The large sample size fallacy.

Science.gov (United States)

Lantz, Björn

2013-06-01

Significance in the statistical sense has little to do with significance in the common practical sense. Statistical significance is a necessary but not a sufficient condition for practical significance. Hence, results that are extremely statistically significant may be highly nonsignificant in practice. The degree of practical significance is generally determined by the size of the observed effect, not the p-value. The results of studies based on large samples are often characterized by extreme statistical significance despite small or even trivial effect sizes. Interpreting such results as significant in practice without further analysis is referred to as the large sample size fallacy in this article. The aim of this article is to explore the relevance of the large sample size fallacy in contemporary nursing research. Relatively few nursing articles display explicit measures of observed effect sizes or include a qualitative discussion of observed effect sizes. Statistical significance is often treated as an end in itself. Effect sizes should generally be calculated and presented along with p-values for statistically significant results, and observed effect sizes should be discussed qualitatively through direct and explicit comparisons with the effects in related literature. © 2012 Nordic College of Caring Science.

Sample size in qualitative interview studies

DEFF Research Database (Denmark)

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

2016-01-01

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

Relationship between sleep characteristics and measures of body size and composition in a nationally-representative sample.

Science.gov (United States)

Xiao, Qian; Gu, Fangyi; Caporaso, Neil; Matthews, Charles E

2016-01-01

Short sleep has been linked to obesity. However, sleep is a multidimensional behavior that cannot be characterized solely by sleep duration. There is limited study that comprehensively examined different sleep characteristics in relation to obesity. We examined various aspects of sleep in relation to adiposity in 2005-2006 NHANES participants who were 18 or older and free of cardiovascular disease, cancer, emphysema, chronic bronchitis and depression ( N  = 3995). Sleep characteristics were self-reported, and included duration, overall quality, onset latency, fragmentation, daytime sleepiness, snoring, and sleep disorders. Body measurements included weight, height, waist circumference, and dual-energy X-ray absorptiometry measured fat mass. Snoring was associated with higher BMI (adjusted difference in kg/m 2 comparing snoring for 5+ nights/week with no snoring (95 % confidence interval), 1.85 (0.88, 2.83)), larger waist circumference (cm, 4.52 (2.29, 6.75)), higher percentage of body fat (%, 1.61 (0.84, 2.38)), and higher android/gynoid ratio (0.03 (0.01, 0.06)). The associations were independent of sleep duration and sleep quality, and cannot be explained by the existence of sleep disorders such as sleep apnea. Poor sleep quality (two or more problematic sleep conditions) and short sleep duration (body size and fat composition, although the effects were attenuated after snoring was adjusted. In a nationally representative sample of healthy US adults, snoring, short sleep, and poor sleep quality were associated with higher adiposity.

Towards Representative Metallurgical Sampling and Gold Recovery Testwork Programmes

Directory of Open Access Journals (Sweden)

Simon C. Dominy

2018-05-01

Full Text Available When developing a process flowsheet, the risks in achieving positive financial outcomes are minimised by ensuring representative metallurgical samples and high quality testwork. The quality and type of samples used are as important as the testwork itself. The key characteristic required of any set of samples is that they represent a given domain and quantify its variability. There are those who think that stating a sample(s is representative makes it representative without justification. There is a need to consider both (1 in-situ and (2 testwork sub-sample representativity. Early ore/waste characterisation and domain definition are required, so that sampling and testwork protocols can be designed to suit the style of mineralisation in question. The Theory of Sampling (TOS provides an insight into the causes and magnitude of errors that may occur during the sampling of particulate materials (e.g., broken rock and is wholly applicable to metallurgical sampling. Quality assurance/quality control (QAQC is critical throughout all programmes. Metallurgical sampling and testwork should be fully integrated into geometallurgical studies. Traditional metallurgical testwork is critical for plant design and is an inherent part of geometallurgy. In a geometallurgical study, multiple spatially distributed small-scale tests are used as proxies for process parameters. These will be validated against traditional testwork results. This paper focusses on sampling and testwork for gold recovery determination. It aims to provide the reader with the background to move towards the design, implementation and reporting of representative and fit-for-purpose sampling and testwork programmes. While the paper does not intend to provide a definitive commentary, it critically assesses the hard-rock sampling methods used and their optimal collection and preparation. The need for representative sampling and quality testwork to avoid financial and intangible losses is

Concepts in sample size determination

Directory of Open Access Journals (Sweden)

Umadevi K Rao

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Sun Xiao

2004-03-01

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

Improved sample size determination for attributes and variables sampling

International Nuclear Information System (INIS)

Stirpe, D.; Picard, R.R.

1985-01-01

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

Socioeconomic Determinants of Bullying in the Workplace: A National Representative Sample in Japan

OpenAIRE

Tsuno, Kanami; Kawakami, Norito; Tsutsumi, Akizumi; Shimazu, Akihito; Inoue, Akiomi; Odagiri, Yuko; Yoshikawa, Toru; Haratani, Takashi; Shimomitsu, Teruichi; Kawachi, Ichiro

2015-01-01

Bullying in the workplace is an increasingly recognized threat to employee health. We sought to test three hypotheses related to the determinants of workplace bullying: power distance at work; safety climate; and frustration related to perceived social inequality. A questionnaire survey was administered to a nationally representative community-based sample of 5,000 residents in Japan aged 20-60 years. The questionnaire included questions about employment, occupation, company size, education, ...

Experimental determination of size distributions: analyzing proper sample sizes

International Nuclear Information System (INIS)

Buffo, A; Alopaeus, V

2016-01-01

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

40 CFR Appendix I to Part 261 - Representative Sampling Methods

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Representative Sampling Methods I...—Representative Sampling Methods The methods and equipment used for sampling waste materials will vary with the form and consistency of the waste materials to be sampled. Samples collected using the sampling...

[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].

Science.gov (United States)

Suzukawa, Yumi; Toyoda, Hideki

2012-04-01

This study analyzed the statistical power of research studies published in the "Japanese Journal of Psychology" in 2008 and 2009. Sample effect sizes and sample statistical powers were calculated for each statistical test and analyzed with respect to the analytical methods and the fields of the studies. The results show that in the fields like perception, cognition or learning, the effect sizes were relatively large, although the sample sizes were small. At the same time, because of the small sample sizes, some meaningful effects could not be detected. In the other fields, because of the large sample sizes, meaningless effects could be detected. This implies that researchers who could not get large enough effect sizes would use larger samples to obtain significant results.

Sample size calculations for case-control studies

Science.gov (United States)

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

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

Science.gov (United States)

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

2011-02-01

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

Optimal Sample Size for Probability of Detection Curves

International Nuclear Information System (INIS)

Annis, Charles; Gandossi, Luca; Martin, Oliver

2012-01-01

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

Obtaining Samples Representative of Contaminant Distribution in an Aquifer

International Nuclear Information System (INIS)

Schalla, Ronald; Spane, Frank A.; Narbutovskih, Susan M.; Conley, Scott F.; Webber, William D.

2002-01-01

Historically, groundwater samples collected from monitoring wells have been assumed to provide average indications of contaminant concentrations within the aquifer over the well-screen interval. In-well flow circulation, heterogeneity in the surrounding aquifer, and the sampling method utilized, however, can significantly impact the representativeness of samples as contaminant indicators of actual conditions within the surrounding aquifer. This paper identifies the need and approaches essential for providing cost-effective and technically meaningful groundwater-monitoring results. Proper design of the well screen interval is critical. An accurate understanding of ambient (non-pumping) flow conditions within the monitoring well is essential for determining the contaminant distribution within the aquifer. The ambient in-well flow velocity, flow direction and volumetric flux rate are key to this understanding. Not only do the ambient flow conditions need to be identified for preferential flow zones, but also the probable changes that will be imposed under dynamic conditions that occur during groundwater sampling. Once the in-well flow conditions are understood, effective sampling can be conducted to obtain representative samples for specific depth zones or zones of interest. The question of sample representativeness has become an important issue as waste minimization techniques such as low flow purging and sampling are implemented to combat the increasing cost of well purging and sampling at many hazardous waste sites. Several technical approaches (e.g., well tracer techniques and flowmeter surveys) can be used to determine in-well flow conditions, and these are discussed with respect to both their usefulness and limitations. Proper fluid extraction methods using minimal, (low) volume and no purge sampling methods that are used to obtain representative samples of aquifer conditions are presented

Representative mass reduction in sampling

DEFF Research Database (Denmark)

Petersen, Lars; Esbensen, Harry Kim; Dahl, Casper Kierulf

2004-01-01

We here present a comprehensive survey of current mass reduction principles and hardware available in the current market. We conduct a rigorous comparison study of the performance of 17 field and/or laboratory instruments or methods which are quantitatively characterized (and ranked) for accuracy...... dividers, the Boerner Divider, the ??spoon method??, alternate/fractional shoveling and grab sampling. Only devices based on riffle splitting principles (static or rotational) passes the ultimate representativity test (with minor, but significant relative differences). Grab sampling, the overwhelmingly...... most often used mass reduction method, performs appallingly?its use must be discontinued (with the singular exception for completely homogenized fine powders). Only proper mass reduction (i.e. carried out in complete compliance with all appropriate design principles, maintenance and cleaning rules) can...

Neuromuscular dose-response studies: determining sample size.

Science.gov (United States)

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

2011-02-01

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

Does self-selection affect samples' representativeness in online surveys? An investigation in online video game research.

Science.gov (United States)

Khazaal, Yasser; van Singer, Mathias; Chatton, Anne; Achab, Sophia; Zullino, Daniele; Rothen, Stephane; Khan, Riaz; Billieux, Joel; Thorens, Gabriel

2014-07-07

The number of medical studies performed through online surveys has increased dramatically in recent years. Despite their numerous advantages (eg, sample size, facilitated access to individuals presenting stigmatizing issues), selection bias may exist in online surveys. However, evidence on the representativeness of self-selected samples in online studies is patchy. Our objective was to explore the representativeness of a self-selected sample of online gamers using online players' virtual characters (avatars). All avatars belonged to individuals playing World of Warcraft (WoW), currently the most widely used online game. Avatars' characteristics were defined using various games' scores, reported on the WoW's official website, and two self-selected samples from previous studies were compared with a randomly selected sample of avatars. We used scores linked to 1240 avatars (762 from the self-selected samples and 478 from the random sample). The two self-selected samples of avatars had higher scores on most of the assessed variables (except for guild membership and exploration). Furthermore, some guilds were overrepresented in the self-selected samples. Our results suggest that more proficient players or players more involved in the game may be more likely to participate in online surveys. Caution is needed in the interpretation of studies based on online surveys that used a self-selection recruitment procedure. Epidemiological evidence on the reduced representativeness of sample of online surveys is warranted.

Estimating Sample Size for Usability Testing

Directory of Open Access Journals (Sweden)

Alex Cazañas

2017-02-01

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

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

Science.gov (United States)

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

2008-01-01

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

Sample size determination for mediation analysis of longitudinal data.

Science.gov (United States)

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 of the reference sample in a case-augmented study.

Science.gov (United States)

Ghosh, Palash; Dewanji, Anup

2017-05-01

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

40 CFR 80.127 - Sample size guidelines.

Science.gov (United States)

2010-07-01

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

On the representativeness of behavior observation samples in classrooms.

Science.gov (United States)

Tiger, Jeffrey H; Miller, Sarah J; Mevers, Joanna Lomas; Mintz, Joslyn Cynkus; Scheithauer, Mindy C; Alvarez, Jessica

2013-01-01

School consultants who rely on direct observation typically conduct observational samples (e.g., 1 30-min observation per day) with the hopes that the sample is representative of performance during the remainder of the day, but the representativeness of these samples is unclear. In the current study, we recorded the problem behavior of 3 referred students for 4 consecutive school days between 9:30 a.m. and 2:30 p.m. using duration recording in consecutive 10-min sessions. We then culled 10-min, 20-min, 30-min, and 60-min observations from the complete record and compared these observations to the true daily mean to assess their accuracy (i.e., how well individual observations represented the daily occurrence of target behaviors). The results indicated that when behavior occurred with low variability, the majority of brief observations were representative of the overall levels; however, when behavior occurred with greater variability, even 60-min observations did not accurately capture the true levels of behavior. © Society for the Experimental Analysis of Behavior.

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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

[Practical aspects regarding sample size in clinical research].

Science.gov (United States)

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

1996-01-01

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

Testing a groundwater sampling tool: Are the samples representative?

International Nuclear Information System (INIS)

Kaback, D.S.; Bergren, C.L.; Carlson, C.A.; Carlson, C.L.

1989-01-01

A ground water sampling tool, the HydroPunch trademark, was tested at the Department of Energy's Savannah River Site in South Carolina to determine if representative ground water samples could be obtained without installing monitoring wells. Chemical analyses of ground water samples collected with the HydroPunch trademark from various depths within a borehole were compared with chemical analyses of ground water from nearby monitoring wells. The site selected for the test was in the vicinity of a large coal storage pile and a coal pile runoff basin that was constructed to collect the runoff from the coal storage pile. Existing monitoring wells in the area indicate the presence of a ground water contaminant plume that: (1) contains elevated concentrations of trace metals; (2) has an extremely low pH; and (3) contains elevated concentrations of major cations and anions. Ground water samples collected with the HydroPunch trademark provide in excellent estimate of ground water quality at discrete depths. Groundwater chemical data collected from various depths using the HydroPunch trademark can be averaged to simulate what a screen zone in a monitoring well would sample. The averaged depth-discrete data compared favorably with the data obtained from the nearby monitoring wells

Sample size calculation in metabolic phenotyping studies.

Science.gov (United States)

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

2015-09-01

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

Sample size determination and power

CERN Document Server

Ryan, Thomas P, Jr

2013-01-01

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

Sampling device for withdrawing a representative sample from single and multi-phase flows

Science.gov (United States)

Apley, Walter J.; Cliff, William C.; Creer, James M.

1984-01-01

A fluid stream sampling device has been developed for the purpose of obtaining a representative sample from a single or multi-phase fluid flow. This objective is carried out by means of a probe which may be inserted into the fluid stream. Individual samples are withdrawn from the fluid flow by sampling ports with particular spacings, and the sampling parts are coupled to various analytical systems for characterization of the physical, thermal, and chemical properties of the fluid flow as a whole and also individually.

Notes on representing grain size distributions obtained by electron backscatter diffraction

International Nuclear Information System (INIS)

Toth, Laszlo S.; Biswas, Somjeet; Gu, Chengfan; Beausir, Benoit

2013-01-01

Grain size distributions measured by electron backscatter diffraction are commonly represented by histograms using either number or area fraction definitions. It is shown here that they should be presented in forms of density distribution functions for direct quantitative comparisons between different measurements. Here we make an interpretation of the frequently seen parabolic tales of the area distributions of bimodal grain structures and a transformation formula between the two distributions are given in this paper. - Highlights: • Grain size distributions are represented by density functions. • The parabolic tales corresponds to equal number of grains in a bin of the histogram. • A simple transformation formula is given to number and area weighed distributions. • The particularities of uniform and lognormal distributions are examined

Patch-based visual tracking with online representative sample selection

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Ou, Weihua; Yuan, Di; Li, Donghao; Liu, Bin; Xia, Daoxun; Zeng, Wu

2017-05-01

Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of discriminative methods have been proposed to deal with this problem. For the discriminative methods, it is difficult to select the representative samples for the target template updating. In general, the holistic bounding boxes that contain tracked results are selected as the positive samples. However, when the objects are occluded, this simple strategy easily introduces the noises into the training data set and the target template and then leads the tracker to drift away from the target seriously. To address this problem, we propose a robust patch-based visual tracker with online representative sample selection. Different from previous works, we divide the object and the candidates into several patches uniformly and propose a score function to calculate the score of each patch independently. Then, the average score is adopted to determine the optimal candidate. Finally, we utilize the non-negative least square method to find the representative samples, which are used to update the target template. The experimental results on the object tracking benchmark 2013 and on the 13 challenging sequences show that the proposed method is robust to the occlusion and achieves promising results.

Predicting sample size required for classification performance

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Figueroa Rosa L

2012-02-01

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

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

Science.gov (United States)

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

2012-01-01

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

Personality factors and suicide risk in a representative sample of the German general population.

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Victor Blüml

Full Text Available OBJECTIVE: Previous research has shown an association between certain personality characteristics and suicidality. Methodological differences including small sample sizes and missing adjustment for possible confounding factors could explain the varying results. The aim of this study was to assess the impact of the Big Five personality dimensions on suicidality in a representative population based sample of adults. METHOD: Interviews were conducted in a representative German population-based sample (n=2555 in 2011. Personality characteristics were assessed using the Big Five Inventory-10 (BFI-10 and suicide risk was assessed with the Suicidal Behaviors Questionnaire-Revised (SBQ-R. Multivariate logistic regression models were calculated adjusting for depression, anxiety, and various sociodemographic variables. RESULTS: Neuroticism and openness were significantly associated with suicide risk, while extraversion and conscientiousness were found to be protective. Significant sex differences were observed. For males, extraversion and conscientiousness were protective factors. Neuroticism and openness were found to be associated with suicide risk only in females. These associations remained significant after adjusting for covariates. CONCLUSION: The results highlight the role of personality dimensions as risk factors for suicide-related behaviors. Different personality dimensions are significantly associated with suicide-related behaviors even when adjusting for other known risk factors of suicidality.

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

Science.gov (United States)

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

2000-01-01

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

Sample size determination for equivalence assessment with multiple endpoints.

Science.gov (United States)

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

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

Preeminence and prerequisites of sample size calculations in clinical trials

OpenAIRE

Richa Singhal; Rakesh Rana

2015-01-01

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

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

Science.gov (United States)

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

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

Sample size for morphological traits of pigeonpea

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Giovani Facco

2015-12-01

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

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

Directory of Open Access Journals (Sweden)

Rocío Joo

2017-04-01

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

Sampling of suspended particulate matter using particle traps in the Rhône River: Relevance and representativeness for the monitoring of contaminants.

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Masson, M; Angot, H; Le Bescond, C; Launay, M; Dabrin, A; Miège, C; Le Coz, J; Coquery, M

2018-05-10

Monitoring hydrophobic contaminants in surface freshwaters requires measuring contaminant concentrations in the particulate fraction (sediment or suspended particulate matter, SPM) of the water column. Particle traps (PTs) have been recently developed to sample SPM as cost-efficient, easy to operate and time-integrative tools. But the representativeness of SPM collected with PTs is not fully understood, notably in terms of grain size distribution and particulate organic carbon (POC) content, which could both skew particulate contaminant concentrations. The aim of this study was to evaluate the representativeness of SPM characteristics (i.e. grain size distribution and POC content) and associated contaminants (i.e. polychlorinated biphenyls, PCBs; mercury, Hg) in samples collected in a large river using PTs for differing hydrological conditions. Samples collected using PTs (n = 74) were compared with samples collected during the same time period by continuous flow centrifugation (CFC). The grain size distribution of PT samples shifted with increasing water discharge: the proportion of very fine silts (2-6 μm) decreased while that of coarse silts (27-74 μm) increased. Regardless of water discharge, POC contents were different likely due to integration by PT of high POC-content phytoplankton blooms or low POC-content flood events. Differences in PCBs and Hg concentrations were usually within the range of analytical uncertainties and could not be related to grain size or POC content shifts. Occasional Hg-enriched inputs may have led to higher Hg concentrations in a few PT samples (n = 4) which highlights the time-integrative capacity of the PTs. The differences of annual Hg and PCB fluxes calculated either from PT samples or CFC samples were generally below 20%. Despite some inherent limitations (e.g. grain size distribution bias), our findings suggest that PT sampling is a valuable technique to assess reliable spatial and temporal trends of particulate

Preeminence and prerequisites of sample size calculations in clinical trials

Directory of Open Access Journals (Sweden)

Richa Singhal

2015-01-01

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

Revisiting sample size: are big trials the answer?

Science.gov (United States)

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

2012-07-18

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

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

International Nuclear Information System (INIS)

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

1981-11-01

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

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

Directory of Open Access Journals (Sweden)

R. Eric Heidel

2016-01-01

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

Determination of geostatistically representative sampling locations in Porsuk Dam Reservoir (Turkey)

Science.gov (United States)

Aksoy, A.; Yenilmez, F.; Duzgun, S.

