Sample size calculation: Basic principles
Das, Sabyasachi; Mitra, Koel; Mandal, Mohanchandra
2016-01-01
Addressing a sample size is a practical issue that has to be solved during planning and designing stage of the study. The aim of any clinical research is to detect the actual difference between two groups (power) and to provide an estimate of the difference with a reasonable accuracy (precision). Hence, researchers should do a priori estimate of sample size well ahead, before conducting the study. Post hoc sample size computation is not encouraged conventionally. Adequate sample size minimizes the random error or in other words, lessens something happening by chance. Too small a sample may fail to answer the research question and can be of questionable validity or provide an imprecise answer while too large a sample may answer the question but is resource-intensive and also may be unethical. More transparency in the calculation of sample size is required so that it can be justified and replicated while reporting. PMID:27729692
Sample size calculation in metabolic phenotyping studies.
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. PMID:25600654
Considerations when calculating the sample size for an inequality test
2016-01-01
Click here for Korean Translation. Calculating the sample size is a vital step during the planning of a study in order to ensure the desired power for detecting clinically meaningful differences. However, estimating the sample size is not always straightforward. A number of key components should be considered to calculate a suitable sample size. In this paper, general considerations for conducting sample size calculations for inequality tests are summarized. PMID:27482308
Sample size calculation for the proportional hazards cure model.
Wang, Songfeng; Zhang, Jiajia; Lu, Wenbin
2012-12-20
In clinical trials with time-to-event endpoints, it is not uncommon to see a significant proportion of patients being cured (or long-term survivors), such as trials for the non-Hodgkins lymphoma disease. The popularly used sample size formula derived under the proportional hazards (PH) model may not be proper to design a survival trial with a cure fraction, because the PH model assumption may be violated. To account for a cure fraction, the PH cure model is widely used in practice, where a PH model is used for survival times of uncured patients and a logistic distribution is used for the probability of patients being cured. In this paper, we develop a sample size formula on the basis of the PH cure model by investigating the asymptotic distributions of the standard weighted log-rank statistics under the null and local alternative hypotheses. The derived sample size formula under the PH cure model is more flexible because it can be used to test the differences in the short-term survival and/or cure fraction. Furthermore, we also investigate as numerical examples the impacts of accrual methods and durations of accrual and follow-up periods on sample size calculation. The results show that ignoring the cure rate in sample size calculation can lead to either underpowered or overpowered studies. We evaluate the performance of the proposed formula by simulation studies and provide an example to illustrate its application with the use of data from a melanoma trial. PMID:22786805
GLIMMPSE Lite: Calculating Power and Sample Size on Smartphone Devices
Munjal, Aarti; Sakhadeo, Uttara R.; Muller, Keith E.; Glueck, Deborah H.; Kreidler, Sarah M.
2014-01-01
Researchers seeking to develop complex statistical applications for mobile devices face a common set of difficult implementation issues. In this work, we discuss general solutions to the design challenges. We demonstrate the utility of the solutions for a free mobile application designed to provide power and sample size calculations for univariate, one-way analysis of variance (ANOVA), GLIMMPSE Lite. Our design decisions provide a guide for other scientists seeking to produce statistical software for mobile platforms. PMID:25541688
Sample size calculation for meta-epidemiological studies.
Giraudeau, Bruno; Higgins, Julian P T; Tavernier, Elsa; Trinquart, Ludovic
2016-01-30
Meta-epidemiological studies are used to compare treatment effect estimates between randomized clinical trials with and without a characteristic of interest. To our knowledge, there is presently nothing to help researchers to a priori specify the required number of meta-analyses to be included in a meta-epidemiological study. We derived a theoretical power function and sample size formula in the framework of a hierarchical model that allows for variation in the impact of the characteristic between trials within a meta-analysis and between meta-analyses. A simulation study revealed that the theoretical function overestimated power (because of the assumption of equal weights for each trial within and between meta-analyses). We also propose a simulation approach that allows for relaxing the constraints used in the theoretical approach and is more accurate. We illustrate that the two variables that mostly influence power are the number of trials per meta-analysis and the proportion of trials with the characteristic of interest. We derived a closed-form power function and sample size formula for estimating the impact of trial characteristics in meta-epidemiological studies. Our analytical results can be used as a 'rule of thumb' for sample size calculation for a meta-epidemiologic study. A more accurate sample size can be derived with a simulation study.
Calculating Sample Size in Trials Using Historical Controls
Zhang, Song; Cao, Jing; Ahn, Chul
2011-01-01
Background Makuch and Simon [1] developed a sample size formula for historical control trials. When assessing power, they assumed the true control treatment effect to be equal to the observed effect from the historical control group. Many researchers have pointed out that the M-S approach does not preserve the nominal power and type I error when considering the uncertainty in the true historical control treatment effect. Purpose To develop a sample size formula that properly accounts for the underlying randomness in the observations from the historical control group. Methods We reveal the extremely skewed nature in the distributions of power and type I error, obtained over all the random realizations of the historical control data. The skewness motivates us to derive a sample size formula that controls the percentiles, instead of the means, of the power and type I error. Results A closed-form sample size formula is developed to control arbitrary percentiles of power and type I error for historical control trials. A simulation study further demonstrates that this approach preserves the operational characteristics in a more realistic scenario where the population variances are unknown and replaced by sample variances. Limitations The closed-form sample size formula is derived for continuous outcomes. The formula is more complicated for binary or survival time outcomes. Conclusions We have derived a closed-form sample size formula that controls the percentiles instead of means of power and type I error in historical control trials, which have extremely skewed distributions over all the possible realizations of historical control data. PMID:20573638
Statistical identifiability and sample size calculations for serial seroepidemiology
Vinh, Dao Nguyen; Boni, Maciej F.
2015-01-01
Inference on disease dynamics is typically performed using case reporting time series of symptomatic disease. The inferred dynamics will vary depending on the reporting patterns and surveillance system for the disease in question, and the inference will miss mild or underreported epidemics. To eliminate the variation introduced by differing reporting patterns and to capture asymptomatic or subclinical infection, inferential methods can be applied to serological data sets instead of case reporting data. To reconstruct complete disease dynamics, one would need to collect a serological time series. In the statistical analysis presented here, we consider a particular kind of serological time series with repeated, periodic collections of population-representative serum. We refer to this study design as a serial seroepidemiology (SSE) design, and we base the analysis on our epidemiological knowledge of influenza. We consider a study duration of three to four years, during which a single antigenic type of influenza would be circulating, and we evaluate our ability to reconstruct disease dynamics based on serological data alone. We show that the processes of reinfection, antibody generation, and antibody waning confound each other and are not always statistically identifiable, especially when dynamics resemble a non-oscillating endemic equilibrium behavior. We introduce some constraints to partially resolve this confounding, and we show that transmission rates and basic reproduction numbers can be accurately estimated in SSE study designs. Seasonal forcing is more difficult to identify as serology-based studies only detect oscillations in antibody titers of recovered individuals, and these oscillations are typically weaker than those observed for infected individuals. To accurately estimate the magnitude and timing of seasonal forcing, serum samples should be collected every two months and 200 or more samples should be included in each collection; this sample size estimate
Basic concepts for sample size calculation: Critical step for any clinical trials!
Gupta, KK; Attri, JP; Singh, A; Kaur, H; Kaur, G
2016-01-01
Quality of clinical trials has improved steadily over last two decades, but certain areas in trial methodology still require special attention like in sample size calculation. The sample size is one of the basic steps in planning any clinical trial and any negligence in its calculation may lead to rejection of true findings and false results may get approval. Although statisticians play a major role in sample size estimation basic knowledge regarding sample size calculation is very sparse among most of the anesthesiologists related to research including under trainee doctors. In this review, we will discuss how important sample size calculation is for research studies and the effects of underestimation or overestimation of sample size on project's results. We have highlighted the basic concepts regarding various parameters needed to calculate the sample size along with examples. PMID:27375390
Sample size calculation for the one-sample log-rank test.
Schmidt, René; Kwiecien, Robert; Faldum, Andreas; Berthold, Frank; Hero, Barbara; Ligges, Sandra
2015-03-15
An improved method of sample size calculation for the one-sample log-rank test is provided. The one-sample log-rank test may be the method of choice if the survival curve of a single treatment group is to be compared with that of a historic control. Such settings arise, for example, in clinical phase-II trials if the response to a new treatment is measured by a survival endpoint. Present sample size formulas for the one-sample log-rank test are based on the number of events to be observed, that is, in order to achieve approximately a desired power for allocated significance level and effect the trial is stopped as soon as a certain critical number of events are reached. We propose a new stopping criterion to be followed. Both approaches are shown to be asymptotically equivalent. For small sample size, though, a simulation study indicates that the new criterion might be preferred when planning a corresponding trial. In our simulations, the trial is usually underpowered, and the aspired significance level is not exploited if the traditional stopping criterion based on the number of events is used, whereas a trial based on the new stopping criterion maintains power with the type-I error rate still controlled.
A Comparative Study of Power and Sample Size Calculations for Multivariate General Linear Models
ERIC Educational Resources Information Center
Shieh, Gwowen
2003-01-01
Repeated measures and longitudinal studies arise often in social and behavioral science research. During the planning stage of such studies, the calculations of sample size are of particular interest to the investigators and should be an integral part of the research projects. In this article, we consider the power and sample size calculations for…
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
Code of Federal Regulations, 2010 CFR
2010-10-01
... 45 Public Welfare 4 2010-10-01 2010-10-01 false Calculating Sample Size for NYTD Follow-Up Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... REQUIREMENTS APPLICABLE TO TITLE IV-E Pt. 1356, App. C Appendix C to Part 1356—Calculating Sample Size for...
Sample Size Calculations for Precise Interval Estimation of the Eta-Squared Effect Size
ERIC Educational Resources Information Center
Shieh, Gwowen
2015-01-01
Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…
Sample Size Calculation of Clinical Trials Published in Two Leading Endodontic Journals
Shahravan, Arash; Haghdoost, Ali-Akbar; Rad, Maryam; Hashemipoor, Maryamalsadat; Sharifi, Maryam
2014-01-01
Introduction: The purpose of this article was to evaluate the quality of sample size calculation reports in published clinical trials in Journal of Endodontics and International Endodontic Journal in years 2000-1 and 2009-10. Materials and Methods: Articles fulfilling the inclusion criteria were collected. The criteria were: publication year, research design, types of control group, reporting sample size calculation, the number of participants in each group, study outcome, amount of type I (α) and II (β) errors, method used for estimating prevalence or standard deviation, percentage of meeting the expected sample size and considering clinically importance level in sample size calculation. Data were extracted from all included articles. Descriptive analyses were conducted. Inferential statistical analyses were done using independent T-test and Chi-square test with the significance level set at 0.05. Results: There was a statistically significant increase in years between 2009 and 10 compared to 2000-1 in terms of reporting sample size calculation (P=0.002), reporting clinically importance level (P=0.003) and in samples size of clinical trials (P=0.01). But there was not any significant difference between two journals in terms of reporting sample size calculation, type of control group, frequency of various study designs and frequency of positive and negative clinical trials in different time periods (P>0.05). Conclusion: Sample size calculation in endodontic clinical trials improved significantly in 2009-10 when compared to 2000-1; however further improvements would be desirable. PMID:24396377
Effects of Sample Size on Estimates of Population Growth Rates Calculated with Matrix Models
Fiske, Ian J.; Bruna, Emilio M.; Bolker, Benjamin M.
2008-01-01
Background Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (λ) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of λ–Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of λ due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of λ. Methodology/Principal Findings Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating λ for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of λ with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. Conclusions/Significance We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities. PMID:18769483
An opportunity cost approach to sample size calculation in cost-effectiveness analysis.
Gafni, A; Walter, S D; Birch, S; Sendi, P
2008-01-01
The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers.
A simple formula for the calculation of sample size in pilot studies.
Viechtbauer, Wolfgang; Smits, Luc; Kotz, Daniel; Budé, Luc; Spigt, Mark; Serroyen, Jan; Crutzen, Rik
2015-11-01
One of the goals of a pilot study is to identify unforeseen problems, such as ambiguous inclusion or exclusion criteria or misinterpretations of questionnaire items. Although sample size calculation methods for pilot studies have been proposed, none of them are directed at the goal of problem detection. In this article, we present a simple formula to calculate the sample size needed to be able to identify, with a chosen level of confidence, problems that may arise with a given probability. If a problem exists with 5% probability in a potential study participant, the problem will almost certainly be identified (with 95% confidence) in a pilot study including 59 participants. PMID:26146089
[On the impact of sample size calculation and power in clinical research].
Held, Ulrike
2014-10-01
The aim of a clinical trial is to judge the efficacy of a new therapy or drug. In the planning phase of the study, the calculation of the necessary sample size is crucial in order to obtain a meaningful result. The study design, the expected treatment effect in outcome and its variability, power and level of significance are factors which determine the sample size. It is often difficult to fix these parameters prior to the start of the study, but related papers from the literature can be helpful sources for the unknown quantities. For scientific as well as ethical reasons it is necessary to calculate the sample size in advance in order to be able to answer the study question. PMID:25270749
Power and Sample Size Calculations for Multivariate Linear Models with Random Explanatory Variables
ERIC Educational Resources Information Center
Shieh, Gwowen
2005-01-01
This article considers the problem of power and sample size calculations for normal outcomes within the framework of multivariate linear models. The emphasis is placed on the practical situation that not only the values of response variables for each subject are just available after the observations are made, but also the levels of explanatory…
A Unified Approach to Power Calculation and Sample Size Determination for Random Regression Models
ERIC Educational Resources Information Center
Shieh, Gwowen
2007-01-01
The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
ERIC Educational Resources Information Center
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…
Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning
ERIC Educational Resources Information Center
Li, Zhushan
2014-01-01
Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…
Uniform power method for sample size calculation in historical control studies with binary response.
Lee, J J; Tseng, C
2001-08-01
Makuch and Simon gave a sample size calculation formula for historical control (HC) studies that assumed that the observed response rate in the control group is the true response rate. We dropped this assumption and computed the expected power and expected sample size to evaluate the performance of the procedure under the omniscient model. When there is uncertainty in the HC response rate but this uncertainty is not considered, Makuch and Simon's method produces a sample size that gives a considerably lower power than that specified. Even the larger sample size obtained from the randomized design formula and applied to the HC setting does not guarantee the advertised power in the HC setting. We developed a new uniform power method to search for the sample size required for the experimental group to yield an exact power without relying on the estimated HC response rate being perfectly correct. The new method produces the correct uniform predictive power for all permissible response rates. The resulting sample size is closer to the sample size needed for the randomized design than Makuch and Simon's method, especially when there is a small difference in response rates or a limited sample size in the HC group. HC design may be a viable option in clinical trials when the patient selection bias and the outcome evaluation bias can be minimized. However, the common perception of the extra sample size savings is largely unjustified without the strong assumption that the observed HC response rate is equal to the true control response rate. Generally speaking, results from HC studies need to be confirmed by studies with concurrent controls and cannot be used for making definitive decisions.
Exact Power and Sample Size Calculations for the Two One-Sided Tests of Equivalence
Shieh, Gwowen
2016-01-01
Equivalent testing has been strongly recommended for demonstrating the comparability of treatment effects in a wide variety of research fields including medical studies. Although the essential properties of the favorable two one-sided tests of equivalence have been addressed in the literature, the associated power and sample size calculations were illustrated mainly for selecting the most appropriate approximate method. Moreover, conventional power analysis does not consider the allocation restrictions and cost issues of different sample size choices. To extend the practical usefulness of the two one-sided tests procedure, this article describes exact approaches to sample size determinations under various allocation and cost considerations. Because the presented features are not generally available in common software packages, both R and SAS computer codes are presented to implement the suggested power and sample size computations for planning equivalence studies. The exact power function of the TOST procedure is employed to compute optimal sample sizes under four design schemes allowing for different allocation and cost concerns. The proposed power and sample size methodology should be useful for medical sciences to plan equivalence studies. PMID:27598468
Exact Power and Sample Size Calculations for the Two One-Sided Tests of Equivalence.
Shieh, Gwowen
2016-01-01
Equivalent testing has been strongly recommended for demonstrating the comparability of treatment effects in a wide variety of research fields including medical studies. Although the essential properties of the favorable two one-sided tests of equivalence have been addressed in the literature, the associated power and sample size calculations were illustrated mainly for selecting the most appropriate approximate method. Moreover, conventional power analysis does not consider the allocation restrictions and cost issues of different sample size choices. To extend the practical usefulness of the two one-sided tests procedure, this article describes exact approaches to sample size determinations under various allocation and cost considerations. Because the presented features are not generally available in common software packages, both R and SAS computer codes are presented to implement the suggested power and sample size computations for planning equivalence studies. The exact power function of the TOST procedure is employed to compute optimal sample sizes under four design schemes allowing for different allocation and cost concerns. The proposed power and sample size methodology should be useful for medical sciences to plan equivalence studies. PMID:27598468
Tavernier, Elsa; Trinquart, Ludovic; Giraudeau, Bruno
2016-01-01
Sample sizes for randomized controlled trials are typically based on power calculations. They require us to specify values for parameters such as the treatment effect, which is often difficult because we lack sufficient prior information. The objective of this paper is to provide an alternative design which circumvents the need for sample size calculation. In a simulation study, we compared a meta-experiment approach to the classical approach to assess treatment efficacy. The meta-experiment approach involves use of meta-analyzed results from 3 randomized trials of fixed sample size, 100 subjects. The classical approach involves a single randomized trial with the sample size calculated on the basis of an a priori-formulated hypothesis. For the sample size calculation in the classical approach, we used observed articles to characterize errors made on the formulated hypothesis. A prospective meta-analysis of data from trials of fixed sample size provided the same precision, power and type I error rate, on average, as the classical approach. The meta-experiment approach may provide an alternative design which does not require a sample size calculation and addresses the essential need for study replication; results may have greater external validity. PMID:27362939
Sample size calculations for clinical trials targeting tauopathies: A new potential disease target
Whitwell, Jennifer L.; Duffy, Joseph R.; Strand, Edythe A.; Machulda, Mary M.; Tosakulwong, Nirubol; Weigand, Stephen D.; Senjem, Matthew L.; Spychalla, Anthony J.; Gunter, Jeffrey L.; Petersen, Ronald C.; Jack, Clifford R.; Josephs, Keith A.
2015-01-01
Disease-modifying therapies are being developed to target tau pathology, and should, therefore, be tested in primary tauopathies. We propose that progressive apraxia of speech should be considered one such target group. In this study, we investigate potential neuroimaging and clinical outcome measures for progressive apraxia of speech and determine sample size estimates for clinical trials. We prospectively recruited 24 patients with progressive apraxia of speech who underwent two serial MRI with an interval of approximately two years. Detailed speech and language assessments included the Apraxia of Speech Rating Scale (ASRS) and Motor Speech Disorders (MSD) severity scale. Rates of ventricular expansion and rates of whole brain, striatal and midbrain atrophy were calculated. Atrophy rates across 38 cortical regions were also calculated and the regions that best differentiated patients from controls were selected. Sample size estimates required to power placebo-controlled treatment trials were calculated. The smallest sample size estimates were obtained with rates of atrophy of the precentral gyrus and supplementary motor area, with both measures requiring less than 50 subjects per arm to detect a 25% treatment effect with 80% power. These measures outperformed the other regional and global MRI measures and the clinical scales. Regional rates of cortical atrophy therefore provide the best outcome measures in progressive apraxia of speech. The small sample size estimates demonstrate feasibility for including progressive apraxia of speech in future clinical treatment trials targeting tau. PMID:26076744
Sample size calculation for the Wilcoxon-Mann-Whitney test adjusting for ties.
Zhao, Yan D; Rahardja, Dewi; Qu, Yongming
2008-02-10
In this paper we study sample size calculation methods for the asymptotic Wilcoxon-Mann-Whitney test for data with or without ties. The existing methods are applicable either to data with ties or to data without ties but not to both cases. While the existing methods developed for data without ties perform well, the methods developed for data with ties have limitations in that they are either applicable to proportional odds alternatives or have computational difficulties. We propose a new method which has a closed-form formula and therefore is very easy to calculate. In addition, the new method can be applied to both data with or without ties. Simulations have demonstrated that the new sample size formula performs very well as the corresponding actual powers are close to the nominal powers.
Sample size calculation for the Wilcoxon-Mann-Whitney test adjusting for ties.
Zhao, Yan D; Rahardja, Dewi; Qu, Yongming
2008-02-10
In this paper we study sample size calculation methods for the asymptotic Wilcoxon-Mann-Whitney test for data with or without ties. The existing methods are applicable either to data with ties or to data without ties but not to both cases. While the existing methods developed for data without ties perform well, the methods developed for data with ties have limitations in that they are either applicable to proportional odds alternatives or have computational difficulties. We propose a new method which has a closed-form formula and therefore is very easy to calculate. In addition, the new method can be applied to both data with or without ties. Simulations have demonstrated that the new sample size formula performs very well as the corresponding actual powers are close to the nominal powers. PMID:17487941
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.
NASA Astrophysics Data System (ADS)
Shao, Quanxi; Wang, You-Gan
2009-09-01
Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.
ERIC Educational Resources Information Center
Luh, Wei-Ming; Guo, Jiin-Huarng
2011-01-01
Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…
Statistical issues including design and sample size calculation in thorough QT/QTc studies.
Zhang, Joanne; Machado, Stella G
2008-01-01
After several drugs were removed from the market in recent years because of death due to ventricular tachycardia resulting from drug-induced QT prolongation (Khongphatthanayothin et al., 1998; Lasser et al., 2002; Pratt et al., 1994; Wysowski et al., 2001), the ICH Regulatory agencies requested all sponsors of new drugs to conduct a clinical study, named a Thorough QT/QTc (TQT) study, to assess any possible QT prolongation due to the study drug. The final version of the ICH E14 guidance (ICH, 2005) for "The Clinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential for Nonantiarrhythmic Drugs" was released in May 2005. The purpose of the ICH E14 guidance (ICH, 2005) is to provide recommendations to sponsors concerning the design, conduct, analysis, and interpretation of clinical studies to assess the potential of a drug to delay cardiac repolarization. The guideline, however, is not specific on several issues. In this paper, we try to address some statistical issues, including study design, primary statistical analysis, assay sensitivity analysis, and the calculation of the sample size for a TQT study.
Reliable calculation in probabilistic logic: Accounting for small sample size and model uncertainty
Ferson, S.
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.
Divine, George; Norton, H James; Hunt, Ronald; Dienemann, Jacqueline
2013-09-01
When a study uses an ordinal outcome measure with unknown differences in the anchors and a small range such as 4 or 7, use of the Wilcoxon rank sum test or the Wilcoxon signed rank test may be most appropriate. However, because nonparametric methods are at best indirect functions of standard measures of location such as means or medians, the choice of the most appropriate summary measure can be difficult. The issues underlying use of these tests are discussed. The Wilcoxon-Mann-Whitney odds directly reflects the quantity that the rank sum procedure actually tests, and thus it can be a superior summary measure. Unlike the means and medians, its value will have a one-to-one correspondence with the Wilcoxon rank sum test result. The companion article appearing in this issue of Anesthesia & Analgesia ("Aromatherapy as Treatment for Postoperative Nausea: A Randomized Trial") illustrates these issues and provides an example of a situation for which the medians imply no difference between 2 groups, even though the groups are, in fact, quite different. The trial cited also provides an example of a single sample that has a median of zero, yet there is a substantial shift for much of the nonzero data, and the Wilcoxon signed rank test is quite significant. These examples highlight the potential discordance between medians and Wilcoxon test results. Along with the issues surrounding the choice of a summary measure, there are considerations for the computation of sample size and power, confidence intervals, and multiple comparison adjustment. In addition, despite the increased robustness of the Wilcoxon procedures relative to parametric tests, some circumstances in which the Wilcoxon tests may perform poorly are noted, along with alternative versions of the procedures that correct for such limitations. PMID:23456667
Inference and sample size calculation in the fit assessment of filtering facepiece respirators.
Zhang, Zhiwei; Kotz, Richard M
2008-01-01
Filtering facepiece respirators have recently been cleared by the U.S. Food and Drug Administration (FDA) for use by the general public in public health medical emergencies such as pandemic influenza. In the fit assessment of these devices it is important to distinguish between the two sources of variability: population heterogeneity and random fluctuations over repeated donnings. The FDA Special Controls Guidance Document (SCGD) which describes these devices and their evaluation, recommends that the fit performance of a filtering facepiece respirator be evaluated in terms of the proportion of users who will receive a specified level of protection 95% of the time. A point estimator of this proportion is easily obtained under an analysis of variance model, and the SCGD suggests bootstrap as one possible approach to interval estimation. This paper describes a closed-form procedure to obtain confidence intervals and provides sample size formulas. Simulation results suggest that the proposed procedure performs well in realistic settings and compares favorably to two simple bootstrap procedures. PMID:18607803
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
Code of Federal Regulations, 2012 CFR
2012-10-01
... Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... Follow-Up Populations 1. Using Finite Population Correction The Finite Population Correction (FPC) is applied when the sample is drawn from a population of one to 5,000 youth, because the sample is more...
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
Code of Federal Regulations, 2011 CFR
2011-10-01
... Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... Follow-Up Populations 1. Using Finite Population Correction The Finite Population Correction (FPC) is applied when the sample is drawn from a population of one to 5,000 youth, because the sample is more...
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
Code of Federal Regulations, 2014 CFR
2014-10-01
... Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... Follow-Up Populations 1. Using Finite Population Correction The Finite Population Correction (FPC) is applied when the sample is drawn from a population of one to 5,000 youth, because the sample is more...
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
Code of Federal Regulations, 2013 CFR
2013-10-01
... Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... Follow-Up Populations 1. Using Finite Population Correction The Finite Population Correction (FPC) is applied when the sample is drawn from a population of one to 5,000 youth, because the sample is more...
Phylogenetic effective sample size.
Bartoszek, Krzysztof
2016-10-21
In this paper I address the question-how large is a phylogenetic sample? I propose a definition of a phylogenetic effective sample size for Brownian motion and Ornstein-Uhlenbeck processes-the regression effective sample size. I discuss how mutual information can be used to define an effective sample size in the non-normal process case and compare these two definitions to an already present concept of effective sample size (the mean effective sample size). Through a simulation study I find that the AICc is robust if one corrects for the number of species or effective number of species. Lastly I discuss how the concept of the phylogenetic effective sample size can be useful for biodiversity quantification, identification of interesting clades and deciding on the importance of phylogenetic correlations. PMID:27343033
ERIC Educational Resources Information Center
Dong, Nianbo; Maynard, Rebecca
2013-01-01
This paper and the accompanying tool are intended to complement existing supports for conducting power analysis tools by offering a tool based on the framework of Minimum Detectable Effect Sizes (MDES) formulae that can be used in determining sample size requirements and in estimating minimum detectable effect sizes for a range of individual- and…
Matsouaka, Roland A; Betensky, Rebecca A
2015-02-10
We consider a clinical trial of a potentially lethal disease in which patients are randomly assigned to two treatment groups and are followed for a fixed period of time; a continuous endpoint is measured at the end of follow-up. For some patients; however, death (or severe disease progression) may preclude measurement of the endpoint. A statistical analysis that includes only patients with endpoint measurements may be biased. An alternative analysis includes all randomized patients, with rank scores assigned to the patients who are available for the endpoint measurement on the basis of the magnitude of their responses and with 'worst-rank' scores assigned to those patients whose death precluded the measurement of the continuous endpoint. The worst-rank scores are worse than all observed rank scores. The treatment effect is then evaluated using the Wilcoxon-Mann-Whitney test. In this paper, we derive closed-form formulae for the power and sample size of the Wilcoxon-Mann-Whitney test when missing measurements of the continuous endpoints because of death are replaced by worst-rank scores. We distinguish two approaches for assigning the worst-rank scores. In the tied worst-rank approach, all deaths are weighted equally, and the worst-rank scores are set to a single value that is worse than all measured responses. In the untied worst-rank approach, the worst-rank scores further rank patients according to their time of death, so that an earlier death is considered worse than a later death, which in turn is worse than all measured responses. In addition, we propose four methods for the implementation of the sample size formulae for a trial with expected early death. We conduct Monte Carlo simulation studies to evaluate the accuracy of our power and sample size formulae and to compare the four sample size estimation methods.
