 1,950 peer-reviewed published articles were examined from the following six health education and behavior journals: American Journal of Health Behavior, American Journal of Health Promotion, Health Education & Behavior, Health Education Research, Journal of American College Health, and Journal of School Health Quantitative features from eligible manuscripts were documented using Qualtrics online survey software. Of the 1,245 articles in the final sample that reported quantitative data analyses, approximately 47.9% (n = 597) of the articles reported an effect size. While 16 unique types of effect size were reported across all included journals, many of the effect sizes were reported with little frequency across most journals. Overall, odds ratio/adjusted odds ratio (n = 340, 50.1%), Pearson r/r(2) (n = 162, 23.8%), and eta squared/partial eta squared (n = 46, 7.2%) accounted for the most frequently used effect size. Quality research practice requires both testing statistical significance and reporting effect size. However, our study shows that a substantial portion of published literature in health education and behavior lacks consistent reporting of effect size. © 2016 Society for Public Health Education.

A comparison of selected MMPI-2 and MMPI-2-RF validity scales in assessing effort on cognitive tests in a military sample.

PubMed

Jones, Alvin; Ingram, M Victoria

2011-10-01

Using a relatively new statistical paradigm, Optimal Data Analysis (ODA; Yarnold & Soltysik, 2005), this research demonstrated that newly developed scales for the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and MMPI-2 Restructured Form (MMPI-2-RF) specifically designed to assess over-reporting of cognitive and/or somatic symptoms were more effective than the MMPI-2 F-family of scales in predicting effort status on tests of cognitive functioning in a sample of 288 military members. ODA demonstrated that when all scales were performing at their theoretical maximum possible level of classification accuracy, the Henry Heilbronner Index (HHI), Response Bias Scale (RBS), Fake Bad Scale (FBS), and the Symptom Validity Scale (FBS-r) outperformed the F-family of scales on a variety of ODA indexes of classification accuracy, including an omnibus measure (effect strength total, EST) of the descriptive and prognostic utility of ODA models developed for each scale. Based on the guidelines suggested by Yarnold and Soltysik for evaluating effect strengths for ODA models, the newly developed scales had effects sizes that were moderate in size (37.66 to 45.68), whereas the F-family scales had effects strengths that ranged from weak to moderate (15.42 to 32.80). In addition, traditional analysis demonstrated that HHI, RBS, FBS, and FBS-R had large effect sizes (0.98 to 1.16) based on Cohen's (1988) suggested categorization of effect size when comparing mean scores for adequate versus inadequate effort groups, whereas F-family of scales had small to medium effect sizes (0.25 to 0.76). The MMPI-2-RF Infrequent Somatic Responses Scale (F(S)) tended to perform in a fashion similar to F, the best performing F-family scale.

Ferromagnetism appears in nitrogen implanted nanocrystalline diamond films

NASA Astrophysics Data System (ADS)

Remes, Zdenek; Sun, Shih-Jye; Varga, Marian; Chou, Hsiung; Hsu, Hua-Shu; Kromka, Alexander; Horak, Pavel

2015-11-01

The nanocrystalline diamond films turn to be ferromagnetic after implanting various nitrogen doses on them. Through this research, we confirm that the room-temperature ferromagnetism of the implanted samples is derived from the measurements of magnetic circular dichroism (MCD) and superconducting quantum interference device (SQUID). Samples with larger crystalline grains as well as higher implanted doses present more robust ferromagnetic signals at room temperature. Raman spectra indicate that the small grain-sized samples are much more disordered than the large grain-sized ones. We propose that a slightly large saturated ferromagnetism could be observed at low temperature, because the increased localization effects have a significant impact on more disordered structure.

Sediment loads and transport at constructed chutes along the Missouri River - Upper Hamburg Chute near Nebraska City, Nebraska, and Kansas Chute near Peru, Nebraska

USGS Publications Warehouse

Densmore, Brenda K.; Rus, David L.; Moser, Matthew T.; Hall, Brent M.; Andersen, Michael J.

2016-02-04

Comparisons of concentrations and loads from EWI samples collected from different transects within a study site resulted in few significant differences, but comparisons are limited by small sample sizes and large within-transect variability. When comparing the Missouri River upstream transect to the chute inlet transect, similar results were determined in 2012 as were determined in 2008—the chute inlet affected the amount of sediment entering the chute from the main channel. In addition, the Kansas chute is potentially affecting the sediment concentration within the Missouri River main channel, but small sample size and construction activities within the chute limit the ability to fully understand either the effect of the chute in 2012 or the effect of the chute on the main channel during a year without construction. Finally, some differences in SSC were detected between the Missouri River upstream transects and the chute downstream transects; however, the effect of the chutes on the Missouri River main-channel sediment transport was difficult to isolate because of construction activities and sampling variability.

A robust measure of HIV-1 population turnover within chronically infected individuals.

PubMed

Achaz, G; Palmer, S; Kearney, M; Maldarelli, F; Mellors, J W; Coffin, J M; Wakeley, J

2004-10-01

A simple nonparameteric test for population structure was applied to temporally spaced samples of HIV-1 sequences from the gag-pol region within two chronically infected individuals. The results show that temporal structure can be detected for samples separated by about 22 months or more. The performance of the method, which was originally proposed to detect geographic structure, was tested for temporally spaced samples using neutral coalescent simulations. Simulations showed that the method is robust to variation in samples sizes and mutation rates, to the presence/absence of recombination, and that the power to detect temporal structure is high. By comparing levels of temporal structure in simulations to the levels observed in real data, we estimate the effective intra-individual population size of HIV-1 to be between 10(3) and 10(4) viruses, which is in agreement with some previous estimates. Using this estimate and a simple measure of sequence diversity, we estimate an effective neutral mutation rate of about 5 x 10(-6) per site per generation in the gag-pol region. The definition and interpretation of estimates of such "effective" population parameters are discussed.