2013-12-01

Several factors such as wind action, bathymetry and shape of a lake/reservoir, inflows, outflows, point and diffuse pollution sources result in spatial and temporal variations in water quality of lakes and reservoirs. The guides by the United Nations Environment Programme and the World Health Organization to design and implement water quality monitoring programs suggest that even a single monitoring station near the center or at the deepest part of a lake will be sufficient to observe long-term trends if there is good horizontal mixing. In stratified water bodies, several samples can be required. According to the guide of sampling and analysis under the Turkish Water Pollution Control Regulation, a minimum of five sampling locations should be employed to characterize the water quality in a reservoir or a lake. The European Union Water Framework Directive (2000/60/EC) states to select a sufficient number of monitoring sites to assess the magnitude and impact of point and diffuse sources and hydromorphological pressures in designing a monitoring program. Although existing regulations and guidelines include frameworks for the determination of sampling locations in surface waters, most of them do not specify a procedure in establishment of monitoring aims with representative sampling locations in lakes and reservoirs. In this study, geostatistical tools are used to determine the representative sampling locations in the Porsuk Dam Reservoir (PDR). Kernel density estimation and kriging were used in combination to select the representative sampling locations. Dissolved oxygen and specific conductivity were measured at 81 points. Sixteen of them were used for validation. In selection of the representative sampling locations, care was given to keep similar spatial structure in distributions of measured parameters. A procedure was proposed for that purpose. Results indicated that spatial structure was lost under 30 sampling points. This was as a result of varying water

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-15

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

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

OpenAIRE

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

1990-01-01

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

Sample size calculation for comparing two negative binomial rates.

Science.gov (United States)

Zhu, Haiyuan; Lakkis, Hassan

2014-02-10

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

Elementary representative sizes of soil attributes via attenuation of gamma rays and computerized tomography

International Nuclear Information System (INIS)

Borges, Jaqueline Aparecida Ribaski

2015-01-01

In this study, the Computed Tomography (CT) and gamma-ray attenuation (GRA) techniques were used in the investigation of representative sample sizes for attributes related to soil structure. First of all, the representative elementary length (REL) for experimental measurements of soil mass attenuation coefficient (μes), of samples from a sandy and a clayey soil, was analyzed. The study was conducted with two radioactive sources ( 241 Am and 137 Cs), three collimators (2 - 4 mm diameters), and 14 thickness (x) samples (2-5 cm). From these analyzes, it was possible to identify an ideal thickness range for each of the studied sources (2-4 cm and 12-15 cm for the sources of 241 Am and 137 Cs, respectively). The application of such results in representative elementary area evaluations, in clayey soil clods via CT, indicated that experimental soil mass attenuation coefficient average values obtained for x>4 cm and source 241 Am might induce the use of samples which are not large enough for soil bulk density evaluations. Subsequently, μCT images with a total volume of 39×39×33 mm 3 and spatial resolution of 60 μm were used for macroporous system morphological characterization of a Rhodic Ferralsol with clayey texture, under no-till (NT) and conventional till (CT) systems. Attributes as macroporosity (MAP), number of macropores (NMAP), tortuosity (τ) and connectivity (C) of the pores were assessed. The C degree was estimated based on the Euler-Poincare characteristic (EPC). Once 3D images enable the study of these attributes in different sample volumes, the proposed study is ideal for the analysis of representative elementary volume (REV). Usually, the selection of subvolumes for REV analysis occurs concentrically to a small volume or in adjacent positions. Here, we introduced a new method for selecting the positions of subvolumes, which are randomly chosen within the total image volume (random selection). It was observed that higher fluctuations in amplitude of each

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

Science.gov (United States)

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

2012-02-01

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

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

Science.gov (United States)

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

2017-01-01

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

On the Representativeness of Norming Samples for Aptitude Test

National Research Council Canada - National Science Library

Sims, William

2003-01-01

...). We regressed aptitude test scores on demographics and concluded that: ̂ Norming sample for aptitude tests must be representative of the target population with respect to age, race"ethnicity, gender, respondent's education, and mother's...

Representativeness-based sampling network design for the State of Alaska

Science.gov (United States)

Forrest M. Hoffman; Jitendra Kumar; Richard T. Mills; William W. Hargrove

2013-01-01

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection,...

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

Indian Academy of Sciences (India)

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

Representative volume element size of a polycrystalline aggregate with embedded short crack

International Nuclear Information System (INIS)

Simonovski, I.; Cizelj, L.

2007-01-01

A random polycrystalline aggregate model is proposed for evaluation of a representative volume element size (RVE) of a 316L stainless steel with embedded surface crack. RVE size is important since it defines the size of specimen where the influence of local microstructural features averages out, resulting in the same macroscopic response for geometrically similar specimen. On the other hand macroscopic responses of specimen with size smaller than RVE will, due to the microstructural features, differ significantly. Different sizes and orientations of grains, inclusions, voids,... etc are examples of such microstructural features. If a specimen size is above RVE size, classical continuum mechanics can be applied. On the other hand, advanced material models should be used for specimen with size below RVE. This paper proposes one such model, where random size, shape and orientation of grains are explicitly modeled. Crystal plasticity constitutive model is used to account for slip in the grains. RVE size is estimated by calculating the crack tip opening displacements of aggregates with different grain numbers. Progressively larger number of grains are included in the aggregates until the crack tip displacements for two consecutive aggregates of increasing size differ less than 1 %. At this point the model has reached RVE size. (author)

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

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Leonard eVanbrabant

2015-01-01

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

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

Science.gov (United States)

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

2015-11-27

Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is "saturation." Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose the concept "information power" to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning and during data collection of a qualitative study is discussed. © The Author(s) 2015.

Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

Science.gov (United States)

Morgan, Timothy M; Case, L Douglas

2013-07-05

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2017-06-01

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

Sample size choices for XRCT scanning of highly unsaturated soil mixtures

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Smith Jonathan C.

2016-01-01

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

Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

NARCIS (Netherlands)

Uijlenhoet, R.; Porrà, J.M.; Sempere Torres, D.; Creutin, J.D.

2006-01-01

A stochastic model of the microstructure of rainfall is used to derive explicit expressions for the magnitude of the sampling fluctuations in rainfall properties estimated from raindrop size measurements in stationary rainfall. The model is a marked point process, in which the points represent the

Decision Support on Small size Passive Samples

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Vladimir Popukaylo

2018-05-01

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

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

International Nuclear Information System (INIS)

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

2001-01-01

As part of the preliminary site characterization conducted for Project 57, soils samples were collected for separation into several size-fractions using the Suspended Soil Particle Sizing System (SSPSS). Soil samples were collected specifically for separation by the SSPSS at three general locations in the deposited Project 57 plume, the projected radioactivity of which ranged from 100 to 600 pCi/g. The primary purpose in focusing on samples with this level of activity is that it would represent anticipated residual soil contamination levels at the site after corrective actions are completed. Consequently, the results of the SSPSS analysis can contribute to dose calculation and corrective action-level determinations for future land-use scenarios at the site

Simple and multiple linear regression: sample size considerations.

Science.gov (United States)

Hanley, James A

2016-11-01

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

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

Science.gov (United States)

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

2016-10-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

Risk Gambling and Personality: Results from a Representative Swedish Sample.

Science.gov (United States)

Sundqvist, Kristina; Wennberg, Peter

2015-12-01

The association between personality and gambling has been explored previously. However, few studies are based on representative populations. This study aimed at examining the association between risk gambling and personality in a representative Swedish population. A random Swedish sample (N = 19,530) was screened for risk gambling using the Lie/Bet questionnaire. The study sample (N = 257) consisted of those screening positive on Lie/Bet and completing a postal questionnaire about gambling and personality (measured with the NODS-PERC and the HP5i respectively). Risk gambling was positively correlated with Negative Affectivity (a facet of Neuroticism) and Impulsivity (an inversely related facet of Conscientiousness), but all associations were weak. When taking age and gender into account, there were no differences in personality across game preference groups, though preferred game correlated with level of risk gambling. Risk gamblers scored lower than the population norm data with respect to Negative Affectivity, but risk gambling men scored higher on Impulsivity. The association between risk gambling and personality found in previous studies was corroborated in this study using a representative sample. We conclude that risk and problem gamblers should not be treated as a homogeneous group, and prevention and treatment interventions should be adapted according to differences in personality, preferred type of game and the risk potential of the games.

Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

Science.gov (United States)

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

2011-01-01

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

Phylogenetic representativeness: a new method for evaluating taxon sampling in evolutionary studies

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Passamonti Marco

2010-04-01

Full Text Available Abstract Background Taxon sampling is a major concern in phylogenetic studies. Incomplete, biased, or improper taxon sampling can lead to misleading results in reconstructing evolutionary relationships. Several theoretical methods are available to optimize taxon choice in phylogenetic analyses. However, most involve some knowledge about the genetic relationships of the group of interest (i.e., the ingroup, or even a well-established phylogeny itself; these data are not always available in general phylogenetic applications. Results We propose a new method to assess taxon sampling developing Clarke and Warwick statistics. This method aims to measure the "phylogenetic representativeness" of a given sample or set of samples and it is based entirely on the pre-existing available taxonomy of the ingroup, which is commonly known to investigators. Moreover, our method also accounts for instability and discordance in taxonomies. A Python-based script suite, called PhyRe, has been developed to implement all analyses we describe in this paper. Conclusions We show that this method is sensitive and allows direct discrimination between representative and unrepresentative samples. It is also informative about the addition of taxa to improve taxonomic coverage of the ingroup. Provided that the investigators' expertise is mandatory in this field, phylogenetic representativeness makes up an objective touchstone in planning phylogenetic studies.

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

Science.gov (United States)

Broberg, Per

2013-07-19

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

Spatiotemporally Representative and Cost-Efficient Sampling Design for Validation Activities in Wanglang Experimental Site

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Gaofei Yin

2017-11-01

Full Text Available Spatiotemporally representative Elementary Sampling Units (ESUs are required for capturing the temporal variations in surface spatial heterogeneity through field measurements. Since inaccessibility often coexists with heterogeneity, a cost-efficient sampling design is mandatory. We proposed a sampling strategy to generate spatiotemporally representative and cost-efficient ESUs based on the conditioned Latin hypercube sampling scheme. The proposed strategy was constrained by multi-temporal Normalized Difference Vegetation Index (NDVI imagery, and the ESUs were limited within a sampling feasible region established based on accessibility criteria. A novel criterion based on the Overlapping Area (OA between the NDVI frequency distribution histogram from the sampled ESUs and that from the entire study area was used to assess the sampling efficiency. A case study in Wanglang National Nature Reserve in China showed that the proposed strategy improves the spatiotemporally representativeness of sampling (mean annual OA = 74.7% compared to the single-temporally constrained (OA = 68.7% and the random sampling (OA = 63.1% strategies. The introduction of the feasible region constraint significantly reduces in-situ labour-intensive characterization necessities at expenses of about 9% loss in the spatiotemporal representativeness of the sampling. Our study will support the validation activities in Wanglang experimental site providing a benchmark for locating the nodes of automatic observation systems (e.g., LAINet which need a spatially distributed and temporally fixed sampling design.

Sample Size and Saturation in PhD Studies Using Qualitative Interviews

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Mark Mason

2010-08-01

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

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

Science.gov (United States)

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

2017-04-19

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

Sample size allocation in multiregional equivalence studies.

Science.gov (United States)

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

2018-06-17

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

Towards a representative periphytic diatom sample

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2007-01-01

Full Text Available The need to acquire a representative periphytic diatom sample for river water quality monitoring has been recognised in the development of existing diatom indices, important in the development and employment of diatom monitoring tools for the Water Framework Directive. In this study, a nested design with replication is employed to investigate the magnitude of variation in diatom biomass, composition and Trophic Diatom Index at varying scales within a small chalk river. The study shows that the use of artificial substrates may not result in diatom communities that are typical of the surrounding natural substrates. Periphytic diatom biomass and composition varies between artificial and natural substrates, riffles and glides and between two stretches of the river channel. The study also highlights the existence of high variation in diatom frustule frequency and biovolume at the individual replicate scale which may have implications for the use of diatoms in routine monitoring.

Sampling strategies for estimating brook trout effective population size

Science.gov (United States)

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

2012-01-01

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

Recruiting a representative sample in adherence research-The MALT multisite prospective cohort study experience.

Science.gov (United States)

Shemesh, Eyal; Mitchell, Jeffrey; Neighbors, Katie; Feist, Susan; Hawkins, Andre; Brown, Amanda; Wanrong, Yin; Anand, Ravinder; Stuber, Margaret L; Annunziato, Rachel A

2017-12-01

Medication adherence is an important determinant of transplant outcomes. Attempts to investigate adherence are frequently undermined by selection bias: It is very hard to recruit and retain non-adherent patients in research efforts. This manuscript presents recruitment strategies and results from the MALT (Medication Adherence in children who had a Liver Transplant) multisite prospective cohort study. MALT sites recruited 400 pediatric liver transplant patients who agreed to be followed for 2 years. The primary purpose was to determine whether a marker of adherence, the Medication Level Variability Index (MLVI), predicts rejection outcomes. The present manuscript describes methods used in MALT to ensure that a representative sample was recruited, and presents detailed recruitment results. MALT sites were able to recruit a nationally representative sample, as determined by a comparison between the MALT cohort and a national sample of transplant recipients. Strategies that helped ensure that the sample was representative included monitoring of the outcome measure in comparison with a national sample, drastically limiting patient burden, and specific recruitment methods. We discuss the importance of a representative sample in adherence research and recommend that future efforts to study adherence pay special attention to sample characteristics. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2005-01-01

The authors investigated statistical distributions for concentrations of chemical elements from the National Geochemical Survey (NGS) database of the U.S. Geological Survey. At the time of this study, the NGS data set encompasses 48,544 stream sediment and soil samples from the conterminous United States analyzed by ICP-AES following a 4-acid near-total digestion. This report includes 27 elements: Al, Ca, Fe, K, Mg, Na, P, Ti, Ba, Ce, Co, Cr, Cu, Ga, La, Li, Mn, Nb, Nd, Ni, Pb, Sc, Sr, Th, V, Y and Zn. The goal and challenge for the statistical overview was to delineate chemical distributions in a complex, heterogeneous data set spanning a large geographic range (the conterminous United States), and many different geological provinces and rock types. After declustering to create a uniform spatial sample distribution with 16,511 samples, histograms and quantile-quantile (Q-Q) plots were employed to delineate subpopulations that have coherent chemical and mineral affinities. Probability groupings are discerned by changes in slope (kinks) on the plots. Major rock-forming elements, e.g., Al, Ca, K and Na, tend to display linear segments on normal Q-Q plots. These segments can commonly be linked to petrologic or mineralogical associations. For example, linear segments on K and Na plots reflect dilution of clay minerals by quartz sand (low in K and Na). Minor and trace element relationships are best displayed on lognormal Q-Q plots. These sensitively reflect discrete relationships in subpopulations within the wide range of the data. For example, small but distinctly log-linear subpopulations for Pb, Cu, Zn and Ag are interpreted to represent ore-grade enrichment of naturally occurring minerals such as sulfides. None of the 27 chemical elements could pass the test for either normal or lognormal distribution on the declustered data set. Part of the reasons relate to the presence of mixtures of subpopulations and outliers. Random samples of the data set with successively

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

Science.gov (United States)

2015-08-01

ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal Aluminum...originator. ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal...Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal Aluminum Nitride 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

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

Science.gov (United States)

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

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

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

Science.gov (United States)

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

2015-11-01

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

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

Science.gov (United States)

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

2014-09-01

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

Sample size optimization in nuclear material control. 1

International Nuclear Information System (INIS)

Gladitz, J.

1982-01-01

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

Impact of shoe size in a sample of elderly individuals

Directory of Open Access Journals (Sweden)

Daniel López-López

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

In search of a representative sample of residential building work.

Science.gov (United States)

Lobb, Brenda; Woods, Gregory R

2012-09-01

Most research investigating injuries in construction work is limited by reliance on work samples unrepresentative of the multiple, variable-cycle tasks involved, resulting in incomplete characterisation of ergonomic exposures. In this case study, a participatory approach was used including hierarchical task analysis and site observations of a typical team of house builders in New Zealand, over several working days, to obtain a representative work sample. The builders' work consisted of 14 goal-defined jobs using varying subsets of 15 task types, each taking from less than 1 s to more than 1 h and performed in a variety of postures. Task type and duration varied within and between participants and days, although all participants spent at least 25% of the time moving from place to place, mostly carrying materials, and more than half the time either reaching up or bending down to work. This research has provided a description of residential building work based on a work sample more nearly representative than those previously published and has demonstrated a simple, low-cost but robust field observation method that can provide a valid basis for further study of hazard exposures. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

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

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

Science.gov (United States)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

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

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

Directory of Open Access Journals (Sweden)

Shvydka S.

2018-03-01

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

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

Science.gov (United States)

Wu, Yu-te; Makuch, Robert W

2010-08-01

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

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

Indian Academy of Sciences (India)

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

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

Science.gov (United States)

Algina, James; Olejnik, Stephen

2000-01-01

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

Sample size in psychological research over the past 30 years.

Science.gov (United States)

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

2011-04-01

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

A flexible method for multi-level sample size determination

International Nuclear Information System (INIS)

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

1997-01-01

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

Depression and Suicidality among Bisexual Youth: A Nationally Representative Sample

Science.gov (United States)

Taliaferro, Lindsay A.; Gloppen, Kari M.; Muehlenkamp, Jennifer J.; Eisenberg, Marla E.

2018-01-01

To address gaps in the literature on bisexual youth, we used the first nationally representative sample of high school students from the United States to determine profiles of behaviors related to depressive symptoms, a suicide attempt, and a medically-serious attempt. We examined the data from 922 bisexual students in grades 9-12 who completed…

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

Science.gov (United States)

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

2017-12-01

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

Video Games Exposure and Sexism in a Representative Sample of Adolescents.

Science.gov (United States)

Bègue, Laurent; Sarda, Elisa; Gentile, Douglas A; Bry, Clementine; Roché, Sebastian

2017-01-01

Research has indicated that many video games are saturated with stereotypes of women and that these contents may cultivate sexism. The purpose of this study was to assess the relationship between video game exposure and sexism for the first time in a large and representative sample. Our aim was also to measure the strength of this association when two other significant and well-studied sources of sexism, television exposure and religiosity, were also included in a multivariate model. A representative sample of 13520 French youth aged 11-19 years completed a survey measuring weekly video game and television exposure, religiosity, and sexist attitudes toward women. Controlling for gender and socioeconomic level, results showed that video game exposure and religiosity were both related to sexism. Implications of these results for future research on sexism in video games are discussed.

Sample Size Calculation for Controlling False Discovery Proportion

Directory of Open Access Journals (Sweden)

Shulian Shang

2012-01-01

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

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

Science.gov (United States)

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

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

Rock sampling. [method for controlling particle size distribution

Science.gov (United States)

Blum, P. (Inventor)

1971-01-01

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

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

Indian Academy of Sciences (India)

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

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

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Bruno Giacomini Sari

2017-09-01

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

Effect of sample size on bias correction performance

Science.gov (United States)

Reiter, Philipp; Gutjahr, Oliver; Schefczyk, Lukas; Heinemann, Günther; Casper, Markus C.