Eldridge, S; Cryer, C; Feder, G; Underwood, M
2001-02-15
Because of the central role of the general practice in the delivery of British primary care, intervention trials in primary care often use the practice as the unit of randomization. The creation of primary care groups (PCGs) in April 1999 changed the organization of primary care and the commissioning of secondary care services. PCGs will directly affect the organization and delivery of primary, secondary and social care services. The PCG therefore becomes an appropriate target for organizational and educational interventions. Trials testing these interventions should involve randomization by PCG. This paper discusses the sample size required for a trial in primary care assessing the effect of a falls prevention programme among older people. In this trial PCGs will be randomized. The sample size calculations involve estimating intra-PCG correlation in primary outcome: fractured femur rate for those 65 years and over. No data on fractured femur rate were available at PCG level. PCGs are, however, similar in size and often coterminous with local authorities. Therefore, intra-PCG correlation in fractured femur rate was estimated from the intra-local authority correlation calculated from routine data. Three alternative trial designs are considered. In the first design, PCGs are selected for inclusion in the trial from the total population of England (eight regions). In the second design, PCGs are selected from two regions only. The third design is similar to the second except that PCGs are stratified by region and baseline value of fracture rate. Intracluster correlation is estimated for each of these designs using two methods: an approximation which assumes cluster sizes are equal and an alternative method which takes account of the fact that cluster sizes vary. Estimates of sample size required vary between 26 and 7 PCGs in each intervention group, depending on the trial design and the method used to calculate sample size. Not unexpectedly, stratification by baseline
Hanson, R L; Looker, H C; Ma, L; Muller, Y L; Baier, L J; Knowler, W C
2006-05-01
Association (e.g. case-control) studies are often used to finely map loci identified by linkage analysis. We investigated the influence of various parameters on power and sample size requirements for such a study. Calculations were performed for various values of a high-risk functional allele (fA), frequency of a marker allele associated with the high risk allele (f1), degree of linkage disquilibrium between functional and marker alleles (D') and trait heritability attributable to the functional locus (h2). The calculations show that if cases and controls are selected from equal but opposite extreme quantiles of a quantitative trait, the primary determinants of power are h2 and the specific quantiles selected. For a dichotomous trait, power also depends on population prevalence. Power is optimal if functional alleles are studied (fA= f1 and D'= 1.0) and can decrease substantially as D' diverges from 1.0 or as f(1) diverges from fA. These analyses suggest that association studies to finely map loci are most powerful if potential functional polymorphisms are identified a priori or if markers are typed to maximize haplotypic diversity. In the absence of such information, expected minimum power at a given location for a given sample size can be calculated by specifying a range of potential frequencies for fA (e.g. 0.1-0.9) and determining power for all markers within the region with specification of the expected D' between the markers and the functional locus. This method is illustrated for a fine-mapping project with 662 single nucleotide polymorphisms in 24 Mb. Regions differed by marker density and allele frequencies. Thus, in some, power was near its theoretical maximum and little additional information is expected from additional markers, while in others, additional markers appear to be necessary. These methods may be useful in the analysis and interpretation of fine-mapping studies. PMID:16674556
Gao, Feng; Manatunga, Amita K; Chen, Shande
2005-04-01
Manatunga and Chen [A.K. Manatunga, S. Chen, Sample size estimation for survival outcomes in cluster-randomized studies with small cluster sizes, Biometrics 56 (2000) 616-621] proposed a method to estimate sample size and power for cluster-randomized studies where the primary outcome variable was survival time. The sample size formula was constructed by considering a bivariate marginal distribution (Clayton-Oakes model) with univariate exponential marginal distributions. In this paper, a user-friendly FORTRAN 90 program was provided to implement this method and a simple example was used to illustrate the features of the program.
Calculating body frame size (image)
... boned category. Determining frame size: To determine the body frame size, measure the wrist with a tape measure and use the following chart to determine whether the person is small, medium, or large boned. Women: Height under 5'2" Small = wrist size less ...
van Velthoven, Michelle Helena; Li, Ye; Wang, Wei; Du, Xiaozhen; Chen, Li; Wu, Qiong; Majeed, Azeem; Zhang, Yanfeng; Car, Josip
2013-01-01
Background An important issue for mHealth evaluation is the lack of information for sample size calculations. Objective To explore factors that influence sample size calculations for mHealth–based studies and to suggest strategies for increasing the participation rate. Methods We explored factors influencing recruitment and follow–up of participants (caregivers of children) in an mHealth text messaging data collection cross–over study. With help of village doctors, we recruited 1026 (25%) caregivers of children under five out of the 4170 registered. To explore factors influencing recruitment and provide recommendations for improving recruitment, we conducted semi–structured interviews with village doctors. Of the 1014 included participants, 662 (65%) responded to the first question about willingness to participate, 538 (53%) responded to the first survey question and 356 (35%) completed the text message survey. To explore factors influencing follow–up and provide recommendations for improving follow–up, we conducted interviews with participants. We added views from the researchers who were involved in the study to contextualize the findings. Results We found several factors influencing recruitment related to the following themes: experiences with recruitment, village doctors’ work, village doctors’ motivations, caregivers’ characteristics, caregivers’ motivations. Village doctors gave several recommendations for ways to recruit more caregivers and we added our views to these. We found the following factors influencing follow–up: mobile phone usage, ability to use mobile phone, problems with mobile phone, checking mobile phone, available time, paying back text message costs, study incentives, subjective norm, culture, trust, perceived usefulness of process, perceived usefulness of outcome, perceived ease of use, attitude, behavioural intention to use, and actual use. From our perspective, factors influencing follow–up were: different
Biostatistics Series Module 5: Determining Sample Size.
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 - β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the
Biostatistics Series Module 5: Determining Sample Size.
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 - β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the
Biostatistics Series Module 5: Determining Sample Size
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the
Biostatistics Series Module 5: Determining Sample Size
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the
Sample size: how many patients are necessary?
Fayers, P. M.; Machin, D.
1995-01-01
The need for sample size calculations is briefly reviewed: many of the arguments against small trials are already well known, and we only cursorily repeat them in passing. Problems that arise in the estimation of sample size are then discussed, with particular reference to survival studies. However, most of the issues which we discuss are equally applicable to other types of study. Finally, prognostic factor analysis designs are discussed, since this is another area in which experience shows that far too many studies are of an inadequate size and yield misleading results. PMID:7599035
Sample sizes for confidence limits for reliability.
Darby, John L.
2010-02-01
We recently performed an evaluation of the implications of a reduced stockpile of nuclear weapons for surveillance to support estimates of reliability. We found that one technique developed at Sandia National Laboratories (SNL) under-estimates the required sample size for systems-level testing. For a large population the discrepancy is not important, but for a small population it is important. We found that another technique used by SNL provides the correct required sample size. For systems-level testing of nuclear weapons, samples are selected without replacement, and the hypergeometric probability distribution applies. Both of the SNL techniques focus on samples without defects from sampling without replacement. We generalized the second SNL technique to cases with defects in the sample. We created a computer program in Mathematica to automate the calculation of confidence for reliability. We also evaluated sampling with replacement where the binomial probability distribution applies.
Monte Carlo small-sample perturbation calculations
Feldman, U.; Gelbard, E.; Blomquist, R.
1983-01-01
Two different Monte Carlo methods have been developed for benchmark computations of small-sample-worths in simplified geometries. The first is basically a standard Monte Carlo perturbation method in which neutrons are steered towards the sample by roulette and splitting. One finds, however, that two variance reduction methods are required to make this sort of perturbation calculation feasible. First, neutrons that have passed through the sample must be exempted from roulette. Second, neutrons must be forced to undergo scattering collisions in the sample. Even when such methods are invoked, however, it is still necessary to exaggerate the volume fraction of the sample by drastically reducing the size of the core. The benchmark calculations are then used to test more approximate methods, and not directly to analyze experiments. In the second method the flux at the surface of the sample is assumed to be known. Neutrons entering the sample are drawn from this known flux and tracking by Monte Carlo. The effect of the sample or the fission rate is then inferred from the histories of these neutrons. The characteristics of both of these methods are explored empirically.
Improved sample size determination for attributes and variables sampling
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.
Sample-size requirements for evaluating population size structure
Vokoun, J.C.; Rabeni, C.F.; Stanovick, J.S.
2001-01-01
A method with an accompanying computer program is described to estimate the number of individuals needed to construct a sample length-frequency with a given accuracy and precision. First, a reference length-frequency assumed to be accurate for a particular sampling gear and collection strategy was constructed. Bootstrap procedures created length-frequencies with increasing sample size that were randomly chosen from the reference data and then were compared with the reference length-frequency by calculating the mean squared difference. Outputs from two species collected with different gears and an artificial even length-frequency are used to describe the characteristics of the method. The relations between the number of individuals used to construct a length-frequency and the similarity to the reference length-frequency followed a negative exponential distribution and showed the importance of using 300-400 individuals whenever possible.
Gordon, Derek; Finch, Stephen J; Nothnagel, Michael; Ott, Jürg
2002-01-01
The purpose of this work is to quantify the effects that errors in genotyping have on power and the sample size necessary to maintain constant asymptotic Type I and Type II error rates (SSN) for case-control genetic association studies between a disease phenotype and a di-allelic marker locus, for example a single nucleotide polymorphism (SNP) locus. We consider the effects of three published models of genotyping errors on the chi-square test for independence in the 2 x 3 table. After specifying genotype frequencies for the marker locus conditional on disease status and error model in both a genetic model-based and a genetic model-free framework, we compute the asymptotic power to detect association through specification of the test's non-centrality parameter. This parameter determines the functional dependence of SSN on the genotyping error rates. Additionally, we study the dependence of SSN on linkage disequilibrium (LD), marker allele frequencies, and genotyping error rates for a dominant disease model. Increased genotyping error rate requires a larger SSN. Every 1% increase in sum of genotyping error rates requires that both case and control SSN be increased by 2-8%, with the extent of increase dependent upon the error model. For the dominant disease model, SSN is a nonlinear function of LD and genotyping error rate, with greater SSN for lower LD and higher genotyping error rate. The combination of lower LD and higher genotyping error rates requires a larger SSN than the sum of the SSN for the lower LD and for the higher genotyping error rate.
ERIC Educational Resources Information Center
Mendoza, Jorge L.; Stafford, Karen L.
2001-01-01
Introduces a computer package written for Mathematica, the purpose of which is to perform a number of difficult iterative functions with respect to the squared multiple correlation coefficient under the fixed and random models. These functions include computation of the confidence interval upper and lower bounds, power calculation, calculation of…
NASA Astrophysics Data System (ADS)
Heckmann, Tobias; Gegg, Katharina; Becht, Michael
2013-04-01
Statistical approaches to landslide susceptibility modelling on the catchment and regional scale are used very frequently compared to heuristic and physically based approaches. In the present study, we deal with the problem of the optimal sample size for a logistic regression model. More specifically, a stepwise approach has been chosen in order to select those independent variables (from a number of derivatives of a digital elevation model and landcover data) that explain best the spatial distribution of debris flow initiation zones in two neighbouring central alpine catchments in Austria (used mutually for model calculation and validation). In order to minimise problems arising from spatial autocorrelation, we sample a single raster cell from each debris flow initiation zone within an inventory. In addition, as suggested by previous work using the "rare events logistic regression" approach, we take a sample of the remaining "non-event" raster cells. The recommendations given in the literature on the size of this sample appear to be motivated by practical considerations, e.g. the time and cost of acquiring data for non-event cases, which do not apply to the case of spatial data. In our study, we aim at finding empirically an "optimal" sample size in order to avoid two problems: First, a sample too large will violate the independent sample assumption as the independent variables are spatially autocorrelated; hence, a variogram analysis leads to a sample size threshold above which the average distance between sampled cells falls below the autocorrelation range of the independent variables. Second, if the sample is too small, repeated sampling will lead to very different results, i.e. the independent variables and hence the result of a single model calculation will be extremely dependent on the choice of non-event cells. Using a Monte-Carlo analysis with stepwise logistic regression, 1000 models are calculated for a wide range of sample sizes. For each sample size
Sample Size and Correlational Inference
ERIC Educational Resources Information Center
Anderson, Richard B.; Doherty, Michael E.; Friedrich, Jeff C.
2008-01-01
In 4 studies, the authors examined the hypothesis that the structure of the informational environment makes small samples more informative than large ones for drawing inferences about population correlations. The specific purpose of the studies was to test predictions arising from the signal detection simulations of R. B. Anderson, M. E. Doherty,…
On Sample Size Requirements for Johansen's Test.
ERIC Educational Resources Information Center
Coombs, William T.; Algina, James
1996-01-01
Type I error rates for the Johansen test were estimated using simulated data for a variety of conditions. Results indicate that Type I error rates for the Johansen test depend heavily on the number of groups and the ratio of the smallest sample size to the number of dependent variables. Sample size guidelines are presented. (SLD)
Sample size estimation in prevalence studies.
Arya, Ravindra; Antonisamy, Belavendra; Kumar, Sushil
2012-11-01
Estimation of appropriate sample size for prevalence surveys presents many challenges, particularly when the condition is very rare or has a tendency for geographical clustering. Sample size estimate for prevalence studies is a function of expected prevalence and precision for a given level of confidence expressed by the z statistic. Choice of the appropriate values for these variables is sometimes not straight-forward. Certain other situations do not fulfil the assumptions made in the conventional equation and present a special challenge. These situations include, but are not limited to, smaller population size in relation to sample size, sampling technique or missing data. This paper discusses practical issues in sample size estimation for prevalence studies with an objective to help clinicians and healthcare researchers make more informed decisions whether reviewing or conducting such a study. PMID:22562262
How to Show that Sample Size Matters
ERIC Educational Resources Information Center
Kozak, Marcin
2009-01-01
This article suggests how to explain a problem of small sample size when considering correlation between two Normal variables. Two techniques are shown: one based on graphs and the other on simulation. (Contains 3 figures and 1 table.)
[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].
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.
Experimental determination of size distributions: analyzing proper sample sizes
NASA Astrophysics Data System (ADS)
Buffo, A.; Alopaeus, V.
2016-04-01
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.
A New Sample Size Formula for Regression.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.
The focus of this research was to determine the efficacy of a new method of selecting sample sizes for multiple linear regression. A Monte Carlo simulation was used to study both empirical predictive power rates and empirical statistical power rates of the new method and seven other methods: those of C. N. Park and A. L. Dudycha (1974); J. Cohen…
Exploratory Factor Analysis with Small Sample Sizes
ERIC Educational Resources Information Center
de Winter, J. C. F.; Dodou, D.; Wieringa, P. A.
2009-01-01
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…
Sample size considerations for clinical research studies in nuclear cardiology.
Chiuzan, Cody; West, Erin A; Duong, Jimmy; Cheung, Ken Y K; Einstein, Andrew J
2015-12-01
Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software.
Sample size considerations for clinical research studies in nuclear cardiology.
Chiuzan, Cody; West, Erin A; Duong, Jimmy; Cheung, Ken Y K; Einstein, Andrew J
2015-12-01
Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software. PMID:26403142
Statistical Analysis Techniques for Small Sample Sizes
NASA Technical Reports Server (NTRS)
Navard, S. E.
1984-01-01
The small sample sizes problem which is encountered when dealing with analysis of space-flight data is examined. Because of such a amount of data available, careful analyses are essential to extract the maximum amount of information with acceptable accuracy. Statistical analysis of small samples is described. The background material necessary for understanding statistical hypothesis testing is outlined and the various tests which can be done on small samples are explained. Emphasis is on the underlying assumptions of each test and on considerations needed to choose the most appropriate test for a given type of analysis.
Sample size and optimal sample design in tuberculosis surveys
Sánchez-Crespo, J. L.
1967-01-01
Tuberculosis surveys sponsored by the World Health Organization have been carried out in different communities during the last few years. Apart from the main epidemiological findings, these surveys have provided basic statistical data for use in the planning of future investigations. In this paper an attempt is made to determine the sample size desirable in future surveys that include one of the following examinations: tuberculin test, direct microscopy, and X-ray examination. The optimum cluster sizes are found to be 100-150 children under 5 years of age in the tuberculin test, at least 200 eligible persons in the examination for excretors of tubercle bacilli (direct microscopy) and at least 500 eligible persons in the examination for persons with radiological evidence of pulmonary tuberculosis (X-ray). Modifications of the optimum sample size in combined surveys are discussed. PMID:5300008
Uncertainty of the sample size reduction step in pesticide residue analysis of large-sized crops.
Omeroglu, P Yolci; Ambrus, Á; Boyacioglu, D; Majzik, E Solymosne
2013-01-01
To estimate the uncertainty of the sample size reduction step, each unit in laboratory samples of papaya and cucumber was cut into four segments in longitudinal directions and two opposite segments were selected for further homogenisation while the other two were discarded. Jackfruit was cut into six segments in longitudinal directions, and all segments were kept for further analysis. To determine the pesticide residue concentrations in each segment, they were individually homogenised and analysed by chromatographic methods. One segment from each unit of the laboratory sample was drawn randomly to obtain 50 theoretical sub-samples with an MS Office Excel macro. The residue concentrations in a sub-sample were calculated from the weight of segments and the corresponding residue concentration. The coefficient of variation calculated from the residue concentrations of 50 sub-samples gave the relative uncertainty resulting from the sample size reduction step. The sample size reduction step, which is performed by selecting one longitudinal segment from each unit of the laboratory sample, resulted in relative uncertainties of 17% and 21% for field-treated jackfruits and cucumber, respectively, and 7% for post-harvest treated papaya. The results demonstrated that sample size reduction is an inevitable source of uncertainty in pesticide residue analysis of large-sized crops. The post-harvest treatment resulted in a lower variability because the dipping process leads to a more uniform residue concentration on the surface of the crops than does the foliar application of pesticides.
The Fisher-Yates Exact Test and Unequal Sample Sizes
ERIC Educational Resources Information Center
Johnson, Edgar M.
1972-01-01
A computational short cut suggested by Feldman and Klinger for the one-sided Fisher-Yates exact test is clarified and is extended to the calculation of probability values for certain two-sided tests when sample sizes are unequal. (Author)
Calculation of the size of ice hummocks
Kozitskii, I.E.
1985-03-01
Ice hummocks are often seen during the breakup of water bodies and are the result of shifting of the ice cover during spring movements and are confined both to the shore slope, or exposed stretches of the bottom, and to shallow waters. At the same time, the shore is often used for needs of construction, transportation, power engineering and economic purposes, and cases of damage to structures and disruption of operations by ice hummocks are known. The authors therefore study here the character and extent of the phenomenon as it affects the design of shore engineering structures. They add that existing standards do not fully reflect the composition of ice loads on structures, in connection with which it is expedient to theorize as regards the expected size of ice hummocks.
Fast RPA and GW calculations: cubic system size scaling
NASA Astrophysics Data System (ADS)
Kresse, Georg
The random phase approximation (RPA) to the correlation energy and the related GW approximation are among the most promising methods to obtain accurate correlation energy differences and QP energies from diagrammatic perturbation theory at reasonable computational cost. The calculations are, however, usually one to two orders of magnitude more demanding than conventional density functional theory calculations. Here, we show that a cubic system size scaling can be readily obtained reducing the computation time by one to two orders of magnitude for large systems. Furthermore, the scaling with respect to the number of k points used to sample the Brillouin zone can be reduced to linear order. In combination, this allows accurate and very well-converged single-point RPA and GW calculations, with a time complexity that is roughly on par or better than for self-consistent Hartree-Fock and hybrid-functional calculations. Furthermore, the talk discusses the relation between the RPA correlation energy and the GW approximation: the self-energy is the derivative of the RPA correlation energy with respect to the Green's function. The calculated self-energy can be used to compute QP-energies in the GW approximation, any first derivative of the total energy, as well as corrections to the correlation energy from the changes of the charge density when switching from DFT to a many-body body description (GW singles energy contribution).
40 CFR 80.127 - Sample size guidelines.
Code of Federal Regulations, 2011 CFR
2011-07-01
... attest engagement, the auditor shall sample relevant populations to which agreed-upon procedures will be... population; and (b) Sample size shall be determined using one of the following options: (1) Option 1. Determine the sample size using the following table: Sample Size, Based Upon Population Size No....
Hand calculations for transport of radioactive aerosols through sampling systems.
Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis
2014-05-01
Workplace air monitoring programs for sampling radioactive aerosols in nuclear facilities sometimes must rely on sampling systems to move the air to a sample filter in a safe and convenient location. These systems may consist of probes, straight tubing, bends, contractions and other components. Evaluation of these systems for potential loss of radioactive aerosols is important because significant losses can occur. However, it can be very difficult to find fully described equations to model a system manually for a single particle size and even more difficult to evaluate total system efficiency for a polydispersed particle distribution. Some software methods are available, but they may not be directly applicable to the components being evaluated and they may not be completely documented or validated per current software quality assurance requirements. This paper offers a method to model radioactive aerosol transport in sampling systems that is transparent and easily updated with the most applicable models. Calculations are shown with the R Programming Language, but the method is adaptable to other scripting languages. The method has the advantage of transparency and easy verifiability. This paper shows how a set of equations from published aerosol science models may be applied to aspiration and transport efficiency of aerosols in common air sampling system components. An example application using R calculation scripts is demonstrated. The R scripts are provided as electronic attachments.
Hand calculations for transport of radioactive aerosols through sampling systems.
Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis
2014-05-01
Workplace air monitoring programs for sampling radioactive aerosols in nuclear facilities sometimes must rely on sampling systems to move the air to a sample filter in a safe and convenient location. These systems may consist of probes, straight tubing, bends, contractions and other components. Evaluation of these systems for potential loss of radioactive aerosols is important because significant losses can occur. However, it can be very difficult to find fully described equations to model a system manually for a single particle size and even more difficult to evaluate total system efficiency for a polydispersed particle distribution. Some software methods are available, but they may not be directly applicable to the components being evaluated and they may not be completely documented or validated per current software quality assurance requirements. This paper offers a method to model radioactive aerosol transport in sampling systems that is transparent and easily updated with the most applicable models. Calculations are shown with the R Programming Language, but the method is adaptable to other scripting languages. The method has the advantage of transparency and easy verifiability. This paper shows how a set of equations from published aerosol science models may be applied to aspiration and transport efficiency of aerosols in common air sampling system components. An example application using R calculation scripts is demonstrated. The R scripts are provided as electronic attachments. PMID:24667389
(Sample) Size Matters! An Examination of Sample Size from the SPRINT Trial
Bhandari, Mohit; Tornetta, Paul; Rampersad, Shelly-Ann; Sprague, Sheila; Heels-Ansdell, Diane; Sanders, David W.; Schemitsch, Emil H.; Swiontkowski, Marc; Walter, Stephen
2012-01-01
Introduction Inadequate sample size and power in randomized trials can result in misleading findings. This study demonstrates the effect of sample size in a large, clinical trial by evaluating the results of the SPRINT (Study to Prospectively evaluate Reamed Intramedullary Nails in Patients with Tibial fractures) trial as it progressed. Methods The SPRINT trial evaluated reamed versus unreamed nailing of the tibia in 1226 patients, as well as in open and closed fracture subgroups (N=400 and N=826, respectively). We analyzed the re-operation rates and relative risk comparing treatment groups at 50, 100 and then increments of 100 patients up to the final sample size. Results at various enrollments were compared to the final SPRINT findings. Results In the final analysis, there was a statistically significant decreased risk of re-operation with reamed nails for closed fractures (relative risk reduction 35%). Results for the first 35 patients enrolled suggested reamed nails increased the risk of reoperation in closed fractures by 165%. Only after 543 patients with closed fractures were enrolled did the results reflect the final advantage for reamed nails in this subgroup. Similarly, the trend towards an increased risk of re-operation for open fractures (23%) was not seen until 62 patients with open fractures were enrolled. Conclusions Our findings highlight the risk of conducting a trial with insufficient sample size and power. Such studies are not only at risk of missing true effects, but also of giving misleading results. Level of Evidence N/A PMID:23525086
Public Opinion Polls, Chicken Soup and Sample Size
ERIC Educational Resources Information Center
Nguyen, Phung
2005-01-01
Cooking and tasting chicken soup in three different pots of very different size serves to demonstrate that it is the absolute sample size that matters the most in determining the accuracy of the findings of the poll, not the relative sample size, i.e. the size of the sample in relation to its population.
Effect size estimates: current use, calculations, and interpretation.
Fritz, Catherine O; Morris, Peter E; Richler, Jennifer J
2012-02-01
The Publication Manual of the American Psychological Association (American Psychological Association, 2001, American Psychological Association, 2010) calls for the reporting of effect sizes and their confidence intervals. Estimates of effect size are useful for determining the practical or theoretical importance of an effect, the relative contributions of factors, and the power of an analysis. We surveyed articles published in 2009 and 2010 in the Journal of Experimental Psychology: General, noting the statistical analyses reported and the associated reporting of effect size estimates. Effect sizes were reported for fewer than half of the analyses; no article reported a confidence interval for an effect size. The most often reported analysis was analysis of variance, and almost half of these reports were not accompanied by effect sizes. Partial η2 was the most commonly reported effect size estimate for analysis of variance. For t tests, 2/3 of the articles did not report an associated effect size estimate; Cohen's d was the most often reported. We provide a straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis.
Effect size estimates: current use, calculations, and interpretation.
Fritz, Catherine O; Morris, Peter E; Richler, Jennifer J
2012-02-01
The Publication Manual of the American Psychological Association (American Psychological Association, 2001, American Psychological Association, 2010) calls for the reporting of effect sizes and their confidence intervals. Estimates of effect size are useful for determining the practical or theoretical importance of an effect, the relative contributions of factors, and the power of an analysis. We surveyed articles published in 2009 and 2010 in the Journal of Experimental Psychology: General, noting the statistical analyses reported and the associated reporting of effect size estimates. Effect sizes were reported for fewer than half of the analyses; no article reported a confidence interval for an effect size. The most often reported analysis was analysis of variance, and almost half of these reports were not accompanied by effect sizes. Partial η2 was the most commonly reported effect size estimate for analysis of variance. For t tests, 2/3 of the articles did not report an associated effect size estimate; Cohen's d was the most often reported. We provide a straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis. PMID:21823805
An integrated approach for multi-level sample size determination
Lu, M.S.; Teichmann, T.; Sanborn, J.B.
1997-12-31
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.
7 CFR 52.3757 - Standard sample unit size.
Code of Federal Regulations, 2014 CFR
2014-01-01
... Ripe Olives 1 Product Description, Types, Styles, and Grades § 52.3757 Standard sample unit size... following standard sample unit size for the applicable style: (a) Whole and pitted—50 olives. (b)...
7 CFR 52.3757 - Standard sample unit size.
Code of Federal Regulations, 2013 CFR
2013-01-01
... Ripe Olives 1 Product Description, Types, Styles, and Grades § 52.3757 Standard sample unit size... following standard sample unit size for the applicable style: (a) Whole and pitted—50 olives. (b)...
[Unconditioned logistic regression and sample size: a bibliographic review].
Ortega Calvo, Manuel; Cayuela Domínguez, Aurelio
2002-01-01
Unconditioned logistic regression is a highly useful risk prediction method in epidemiology. This article reviews the different solutions provided by different authors concerning the interface between the calculation of the sample size and the use of logistics regression. Based on the knowledge of the information initially provided, a review is made of the customized regression and predictive constriction phenomenon, the design of an ordinal exposition with a binary output, the event of interest per variable concept, the indicator variables, the classic Freeman equation, etc. Some skeptical ideas regarding this subject are also included. PMID:12025266
Simultaneous calculation of aircraft design loads and structural member sizes
NASA Technical Reports Server (NTRS)
Giles, G. L.; Mccullers, L. A.
1975-01-01
A design process which accounts for the interaction between aerodynamic loads and changes in member sizes during sizing of aircraft structures is described. A simultaneous iteration procedure is used wherein both design loads and member sizes are updated during each cycle yielding converged, compatible loads and member sizes. A description is also given of a system of programs which incorporates this process using lifting surface theory to calculate aerodynamic pressure distributions, using a finite-element method for structural analysis, and using a fully stressed design technique to size structural members. This system is tailored to perform the entire process with computational efficiency in a single computer run so that it can be used effectively during preliminary design. Selected results, considering maneuver, taxi, and fatigue design conditions, are presented to illustrate convergence characteristics of this iterative procedure.
The Relationship between Sample Sizes and Effect Sizes in Systematic Reviews in Education
ERIC Educational Resources Information Center
Slavin, Robert; Smith, Dewi
2009-01-01
Research in fields other than education has found that studies with small sample sizes tend to have larger effect sizes than those with large samples. This article examines the relationship between sample size and effect size in education. It analyzes data from 185 studies of elementary and secondary mathematics programs that met the standards of…
Defect density: a review on the calculation of size program
NASA Astrophysics Data System (ADS)
Hasim, Nurdatillah; Abd Rahman, Aedah
2011-12-01
Defect density is a measurement conducted in one of Malaysia's ICT leading company. This paper will be discussing on issues of defect density measurement. Regarding defects counted, in order to calculate defect density, we also need to consider the total size of product that is the system size. Generally, defect density is a measure of the number of total defect found divided by the size of the system measured. Therefore, the system size is measured by lines of code. Selected projects in the company have been identified and GeroneSoft Code Counter Pro V1.32 is used as tool to count the lines of code. To this end, the paper presents method used. Analyzed defect density data are represented using control chart because shows the capability of the process so that the achievable goal can be set.
40 CFR 89.418 - Raw emission sampling calculations.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Raw emission sampling calculations. 89.418 Section 89.418 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... Test Procedures § 89.418 Raw emission sampling calculations. (a) The final test results shall...
Optimal flexible sample size design with robust power.
Zhang, Lanju; Cui, Lu; Yang, Bo
2016-08-30
It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26999385
On Sample Sizes for Non-Matched-Pair IR Experiments.
ERIC Educational Resources Information Center
Robertson, S. E.
1990-01-01
Discusses the problem of determining an adequate sample size for an information retrieval experiment comparing two systems on separate samples of requests. The application of statistical methods to information retrieval experiments is discussed, the Mann-Whitney U Test is used for determining minimum sample sizes, and variables and distributions…
Are Sample Sizes Clear and Justified in RCTs Published in Dental Journals?