2014-05-01

The output of climate models often shows a bias when compared to observed data, so that a preprocessing is necessary before using it as climate forcing in impact modeling (e.g. hydrology, species distribution). A common bias correction method is the quantile matching approach, which adapts the cumulative distribution function of the model output to the one of the observed data by means of a transfer function. Especially for precipitation we expect the bias correction performance to strongly depend on sample size, i.e. the length of the period used for calibration of the transfer function. We carry out experiments using the precipitation output of ten regional climate model (RCM) hindcast runs from the EU-ENSEMBLES project and the E-OBS observational dataset for the period 1961 to 2000. The 40 years are split into a 30 year calibration period and a 10 year validation period. In the first step, for each RCM transfer functions are set up cell-by-cell, using the complete 30 year calibration period. The derived transfer functions are applied to the validation period of the respective RCM precipitation output and the mean absolute errors in reference to the observational dataset are calculated. These values are treated as "best fit" for the respective RCM. In the next step, this procedure is redone using subperiods out of the 30 year calibration period. The lengths of these subperiods are reduced from 29 years down to a minimum of 1 year, only considering subperiods of consecutive years. This leads to an increasing number of repetitions for smaller sample sizes (e.g. 2 for a length of 29 years). In the last step, the mean absolute errors are statistically tested against the "best fit" of the respective RCM to compare the performances. In order to analyze if the intensity of the effect of sample size depends on the chosen correction method, four variations of the quantile matching approach (PTF, QUANT/eQM, gQM, GQM) are applied in this study. The experiments are further

Stuttering Attitudes among Turkish Family Generations and Neighbors from Representative Samples

Science.gov (United States)

Ozdemir, R. Sertan; St. Louis, Kenneth O.; Topbas, Seyhun

2011-01-01

Purpose: Attitudes toward stuttering, measured by the "Public Opinion Survey of Human Attributes-Stuttering" ("POSHA-S"), are compared among (a) two different representative samples; (b) family generations (children, parents, and either grandparents or uncles and aunts) and neighbors; (c) children, parents, grandparents/adult…

Overestimation of test performance by ROC analysis: Effect of small sample size

International Nuclear Information System (INIS)

Seeley, G.W.; Borgstrom, M.C.; Patton, D.D.; Myers, K.J.; Barrett, H.H.

1984-01-01

New imaging systems are often observer-rated by ROC techniques. For practical reasons the number of different images, or sample size (SS), is kept small. Any systematic bias due to small SS would bias system evaluation. The authors set about to determine whether the area under the ROC curve (AUC) would be systematically biased by small SS. Monte Carlo techniques were used to simulate observer performance in distinguishing signal (SN) from noise (N) on a 6-point scale; P(SN) = P(N) = .5. Four sample sizes (15, 25, 50 and 100 each of SN and N), three ROC slopes (0.8, 1.0 and 1.25), and three intercepts (0.8, 1.0 and 1.25) were considered. In each of the 36 combinations of SS, slope and intercept, 2000 runs were simulated. Results showed a systematic bias: the observed AUC exceeded the expected AUC in every one of the 36 combinations for all sample sizes, with the smallest sample sizes having the largest bias. This suggests that evaluations of imaging systems using ROC curves based on small sample size systematically overestimate system performance. The effect is consistent but subtle (maximum 10% of AUC standard deviation), and is probably masked by the s.d. in most practical settings. Although there is a statistically significant effect (F = 33.34, P<0.0001) due to sample size, none was found for either the ROC curve slope or intercept. Overestimation of test performance by small SS seems to be an inherent characteristic of the ROC technique that has not previously been described

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

International Nuclear Information System (INIS)

Meisenberg, Oliver; Tschiersch, Jochen

2015-01-01

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

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

Science.gov (United States)

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

2013-08-01

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

A Study on the Representative Sampling Survey for Radionuclide Analysis of RI Waste

Energy Technology Data Exchange (ETDEWEB)

Jee, K. Y. [KAERI, Daejeon (Korea, Republic of); Kim, Juyoul; Jung, Gunhyo [FNC Tech. Co., Daejeon (Korea, Republic of)

2007-07-15

We developed a quantitative method for attaining a representative sample during sampling survey of RI waste. Considering a source, process, and type of RI waste, the method computes the number of sample, confidence interval, variance, and coefficient of variance. We also systematize the method of sampling survey logically and quantitatively. The result of this study can be applied to sampling survey of low- and intermediate-level waste generated from nuclear power plant during the transfer process to disposal facility.

Sample sizes and model comparison metrics for species distribution models

Science.gov (United States)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Francisco J. Ariza-López

2018-05-01

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

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

Science.gov (United States)

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

2016-02-01

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

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

Science.gov (United States)

Shieh, Gwowen

2013-01-01

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

Representative volume size: A comparison of statistical continuum mechanics and statistical physics

Energy Technology Data Exchange (ETDEWEB)

AIDUN,JOHN B.; TRUCANO,TIMOTHY G.; LO,CHI S.; FYE,RICHARD M.

1999-05-01

In this combination background and position paper, the authors argue that careful work is needed to develop accurate methods for relating the results of fine-scale numerical simulations of material processes to meaningful values of macroscopic properties for use in constitutive models suitable for finite element solid mechanics simulations. To provide a definite context for this discussion, the problem is couched in terms of the lack of general objective criteria for identifying the size of the representative volume (RV) of a material. The objective of this report is to lay out at least the beginnings of an approach for applying results and methods from statistical physics to develop concepts and tools necessary for determining the RV size, as well as alternatives to RV volume-averaging for situations in which the RV is unmanageably large. The background necessary to understand the pertinent issues and statistical physics concepts is presented.

Marital status as a candidate moderator variable of male-female differences in sexual jealousy: the need for representative population samples.

Science.gov (United States)

Voracek, M

2001-04-01

Evolutionary psychological theories predict pronounced and universal male-female differences in sexual jealousy. Recent cross-cultural research, using the forced-choice jealousy items pioneered by Buss, et al., 1992, repeatedly found a large sex differential on these self-report measures: men significantly more often than women choose their mate's imagined sexual infidelity to be more distressing or upsetting to them than an imagined emotional infidelity. However, this body of evidence is solely based on undergraduate samples and does not take into account demographic factors. This study examined male-female differences in sexual jealousy in a community sample (N = 335, Eastern Austria). Within a logistic regression model, with other variables controlled for, marital status was a stronger predictor for sexual jealousy than respondents' sex. Contrary to previous research, the sex differential's effect size was only modest. These findings stress the pitfalls of prematurely generalizing evidence from undergraduate samples to the general population and the need for representative population samples in this research area.

Myonuclear domain size and myosin isoform expression in muscle fibres from mammals representing a 100,000-fold difference in body size.

Science.gov (United States)

Liu, Jing-Xia; Höglund, Anna-Stina; Karlsson, Patrick; Lindblad, Joakim; Qaisar, Rizwan; Aare, Sudhakar; Bengtsson, Ewert; Larsson, Lars

2009-01-01

This comparative study of myonuclear domain (MND) size in mammalian species representing a 100,000-fold difference in body mass, ranging from 25 g to 2500 kg, was undertaken to improve our understanding of myonuclear organization in skeletal muscle fibres. Myonuclear domain size was calculated from three-dimensional reconstructions in a total of 235 single muscle fibre segments at a fixed sarcomere length. Irrespective of species, the largest MND size was observed in muscle fibres expressing fast myosin heavy chain (MyHC) isoforms, but in the two smallest mammalian species studied (mouse and rat), MND size was not larger in the fast-twitch fibres expressing the IIA MyHC isofom than in the slow-twitch type I fibres. In the larger mammals, the type I fibres always had the smallest average MND size, but contrary to mouse and rat muscles, type IIA fibres had lower mitochondrial enzyme activities than type I fibres. Myonuclear domain size was highly dependent on body mass in the two muscle fibre types expressed in all species, i.e. types I and IIA. Myonuclear domain size increased in muscle fibres expressing both the beta/slow (type I; r = 0.84, P fast IIA MyHC isoform (r = 0.90; P muscle fibre type, independent of species. However, myosin isoform expression is not the sole protein determining MND size, and other protein systems, such as mitochondrial proteins, may be equally or more important determinants of MND size.

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

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

Fu, Yingkun; Xie, Yanming

2011-10-01

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

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

Directory of Open Access Journals (Sweden)

Ian J Fiske

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

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

Science.gov (United States)

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

2008-08-28

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

Determining sample size for assessing species composition in ...

African Journals Online (AJOL)

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

Adherence rates to the Mediterranean diet are low in a representative sample of Greek children and adolescents

NARCIS (Netherlands)

Kontogianni, Meropi D; Vidra, Nikoletta; Farmaki, Anastasia-Eleni; Koinaki, Stella; Belogianni, Katerina; Sofrona, Stavroula; Magkanari, Flora; Yannakoulia, Mary

2008-01-01

Data from studies in pediatric samples exploring adherence to the Mediterranean diet are scarce. The aim of the present work was to explore adherence to a Mediterranean diet pattern in a representative sample of Greek children and adolescents. The study sample (n = 1305, 3-18 y) was representative

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

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

2010-06-30

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

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

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

2013-10-26

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

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

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

2018-07-01

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

Negative associations between corpus callosum midsagittal area and IQ in a representative sample of healthy children and adolescents.

Directory of Open Access Journals (Sweden)

Hooman Ganjavi

Full Text Available Documented associations between corpus callosum size and cognitive ability have heretofore been inconsistent potentially owing to differences in sample characteristics, differing methodologies in measuring CC size, or the use of absolute versus relative measures. We investigated the relationship between CC size and intelligence quotient (IQ in the NIH MRI Study of Normal Brain Development sample, a large cohort of healthy children and adolescents (aged six to 18, n = 198 recruited to be representative of the US population. CC midsagittal area was measured using an automated system that partitioned the CC into 25 subregions. IQ was measured using the Wechsler Abbreviated Scale of Intelligence (WASI. After correcting for total brain volume and age, a significant negative correlation was found between total CC midsagittal area and IQ (r = -0.147; p = 0.040. Post hoc analyses revealed a significant negative correlation in children (age<12 (r = -0.279; p = 0.004 but not in adolescents (age≥12 (r = -0.005; p = 0.962. Partitioning the subjects by gender revealed a negative correlation in males (r = -0.231; p = 0.034 but not in females (r = 0.083; p = 0.389. Results suggest that the association between CC and intelligence is mostly driven by male children. In children, a significant gender difference was observed for FSIQ and PIQ, and in males, a significant age-group difference was observed for FSIQ and PIQ. These findings suggest that the correlation between CC midsagittal area and IQ may be related to age and gender.

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

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

2016-04-25

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

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

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Hanel, Paul H P; Haase, Jennifer

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Antonio Palazón-Bru

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

Psychiatric disorders in a representative sample of incarcerated boys in the Netherlands

NARCIS (Netherlands)

Vreugdenhil, Coby; Doreleijers, Theo A. H.; Vermeiren, Robert; Wouters, Luuk F. J. M.; van den Brink, Wim

2004-01-01

Objective: To determine the prevalence of psychiatric disorders among incarcerated male adolescents and to investigate the influence of psychopathology on allocation to either plain detention or detention with compulsory treatment. Method: A cross-sectional study of a representative sample (N = 204)

Experimental verification of air flow rate measurement for representative isokinetic air sampling in ventilation stacks

International Nuclear Information System (INIS)

Okruhlica, P.; Mrtvy, M.; Kopecky, Z.

2009-01-01

Nuclear facilities are obliged to monitor their discharge's influence on environment. Main monitored factions in NPP's ventilation stacks are usually noble gasses, particulates and iodine. These factions are monitored in air sampled from ventilation stack by means of sampling rosette and bypass followed with on-line measuring monitors and balance sampling devices with laboratory evaluations. Correct air flow rate measurement and representative iso-kinetic air sampling system is essential for physical correct and metrological accurate evaluation of discharge influence on environment. Pairs of measuring sensors (Anemometer, pressure gauge, thermometer and humidity meter) are symmetrically placed in horizontal projection of stack on positions based on measured air flow velocity distribution characteristic, Analogically diameter of sampling rosette nozzles and their placement in the middle of 6 - 7 annuluses are calculated for assurance of representative iso-kinetic sampling. (authors)

Experimental verification of air flow rate measurement for representative isokinetic air sampling in ventilation stacks

International Nuclear Information System (INIS)

Okruhlica, P.; Mrtvy, M.; Kopecky, Z.

2008-01-01

Nuclear facilities are obliged to monitor their discharge's influence on environment. Main monitored factions in NPP's ventilation stacks are usually noble gasses, particulates and iodine. These factions are monitored in air sampled from ventilation stack by means of sampling rosette and bypass followed with on-line measuring monitors and balance sampling devices with laboratory evaluations. Correct air flow rate measurement and representative iso-kinetic air sampling system is essential for physical correct and metrological accurate evaluation of discharge influence on environment. Pairs of measuring sensors (Anemometer, pressure gauge, thermometer and humidity meter) are symmetrically placed in horizontal projection of stack on positions based on measured air flow velocity distribution characteristic, Analogically diameter of sampling rosette nozzles and their placement in the middle of 6- 7 annuluses are calculated for assurance of representative iso-kinetic sampling. (authors)

Early menarche and childhood adversities in a nationally representative sample

OpenAIRE

Henrichs, Kimberly L; McCauley, Heather L; Miller, Elizabeth; Styne, Dennis M; Saito, Naomi; Breslau, Joshua

2014-01-01

Background Epidemiological evidence suggests that early menarche, defined as onset of menses at age 11 or earlier, has increased in prevalence in recent birth cohorts and is associated with multiple poor medical and mental health outcomes in adulthood. There is evidence that childhood adversities occurring prior to menarche contribute to early menarche. Methods Data collected in face-to-face interviews with a nationally representative sample of women age 18 and over (N = 3288), as part of the...

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

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

2017-03-01

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

Size selective isocyanate aerosols personal air sampling using porous plastic foams

International Nuclear Information System (INIS)

Cong Khanh Huynh; Trinh Vu Duc

2009-01-01

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

An integrated approach for multi-level sample size determination

International Nuclear Information System (INIS)

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

1997-01-01

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

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

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Elias Chaibub Neto

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

Applying an Occupational Classification to a National Representative Sample of Work Histories of Young Men and Women.

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Nafziger, Dean H.; And Others

Holland's occupational classification was used to analyze the work histories of a national representative sample of young men and women age 14-24. This study extended previous tests of the classification in three ways: (1) It was applied for the first time to a national, representative sample of women, (2) For the sample of men, 3-year…

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

OpenAIRE

Taylor, Douglas J.; Muller, Keith E.

1995-01-01

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

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

Science.gov (United States)

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

2011-12-01

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

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

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

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

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

Science.gov (United States)

Mayer, B; Muche, R

2013-01-01

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

A contemporary decennial global sample of changing agricultural field sizes

Science.gov (United States)

White, E.; Roy, D. P.

2011-12-01

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

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

Science.gov (United States)

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

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

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

Science.gov (United States)

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

On sample size and different interpretations of snow stability datasets

Science.gov (United States)

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

2009-04-01

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

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

Science.gov (United States)

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

2012-02-01

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

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

Directory of Open Access Journals (Sweden)

Wang Jelai

2006-02-01

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

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

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

2014-09-01

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

Like a virgin (mother): analysis of data from a longitudinal, US population representative sample survey

OpenAIRE

Herring, Amy H; Attard, Samantha M; Gordon-Larsen, Penny; Joyner, William H; Halpern, Carolyn T

2013-01-01

Objective To estimate the incidence of self report of pregnancy without sexual intercourse (virgin pregnancy) and factors related to such reporting, in a population representative group of US adolescents and young adults. Design Longitudinal, population representative sample survey. Setting Nationally representative, multiethnic National Longitudinal Study of Adolescent Health, United States. Participants 7870 women enrolled at wave I (1995) and completing the most recent wave of data collect...

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

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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 Impact of Nutrition and Health Claims on Consumer Perceptions and Portion Size Selection: Results from a Nationally Representative Survey

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Benson, Tony; Lavelle, Fiona; McCloat, Amanda; Mooney, Elaine; Egan, Bernadette; Collins, Clare E.; Dean, Moira

2018-01-01

Nutrition and health claims on foods can help consumers make healthier food choices. However, claims may have a ‘halo’ effect, influencing consumer perceptions of foods and increasing consumption. Evidence for these effects are typically demonstrated in experiments with small samples, limiting generalisability. The current study aimed to overcome this limitation through the use of a nationally representative survey. In a cross-sectional survey of 1039 adults across the island of Ireland, respondents were presented with three different claims (nutrition claim = “Low in fat”; health claim = “With plant sterols. Proven to lower cholesterol”; satiety claim = “Fuller for longer”) on four different foods (cereal, soup, lasagne, and yoghurt). Participants answered questions on perceived healthiness, tastiness, and fillingness of the products with different claims and also selected a portion size they would consume. Claims influenced fillingness perceptions of some of the foods. However, there was little influence of claims on tastiness or healthiness perceptions or the portion size selected. Psychological factors such as consumers’ familiarity with foods carrying claims and belief in the claims were the most consistent predictors of perceptions and portion size selection. Future research should identify additional consumer factors that may moderate the relationships between claims, perceptions, and consumption. PMID:29789472

The Impact of Nutrition and Health Claims on Consumer Perceptions and Portion Size Selection: Results from a Nationally Representative Survey

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Tony Benson

2018-05-01

Full Text Available Nutrition and health claims on foods can help consumers make healthier food choices. However, claims may have a ‘halo’ effect, influencing consumer perceptions of foods and increasing consumption. Evidence for these effects are typically demonstrated in experiments with small samples, limiting generalisability. The current study aimed to overcome this limitation through the use of a nationally representative survey. In a cross-sectional survey of 1039 adults across the island of Ireland, respondents were presented with three different claims (nutrition claim = “Low in fat”; health claim = “With plant sterols. Proven to lower cholesterol”; satiety claim = “Fuller for longer” on four different foods (cereal, soup, lasagne, and yoghurt. Participants answered questions on perceived healthiness, tastiness, and fillingness of the products with different claims and also selected a portion size they would consume. Claims influenced fillingness perceptions of some of the foods. However, there was little influence of claims on tastiness or healthiness perceptions or the portion size selected. Psychological factors such as consumers’ familiarity with foods carrying claims and belief in the claims were the most consistent predictors of perceptions and portion size selection. Future research should identify additional consumer factors that may moderate the relationships between claims, perceptions, and consumption.

Detecting representative data and generating synthetic samples to improve learning accuracy with imbalanced data sets.

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Der-Chiang Li

Full Text Available It is difficult for learning models to achieve high classification performances with imbalanced data sets, because with imbalanced data sets, when one of the classes is much larger than the others, most machine learning and data mining classifiers are overly influenced by the larger classes and ignore the smaller ones. As a result, the classification algorithms often have poor learning performances due to slow convergence in the smaller classes. To balance such data sets, this paper presents a strategy that involves reducing the sizes of the majority data and generating synthetic samples for the minority data. In the reducing operation, we use the box-and-whisker plot approach to exclude outliers and the Mega-Trend-Diffusion method to find representative data from the majority data. To generate the synthetic samples, we propose a counterintuitive hypothesis to find the distributed shape of the minority data, and then produce samples according to this distribution. Four real datasets were used to examine the performance of the proposed approach. We used paired t-tests to compare the Accuracy, G-mean, and F-measure scores of the proposed data pre-processing (PPDP method merging in the D3C method (PPDP+D3C with those of the one-sided selection (OSS, the well-known SMOTEBoost (SB study, and the normal distribution-based oversampling (NDO approach, and the proposed data pre-processing (PPDP method. The results indicate that the classification performance of the proposed approach is better than that of above-mentioned methods.

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

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

2018-04-01

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

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

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Daniel P Beavers

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

Development of sample size allocation program using hypergeometric distribution

International Nuclear Information System (INIS)

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

1996-01-01

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

Recruitment of representative samples for low incidence cancer populations: Do registries deliver?

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Sanson-Fisher Rob

2011-01-01

Full Text Available Abstract Background Recruiting large and representative samples of adolescent and young adult (AYA cancer survivors is important for gaining accurate data regarding the prevalence of unmet needs in this population. This study aimed to describe recruitment rates for AYAs recruited through a cancer registry with particular focus on: active clinician consent protocols, reasons for clinicians not providing consent and the representativeness of the final sample. Methods Adolescents and young adults aged 14 to19 years inclusive and listed on the cancer registry from January 1 2002 to December 31 2007 were identified. An active clinician consent protocol was used whereby the registry sent a letter to AYAs primary treating clinicians requesting permission to contact the survivors. The registry then sent survivors who received their clinician's consent a letter seeking permission to forward their contact details to the research team. Consenting AYAs were sent a questionnaire which assessed their unmet needs. Results The overall consent rate for AYAs identified as eligible by the registry was 7.8%. Of the 411 potentially eligible survivors identified, just over half (n = 232, 56% received their clinician's consent to be contacted. Of those 232 AYAs, 65% were unable to be contacted. Only 18 AYAs (7.8% refused permission for their contact details to be passed on to the research team. Of the 64 young people who agreed to be contacted, 50% (n = 32 completed the questionnaire. Conclusions Cancer registries which employ active clinician consent protocols may not be appropriate for recruiting large, representative samples of AYAs diagnosed with cancer. Given that AYA cancer survivors are highly mobile, alternative methods such as treatment centre and clinic based recruitment may need to be considered.

Victimization and adversity among children experiencing war-related parental absence or deployment in a nationally representative US sample.

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Turner, Heather A; Finkelhor, David; Hamby, Sherry; Henly, Megan

2017-05-01

This study compares children and youth who have experienced lifetime war-related parental absence or deployment with those having no such history on a variety of victimization types, non-victimization adversity, trauma symptoms, and delinquency; and assesses whether cumulative adversity and victimization help to explain elevated emotional and behavioral problems among children of parents who have experienced war-related absence or deployment. The National Surveys of Children's Exposure to Violence (NatSCEV) are comprised of three cross-sectional telephone surveys conducted in 2008, 2011, and 2014. Data were collected on the experiences of children aged one month to seventeen years. In each survey, interviews were conducted with youth 10-17 years old and with caregivers of children 0-9 years old. The analyses use pooled data from all three U.S. nationally-representative samples (total sample size of 13,052). Lifetime parental war-related absence or deployment was a marker for elevated childhood exposure to a wide array of victimization and adversity types. Cumulative past year exposure to multiple forms of victimization and adversity fully explained elevated trauma symptoms and delinquency in this population of children. Given the breadth of victimization and adversity risk, children with histories of parental war-related absence or deployment, as well as their families, represent important target groups for broad-based prevention and interventions to reduce exposure and ameliorate consequences when it does occur. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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

2018-03-01

To determine whether novel methods of selecting joints through (i) ultrasonography (individualized-ultrasound [IUS] method), or (ii) ultrasonography and clinical examination (individualized-composite-ultrasound [ICUS] method) translate into smaller rheumatoid arthritis (RA) clinical trial sample sizes when compared to existing methods utilizing predetermined joint sites for ultrasonography. Cohen's effect size (ES) was estimated (ES^) and a 95% CI (ES^L, ES^U) calculated on a mean change in 3-month total inflammatory score for each method. Corresponding 95% CIs [nL(ES^U), nU(ES^L)] were obtained on a post hoc sample size reflecting the uncertainty in ES^. Sample size calculations were based on a one-sample t-test as the patient numbers needed to provide 80% power at α = 0.05 to reject a null hypothesis H 0 : ES = 0 versus alternative hypotheses H 1 : ES = ES^, ES = ES^L and ES = ES^U. We aimed to provide point and interval estimates on projected sample sizes for future studies reflecting the uncertainty in our study ES^S. Twenty-four treated RA patients were followed up for 3 months. Utilizing the 12-joint approach and existing methods, the post hoc sample size (95% CI) was 22 (10-245). Corresponding sample sizes using ICUS and IUS were 11 (7-40) and 11 (6-38), respectively. Utilizing a seven-joint approach, the corresponding sample sizes using ICUS and IUS methods were nine (6-24) and 11 (6-35), respectively. Our pilot study suggests that sample size for RA clinical trials with ultrasound endpoints may be reduced using the novel methods, providing justification for larger studies to confirm these observations. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

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

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Kim Seon-Young

2009-05-01

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

Two-dimensional structure and kinematics of a representative sample of low-z ULIRGs

International Nuclear Information System (INIS)

Garcia-Marin, M; Colina, L; Arribas, S

2008-01-01

We present the optical INTEGRAL integral field spectroscopy data and Hubble Space Telescope archive images obtained for a representative sample of 22 local Ultraluminous Infrared Galaxies (ULIRGs L IR >10 12 L o-dot ). The sample has been designed for fulfilling a program aimed at studying the internal structure and kinematics of this type of galaxies. Taking advantage of the two-dimensional nature of the data, we study the structure of the stellar and ionized gas, the internal ionization state and the gas kinematics. In this contribution we present the sample and the most important results obtained so far.

The prevalence of Nonsuicidal Self-Injury (NSSI in a representative sample of the German population

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Paul L. Plener

2016-10-01

Full Text Available Abstract Background Non-suicidal self-injury (NSSI is a proposed new “condition for further study” in the DSM-5. To date no prevalence data has been available on this diagnostic entity from a representative sample of the general population. Methods A representative sample of the German population (N = 2509, mean age = 48.8 years, SD = 18.1, female 55.4 % completed the NSSI section of the German version of the Self-Injurious Thoughts and Behaviors Interview (SITBI-G. Results A history of NSSI at least once during lifetime was reported by 3.1 % of all participants, with higher lifetime prevalence rates in younger age groups. DSM-5 NSSI disorder criteria were met by 0.3 %. The most common function of NSSI was automatic negative reinforcement (e.g. to alleviate negative feelings. Conclusions To the best of our knowledge, this is the first study reporting rates for the proposed NSSI category in DSM-5 from a representative sample of the general population. In comparison to findings from community samples of adolescents, adults seem to have lower lifetime prevalence rates of NSSI, thus making it necessary to emphasize prevention and treatment efforts in younger age groups.

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

International Nuclear Information System (INIS)

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

1977-01-01

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

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

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

2010-01-15

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

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

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Lawson, Chris A

2014-07-01

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

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

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Konikoff, Jacob; Brookmeyer, Ron

2015-12-01

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

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

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

2018-06-01

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

Sleepiness and Motor Vehicle Crashes in a Representative Sample of Portuguese Drivers: The Importance of Epidemiological Representative Surveys.

Science.gov (United States)

Gonçalves, M; Peralta, A R; Monteiro Ferreira, J; Guilleminault, Christian

2015-01-01

Sleepiness is considered to be a leading cause of crashes. Despite the huge amount of information collected in questionnaire studies, only some are based on representative samples of the population. Specifics of the populations studied hinder the generalization of these previous findings. For the Portuguese population, data from sleep-related car crashes/near misses and sleepiness while driving are missing. The objective of this study is to determine the prevalence of near-miss and nonfatal motor vehicle crashes related to sleepiness in a representative sample of Portuguese drivers. Structured phone interviews regarding sleepiness and sleep-related crashes and near misses, driving habits, demographic data, and sleep quality were conducted using the Pittsburgh Sleep Quality Index and sleep apnea risk using the Berlin questionnaire. A multivariate regression analysis was used to determine the associations with sleepy driving (feeling sleepy or falling asleep while driving) and sleep-related near misses and crashes. Nine hundred subjects, representing the Portuguese population of drivers, were included; 3.1% acknowledged falling asleep while driving during the previous year and 0.67% recalled sleepiness-related crashes. Higher education, driving more than 15,000 km/year, driving more frequently between 12:00 a.m. and 6 a.m., fewer years of having a driver's license, less total sleep time per night, and higher scores on the Epworth Sleepiness Scale (ESS) were all independently associated with sleepy driving. Sleepiness-related crashes and near misses were associated only with falling asleep at the wheel in the previous year. Sleep-related crashes occurred more frequently in drivers who had also had sleep-related near misses. Portugal has lower self-reported sleepiness at the wheel and sleep-related near misses than most other countries where epidemiological data are available. Different population characteristics and cultural, social, and road safety specificities may

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

Science.gov (United States)

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

2014-01-01

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

Socioeconomic determinants of bullying in the workplace: a national representative sample in Japan.

Science.gov (United States)

Tsuno, Kanami; Kawakami, Norito; Tsutsumi, Akizumi; Shimazu, Akihito; Inoue, Akiomi; Odagiri, Yuko; Yoshikawa, Toru; Haratani, Takashi; Shimomitsu, Teruichi; Kawachi, Ichiro

2015-01-01

Bullying in the workplace is an increasingly recognized threat to employee health. We sought to test three hypotheses related to the determinants of workplace bullying: power distance at work; safety climate; and frustration related to perceived social inequality. A questionnaire survey was administered to a nationally representative community-based sample of 5,000 residents in Japan aged 20-60 years. The questionnaire included questions about employment, occupation, company size, education, household income, and subjective social status (SSS). We inquired about both the witnessing and personal experience of workplace bullying during the past 30 days. Among 2,384 respondents, data were analyzed from 1,546 workers. Multiple logistic regression analyses were used to examine the social determinants of workplace bullying. Six percent and 15 percent of the total sample reported experiencing or witnessing workplace bullying, respectively. After adjusting for gender and age, temporary employees (Odds Ratio [OR]: 2.45 [95% Confidence Interval (CI) = 1.03-5.85]), junior high school graduates (OR: 2.62 [95%CI: 1.01-6.79]), workers with lowest household income (OR: 4.13 [95%CI:1.58-10.8]), and workers in the lowest SSS stratum (OR: 4.21 [95%CI:1.66-10.7]) were at increased risk of experiencing workplace bullying. When all variables were entered simultaneously in the model, a significant inverse association was observed between higher SSS and experiencing bullying (p = 0.002). Similarly in terms of witnessing bullying; SSS was significantly inversely associated (p = 0.017) while temporary employees reported a significantly higher risk of witnessing bullying compared to permanent workers (OR: 2.25 [95%CI:1.04 to 4.87]). The significant association between SSS and experiencing/witnessing workplace bullying supports the frustration hypothesis. The power distance hypothesis was also partly supported by the finding that temporary employees experienced a higher prevalence of

Socioeconomic determinants of bullying in the workplace: a national representative sample in Japan.

Directory of Open Access Journals (Sweden)

Kanami Tsuno

Full Text Available Bullying in the workplace is an increasingly recognized threat to employee health. We sought to test three hypotheses related to the determinants of workplace bullying: power distance at work; safety climate; and frustration related to perceived social inequality. A questionnaire survey was administered to a nationally representative community-based sample of 5,000 residents in Japan aged 20-60 years. The questionnaire included questions about employment, occupation, company size, education, household income, and subjective social status (SSS. We inquired about both the witnessing and personal experience of workplace bullying during the past 30 days. Among 2,384 respondents, data were analyzed from 1,546 workers. Multiple logistic regression analyses were used to examine the social determinants of workplace bullying. Six percent and 15 percent of the total sample reported experiencing or witnessing workplace bullying, respectively. After adjusting for gender and age, temporary employees (Odds Ratio [OR]: 2.45 [95% Confidence Interval (CI = 1.03-5.85], junior high school graduates (OR: 2.62 [95%CI: 1.01-6.79], workers with lowest household income (OR: 4.13 [95%CI:1.58-10.8], and workers in the lowest SSS stratum (OR: 4.21 [95%CI:1.66-10.7] were at increased risk of experiencing workplace bullying. When all variables were entered simultaneously in the model, a significant inverse association was observed between higher SSS and experiencing bullying (p = 0.002. Similarly in terms of witnessing bullying; SSS was significantly inversely associated (p = 0.017 while temporary employees reported a significantly higher risk of witnessing bullying compared to permanent workers (OR: 2.25 [95%CI:1.04 to 4.87]. The significant association between SSS and experiencing/witnessing workplace bullying supports the frustration hypothesis. The power distance hypothesis was also partly supported by the finding that temporary employees experienced a higher prevalence

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

International Nuclear Information System (INIS)

Smith, D.L.

1975-09-01

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

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

Science.gov (United States)

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

2010-11-01

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

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

NARCIS (Netherlands)

Velleman, Eric Martin; van der Geest, Thea

2013-01-01

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

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

OpenAIRE

ALWI, IDRUS

2011-01-01

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

γ-Ray spectrometry of radon in water and the role of radon to representatively sample aquifers

International Nuclear Information System (INIS)

Talha, S.A.; Lindsay, R.; Newman, R.T.; Meijer, R.J. de; Maleka, P.P.; Hlatshwayo, I.N.; Mlwilo, N.A.; Mohanty, A.K.

2008-01-01

Measurement of radon in water by γ-ray spectrometry using a HPGe detector has been investigated to determine aquifer characteristics. The radon activity concentration is determined by taking the weighted average of the concentrations derived from γ-ray lines associated with 214 Pb and 214 Bi decay. The role of accurate radon data to representatively sample aquifers was also investigated by studying a semi-cased borehole. A simplified physical model describing the change of radon concentration with the pumping time, reproduces the data and predicts the time for representative sampling of the aquifer

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

African Journals Online (AJOL)

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

Association of post-traumatic stress disorder and obesity in a nationally representative sample.

Science.gov (United States)

Pagoto, Sherry L; Schneider, Kristin L; Bodenlos, Jamie S; Appelhans, Bradley M; Whited, Matthew C; Ma, Yunsheng; Lemon, Stephenie C

2012-01-01

Recent studies suggest a possible link between post-traumatic stress disorder (PTSD) and obesity risk, which would have implications for the development of obesity-related diseases in this population. The present study examined the association between PTSD and obesity and whether this association differed by sex in a representative sample of the US population. A secondary objective was to determine whether the association between PTSD and obesity was mediated by binge eating disorder (BED). Data were from the Collaborative Psychiatric Epidemiology Surveys (CPES), which comprises three nationally representative cross-sectional surveys that were conducted between 2001 and 2003. Logistic regression analyses weighted to represent the general US adult population were performed. In the total sample of 20,013 participants, rates of obesity were 24.1% for persons without a lifetime history of PTSD and 32.6% among persons with PTSD in the past year. Adjusting for socio-demographic characteristics, depression, substance and alcohol abuse/dependence, and psychotropic medication status, past year PTSD was associated with greater likelihood of obesity (odds ratio (OR) = 1.51; 95% confidence interval (CI) = 1.18, 1.95), with no differences by gender. BED did not statistically mediate the relationship between PTSD and obesity. The present study provides support for a link between PTSD and obesity. Findings further existing literature by indicating that the association is consistent across sexes and is not statistically mediated by BED.

Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls

Directory of Open Access Journals (Sweden)

Wolfgang Gaissmeier

2011-02-01

Full Text Available We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naive recognition-based election forecasts computed from convenience samples of citizens' recognition of party names to (i standard polling forecasts computed from representative samples of citizens' voting intentions, and to (ii simple---and typically very accurate---wisdom-of-crowds-forecasts computed from the same convenience samples of citizens' aggregated hunches about election results. Results from four major German elections show that mere recognition of party names forecast the parties' electoral success fairly well. Recognition-based forecasts were most competitive with the other models when forecasting the smaller parties' success and for small sample sizes. However, wisdom-of-crowds-forecasts outperformed recognition-based forecasts in most cases. It seems that wisdom-of-crowds-forecasts are able to draw on the benefits of recognition while at the same time avoiding its downsides, such as lack of discrimination among very famous parties or recognition caused by factors unrelated to electoral success. Yet it seems that a simple extension of the recognition-based forecasts---asking people what proportion of the population would recognize a party instead of whether they themselves recognize it---is also able to eliminate these downsides.

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

Science.gov (United States)

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

2014-07-01

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

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

Directory of Open Access Journals (Sweden)

Malhotra Rajeev

2010-01-01

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

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

African Journals Online (AJOL)

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

Symptoms and problems in a nationally representative sample of advanced cancer patients

DEFF Research Database (Denmark)

Johnsen, Anna Thit; Petersen, Morten Aagaard; Pedersen, Lise

2009-01-01

Little is known about the need for palliative care among advanced cancer patients who are not in specialist palliative care. The purpose was to identify prevalence and predictors of symptoms and problems in a nationally representative sample of Danish advanced cancer patients. Patients with cancer...... or not were associated with several symptoms and problems. This is probably the first nationally representative study of its kind. It shows that advanced cancer patients in Denmark have symptoms and problems that deserve attention and that some patient groups are especially at risk....... predictors. In total, 977 (60%) patients participated. The most frequent symptoms/problems were fatigue (57%; severe 22%) followed by reduced role function, insomnia and pain. Age, cancer stage, primary tumour, type of department, marital status and whether the patient had recently been hospitalized...

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Sample size for monitoring sirex populations and their natural enemies

Directory of Open Access Journals (Sweden)

Susete do Rocio Chiarello Penteado

2016-09-01

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

76 FR 69585 - Testing and Labeling Pertaining to Product Certification Regarding Representative Samples for...

Science.gov (United States)

2011-11-08

... 1107 Testing and Labeling Pertaining to Product Certification Regarding Representative Samples for... [CPSC Docket No. CPSC-2011-0082] Testing and Labeling Pertaining to Product Certification Regarding... to Product Certification.'' The proposed rule was intended to implement what was then known as...

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

International Nuclear Information System (INIS)

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

2004-01-01

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

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

Science.gov (United States)

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

2017-12-04

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

Representativeness of two sampling procedures for an internet intervention targeting cancer-related distress: a comparison of convenience and registry samples.

Science.gov (United States)

Owen, Jason E; Bantum, Erin O'Carroll; Criswell, Kevin; Bazzo, Julie; Gorlick, Amanda; Stanton, Annette L

2014-08-01

Internet interventions often rely on convenience sampling, yet convenience samples may differ in important ways from systematic recruitment approaches. The purpose of this study was to evaluate potential demographic, medical, and psychosocial differences between Internet-recruited and registry-recruited cancer survivors in an Internet-based intervention. Participants were recruited from a cancer registry (n = 80) and via broad Internet outreach efforts (n = 160). Participants completed a set of self-report questionnaires, and both samples were compared to a population-based sample of cancer survivors (n = 5,150). The Internet sample was younger, better educated, more likely to be female, had longer time since diagnosis, and had more advanced stage of disease (p's sample was over-represented by men and those with prostate or other cancer types (p's sample also exhibited lower quality of life and social support and greater mood disturbance (p's convenience and systematic samples differ has important implications for external validity and potential for dissemination of Internet-based interventions.

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

Science.gov (United States)

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

2013-11-01

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

Critical analysis of consecutive unilateral cleft lip repairs: determining ideal sample size.

Science.gov (United States)

Power, Stephanie M; Matic, Damir B

2013-03-01

Objective : Cleft surgeons often show 10 consecutive lip repairs to reduce presentation bias, however the validity remains unknown. The purpose of this study is to determine the number of consecutive cases that represent average outcomes. Secondary objectives are to determine if outcomes correlate with cleft severity and to calculate interrater reliability. Design : Consecutive preoperative and 2-year postoperative photographs of the unilateral cleft lip-nose complex were randomized and evaluated by cleft surgeons. Parametric analysis was performed according to chronologic, consecutive order. The mean standard deviation over all raters enabled calculation of expected 95% confidence intervals around a mean tested for various sample sizes. Setting : Meeting of the American Cleft Palate-Craniofacial Association in 2009. Patients, Participants : Ten senior cleft surgeons evaluated 39 consecutive lip repairs. Main Outcome Measures : Preoperative severity and postoperative outcomes were evaluated using descriptive and quantitative scales. Results : Intraclass correlation coefficients for cleft severity and postoperative evaluations were 0.65 and 0.21, respectively. Outcomes did not correlate with cleft severity (P  =  .28). Calculations for 10 consecutive cases demonstrated wide 95% confidence intervals, spanning two points on both postoperative grading scales. Ninety-five percent confidence intervals narrowed within one qualitative grade (±0.30) and one point (±0.50) on the 10-point scale for 27 consecutive cases. Conclusions : Larger numbers of consecutive cases (n > 27) are increasingly representative of average results, but less practical in presentation format. Ten consecutive cases lack statistical support. Cleft surgeons showed low interrater reliability for postoperative assessments, which may reflect personal bias when evaluating another surgeon's results.

Health Correlates of Insomnia Symptoms and Comorbid Mental Disorders in a Nationally Representative Sample of US Adolescents

NARCIS (Netherlands)

Blank, M.; Zhang, J.H.; Lamers, F.; Taylor, A.D.; Hickie, I.B.; Merikangas, K.R.

2015-01-01

Study Objectives: To estimate the prevalence and health correlates of insomnia symptoms and their association with comorbid mental disorders in a nationally representative sample of adolescents in the United States. Design: National representative cross-sectional study. Setting: Population-based

[Anxiety in a representative sample of the Spanish population over 50 years-old].