Koletsi, Despina; Fleming, Padhraig S.; Seehra, Jadbinder; Bagos, Pantelis G.; Pandis, Nikolaos
2014-01-01
Sample size calculations are advocated by the CONSORT group to justify sample sizes in randomized controlled trials (RCTs). The aim of this study was primarily to evaluate the reporting of sample size calculations, to establish the accuracy of these calculations in dental RCTs and to explore potential predictors associated with adequate reporting. Electronic searching was undertaken in eight leading specific and general dental journals. Replication of sample size calculations was undertaken where possible. Assumed variances or odds for control and intervention groups were also compared against those observed. The relationship between parameters including journal type, number of authors, trial design, involvement of methodologist, single-/multi-center study and region and year of publication, and the accuracy of sample size reporting was assessed using univariable and multivariable logistic regression. Of 413 RCTs identified, sufficient information to allow replication of sample size calculations was provided in only 121 studies (29.3%). Recalculations demonstrated an overall median overestimation of sample size of 15.2% after provisions for losses to follow-up. There was evidence that journal, methodologist involvement (OR = 1.97, CI: 1.10, 3.53), multi-center settings (OR = 1.86, CI: 1.01, 3.43) and time since publication (OR = 1.24, CI: 1.12, 1.38) were significant predictors of adequate description of sample size assumptions. Among journals JCP had the highest odds of adequately reporting sufficient data to permit sample size recalculation, followed by AJODO and JDR, with 61% (OR = 0.39, CI: 0.19, 0.80) and 66% (OR = 0.34, CI: 0.15, 0.75) lower odds, respectively. Both assumed variances and odds were found to underestimate the observed values. Presentation of sample size calculations in the dental literature is suboptimal; incorrect assumptions may have a bearing on the power of RCTs. PMID:24465806
7 CFR 52.803 - Sample unit size.
Code of Federal Regulations, 2010 CFR
2010-01-01
... following sample unit sizes for the applicable factor: (a) Pits, character, and harmless extraneous material—20 ounces of drained cherries. (b) Size, color, and defects (other than harmless extraneous...
7 CFR 52.775 - Sample unit size.
Code of Federal Regulations, 2010 CFR
2010-01-01
... unit size. Compliance with requirements for the size and the various quality factors is based on the... extraneous material—The total contents of each container in the sample. Factors of Quality...
A computer program for sample size computations for banding studies
Wilson, K.R.; Nichols, J.D.; Hines, J.E.
1989-01-01
Sample sizes necessary for estimating survival rates of banded birds, adults and young, are derived based on specified levels of precision. The banding study can be new or ongoing. The desired coefficient of variation (CV) for annual survival estimates, the CV for mean annual survival estimates, and the length of the study must be specified to compute sample sizes. A computer program is available for computation of the sample sizes, and a description of the input and output is provided.
A review of software for sample size determination.
Dattalo, Patrick
2009-09-01
The size of a sample is an important element in determining the statistical precision with which population values can be estimated. This article identifies and describes free and commercial programs for sample size determination. Programs are categorized as follows: (a) multiple procedure for sample size determination; (b) single procedure for sample size determination; and (c) Web-based. Programs are described in terms of (a) cost; (b) ease of use, including interface, operating system and hardware requirements, and availability of documentation and technical support; (c) file management, including input and output formats; and (d) analytical and graphical capabilities. PMID:19696082
IBAR: Interacting boson model calculations for large system sizes
NASA Astrophysics Data System (ADS)
Casperson, R. J.
2012-04-01
Scaling the system size of the interacting boson model-1 (IBM-1) into the realm of hundreds of bosons has many interesting applications in the field of nuclear structure, most notably quantum phase transitions in nuclei. We introduce IBAR, a new software package for calculating the eigenvalues and eigenvectors of the IBM-1 Hamiltonian, for large numbers of bosons. Energies and wavefunctions of the nuclear states, as well as transition strengths between them, are calculated using these values. Numerical errors in the recursive calculation of reduced matrix elements of the d-boson creation operator are reduced by using an arbitrary precision mathematical library. This software has been tested for up to 1000 bosons using comparisons to analytic expressions. Comparisons have also been made to the code PHINT for smaller system sizes. Catalogue identifier: AELI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 28 734 No. of bytes in distributed program, including test data, etc.: 4 104 467 Distribution format: tar.gz Programming language: C++ Computer: Any computer system with a C++ compiler Operating system: Tested under Linux RAM: 150 MB for 1000 boson calculations with angular momenta of up to L=4 Classification: 17.18, 17.20 External routines: ARPACK (http://www.caam.rice.edu/software/ARPACK/) Nature of problem: Construction and diagonalization of large Hamiltonian matrices, using reduced matrix elements of the d-boson creation operator. Solution method: Reduced matrix elements of the d-boson creation operator have been stored in data files at machine precision, after being recursively calculated with higher than machine precision. The Hamiltonian matrix is calculated and diagonalized, and the requested transition strengths are calculated
Mesh size and code option effects of strength calculations
Kaul, Ann M
2010-12-10
Modern Lagrangian hydrodynamics codes include numerical methods which allow calculations to proceed past the point obtainable by a purely Lagrangian scheme. These options can be employed as the user deems necessary to 'complete' a calculation. While one could argue that any calculation is better than none, to truly understand the calculated results and their relationship to physical reality, the user needs to understand how their runtime choices affect the calculated results. One step toward this goal is to understand the effect of each runtime choice on particular pieces of the code physics. This paper will present simulation results for some experiments typically used for strength model validation. Topics to be covered include effect of mesh size, use of various ALE schemes for mesh detangling, and use of anti-hour-glassing schemes. Experiments to be modeled include the lower strain rate ({approx} 10{sup 4} s{sup -1}) gas gun driven Taylor impact experiments and the higher strain rate ({approx} 10{sup 5}-10{sup 6} s{sup -1}) HE products driven perturbed plate experiments. The necessary mesh resolution and the effect of the code runtime options are highly dependent on the amount of localization of strain and stress in each experiment. In turn, this localization is dependent on the geometry of the experimental setup and the drive conditions.
40 CFR 80.127 - Sample size guidelines.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) REGULATION OF FUELS AND FUEL ADDITIVES Attest Engagements § 80.127 Sample size guidelines. In performing the attest engagement, the auditor shall sample relevant populations to which agreed-upon procedures will...
7 CFR 52.775 - Sample unit size.
Code of Federal Regulations, 2011 CFR
2011-01-01
... United States Standards for Grades of Canned Red Tart Pitted Cherries 1 Sample Unit Size § 52.775 Sample... drained cherries. (b) Defects (other than harmless extraneous material)—100 cherries. (c)...
Dose Rate Calculations for Rotary Mode Core Sampling Exhauster
FOUST, D.J.
2000-10-26
This document provides the calculated estimated dose rates for three external locations on the Rotary Mode Core Sampling (RMCS) exhauster HEPA filter housing, per the request of Characterization Field Engineering.
40 CFR 600.208-77 - Sample calculation.
Code of Federal Regulations, 2010 CFR
2010-07-01
... ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Fuel Economy Regulations for 1977 and Later Model Year Automobiles-Procedures for Calculating Fuel Economy Values § 600.208-77 Sample...
NASA Astrophysics Data System (ADS)
Campolina, Daniel de A. M.; Lima, Claubia P. B.; Veloso, Maria Auxiliadora F.
2014-06-01
For all the physical components that comprise a nuclear system there is an uncertainty. Assessing the impact of uncertainties in the simulation of fissionable material systems is essential for a best estimate calculation that has been replacing the conservative model calculations as the computational power increases. The propagation of uncertainty in a simulation using a Monte Carlo code by sampling the input parameters is recent because of the huge computational effort required. In this work a sample space of MCNPX calculations was used to propagate the uncertainty. The sample size was optimized using the Wilks formula for a 95th percentile and a two-sided statistical tolerance interval of 95%. Uncertainties in input parameters of the reactor considered included geometry dimensions and densities. It was showed the capacity of the sampling-based method for burnup when the calculations sample size is optimized and many parameter uncertainties are investigated together, in the same input.
Sample Size and Bentler and Bonett's Nonnormed Fit Index.
ERIC Educational Resources Information Center
Bollen, Kenneth A.
1986-01-01
This note shows that, contrary to what has been claimed, Bentler and Bonnett's nonnormed fit index is dependent on sample size. Specifically for a constant value of a fitting function, the nonnormed index is inversely related to sample size. A simple alternative fit measure is proposed that removes this dependency. (Author/LMO)
Preliminary Proactive Sample Size Determination for Confirmatory Factor Analysis Models
ERIC Educational Resources Information Center
Koran, Jennifer
2016-01-01
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Sample size reassessment for a two-stage design controlling the false discovery rate.
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.
ERIC Educational Resources Information Center
Sahin, Alper; Weiss, David J.
2015-01-01
This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500,…
Power Analysis and Sample Size Determination in Metabolic Phenotyping.
Blaise, Benjamin J; Correia, Gonçalo; Tin, Adrienne; Young, J Hunter; Vergnaud, Anne-Claire; Lewis, Matthew; Pearce, Jake T M; Elliott, Paul; Nicholson, Jeremy K; Holmes, Elaine; Ebbels, Timothy M D
2016-05-17
Estimation of statistical power and sample size is a key aspect of experimental design. However, in metabolic phenotyping, there is currently no accepted approach for these tasks, in large part due to the unknown nature of the expected effect. In such hypothesis free science, neither the number or class of important analytes nor the effect size are known a priori. We introduce a new approach, based on multivariate simulation, which deals effectively with the highly correlated structure and high-dimensionality of metabolic phenotyping data. First, a large data set is simulated based on the characteristics of a pilot study investigating a given biomedical issue. An effect of a given size, corresponding either to a discrete (classification) or continuous (regression) outcome is then added. Different sample sizes are modeled by randomly selecting data sets of various sizes from the simulated data. We investigate different methods for effect detection, including univariate and multivariate techniques. Our framework allows us to investigate the complex relationship between sample size, power, and effect size for real multivariate data sets. For instance, we demonstrate for an example pilot data set that certain features achieve a power of 0.8 for a sample size of 20 samples or that a cross-validated predictivity QY(2) of 0.8 is reached with an effect size of 0.2 and 200 samples. We exemplify the approach for both nuclear magnetic resonance and liquid chromatography-mass spectrometry data from humans and the model organism C. elegans.
Hickson, Kevin J; O'Keefe, Graeme J
2014-09-01
The scalable XCAT voxelised phantom was used with the GATE Monte Carlo toolkit to investigate the effect of voxel size on dosimetry estimates of internally distributed radionuclide calculated using direct Monte Carlo simulation. A uniformly distributed Fluorine-18 source was simulated in the Kidneys of the XCAT phantom with the organ self dose (kidney ← kidney) and organ cross dose (liver ← kidney) being calculated for a number of organ and voxel sizes. Patient specific dose factors (DF) from a clinically acquired FDG PET/CT study have also been calculated for kidney self dose and liver ← kidney cross dose. Using the XCAT phantom it was found that significantly small voxel sizes are required to achieve accurate calculation of organ self dose. It has also been used to show that a voxel size of 2 mm or less is suitable for accurate calculations of organ cross dose. To compensate for insufficient voxel sampling a correction factor is proposed. This correction factor is applied to the patient specific dose factors calculated with the native voxel size of the PET/CT study.
SNS Sample Activation Calculator Flux Recommendations and Validation
McClanahan, Tucker C.; Gallmeier, Franz X.; Iverson, Erik B.; Lu, Wei
2015-02-01
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) uses the Sample Activation Calculator (SAC) to calculate the activation of a sample after the sample has been exposed to the neutron beam in one of the SNS beamlines. The SAC webpage takes user inputs (choice of beamline, the mass, composition and area of the sample, irradiation time, decay time, etc.) and calculates the activation for the sample. In recent years, the SAC has been incorporated into the user proposal and sample handling process, and instrument teams and users have noticed discrepancies in the predicted activation of their samples. The Neutronics Analysis Team validated SAC by performing measurements on select beamlines and confirmed the discrepancies seen by the instrument teams and users. The conclusions were that the discrepancies were a result of a combination of faulty neutron flux spectra for the instruments, improper inputs supplied by SAC (1.12), and a mishandling of cross section data in the Sample Activation Program for Easy Use (SAPEU) (1.1.2). This report focuses on the conclusion that the SAPEU (1.1.2) beamline neutron flux spectra have errors and are a significant contributor to the activation discrepancies. The results of the analysis of the SAPEU (1.1.2) flux spectra for all beamlines will be discussed in detail. The recommendations for the implementation of improved neutron flux spectra in SAPEU (1.1.3) are also discussed.
How to calculate normal curvatures of sampled geological surfaces
NASA Astrophysics Data System (ADS)
Bergbauer, Stephan; Pollard, David D.
2003-02-01
Curvature has been used both to describe geological surfaces and to predict the distribution of deformation in folded or domed strata. Several methods have been proposed in the geoscience literature to approximate the curvature of surfaces; however we advocate a technique for the exact calculation of normal curvature for single-valued gridded surfaces. This technique, based on the First and Second Fundamental Forms of differential geometry, allows for the analytical calculation of the magnitudes and directions of principal curvatures, as well as Gaussian and mean curvature. This approach is an improvement over previous methods to calculate surface curvatures because it avoids common mathematical approximations, which introduce significant errors when calculated over sloped horizons. Moreover, the technique is easily implemented numerically as it calculates curvatures directly from gridded surface data (e.g. seismic or GPS data) without prior surface triangulation. In geological curvature analyses, problems arise because of the sampled nature of geological horizons, which introduces a dependence of calculated curvatures on the sample grid. This dependence makes curvature analysis without prior data manipulation problematic. To ensure a meaningful curvature analysis, surface data should be filtered to extract only those surface wavelengths that scale with the feature under investigation. A curvature analysis of the top-Pennsylvanian horizon at Goose Egg dome, Wyoming shows that sampled surfaces can be smoothed using a moving average low-pass filter to extract curvature information associated with the true morphology of the structure.
Sample Size Requirements for Comparing Two Alpha Coefficients.
ERIC Educational Resources Information Center
Bonnett, Douglas G.
2003-01-01
Derived general formulas to determine the sample size requirements for hypothesis testing with desired power and interval estimation with desired precision. Illustrated the approach with the example of a screening test for adolescent attention deficit disorder. (SLD)
Effects of Mesh Size on Sieved Samples of Corophium volutator
NASA Astrophysics Data System (ADS)
Crewe, Tara L.; Hamilton, Diana J.; Diamond, Antony W.
2001-08-01
Corophium volutator (Pallas), gammaridean amphipods found on intertidal mudflats, are frequently collected in mud samples sieved on mesh screens. However, mesh sizes used vary greatly among studies, raising the possibility that sampling methods bias results. The effect of using different mesh sizes on the resulting size-frequency distributions of Corophium was tested by collecting Corophium from mud samples with 0·5 and 0·25 mm sieves. More than 90% of Corophium less than 2 mm long passed through the larger sieve. A significantly smaller, but still substantial, proportion of 2-2·9 mm Corophium (30%) was also lost. Larger size classes were unaffected by mesh size. Mesh size significantly changed the observed size-frequency distribution of Corophium, and effects varied with sampling date. It is concluded that a 0·5 mm sieve is suitable for studies concentrating on adults, but to accurately estimate Corophium density and size-frequency distributions, a 0·25 mm sieve must be used.
The Precision Efficacy Analysis for Regression Sample Size Method.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.
The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…
Sample Size Determination: A Comparison of Attribute, Continuous Variable, and Cell Size Methods.
ERIC Educational Resources Information Center
Clark, Philip M.
1984-01-01
Describes three methods of sample size determination, each having its use in investigation of social science problems: Attribute method; Continuous Variable method; Galtung's Cell Size method. Statistical generalization, benefits of cell size method (ease of use, trivariate analysis and trichotyomized variables), and choice of method are…
Optimal and maximin sample sizes for multicentre cost-effectiveness trials.
Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F
2015-10-01
This paper deals with the optimal sample sizes for a multicentre trial in which the cost-effectiveness of two treatments in terms of net monetary benefit is studied. A bivariate random-effects model, with the treatment-by-centre interaction effect being random and the main effect of centres fixed or random, is assumed to describe both costs and effects. The optimal sample sizes concern the number of centres and the number of individuals per centre in each of the treatment conditions. These numbers maximize the efficiency or power for given research costs or minimize the research costs at a desired level of efficiency or power. Information on model parameters and sampling costs are required to calculate these optimal sample sizes. In case of limited information on relevant model parameters, sample size formulas are derived for so-called maximin sample sizes which guarantee a power level at the lowest study costs. Four different maximin sample sizes are derived based on the signs of the lower bounds of two model parameters, with one case being worst compared to others. We numerically evaluate the efficiency of the worst case instead of using others. Finally, an expression is derived for calculating optimal and maximin sample sizes that yield sufficient power to test the cost-effectiveness of two treatments. PMID:25656551
Hellman-Feynman operator sampling in diffusion Monte Carlo calculations.
Gaudoin, R; Pitarke, J M
2007-09-21
Diffusion Monte Carlo (DMC) calculations typically yield highly accurate results in solid-state and quantum-chemical calculations. However, operators that do not commute with the Hamiltonian are at best sampled correctly up to second order in the error of the underlying trial wave function once simple corrections have been applied. This error is of the same order as that for the energy in variational calculations. Operators that suffer from these problems include potential energies and the density. This Letter presents a new method, based on the Hellman-Feynman theorem, for the correct DMC sampling of all operators diagonal in real space. Our method is easy to implement in any standard DMC code.
The Effect of Sample Size on Latent Growth Models.
ERIC Educational Resources Information Center
Hamilton, Jennifer; Gagne, Phillip E.; Hancock, Gregory R.
A Monte Carlo simulation approach was taken to investigate the effect of sample size on a variety of latent growth models. A fully balanced experimental design was implemented, with samples drawn from multivariate normal populations specified to represent 12 unique growth models. The models varied factorially by crossing number of time points,…
CSnrc: Correlated sampling Monte Carlo calculations using EGSnrc
Buckley, Lesley A.; Kawrakow, I.; Rogers, D.W.O.
2004-12-01
CSnrc, a new user-code for the EGSnrc Monte Carlo system is described. This user-code improves the efficiency when calculating ratios of doses from similar geometries. It uses a correlated sampling variance reduction technique. CSnrc is developed from an existing EGSnrc user-code CAVRZnrc and improves upon the correlated sampling algorithm used in an earlier version of the code written for the EGS4 Monte Carlo system. Improvements over the EGS4 version of the algorithm avoid repetition of sections of particle tracks. The new code includes a rectangular phantom geometry not available in other EGSnrc cylindrical codes. Comparison to CAVRZnrc shows gains in efficiency of up to a factor of 64 for a variety of test geometries when computing the ratio of doses to the cavity for two geometries. CSnrc is well suited to in-phantom calculations and is used to calculate the central electrode correction factor P{sub cel} in high-energy photon and electron beams. Current dosimetry protocols base the value of P{sub cel} on earlier Monte Carlo calculations. The current CSnrc calculations achieve 0.02% statistical uncertainties on P{sub cel}, much lower than those previously published. The current values of P{sub cel} compare well with the values used in dosimetry protocols for photon beams. For electrons beams, CSnrc calculations are reported at the reference depth used in recent protocols and show up to a 0.2% correction for a graphite electrode, a correction currently ignored by dosimetry protocols. The calculations show that for a 1 mm diameter aluminum central electrode, the correction factor differs somewhat from the values used in both the IAEA TRS-398 code of practice and the AAPM's TG-51 protocol.
Two-stage chain sampling inspection plans with different sample sizes in the two stages
NASA Technical Reports Server (NTRS)
Stephens, K. S.; Dodge, H. F.
1976-01-01
A further generalization of the family of 'two-stage' chain sampling inspection plans is developed - viz, the use of different sample sizes in the two stages. Evaluation of the operating characteristics is accomplished by the Markov chain approach of the earlier work, modified to account for the different sample sizes. Markov chains for a number of plans are illustrated and several algebraic solutions are developed. Since these plans involve a variable amount of sampling, an evaluation of the average sampling number (ASN) is developed. A number of OC curves and ASN curves are presented. Some comparisons with plans having only one sample size are presented and indicate that improved discrimination is achieved by the two-sample-size plans.
Sample Size Determination for One- and Two-Sample Trimmed Mean Tests
ERIC Educational Resources Information Center
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…
Surprise Calculator: Estimating relative entropy and Surprise between samples
NASA Astrophysics Data System (ADS)
Seehars, Sebastian
2016-05-01
The Surprise is a measure for consistency between posterior distributions and operates in parameter space. It can be used to analyze either the compatibility of separately analyzed posteriors from two datasets, or the posteriors from a Bayesian update. The Surprise Calculator estimates relative entropy and Surprise between two samples, assuming they are Gaussian. The software requires the R package CompQuadForm to estimate the significance of the Surprise, and rpy2 to interface R with Python.
Sample size in psychological research over the past 30 years.
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.
Molenberghs, Geert; Kenward, Michael G; Aerts, Marc; Verbeke, Geert; Tsiatis, Anastasios A; Davidian, Marie; Rizopoulos, Dimitris
2014-02-01
The vast majority of settings for which frequentist statistical properties are derived assume a fixed, a priori known sample size. Familiar properties then follow, such as, for example, the consistency, asymptotic normality, and efficiency of the sample average for the mean parameter, under a wide range of conditions. We are concerned here with the alternative situation in which the sample size is itself a random variable which may depend on the data being collected. Further, the rule governing this may be deterministic or probabilistic. There are many important practical examples of such settings, including missing data, sequential trials, and informative cluster size. It is well known that special issues can arise when evaluating the properties of statistical procedures under such sampling schemes, and much has been written about specific areas (Grambsch P. Sequential sampling based on the observed Fisher information to guarantee the accuracy of the maximum likelihood estimator. Ann Stat 1983; 11: 68-77; Barndorff-Nielsen O and Cox DR. The effect of sampling rules on likelihood statistics. Int Stat Rev 1984; 52: 309-326). Our aim is to place these various related examples into a single framework derived from the joint modeling of the outcomes and sampling process and so derive generic results that in turn provide insight, and in some cases practical consequences, for different settings. It is shown that, even in the simplest case of estimating a mean, some of the results appear counterintuitive. In many examples, the sample average may exhibit small sample bias and, even when it is unbiased, may not be optimal. Indeed, there may be no minimum variance unbiased estimator for the mean. Such results follow directly from key attributes such as non-ancillarity of the sample size and incompleteness of the minimal sufficient statistic of the sample size and sample sum. Although our results have direct and obvious implications for estimation following group sequential
Yang, Yaning; Remmers, Elaine F; Ogunwole, Chukwuma B; Kastner, Daniel L; Gregersen, Peter K; Li, Wentian
2011-02-01
Affected relatives are essential for pedigree linkage analysis, however, they cause a violation of the independent sample assumption in case-control association studies. To avoid the correlation between samples, a common practice is to take only one affected sample per pedigree in association analysis. Although several methods exist in handling correlated samples, they are still not widely used in part because these are not easily implemented, or because they are not widely known. We advocate the effective sample size method as a simple and accessible approach for case-control association analysis with correlated samples. This method modifies the chi-square test statistic, p-value, and 95% confidence interval of the odds-ratio by replacing the apparent number of allele or genotype counts with the effective ones in the standard formula, without the need for specialized computer programs. We present a simple formula for calculating effective sample size for many types of relative pairs and relative sets. For allele frequency estimation, the effective sample size method captures the variance inflation exactly. For genotype frequency, simulations showed that effective sample size provides a satisfactory approximation. A gene which is previously identified as a type 1 diabetes susceptibility locus, the interferon-induced helicase gene (IFIH1), is shown to be significantly associated with rheumatoid arthritis when the effective sample size method is applied. This significant association is not established if only one affected sib per pedigree were used in the association analysis. Relationship between the effective sample size method and other methods - the generalized estimation equation, variance of eigenvalues for correlation matrices, and genomic controls - are discussed.
Yang, Yaning; Remmers, Elaine F.; Ogunwole, Chukwuma B.; Kastner, Daniel L.; Gregersen, Peter K.; Li, Wentian
2011-01-01
Summary Affected relatives are essential for pedigree linkage analysis, however, they cause a violation of the independent sample assumption in case-control association studies. To avoid the correlation between samples, a common practice is to take only one affected sample per pedigree in association analysis. Although several methods exist in handling correlated samples, they are still not widely used in part because these are not easily implemented, or because they are not widely known. We advocate the effective sample size method as a simple and accessible approach for case-control association analysis with correlated samples. This method modifies the chi-square test statistic, p-value, and 95% confidence interval of the odds-ratio by replacing the apparent number of allele or genotype counts with the effective ones in the standard formula, without the need for specialized computer programs. We present a simple formula for calculating effective sample size for many types of relative pairs and relative sets. For allele frequency estimation, the effective sample size method captures the variance inflation exactly. For genotype frequency, simulations showed that effective sample size provides a satisfactory approximation. A gene which is previously identified as a type 1 diabetes susceptibility locus, the interferon-induced helicase gene (IFIH1), is shown to be significantly associated with rheumatoid arthritis when the effective sample size method is applied. This significant association is not established if only one affected sib per pedigree were used in the association analysis. Relationship between the effective sample size method and other methods – the generalized estimation equation, variance of eigenvalues for correlation matrices, and genomic controls – are discussed. PMID:21333602
Yang, Yaning; Remmers, Elaine F; Ogunwole, Chukwuma B; Kastner, Daniel L; Gregersen, Peter K; Li, Wentian
2011-02-01
Affected relatives are essential for pedigree linkage analysis, however, they cause a violation of the independent sample assumption in case-control association studies. To avoid the correlation between samples, a common practice is to take only one affected sample per pedigree in association analysis. Although several methods exist in handling correlated samples, they are still not widely used in part because these are not easily implemented, or because they are not widely known. We advocate the effective sample size method as a simple and accessible approach for case-control association analysis with correlated samples. This method modifies the chi-square test statistic, p-value, and 95% confidence interval of the odds-ratio by replacing the apparent number of allele or genotype counts with the effective ones in the standard formula, without the need for specialized computer programs. We present a simple formula for calculating effective sample size for many types of relative pairs and relative sets. For allele frequency estimation, the effective sample size method captures the variance inflation exactly. For genotype frequency, simulations showed that effective sample size provides a satisfactory approximation. A gene which is previously identified as a type 1 diabetes susceptibility locus, the interferon-induced helicase gene (IFIH1), is shown to be significantly associated with rheumatoid arthritis when the effective sample size method is applied. This significant association is not established if only one affected sib per pedigree were used in the association analysis. Relationship between the effective sample size method and other methods - the generalized estimation equation, variance of eigenvalues for correlation matrices, and genomic controls - are discussed. PMID:21333602
Fujita, Masahiro; Yajima, Tomonari; Iijima, Kazuaki; Sato, Kiyoshi
2012-05-01
The uncertainty in pesticide residue levels (UPRL) associated with sampling size was estimated using individual acetamiprid and cypermethrin residue data from preharvested apple, broccoli, cabbage, grape, and sweet pepper samples. The relative standard deviation from the mean of each sampling size (n = 2(x), where x = 1-6) of randomly selected samples was defined as the UPRL for each sampling size. The estimated UPRLs, which were calculated on the basis of the regulatory sampling size recommended by the OECD Guidelines on Crop Field Trials (weights from 1 to 5 kg, and commodity unit numbers from 12 to 24), ranged from 2.1% for cypermethrin in sweet peppers to 14.6% for cypermethrin in cabbage samples. The percentages of commodity exceeding the maximum residue limits (MRLs) specified by the Japanese Food Sanitation Law may be predicted from the equation derived from this study, which was based on samples of various size ranges with mean residue levels below the MRL. The estimated UPRLs have confirmed that sufficient sampling weight and numbers are required for analysis and/or re-examination of subsamples to provide accurate values of pesticide residue levels for the enforcement of MRLs. The equation derived from the present study would aid the estimation of more accurate residue levels even from small sampling sizes. PMID:22475588
Calculating Confidence Intervals for Effect Sizes Using Noncentral Distributions.
ERIC Educational Resources Information Center
Norris, Deborah
This paper provides a brief review of the concepts of confidence intervals, effect sizes, and central and noncentral distributions. The use of confidence intervals around effect sizes is discussed. A demonstration of the Exploratory Software for Confidence Intervals (G. Cuming and S. Finch, 2001; ESCI) is given to illustrate effect size confidence…
Approximate sample sizes required to estimate length distributions
Miranda, L.E.
2007-01-01
The sample sizes required to estimate fish length were determined by bootstrapping from reference length distributions. Depending on population characteristics and species-specific maximum lengths, 1-cm length-frequency histograms required 375-1,200 fish to estimate within 10% with 80% confidence, 2.5-cm histograms required 150-425 fish, proportional stock density required 75-140 fish, and mean length required 75-160 fish. In general, smaller species, smaller populations, populations with higher mortality, and simpler length statistics required fewer samples. Indices that require low sample sizes may be suitable for monitoring population status, and when large changes in length are evident, additional sampling effort may be allocated to more precisely define length status with more informative estimators. ?? Copyright by the American Fisheries Society 2007.
An Investigation of Sample Size Splitting on ATFIND and DIMTEST
ERIC Educational Resources Information Center
Socha, Alan; DeMars, Christine E.
2013-01-01
Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…
Sample Size Bias in Judgments of Perceptual Averages
ERIC Educational Resources Information Center
Price, Paul C.; Kimura, Nicole M.; Smith, Andrew R.; Marshall, Lindsay D.
2014-01-01
Previous research has shown that people exhibit a sample size bias when judging the average of a set of stimuli on a single dimension. The more stimuli there are in the set, the greater people judge the average to be. This effect has been demonstrated reliably for judgments of the average likelihood that groups of people will experience negative,…
Sample Size Tables, "t" Test, and a Prevalent Psychometric Distribution.
ERIC Educational Resources Information Center
Sawilowsky, Shlomo S.; Hillman, Stephen B.
Psychology studies often have low statistical power. Sample size tables, as given by J. Cohen (1988), may be used to increase power, but they are based on Monte Carlo studies of relatively "tame" mathematical distributions, as compared to psychology data sets. In this study, Monte Carlo methods were used to investigate Type I and Type II error…
Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests
Duncanson, L.; Rourke, O.; Dubayah, R.
2015-01-01
Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height and crown radius. We use LiDAR remote sensing to isolate between 10,000 to more than 1,000,000 tree height and crown radius measurements per site in six U.S. forests. We find that fitted allometric parameters are highly sensitive to sample size, producing systematic overestimates of height. We extend our analysis to biomass through the application of empirical relationships from the literature, and show that given the small sample sizes used in common allometric equations for biomass, the average site-level biomass bias is ~+70% with a standard deviation of 71%, ranging from −4% to +193%. These findings underscore the importance of increasing the sample sizes used for allometric equation generation. PMID:26598233
Evaluation of morphological representative sample sizes for nanolayered polymer blends.
Bironeau, A; Dirrenberger, J; Sollogoub, C; Miquelard-Garnier, G; Roland, S
2016-10-01
The size of representative microstructural samples obtained from atomic force microscopy is addressed in this paper. The case of an archetypal one-dimensional nanolayered polymer blend is considered. Image analysis is performed on micrographs obtained through atomic force microscopy, yielding statistical data concerning morphological properties of the material. The variability in terms of microstructural morphology is due to the thermomechanical processing route. The statistical data is used in order to estimate sample size representativity, based on an asymptotic relationship relating the inherent point variance of the indicator function of one material phase to the statistical, size-dependent, ensemble variance of the same function. From the study of nanolayered material systems, the statistical approach was found to be an effective mean for discriminating and characterizing multiple scales of heterogeneity.
Zhang, Boshao; Zhi, Degui; Zhang, Kui; Gao, Guimin; Limdi, Nita N.; Liu, Nianjun
2011-01-01
Imputation offers a promising way to infer the missing and/or untyped genotypes in genetic studies. In practice, however, many factors may affect the quality of imputation. In this study, we evaluated the influence of untyped rate, sizes of the study sample and the reference sample, window size, and reference choice (for admixed population), as the factors affecting the quality of imputation. The results show that in order to obtain good imputation quality, it is necessary to have an untyped rate less than 50%, a reference sample size greater than 50, and a window size of greater than 500 SNPs (roughly 1 MB in base pairs). Compared with the whole-region imputation, piecewise imputation with large-enough window sizes provides improved efficacy. For an admixed study sample, if only an external reference panel is used, it should include samples from the ancestral populations that represent the admixed population under investigation. Internal references are strongly recommended. When internal references are limited, however, augmentation by external references should be used carefully. More specifically, augmentation with samples from the major source populations of the admixture can lower the quality of imputation; augmentation with seemingly genetically unrelated cohorts may improve the quality of imputation. PMID:22308193
McCain, J.D.; Dawes, S.S.; Farthing, W.E.
1986-05-01
The report is Attachment No. 2 to the Final Report of ARB Contract A3-092-32 and provides a tutorial on the use of Cascade (Series) Cyclones to obtain size-fractionated particulate samples from industrial flue gases at stationary sources. The instrumentation and procedures described are designed to protect the purity of the collected samples so that post-test chemical analysis may be performed for organic and inorganic compounds, including instrumental analysis for trace elements. The instrumentation described collects bulk quantities for each of six size fractions over the range 10 to 0.4 micrometer diameter. The report describes the operating principles, calibration, and empirical modeling of small cyclone performance. It also discusses the preliminary calculations, operation, sample retrieval, and data analysis associated with the use of cyclones to obtain size-segregated samples and to measure particle-size distributions.
Optimal sample size allocation for Welch's test in one-way heteroscedastic ANOVA.
Shieh, Gwowen; Jan, Show-Li
2015-06-01
The determination of an adequate sample size is a vital aspect in the planning stage of research studies. A prudent strategy should incorporate all of the critical factors and cost considerations into sample size calculations. This study concerns the allocation schemes of group sizes for Welch's test in a one-way heteroscedastic ANOVA. Optimal allocation approaches are presented for minimizing the total cost while maintaining adequate power and for maximizing power performance for a fixed cost. The commonly recommended ratio of sample sizes is proportional to the ratio of the population standard deviations or the ratio of the population standard deviations divided by the square root of the ratio of the unit sampling costs. Detailed numerical investigations have shown that these usual allocation methods generally do not give the optimal solution. The suggested procedures are illustrated using an example of the cost-efficiency evaluation in multidisciplinary pain centers.
Sample size consideration for immunoassay screening cut-point determination.
Zhang, Jianchun; Zhang, Lanju; Yang, Harry
2014-01-01
Past decades have seen a rapid growth of biopharmaceutical products on the market. The administration of such large molecules can generate antidrug antibodies that can induce unwanted immune reactions in the recipients. Assessment of immunogenicity is required by regulatory agencies in clinical and nonclinical development, and this demands a well-validated assay. One of the important performance characteristics during assay validation is the cut point, which serves as a threshold between positive and negative samples. To precisely determine the cut point, a sufficiently large data set is often needed. However, there is no guideline other than some rule-of-thumb recommendations for sample size requirement in immunoassays. In this article, we propose a systematic approach to sample size determination for immunoassays and provide tables that facilitate its applications by scientists.
Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters
Schnack, Hugo G.; Kahn, René S.
2016-01-01
In a recent review, it was suggested that much larger cohorts are needed to prove the diagnostic value of neuroimaging biomarkers in psychiatry. While within a sample, an increase of diagnostic accuracy of schizophrenia (SZ) with number of subjects (N) has been shown, the relationship between N and accuracy is completely different between studies. Using data from a recent meta-analysis of machine learning (ML) in imaging SZ, we found that while low-N studies can reach 90% and higher accuracy, above N/2 = 50 the maximum accuracy achieved steadily drops to below 70% for N/2 > 150. We investigate the role N plays in the wide variability in accuracy results in SZ studies (63–97%). We hypothesize that the underlying cause of the decrease in accuracy with increasing N is sample heterogeneity. While smaller studies more easily include a homogeneous group of subjects (strict inclusion criteria are easily met; subjects live close to study site), larger studies inevitably need to relax the criteria/recruit from large geographic areas. A SZ prediction model based on a heterogeneous group of patients with presumably a heterogeneous pattern of structural or functional brain changes will not be able to capture the whole variety of changes, thus being limited to patterns shared by most patients. In addition to heterogeneity (sample size), we investigate other factors influencing accuracy and introduce a ML effect size. We derive a simple model of how the different factors, such as sample heterogeneity and study setup determine this ML effect size, and explain the variation in prediction accuracies found from the literature, both in cross-validation and independent sample testing. From this, we argue that smaller-N studies may reach high prediction accuracy at the cost of lower generalizability to other samples. Higher-N studies, on the other hand, will have more generalization power, but at the cost of lower accuracy. In conclusion, when comparing results from different
Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters.
Schnack, Hugo G; Kahn, René S
2016-01-01
In a recent review, it was suggested that much larger cohorts are needed to prove the diagnostic value of neuroimaging biomarkers in psychiatry. While within a sample, an increase of diagnostic accuracy of schizophrenia (SZ) with number of subjects (N) has been shown, the relationship between N and accuracy is completely different between studies. Using data from a recent meta-analysis of machine learning (ML) in imaging SZ, we found that while low-N studies can reach 90% and higher accuracy, above N/2 = 50 the maximum accuracy achieved steadily drops to below 70% for N/2 > 150. We investigate the role N plays in the wide variability in accuracy results in SZ studies (63-97%). We hypothesize that the underlying cause of the decrease in accuracy with increasing N is sample heterogeneity. While smaller studies more easily include a homogeneous group of subjects (strict inclusion criteria are easily met; subjects live close to study site), larger studies inevitably need to relax the criteria/recruit from large geographic areas. A SZ prediction model based on a heterogeneous group of patients with presumably a heterogeneous pattern of structural or functional brain changes will not be able to capture the whole variety of changes, thus being limited to patterns shared by most patients. In addition to heterogeneity (sample size), we investigate other factors influencing accuracy and introduce a ML effect size. We derive a simple model of how the different factors, such as sample heterogeneity and study setup determine this ML effect size, and explain the variation in prediction accuracies found from the literature, both in cross-validation and independent sample testing. From this, we argue that smaller-N studies may reach high prediction accuracy at the cost of lower generalizability to other samples. Higher-N studies, on the other hand, will have more generalization power, but at the cost of lower accuracy. In conclusion, when comparing results from different
Effects of sample size on KERNEL home range estimates
Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.
1999-01-01
Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.
Rock sampling. [method for controlling particle size distribution
NASA Technical Reports Server (NTRS)
Blum, P. (Inventor)
1971-01-01
A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.
Chaibub Neto, Elias
2015-01-01
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. PMID:26125965
Chaibub Neto, Elias
2015-01-01
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.
CALCULATING TIME LAGS FROM UNEVENLY SAMPLED LIGHT CURVES
Zoghbi, A.; Reynolds, C.; Cackett, E. M.
2013-11-01
Timing techniques are powerful tools to study dynamical astrophysical phenomena. In the X-ray band, they offer the potential of probing accretion physics down to the event horizon. Recent work has used frequency- and energy-dependent time lags as tools for studying relativistic reverberation around the black holes in several Seyfert galaxies. This was achieved due to the evenly sampled light curves obtained using XMM-Newton. Continuously sampled data are, however, not always available and standard Fourier techniques are not applicable. Here, building on the work of Miller et al., we discuss and use a maximum likelihood method to obtain frequency-dependent lags that takes into account light curve gaps. Instead of calculating the lag directly, the method estimates the most likely lag values at a particular frequency given two observed light curves. We use Monte Carlo simulations to assess the method's applicability and use it to obtain lag-energy spectra from Suzaku data for two objects, NGC 4151 and MCG-5-23-16, that had previously shown signatures of iron K reverberation. The lags obtained are consistent with those calculated using standard methods using XMM-Newton data.
Air sampling filtration media: Collection efficiency for respirable size-selective sampling
Soo, Jhy-Charm; Monaghan, Keenan; Lee, Taekhee; Kashon, Mike; Harper, Martin
2016-01-01
The collection efficiencies of commonly used membrane air sampling filters in the ultrafine particle size range were investigated. Mixed cellulose ester (MCE; 0.45, 0.8, 1.2, and 5 μm pore sizes), polycarbonate (0.4, 0.8, 2, and 5 μm pore sizes), polytetrafluoroethylene (PTFE; 0.45, 1, 2, and 5 μm pore sizes), polyvinyl chloride (PVC; 0.8 and 5 μm pore sizes), and silver membrane (0.45, 0.8, 1.2, and 5 μm pore sizes) filters were exposed to polydisperse sodium chloride (NaCl) particles in the size range of 10–400 nm. Test aerosols were nebulized and introduced into a calm air chamber through a diffusion dryer and aerosol neutralizer. The testing filters (37 mm diameter) were mounted in a conductive polypropylene filter-holder (cassette) within a metal testing tube. The experiments were conducted at flow rates between 1.7 and 11.2 l min−1. The particle size distributions of NaCl challenge aerosol were measured upstream and downstream of the test filters by a scanning mobility particle sizer (SMPS). Three different filters of each type with at least three repetitions for each pore size were tested. In general, the collection efficiency varied with airflow, pore size, and sampling duration. In addition, both collection efficiency and pressure drop increased with decreased pore size and increased sampling flow rate, but they differed among filter types and manufacturer. The present study confirmed that the MCE, PTFE, and PVC filters have a relatively high collection efficiency for challenge particles much smaller than their nominal pore size and are considerably more efficient than polycarbonate and silver membrane filters, especially at larger nominal pore sizes. PMID:26834310
Sample size determination for testing equality in a cluster randomized trial with noncompliance.
Lui, Kung-Jong; Chang, Kuang-Chao
2011-01-01
For administrative convenience or cost efficiency, we may often employ a cluster randomized trial (CRT), in which randomized units are clusters of patients rather than individual patients. Furthermore, because of ethical reasons or patient's decision, it is not uncommon to encounter data in which there are patients not complying with their assigned treatments. Thus, the development of a sample size calculation procedure for a CRT with noncompliance is important and useful in practice. Under the exclusion restriction model, we have developed an asymptotic test procedure using a tanh(-1)(x) transformation for testing equality between two treatments among compliers for a CRT with noncompliance. We have further derived a sample size formula accounting for both noncompliance and the intraclass correlation for a desired power 1 - β at a nominal α level. We have employed Monte Carlo simulation to evaluate the finite-sample performance of the proposed test procedure with respect to type I error and the accuracy of the derived sample size calculation formula with respect to power in a variety of situations. Finally, we use the data taken from a CRT studying vitamin A supplementation to reduce mortality among preschool children to illustrate the use of sample size calculation proposed here. PMID:21191850
Tooth Wear Prevalence and Sample Size Determination : A Pilot Study
Abd. Karim, Nama Bibi Saerah; Ismail, Noorliza Mastura; Naing, Lin; Ismail, Abdul Rashid
2008-01-01
Tooth wear is the non-carious loss of tooth tissue, which results from three processes namely attrition, erosion and abrasion. These can occur in isolation or simultaneously. Very mild tooth wear is a physiological effect of aging. This study aims to estimate the prevalence of tooth wear among 16-year old Malay school children and determine a feasible sample size for further study. Fifty-five subjects were examined clinically, followed by the completion of self-administered questionnaires. Questionnaires consisted of socio-demographic and associated variables for tooth wear obtained from the literature. The Smith and Knight tooth wear index was used to chart tooth wear. Other oral findings were recorded using the WHO criteria. A software programme was used to determine pathological tooth wear. About equal ratio of male to female were involved. It was found that 18.2% of subjects have no tooth wear, 63.6% had very mild tooth wear, 10.9% mild tooth wear, 5.5% moderate tooth wear and 1.8 % severe tooth wear. In conclusion 18.2% of subjects were deemed to have pathological tooth wear (mild, moderate & severe). Exploration with all associated variables gave a sample size ranging from 560 – 1715. The final sample size for further study greatly depends on available time and resources. PMID:22589636
Evaluation of Size Correction Factor for Size-specific Dose Estimates (SSDE) Calculation.
Mizonobe, Kazufusa; Shiraishi, Yuta; Nakano, Satoshi; Fukuda, Chiaki; Asanuma, Osamu; Harada, Kohei; Date, Hiroyuki
2016-09-01
American Association of Physicists in Medicine (AAPM) Report No.204 recommends the size-specific dose estimates (SSDE), wherein SSDE=computed tomography dose index-volume (CTDIvol )×size correction factor (SCF), as an index of the CT dose to consider patient thickness. However, the study on SSDE has not been made yet for area detector CT (ADCT) device such as a 320-row CT scanner. The purpose of this study was to evaluate the SCF values for ADCT by means of a simulation technique to look into the differences in SCF values due to beam width. In the simulation, to construct the geometry of the Aquilion ONE X-ray CT system (120 kV), the dose ratio and the effective energies were measured in the cone angle and fan angle directions, and these were incorporated into the simulation code, Electron Gamma Shower Ver.5 (EGS5). By changing the thickness of a PMMA phantom from 8 cm to 40 cm, CTDIvol and SCF were determined. The SCF values for the beam widths in conventional and volume scans were calculated. The differences among the SCF values of conventional, volume scans, and AAPM were up to 23.0%. However, when SCF values were normalized in a phantom of 16 cm diameter, the error tended to decrease for the cases of thin body thickness, such as those of children. It was concluded that even if beam width and device are different, the SCF values recommended by AAPM are useful in clinical situations. PMID:27647595
Calculating Size of the Saturn's "Leopard Skin" Spots
NASA Astrophysics Data System (ADS)
Kochemasov, G. G.
2007-03-01
An IR image of the saturnian south (PIA08333) shows huge storm ~8000 km across containing smaller storms about 300 to 600 km across. Assuming a wave nature of this phenomena calculations with wave modulation give diameters of small forms ~400 km.
A Fourier analysis on the maximum acceptable grid size for discrete proton beam dose calculation
Li, Haisen S.; Romeijn, H. Edwin; Dempsey, James F.
2006-09-15
We developed an analytical method for determining the maximum acceptable grid size for discrete dose calculation in proton therapy treatment plan optimization, so that the accuracy of the optimized dose distribution is guaranteed in the phase of dose sampling and the superfluous computational work is avoided. The accuracy of dose sampling was judged by the criterion that the continuous dose distribution could be reconstructed from the discrete dose within a 2% error limit. To keep the error caused by the discrete dose sampling under a 2% limit, the dose grid size cannot exceed a maximum acceptable value. The method was based on Fourier analysis and the Shannon-Nyquist sampling theorem as an extension of our previous analysis for photon beam intensity modulated radiation therapy [J. F. Dempsey, H. E. Romeijn, J. G. Li, D. A. Low, and J. R. Palta, Med. Phys. 32, 380-388 (2005)]. The proton beam model used for the analysis was a near mono-energetic (of width about 1% the incident energy) and monodirectional infinitesimal (nonintegrated) pencil beam in water medium. By monodirection, we mean that the proton particles are in the same direction before entering the water medium and the various scattering prior to entrance to water is not taken into account. In intensity modulated proton therapy, the elementary intensity modulation entity for proton therapy is either an infinitesimal or finite sized beamlet. Since a finite sized beamlet is the superposition of infinitesimal pencil beams, the result of the maximum acceptable grid size obtained with infinitesimal pencil beam also applies to finite sized beamlet. The analytic Bragg curve function proposed by Bortfeld [T. Bortfeld, Med. Phys. 24, 2024-2033 (1997)] was employed. The lateral profile was approximated by a depth dependent Gaussian distribution. The model included the spreads of the Bragg peak and the lateral profiles due to multiple Coulomb scattering. The dependence of the maximum acceptable dose grid size on the
Allocating Sample Sizes to Reduce Budget for Fixed-Effect 2×2 Heterogeneous Analysis of Variance
ERIC Educational Resources Information Center
Luh, Wei-Ming; Guo, Jiin-Huarng
2016-01-01
This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…
Olson, J.M.; Wijsman, E.M.
1994-09-01
The presence of linkage disequilibrium between closely linked loci can aid in the fine mapping of disease loci. The authors investigate the power of several designs for sampling individuals with different disease genotypes. As expected, haplotype data provide the greatest power for detecting disequilibrium, but, in the absence of parental information to resolve the phase of double heterozygotes, the most powerful design samples only individuals homozygous at the trait locus. For rare diseases, such a scheme is generally not feasible, and the authors also provide power and sample-size calculations for designs that sample heterozygotes. The results provide information useful in planning disequilibrium studies. 17 refs., 3 figs., 4 tabs.
NASA Astrophysics Data System (ADS)
Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander
2016-04-01
In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least
NASA Astrophysics Data System (ADS)
Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander
2016-09-01
In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous
Computer program for the calculation of grain size statistics by the method of moments
Sawyer, Michael B.
1977-01-01
A computer program is presented for a Hewlett-Packard Model 9830A desk-top calculator (1) which calculates statistics using weight or point count data from a grain-size analysis. The program uses the method of moments in contrast to the more commonly used but less inclusive graphic method of Folk and Ward (1957). The merits of the program are: (1) it is rapid; (2) it can accept data in either grouped or ungrouped format; (3) it allows direct comparison with grain-size data in the literature that have been calculated by the method of moments; (4) it utilizes all of the original data rather than percentiles from the cumulative curve as in the approximation technique used by the graphic method; (5) it is written in the computer language BASIC, which is easily modified and adapted to a wide variety of computers; and (6) when used in the HP-9830A, it does not require punching of data cards. The method of moments should be used only if the entire sample has been measured and the worker defines the measured grain-size range. (1) Use of brand names in this paper does not imply endorsement of these products by the U.S. Geological Survey.
MINSIZE: A Computer Program for Obtaining Minimum Sample Size as an Indicator of Effect Size.
ERIC Educational Resources Information Center
Morse, David T.
1998-01-01
Describes MINSIZE, an MS-DOS computer program that permits the user to determine the minimum sample size needed for the results of a given analysis to be statistically significant. Program applications for statistical significance tests are presented and illustrated. (SLD)
Kikuchi, Takashi; Gittins, John
2011-08-01
The behavioural Bayes approach to sample size determination for clinical trials assumes that the number of subsequent patients switching to a new drug from the current drug depends on the strength of the evidence for efficacy and safety that was observed in the clinical trials. The optimal sample size is the one which maximises the expected net benefit of the trial. The approach has been developed in a series of papers by Pezeshk and the present authors (Gittins JC, Pezeshk H. A behavioral Bayes method for determining the size of a clinical trial. Drug Information Journal 2000; 34: 355-63; Gittins JC, Pezeshk H. How Large should a clinical trial be? The Statistician 2000; 49(2): 177-87; Gittins JC, Pezeshk H. A decision theoretic approach to sample size determination in clinical trials. Journal of Biopharmaceutical Statistics 2002; 12(4): 535-51; Gittins JC, Pezeshk H. A fully Bayesian approach to calculating sample sizes for clinical trials with binary responses. Drug Information Journal 2002; 36: 143-50; Kikuchi T, Pezeshk H, Gittins J. A Bayesian cost-benefit approach to the determination of sample size in clinical trials. Statistics in Medicine 2008; 27(1): 68-82; Kikuchi T, Gittins J. A behavioral Bayes method to determine the sample size of a clinical trial considering efficacy and safety. Statistics in Medicine 2009; 28(18): 2293-306; Kikuchi T, Gittins J. A Bayesian procedure for cost-benefit evaluation of a new drug in multi-national clinical trials. Statistics in Medicine 2009 (Submitted)). The purpose of this article is to provide a rationale for experimental designs which allocate more patients to the new treatment than to the control group. The model uses a logistic weight function, including an interaction term linking efficacy and safety, which determines the number of patients choosing the new drug, and hence the resulting benefit. A Monte Carlo simulation is employed for the calculation. Having a larger group of patients on the new drug in general
Calculating ensemble averaged descriptions of protein rigidity without sampling.
González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J
2012-01-01
Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.
Calculation of a fluctuating entropic force by phase space sampling.
Waters, James T; Kim, Harold D
2015-07-01
A polymer chain pinned in space exerts a fluctuating force on the pin point in thermal equilibrium. The average of such fluctuating force is well understood from statistical mechanics as an entropic force, but little is known about the underlying force distribution. Here, we introduce two phase space sampling methods that can produce the equilibrium distribution of instantaneous forces exerted by a terminally pinned polymer. In these methods, both the positions and momenta of mass points representing a freely jointed chain are perturbed in accordance with the spatial constraints and the Boltzmann distribution of total energy. The constraint force for each conformation and momentum is calculated using Lagrangian dynamics. Using terminally pinned chains in space and on a surface, we show that the force distribution is highly asymmetric with both tensile and compressive forces. Most importantly, the mean of the distribution, which is equal to the entropic force, is not the most probable force even for long chains. Our work provides insights into the mechanistic origin of entropic forces, and an efficient computational tool for unbiased sampling of the phase space of a constrained system. PMID:26274308
Computer program calculates and plots surface area and pore size distribution data
NASA Technical Reports Server (NTRS)
Halpert, G.
1968-01-01
Computer program calculates surface area and pore size distribution of powders, metals, ceramics, and catalysts, and prints and plots the desired data directly. Surface area calculations are based on the gas adsorption technique of Brunauer, Emmett, and Teller, and pore size distribution calculations are based on the gas adsorption technique of Pierce.
Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes
Kelleher, Jerome; Etheridge, Alison M; McVean, Gilean
2016-01-01
A central challenge in the analysis of genetic variation is to provide realistic genome simulation across millions of samples. Present day coalescent simulations do not scale well, or use approximations that fail to capture important long-range linkage properties. Analysing the results of simulations also presents a substantial challenge, as current methods to store genealogies consume a great deal of space, are slow to parse and do not take advantage of shared structure in correlated trees. We solve these problems by introducing sparse trees and coalescence records as the key units of genealogical analysis. Using these tools, exact simulation of the coalescent with recombination for chromosome-sized regions over hundreds of thousands of samples is possible, and substantially faster than present-day approximate methods. We can also analyse the results orders of magnitude more quickly than with existing methods. PMID:27145223
GUIDE TO CALCULATING TRANSPORT EFFICIENCY OF AEROSOLS IN OCCUPATIONAL AIR SAMPLING SYSTEMS
Hogue, M.; Hadlock, D.; Thompson, M.; Farfan, E.
2013-11-12
This report will present hand calculations for transport efficiency based on aspiration efficiency and particle deposition losses. Because the hand calculations become long and tedious, especially for lognormal distributions of aerosols, an R script (R 2011) will be provided for each element examined. Calculations are provided for the most common elements in a remote air sampling system, including a thin-walled probe in ambient air, straight tubing, bends and a sample housing. One popular alternative approach would be to put such calculations in a spreadsheet, a thorough version of which is shared by Paul Baron via the Aerocalc spreadsheet (Baron 2012). To provide greater transparency and to avoid common spreadsheet vulnerabilities to errors (Burns 2012), this report uses R. The particle size is based on the concept of activity median aerodynamic diameter (AMAD). The AMAD is a particle size in an aerosol where fifty percent of the activity in the aerosol is associated with particles of aerodynamic diameter greater than the AMAD. This concept allows for the simplification of transport efficiency calculations where all particles are treated as spheres with the density of water (1g cm-3). In reality, particle densities depend on the actual material involved. Particle geometries can be very complicated. Dynamic shape factors are provided by Hinds (Hinds 1999). Some example factors are: 1.00 for a sphere, 1.08 for a cube, 1.68 for a long cylinder (10 times as long as it is wide), 1.05 to 1.11 for bituminous coal, 1.57 for sand and 1.88 for talc. Revision 1 is made to correct an error in the original version of this report. The particle distributions are based on activity weighting of particles rather than based on the number of particles of each size. Therefore, the mass correction made in the original version is removed from the text and the calculations. Results affected by the change are updated.
Reduced sample sizes for atrophy outcomes in Alzheimer's disease trials: baseline adjustment.
Schott, J M; Bartlett, J W; Barnes, J; Leung, K K; Ourselin, S; Fox, N C
2010-08-01
Cerebral atrophy rate is increasingly used as an outcome measure for Alzheimer's disease (AD) trials. We used the Alzheimer's disease Neuroimaging initiative (ADNI) dataset to assess if adjusting for baseline characteristics can reduce sample sizes. Controls (n = 199), patients with mild cognitive impairment (MCI) (n = 334) and AD (n = 144) had two MRI scans, 1-year apart; approximately 55% had baseline CSF tau, p-tau, and Abeta1-42. Whole brain (KN-BSI) and hippocampal (HMAPS-HBSI) atrophy rate, and ventricular expansion (VBSI) were calculated for each group; numbers required to power a placebo-controlled trial were estimated. Sample sizes per arm (80% power, 25% absolute rate reduction) for AD were (95% CI): brain atrophy = 81 (64,109), hippocampal atrophy = 88 (68,119), ventricular expansion = 118 (92,157); and for MCI: brain atrophy = 149 (122,188), hippocampal atrophy = 201 (160,262), ventricular expansion = 234 (191,295). To detect a 25% reduction relative to normal aging required increased sample sizes approximately 3-fold (AD), and approximately 5-fold (MCI). Disease severity and Abeta1-42 contributed significantly to atrophy rate variability. Adjusting for 11 predefined covariates reduced sample sizes by up to 30%. Treatment trials in AD should consider the effects of normal aging; adjusting for baseline characteristics can significantly reduce required sample sizes.
Piepel, Gregory F.; Matzke, Brett D.; Sego, Landon H.; Amidan, Brett G.
2013-04-27
This report discusses the methodology, formulas, and inputs needed to make characterization and clearance decisions for Bacillus anthracis-contaminated and uncontaminated (or decontaminated) areas using a statistical sampling approach. Specifically, the report includes the methods and formulas for calculating the • number of samples required to achieve a specified confidence in characterization and clearance decisions • confidence in making characterization and clearance decisions for a specified number of samples for two common statistically based environmental sampling approaches. In particular, the report addresses an issue raised by the Government Accountability Office by providing methods and formulas to calculate the confidence that a decision area is uncontaminated (or successfully decontaminated) if all samples collected according to a statistical sampling approach have negative results. Key to addressing this topic is the probability that an individual sample result is a false negative, which is commonly referred to as the false negative rate (FNR). The two statistical sampling approaches currently discussed in this report are 1) hotspot sampling to detect small isolated contaminated locations during the characterization phase, and 2) combined judgment and random (CJR) sampling during the clearance phase. Typically if contamination is widely distributed in a decision area, it will be detectable via judgment sampling during the characterization phrase. Hotspot sampling is appropriate for characterization situations where contamination is not widely distributed and may not be detected by judgment sampling. CJR sampling is appropriate during the clearance phase when it is desired to augment judgment samples with statistical (random) samples. The hotspot and CJR statistical sampling approaches are discussed in the report for four situations: 1. qualitative data (detect and non-detect) when the FNR = 0 or when using statistical sampling methods that account
NASA Astrophysics Data System (ADS)
Cienciala, Piotr; Hassan, Marwan A.