Science.gov (United States)

Carreira Capeáns, Cecilia; Facal, David

Anxiety is common throughout the ageing process. The objective of this study is to estimate the prevalence of anxiety in a representative sample of the Spanish population over 50 years-old. The data of this study come from the Pilot Study developed within the Longitudinal Ageing Study in Spain (ELES), in which a representative sample of the non-institutionalised Spanish population was evaluated. An analysis was performed on the data of 1086 people who answered the question «I am now going to read a list with a series of diseases or health problems. I would like you to tell me if your doctor has diagnosed any of them». The tools used were a questionnaire consisting of 218 questions, along with standardised tests, such as the Spanish version of the Mini-Mental State Examination. Anxiety was reported to have been diagnosed at some time in 14.3% of the sample. The prevalence was higher in women than in men (77.8 vs. 22.2%), decreasing with age, and related to different chronic diseases. The results show that the prevalence of anxiety throughout the lifespan is noticeable in people over 50 years, and should be taken into account, especially in the female population and in those with chronic diseases. Copyright © 2017 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

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

Science.gov (United States)

Arthur, Steve M.; Schwartz, Charles C.

1999-01-01

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

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

Directory of Open Access Journals (Sweden)

Esther Wong

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

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

Science.gov (United States)

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

2012-03-01

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

Cryogenic homogenization and sampling of heterogeneous multi-phase feedstock

Science.gov (United States)

Doyle, Glenn Michael; Ideker, Virgene Linda; Siegwarth, James David

2002-01-01

An apparatus and process for producing a homogeneous analytical sample from a heterogenous feedstock by: providing the mixed feedstock, reducing the temperature of the feedstock to a temperature below a critical temperature, reducing the size of the feedstock components, blending the reduced size feedstock to form a homogeneous mixture; and obtaining a representative sample of the homogeneous mixture. The size reduction and blending steps are performed at temperatures below the critical temperature in order to retain organic compounds in the form of solvents, oils, or liquids that may be adsorbed onto or absorbed into the solid components of the mixture, while also improving the efficiency of the size reduction. Preferably, the critical temperature is less than 77 K (-196.degree. C.). Further, with the process of this invention the representative sample may be maintained below the critical temperature until being analyzed.

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

Science.gov (United States)

Vegué, Marina; Perin, Rodrigo; Roxin, Alex

2017-08-30

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

Liquid praseodymium heat content by levitation calorimetry. [Sample size 0. 5 - 1. 5g; 1460 to 2289/sup 0/K

Energy Technology Data Exchange (ETDEWEB)

Stretz, L.A.; Bautista, R.G.

1976-01-01

The high-temperature heat content of liquid praseodymium was measured experimentally by the levitation calorimetry technique. The samples, ranging in size from 0.5 to 1.5 g, were simultaneously levitated and heated by a radiofrequency generator in an argon-helium mixture prior to being dropped into a conventional copper block drop calorimeter. Corrections were made for the convection and radiation losses during the fall of the sample from the levitation chamber into the calorimeter. The praseodymium data, from 1460 to 2289K, were fitted by the following equation where the indicated errors represent the average deviation of the experimental value from the value predicted by the equation: H/sub T/ - H/sub 298/./sub 15/ = (41.57 +- 0.29) (T - 1208) + (41733 +- 197) J/mol. (auth)

Sampling problems for randomly broken sticks

Energy Technology Data Exchange (ETDEWEB)

Huillet, Thierry [Laboratoire de Physique Theorique et Modelisation, CNRS-UMR 8089 et Universite de Cergy-Pontoise, 5 mail Gay-Lussac, 95031, Neuville sur Oise (France)

2003-04-11

Consider the random partitioning model of a population (represented by a stick of length 1) into n species (fragments) with identically distributed random weights (sizes). Upon ranking the fragments' weights according to ascending sizes, let S{sub m:n} be the size of the mth smallest fragment. Assume that some observer is sampling such populations as follows: drop at random k points (the sample size) onto this stick and record the corresponding numbers of visited fragments. We shall investigate the following sampling problems: (1) what is the sample size if the sampling is carried out until the first visit of the smallest fragment (size S{sub 1:n})? (2) For a given sample size, have all the fragments of the stick been visited at least once or not? This question is related to Feller's random coupon collector problem. (3) In what order are new fragments being discovered and what is the random number of samples separating the discovery of consecutive new fragments until exhaustion of the list? For this problem, the distribution of the size-biased permutation of the species' weights, as the sequence of their weights in their order of appearance is needed and studied.

Investigating sex differences in psychological predictors of snack intake among a large representative sample

NARCIS (Netherlands)

Adriaanse, M.A.; Evers, C.; Verhoeven, A.A.C.; de Ridder, D.T.D.

It is often assumed that there are substantial sex differences in eating behaviour (e.g. women are more likely to be dieters or emotional eaters than men). The present study investigates this assumption in a large representative community sample while incorporating a comprehensive set of

Disentangling the Relationship between Child Maltreatment and Violent Delinquency: Using a Nationally Representative Sample

Science.gov (United States)

Yun, Ilhong; Ball, Jeremy D.; Lim, Hyeyoung

2011-01-01

This study uses the National Longitudinal Study of Adolescents (Add Health) data, a nationally representative sample of adolescents, to disentangle the relationship between child maltreatment and violent delinquency. Also examined are potential moderating effects of gender, socioeconomic status (SES), and religiosity on the association between…

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

International Nuclear Information System (INIS)

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

2001-01-01

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

Tamanho da subamostra e representatividade da fertilidade do solo no sistema plantio direto Subsample size and soil fertility representativity in the no tillage system

Directory of Open Access Journals (Sweden)

Jairo André Schlindwein

2002-12-01

increase in the horizontal variability of the soil chemical characteristics, and in difficulties for collecting representative soil fertility samples. This research was carried out in two studies: the first one was to relate the subsample size with variability of the available phosphorus and potassium. Soil samples were collected with a shovel in an experiment and in a crop fild area in the no tillage system broadcast fertilized, at different sizes and layers up to 20cm depth. The second study was conducted to test the efficiency of different sizes and shapes of subsamples, given by soil sample equipments, througth the variability of soil fertility indexes. Two crop field areass under no tillage system were sampled at the 0-10cm depth with a screw auger and with a shovel with 5/10cm (thickness/wideness in the broadcast fertilizer field, and with 5cm thick and inter-row width in the row fertilized field. When the soil was sampled with the screw auger, the soil organic matter and available potassium content was lower in the row fertilized field, and available phosphorus content was lower in both, broadcast and row fertilized fields. In this situation, the variability was higher and, as a consequence, a higher number of subsamples were required to represent the fertility status of the soil. Soil samples taken with the shovel at the 5/10cm size were efficient to represent the soil fertility when the soil was broadcast fertilized in the no tillage system.

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

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Thomaz C. e C. da Costa

2004-12-01

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

The development and validation of the Male Genital Self-Image Scale: results from a nationally representative probability sample of men in the United States.

Science.gov (United States)

Herbenick, Debby; Schick, Vanessa; Reece, Michael; Sanders, Stephanie A; Fortenberry, J Dennis

2013-06-01

Numerous factors may affect men's sexual experiences, including their health status, past trauma or abuse, medication use, relationships, mood, anxiety, and body image. Little research has assessed the influence of men's genital self-image on their sexual function or behaviors and none has done so in a nationally representative sample. The purpose of this study was to, in a nationally representative probability sample of men ages 18 to 60, assess the reliability and validity of the Male Genital Self-Image Scale (MGSIS), and to examine the relationship between scores on the MGSIS and men's scores on the International Index of Erectile Function (IIEF). The MGSIS was developed in two stages. Phase One involved a review of the literature and an analysis of cross-sectional survey data. Phase Two involved an administration of the scale items to a nationally representative sample of men in the United States ages 18 to 60. Measures include demographic items, the IIEF, and the MGSIS. Overall, most men felt positively about their genitals. However, 24.6% of men expressed some discomfort letting a healthcare provider examine their genitals and about 20% reported dissatisfaction with their genital size. The MGSIS was found to be reliable and valid, with the MGSIS-5 (consisting of five items) being the best fit to the data. The MGSIS was found to be a reliable and valid measure. In addition, men's scores on the MGSIS-5 were found to be positively related to men's scores on the IIEF. © 2013 International Society for Sexual Medicine.

Socioeconomic Determinants of Bullying in the Workplace: A National Representative Sample in Japan

Science.gov (United States)

Tsutsumi, Akizumi; Shimazu, Akihito; Inoue, Akiomi; Odagiri, Yuko; Yoshikawa, Toru; Haratani, Takashi; Shimomitsu, Teruichi

2015-01-01

Bullying in the workplace is an increasingly recognized threat to employee health. We sought to test three hypotheses related to the determinants of workplace bullying: power distance at work; safety climate; and frustration related to perceived social inequality. A questionnaire survey was administered to a nationally representative community-based sample of 5,000 residents in Japan aged 20–60 years. The questionnaire included questions about employment, occupation, company size, education, household income, and subjective social status (SSS). We inquired about both the witnessing and personal experience of workplace bullying during the past 30 days. Among 2,384 respondents, data were analyzed from 1,546 workers. Multiple logistic regression analyses were used to examine the social determinants of workplace bullying. Six percent and 15 percent of the total sample reported experiencing or witnessing workplace bullying, respectively. After adjusting for gender and age, temporary employees (Odds Ratio [OR]: 2.45 [95% Confidence Interval (CI) = 1.03–5.85]), junior high school graduates (OR: 2.62 [95%CI: 1.01–6.79]), workers with lowest household income (OR: 4.13 [95%CI:1.58–10.8]), and workers in the lowest SSS stratum (OR: 4.21 [95%CI:1.66–10.7]) were at increased risk of experiencing workplace bullying. When all variables were entered simultaneously in the model, a significant inverse association was observed between higher SSS and experiencing bullying (p = 0.002). Similarly in terms of witnessing bullying; SSS was significantly inversely associated (p = 0.017) while temporary employees reported a significantly higher risk of witnessing bullying compared to permanent workers (OR: 2.25 [95%CI:1.04 to 4.87]). The significant association between SSS and experiencing/witnessing workplace bullying supports the frustration hypothesis. The power distance hypothesis was also partly supported by the finding that temporary employees experienced a higher prevalence

Ordinary or peculiar men? Comparing the customers of prostitutes with a nationally representative sample of men.

Science.gov (United States)

Monto, Martin A; Milrod, Christine

2014-07-01

Recent media attention implies that prostitution seeking is widespread, an "ordinary" aspect of masculine sexual behavior. Other accounts suggest that customers are "peculiar," characterized by distinct qualities, perversions, or psychological impairments. Using the nationally representative General Social Survey (GSS), this study demonstrates that prostitution seeking is relatively uncommon. Only about 14% of men in the United States report having ever paid for sex, and only 1% report having done so during the previous year. Furthermore, this study dissects whether customers are ordinary or peculiar by comparing a new sample of active customers who solicit sex on the Internet with an older sample of arrested customers, a sample of customers from the GSS, and a nationally representative sample of noncustomers. The customers of Internet sexual service providers differed greatly from men in general and also from other customers. The remaining samples of customers differed slightly from noncustomers in general. We argue for a balanced perspective that recognizes the significant variety among customers. There is no evidence of a peculiar quality that differentiates customers in general from men who have not paid for sex. © The Author(s) 2013.

Methodology for sample preparation and size measurement of commercial ZnO nanoparticles

Directory of Open Access Journals (Sweden)

Pei-Jia Lu

2018-04-01

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

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

Science.gov (United States)

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

2018-02-01

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

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

Directory of Open Access Journals (Sweden)

Shaukat S. Shahid

2016-06-01

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

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

NARCIS (Netherlands)

Spreen, M.; Bogaerts, S.

2015-01-01

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

Procedures for sampling and sample-reduction within quality assurance systems for solid biofuels

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-04-15

The bias introduced when sampling solid biofuels from stockpiles or containers instead of from moving streams is assessed as well as the number and size of samples required to represent accurately the bulk sample, variations introduced when reducing bulk samples into samples for testing, and the usefulness of sample reduction methods. Details are given of the experimental work carried out in Sweden and Denmark using sawdust, wood chips, wood pellets, forestry residues and straw. The production of a model European Standard for quality assurance of solid biofuels is examined.

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

Science.gov (United States)

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

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

Examination of Hydrate Formation Methods: Trying to Create Representative Samples

Energy Technology Data Exchange (ETDEWEB)

Kneafsey, T.J.; Rees, E.V.L.; Nakagawa, S.; Kwon, T.-H.

2011-04-01

Forming representative gas hydrate-bearing laboratory samples is important so that the properties of these materials may be measured, while controlling the composition and other variables. Natural samples are rare, and have often experienced pressure and temperature changes that may affect the property to be measured [Waite et al., 2008]. Forming methane hydrate samples in the laboratory has been done a number of ways, each having advantages and disadvantages. The ice-to-hydrate method [Stern et al., 1996], contacts melting ice with methane at the appropriate pressure to form hydrate. The hydrate can then be crushed and mixed with mineral grains under controlled conditions, and then compacted to create laboratory samples of methane hydrate in a mineral medium. The hydrate in these samples will be part of the load-bearing frame of the medium. In the excess gas method [Handa and Stupin, 1992], water is distributed throughout a mineral medium (e.g. packed moist sand, drained sand, moistened silica gel, other porous media) and the mixture is brought to hydrate-stable conditions (chilled and pressurized with gas), allowing hydrate to form. This method typically produces grain-cementing hydrate from pendular water in sand [Waite et al., 2004]. In the dissolved gas method [Tohidi et al., 2002], water with sufficient dissolved guest molecules is brought to hydrate-stable conditions where hydrate forms. In the laboratory, this is can be done by pre-dissolving the gas of interest in water and then introducing it to the sample under the appropriate conditions. With this method, it is easier to form hydrate from more soluble gases such as carbon dioxide. It is thought that this method more closely simulates the way most natural gas hydrate has formed. Laboratory implementation, however, is difficult, and sample formation is prohibitively time consuming [Minagawa et al., 2005; Spangenberg and Kulenkampff, 2005]. In another version of this technique, a specified quantity of gas

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

International Nuclear Information System (INIS)

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

2013-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-07-01

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

Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments.

Science.gov (United States)

Bi, Ran; Liu, Peng

2016-03-31

RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments. In this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method. Our proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network ( http://cran.r-project.org ).

Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats

Science.gov (United States)

Ellison, Laura E.; Lukacs, Paul M.

2014-01-01

Concern for migratory tree-roosting bats in North America has grown because of possible population declines from wind energy development. This concern has driven interest in estimating population-level changes. Mark-recapture methodology is one possible analytical framework for assessing bat population changes, but sample size requirements to produce reliable estimates have not been estimated. To illustrate the sample sizes necessary for a mark-recapture-based monitoring program we conducted power analyses using a statistical model that allows reencounters of live and dead marked individuals. We ran 1,000 simulations for each of five broad sample size categories in a Burnham joint model, and then compared the proportion of simulations in which 95% confidence intervals overlapped between and among years for a 4-year study. Additionally, we conducted sensitivity analyses of sample size to various capture probabilities and recovery probabilities. More than 50,000 individuals per year would need to be captured and released to accurately determine 10% and 15% declines in annual survival. To detect more dramatic declines of 33% or 50% survival over four years, then sample sizes of 25,000 or 10,000 per year, respectively, would be sufficient. Sensitivity analyses reveal that increasing recovery of dead marked individuals may be more valuable than increasing capture probability of marked individuals. Because of the extraordinary effort that would be required, we advise caution should such a mark-recapture effort be initiated because of the difficulty in attaining reliable estimates. We make recommendations for what techniques show the most promise for mark-recapture studies of bats because some techniques violate the assumptions of mark-recapture methodology when used to mark bats.

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

Science.gov (United States)

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

2017-01-01

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

Patterns of Childhood Abuse and Neglect in a Representative German Population Sample.

Directory of Open Access Journals (Sweden)

Christoph Schilling

Full Text Available Different types of childhood maltreatment, like emotional abuse, emotional neglect, physical abuse, physical neglect and sexual abuse are interrelated because of their co-occurrence. Different patterns of childhood abuse and neglect are associated with the degree of severity of mental disorders in adulthood. The purpose of this study was (a to identify different patterns of childhood maltreatment in a representative German community sample, (b to replicate the patterns of childhood neglect and abuse recently found in a clinical German sample, (c to examine whether participants reporting exposure to specific patterns of child maltreatment would report different levels of psychological distress, and (d to compare the results of the typological approach and the results of a cumulative risk model based on our data set.In a cross-sectional survey conducted in 2010, a representative random sample of 2504 German participants aged between 14 and 92 years completed the Childhood Trauma Questionnaire (CTQ. General anxiety and depression were assessed by standardized questionnaires (GAD-2, PHQ-2. Cluster analysis was conducted with the CTQ-subscales to identify different patterns of childhood maltreatment.Three different patterns of childhood abuse and neglect could be identified by cluster analysis. Cluster one showed low values on all CTQ-scales. Cluster two showed high values in emotional and physical neglect. Only cluster three showed high values in physical and sexual abuse. The three patterns of childhood maltreatment showed different degrees of depression (PHQ-2 and anxiety (GAD-2. Cluster one showed lowest levels of psychological distress, cluster three showed highest levels of mental distress.The results show that different types of childhood maltreatment are interrelated and can be grouped into specific patterns of childhood abuse and neglect, which are associated with differing severity of psychological distress in adulthood. The results

Patterns of Childhood Abuse and Neglect in a Representative German Population Sample

Science.gov (United States)

Schilling, Christoph; Weidner, Kerstin; Brähler, Elmar; Glaesmer, Heide; Häuser, Winfried; Pöhlmann, Karin

2016-01-01

Background Different types of childhood maltreatment, like emotional abuse, emotional neglect, physical abuse, physical neglect and sexual abuse are interrelated because of their co-occurrence. Different patterns of childhood abuse and neglect are associated with the degree of severity of mental disorders in adulthood. The purpose of this study was (a) to identify different patterns of childhood maltreatment in a representative German community sample, (b) to replicate the patterns of childhood neglect and abuse recently found in a clinical German sample, (c) to examine whether participants reporting exposure to specific patterns of child maltreatment would report different levels of psychological distress, and (d) to compare the results of the typological approach and the results of a cumulative risk model based on our data set. Methods In a cross-sectional survey conducted in 2010, a representative random sample of 2504 German participants aged between 14 and 92 years completed the Childhood Trauma Questionnaire (CTQ). General anxiety and depression were assessed by standardized questionnaires (GAD-2, PHQ-2). Cluster analysis was conducted with the CTQ-subscales to identify different patterns of childhood maltreatment. Results Three different patterns of childhood abuse and neglect could be identified by cluster analysis. Cluster one showed low values on all CTQ-scales. Cluster two showed high values in emotional and physical neglect. Only cluster three showed high values in physical and sexual abuse. The three patterns of childhood maltreatment showed different degrees of depression (PHQ-2) and anxiety (GAD-2). Cluster one showed lowest levels of psychological distress, cluster three showed highest levels of mental distress. Conclusion The results show that different types of childhood maltreatment are interrelated and can be grouped into specific patterns of childhood abuse and neglect, which are associated with differing severity of psychological distress in

Crystallite size variation of TiO_2 samples depending time heat treatment

International Nuclear Information System (INIS)

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

2016-01-01

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

How Sample Size Affects a Sampling Distribution

Science.gov (United States)

Mulekar, Madhuri S.; Siegel, Murray H.

2009-01-01

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

Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample.

Science.gov (United States)

Bányai, Fanni; Zsila, Ágnes; Király, Orsolya; Maraz, Aniko; Elekes, Zsuzsanna; Griffiths, Mark D; Andreassen, Cecilie Schou; Demetrovics, Zsolt

2017-01-01

Despite social media use being one of the most popular activities among adolescents, prevalence estimates among teenage samples of social media (problematic) use are lacking in the field. The present study surveyed a nationally representative Hungarian sample comprising 5,961 adolescents as part of the European School Survey Project on Alcohol and Other Drugs (ESPAD). Using the Bergen Social Media Addiction Scale (BSMAS) and based on latent profile analysis, 4.5% of the adolescents belonged to the at-risk group, and reported low self-esteem, high level of depression symptoms, and elevated social media use. Results also demonstrated that BSMAS has appropriate psychometric properties. It is concluded that adolescents at-risk of problematic social media use should be targeted by school-based prevention and intervention programs.

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

NARCIS (Netherlands)

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

2013-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-01-01

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Intergenerational Transmission of Marital Violence: Results From a Nationally Representative Sample of Men.