2016-03-01
Adequate description of hydraulic variables based on a sample of field measurements is challenging in coarse-bed streams, a consequence of high spatial heterogeneity in flow properties that arises due to the complexity of channel boundary. By applying a resampling procedure based on bootstrapping to an extensive field data set, we have estimated sampling variability and its relationship with sample size in relation to two common methods of representing flow characteristics, spatially averaged velocity profiles and fitted probability distributions. The coefficient of variation in bed shear stress and roughness length estimated from spatially averaged velocity profiles and in shape and scale parameters of gamma distribution fitted to local values of bed shear stress, velocity, and depth was high, reaching 15-20% of the parameter value even at the sample size of 100 (sampling density 1 m-2). We illustrated implications of these findings with two examples. First, sensitivity analysis of a 2-D hydrodynamic model to changes in roughness length parameter showed that the sampling variability range observed in our resampling procedure resulted in substantially different frequency distributions and spatial patterns of modeled hydraulic variables. Second, using a bedload formula, we showed that propagation of uncertainty in the parameters of a gamma distribution used to model bed shear stress led to the coefficient of variation in predicted transport rates exceeding 50%. Overall, our findings underscore the importance of reporting the precision of estimated hydraulic parameters. When such estimates serve as input into models, uncertainty propagation should be explicitly accounted for by running ensemble simulations.
Quantum state discrimination bounds for finite sample size
Audenaert, Koenraad M. R.; Mosonyi, Milan; Verstraete, Frank
2012-12-15
In the problem of quantum state discrimination, one has to determine by measurements the state of a quantum system, based on the a priori side information that the true state is one of the two given and completely known states, {rho} or {sigma}. In general, it is not possible to decide the identity of the true state with certainty, and the optimal measurement strategy depends on whether the two possible errors (mistaking {rho} for {sigma}, or the other way around) are treated as of equal importance or not. Results on the quantum Chernoff and Hoeffding bounds and the quantum Stein's lemma show that, if several copies of the system are available then the optimal error probabilities decay exponentially in the number of copies, and the decay rate is given by a certain statistical distance between {rho} and {sigma} (the Chernoff distance, the Hoeffding distances, and the relative entropy, respectively). While these results provide a complete solution to the asymptotic problem, they are not completely satisfying from a practical point of view. Indeed, in realistic scenarios one has access only to finitely many copies of a system, and therefore it is desirable to have bounds on the error probabilities for finite sample size. In this paper we provide finite-size bounds on the so-called Stein errors, the Chernoff errors, the Hoeffding errors, and the mixed error probabilities related to the Chernoff and the Hoeffding errors.
Sample size determination for a t test given a t value from a previous study: A FORTRAN 77 program.
Gillett, R
2001-11-01
When uncertain about the magnitude of an effect, researchers commonly substitute in the standard sample-size-determination formula an estimate of effect size derived from a previous experiment. A problem with this approach is that the traditional sample-size-determination formula was not designed to deal with the uncertainty inherent in an effect-size estimate. Consequently, estimate-substitution in the traditional sample-size-determination formula can lead to a substantial loss of power. A method of sample-size determination designed to handle uncertainty in effect-size estimates is described. The procedure uses the t value and sample size from a previous study, which might be a pilot study or a related study in the same area, to establish a distribution of probable effect sizes. The sample size to be employed in the new study is that which supplies an expected power of the desired amount over the distribution of probable effect sizes. A FORTRAN 77 program is presented that permits swift calculation of sample size for a variety of t tests, including independent t tests, related t tests, t tests of correlation coefficients, and t tests of multiple regression b coefficients.
MEPAG Recommendations for a 2018 Mars Sample Return Caching Lander - Sample Types, Number, and Sizes
NASA Technical Reports Server (NTRS)
Allen, Carlton C.
2011-01-01
The return to Earth of geological and atmospheric samples from the surface of Mars is among the highest priority objectives of planetary science. The MEPAG Mars Sample Return (MSR) End-to-End International Science Analysis Group (MEPAG E2E-iSAG) was chartered to propose scientific objectives and priorities for returned sample science, and to map out the implications of these priorities, including for the proposed joint ESA-NASA 2018 mission that would be tasked with the crucial job of collecting and caching the samples. The E2E-iSAG identified four overarching scientific aims that relate to understanding: (A) the potential for life and its pre-biotic context, (B) the geologic processes that have affected the martian surface, (C) planetary evolution of Mars and its atmosphere, (D) potential for future human exploration. The types of samples deemed most likely to achieve the science objectives are, in priority order: (1A). Subaqueous or hydrothermal sediments (1B). Hydrothermally altered rocks or low temperature fluid-altered rocks (equal priority) (2). Unaltered igneous rocks (3). Regolith, including airfall dust (4). Present-day atmosphere and samples of sedimentary-igneous rocks containing ancient trapped atmosphere Collection of geologically well-characterized sample suites would add considerable value to interpretations of all collected rocks. To achieve this, the total number of rock samples should be about 30-40. In order to evaluate the size of individual samples required to meet the science objectives, the E2E-iSAG reviewed the analytical methods that would likely be applied to the returned samples by preliminary examination teams, for planetary protection (i.e., life detection, biohazard assessment) and, after distribution, by individual investigators. It was concluded that sample size should be sufficient to perform all high-priority analyses in triplicate. In keeping with long-established curatorial practice of extraterrestrial material, at least 40% by
Optimization of finite-size errors in finite-temperature calculations of unordered phases
NASA Astrophysics Data System (ADS)
Iyer, Deepak; Srednicki, Mark; Rigol, Marcos
It is common knowledge that the microcanonical, canonical, and grand canonical ensembles are equivalent in thermodynamically large systems. Here, we study finite-size effects in the latter two ensembles. We show that contrary to naive expectations, finite-size errors are exponentially small in grand canonical ensemble calculations of translationally invariant systems in unordered phases at finite temperature. Open boundary conditions and canonical ensemble calculations suffer from finite-size errors that are only polynomially small in the system size. We further show that finite-size effects are generally smallest in numerical linked cluster expansions. Our conclusions are supported by analytical and numerical analyses of classical and quantum systems.
40 CFR 600.208-77 - Sample calculation.
Code of Federal Regulations, 2011 CFR
2011-07-01
... ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Procedures for Calculating Fuel Economy and Carbon-Related Exhaust Emission Values for 1977 and Later Model Year Automobiles § 600.208-77...
Implications of sampling design and sample size for national carbon accounting systems
2011-01-01
Background Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources. Results We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives. Conclusions, brief summary and potential implications Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial
Power analysis and sample size estimation for RNA-Seq differential expression
Ching, Travers; Huang, Sijia
2014-01-01
It is crucial for researchers to optimize RNA-seq experimental designs for differential expression detection. Currently, the field lacks general methods to estimate power and sample size for RNA-Seq in complex experimental designs, under the assumption of the negative binomial distribution. We simulate RNA-Seq count data based on parameters estimated from six widely different public data sets (including cell line comparison, tissue comparison, and cancer data sets) and calculate the statistical power in paired and unpaired sample experiments. We comprehensively compare five differential expression analysis packages (DESeq, edgeR, DESeq2, sSeq, and EBSeq) and evaluate their performance by power, receiver operator characteristic (ROC) curves, and other metrics including areas under the curve (AUC), Matthews correlation coefficient (MCC), and F-measures. DESeq2 and edgeR tend to give the best performance in general. Increasing sample size or sequencing depth increases power; however, increasing sample size is more potent than sequencing depth to increase power, especially when the sequencing depth reaches 20 million reads. Long intergenic noncoding RNAs (lincRNA) yields lower power relative to the protein coding mRNAs, given their lower expression level in the same RNA-Seq experiment. On the other hand, paired-sample RNA-Seq significantly enhances the statistical power, confirming the importance of considering the multifactor experimental design. Finally, a local optimal power is achievable for a given budget constraint, and the dominant contributing factor is sample size rather than the sequencing depth. In conclusion, we provide a power analysis tool (http://www2.hawaii.edu/~lgarmire/RNASeqPowerCalculator.htm) that captures the dispersion in the data and can serve as a practical reference under the budget constraint of RNA-Seq experiments. PMID:25246651
Lakens, Daniël
2013-01-01
Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists themselves, effect sizes are most useful because they facilitate cumulative science. Effect sizes can be used to determine the sample size for follow-up studies, or examining effects across studies. This article aims to provide a practical primer on how to calculate and report effect sizes for t-tests and ANOVA's such that effect sizes can be used in a-priori power analyses and meta-analyses. Whereas many articles about effect sizes focus on between-subjects designs and address within-subjects designs only briefly, I provide a detailed overview of the similarities and differences between within- and between-subjects designs. I suggest that some research questions in experimental psychology examine inherently intra-individual effects, which makes effect sizes that incorporate the correlation between measures the best summary of the results. Finally, a supplementary spreadsheet is provided to make it as easy as possible for researchers to incorporate effect size calculations into their workflow. PMID:24324449
Threshold-dependent sample sizes for selenium assessment with stream fish tissue
Hitt, Nathaniel P.; Smith, David
2013-01-01
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 4-8 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 8 fish could detect an increase of ∼ 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 ∼ 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 ∼ 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 by increased precision of composites for estimating mean
Threshold-dependent sample sizes for selenium assessment with stream fish tissue.
Hitt, Nathaniel P; Smith, David R
2015-01-01
Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α=0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites
40 CFR 91.419 - Raw emission sampling calculations.
Code of Federal Regulations, 2012 CFR
2012-07-01
... mass flow rate , MHCexh = Molecular weight of hydrocarbons in the exhaust; see the following equation: MHCexh = 12.01 + 1.008 × α Where: α=Hydrocarbon/carbon atomic ratio of the fuel. Mexh=Molecular weight of..., calculated from the following equation: ER04OC96.019 WCO = Mass rate of CO in exhaust, MCO = Molecular...
40 CFR 91.419 - Raw emission sampling calculations.
Code of Federal Regulations, 2010 CFR
2010-07-01
... mass flow rate , MHCexh = Molecular weight of hydrocarbons in the exhaust; see the following equation: MHCexh = 12.01 + 1.008 × α Where: α=Hydrocarbon/carbon atomic ratio of the fuel. Mexh=Molecular weight of..., calculated from the following equation: ER04OC96.019 WCO = Mass rate of CO in exhaust, MCO = Molecular...
40 CFR 91.419 - Raw emission sampling calculations.
Code of Federal Regulations, 2014 CFR
2014-07-01
... mass flow rate , MHCexh = Molecular weight of hydrocarbons in the exhaust; see the following equation: MHCexh = 12.01 + 1.008 × α Where: α=Hydrocarbon/carbon atomic ratio of the fuel. Mexh=Molecular weight of..., calculated from the following equation: ER04OC96.019 WCO = Mass rate of CO in exhaust, MCO = Molecular...
40 CFR 91.419 - Raw emission sampling calculations.
Code of Federal Regulations, 2011 CFR
2011-07-01
... mass flow rate , MHCexh = Molecular weight of hydrocarbons in the exhaust; see the following equation: MHCexh = 12.01 + 1.008 × α Where: α=Hydrocarbon/carbon atomic ratio of the fuel. Mexh=Molecular weight of..., calculated from the following equation: ER04OC96.019 WCO = Mass rate of CO in exhaust, MCO = Molecular...
40 CFR 91.419 - Raw emission sampling calculations.
Code of Federal Regulations, 2013 CFR
2013-07-01
... mass flow rate , MHCexh = Molecular weight of hydrocarbons in the exhaust; see the following equation: MHCexh = 12.01 + 1.008 × α Where: α=Hydrocarbon/carbon atomic ratio of the fuel. Mexh=Molecular weight of..., calculated from the following equation: ER04OC96.019 WCO = Mass rate of CO in exhaust, MCO = Molecular...
Sample size and allocation of effort in point count sampling of birds in bottomland hardwood forests
Smith, W.P.; Twedt, D.J.; Cooper, R.J.; Wiedenfeld, D.A.; Hamel, P.B.; Ford, R.P.; Ralph, C. John; Sauer, John R.; Droege, Sam
1995-01-01
To examine sample size requirements and optimum allocation of effort in point count sampling of bottomland hardwood forests, we computed minimum sample sizes from variation recorded during 82 point counts (May 7-May 16, 1992) from three localities containing three habitat types across three regions of the Mississippi Alluvial Valley (MAV). Also, we estimated the effect of increasing the number of points or visits by comparing results of 150 four-minute point counts obtained from each of four stands on Delta Experimental Forest (DEF) during May 8-May 21, 1991 and May 30-June 12, 1992. For each stand, we obtained bootstrap estimates of mean cumulative number of species each year from all possible combinations of six points and six visits. ANOVA was used to model cumulative species as a function of number of points visited, number of visits to each point, and interaction of points and visits. There was significant variation in numbers of birds and species between regions and localities (nested within region); neither habitat, nor the interaction between region and habitat, was significant. For a = 0.05 and a = 0.10, minimum sample size estimates (per factor level) varied by orders of magnitude depending upon the observed or specified range of desired detectable difference. For observed regional variation, 20 and 40 point counts were required to accommodate variability in total individuals (MSE = 9.28) and species (MSE = 3.79), respectively, whereas ? 25 percent of the mean could be achieved with five counts per factor level. Sample size sufficient to detect actual differences of Wood Thrush (Hylocichla mustelina) was >200, whereas the Prothonotary Warbler (Protonotaria citrea) required <10 counts. Differences in mean cumulative species were detected among number of points visited and among number of visits to a point. In the lower MAV, mean cumulative species increased with each added point through five points and with each additional visit through four visits
Axelrod, M
2005-08-18
Discovery sampling is a tool used in a discovery auditing. The purpose of such an audit is to provide evidence that some (usually large) inventory of items complies with a defined set of criteria by inspecting (or measuring) a representative sample drawn from the inventory. If any of the items in the sample fail compliance (defective items), then the audit has discovered an impropriety, which often triggers some action. However finding defective items in a sample is an unusual event--auditors expect the inventory to be in compliance because they come to the audit with an ''innocent until proven guilty attitude''. As part of their work product, the auditors must provide a confidence statement about compliance level of the inventory. Clearly the more items they inspect, the greater their confidence, but more inspection means more cost. Audit costs can be purely economic, but in some cases, the cost is political because more inspection means more intrusion, which communicates an attitude of distrust. Thus, auditors have every incentive to minimize the number of items in the sample. Indeed, in some cases the sample size can be specifically limited by a prior agreement or an ongoing policy. Statements of confidence about the results of a discovery sample generally use the method of confidence intervals. After finding no defectives in the sample, the auditors provide a range of values that bracket the number of defective items that could credibly be in the inventory. They also state a level of confidence for the interval, usually 90% or 95%. For example, the auditors might say: ''We believe that this inventory of 1,000 items contains no more than 10 defectives with a confidence of 95%''. Frequently clients ask their auditors questions such as: How many items do you need to measure to be 95% confident that there are no more than 10 defectives in the entire inventory? Sometimes when the auditors answer with big numbers like ''300'', their clients balk. They balk because a
40 CFR Appendix II to Part 600 - Sample Fuel Economy Calculations
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 30 2014-07-01 2014-07-01 false Sample Fuel Economy Calculations II... FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. II Appendix II to Part 600—Sample Fuel Economy Calculations (a) This sample fuel economy calculation is applicable...
40 CFR Appendix II to Part 600 - Sample Fuel Economy Calculations
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 31 2013-07-01 2013-07-01 false Sample Fuel Economy Calculations II... FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. II Appendix II to Part 600—Sample Fuel Economy Calculations (a) This sample fuel economy calculation is applicable...
40 CFR Appendix II to Part 600 - Sample Fuel Economy Calculations
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 30 2011-07-01 2011-07-01 false Sample Fuel Economy Calculations II... FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. II Appendix II to Part 600—Sample Fuel Economy Calculations (a) This sample fuel economy calculation is applicable...
40 CFR Appendix II to Part 600 - Sample Fuel Economy Calculations
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 31 2012-07-01 2012-07-01 false Sample Fuel Economy Calculations II... FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. II Appendix II to Part 600—Sample Fuel Economy Calculations (a) This sample fuel economy calculation is applicable...
40 CFR Appendix II to Part 600 - Sample Fuel Economy Calculations
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sample Fuel Economy Calculations II... FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. II Appendix II to Part 600—Sample Fuel Economy Calculations (a) This sample fuel economy calculation is applicable...
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
Lee, Eun Gyung; Lee, Taekhee; Kim, Seung Won; Lee, Larry; Flemmer, Michael M.; Harper, Martin
2015-01-01
This second, and concluding, part of this study evaluated changes in sampling efficiency of respirable size-selective samplers due to air pulsations generated by the selected personal sampling pumps characterized in Part I (Lee E, Lee L, Möhlmann C et al. Evaluation of pump pulsation in respirable size-selective sampling: Part I. Pulsation measurements. Ann Occup Hyg 2013). Nine particle sizes of monodisperse ammonium fluorescein (from 1 to 9 μm mass median aerodynamic diameter) were generated individually by a vibrating orifice aerosol generator from dilute solutions of fluorescein in aqueous ammonia and then injected into an environmental chamber. To collect these particles, 10-mm nylon cyclones, also known as Dorr-Oliver (DO) cyclones, were used with five medium volumetric flow rate pumps. Those were the Apex IS, HFS513, GilAir5, Elite5, and Basic5 pumps, which were found in Part I to generate pulsations of 5% (the lowest), 25%, 30%, 56%, and 70% (the highest), respectively. GK2.69 cyclones were used with the Legacy [pump pulsation (PP) = 15%] and Elite12 (PP = 41%) pumps for collection at high flows. The DO cyclone was also used to evaluate changes in sampling efficiency due to pulse shape. The HFS513 pump, which generates a more complex pulse shape, was compared to a single sine wave fluctuation generated by a piston. The luminescent intensity of the fluorescein extracted from each sample was measured with a luminescence spectrometer. Sampling efficiencies were obtained by dividing the intensity of the fluorescein extracted from the filter placed in a cyclone with the intensity obtained from the filter used with a sharp-edged reference sampler. Then, sampling efficiency curves were generated using a sigmoid function with three parameters and each sampling efficiency curve was compared to that of the reference cyclone by constructing bias maps. In general, no change in sampling efficiency (bias under ±10%) was observed until pulsations exceeded 25% for the
A Variational Approach to Enhanced Sampling and Free Energy Calculations
NASA Astrophysics Data System (ADS)
Parrinello, Michele
2015-03-01
The presence of kinetic bottlenecks severely hampers the ability of widely used sampling methods like molecular dynamics or Monte Carlo to explore complex free energy landscapes. One of the most popular methods for addressing this problem is umbrella sampling which is based on the addition of an external bias which helps overcoming the kinetic barriers. The bias potential is usually taken to be a function of a restricted number of collective variables. However constructing the bias is not simple, especially when the number of collective variables increases. Here we introduce a functional of the bias which, when minimized, allows us to recover the free energy. We demonstrate the usefulness and the flexibility of this approach on a number of examples which include the determination of a six dimensional free energy surface. Besides the practical advantages, the existence of such a variational principle allows us to look at the enhanced sampling problem from a rather convenient vantage point.
Variational Approach to Enhanced Sampling and Free Energy Calculations
NASA Astrophysics Data System (ADS)
Valsson, Omar; Parrinello, Michele
2014-08-01
The ability of widely used sampling methods, such as molecular dynamics or Monte Carlo simulations, to explore complex free energy landscapes is severely hampered by the presence of kinetic bottlenecks. A large number of solutions have been proposed to alleviate this problem. Many are based on the introduction of a bias potential which is a function of a small number of collective variables. However constructing such a bias is not simple. Here we introduce a functional of the bias potential and an associated variational principle. The bias that minimizes the functional relates in a simple way to the free energy surface. This variational principle can be turned into a practical, efficient, and flexible sampling method. A number of numerical examples are presented which include the determination of a three-dimensional free energy surface. We argue that, beside being numerically advantageous, our variational approach provides a convenient and novel standpoint for looking at the sampling problem.
40 CFR 89.424 - Dilute emission sampling calculations.
Code of Federal Regulations, 2014 CFR
2014-07-01
... during the mode divided by the sample time for the mode. WFi = Effective weighing factor. Pi = Power measured during each mode (Power set = zero for the idle mode). (b) The mass of each pollutant for each... diesel, and (0.5746 kg/m3) for #2 diesel, assuming an average carbon to hydrogen ratio of 1:1.93 for...
40 CFR 89.424 - Dilute emission sampling calculations.
Code of Federal Regulations, 2010 CFR
2010-07-01
... during the mode divided by the sample time for the mode. WFi = Effective weighing factor. Pi = Power measured during each mode (Power set = zero for the idle mode). (b) The mass of each pollutant for each... diesel, and (0.5746 kg/m3) for #2 diesel, assuming an average carbon to hydrogen ratio of 1:1.93 for...
40 CFR 89.424 - Dilute emission sampling calculations.
Code of Federal Regulations, 2012 CFR
2012-07-01
... during the mode divided by the sample time for the mode. WFi = Effective weighing factor. Pi = Power measured during each mode (Power set = zero for the idle mode). (b) The mass of each pollutant for each... diesel, and (0.5746 kg/m3) for #2 diesel, assuming an average carbon to hydrogen ratio of 1:1.93 for...
40 CFR 89.424 - Dilute emission sampling calculations.
Code of Federal Regulations, 2011 CFR
2011-07-01
... during the mode divided by the sample time for the mode. WFi = Effective weighing factor. Pi = Power measured during each mode (Power set = zero for the idle mode). (b) The mass of each pollutant for each... diesel, and (0.5746 kg/m3) for #2 diesel, assuming an average carbon to hydrogen ratio of 1:1.93 for...
40 CFR 89.424 - Dilute emission sampling calculations.
Code of Federal Regulations, 2013 CFR
2013-07-01
... during the mode divided by the sample time for the mode. WFi = Effective weighing factor. Pi = Power measured during each mode (Power set = zero for the idle mode). (b) The mass of each pollutant for each... diesel, and (0.5746 kg/m3) for #2 diesel, assuming an average carbon to hydrogen ratio of 1:1.93 for...
Space resection model calculation based on Random Sample Consensus algorithm
NASA Astrophysics Data System (ADS)
Liu, Xinzhu; Kang, Zhizhong
2016-03-01
Resection has been one of the most important content in photogrammetry. It aims at the position and attitude information of camera at the shooting point. However in some cases, the observed values for calculating are with gross errors. This paper presents a robust algorithm that using RANSAC method with DLT model can effectually avoiding the difficulties to determine initial values when using co-linear equation. The results also show that our strategies can exclude crude handicap and lead to an accurate and efficient way to gain elements of exterior orientation.
Hauschke, D; Steinijans, W V; Diletti, E; Schall, R; Luus, H G; Elze, M; Blume, H
1994-07-01
Bioequivalence studies are generally performed as crossover studies and, therefore, information on the intrasubject coefficient of variation is needed for sample size planning. Unfortunately, this information is usually not presented in publications on bioequivalence studies, and only the pooled inter- and intrasubject coefficient of variation for either test or reference formulation is reported. Thus, the essential information for sample size planning of future studies is not made available to other researchers. In order to overcome such shortcomings, the presentation of results from bioequivalence studies should routinely include the intrasubject coefficient of variation. For the relevant coefficients of variation, theoretical background together with modes of calculation and presentation are given in this communication with particular emphasis on the multiplicative model.
Sample sizes for brain atrophy outcomes in trials for secondary progressive multiple sclerosis
Altmann, D R.; Jasperse, B; Barkhof, F; Beckmann, K; Filippi, M; Kappos, L D.; Molyneux, P; Polman, C H.; Pozzilli, C; Thompson, A J.; Wagner, K; Yousry, T A.; Miller, D H.
2009-01-01
Background: Progressive brain atrophy in multiple sclerosis (MS) may reflect neuroaxonal and myelin loss and MRI measures of brain tissue loss are used as outcome measures in MS treatment trials. This study investigated sample sizes required to demonstrate reduction of brain atrophy using three outcome measures in a parallel group, placebo-controlled trial for secondary progressive MS (SPMS). Methods: Data were taken from a cohort of 43 patients with SPMS who had been followed up with 6-monthly T1-weighted MRI for up to 3 years within the placebo arm of a therapeutic trial. Central cerebral volumes (CCVs) were measured using a semiautomated segmentation approach, and brain volume normalized for skull size (NBV) was measured using automated segmentation (SIENAX). Change in CCV and NBV was measured by subtraction of baseline from serial CCV and SIENAX images; in addition, percentage brain volume change relative to baseline was measured directly using a registration-based method (SIENA). Sample sizes for given treatment effects and power were calculated for standard analyses using parameters estimated from the sample. Results: For a 2-year trial duration, minimum sample sizes per arm required to detect a 50% treatment effect at 80% power were 32 for SIENA, 69 for CCV, and 273 for SIENAX. Two-year minimum sample sizes were smaller than 1-year by 71% for SIENAX, 55% for CCV, and 44% for SIENA. Conclusion: SIENA and central cerebral volume are feasible outcome measures for inclusion in placebo-controlled trials in secondary progressive multiple sclerosis. GLOSSARY ANCOVA = analysis of covariance; CCV = central cerebral volume; FSL = FMRIB Software Library; MNI = Montreal Neurological Institute; MS = multiple sclerosis; NBV = normalized brain volume; PBVC = percent brain volume change; RRMS = relapsing–remitting multiple sclerosis; SPMS = secondary progressive multiple sclerosis. PMID:19005170
On the validity of the Poisson assumption in sampling nanometer-sized aerosols
Damit, Brian E; Wu, Dr. Chang-Yu; Cheng, Mengdawn
2014-01-01
A Poisson process is traditionally believed to apply to the sampling of aerosols. For a constant aerosol concentration, it is assumed that a Poisson process describes the fluctuation in the measured concentration because aerosols are stochastically distributed in space. Recent studies, however, have shown that sampling of micrometer-sized aerosols has non-Poissonian behavior with positive correlations. The validity of the Poisson assumption for nanometer-sized aerosols has not been examined and thus was tested in this study. Its validity was tested for four particle sizes - 10 nm, 25 nm, 50 nm and 100 nm - by sampling from indoor air with a DMA- CPC setup to obtain a time series of particle counts. Five metrics were calculated from the data: pair-correlation function (PCF), time-averaged PCF, coefficient of variation, probability of measuring a concentration at least 25% greater than average, and posterior distributions from Bayesian inference. To identify departures from Poissonian behavior, these metrics were also calculated for 1,000 computer-generated Poisson time series with the same mean as the experimental data. For nearly all comparisons, the experimental data fell within the range of 80% of the Poisson-simulation values. Essentially, the metrics for the experimental data were indistinguishable from a simulated Poisson process. The greater influence of Brownian motion for nanometer-sized aerosols may explain the Poissonian behavior observed for smaller aerosols. Although the Poisson assumption was found to be valid in this study, it must be carefully applied as the results here do not definitively prove applicability in all sampling situations.
Effects of sample size and sampling frequency on studies of brown bear home ranges and habitat use
Arthur, Steve M.; Schwartz, Charles C.
1999-01-01
We equipped 9 brown bears (Ursus arctos) on the Kenai Peninsula, Alaska, with collars containing both conventional very-high-frequency (VHF) transmitters and global positioning system (GPS) receivers programmed to determine an animal's position at 5.75-hr intervals. We calculated minimum convex polygon (MCP) and fixed and adaptive kernel home ranges for randomly-selected subsets of the GPS data to examine the effects of sample size on accuracy and precision of home range estimates. We also compared results obtained by weekly aerial radiotracking versus more frequent GPS locations to test for biases in conventional radiotracking data. Home ranges based on the MCP were 20-606 km2 (x = 201) for aerial radiotracking data (n = 12-16 locations/bear) and 116-1,505 km2 (x = 522) for the complete GPS data sets (n = 245-466 locations/bear). Fixed kernel home ranges were 34-955 km2 (x = 224) for radiotracking data and 16-130 km2 (x = 60) for the GPS data. Differences between means for radiotracking and GPS data were due primarily to the larger samples provided by the GPS data. Means did not differ between radiotracking data and equivalent-sized subsets of GPS data (P > 0.10). For the MCP, home range area increased and variability decreased asymptotically with number of locations. For the kernel models, both area and variability decreased with increasing sample size. Simulations suggested that the MCP and kernel models required >60 and >80 locations, respectively, for estimates to be both accurate (change in area <1%/additional location) and precise (CV < 50%). Although the radiotracking data appeared unbiased, except for the relationship between area and sample size, these data failed to indicate some areas that likely were important to bears. Our results suggest that the usefulness of conventional radiotracking data may be limited by potential biases and variability due to small samples. Investigators that use home range estimates in statistical tests should consider the
40 CFR 80.127 - Sample size guidelines.
Code of Federal Regulations, 2012 CFR
2012-07-01
...) Sample items shall be selected in such a way as to comprise a simple random sample of each relevant...% Expected Error Rate—0% Maximum Tolerable Error Rate—10% (3) Option 3. The auditor may use some other...
40 CFR 80.127 - Sample size guidelines.
Code of Federal Regulations, 2014 CFR
2014-07-01
...) Sample items shall be selected in such a way as to comprise a simple random sample of each relevant...% Expected Error Rate—0% Maximum Tolerable Error Rate—10% (3) Option 3. The auditor may use some other...