Science.gov (United States)

Murshid, Nadine Shaanta; Murshid, Navine

2015-09-16

The present study assesses the association between childhood exposure to parental violence and perpetration of marital violence as adults among a representative sample of 3,396 men in Bangladesh. We used secondary analysis of survey data from the nationally representative Bangladesh Demographic and Health Survey 2007 to examine factors associated with perpetration of martial violence among 3,396 ever-married men between the ages of 16 and 50 years. Outcome measure, marital violence perpetration, was measured using a modified Conflict Tactics Scale, and predictor variables included childhood exposure to parental violence, justification of marital violence, marital duration, religion, and demographic variables. Results indicate that marital violence perpetration is significantly associated with childhood exposure to marital violence, suggesting a cycle of violence that is maintained across generations. Implications for policy and practice are discussed. © The Author(s) 2015.

Neighborhood size of training data influences soil map disaggregation

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Soil class mapping relies on the ability of sample locations to represent portions of the landscape with similar soil types; however, most digital soil mapping (DSM) approaches intersect sample locations with one raster pixel per covariate layer regardless of pixel size. This approach does not take ...

Under-five mortality among mothers employed in agriculture: findings from a nationally representative sample

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Rajvir Singh

2015-01-01

Full Text Available Background. India accounts for 24% to all under-five mortality in the world. Residence in rural area, poverty and low levels of mother’s education are known confounders of under-five mortality. Since two-thirds of India’s population lives in rural areas, mothers employed in agriculture present a particularly vulnerable population in the Indian context and it is imperative that concerns of this sizeable population are addressed in order to achieve MDG4 targets of reducing U5MR to fewer than 41 per 1,000 by 2015. This study was conducted to examine factors associated with under-five mortality among mothers employed in agriculture.Methods. Data was retrieved from National Family Household Survey-3 in India (2008. The study population is comprised of a national representative sample of single children aged 0 to 59 months and born to mothers aged 15 to 49 years employed in agriculture from all 29 states of India. Univariate and Multivariate Cox PH regression analysis was used to analyse the Hazard Rates of mortality. The predictive power of child mortality among mothers employed in agriculture was assessed by calculating the area under the receiver operating characteristic (ROC curve.Results. An increase in mothers’ ages corresponds with a decrease in child mortality. Breastfeeding reduces child mortality by 70% (HR 0.30, 0.25–0.35, p = 0.001. Standard of Living reduces child mortality by 32% with high standard of living (HR 0.68, 0.52–0.89, 0.001 in comparison to low standard of living. Prenatal care (HR 0.40, 0.34–0.48, p = 0.001 and breastfeeding health nutrition education (HR 0.45, 0.31–0.66, p = 0.001 are associated significant factors for child mortality. Birth Order five is a risk factor for mortality (HR 1.49, 1.05–2.10, p = 0.04 in comparison to Birth Order one among women engaged in agriculture while the household size (6–10 members and ≥ 11 members is significant in reducing child mortality in comparison to ≤5 members

Under-five mortality among mothers employed in agriculture: findings from a nationally representative sample.

Science.gov (United States)

Singh, Rajvir; Tripathi, Vrijesh

2015-01-01

Background. India accounts for 24% to all under-five mortality in the world. Residence in rural area, poverty and low levels of mother's education are known confounders of under-five mortality. Since two-thirds of India's population lives in rural areas, mothers employed in agriculture present a particularly vulnerable population in the Indian context and it is imperative that concerns of this sizeable population are addressed in order to achieve MDG4 targets of reducing U5MR to fewer than 41 per 1,000 by 2015. This study was conducted to examine factors associated with under-five mortality among mothers employed in agriculture. Methods. Data was retrieved from National Family Household Survey-3 in India (2008). The study population is comprised of a national representative sample of single children aged 0 to 59 months and born to mothers aged 15 to 49 years employed in agriculture from all 29 states of India. Univariate and Multivariate Cox PH regression analysis was used to analyse the Hazard Rates of mortality. The predictive power of child mortality among mothers employed in agriculture was assessed by calculating the area under the receiver operating characteristic (ROC) curve. Results. An increase in mothers' ages corresponds with a decrease in child mortality. Breastfeeding reduces child mortality by 70% (HR 0.30, 0.25-0.35, p = 0.001). Standard of Living reduces child mortality by 32% with high standard of living (HR 0.68, 0.52-0.89, 0.001) in comparison to low standard of living. Prenatal care (HR 0.40, 0.34-0.48, p = 0.001) and breastfeeding health nutrition education (HR 0.45, 0.31-0.66, p = 0.001) are associated significant factors for child mortality. Birth Order five is a risk factor for mortality (HR 1.49, 1.05-2.10, p = 0.04) in comparison to Birth Order one among women engaged in agriculture while the household size (6-10 members and ≥ 11 members) is significant in reducing child mortality in comparison to ≤5 members in the house. Under

Radial line-scans as representative sampling strategy in dried-droplet laser ablation of liquid samples deposited on pre-cut filter paper disks

Energy Technology Data Exchange (ETDEWEB)

Nischkauer, Winfried [Institute of Chemical Technologies and Analytics, Vienna University of Technology, Vienna (Austria); Department of Analytical Chemistry, Ghent University, Ghent (Belgium); Vanhaecke, Frank [Department of Analytical Chemistry, Ghent University, Ghent (Belgium); Bernacchi, Sébastien; Herwig, Christoph [Institute of Chemical Engineering, Vienna University of Technology, Vienna (Austria); Limbeck, Andreas, E-mail: Andreas.Limbeck@tuwien.ac.at [Institute of Chemical Technologies and Analytics, Vienna University of Technology, Vienna (Austria)

2014-11-01

Nebulising liquid samples and using the aerosol thus obtained for further analysis is the standard method in many current analytical techniques, also with inductively coupled plasma (ICP)-based devices. With such a set-up, quantification via external calibration is usually straightforward for samples with aqueous or close-to-aqueous matrix composition. However, there is a variety of more complex samples. Such samples can be found in medical, biological, technological and industrial contexts and can range from body fluids, like blood or urine, to fuel additives or fermentation broths. Specialized nebulizer systems or careful digestion and dilution are required to tackle such demanding sample matrices. One alternative approach is to convert the liquid into a dried solid and to use laser ablation for sample introduction. Up to now, this approach required the application of internal standards or matrix-adjusted calibration due to matrix effects. In this contribution, we show a way to circumvent these matrix effects while using simple external calibration for quantification. The principle of representative sampling that we propose uses radial line-scans across the dried residue. This compensates for centro-symmetric inhomogeneities typically observed in dried spots. The effectiveness of the proposed sampling strategy is exemplified via the determination of phosphorus in biochemical fermentation media. However, the universal viability of the presented measurement protocol is postulated. Detection limits using laser ablation-ICP-optical emission spectrometry were in the order of 40 μg mL{sup −1} with a reproducibility of 10 % relative standard deviation (n = 4, concentration = 10 times the quantification limit). The reported sensitivity is fit-for-purpose in the biochemical context described here, but could be improved using ICP-mass spectrometry, if future analytical tasks would require it. Trueness of the proposed method was investigated by cross-validation with

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

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

2017-12-01

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

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

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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.

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

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Fan, Chunpeng; Zhang, Donghui

2012-01-01

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

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

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Mark Heckmann

2017-01-01

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

Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample.

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Fanni Bányai

Full Text Available Despite social media use being one of the most popular activities among adolescents, prevalence estimates among teenage samples of social media (problematic use are lacking in the field. The present study surveyed a nationally representative Hungarian sample comprising 5,961 adolescents as part of the European School Survey Project on Alcohol and Other Drugs (ESPAD. Using the Bergen Social Media Addiction Scale (BSMAS and based on latent profile analysis, 4.5% of the adolescents belonged to the at-risk group, and reported low self-esteem, high level of depression symptoms, and elevated social media use. Results also demonstrated that BSMAS has appropriate psychometric properties. It is concluded that adolescents at-risk of problematic social media use should be targeted by school-based prevention and intervention programs.

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

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

2016-01-01

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

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

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

1998-05-01

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

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

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

2011-03-01

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

The Paternal Landscape along the Bight of Benin - Testing Regional Representativeness of West-African Population Samples Using Y-Chromosomal Markers.

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Maarten H D Larmuseau

Full Text Available Patterns of genetic variation in human populations across the African continent are still not well studied in comparison with Eurasia and America, despite the high genetic and cultural diversity among African populations. In population and forensic genetic studies a single sample is often used to represent a complete African region. In such a scenario, inappropriate sampling strategies and/or the use of local, isolated populations may bias interpretations and pose questions of representativeness at a macrogeographic-scale. The non-recombining region of the Y-chromosome (NRY has great potential to reveal the regional representation of a sample due to its powerful phylogeographic information content. An area poorly characterized for Y-chromosomal data is the West-African region along the Bight of Benin, despite its important history in the trans-Atlantic slave trade and its large number of ethnic groups, languages and lifestyles. In this study, Y-chromosomal haplotypes from four Beninese populations were determined and a global meta-analysis with available Y-SNP and Y-STR data from populations along the Bight of Benin and surrounding areas was performed. A thorough methodology was developed allowing comparison of population samples using Y-chromosomal lineage data based on different Y-SNP panels and phylogenies. Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin. Nevertheless, based on Y-chromosomal data from the literature two population samples differed strongly from others from the same or neighbouring areas and are not regionally representative within large-scale studies. Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample

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

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Simon Boitard

2016-03-01

Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

A study on the representative sampling survey for the inspection of the clearance level for the radioisotope waste

International Nuclear Information System (INIS)

Hong Joo Ahn; Se Chul Sohn; Kwang Yong Jee; Ju Youl Kim; In Koo Lee

2007-01-01

Utilization facilities for radioisotope (RI) are increasing annually in South Korea, and the total number was 2,723, as of December 31, 2005. The inspection of a clearance level is a very important problem in order to ensure a social reliance for releasing radioactive materials to the environment. Korean regulations for such a clearance are described in Notice No. 2001-30 of the Ministry of Science and Technology (MOST) and Notice No. 2002-67 of the Ministry of Commerce, Industry and Energy (MOCIE). Most unsealed sources in RI waste drums at a storage facility are low-level beta-emitters with short half-lives, so it is impossible to measure their inventories by a nondestructive analysis. Furthermore, RI wastes generated from hospital, educational and research institutes and industry have a heterogeneous, multiple, irregular, and a small quantity of a waste stream. This study addresses a representative (master) sampling survey and analysis plan for RI wastes because a complete enumeration of waste drums is impossible and not desirable in terms of a cost and efficiency. The existing approaches to a representative sampling include a judgmental, simple random, stratified random, systematic grid, systematic random, composite, and adaptive sampling. A representative sampling plan may combine two or more of the above sampling approaches depending on the type and distribution of a waste stream. Stratified random sampling (constrained randomization) is proven to be adequate for a sampling design of a RI waste regarding a half-life, surface dose, undertaking time to a storage facility, and type of waste. The developed sampling protocol includes estimating the number of drums within a waste stream, estimating the number of samples, and a confirmation of the required number of samples. The statistical process control for a quality assurance plan includes control charts and an upper control limit (UCL) of 95% to determine whether a clearance level is met or not. (authors)

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

International Nuclear Information System (INIS)

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

2004-01-01

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

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.

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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 Distributions and Characterization of Native and Ground Samples for Toxicology Studies

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

2010-01-01

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

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

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Christopher Ryan Penton

2016-06-01

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

Representative process sampling for reliable data analysis

DEFF Research Database (Denmark)

Julius, Lars Petersen; Esbensen, Kim

2005-01-01

(sampling variances) can be reduced greatly however, and sampling biases can be eliminated completely, by respecting a simple set of rules and guidelines provided by TOS. A systematic approach for description of process heterogeneity furnishes in-depth knowledge about the specific variability of any 1-D lot...

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

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Peng-Cheng Yao

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

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

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

2013-04-15

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

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

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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…

How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables.

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Brooks, Mollie E; Mugabo, Marianne; Rodgers, Gwendolen M; Benton, Timothy G; Ozgul, Arpat

2016-03-01

Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

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

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Le Boedec, Kevin

2016-12-01

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

An individual urinary proteome analysis in normal human beings to define the minimal sample number to represent the normal urinary proteome

Directory of Open Access Journals (Sweden)

Liu Xuejiao

2012-11-01

Full Text Available Abstract Background The urinary proteome has been widely used for biomarker discovery. A urinary proteome database from normal humans can provide a background for discovery proteomics and candidate proteins/peptides for targeted proteomics. Therefore, it is necessary to define the minimum number of individuals required for sampling to represent the normal urinary proteome. Methods In this study, inter-individual and inter-gender variations of urinary proteome were taken into consideration to achieve a representative database. An individual analysis was performed on overnight urine samples from 20 normal volunteers (10 males and 10 females by 1DLC/MS/MS. To obtain a representative result of each sample, a replicate 1DLCMS/MS analysis was performed. The minimal sample number was estimated by statistical analysis. Results For qualitative analysis, less than 5% of new proteins/peptides were identified in a male/female normal group by adding a new sample when the sample number exceeded nine. In addition, in a normal group, the percentage of newly identified proteins/peptides was less than 5% upon adding a new sample when the sample number reached 10. Furthermore, a statistical analysis indicated that urinary proteomes from normal males and females showed different patterns. For quantitative analysis, the variation of protein abundance was defined by spectrum count and western blotting methods. And then the minimal sample number for quantitative proteomic analysis was identified. Conclusions For qualitative analysis, when considering the inter-individual and inter-gender variations, the minimum sample number is 10 and requires a balanced number of males and females in order to obtain a representative normal human urinary proteome. For quantitative analysis, the minimal sample number is much greater than that for qualitative analysis and depends on the experimental methods used for quantification.

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

DEFF Research Database (Denmark)

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

2006-01-01

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

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

Science.gov (United States)

Rambo, Robert P

2017-01-01

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

Associations among School Characteristics and Foodservice Practices in a Nationally Representative Sample of United States Schools

Science.gov (United States)

Thomson, Jessica L.; Tussing-Humphreys, Lisa M.; Martin, Corby K.; LeBlanc, Monique M.; Onufrak, Stephen J.

2012-01-01

Objective: Determine school characteristics associated with healthy/unhealthy food service offerings or healthy food preparation practices. Design: Secondary analysis of cross-sectional data. Setting: Nationally representative sample of public and private elementary, middle, and high schools. Participants: Data from the 2006 School Health Policies…

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Discrepancies in sample size calculations and data analyses reported in randomised trials: comparison of publications with protocols

DEFF Research Database (Denmark)

Chan, A.W.; Hrobjartsson, A.; Jorgensen, K.J.

2008-01-01

OBJECTIVE: To evaluate how often sample size calculations and methods of statistical analysis are pre-specified or changed in randomised trials. DESIGN: Retrospective cohort study. Data source Protocols and journal publications of published randomised parallel group trials initially approved...... in 1994-5 by the scientific-ethics committees for Copenhagen and Frederiksberg, Denmark (n=70). MAIN OUTCOME MEASURE: Proportion of protocols and publications that did not provide key information about sample size calculations and statistical methods; proportion of trials with discrepancies between...... of handling missing data was described in 16 protocols and 49 publications. 39/49 protocols and 42/43 publications reported the statistical test used to analyse primary outcome measures. Unacknowledged discrepancies between protocols and publications were found for sample size calculations (18/34 trials...

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

Directory of Open Access Journals (Sweden)

Hojin Moon

2002-12-01

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

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

International Nuclear Information System (INIS)

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

1986-11-01

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

Levels of Cadmium in Soil, Sediment and Water Samples from ...

African Journals Online (AJOL)

cce

The agricultural application of phosphate fertilizers represents a direct ... The samples were put into clean plastic containers and sealed. The plastic ... dried samples were ground and homogenized in a porcelain mortar, sieved to 40 mesh size.

Assessing representativeness of sampling methods for reaching men who have sex with men: a direct comparison of results obtained from convenience and probability samples.

Science.gov (United States)

Schwarcz, Sandra; Spindler, Hilary; Scheer, Susan; Valleroy, Linda; Lansky, Amy

2007-07-01

Convenience samples are used to determine HIV-related behaviors among men who have sex with men (MSM) without measuring the extent to which the results are representative of the broader MSM population. We compared results from a cross-sectional survey of MSM recruited from gay bars between June and October 2001 to a random digit dial telephone survey conducted between June 2002 and January 2003. The men in the probability sample were older, better educated, and had higher incomes than men in the convenience sample, the convenience sample enrolled more employed men and men of color. Substance use around the time of sex was higher in the convenience sample but other sexual behaviors were similar. HIV testing was common among men in both samples. Periodic validation, through comparison of data collected by different sampling methods, may be useful when relying on survey data for program and policy development.

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

Science.gov (United States)

van Rijnsoever, Frank J

2017-01-01

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

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

International Nuclear Information System (INIS)

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

1994-01-01

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

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

OpenAIRE

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

2011-01-01

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

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

International Nuclear Information System (INIS)

Sampson, T.E.

1991-01-01

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

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

Science.gov (United States)

Tang, Yongqiang

2015-01-01

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

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

Science.gov (United States)

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

2006-01-01

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

Predictors of type 2 diabetes in a nationally representative sample of adults with psychosis

OpenAIRE

Foley, Debra L; Mackinnon, Andrew; Morgan, Vera A; Watts, Gerald F; McGrath, John J; Castle, David J; Waterreus, Anna; Galletly, Cherrie A

2014-01-01

Antipsychotic drugs such as clozapine and olanzapine are associated with an increased risk for type 2 diabetes, but relatively little is known about the relationship between risk factors for type 2 diabetes established in the general population and type 2 diabetes in people with psychosis. We estimated the prevalence of established risk factors and their association with type 2 diabetes in a nationally representative sample of people with an ICD-10 psychosis (N=1642) who gave a fasting blood ...

Ethnic Variations of Pathways Linking Socioeconomic Status, Parenting, and Preacademic Skills in a Nationally Representative Sample

Science.gov (United States)

Iruka, Iheoma U.; Dotterer, Aryn M.; Pungello, Elizabeth P.

2014-01-01

Research Findings: Grounded in the investment model and informed by the integrative theory of the study of minority children, this study used the Early Childhood Longitudinal Study-Birth Cohort data set, a nationally representative sample of young children, to investigate whether the association between socioeconomic status (family income and…

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

International Nuclear Information System (INIS)

Dasari, K.B.; Acharya, R.

2014-01-01

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

A contemporary decennial global Landsat sample of changing agricultural field sizes

Science.gov (United States)

White, Emma; Roy, David

2014-05-01

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

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

Science.gov (United States)

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

2018-03-01

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

Determination of the minimum size of a statistical representative volume element from a fibre-reinforced composite based on point pattern statistics

DEFF Research Database (Denmark)

Hansen, Jens Zangenberg; Brøndsted, Povl

2013-01-01

In a previous study, Trias et al. [1] determined the minimum size of a statistical representative volume element (SRVE) of a unidirectional fibre-reinforced composite primarily based on numerical analyses of the stress/strain field. In continuation of this, the present study determines the minimu...... size of an SRVE based on a statistical analysis on the spatial statistics of the fibre packing patterns found in genuine laminates, and those generated numerically using a microstructure generator. © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved....

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

Directory of Open Access Journals (Sweden)

Zhihua Wang

2014-01-01

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

Testing of Small Graphite Samples for Nuclear Qualification

Energy Technology Data Exchange (ETDEWEB)

Julie Chapman

2010-11-01

Accurately determining the mechanical properties of small irradiated samples is crucial to predicting the behavior of the overal irradiated graphite components within a Very High Temperature Reactor. The sample size allowed in a material test reactor, however, is limited, and this poses some difficulties with respect to mechanical testing. In the case of graphite with a larger grain size, a small sample may exhibit characteristics not representative of the bulk material, leading to inaccuracies in the data. A study to determine a potential size effect on the tensile strength was pursued under the Next Generation Nuclear Plant program. It focuses first on optimizing the tensile testing procedure identified in the American Society for Testing and Materials (ASTM) Standard C 781-08. Once the testing procedure was verified, a size effect was assessed by gradually reducing the diameter of the specimens. By monitoring the material response, a size effect was successfully identified.