40 CFR 80.127 - Sample size guidelines.
Code of Federal Regulations, 2013 CFR
2013-07-01
...) Sample items shall be selected in such a way as to comprise a simple random sample of each relevant...% Expected Error Rate—0% Maximum Tolerable Error Rate—10% (3) Option 3. The auditor may use some other...
Sample size allocation for food item radiation monitoring and safety inspection.
Seto, Mayumi; Uriu, Koichiro
2015-03-01
The objective of this study is to identify a procedure for determining sample size allocation for food radiation inspections of more than one food item to minimize the potential risk to consumers of internal radiation exposure. We consider a simplified case of food radiation monitoring and safety inspection in which a risk manager is required to monitor two food items, milk and spinach, in a contaminated area. Three protocols for food radiation monitoring with different sample size allocations were assessed by simulating random sampling and inspections of milk and spinach in a conceptual monitoring site. Distributions of (131)I and radiocesium concentrations were determined in reference to (131)I and radiocesium concentrations detected in Fukushima prefecture, Japan, for March and April 2011. The results of the simulations suggested that a protocol that allocates sample size to milk and spinach based on the estimation of (131)I and radiocesium concentrations using the apparent decay rate constants sequentially calculated from past monitoring data can most effectively minimize the potential risks of internal radiation exposure.
Comparing Server Energy Use and Efficiency Using Small Sample Sizes
Coles, Henry C.; Qin, Yong; Price, Phillip N.
2014-11-01
This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency. The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro. Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured. At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a
Pang, Herbert; Jung, Sin-Ho
2013-04-01
A variety of prediction methods are used to relate high-dimensional genome data with a clinical outcome using a prediction model. Once a prediction model is developed from a data set, it should be validated using a resampling method or an independent data set. Although the existing prediction methods have been intensively evaluated by many investigators, there has not been a comprehensive study investigating the performance of the validation methods, especially with a survival clinical outcome. Understanding the properties of the various validation methods can allow researchers to perform more powerful validations while controlling for type I error. In addition, sample size calculation strategy based on these validation methods is lacking. We conduct extensive simulations to examine the statistical properties of these validation strategies. In both simulations and a real data example, we have found that 10-fold cross-validation with permutation gave the best power while controlling type I error close to the nominal level. Based on this, we have also developed a sample size calculation method that will be used to design a validation study with a user-chosen combination of prediction. Microarray and genome-wide association studies data are used as illustrations. The power calculation method in this presentation can be used for the design of any biomedical studies involving high-dimensional data and survival outcomes.
A Novel Size-Selective Airborne Particle Sampling Instrument (Wras) for Health Risk Evaluation
NASA Astrophysics Data System (ADS)
Gnewuch, H.; Muir, R.; Gorbunov, B.; Priest, N. D.; Jackson, P. R.
Health risks associated with inhalation of airborne particles are known to be influenced by particle sizes. A reliable, size resolving sampler, classifying particles in size ranges from 2 nm—30 μm and suitable for use in the field would be beneficial in investigating health risks associated with inhalation of airborne particles. A review of current aerosol samplers highlighted a number of limitations. These could be overcome by combining an inertial deposition impactor with a diffusion collector in a single device. The instrument was designed for analysing mass size distributions. Calibration was carried out using a number of recognised techniques. The instrument was tested in the field by collecting size resolved samples of lead containing aerosols present at workplaces in factories producing crystal glass. The mass deposited on each substrate proved sufficient to be detected and measured using atomic absorption spectroscopy. Mass size distributions of lead were produced and the proportion of lead present in the aerosol nanofraction calculated and varied from 10% to 70% by weight.
Communication: Finite size correction in periodic coupled cluster theory calculations of solids
NASA Astrophysics Data System (ADS)
Liao, Ke; Grüneis, Andreas
2016-10-01
We present a method to correct for finite size errors in coupled cluster theory calculations of solids. The outlined technique shares similarities with electronic structure factor interpolation methods used in quantum Monte Carlo calculations. However, our approach does not require the calculation of density matrices. Furthermore we show that the proposed finite size corrections achieve chemical accuracy in the convergence of second-order Møller-Plesset perturbation and coupled cluster singles and doubles correlation energies per atom for insulating solids with two atomic unit cells using 2 × 2 × 2 and 3 × 3 × 3 k-point meshes only.
Central limit theorem for variable size simple random sampling from a finite population
Wright, T.
1986-02-01
This paper introduces a sampling plan for finite populations herein called ''variable size simple random sampling'' and compares properties of estimators based on it with results from the usual fixed size simple random sampling without replacement. Necessary and sufficient conditions (in the spirit of Hajek) for the limiting distribution of the sample total (or sample mean) to be normal are given. 19 refs.
NASA Astrophysics Data System (ADS)
Goossens, Dirk
2010-11-01
Wind tunnel experiments were conducted with the USGS (United States Geological Survey) dust deposition sampler to test its efficiency for dust deposition and its capacity to collect representative samples for grain size analysis. Efficiency for dust deposition was ascertained relative to a water surface, which was considered the best alternative for simulating a perfectly absorbent surface. Capacity to collect representative samples for grain size analysis was ascertained by comparing the grain size distribution of the collected dust to that of the original dust. Three versions were tested: an empty sampler, a sampler filled with glass marbles, and a sampler filled with water. Efficiencies and capacity to collect representative samples were ascertained for five wind velocities (range: 1-5 m s -1) and seven grain size classes (range: 10-80 μm). All samplers showed a rapid drop in collection efficiency with increasing wind speed. Efficiencies are low, in the order of 10% or less for most common wind speeds over the continents. Efficiency also drops as the particles become coarser. Adding glass marbles to the sampler increases its efficiency, protects the settled dust from resuspension, and minimizes outsplash during rainfall. The sediment collected by the sampler is finer than the original dust. The bias in the grain size is more expressed in fine particle fractions than in coarse particle fractions. The performance of the USGS sampler is rather low when compared to other dust deposition samplers, but a procedure is provided that allows calculation of the original grain size distribution and dust deposition quantities.
Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.
ERIC Educational Resources Information Center
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)
10 CFR Appendix to Part 474 - Sample Petroleum-Equivalent Fuel Economy Calculations
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 3 2014-01-01 2014-01-01 false Sample Petroleum-Equivalent Fuel Economy Calculations..., DEVELOPMENT, AND DEMONSTRATION PROGRAM; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION Pt. 474, App. Appendix to Part 474—Sample Petroleum-Equivalent Fuel Economy Calculations Example 1: An electric vehicle...
10 CFR Appendix to Part 474 - Sample Petroleum-Equivalent Fuel Economy Calculations
Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 3 2013-01-01 2013-01-01 false Sample Petroleum-Equivalent Fuel Economy Calculations..., DEVELOPMENT, AND DEMONSTRATION PROGRAM; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION Pt. 474, App. Appendix to Part 474—Sample Petroleum-Equivalent Fuel Economy Calculations Example 1: An electric vehicle...
10 CFR Appendix to Part 474 - Sample Petroleum-Equivalent Fuel Economy Calculations
Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 3 2012-01-01 2012-01-01 false Sample Petroleum-Equivalent Fuel Economy Calculations..., DEVELOPMENT, AND DEMONSTRATION PROGRAM; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION Pt. 474, App. Appendix to Part 474—Sample Petroleum-Equivalent Fuel Economy Calculations Example 1: An electric vehicle...
10 CFR Appendix to Part 474 - Sample Petroleum-Equivalent Fuel Economy Calculations
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 3 2010-01-01 2010-01-01 false Sample Petroleum-Equivalent Fuel Economy Calculations..., DEVELOPMENT, AND DEMONSTRATION PROGRAM; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION Pt. 474, App. Appendix to Part 474—Sample Petroleum-Equivalent Fuel Economy Calculations Example 1: An electric vehicle...
A contemporary decennial global sample of changing agricultural field sizes
NASA Astrophysics Data System (ADS)
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.
Sample Size Determination for Regression Models Using Monte Carlo Methods in R
ERIC Educational Resources Information Center
Beaujean, A. Alexander
2014-01-01
A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…
7 CFR 201.43 - Size of sample.
Code of Federal Regulations, 2013 CFR
2013-01-01
... Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT... seeds of similar or larger size. (e) Two quarts (2.2 liters) of screenings. (f) Vegetable seed...
7 CFR 201.43 - Size of sample.
Code of Federal Regulations, 2010 CFR
2010-01-01
... examination: (a) Two ounces (57 grams) of grass seed not otherwise mentioned, white or alsike clover, or seeds not larger than these. (b) Five ounces (142 grams) of red or crimson clover, alfalfa, lespedeza, ryegrass, bromegrass, millet, flax, rape, or seeds of similar size. (c) One pound (454 grams) of...
NASA Technical Reports Server (NTRS)
Sandlin, Doral R.; Swanson, Stephen Mark
1990-01-01
The creation of a computer module used to calculate the size of the horizontal control surfaces of a conceptual aircraft design is discussed. The control surface size is determined by first calculating the size needed to rotate the aircraft during takeoff, and, second, by determining if the calculated size is large enough to maintain stability of the aircraft throughout any specified mission. The tail size needed to rotate during takeoff is calculated from a summation of forces about the main landing gear of the aircraft. The stability of the aircraft is determined from a summation of forces about the center of gravity during different phases of the aircraft's flight. Included in the horizontal control surface analysis are: downwash effects on an aft tail, upwash effects on a forward canard, and effects due to flight in close proximity to the ground. Comparisons of production aircraft with numerical models show good accuracy for control surface sizing. A modified canard design verified the accuracy of the module for canard configurations. Added to this stability and control module is a subroutine that determines one of the three design variables, for a stable vectored thrust aircraft. These include forward thrust nozzle position, aft thrust nozzle angle, and forward thrust split.
Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses
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
Exploring the Dependence of QM/MM Calculations of Enzyme Catalysis on the Size of the QM Region
2016-01-01
Although QM/MM calculations are the primary current tool for modeling enzymatic reactions, the reliability of such calculations can be limited by the size of the QM region. Thus, we examine in this work the dependence of QM/MM calculations on the size of the QM region, using the reaction of catechol-O-methyl transferase (COMT) as a test case. Our study focuses on the effect of adding residues to the QM region on the activation free energy, obtained with extensive QM/MM sampling. It is found that the sensitivity of the activation barrier to the size of the QM is rather limited, while the dependence of the reaction free energy is somewhat larger. Of course, the results depend on the inclusion of the first solvation shell in the QM regions. For example, the inclusion of the Mg2+ ion can change the activation barrier due to charge transfer effects. However, such effects can easily be included in semiempirical approaches by proper parametrization. Overall, we establish that QM/MM calculations of activation barriers of enzymatic reactions are not highly sensitive to the size of the QM region, beyond the immediate region that describes the reacting atoms. PMID:27552257
M. Gross
2004-09-01
The purpose of this scientific analysis is to define the sampled values of stochastic (random) input parameters for (1) rockfall calculations in the lithophysal and nonlithophysal zones under vibratory ground motions, and (2) structural response calculations for the drip shield and waste package under vibratory ground motions. This analysis supplies: (1) Sampled values of ground motion time history and synthetic fracture pattern for analysis of rockfall in emplacement drifts in nonlithophysal rock (Section 6.3 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (2) Sampled values of ground motion time history and rock mechanical properties category for analysis of rockfall in emplacement drifts in lithophysal rock (Section 6.4 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (3) Sampled values of ground motion time history and metal to metal and metal to rock friction coefficient for analysis of waste package and drip shield damage to vibratory motion in ''Structural Calculations of Waste Package Exposed to Vibratory Ground Motion'' (BSC 2004 [DIRS 167083]) and in ''Structural Calculations of Drip Shield Exposed to Vibratory Ground Motion'' (BSC 2003 [DIRS 163425]). The sampled values are indices representing the number of ground motion time histories, number of fracture patterns and rock mass properties categories. These indices are translated into actual values within the respective analysis and model reports or calculations. This report identifies the uncertain parameters and documents the sampled values for these parameters. The sampled values are determined by GoldSim V6.04.007 [DIRS 151202] calculations using appropriate distribution types and parameter ranges. No software development or model development was required for these calculations. The calculation of the sampled values allows parameter uncertainty to be incorporated into the rockfall and structural response calculations that support development of the seismic scenario for the
Unbiased Comparison of Sample Size Estimates From Longitudinal Structural Measures in ADNI
Holland, Dominic; McEvoy, Linda K.; Dale, Anders M.
2013-01-01
Structural changes in neuroanatomical subregions can be measured using serial magnetic resonance imaging scans, and provide powerful biomarkers for detecting and monitoring Alzheimer's disease. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has made a large database of longitudinal scans available, with one of its primary goals being to explore the utility of structural change measures for assessing treatment effects in clinical trials of putative disease-modifying therapies. Several ADNI-funded research laboratories have calculated such measures from the ADNI database and made their results publicly available. Here, using sample size estimates, we present a comparative analysis of the overall results that come from the application of each laboratory's extensive processing stream to the ADNI database. Obtaining accurate measures of change requires correcting for potential bias due to the measurement methods themselves; and obtaining realistic sample size estimates for treatment response, based on longitudinal imaging measures from natural history studies such as ADNI, requires calibrating measured change in patient cohorts with respect to longitudinal anatomical changes inherent to normal aging. We present results showing that significant longitudinal change is present in healthy control subjects who test negative for amyloid-β pathology. Therefore, sample size estimates as commonly reported from power calculations based on total structural change in patients, rather than change in patients relative to change in healthy controls, are likely to be unrealistically low for treatments targeting amyloid-related pathology. Of all the measures publicly available in ADNI, thinning of the entorhinal cortex quantified with the Quarc methodology provides the most powerful change biomarker. PMID:21830259
Ab initio spur size calculation in liquid water at room temperature
NASA Astrophysics Data System (ADS)
Muroya, Yusa; Mozumder, Asokendu
2016-07-01
An attempt was made to calculate the spur size in liquid water at room temperature from fundamental interactions. Electron trapping, elastic scattering, and positive-ion back attraction undergone in sub-excitation and sub-vibrational stages in the 100 fs time scale for thermalization were considered and included in the model. Overall diffusional broadening was estimated to be 41.2 Å, attended by the positive-ion pull back of 24.0 Å, resulting in a calculated spur size of 17.2 Å. Electron trapping is seen in competition with thermalization in the ultimate stage, which results in the trapped electron position distribution as a sum of Gaussians.
A fast algorithm for calculating an expected outbreak size on dynamic contagion networks.
Enright, Jessica; Kao, Rowland R
2016-09-01
Calculation of expected outbreak size of a simple contagion on a known contact network is a common and important epidemiological task, and is typically carried out by computationally intensive simulation. We describe an efficient exact method to calculate the expected outbreak size of a contagion on an outbreak-invariant network that is a directed and acyclic, allowing us to model all dynamically changing networks when contagion can only travel forward in time. We describe our algorithm and its use in pseudocode, as well as showing examples of its use on disease relevant, data-derived networks. PMID:27379615
7 CFR 201.43 - Size of sample.
Code of Federal Regulations, 2012 CFR
2012-01-01
... units. Coated seed for germination test only shall consist of at least 1,000 seed units. ..., Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT... of samples of agricultural seed, vegetable seed and screenings to be submitted for analysis, test,...
7 CFR 201.43 - Size of sample.
Code of Federal Regulations, 2014 CFR
2014-01-01
... units. Coated seed for germination test only shall consist of at least 1,000 seed units. ..., Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT... of samples of agricultural seed, vegetable seed and screenings to be submitted for analysis, test,...
7 CFR 201.43 - Size of sample.
Code of Federal Regulations, 2011 CFR
2011-01-01
... units. Coated seed for germination test only shall consist of at least 1,000 seed units. ..., Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT... of samples of agricultural seed, vegetable seed and screenings to be submitted for analysis, test,...
Systematic study of finite-size effects in quantum Monte Carlo calculations of real metallic systems
Azadi, Sam Foulkes, W. M. C.
2015-09-14
We present a systematic and comprehensive study of finite-size effects in diffusion quantum Monte Carlo calculations of metals. Several previously introduced schemes for correcting finite-size errors are compared for accuracy and efficiency, and practical improvements are introduced. In particular, we test a simple but efficient method of finite-size correction based on an accurate combination of twist averaging and density functional theory. Our diffusion quantum Monte Carlo results for lithium and aluminum, as examples of metallic systems, demonstrate excellent agreement between all of the approaches considered.
Theory of finite size effects for electronic quantum Monte Carlo calculations of liquids and solids
NASA Astrophysics Data System (ADS)
Holzmann, Markus; Clay, Raymond C.; Morales, Miguel A.; Tubman, Norm M.; Ceperley, David M.; Pierleoni, Carlo
2016-07-01
Concentrating on zero temperature quantum Monte Carlo calculations of electronic systems, we give a general description of the theory of finite size extrapolations of energies to the thermodynamic limit based on one- and two-body correlation functions. We introduce effective procedures, such as using the potential and wave function split up into long and short range functions to simplify the method, and we discuss how to treat backflow wave functions. Then we explicitly test the accuracy of our method to correct finite size errors on example hydrogen and helium many-body systems and show that the finite size bias can be drastically reduced for even small systems.
Naimi, Ladan J.; Collard, Flavien; Bi, Xiaotao; Lim, C. Jim; Sokhansanj, Shahab
2016-01-05
Size reduction is an unavoidable operation for preparing biomass for biofuels and bioproduct conversion. Yet, there is considerable uncertainty in power input requirement and the uniformity of ground biomass. Considerable gains are possible if the required power input for a size reduction ratio is estimated accurately. In this research three well-known mechanistic equations attributed to Rittinger, Kick, and Bond available for predicting energy input for grinding pine wood chips were tested against experimental grinding data. Prior to testing, samples of pine wood chips were conditioned to 11.7% wb, moisture content. The wood chips were successively ground in a hammer millmore » using screen sizes of 25.4 mm, 10 mm, 6.4 mm, and 3.2 mm. The input power and the flow of material into the grinder were recorded continuously. The recorded power input vs. mean particle size showed that the Rittinger equation had the best fit to the experimental data. The ground particle sizes were 4 to 7 times smaller than the size of installed screen. Geometric mean size of particles were calculated using two methods (1) Tyler sieves and using particle size analysis and (2) Sauter mean diameter calculated from the ratio of volume to surface that were estimated from measured length and width. The two mean diameters agreed well, pointing to the fact that either mechanical sieving or particle imaging can be used to characterize particle size. In conclusion, specific energy input to the hammer mill increased from 1.4 kWh t–1 (5.2 J g–1) for large 25.1-mm screen to 25 kWh t–1 (90.4 J g–1) for small 3.2-mm screen.« less
Enhanced Z-LDA for Small Sample Size Training in Brain-Computer Interface Systems
Gao, Dongrui; Zhang, Rui; Liu, Tiejun; Li, Fali; Ma, Teng; Lv, Xulin; Li, Peiyang; Yao, Dezhong; Xu, Peng
2015-01-01
Background. Usually the training set of online brain-computer interface (BCI) experiment is small. For the small training set, it lacks enough information to deeply train the classifier, resulting in the poor classification performance during online testing. Methods. In this paper, on the basis of Z-LDA, we further calculate the classification probability of Z-LDA and then use it to select the reliable samples from the testing set to enlarge the training set, aiming to mine the additional information from testing set to adjust the biased classification boundary obtained from the small training set. The proposed approach is an extension of previous Z-LDA and is named enhanced Z-LDA (EZ-LDA). Results. We evaluated the classification performance of LDA, Z-LDA, and EZ-LDA on simulation and real BCI datasets with different sizes of training samples, and classification results showed EZ-LDA achieved the best classification performance. Conclusions. EZ-LDA is promising to deal with the small sample size training problem usually existing in online BCI system. PMID:26550023
40 CFR Appendix III to Part 600 - Sample Fuel Economy Label Calculation
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 30 2014-07-01 2014-07-01 false Sample Fuel Economy Label Calculation...) ENERGY POLICY FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. III Appendix III to Part 600—Sample Fuel Economy Label Calculation Suppose that a manufacturer called...
40 CFR Appendix III to Part 600 - Sample Fuel Economy Label Calculation
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 31 2012-07-01 2012-07-01 false Sample Fuel Economy Label Calculation...) ENERGY POLICY FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. III Appendix III to Part 600—Sample Fuel Economy Label Calculation Suppose that a manufacturer called...
40 CFR Appendix III to Part 600 - Sample Fuel Economy Label Calculation
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 30 2011-07-01 2011-07-01 false Sample Fuel Economy Label Calculation...) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. III Appendix III to Part 600—Sample Fuel Economy Label Calculation Suppose that a manufacturer called...
40 CFR Appendix III to Part 600 - Sample Fuel Economy Label Calculation
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 31 2013-07-01 2013-07-01 false Sample Fuel Economy Label Calculation...) ENERGY POLICY FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. III Appendix III to Part 600—Sample Fuel Economy Label Calculation Suppose that a manufacturer called...
40 CFR Appendix III to Part 600 - Sample Fuel Economy Label Calculation
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sample Fuel Economy Label Calculation...) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. III Appendix III to Part 600—Sample Fuel Economy Label Calculation Suppose that a manufacturer called...
Air and smear sample calculational tool for Fluor Hanford Radiological control
BAUMANN, B.L.
2003-09-24
A spreadsheet calculation tool was developed to automate the calculations performed for determining the concentration of airborne radioactivity and smear counting as outlined in HNF-13536, Section 5.2.7, Analyzing Air and smear Samples. This document reports on the design and testing of the calculation tool.
Geoscience Education Research Methods: Thinking About Sample Size
NASA Astrophysics Data System (ADS)
Slater, S. J.; Slater, T. F.; CenterAstronomy; Physics Education Research
2011-12-01
Geoscience education research is at a critical point in which conditions are sufficient to propel our field forward toward meaningful improvements in geosciences education practices. Our field has now reached a point where the outcomes of our research is deemed important to endusers and funding agencies, and where we now have a large number of scientists who are either formally trained in geosciences education research, or who have dedicated themselves to excellence in this domain. At this point we now must collectively work through our epistemology, our rules of what methodologies will be considered sufficiently rigorous, and what data and analysis techniques will be acceptable for constructing evidence. In particular, we have to work out our answer to that most difficult of research questions: "How big should my 'N' be??" This paper presents a very brief answer to that question, addressing both quantitative and qualitative methodologies. Research question/methodology alignment, effect size and statistical power will be discussed, in addition to a defense of the notion that bigger is not always better.
A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models
ERIC Educational Resources Information Center
Jackson, Dennis L.; Voth, Jennifer; Frey, Marc P.
2013-01-01
Determining an appropriate sample size for use in latent variable modeling techniques has presented ongoing challenges to researchers. In particular, small sample sizes are known to present concerns over sampling error for the variances and covariances on which model estimation is based, as well as for fit indexes and convergence failures. The…
Sample Size in Differential Item Functioning: An Application of Hierarchical Linear Modeling
ERIC Educational Resources Information Center
Acar, Tulin
2011-01-01
The purpose of this study is to examine the number of DIF items detected by HGLM at different sample sizes. Eight different sized data files have been composed. The population of the study is 798307 students who had taken the 2006 OKS Examination. 10727 students of 798307 are chosen by random sampling method as the sample of the study. Turkish,…
Sample size estimation for the van Elteren test--a stratified Wilcoxon-Mann-Whitney test.
Zhao, Yan D
2006-08-15
The van Elteren test is a type of stratified Wilcoxon-Mann-Whitney test for comparing two treatments accounting for strata. In this paper, we study sample size estimation methods for the asymptotic version of the van Elteren test, assuming that the stratum fractions (ratios of each stratum size to the total sample size) and the treatment fractions (ratios of each treatment size to the stratum size) are known in the study design. In particular, we develop three large-sample sample size estimation methods and present a real data example to illustrate the necessary information in the study design phase in order to apply the methods. Simulation studies are conducted to compare the performance of the methods and recommendations are made for method choice. Finally, sample size estimation for the van Elteren test when the stratum fractions are unknown is also discussed.
Sample size estimation for the van Elteren test--a stratified Wilcoxon-Mann-Whitney test.
Zhao, Yan D
2006-08-15
The van Elteren test is a type of stratified Wilcoxon-Mann-Whitney test for comparing two treatments accounting for strata. In this paper, we study sample size estimation methods for the asymptotic version of the van Elteren test, assuming that the stratum fractions (ratios of each stratum size to the total sample size) and the treatment fractions (ratios of each treatment size to the stratum size) are known in the study design. In particular, we develop three large-sample sample size estimation methods and present a real data example to illustrate the necessary information in the study design phase in order to apply the methods. Simulation studies are conducted to compare the performance of the methods and recommendations are made for method choice. Finally, sample size estimation for the van Elteren test when the stratum fractions are unknown is also discussed. PMID:16372389
40 CFR 761.243 - Standard wipe sample method and size.
Code of Federal Regulations, 2014 CFR
2014-07-01
... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas... June 23, 1987 and revised on April 18, 1991. This document is available on EPA's Web site at...
40 CFR 761.243 - Standard wipe sample method and size.
Code of Federal Regulations, 2013 CFR
2013-07-01
... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas... June 23, 1987 and revised on April 18, 1991. This document is available on EPA's Web site at...
40 CFR 761.243 - Standard wipe sample method and size.
Code of Federal Regulations, 2011 CFR
2011-07-01
... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas... June 23, 1987 and revised on April 18, 1991. This document is available on EPA's Web site at...
40 CFR 761.243 - Standard wipe sample method and size.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas... June 23, 1987 and revised on April 18, 1991. This document is available on EPA's Web site at...
40 CFR 761.243 - Standard wipe sample method and size.
Code of Federal Regulations, 2012 CFR
2012-07-01
... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.243 Standard wipe sample method and size. (a) Collect a surface sample from a natural gas... June 23, 1987 and revised on April 18, 1991. This document is available on EPA's Web site at...
Ranjard, Lionel; Lejon, David P H; Mougel, Christophe; Schehrer, Lucie; Merdinoglu, Didier; Chaussod, Rémi
2003-11-01
Assessing soil microbial community structure by the use of molecular techniques requires a satisfactory sampling strategy that takes into account the high microbial diversity and the heterogeneous distribution of microorganisms in the soil matrix. The influence of the sample size of three different soil types (sand, silt and clay soils) on the DNA yield and analysis of bacterial and fungal community structure were investigated. Six sample sizes from 0.125 g to 4 g were evaluated. The genetic community structure was assessed by automated ribosomal intergenic spacer analysis (A-RISA fingerprint). Variations between bacterial (B-ARISA) and fungal (F-ARISA) community structure were quantified by using principal component analysis (PCA). DNA yields were positively correlated with the sample size for the sandy and silty soils, suggesting an influence of the sample size on DNA recovery, whereas no correlation was observed in the clay soil. B-ARISA was shown to be consistent between the different sample sizes for each soil type indicating that the sampling procedure has no influence on the assessment of bacterial community structure. On the contrary for F-ARISA profiles, strong variations were observed between replicates of the smaller samples (<1 g). Principal component analysis analysis revealed that sampling aliquots of soil > or =1 g are required to obtain robust and reproducible fingerprinting analysis of the genetic structure of fungal communities. However, the smallest samples could be adequate for the detection of minor populations masked by dominant ones in larger samples. The sampling strategy should therefore be different according to the objectives: rather large soil samples (> or =1 g) for a global description of the genetic community structure, or a large number of small soil samples for a more complete inventory of microbial diversity.
Evaluation of design flood estimates with respect to sample size
NASA Astrophysics Data System (ADS)
Kobierska, Florian; Engeland, Kolbjorn
2016-04-01
Estimation of design floods forms the basis for hazard management related to flood risk and is a legal obligation when building infrastructure such as dams, bridges and roads close to water bodies. Flood inundation maps used for land use planning are also produced based on design flood estimates. In Norway, the current guidelines for design flood estimates give recommendations on which data, probability distribution, and method to use dependent on length of the local record. If less than 30 years of local data is available, an index flood approach is recommended where the local observations are used for estimating the index flood and regional data are used for estimating the growth curve. For 30-50 years of data, a 2 parameter distribution is recommended, and for more than 50 years of data, a 3 parameter distribution should be used. Many countries have national guidelines for flood frequency estimation, and recommended distributions include the log Pearson II, generalized logistic and generalized extreme value distributions. For estimating distribution parameters, ordinary and linear moments, maximum likelihood and Bayesian methods are used. The aim of this study is to r-evaluate the guidelines for local flood frequency estimation. In particular, we wanted to answer the following questions: (i) Which distribution gives the best fit to the data? (ii) Which estimation method provides the best fit to the data? (iii) Does the answer to (i) and (ii) depend on local data availability? To answer these questions we set up a test bench for local flood frequency analysis using data based cross-validation methods. The criteria were based on indices describing stability and reliability of design flood estimates. Stability is used as a criterion since design flood estimates should not excessively depend on the data sample. The reliability indices describe to which degree design flood predictions can be trusted.
Yu, Xiao; Xiahui, Tang; Yingxiong, Qin; Hao, Peng; Wei, Wang
2012-11-01
Band-limited angular spectrum (BLAS) methods can be used for simulating the diffractional propagation in the near field, the far field, the tilted system, and the nonparaxial system. However, it does not allow free sample interval on the output calculation window. In this paper, an improved BLAS method is proposed. This new algorithm permits a selective scaling of observation window size and sample number on the observation plane. The method is based on the linear convolution, which can be calculated by fast Fourier transform effectively.