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

Science.gov (United States)

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

2015-08-01

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

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

Science.gov (United States)

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

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

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

Science.gov (United States)

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

2018-07-01

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

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

NARCIS (Netherlands)

van Schie, Sander; Moerbeek, Mirjam

2014-01-01

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

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

Science.gov (United States)

Vaeth, Michael; Skovlund, Eva

2004-06-15

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

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

DEFF Research Database (Denmark)

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

2009-01-01

PURPOSE: For certain cancer indications, the current patient evaluation strategy is a perfect but locally restricted gold standard procedure. If positron emission tomography/computed tomography (PET/CT) can be shown to be reliable within the gold standard region and if it can be argued that PET...... of metastasized prostate cancer. RESULTS: An added value in accuracy of PET/CT in adjacent areas can outweigh a downsized target level of accuracy in the gold standard region, justifying smaller sample sizes. CONCLUSIONS: If PET/CT provides an accuracy benefit in adjacent regions, then sample sizes can be reduced....../CT also performs well in adjacent areas, then sample sizes in accuracy studies can be reduced. PROCEDURES: Traditional standard power calculations for demonstrating sensitivities of both 80% and 90% are shown. The argument is then described in general terms and demonstrated by an ongoing study...

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

Science.gov (United States)

2017-01-01

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

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

International Nuclear Information System (INIS)

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

2018-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-07

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

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

Czech Academy of Sciences Publication Activity Database

Zíková, Naděžda; Ondráček, Jakub; Ždímal, Vladimír

2015-01-01

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

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

NARCIS (Netherlands)

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

2012-01-01

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

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

Science.gov (United States)

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

2017-06-30

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

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

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

OpenAIRE

Terada, Yoshikazu

2013-01-01

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

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

Science.gov (United States)

Li, Zhushan

2014-01-01

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

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

Science.gov (United States)

Krishnamoorthy, K.; Xia, Yanping

2008-01-01

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

Transgender Population Size in the United States: a Meta-Regression of Population-Based Probability Samples

Science.gov (United States)

Sevelius, Jae M.

2017-01-01

Background. Transgender individuals have a gender identity that differs from the sex they were assigned at birth. The population size of transgender individuals in the United States is not well-known, in part because official records, including the US Census, do not include data on gender identity. Population surveys today more often collect transgender-inclusive gender-identity data, and secular trends in culture and the media have created a somewhat more favorable environment for transgender people. Objectives. To estimate the current population size of transgender individuals in the United States and evaluate any trend over time. Search methods. In June and July 2016, we searched PubMed, Cumulative Index to Nursing and Allied Health Literature, and Web of Science for national surveys, as well as “gray” literature, through an Internet search. We limited the search to 2006 through 2016. Selection criteria. We selected population-based surveys that used probability sampling and included self-reported transgender-identity data. Data collection and analysis. We used random-effects meta-analysis to pool eligible surveys and used meta-regression to address our hypothesis that the transgender population size estimate would increase over time. We used subsample and leave-one-out analysis to assess for bias. Main results. Our meta-regression model, based on 12 surveys covering 2007 to 2015, explained 62.5% of model heterogeneity, with a significant effect for each unit increase in survey year (F = 17.122; df = 1,10; b = 0.026%; P = .002). Extrapolating these results to 2016 suggested a current US population size of 390 adults per 100 000, or almost 1 million adults nationally. This estimate may be more indicative for younger adults, who represented more than 50% of the respondents in our analysis. Authors’ conclusions. Future national surveys are likely to observe higher numbers of transgender people. The large variety in questions used to ask

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

Science.gov (United States)

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

2016-07-20

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

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

Directory of Open Access Journals (Sweden)

Elsa Tavernier

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

The Stages of Change in Smoking Cessation in a Representative Sample of Korean Adult Smokers

OpenAIRE

Jhun, Hyung-Joon; Seo, Hong-Gwan

2006-01-01

This study reports the stages of change in smoking cessation in a representative sample of Korean adult smokers. The study subjects, all adult smokers (n=2,422), were recruited from the second Korea National Health and Nutrition Examination Survey conducted in 2001. The stages of change were categorized using demographic (age and sex), socioeconomic (education, residence, and household income), and smoking characteristics (age at smoking onset, duration of smoking, and number of cigarettes sm...

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

Energy Technology Data Exchange (ETDEWEB)

Reer, B

2004-03-01

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

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

International Nuclear Information System (INIS)

Reer, B.

2004-01-01

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

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

Science.gov (United States)

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

2015-02-01

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

A method of language sampling

DEFF Research Database (Denmark)

Rijkhoff, Jan; Bakker, Dik; Hengeveld, Kees

1993-01-01

In recent years more attention is paid to the quality of language samples in typological work. Without an adequate sampling strategy, samples may suffer from various kinds of bias. In this article we propose a sampling method in which the genetic criterion is taken as the most important: samples...... created with this method will reflect optimally the diversity of the languages of the world. On the basis of the internal structure of each genetic language tree a measure is computed that reflects the linguistic diversity in the language families represented by these trees. This measure is used...... to determine how many languages from each phylum should be selected, given any required sample size....

Bacterial community composition of size-fractioned aggregates within the phycosphere of cyanobacterial blooms in a eutrophic freshwater lake.

Directory of Open Access Journals (Sweden)

Haiyuan Cai

Full Text Available Bacterial community composition of different sized aggregates within the Microcystis cyanobacterial phycosphere were determined during summer and fall in Lake Taihu, a eutrophic lake in eastern China. Bloom samples taken in August and September represent healthy bloom biomass, whereas samples from October represent decomposing bloom biomass. To improve our understanding of the complex interior structure in the phycosphere, bloom samples were separated into large (>100 µm, medium (10-100 µm and small (0.2-10 µm size aggregates. Species richness and library coverage indicated that pyrosequencing recovered a large bacterial diversity. The community of each size aggregate was highly organized, indicating highly specific conditions within the Microcystis phycosphere. While the communities of medium and small-size aggregates clustered together in August and September samples, large- and medium-size aggregate communities in the October sample were grouped together and distinct from small-size aggregate community. Pronounced changes in the absolute and relative percentages of the dominant genus from the two most important phyla Proteobacteria and Bacteroidetes were observed among the various size aggregates. Bacterial species on large and small-size aggregates likely have the ability to degrade high and low molecular weight compounds, respectively. Thus, there exists a spatial differentiation of bacterial taxa within the phycosphere, possibly operating in sequence and synergy to catalyze the turnover of complex organic matters.

Size, surface texture, chemical composition and mineralogy interrelations in ferromanganese nodules of central Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Banakar, V.K; Pattan, J.N.; Jauhari, P.

Fiftyseven ferromanganese nodules, classified into 3 size class (4,4-6 and 6-8 cm diam.), from the siliceous sediments of central Indian Ocean were analysed for transition metals and representative sample from each size class for mineralogy. Smaller...

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

Science.gov (United States)

Moustakas, Aristides; Evans, Matthew R

2015-02-28

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

Quantitative analysis of nano-pore geomaterials and representative sampling for digital rock physics

Science.gov (United States)

Yoon, H.; Dewers, T. A.

2014-12-01

Geomaterials containing nano-pores (e.g., shales and carbonate rocks) have become increasingly important for emerging problems such as unconventional gas and oil resources, enhanced oil recovery, and geologic storage of CO2. Accurate prediction of coupled geophysical and chemical processes at the pore scale requires realistic representation of pore structure and topology. This is especially true for chalk materials, where pore networks are small and complex, and require characterization at sub-micron scale. In this work, we apply laser scanning confocal microscopy to characterize pore structures and microlithofacies at micron- and greater scales and dual focused ion beam-scanning electron microscopy (FIB-SEM) for 3D imaging of nanometer-to-micron scale microcracks and pore distributions. With imaging techniques advanced for nano-pore characterization, a problem of scale with FIB-SEM images is how to take nanometer scale information and apply it to the thin-section or larger scale. In this work, several texture characterization techniques including graph-based spectral segmentation, support vector machine, and principal component analysis are applied for segmentation clusters represented by 1-2 FIB-SEM samples per each cluster. Geometric and topological properties are analyzed and lattice-Boltzmann method (LBM) is used to obtain permeability at several different scales. Upscaling of permeability to the Darcy scale (e.g., the thin-section scale) with image dataset will be discussed with emphasis on understanding microfracture-matrix interaction, representative volume for FIB-SEM sampling, and multiphase flow and reactive transport. Funding from the DOE Basic Energy Sciences Geosciences Program is gratefully acknowledged. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under

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

Directory of Open Access Journals (Sweden)

Aidan G. O’Keeffe

2017-12-01

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

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

Science.gov (United States)

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

2014-12-19

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

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

Directory of Open Access Journals (Sweden)

Stefano Schiavon

2010-01-01

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

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

Science.gov (United States)

Lusiana, Evellin Dewi

2017-12-01

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

Sampling of solid particles in clouds

International Nuclear Information System (INIS)

Feuillebois, F.; Lasek, A.; Scibilia, M.F.

1986-01-01

This paper is concerned with the sampling of small solid particles from clouds by an airborne apparatus to be mounted on an airplane for meteorological investigations. In the airborne experiment the particles entering the test tube should be as representative as possible of the upstream conditions ahead of the plane, in the real cloud. Due to the inertia of the particles, the proportion of the different sizes of particles entering the test tube depends on the location of the tube mouth. We present a method of calculating the real concentration in particles of different sizes, using the results of measurements executed during the flight of an airplane in a cloud. Two geometries are considered: the nose of the airplane, represented schematically by a hemisphere, and a wing represented by a (2D) Joukowski profile which matches well a NACA 0015 profile on its leading edge

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

Science.gov (United States)

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

2017-08-28

The use of benchmarks to assess the performance of implants such as those used in arthroplasty surgery is a widespread practice. It provides surgeons, patients and regulatory authorities with the reassurance that implants used are safe and effective. However, it is not currently clear how or how many implants should be statistically compared with a benchmark to assess whether or not that implant is superior, equivalent, non-inferior or inferior to the performance benchmark of interest.We aim to describe the methods and sample size required to conduct a one-sample non-inferiority study of a medical device for the purposes of benchmarking. Simulation study. Simulation study of a national register of medical devices. We simulated data, with and without a non-informative competing risk, to represent an arthroplasty population and describe three methods of analysis (z-test, 1-Kaplan-Meier and competing risks) commonly used in surgical research. We evaluate the performance of each method using power, bias, root-mean-square error, coverage and CI width. 1-Kaplan-Meier provides an unbiased estimate of implant net failure, which can be used to assess if a surgical device is non-inferior to an external benchmark. Small non-inferiority margins require significantly more individuals to be at risk compared with current benchmarking standards. A non-inferiority testing paradigm provides a useful framework for determining if an implant meets the required performance defined by an external benchmark. Current contemporary benchmarking standards have limited power to detect non-inferiority, and substantially larger samples sizes, in excess of 3200 procedures, are required to achieve a power greater than 60%. It is clear when benchmarking implant performance, net failure estimated using 1-KM is preferential to crude failure estimated by competing risk models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No

Sample size estimation to substantiate freedom from disease for clustered binary data with a specific risk profile

DEFF Research Database (Denmark)

Kostoulas, P.; Nielsen, Søren Saxmose; Browne, W. J.

2013-01-01

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

Change in Corporal Punishment Over Time in a Representative Sample of Canadian Parents.

Science.gov (United States)

Fréchette, Sabrina; Romano, Elisa

2015-08-01

Corporal punishment is a controversial form of discipline. Although its prevalence appears high, legal reforms and public education efforts to limit corporal punishment may be resulting in a decrease in its prevalence and frequency of use. This study drew on Canadian nationally representative data to understand the social change that might be happening and to characterize parents who continue to use corporal punishment. The study relied on cross-sectional data from Cycles 1 (1994) to 8 (2008) of the Canadian National Longitudinal Survey of Children and Youth to examine parental reports of corporal punishment for children ages 2–11 years. Analyses were conducted separately for 2- to 5-, 6- to 9-, and 10- to 11-year-olds, and sociodemographics associated with corporal punishment were examined. A significant decrease in the prevalence and frequency of corporal punishment use was observed across time for all age groups. Child sex, parent age, employment status, family structure, household size, immigration status, ethnicity, and religion significantly distinguished parents who use corporal punishment from those who do not, but there was variability across the age groups. Effect sizes question the relevance of the observed decrease in corporal punishment from an applied perspective. Approximately 25% of Canadian parents still use corporal punishment with children ages 2–11 years; therefore, it remains an issue that merits continued attention. Certain child, parent, and family characteristics seem to characterize parents who use corporal punishment, but other more dynamic variables may be important to consider, such as parental stress and their attitudes toward corporal punishment.

Analysis of time series and size of equivalent sample

International Nuclear Information System (INIS)

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

2004-01-01

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

Prevalence and correlates of bullying victimisation and perpetration in a nationally representative sample of Australian youth.

Science.gov (United States)

Thomas, Hannah J; Connor, Jason P; Lawrence, David M; Hafekost, Jennifer M; Zubrick, Stephen R; Scott, James G

2017-09-01

Bullying prevalence studies are limited by varied measurement methods and a lack of representative samples. This study estimated the national prevalence of bullying victimisation, perpetration and combined victim-perpetration experiences in a representative population-based sample of Australian youth. The relationships between the three types of bullying involvement with a range of mental health symptoms and diagnoses were also examined. A randomly selected nationally representative sample aged 11-17 years ( N = 2967, M age = 14.6 years; 51.6% male) completed the youth component of the Second Australian Child and Adolescent Survey of Mental Health and Wellbeing (Young Minds Matter). Parents or carers also completed a structured face-to-face interview that asked questions about a single randomly selected child in the household. The youth survey comprised self-reported bullying victimisation and perpetration (Olweus Bully-Victim Questionnaire-adapted), psychological distress (K10), emotional and behavioural problems (Strengths and Difficulties Questionnaire), as well as self-harm, suicide attempts and substance use. Modules from the Diagnostic Interview Schedule for Children Version IV were administered to all youth and parents to assess for mental disorder diagnoses (major depressive disorder, any anxiety disorder and any externalising disorder [attention-deficit hyperactivity disorder, oppositional defiant disorder and conduct disorder]). The 12-month prevalence of bullying victimisation was 13.3%, perpetration 1.6% and victim-perpetration 1.9%. Logistic regression models showed all forms of involvement in bullying were associated with increased risk of psychological distress, emotional and behavioural problems, substance use, self-harm and attempted suicide. Victimisation and victim-perpetration were associated with youth-reported major depressive disorder. There were also significant associations between bullying involvement and parent-reported diagnoses of major

The prevalence of discrimination across racial groups in contemporary America: Results from a nationally representative sample of adults.

Directory of Open Access Journals (Sweden)

Brian B Boutwell

Full Text Available A large body of social science research is devoted to understanding the causes and correlates of discrimination. Comparatively less effort has been aimed at providing a general prevalence estimate of discrimination using a nationally representative sample. The current study is intended to offer such an estimate using a large sample of American respondents (N = 14,793 while also exploring perceptions regarding why respondents felt they were discriminated against. The results provide a broad estimate of self-reported discrimination experiences-an event that was only reported by about one-quarter of all sample members-across racial and ethnic categories.

The prevalence of discrimination across racial groups in contemporary America: Results from a nationally representative sample of adults

Science.gov (United States)

Nedelec, Joseph L.; Winegard, Bo; Shackelford, Todd; Beaver, Kevin M.; Vaughn, Michael; Barnes, J. C.; Wright, John P.

2017-01-01

A large body of social science research is devoted to understanding the causes and correlates of discrimination. Comparatively less effort has been aimed at providing a general prevalence estimate of discrimination using a nationally representative sample. The current study is intended to offer such an estimate using a large sample of American respondents (N = 14,793) while also exploring perceptions regarding why respondents felt they were discriminated against. The results provide a broad estimate of self-reported discrimination experiences—an event that was only reported by about one-quarter of all sample members—across racial and ethnic categories. PMID:28837680

Sexuality education in a representative sample of Portuguese schools: examining the impact of legislation.

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Rocha, Ana Cristina; Duarte, Cidália

2015-02-01

To share Portugal's experience with school-based sexuality education, and to describe its implementation at a local level, following an ecological model and using a mixed methodology approach. The study also examines the impact of the latest policies put into effect, identifying potential weaknesses and strengths affecting the effectiveness of sexuality education enforcement. A representative sample of 296 schools in Portugal was analysed. Teachers representing the school completed a questionnaire and were asked to share any kind of official document from their sexuality education project (such as curriculum content). A subsample of these documents was analysed by two coders. Quantitative analysis was carried out using descriptive statistics. The majority of Portuguese schools delivered sexuality education, in line with Portuguese technical guidelines and international recommendations. There were common procedures in planning, implementation and evaluation of sexuality education. Some strengths and weaknesses were identified. Results highlighted the impact of the various systems on the planning, enforcement and evaluation of sexuality education in school. The latest policies introduced valuable changes in school-based sexuality education. A way of assessing effectiveness of sexuality education is still needed.

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models.

Science.gov (United States)

Blutke, Andreas; Wanke, Rüdiger

2018-03-06

In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of genetically modified pig models, and the often-limited number of available animals of these models, establishment of (biobank) collections of adequately processed tissue samples suited for a broad spectrum of subsequent analyses methods, including analyses not specified at the time point of sampling, represent meaningful approaches to take full advantage of the translational value of the model. With respect to the peculiarities of porcine anatomy, comprehensive guidelines have recently been established for standardized generation of representative, high-quality samples from different porcine organs and tissues. These guidelines are essential prerequisites for the reproducibility of results and their comparability between different studies and investigators. The recording of basic data, such as organ weights and volumes, the determination of the sampling locations and of the numbers of tissue samples to be generated, as well as their orientation, size, processing and trimming directions, are relevant factors determining the generalizability and usability of the specimen for molecular, qualitative, and quantitative morphological analyses. Here, an illustrative, practical, step-by-step demonstration of the most important techniques for generation of representative, multi-purpose biobank specimen from porcine tissues is presented. The methods described here include determination of organ/tissue volumes and densities, the application of a volume-weighted systematic random sampling procedure for parenchymal organs by point-counting, determination of the extent of tissue shrinkage related to histological embedding of samples, and generation of randomly oriented samples for quantitative stereological analyses, such as isotropic uniform random (IUR) sections generated by the "Orientator" and "Isector" methods, and vertical

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

Science.gov (United States)

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

2011-01-01

Preservation of β-cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet), repeated 2-hour Mixed Meal Tolerance Tests (MMTT) were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC) of the C-peptide values. The natural log(x), log(x+1) and square-root (√x) transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8-12 years of age, adolescents (13-17 years) and adults (18+ years). The sample size needed to detect a given relative (percentage) difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13-17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(x+1) and √x transformed values in terms of the original units of measurement (pmol/ml). Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab) versus masked placebo. These results provide the information needed to accurately

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

Directory of Open Access Journals (Sweden)

John M Lachin

Full Text Available Preservation of β-cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet, repeated 2-hour Mixed Meal Tolerance Tests (MMTT were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC of the C-peptide values. The natural log(x, log(x+1 and square-root (√x transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8-12 years of age, adolescents (13-17 years and adults (18+ years. The sample size needed to detect a given relative (percentage difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13-17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(x+1 and √x transformed values in terms of the original units of measurement (pmol/ml. Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab versus masked placebo. These results provide the information needed to

The prevalence of workaholism: a survey study in a nationally representative sample of Norwegian employees.

Directory of Open Access Journals (Sweden)

Cecilie Schou Andreassen

Full Text Available Workaholism has become an increasingly popular area for empirical study. However, most studies examining the prevalence of workaholism have used non-representative samples and measures with poorly defined cut-off scores. To overcome these methodological limitations, a nationally representative survey among employees in Norway (N = 1,124 was conducted. Questions relating to gender, age, marital status, caretaker responsibility for children, percentage of full-time equivalent, and educational level were asked. Workaholism was assessed by the use of a psychometrically validated instrument (i.e., Bergen Work Addiction Scale. Personality was assessed using the Mini-International Personality Item Pool. Results showed that the prevalence of workaholism was 8.3% (95% CI  = 6.7-9.9%. An adjusted logistic regression analysis showed that workaholism was negatively related to age and positively related to the personality dimensions agreeableness, neuroticism, and intellect/imagination. Implications for these findings are discussed.