ERIC Educational Resources Information Center
Eisenberg, Sarita L.; Guo, Ling-Yu
2015-01-01
Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…
Sampling bee communities using pan traps: alternative methods increase sample size
Technology Transfer Automated Retrieval System (TEKTRAN)
Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...
NASA Astrophysics Data System (ADS)
Bormann, H.
2006-09-01
This paper analyses the effect of spatial input data resolution on the simulated effects of regional scale landuse scenarios using the TOPLATS model. A data set of 25 m resolution of the central German Dill catchment (693 km2) and three different landuse scenarios are used for the investigation. Landuse scenarios in this study are field size scenarios, and depending on a specific target field size (0.5 ha, 1.5 ha and 5.0 ha) landuse is determined by optimising economic outcome of agricultural used areas and forest. After an aggregation of digital elevation model, soil map, current landuse and landuse scenarios to 50 m, 75 m, 100 m, 150 m, 200 m, 300 m, 500 m, 1 km and 2 km, water balances and water flow components for a 20 years time period are calculated for the entire Dill catchment as well as for 3 subcatchments without any recalibration. Additionally water balances based on the three landuse scenarios as well as changes between current conditions and scenarios are calculated. The study reveals that both model performance measures (for current landuse) as well as water balances (for current landuse and landuse scenarios) almost remain constant for most of the aggregation steps for all investigated catchments. Small deviations are detected at the resolution of 50 m to 500 m, while significant differences occur at the resolution of 1 km and 2 km which can be explained by changes in the statistics of the input data. Calculating the scenario effects based on increasing grid sizes yields similar results. However, the change effects react more sensitive to data aggregation than simple water balance calculations. Increasing deviations between simulations based on small grid sizes and simulations using grid sizes of 300 m and more are observed. Summarizing, this study indicates that an aggregation of input data for the calculation of regional water balances using TOPLATS type models does not lead to significant errors up to a resolution of 500 m. Focusing on scenario
Distribution of the two-sample t-test statistic following blinded sample size re-estimation.
Lu, Kaifeng
2016-05-01
We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd.
Dziak, John J.; Lanza, Stephanie T.; Tan, Xianming
2014-01-01
Selecting the number of different classes which will be assumed to exist in the population is an important step in latent class analysis (LCA). The bootstrap likelihood ratio test (BLRT) provides a data-driven way to evaluate the relative adequacy of a (K −1)-class model compared to a K-class model. However, very little is known about how to predict the power or the required sample size for the BLRT in LCA. Based on extensive Monte Carlo simulations, we provide practical effect size measures and power curves which can be used to predict power for the BLRT in LCA given a proposed sample size and a set of hypothesized population parameters. Estimated power curves and tables provide guidance for researchers wishing to size a study to have sufficient power to detect hypothesized underlying latent classes. PMID:25328371
40 CFR 761.286 - Sample size and procedure for collecting a sample.
Code of Federal Regulations, 2010 CFR
2010-07-01
... (CONTINUED) TOXIC SUBSTANCES CONTROL ACT POLYCHLORINATED BIPHENYLS (PCBs) MANUFACTURING, PROCESSING, DISTRIBUTION IN COMMERCE, AND USE PROHIBITIONS Sampling To Verify Completion of Self-Implementing Cleanup...
XAFSmass: a program for calculating the optimal mass of XAFS samples
NASA Astrophysics Data System (ADS)
Klementiev, K.; Chernikov, R.
2016-05-01
We present a new implementation of the XAFSmass program that calculates the optimal mass of XAFS samples. It has several improvements as compared to the old Windows based program XAFSmass: 1) it is truly platform independent, as provided by Python language, 2) it has an improved parser of chemical formulas that enables parentheses and nested inclusion-to-matrix weight percentages. The program calculates the absorption edge height given the total optical thickness, operates with differently determined sample amounts (mass, pressure, density or sample area) depending on the aggregate state of the sample and solves the inverse problem of finding the elemental composition given the experimental absorption edge jump and the chemical formula.
NASA Astrophysics Data System (ADS)
Lai, B. W.; Wu, Z. X.; Dong, X. P.; Lu, D.; Tao, S. C.
2016-07-01
We proposed a novel method to calculate the similarity between samples with only small differences at unknown and specific positions in their Raman spectra, using a moving interval window scanning across the whole Raman spectra. Two ABS plastic samples, one with and the other without flame retardant, were tested in the experiment. Unlike the traditional method in which the similarity is calculated based on the whole spectrum, we do the calculation by using a window to cut out a certain segment from Raman spectra, each at a time as the window moves across the entire spectrum range. By our method, a curve of similarity versus wave number is obtained. And the curve shows a large change where the partial spectra of the two samples is different. Thus, the new similarity calculation method identifies samples with tiny difference in their Raman spectra better.
ERIC Educational Resources Information Center
Andrews, Steven S.
2004-01-01
The mathematics behind the average absorption cross-section is exactly one third of the maximum value described. The goal is to calculate experimental observables, or other properties of bulk sample, in terms of microscopic molecular parameters.
Using the Student's "t"-Test with Extremely Small Sample Sizes
ERIC Educational Resources Information Center
de Winter, J. C .F.
2013-01-01
Researchers occasionally have to work with an extremely small sample size, defined herein as "N" less than or equal to 5. Some methodologists have cautioned against using the "t"-test when the sample size is extremely small, whereas others have suggested that using the "t"-test is feasible in such a case. The present…
Sample Size for Confidence Interval of Covariate-Adjusted Mean Difference
ERIC Educational Resources Information Center
Liu, Xiaofeng Steven
2010-01-01
This article provides a way to determine adequate sample size for the confidence interval of covariate-adjusted mean difference in randomized experiments. The standard error of adjusted mean difference depends on covariate variance and balance, which are two unknown quantities at the stage of planning sample size. If covariate observations are…
ERIC Educational Resources Information Center
Wolf, Erika J.; Harrington, Kelly M.; Clark, Shaunna L.; Miller, Mark W.
2013-01-01
Determining sample size requirements for structural equation modeling (SEM) is a challenge often faced by investigators, peer reviewers, and grant writers. Recent years have seen a large increase in SEMs in the behavioral science literature, but consideration of sample size requirements for applied SEMs often relies on outdated rules-of-thumb.…
Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis
ERIC Educational Resources Information Center
Marin-Martinez, Fulgencio; Sanchez-Meca, Julio
2010-01-01
Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…
GPU-based ultra-fast dose calculation using a finite size pencil beam model
NASA Astrophysics Data System (ADS)
Gu, Xuejun; Choi, Dongju; Men, Chunhua; Pan, Hubert; Majumdar, Amitava; Jiang, Steve B.
2009-10-01
Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.
Thermomagnetic behavior of magnetic susceptibility - heating rate and sample size effects
NASA Astrophysics Data System (ADS)
Jordanova, Diana; Jordanova, Neli
2015-12-01
Thermomagnetic analysis of magnetic susceptibility k(T) was carried out for a number of natural powder materials from soils, baked clay and anthropogenic dust samples using fast (11oC/min) and slow (6.5oC/min) heating rates available in the furnace of Kappabridge KLY2 (Agico). Based on the additional data for mineralogy, grain size and magnetic properties of the studied samples, behaviour of k(T) cycles and the observed differences in the curves for fast and slow heating rate are interpreted in terms of mineralogical transformations and Curie temperatures (Tc). The effect of different sample size is also explored, using large volume and small volume of powder material. It is found that soil samples show enhanced information on mineralogical transformations and appearance of new strongly magnetic phases when using fast heating rate and large sample size. This approach moves the transformation at higher temperature, but enhances the amplitude of the signal of newly created phase. Large sample size gives prevalence of the local micro- environment, created by evolving gases, released during transformations. The example from archeological brick reveals the effect of different sample sizes on the observed Curie temperatures on heating and cooling curves, when the magnetic carrier is substituted magnetite (Mn0.2Fe2.70O4). Large sample size leads to bigger differences in Tcs on heating and cooling, while small sample size results in similar Tcs for both heating rates.
40 CFR 600.211-08 - Sample calculation of fuel economy values for labeling.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 30 2011-07-01 2011-07-01 false Sample calculation of fuel economy... AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Procedures for Calculating Fuel Economy and Carbon-Related Exhaust Emission Values for 1977 and Later...
40 CFR 600.211-08 - Sample calculation of fuel economy values for labeling.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sample calculation of fuel economy... AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Fuel Economy Regulations for 1977 and Later Model Year Automobiles-Procedures for Calculating Fuel...
7 CFR 51.308 - Methods of sampling and calculation of percentages.
Code of Federal Regulations, 2012 CFR
2012-01-01
..., CERTIFICATION, AND STANDARDS) United States Standards for Grades of Apples Methods of Sampling and Calculation... where the minimum diameter of the smallest apple does not vary more than 1/2 inch from the minimum diameter of the largest apple, percentages shall be calculated on the basis of count. (b) In all...
7 CFR 51.308 - Methods of sampling and calculation of percentages.
Code of Federal Regulations, 2010 CFR
2010-01-01
..., CERTIFICATION, AND STANDARDS) United States Standards for Grades of Apples Methods of Sampling and Calculation... where the minimum diameter of the smallest apple does not vary more than 1/2 inch from the minimum diameter of the largest apple, percentages shall be calculated on the basis of count. (b) In all...
7 CFR 51.308 - Methods of sampling and calculation of percentages.
Code of Federal Regulations, 2011 CFR
2011-01-01
..., CERTIFICATION, AND STANDARDS) United States Standards for Grades of Apples Methods of Sampling and Calculation... where the minimum diameter of the smallest apple does not vary more than 1/2 inch from the minimum diameter of the largest apple, percentages shall be calculated on the basis of count. (b) In all...
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. PMID:16676681
Ando, Yuki; Hamasaki, Toshimitsu; Evans, Scott R.; Asakura, Koko; Sugimoto, Tomoyuki; Sozu, Takashi; Ohno, Yuko
2015-01-01
The effects of interventions are multi-dimensional. Use of more than one primary endpoint offers an attractive design feature in clinical trials as they capture more complete characterization of the effects of an intervention and provide more informative intervention comparisons. For these reasons, multiple primary endpoints have become a common design feature in many disease areas such as oncology, infectious disease, and cardiovascular disease. More specifically in medical product development, multiple endpoints are utilized as co-primary to evaluate the effect of the new interventions. Although methodologies to address continuous co-primary endpoints are well-developed, methodologies for binary endpoints are limited. In this paper, we describe power and sample size determination for clinical trials with multiple correlated binary endpoints, when relative risks are evaluated as co-primary. We consider a scenario where the objective is to evaluate evidence for superiority of a test intervention compared with a control intervention, for all of the relative risks. We discuss the normal approximation methods for power and sample size calculations and evaluate how the required sample size, power and Type I error vary as a function of the correlations among the endpoints. Also we discuss a simple, but conservative procedure for appropriate sample size calculation. We then extend the methods allowing for interim monitoring using group-sequential methods. PMID:26167243
Brera, Carlo; De Santis, Barbara; Prantera, Elisabetta; Debegnach, Francesca; Pannunzi, Elena; Fasano, Floriana; Berdini, Clara; Slate, Andrew B; Miraglia, Marina; Whitaker, Thomas B
2010-08-11
Use of proper sampling methods throughout the agri-food chain is crucial when it comes to effectively detecting contaminants in foods and feeds. The objective of the study was to estimate the performance of sampling plan designs to determine aflatoxin B(1) (AFB(1)) contamination in corn fields. A total of 840 ears were selected from a corn field suspected of being contaminated with aflatoxin. The mean and variance among the aflatoxin values for each ear were 10.6 mug/kg and 2233.3, respectively. The variability and confidence intervals associated with sample means of a given size could be predicted using an equation associated with the normal distribution. Sample sizes of 248 and 674 ears would be required to estimate the true field concentration of 10.6 mug/kg within +/-50 and +/-30%, respectively. Using the distribution information from the study, operating characteristic curves were developed to show the performance of various sampling plan designs.
Sample Size under Inverse Negative Binomial Group Testing for Accuracy in Parameter Estimation
Montesinos-López, Osval Antonio; Montesinos-López, Abelardo; Crossa, José; Eskridge, Kent
2012-01-01
Background The group testing method has been proposed for the detection and estimation of genetically modified plants (adventitious presence of unwanted transgenic plants, AP). For binary response variables (presence or absence), group testing is efficient when the prevalence is low, so that estimation, detection, and sample size methods have been developed under the binomial model. However, when the event is rare (low prevalence <0.1), and testing occurs sequentially, inverse (negative) binomial pooled sampling may be preferred. Methodology/Principal Findings This research proposes three sample size procedures (two computational and one analytic) for estimating prevalence using group testing under inverse (negative) binomial sampling. These methods provide the required number of positive pools (), given a pool size (k), for estimating the proportion of AP plants using the Dorfman model and inverse (negative) binomial sampling. We give real and simulated examples to show how to apply these methods and the proposed sample-size formula. The Monte Carlo method was used to study the coverage and level of assurance achieved by the proposed sample sizes. An R program to create other scenarios is given in Appendix S2. Conclusions The three methods ensure precision in the estimated proportion of AP because they guarantee that the width (W) of the confidence interval (CI) will be equal to, or narrower than, the desired width (), with a probability of . With the Monte Carlo study we found that the computational Wald procedure (method 2) produces the more precise sample size (with coverage and assurance levels very close to nominal values) and that the samples size based on the Clopper-Pearson CI (method 1) is conservative (overestimates the sample size); the analytic Wald sample size method we developed (method 3) sometimes underestimated the optimum number of pools. PMID:22457714
Calculation of the mean circle size does not circumvent the bottleneck of crowding.
Banno, Hayaki; Saiki, Jun
2012-10-22
Visually, we can extract a statistical summary of sets of elements efficiently. However, our visual system has a severe limitation in that the ability to recognize an object is remarkably impaired when it is surrounded by other objects. The goal of this study was to investigate whether the crowding effect obstructs the calculation of the mean size of objects. First, we verified that the crowding effect occurs when comparing the sizes of circles (Experiment 1). Next, we manipulated the distances between circles and measured the sensitivity when circles were on or off the limitation of crowding (Experiment 2). Participants were asked to compare the mean sizes of the circles in the left and right visual fields and to judge which was larger. Participants' sensitivity to mean size difference was lower when the circles were located in the nearer distance. Finally, we confirmed that crowding is responsible for the observed results by showing that displays without a crowded object eliminated the effects (Experiment 3). Our results indicate that the statistical information of size does not circumvent the bottleneck of crowding.
7 CFR 51.308 - Methods of sampling and calculation of percentages.
Code of Federal Regulations, 2014 CFR
2014-01-01
... Grades of Apples Methods of Sampling and Calculation of Percentages § 51.308 Methods of sampling and... weigh ten pounds or less, or in any container where the minimum diameter of the smallest apple does not vary more than 1/2 inch from the minimum diameter of the largest apple, percentages shall be...
7 CFR 51.308 - Methods of sampling and calculation of percentages.
Code of Federal Regulations, 2013 CFR
2013-01-01
... Grades of Apples Methods of Sampling and Calculation of Percentages § 51.308 Methods of sampling and... weigh ten pounds or less, or in any container where the minimum diameter of the smallest apple does not vary more than 1/2 inch from the minimum diameter of the largest apple, percentages shall be...
Guo, Ling-Yu
2015-01-01
Purpose The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method Language samples were elicited by asking forty 3-year-old children with varying language skills to talk about pictures in response to prompts. PGU scores were computed for each of two 7-picture sets and for the full set of 15 pictures. Results PGU scores for the two 7-picture sets did not differ significantly from, and were highly correlated with, PGU scores for the full set and with each other. Agreement for making pass–fail decisions between each 7-picture set and the full set and between the two 7-picture sets ranged from 80% to 100%. Conclusion The current study suggests that the PGU measure is robust enough that it can be computed on the basis of 7, at least in 3-year-old children whose language samples were elicited using similar procedures. PMID:25615691
Teoh, Wei Lin; Khoo, Michael B C; Teh, Sin Yin
2013-01-01
Designs of the double sampling (DS) X chart are traditionally based on the average run length (ARL) criterion. However, the shape of the run length distribution changes with the process mean shifts, ranging from highly skewed when the process is in-control to almost symmetric when the mean shift is large. Therefore, we show that the ARL is a complicated performance measure and that the median run length (MRL) is a more meaningful measure to depend on. This is because the MRL provides an intuitive and a fair representation of the central tendency, especially for the rightly skewed run length distribution. Since the DS X chart can effectively reduce the sample size without reducing the statistical efficiency, this paper proposes two optimal designs of the MRL-based DS X chart, for minimizing (i) the in-control average sample size (ASS) and (ii) both the in-control and out-of-control ASSs. Comparisons with the optimal MRL-based EWMA X and Shewhart X charts demonstrate the superiority of the proposed optimal MRL-based DS X chart, as the latter requires a smaller sample size on the average while maintaining the same detection speed as the two former charts. An example involving the added potassium sorbate in a yoghurt manufacturing process is used to illustrate the effectiveness of the proposed MRL-based DS X chart in reducing the sample size needed. PMID:23935873
Teoh, Wei Lin; Khoo, Michael B. C.; Teh, Sin Yin
2013-01-01
Designs of the double sampling (DS) chart are traditionally based on the average run length (ARL) criterion. However, the shape of the run length distribution changes with the process mean shifts, ranging from highly skewed when the process is in-control to almost symmetric when the mean shift is large. Therefore, we show that the ARL is a complicated performance measure and that the median run length (MRL) is a more meaningful measure to depend on. This is because the MRL provides an intuitive and a fair representation of the central tendency, especially for the rightly skewed run length distribution. Since the DS chart can effectively reduce the sample size without reducing the statistical efficiency, this paper proposes two optimal designs of the MRL-based DS chart, for minimizing (i) the in-control average sample size (ASS) and (ii) both the in-control and out-of-control ASSs. Comparisons with the optimal MRL-based EWMA and Shewhart charts demonstrate the superiority of the proposed optimal MRL-based DS chart, as the latter requires a smaller sample size on the average while maintaining the same detection speed as the two former charts. An example involving the added potassium sorbate in a yoghurt manufacturing process is used to illustrate the effectiveness of the proposed MRL-based DS chart in reducing the sample size needed. PMID:23935873
NASA Technical Reports Server (NTRS)
Johnson, Kenneth L.; White, K. Preston, Jr.
2012-01-01
The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.
Parameter Estimation with Small Sample Size: A Higher-Order IRT Model Approach
ERIC Educational Resources Information Center
de la Torre, Jimmy; Hong, Yuan
2010-01-01
Sample size ranks as one of the most important factors that affect the item calibration task. However, due to practical concerns (e.g., item exposure) items are typically calibrated with much smaller samples than what is desired. To address the need for a more flexible framework that can be used in small sample item calibration, this article…
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.
NASA Astrophysics Data System (ADS)
Aleksandrov, V. D.; Pokyntelytsia, O. A.
2016-09-01
An alternative approach to calculating critical sizes l k of nucleation centers and work A k of their formation upon crystallization from a supercooled melt by analyzing the variation in the Gibbs energy during the phase transformation is considered. Unlike the classical variant, it is proposed that the transformation entropy be associated not with melting temperature T L but with temperature T < T L at which the nucleation of crystals occurs. New equations for l k and A k are derived. Based on the results from calculating these quantities for a series of compounds, it is shown that this approach is unbiased and it is possible to eliminate known conflicts in analyzing these parameters in the classical interpretation.
Calculation of the radionuclides in PWR spent fuel samples for SFR experiment planning.
Naegeli, Robert Earl
2004-06-01
This report documents the calculation of radionuclide content in the pressurized water reactor (PWR) spent fuel samples planned for use in the Spent Fuel Ratio (SPR) Experiments at Sandia National Laboratories, Albuquerque, New Mexico (SNL) to aid in experiment planning. The calculation methods using the ORIGEN2 and ORIGEN-ARP computer codes and the input modeling of the planned PWR spent fuel from the H. B. Robinson and the Surry nuclear power plants are discussed. The safety hazards for the calculated nuclide inventories in the spent fuel samples are characterized by the potential airborne dose and by the portion of the nuclear facility hazard category 2 and 3 thresholds that the experiment samples would present. In addition, the gamma ray photon energy source for the nuclide inventories is tabulated to facilitate subsequent calculation of the direct and shielded dose rates expected from the samples. The relative hazards of the high burnup 72 gigawatt-day per metric ton of uranium (GWd/MTU) spent fuel from H. B. Robinson and the medium burnup 36 GWd/MTU spent fuel from Surry are compared against a parametric calculation of various fuel burnups to assess the potential for higher hazard PWR fuel samples.
NASA Technical Reports Server (NTRS)
Bice, K.; Clement, S. C.
1981-01-01
X-ray diffraction and spectroscopy were used to investigate the mineralogical and chemical properties of the Calvert, Ball Old Mine, Ball Martin, and Jordan Sediments. The particle size distribution and index of refraction of each sample were determined. The samples are composed primarily of quartz, kaolinite, and illite. The clay minerals are most abundant in the finer particle size fractions. The chemical properties of the four samples are similar. The Calvert sample is most notably different in that it contains a relatively high amount of iron. The dominant particle size fraction in each sample is silt, with lesser amounts of clay and sand. The indices of refraction of the sediments are the same with the exception of the Calvert sample which has a slightly higher value.
Ramírez, Cristian; Young, Ashley; James, Bryony; Aguilera, José M
2010-10-01
Quantitative analysis of food structure is commonly obtained by image analysis of a small portion of the material that may not be the representative of the whole sample. In order to quantify structural parameters (air cells) of 2 types of bread (bread and bagel) the concept of representative volume element (RVE) was employed. The RVE for bread, bagel, and gelatin-gel (used as control) was obtained from the relationship between sample size and the coefficient of variation, calculated from the apparent Young's modulus measured on 25 replicates. The RVE was obtained when the coefficient of variation for different sample sizes converged to a constant value. In the 2 types of bread tested, the tendency of the coefficient of variation was to decrease as the sample size increased, while in the homogeneous gelatin-gel, it remained always constant around 2.3% to 2.4%. The RVE resulted to be cubes with sides of 45 mm for bread, 20 mm for bagels, and 10 mm for gelatin-gel (smallest sample tested). The quantitative image analysis as well as visual observation demonstrated that bread presented the largest dispersion of air-cell sizes. Moreover, both the ratio of maximum air-cell area/image area and maximum air-cell height/image height were greater for bread (values of 0.05 and 0.30, respectively) than for bagels (0.03 and 0.20, respectively). Therefore, the size and the size variation of air cells present in the structure determined the size of the RVE. It was concluded that RVE is highly dependent on the heterogeneity of the structure of the types of baked products.
Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology
Vavrek, Matthew J.
2015-01-01
Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes. PMID:25780770
König, Gerhard; Miller, Benjamin T; Boresch, Stefan; Wu, Xiongwu; Brooks, Bernard R
2012-10-01
One of the key requirements for the accurate calculation of free energy differences is proper sampling of conformational space. Especially in biological applications, molecular dynamics simulations are often confronted with rugged energy surfaces and high energy barriers, leading to insufficient sampling and, in turn, poor convergence of the free energy results. In this work, we address this problem by employing enhanced sampling methods. We explore the possibility of using self-guided Langevin dynamics (SGLD) to speed up the exploration process in free energy simulations. To obtain improved free energy differences from such simulations, it is necessary to account for the effects of the bias due to the guiding forces. We demonstrate how this can be accomplished for the Bennett's acceptance ratio (BAR) and the enveloping distribution sampling (EDS) methods. While BAR is considered among the most efficient methods available for free energy calculations, the EDS method developed by Christ and van Gunsteren is a promising development that reduces the computational costs of free energy calculations by simulating a single reference state. To evaluate the accuracy of both approaches in connection with enhanced sampling, EDS was implemented in CHARMM. For testing, we employ benchmark systems with analytical reference results and the mutation of alanine to serine. We find that SGLD with reweighting can provide accurate results for BAR and EDS where conventional molecular dynamics simulations fail. In addition, we compare the performance of EDS with other free energy methods. We briefly discuss the implications of our results and provide practical guidelines for conducting free energy simulations with SGLD.
Comparison of k0-NAA measurement results with calculated uncertainties for reference samples
NASA Astrophysics Data System (ADS)
Smodiš, B.; Bučar, T.
2010-10-01
Standard samples of well-defined geometry containing accurately known amounts of Co, Fe, Gd, Mo, Nd, Sb, Se, W, Zn and Zr were prepared and assayed using k0-based neutron activation analysis ( k0-NAA). Measurement results for six independent determinations of each standard spiked sample were evaluated and compared to calculated uncertainties using the computer program ERON, which computes uncertainty propagation factors from the relevant formulae and calculates the overall uncertainty following the internationally recommended approach. The calculated relative expanded uncertainties U ( k=2), which ranged from 6 to 11% for particular nuclides/gamma-lines agreed well with the measurements results thus proving the correctness of the applied approach. One of the important measures to further reduce uncertainties in the k0-NAA measurements is to review and re-determine more accurately specific nuclear constants involved in the relevant calculations.
Calculation of Collective Variable-based PMF by Combining WHAM with Umbrella Sampling
NASA Astrophysics Data System (ADS)
Xu, Wei-Xin; Li, Yang; Zhang, John Z. H.
2012-06-01
Potential of mean force (PMF) with respect to localized reaction coordinates (RCs) such as distance is often applied to evaluate the free energy profile along the reaction pathway for complex molecular systems. However, calculation of PMF as a function of global RCs is still a challenging and important problem in computational biology. We examine the combined use of the weighted histogram analysis method and the umbrella sampling method for the calculation of PMF as a function of a global RC from the coarse-grained Langevin dynamics simulations for a model protein. The method yields the folding free energy profile projected onto a global RC, which is in accord with benchmark results. With this method rare global events would be sufficiently sampled because the biased potential can be used for restricting the global conformation to specific regions during free energy calculations. The strategy presented can also be utilized in calculating the global intra- and intermolecular PMF at more detailed levels.
NASA Astrophysics Data System (ADS)
Zan, Jinbo; Fang, Xiaomin; Yang, Shengli; Yan, Maodu
2015-01-01
studies demonstrate that particle size separation based on gravitational settling and detailed rock magnetic measurements of the resulting fractionated samples constitutes an effective approach to evaluating the relative contributions of pedogenic and detrital components in the loess and paleosol sequences on the Chinese Loess Plateau. So far, however, similar work has not been undertaken on the loess deposits in Central Asia. In this paper, 17 loess and paleosol samples from three representative loess sections in Central Asia were separated into four grain size fractions, and then systematic rock magnetic measurements were made on the fractions. Our results demonstrate that the content of the <4 μm fraction in the Central Asian loess deposits is relatively low and that the samples generally have a unimodal particle distribution with a peak in the medium-coarse silt range. We find no significant difference between the particle size distributions obtained by the laser diffraction and the pipette and wet sieving methods. Rock magnetic studies further demonstrate that the medium-coarse silt fraction (e.g., the 20-75 μm fraction) provides the main control on the magnetic properties of the loess and paleosol samples in Central Asia. The contribution of pedogenically produced superparamagnetic (SP) and stable single-domain (SD) magnetic particles to the bulk magnetic properties is very limited. In addition, the coarsest fraction (>75 μm) exhibits the minimum values of χ, χARM, and SIRM, demonstrating that the concentrations of ferrimagnetic grains are not positively correlated with the bulk particle size in the Central Asian loess deposits.
ERIC Educational Resources Information Center
Kelley, Ken; Rausch, Joseph R.
2011-01-01
Longitudinal studies are necessary to examine individual change over time, with group status often being an important variable in explaining some individual differences in change. Although sample size planning for longitudinal studies has focused on statistical power, recent calls for effect sizes and their corresponding confidence intervals…
The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models
ERIC Educational Resources Information Center
Schoeneberger, Jason A.
2016-01-01
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
A comparison of single-sample estimators of effective population sizes from genetic marker data.
Wang, Jinliang
2016-10-01
In molecular ecology and conservation genetics studies, the important parameter of effective population size (Ne ) is increasingly estimated from a single sample of individuals taken at random from a population and genotyped at a number of marker loci. Several estimators are developed, based on the information of linkage disequilibrium (LD), heterozygote excess (HE), molecular coancestry (MC) and sibship frequency (SF) in marker data. The most popular is the LD estimator, because it is more accurate than HE and MC estimators and is simpler to calculate than SF estimator. However, little is known about the accuracy of LD estimator relative to that of SF and about the robustness of all single-sample estimators when some simplifying assumptions (e.g. random mating, no linkage, no genotyping errors) are violated. This study fills the gaps and uses extensive simulations to compare the biases and accuracies of the four estimators for different population properties (e.g. bottlenecks, nonrandom mating, haplodiploid), marker properties (e.g. linkage, polymorphisms) and sample properties (e.g. numbers of individuals and markers) and to compare the robustness of the four estimators when marker data are imperfect (with allelic dropouts). Extensive simulations show that SF estimator is more accurate, has a much wider application scope (e.g. suitable to nonrandom mating such as selfing, haplodiploid species, dominant markers) and is more robust (e.g. to the presence of linkage and genotyping errors of markers) than the other estimators. An empirical data set from a Yellowstone grizzly bear population was analysed to demonstrate the use of the SF estimator in practice.
A comparison of single-sample estimators of effective population sizes from genetic marker data.