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

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Tang, Yongqiang

2017-05-25

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

Evaluation of Respondent-Driven Sampling

Science.gov (United States)

McCreesh, Nicky; Frost, Simon; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda Ndagire; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Background Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex-workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total-population data. Methods Total-population data on age, tribe, religion, socioeconomic status, sexual activity and HIV status were available on a population of 2402 male household-heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, employing current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). Results We recruited 927 household-heads. Full and small RDS samples were largely representative of the total population, but both samples under-represented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven-sampling statistical-inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven-sampling bootstrap 95% confidence intervals included the population proportion. Conclusions Respondent-driven sampling produced a generally representative sample of this well-connected non-hidden population. However, current respondent-driven-sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience-sampling

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

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

2014-01-01

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

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

Science.gov (United States)

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

2012-11-01

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

Spatial resolution of 2D ionization chamber arrays for IMRT dose verification: single-detector size and sampling step width

International Nuclear Information System (INIS)

Poppe, Bjoern; Djouguela, Armand; Blechschmidt, Arne; Willborn, Kay; Ruehmann, Antje; Harder, Dietrich

2007-01-01

The spatial resolution of 2D detector arrays equipped with ionization chambers or diodes, used for the dose verification of IMRT treatment plans, is limited by the size of the single detector and the centre-to-centre distance between the detectors. Optimization criteria with regard to these parameters have been developed by combining concepts of dosimetry and pattern analysis. The 2D-ARRAY Type 10024 (PTW-Freiburg, Germany), single-chamber cross section 5 x 5 mm 2 , centre-to-centre distance between chambers in each row and column 10 mm, served as an example. Additional frames of given dose distributions can be taken by shifting the whole array parallel or perpendicular to the MLC leaves by, e.g., 5 mm. The size of the single detector is characterized by its lateral response function, a trapezoid with 5 mm top width and 9 mm base width. Therefore, values measured with the 2D array are regarded as sample values from the convolution product of the accelerator generated dose distribution and this lateral response function. Consequently, the dose verification, e.g., by means of the gamma index, is performed by comparing the measured values of the 2D array with the values of the convolution product of the treatment planning system (TPS) calculated dose distribution and the single-detector lateral response function. Sufficiently small misalignments of the measured dose distributions in comparison with the calculated ones can be detected since the lateral response function is symmetric with respect to the centre of the chamber, and the change of dose gradients due to the convolution is sufficiently small. The sampling step width of the 2D array should provide a set of sample values representative of the sampled distribution, which is achieved if the highest spatial frequency contained in this function does not exceed the 'Nyquist frequency', one half of the sampling frequency. Since the convolution products of IMRT-typical dose distributions and the single

Associated factors of obesity in Spanish representative samples.

Science.gov (United States)

Ortega Anta, Rosa M; López-Solaber, Ana M; Pérez-Farinós, Napoleón

2013-09-01

Given the dramatic increase in the prevalence of obesity and the serious health and economic consequences, the scientific community, health professionals and health agencies are looking for the best strategies to prevent/ fight this trend. In order to plan the most appropriate intervention measures the first step is to identify the associated factors of obesity. This paper presents the results of research conducted/coordinated by our research team and promoted by the Spanish Food Safety Agency (AESAN), in the last five years. These studies were focussed on representative samples of the Spanish population, paying attention to the condition of overweight/obesity and their associated factors. The first study, FANPE ("Fuentes alimentarias de nutrientes de la población española") (2009), was centered in 418 adults (18-60 years) from 15 provinces (30 sampling points). Its aim was to analyze the dietary sources of nutrients, paying particular attention to sodium. This research showed that the risk of overweight/obesity increa ses with age, in people who have follow weight control diets, in ex-smokers, married people and those who slept less than 8.5 hours per day, while the risk is lower in women, people who make sport and those with a University degree. It was also found that overweight people had higher sodium intake and urine excretion. Therefore, and having in mind that 88.2% of the subjects took more than 2 g/day of sodium (the maximum recommended), it is advised to lower the sodium intake not only from the health point of view but also as a probably strategy against obesity. The study ALADINO (Estudio de Alimentación, Actividad física, Desarrollo Infantil y Obesidad--Study of the Diet, Physical Activity, Child Development and Obesity) (2010-2011) was focused on 7659 children (6-9 years) from 19 autonomous communities. We founded a higher percentage of overweight/obesity in boys than in girls, and a significant increase in the figures from the age of 7. Being

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

Science.gov (United States)

Li, Johnson Ching-Hong

2016-12-01

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

A comprehensive literature review reflecting fifteen years of debate regarding the representativity of reverse circulation vs blast hole drill sampling

DEFF Research Database (Denmark)

Engström, Karin

2017-01-01

Blast hole sampling is widely used for grade control by the mining industry all over the world, both in precious and base metal open pit mining. Blast hole (BH) samples are often regarded as inferior in comparison to “proper drill sampling” like reverse circulation (RC) and diamond (core) drilling...... (DD), and are accused of lacking representativity by the sampling community. The present paper aims at collecting all peer reviewed publications from 2000 onwards that concern open pit mine sampling performance of BH, RC and/or DD drill sampling. This will form a comprehensive literature review...

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

Science.gov (United States)

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

2011-08-01

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

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

Science.gov (United States)

Hagell, Peter; Westergren, Albert

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

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

Science.gov (United States)

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

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

Reproducibility of preclinical animal research improves with heterogeneity of study samples

Science.gov (United States)

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

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

Science.gov (United States)

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

2017-01-01

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

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

International Nuclear Information System (INIS)

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

2007-01-01

To determine the reproducibility of measurements of brain 5-HT 2A receptors with an [ 18 F]altanserin PET bolus/infusion approach. Further, to estimate the sample size needed to detect regional differences between two groups and, finally, to evaluate how partial volume correction affects reproducibility and the required sample size. For assessment of the variability, six subjects were investigated with [ 18 F]altanserin PET twice, at an interval of less than 2 weeks. The sample size required to detect a 20% difference was estimated from [ 18 F]altanserin PET studies in 84 healthy subjects. Regions of interest were automatically delineated on co-registered MR and PET images. In cortical brain regions with a high density of 5-HT 2A receptors, the outcome parameter (binding potential, BP 1 ) showed high reproducibility, with a median difference between the two group measurements of 6% (range 5-12%), whereas in regions with a low receptor density, BP 1 reproducibility was lower, with a median difference of 17% (range 11-39%). Partial volume correction reduced the variability in the sample considerably. The sample size required to detect a 20% difference in brain regions with high receptor density is approximately 27, whereas for low receptor binding regions the required sample size is substantially higher. This study demonstrates that [ 18 F]altanserin PET with a bolus/infusion design has very low variability, particularly in larger brain regions with high 5-HT 2A receptor density. Moreover, partial volume correction considerably reduces the sample size required to detect regional changes between groups. (orig.)

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

Science.gov (United States)

Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik

2017-09-01

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

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

Directory of Open Access Journals (Sweden)

B. Boessenkool

2017-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-12-15

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Are extracted materials truly representative of original samples? Impact of C18 extraction on CDOM optical and chemical properties

Directory of Open Access Journals (Sweden)

Andrea A Andrew

2016-02-01

Full Text Available Some properties of dissolved organic matter (DOM and chromophoric dissolved organic matter (CDOM can be easily measured directly on whole waters, while others require sample concentration and removal of natural salts. To increase CDOM content and eliminate salts, solid phase extraction is often employed. Biases following extraction and elution are inevitable, thus raising the question of how truly representative the extracted material is of the original. In this context, we investigated the wavelength dependence of extraction efficiency for C18 cartridges with respect to CDOM optical properties using samples obtained from the Middle Atlantic Bight (MAB and the Equatorial Atlantic Ocean (EAO. Further, we compared the optical changes of C18 extracts and the corresponding whole water following chemical reduction with sodium borohydride (NaBH4.C18 cartridges preferentially extracted long-wavelength absorbing/emitting material for samples impacted by riverine input. Extraction efficiency overall decreased with offshore distance away from riverine input. Spectral slopes of C18-OM samples were also almost always lower than those of their corresponding CDOM samples supporting the preferential extraction of higher molecular weight absorbing material. The wavelength dependence of the optical properties (absorption, fluorescence emission and quantum yield of the original water samples and their corresponding extracted material were very similar. C18 extracts and corresponding water samples further exhibited comparable optical changes following NaBH4 reduction, thus suggesting a similarity in nature (structure of the optically active extracted material, independent of geographical locale. Altogether, these data suggested a strong similarity between C18 extracts and corresponding whole waters, thus indicating that extracts are representative of the CDOM content of original waters.

Are Extracted Materials Truly Representative of Original Samples? Impact of C18 Extraction on CDOM Optical and Chemical Properties.

Science.gov (United States)

Andrew, Andrea A; Del Vecchio, Rossana; Zhang, Yi; Subramaniam, Ajit; Blough, Neil V

2016-01-01

Some properties of dissolved organic matter (DOM) and chromophoric dissolved organic matter (CDOM) can be easily measured directly on whole waters, while others require sample concentration and removal of natural salts. To increase CDOM content and eliminate salts, solid phase extraction (SPE) is often employed. Biases following extraction and elution are inevitable, thus raising the question of how truly representative the extracted material is of the original. In this context, we investigated the wavelength dependence of extraction efficiency for C18 cartridges with respect to CDOM optical properties using samples obtained from the Middle Atlantic Bight (MAB) and the Equatorial Atlantic Ocean (EAO). Further, we compared the optical changes of C18 extracts and the corresponding whole water following chemical reduction with sodium borohydride (NaBH4). C18 cartridges preferentially extracted long-wavelength absorbing/emitting material for samples impacted by riverine input. Extraction efficiency overall decreased with offshore distance away from riverine input. Spectral slopes of C18-OM samples were also almost always lower than those of their corresponding CDOM samples supporting the preferential extraction of higher molecular weight absorbing material. The wavelength dependence of the optical properties (absorption, fluorescence emission, and quantum yield) of the original water samples and their corresponding extracted material were very similar. C18 extracts and corresponding water samples further exhibited comparable optical changes following NaBH4 reduction, thus suggesting a similarity in nature (structure) of the optically active extracted material, independent of geographical locale. Altogether, these data suggested a strong similarity between C18 extracts and corresponding whole waters, thus indicating that extracts are representative of the CDOM content of original waters.

Are extracted materials truly representative of original samples? Impact of C18 extraction on CDOM optical and chemical properties

Science.gov (United States)

Andrew, Andrea; Del Vecchio, Rossana; Zhang, Yi; Subramaniam, Ajit; Blough, Neil

2016-02-01

Some properties of dissolved organic matter (DOM) and chromophoric dissolved organic matter (CDOM) can be easily measured directly on whole waters, while others require sample concentration and removal of natural salts. To increase CDOM content and eliminate salts, solid phase extraction is often employed. Biases following extraction and elution are inevitable, thus raising the question of how truly representative the extracted material is of the original. In this context, we investigated the wavelength dependence of extraction efficiency for C18 cartridges with respect to CDOM optical properties using samples obtained from the Middle Atlantic Bight (MAB) and the Equatorial Atlantic Ocean (EAO). Further, we compared the optical changes of C18 extracts and the corresponding whole water following chemical reduction with sodium borohydride (NaBH4). C18 cartridges preferentially extracted long-wavelength absorbing/emitting material for samples impacted by riverine input. Extraction efficiency overall decreased with offshore distance away from riverine input. Spectral slopes of C18-OM samples were also almost always lower than those of their corresponding CDOM samples supporting the preferential extraction of higher molecular weight absorbing material. The wavelength dependence of the optical properties (absorption, fluorescence emission and quantum yield) of the original water samples and their corresponding extracted material were very similar. C18 extracts and corresponding water samples further exhibited comparable optical changes following NaBH4 reduction, thus suggesting a similarity in nature (structure) of the optically active extracted material, independent of geographical locale. Altogether, these data suggested a strong similarity between C18 extracts and corresponding whole waters, thus indicating that extracts are representative of the CDOM content of original waters.

Optimism is universal: exploring the presence and benefits of optimism in a representative sample of the world.

Science.gov (United States)

Gallagher, Matthew W; Lopez, Shane J; Pressman, Sarah D

2013-10-01

Current theories of optimism suggest that the tendency to maintain positive expectations for the future is an adaptive psychological resource associated with improved well-being and physical health, but the majority of previous optimism research has been conducted in industrialized nations. The present study examined (a) whether optimism is universal, (b) what demographic factors predict optimism, and (c) whether optimism is consistently associated with improved subjective well-being and perceived health worldwide. The present study used representative samples of 142 countries that together represent 95% of the world's population. The total sample of 150,048 individuals had a mean age of 38.28 (SD = 16.85) and approximately equal sex distribution (51.2% female). The relationships between optimism, subjective well-being, and perceived health were examined using hierarchical linear modeling. Results indicated that most individuals and most countries worldwide are optimistic and that higher levels of optimism are associated with improved subjective well-being and perceived health worldwide. The present study provides compelling evidence that optimism is a universal phenomenon and that the associations between optimism and improved psychological functioning are not limited to industrialized nations. © 2012 Wiley Periodicals, Inc.

Reliable calculation in probabilistic logic: Accounting for small sample size and model uncertainty

Energy Technology Data Exchange (ETDEWEB)

Ferson, S. [Applied Biomathematics, Setauket, NY (United States)

1996-12-31

A variety of practical computational problems arise in risk and safety assessments, forensic statistics and decision analyses in which the probability of some event or proposition E is to be estimated from the probabilities of a finite list of related subevents or propositions F,G,H,.... In practice, the analyst`s knowledge may be incomplete in two ways. First, the probabilities of the subevents may be imprecisely known from statistical estimations, perhaps based on very small sample sizes. Second, relationships among the subevents may be known imprecisely. For instance, there may be only limited information about their stochastic dependencies. Representing probability estimates as interval ranges on has been suggested as a way to address the first source of imprecision. A suite of AND, OR and NOT operators defined with reference to the classical Frochet inequalities permit these probability intervals to be used in calculations that address the second source of imprecision, in many cases, in a best possible way. Using statistical confidence intervals as inputs unravels the closure properties of this approach however, requiring that probability estimates be characterized by a nested stack of intervals for all possible levels of statistical confidence, from a point estimate (0% confidence) to the entire unit interval (100% confidence). The corresponding logical operations implied by convolutive application of the logical operators for every possible pair of confidence intervals reduces by symmetry to a manageably simple level-wise iteration. The resulting calculus can be implemented in software that allows users to compute comprehensive and often level-wise best possible bounds on probabilities for logical functions of events.

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

International Nuclear Information System (INIS)

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

2000-01-01

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

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

Science.gov (United States)

Terry, Leann; Kelley, Ken

2012-11-01

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

Elementary representative sizes of soil attributes via attenuation of gamma rays and computerized tomography; Tamanhos elementares representativos de atributos do solo via atenuacao de raios gama e tomografia computadorizada

Energy Technology Data Exchange (ETDEWEB)

Borges, Jaqueline Aparecida Ribaski

2015-07-01

In this study, the Computed Tomography (CT) and gamma-ray attenuation (GRA) techniques were used in the investigation of representative sample sizes for attributes related to soil structure. First of all, the representative elementary length (REL) for experimental measurements of soil mass attenuation coefficient (μes), of samples from a sandy and a clayey soil, was analyzed. The study was conducted with two radioactive sources ({sup 241}Am and {sup 137}Cs), three collimators (2 - 4 mm diameters), and 14 thickness (x) samples (2-5 cm). From these analyzes, it was possible to identify an ideal thickness range for each of the studied sources (2-4 cm and 12-15 cm for the sources of {sup 241}Am and {sup 137}Cs, respectively). The application of such results in representative elementary area evaluations, in clayey soil clods via CT, indicated that experimental soil mass attenuation coefficient average values obtained for x>4 cm and source {sup 241}Am might induce the use of samples which are not large enough for soil bulk density evaluations. Subsequently, μCT images with a total volume of 39×39×33 mm{sup 3} and spatial resolution of 60 μm were used for macroporous system morphological characterization of a Rhodic Ferralsol with clayey texture, under no-till (NT) and conventional till (CT) systems. Attributes as macroporosity (MAP), number of macropores (NMAP), tortuosity (τ) and connectivity (C) of the pores were assessed. The C degree was estimated based on the Euler-Poincare characteristic (EPC). Once 3D images enable the study of these attributes in different sample volumes, the proposed study is ideal for the analysis of representative elementary volume (REV). Usually, the selection of subvolumes for REV analysis occurs concentrically to a small volume or in adjacent positions. Here, we introduced a new method for selecting the positions of subvolumes, which are randomly chosen within the total image volume (random selection). It was observed that higher

Engaging workplace representatives in research: what recruitment strategies work best?

Science.gov (United States)

Coole, C; Nouri, F; Narayanasamy, M; Baker, P; Khan, S; Drummond, A

2018-05-23

Workplaces are key stakeholders in work and health but little is known about the methods used to recruit workplace representatives (WRs), including managers, occupational health advisers and colleagues, to externally funded healthcare research studies. To detail the strategies used in recruiting WRs from three areas of the UK to a qualitative study concerning their experience of employees undergoing hip or knee replacement, to compare the strategies and inform recruitment methods for future studies. Six strategies were used to recruit WRs from organizations of different sizes and sectors. Data on numbers approached and responses received were analysed descriptively. Twenty-five WRs were recruited. Recruitment had to be extended outside the main three study areas, and took several months. It proved more difficult to recruit from non-service sectors and small- and medium-sized enterprises. The most successful strategies were approaching organizations that had participated in previous research studies, or known professionally or personally to team members. Recruiting a diverse sample of WRs to healthcare research requires considerable resources and persistence, and a range of strategies. Recruitment is easier where local relationships already exist; the importance of building and maintaining these relationships cannot be underestimated. However, the potential risks of bias and participant fatigue need to be acknowledged and managed. Further studies are needed to explore how WRs can be recruited to health research, and to identify the researcher effort and costs involved in achieving unbiased and representative samples.

Size Effect Studies on Tensile Tests for Hot Stamping Steel

Science.gov (United States)

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

2018-02-01

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

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

Science.gov (United States)

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

2018-01-01

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

Estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean.

Science.gov (United States)

Schillaci, Michael A; Schillaci, Mario E

2009-02-01

The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (nresearchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.

Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies

Directory of Open Access Journals (Sweden)

Finch Stephen J

2005-04-01

Full Text Available Abstract Background Phenotype error causes reduction in power to detect genetic association. We present a quantification of phenotype error, also known as diagnostic error, on power and sample size calculations for case-control genetic association studies between a marker locus and a disease phenotype. We consider the classic Pearson chi-square test for independence as our test of genetic association. To determine asymptotic power analytically, we compute the distribution's non-centrality parameter, which is a function of the case and control sample sizes, genotype frequencies, disease prevalence, and phenotype misclassification probabilities. We derive the non-centrality parameter in the presence of phenotype errors and equivalent formulas for misclassification cost (the percentage increase in minimum sample size needed to maintain constant asymptotic power at a fixed significance level for each percentage increase in a given misclassification parameter. We use a linear Taylor Series approximation for the cost of phenotype misclassification to determine lower bounds for the relative costs of misclassifying a true affected (respectively, unaffected as a control (respectively, case. Power is verified by computer simulation. Results Our major findings are that: (i the median absolute difference between analytic power with our method and simulation power was 0.001 and the absolute difference was no larger than 0.011; (ii as the disease prevalence approaches 0, the cost of misclassifying a unaffected as a case becomes infinitely large while the cost of misclassifying an affected as a control approaches 0. Conclusion Our work enables researchers to specifically quantify power loss and minimum sample size requirements in the presence of phenotype errors, thereby allowing for more realistic study design. For most diseases of current interest, verifying that cases are correctly classified is of paramount importance.

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

Science.gov (United States)

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

2018-05-01

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

Studying the sampling representativeness in the NPP ventilation ducts

International Nuclear Information System (INIS)

Sosnovskij, R.I.; Fedchenko, T.K.; Minin, S.A.

2000-01-01

Measurements of the gas and aerosol voluminous activity in the NPP ventilation ducts are an important source of information on the radiation contaminants ingress into the environmental medium. These measurements include sampling, samples transport and proper measurements. The work is devoted to calculation of metrological characteristics of the sampling systems for the NPP gas-aerosol releases by different parameters of these systems and ventilation ducts. The results obtained are intended for application by designing such systems and their metrological certification [ru

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