Wang, Jinliang
2016-10-01
In molecular ecology and conservation genetics studies, the important parameter of effective population size (Ne ) is increasingly estimated from a single sample of individuals taken at random from a population and genotyped at a number of marker loci. Several estimators are developed, based on the information of linkage disequilibrium (LD), heterozygote excess (HE), molecular coancestry (MC) and sibship frequency (SF) in marker data. The most popular is the LD estimator, because it is more accurate than HE and MC estimators and is simpler to calculate than SF estimator. However, little is known about the accuracy of LD estimator relative to that of SF and about the robustness of all single-sample estimators when some simplifying assumptions (e.g. random mating, no linkage, no genotyping errors) are violated. This study fills the gaps and uses extensive simulations to compare the biases and accuracies of the four estimators for different population properties (e.g. bottlenecks, nonrandom mating, haplodiploid), marker properties (e.g. linkage, polymorphisms) and sample properties (e.g. numbers of individuals and markers) and to compare the robustness of the four estimators when marker data are imperfect (with allelic dropouts). Extensive simulations show that SF estimator is more accurate, has a much wider application scope (e.g. suitable to nonrandom mating such as selfing, haplodiploid species, dominant markers) and is more robust (e.g. to the presence of linkage and genotyping errors of markers) than the other estimators. An empirical data set from a Yellowstone grizzly bear population was analysed to demonstrate the use of the SF estimator in practice. PMID:27288989
SAMPLE AOR CALCULATION USING ANSYS FULL PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS parametric 360-degree model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric full model for the single shell tank (SST) SX to deal with asymmetry loading conditions and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (SST) SX, and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS AXISYMMETRIC PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS axisymmetric parametric model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for single shell tank (SST) SX, and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
Mayer sampling: calculation of cluster integrals using free-energy perturbation methods.
Singh, Jayant K; Kofke, David A
2004-06-01
Free-energy simulation methods are applied toward the calculation of cluster integrals that appear in diagrammatic methods of statistical mechanics. In this approach, Monte Carlo sampling is performed on a number of molecules equal to the order of the integral, and configurations are weighted according to the absolute value of the integrand. An umbrella-sampling average yields the value of the cluster integral in reference to a known integral. Virial coefficients, up to the sixth for the Lennard-Jones model and the fifth for the SPCE model of water, are calculated as a demonstration.
A margin based approach to determining sample sizes via tolerance bounds.
Newcomer, Justin T.; Freeland, Katherine Elizabeth
2013-09-01
This paper proposes a tolerance bound approach for determining sample sizes. With this new methodology we begin to think of sample size in the context of uncertainty exceeding margin. As the sample size decreases the uncertainty in the estimate of margin increases. This can be problematic when the margin is small and only a few units are available for testing. In this case there may be a true underlying positive margin to requirements but the uncertainty may be too large to conclude we have sufficient margin to those requirements with a high level of statistical confidence. Therefore, we provide a methodology for choosing a sample size large enough such that an estimated QMU uncertainty based on the tolerance bound approach will be smaller than the estimated margin (assuming there is positive margin). This ensures that the estimated tolerance bound will be within performance requirements and the tolerance ratio will be greater than one, supporting a conclusion that we have sufficient margin to the performance requirements. In addition, this paper explores the relationship between margin, uncertainty, and sample size and provides an approach and recommendations for quantifying risk when sample sizes are limited.
Minimum Sample Size for Cronbach's Coefficient Alpha: A Monte-Carlo Study
ERIC Educational Resources Information Center
Yurdugul, Halil
2008-01-01
The coefficient alpha is the most widely used measure of internal consistency for composite scores in the educational and psychological studies. However, due to the difficulties of data gathering in psychometric studies, the minimum sample size for the sample coefficient alpha has been frequently debated. There are various suggested minimum sample…
ERIC Educational Resources Information Center
Du, Yunfei
This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…
ERIC Educational Resources Information Center
Finch, W. Holmes; Finch, Maria E. Hernandez
2016-01-01
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests
ERIC Educational Resources Information Center
Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.
2015-01-01
The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…
Computer program for sample sizes required to determine disease incidence in fish populations
Ossiander, Frank J.; Wedemeyer, Gary
1973-01-01
A computer program is described for generating the sample size tables required in fish hatchery disease inspection and certification. The program was designed to aid in detection of infectious pancreatic necrosis (IPN) in salmonids, but it is applicable to any fish disease inspection when the sampling plan follows the hypergeometric distribution.
The Maximal Value of a Zipf Size Variable: Sampling Properties and Relationship to Other Parameters.
ERIC Educational Resources Information Center
Tague, Jean; Nicholls, Paul
1987-01-01
Examines relationships among the parameters of the Zipf size-frequency distribution as well as its sampling properties. Highlights include its importance in bibliometrics, tables for the sampling distribution of the maximal value of a finite Zipf distribution, and an approximation formula for confidence intervals. (Author/LRW)
Kikuchi, Takashi; Gittins, John
2009-08-15
It is necessary for the calculation of sample size to achieve the best balance between the cost of a clinical trial and the possible benefits from a new treatment. Gittins and Pezeshk developed an innovative (behavioral Bayes) approach, which assumes that the number of users is an increasing function of the difference in performance between the new treatment and the standard treatment. The better a new treatment, the more the number of patients who want to switch to it. The optimal sample size is calculated in this framework. This BeBay approach takes account of three decision-makers, a pharmaceutical company, the health authority and medical advisers. Kikuchi, Pezeshk and Gittins generalized this approach by introducing a logistic benefit function, and by extending to the more usual unpaired case, and with unknown variance. The expected net benefit in this model is based on the efficacy of the new drug but does not take account of the incidence of adverse reactions. The present paper extends the model to include the costs of treating adverse reactions and focuses on societal cost-effectiveness as the criterion for determining sample size. The main application is likely to be to phase III clinical trials, for which the primary outcome is to compare the costs and benefits of a new drug with a standard drug in relation to national health-care.
Fienen, Michael N.; Selbig, William R.
2012-01-01
A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.
46 CFR 280.11 - Example of calculation and sample report.
Code of Federal Regulations, 2010 CFR
2010-10-01
... to 46 CFR Part 280 Form Approval—OMB No. 41.R2954-15 Trade Route No. Dollars Percent Trade Route No... 46 Shipping 8 2010-10-01 2010-10-01 false Example of calculation and sample report. 280.11 Section... VESSELS AND OPERATORS LIMITATIONS ON THE AWARD AND PAYMENT OF OPERATING-DIFFERENTIAL SUBSIDY FOR...
Scheuerell, Mark D
2016-01-01
Stock-recruitment models have been used for decades in fisheries management as a means of formalizing the expected number of offspring that recruit to a fishery based on the number of parents. In particular, Ricker's stock recruitment model is widely used due to its flexibility and ease with which the parameters can be estimated. After model fitting, the spawning stock size that produces the maximum sustainable yield (S MSY) to a fishery, and the harvest corresponding to it (U MSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both S MSY and U MSY in terms of the productivity and density-dependent parameters of Ricker's model.
Brera, Carlo; De Santis, Barbara; Prantera, Elisabetta; Debegnach, Francesca; Pannunzi, Elena; Fasano, Floriana; Berdini, Clara; Slate, Andrew B; Miraglia, Marina; Whitaker, Thomas B
2010-08-11
Use of proper sampling methods throughout the agri-food chain is crucial when it comes to effectively detecting contaminants in foods and feeds. The objective of the study was to estimate the performance of sampling plan designs to determine aflatoxin B(1) (AFB(1)) contamination in corn fields. A total of 840 ears were selected from a corn field suspected of being contaminated with aflatoxin. The mean and variance among the aflatoxin values for each ear were 10.6 mug/kg and 2233.3, respectively. The variability and confidence intervals associated with sample means of a given size could be predicted using an equation associated with the normal distribution. Sample sizes of 248 and 674 ears would be required to estimate the true field concentration of 10.6 mug/kg within +/-50 and +/-30%, respectively. Using the distribution information from the study, operating characteristic curves were developed to show the performance of various sampling plan designs. PMID:20608734
EFFECTS OF SAMPLE SIZE ON THE STRESS-PERMEABILITY RELATIONSHIP FOR NATURAL FRACTURES
Gale, J. E.; Raven, K. G.
1980-10-01
Five granite cores (10.0, 15.0, 19.3, 24.5, and 29.4 cm in diameter) containing natural fractures oriented normal to the core axis, were used to study the effect of sample size on the permeability of natural fractures. Each sample, taken from the same fractured plane, was subjected to three uniaxial compressive loading and unloading cycles with a maximum axial stress of 30 MPa. For each loading and unloading cycle, the flowrate through the fracture plane from a central borehole under constant (±2% of the pressure increment) injection pressures was measured at specified increments of effective normal stress. Both fracture deformation and flowrate exhibited highly nonlinear variation with changes in normal stress. Both fracture deformation and flowrate hysteresis between loading and unloading cycles were observed for all samples, but this hysteresis decreased with successive loading cycles. The results of this study suggest that a sample-size effect exists. Fracture deformation and flowrate data indicate that crushing of the fracture plane asperities occurs in the smaller samples because of a poorer initial distribution of contact points than in the larger samples, which deform more elastically. Steady-state flow tests also suggest a decrease in minimum fracture permeability at maximum normal stress with increasing sample size for four of the five samples. Regression analyses of the flowrate and fracture closure data suggest that deformable natural fractures deviate from the cubic relationship between fracture aperture and flowrate and that this is especially true for low flowrates and small apertures, when the fracture sides are in intimate contact under high normal stress conditions, In order to confirm the trends suggested in this study, it is necessary to quantify the scale and variation of fracture plane roughness and to determine, from additional laboratory studies, the degree of variation in the stress-permeability relationship between samples of the same
NASA Astrophysics Data System (ADS)
Malm, William C.; Pitchford, Marc L.
Size distributions and resulting optical properties of sulfur aerosols were investigated at three national parks by a Davis Rotating-drum Universal-size-cut Monitoring (DRUM) impactor. Sulfur size distribution measurements for 88, 177, and 315 consecutive time periods were made at Grand Canyon National Park during January and February 1988, Meadview, AZ during July, August, and September 1992, and at Shenandoah National Park during summer, 1990, respectively. The DRUM impactor is designed to collect aerosols with an aerodynamic diameter between 0.07 and 15.0 μm in eight size ranges. Focused beam particle-induced X-ray emission (PIXE) analysis of the aerosol deposits produces a time history of size-resolved elemental composition of varied temporal resolution. As part of the quality assurance protocol, an interagency monitoring of protected visual environments (IMPROVE) channel A sampler collecting 0-2.5 μm diameter particles was operated simultaneously alongside the DRUM sampler. During these sampling periods, the average sulfur mass, interpreted as ammonium sulfate, is 0.49, 2.30, and 10.36 μg m -3 at Grand Canyon, Meadview, and Shenandoah, respectively. The five drum stages were "inverted" using the Twomey (1975) scheme to give 486 size distributions, each made up of 72 discreet pairs of d C/dlog( D) and diameter ( D). From these distributions mass mean diameters ( Dg), geometric standard deviations ( σg), and mass scattering efficiencies ( em)) were calculated. The geometric mass mean diameters in ascending order were 0.21 μm at Meadview, 0.32 μm at Grand Canyon, and 0.42 μm at Shenandoah corresponding σg were 2.1, 2.3, and 1.9. Mie theory mass scattering efficiencies calculated from d C/dlog( D) distributions for the three locations were 2.05, 2.59, and 3.81 m 2 g -1, respectively. At Shenandoah, mass scattering efficiencies approached five but only when the mass median diameters were approximately 0.4 μm and σg were about 1.5. σg near 1.5 were
Bartsch, L.A.; Richardson, W.B.; Naimo, T.J.
1998-01-01
Estimation of benthic macroinvertebrate populations over large spatial scales is difficult due to the high variability in abundance and the cost of sample processing and taxonomic analysis. To determine a cost-effective, statistically powerful sample design, we conducted an exploratory study of the spatial variation of benthic macroinvertebrates in a 37 km reach of the Upper Mississippi River. We sampled benthos at 36 sites within each of two strata, contiguous backwater and channel border. Three standard ponar (525 cm(2)) grab samples were obtained at each site ('Original Design'). Analysis of variance and sampling cost of strata-wide estimates for abundance of Oligochaeta, Chironomidae, and total invertebrates showed that only one ponar sample per site ('Reduced Design') yielded essentially the same abundance estimates as the Original Design, while reducing the overall cost by 63%. A posteriori statistical power analysis (alpha = 0.05, beta = 0.20) on the Reduced Design estimated that at least 18 sites per stratum were needed to detect differences in mean abundance between contiguous backwater and channel border areas for Oligochaeta, Chironomidae, and total invertebrates. Statistical power was nearly identical for the three taxonomic groups. The abundances of several taxa of concern (e.g., Hexagenia mayflies and Musculium fingernail clams) were too spatially variable to estimate power with our method. Resampling simulations indicated that to achieve adequate sampling precision for Oligochaeta, at least 36 sample sites per stratum would be required, whereas a sampling precision of 0.2 would not be attained with any sample size for Hexagenia in channel border areas, or Chironomidae and Musculium in both strata given the variance structure of the original samples. Community-wide diversity indices (Brillouin and 1-Simpsons) increased as sample area per site increased. The backwater area had higher diversity than the channel border area. The number of sampling sites
Sleeth, Darrah K
2013-05-01
In 2010, the American Conference of Governmental Industrial Hygienists (ACGIH) formally changed its Threshold Limit Value (TLV) for beryllium from a 'total' particulate sample to an inhalable particulate sample. This change may have important implications for workplace air sampling of beryllium. A history of particle size-selective sampling methods, with a special focus on beryllium, will be provided. The current state of the science on inhalable sampling will also be presented, including a look to the future at what new methods or technology may be on the horizon. This includes new sampling criteria focused on particle deposition in the lung, proposed changes to the existing inhalable convention, as well as how the issues facing beryllium sampling may help drive other changes in sampling technology.
Demonstration of multi- and single-reader sample size program for diagnostic studies software
NASA Astrophysics Data System (ADS)
Hillis, Stephen L.; Schartz, Kevin M.
2015-03-01
The recently released software Multi- and Single-Reader Sample Size Sample Size Program for Diagnostic Studies, written by Kevin Schartz and Stephen Hillis, performs sample size computations for diagnostic reader-performance studies. The program computes the sample size needed to detect a specified difference in a reader performance measure between two modalities, when using the analysis methods initially proposed by Dorfman, Berbaum, and Metz (DBM) and Obuchowski and Rockette (OR), and later unified and improved by Hillis and colleagues. A commonly used reader performance measure is the area under the receiver-operating-characteristic curve. The program can be used with typical common reader-performance measures which can be estimated parametrically or nonparametrically. The program has an easy-to-use step-by-step intuitive interface that walks the user through the entry of the needed information. Features of the software include the following: (1) choice of several study designs; (2) choice of inputs obtained from either OR or DBM analyses; (3) choice of three different inference situations: both readers and cases random, readers fixed and cases random, and readers random and cases fixed; (4) choice of two types of hypotheses: equivalence or noninferiority; (6) choice of two output formats: power for specified case and reader sample sizes, or a listing of case-reader combinations that provide a specified power; (7) choice of single or multi-reader analyses; and (8) functionality in Windows, Mac OS, and Linux.
NASA Astrophysics Data System (ADS)
Reyer, Dorothea; Philipp, Sonja
2014-05-01
It is desirable to enlarge the profit margin of geothermal projects by reducing the total drilling costs considerably. Substantiated assumptions on uniaxial compressive strengths and failure criteria are important to avoid borehole instabilities and adapt the drilling plan to rock mechanical conditions to minimise non-productive time. Because core material is rare we aim at predicting in situ rock properties from outcrop analogue samples which are easy and cheap to provide. The comparability of properties determined from analogue samples with samples from depths is analysed by performing physical characterisation (P-wave velocities, densities), conventional triaxial tests, and uniaxial compressive strength tests of both quarry and equivalent core samples. "Equivalent" means that the quarry sample is of the same stratigraphic age and of comparable sedimentary facies and composition as the correspondent core sample. We determined the parameters uniaxial compressive strength (UCS) and Young's modulus for 35 rock samples from quarries and 14 equivalent core samples from the North German Basin. A subgroup of these samples was used for triaxial tests. For UCS versus Young's modulus, density and P-wave velocity, linear- and non-linear regression analyses were performed. We repeated regression separately for clastic rock samples or carbonate rock samples only as well as for quarry samples or core samples only. Empirical relations were used to calculate UCS values from existing logs of sampled wellbore. Calculated UCS values were then compared with measured UCS of core samples of the same wellbore. With triaxial tests we determined linearized Mohr-Coulomb failure criteria, expressed in both principal stresses and shear and normal stresses, for quarry samples. Comparison with samples from larger depths shows that it is possible to apply the obtained principal stress failure criteria to clastic and volcanic rocks, but less so for carbonates. Carbonate core samples have higher
Efficient calculation of relative binding free energies by umbrella sampling perturbation.
Zeller, Fabian; Zacharias, Martin
2014-12-01
An important task of biomolecular simulation is the calculation of relative binding free energies upon chemical modification of partner molecules in a biomolecular complex. The potential of mean force (PMF) along a reaction coordinate for association or dissociation of the complex can be used to estimate binding affinities. A free energy perturbation approach, termed umbrella sampling (US) perturbation, has been designed that allows an efficient calculation of the change of the PMF upon modification of a binding partner based on the trajectories obtained for the wild type reference complex. The approach was tested on the interaction of modified water molecules in aqueous solution and applied to in silico alanine scanning of a peptide-protein complex. For the water interaction test case, excellent agreement with an explicit PMF calculation for each modification was obtained as long as no long range electrostatic perturbations were considered. For the alanine scanning, the experimentally determined ranking and binding affinity changes upon alanine substitutions could be reproduced within 0.1-2.0 kcal/mol. In addition, good agreement with explicitly calculated PMFs was obtained mostly within the sampling uncertainty. The combined US and perturbation approach yields, under the condition of sufficiently small system modifications, rigorously derived changes in free energy and is applicable to any PMF calculation.
The influence of virtual sample size on confidence and causal-strength judgments.
Liljeholm, Mimi; Cheng, Patricia W
2009-01-01
The authors investigated whether confidence in causal judgments varies with virtual sample size--the frequency of cases in which the outcome is (a) absent before the introduction of a generative cause or (b) present before the introduction of a preventive cause. Participants were asked to evaluate the influence of various candidate causes on an outcome as well as to rate their confidence in those judgments. They were presented with information on the relative frequencies of the outcome given the presence and absence of various candidate causes. These relative frequencies, sample size, and the direction of the causal influence (generative vs. preventive) were manipulated. It was found that both virtual and actual sample size affected confidence. Further, confidence affected estimates of strength, but confidence and strength are dissociable. The results enable a consistent explanation of the puzzling previous finding that observed causal-strength ratings often deviated from the predictions of both of the 2 dominant models of causal strength.
Information-based sample size re-estimation in group sequential design for longitudinal trials.
Zhou, Jing; Adewale, Adeniyi; Shentu, Yue; Liu, Jiajun; Anderson, Keaven
2014-09-28
Group sequential design has become more popular in clinical trials because it allows for trials to stop early for futility or efficacy to save time and resources. However, this approach is less well-known for longitudinal analysis. We have observed repeated cases of studies with longitudinal data where there is an interest in early stopping for a lack of treatment effect or in adapting sample size to correct for inappropriate variance assumptions. We propose an information-based group sequential design as a method to deal with both of these issues. Updating the sample size at each interim analysis makes it possible to maintain the target power while controlling the type I error rate. We will illustrate our strategy with examples and simulations and compare the results with those obtained using fixed design and group sequential design without sample size re-estimation.
Mesh-size effects on drift sample composition as determined with a triple net sampler
Slack, K.V.; Tilley, L.J.; Kennelly, S.S.
1991-01-01
Nested nets of three different mesh apertures were used to study mesh-size effects on drift collected in a small mountain stream. The innermost, middle, and outermost nets had, respectively, 425 ??m, 209 ??m and 106 ??m openings, a design that reduced clogging while partitioning collections into three size groups. The open area of mesh in each net, from largest to smallest mesh opening, was 3.7, 5.7 and 8.0 times the area of the net mouth. Volumes of filtered water were determined with a flowmeter. The results are expressed as (1) drift retained by each net, (2) drift that would have been collected by a single net of given mesh size, and (3) the percentage of total drift (the sum of the catches from all three nets) that passed through the 425 ??m and 209 ??m nets. During a two day period in August 1986, Chironomidae larvae were dominant numerically in all 209 ??m and 106 ??m samples and midday 425 ??m samples. Large drifters (Ephemerellidae) occurred only in 425 ??m or 209 ??m nets, but the general pattern was an increase in abundance and number of taxa with decreasing mesh size. Relatively more individuals occurred in the larger mesh nets at night than during the day. The two larger mesh sizes retained 70% of the total sediment/detritus in the drift collections, and this decreased the rate of clogging of the 106 ??m net. If an objective of a sampling program is to compare drift density or drift rate between areas or sampling dates, the same mesh size should be used for all sample collection and processing. The mesh aperture used for drift collection should retain all species and life stages of significance in a study. The nested net design enables an investigator to test the adequacy of drift samples. ?? 1991 Kluwer Academic Publishers.
Calculating partial expected value of perfect information via Monte Carlo sampling algorithms.
Brennan, Alan; Kharroubi, Samer; O'hagan, Anthony; Chilcott, Jim
2007-01-01
Partial expected value of perfect information (EVPI) calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. Published case studies have used different computational approaches. This article examines the computation of partial EVPI estimates via Monte Carlo sampling algorithms. The mathematical definition shows 2 nested expectations, which must be evaluated separately because of the need to compute a maximum between them. A generalized Monte Carlo sampling algorithm uses nested simulation with an outer loop to sample parameters of interest and, conditional upon these, an inner loop to sample remaining uncertain parameters. Alternative computation methods and shortcut algorithms are discussed and mathematical conditions for their use considered. Maxima of Monte Carlo estimates of expectations are biased upward, and the authors show that the use of small samples results in biased EVPI estimates. Three case studies illustrate 1) the bias due to maximization and also the inaccuracy of shortcut algorithms 2) when correlated variables are present and 3) when there is nonlinearity in net benefit functions. If relatively small correlation or nonlinearity is present, then the shortcut algorithm can be substantially inaccurate. Empirical investigation of the numbers of Monte Carlo samples suggests that fewer samples on the outer level and more on the inner level could be efficient and that relatively small numbers of samples can sometimes be used. Several remaining areas for methodological development are set out. A wider application of partial EVPI is recommended both for greater understanding of decision uncertainty and for analyzing research priorities. PMID:17761960
Free Energy Calculations using a Swarm-Enhanced Sampling Molecular Dynamics Approach.
Burusco, Kepa K; Bruce, Neil J; Alibay, Irfan; Bryce, Richard A
2015-10-26
Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange.
Power and Sample Size for Randomized Phase III Survival Trials under the Weibull Model
Wu, Jianrong
2015-01-01
Two parametric tests are proposed for designing randomized two-arm phase III survival trials under the Weibull model. The properties of the two parametric tests are compared with the non-parametric log-rank test through simulation studies. Power and sample size formulas of the two parametric tests are derived. The impact on sample size under mis-specification of the Weibull shape parameter is also investigated. The study can be designed by planning the study duration and handling nonuniform entry and loss to follow-up under the Weibull model using either the proposed parametric tests or the well known non-parametric log-rank test. PMID:24895942
Monticelli, D; Laglera, L M; Caprara, S
2014-10-01
Voltammetric techniques have emerged as powerful methods for the determination and speciation of trace and ultratrace elements without any preconcentration in several research fields. Nevertheless, large sample volumes are typically required (10 mL), which strongly limits their application and/or the precision of the results. In this work, we report a 20-fold reduction in sample size for trace and ultratrace elemental determination and speciation by conventional voltammetric instrumentation, introducing the lowest amount of sample (0.5 mL) in which ultratrace detection has been performed up to now. This goal was achieved by a careful design of a new sample holder. Reliable, validated results were obtained for the determination of trace/ultratrace elements in rainwater (Cd, Co, Cu, Ni, Pb) and seawater (Cu). Moreover, copper speciation in seawater samples was consistently determined by competitive ligand equilibration-cathodic stripping voltammetry (CLE-CSV). The proposed apparatus showed several advantages: (1) 20-fold reduction in sample volume (the sample size is lowered from 120 to 6 mL for the CLE-CSV procedure); (2) decrease in analysis time due to the reduction in purging time up to 2.5 fold; (3) 20-fold drop in reagent consumption. Moreover, the analytical performances were not affected: similar detection capabilities, precision and accuracy were obtained. Application to sample of limited availability (e.g. porewaters, snow, rainwater, open ocean water, biological samples) and to the description of high resolution temporal trends may be easily foreseen.
Azbouche, Ahmed; Belgaid, Mohamed; Mazrou, Hakim
2015-08-01
A fully detailed Monte Carlo geometrical model of a High Purity Germanium detector with a (152)Eu source, packed in Marinelli beaker, was developed for routine analysis of large volume environmental samples. Then, the model parameters, in particular, the dead layer thickness were adjusted thanks to a specific irradiation configuration together with a fine-tuning procedure. Thereafter, the calculated efficiencies were compared to the measured ones for standard samples containing (152)Eu source filled in both grass and resin matrices packed in Marinelli beaker. From this comparison, a good agreement between experiment and Monte Carlo calculation results was obtained highlighting thereby the consistency of the geometrical computational model proposed in this work. Finally, the computational model was applied successfully to determine the (137)Cs distribution in soil matrix. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site.
Simulation analyses of space use: Home range estimates, variability, and sample size
Bekoff, M.; Mech, L.D.
1984-01-01
Simulations of space use by animals were run to determine the relationship among home range area estimates, variability, and sample size {number of locations}. As sample size increased, home range size increased asymptotically, whereas variability decreased among mean home range area estimates generated by multiple simulations for the same sample size. Our results suggest that field workers should ascertain between 100 and 200 locations in order to estimate reliably home range area. In some cases, this suggested guideline is higher than values found in the few published studies in which the relationship between home range area and number of locations is addressed. Sampling differences for small species occupying relatively small home ranges indicate that fewer locations may be sufficient to allow for a reliable estimate of home range. Intraspecffic variability in social status (group member, loner, resident, transient), age, sex, reproductive condition, and food resources also have to be considered, as do season, habitat, and differences in sampling and analytical methods. Comparative data still are needed.
Hoyle, Rick H; Gottfredson, Nisha C
2015-10-01
When the goal of prevention research is to capture in statistical models some measure of the dynamic complexity in structures and processes implicated in problem behavior and its prevention, approaches such as multilevel modeling (MLM) and structural equation modeling (SEM) are indicated. Yet the assumptions that must be satisfied if these approaches are to be used responsibly raise concerns regarding their use in prevention research involving smaller samples. In this article, we discuss in nontechnical terms the role of sample size in MLM and SEM and present findings from the latest simulation work on the performance of each approach at sample sizes typical of prevention research. For each statistical approach, we draw from extant simulation studies to establish lower bounds for sample size (e.g., MLM can be applied with as few as ten groups comprising ten members with normally distributed data, restricted maximum likelihood estimation, and a focus on fixed effects; sample sizes as small as N = 50 can produce reliable SEM results with normally distributed data and at least three reliable indicators per factor) and suggest strategies for making the best use of the modeling approach when N is near the lower bound.
NASA Technical Reports Server (NTRS)
ROBERT
1922-01-01
This report presents the attempt to develop a law which will permit the use of results obtained on small models in a tunnel for the calculation of full-sized airplanes, or if it exists, a law of similitude relating air forces on a full-sized plane to those on a reduced scale model.
ERIC Educational Resources Information Center
Dunst, Carl J.; Hamby, Deborah W.
2012-01-01
This paper includes a nontechnical description of methods for calculating effect sizes in intellectual and developmental disability studies. Different hypothetical studies are used to illustrate how null hypothesis significance testing (NHST) and effect size findings can result in quite different outcomes and therefore conflicting results. Whereas…
Big data and large sample size: a cautionary note on the potential for bias.
Kaplan, Robert M; Chambers, David A; Glasgow, Russell E
2014-08-01
A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of "big data" that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design.
New algorithms for the Vavilov distribution calculation and the corresponding energy loss sampling
Chibani, O. |
1998-10-01
Two new algorithms for the fast calculation of the Vavilov distribution within the interval 0.01 {le} {kappa} {le} 10, where neither the Gaussian approximation nor the Landau distribution may be used, are presented. These algorithms are particularly convenient for the sampling of the corresponding random energy loss. A comparison with the exact Vavilov distribution for the case of protons traversing Al slabs is given.
The effect of molecular dynamics sampling on the calculated observable gas-phase structures.
Tikhonov, Denis S; Otlyotov, Arseniy A; Rybkin, Vladimir V
2016-07-21
In this study, we compare the performance of various ab initio molecular dynamics (MD) sampling methods for the calculation of the observable vibrationally-averaged gas-phase structures of benzene, naphthalene and anthracene molecules. Nose-Hoover (NH), canonical and quantum generalized-Langevin-equation (GLE) thermostats as well as the a posteriori quantum correction to the classical trajectories have been tested and compared to the accurate path-integral molecular dynamics (PIMD), static anharmonic vibrational calculations as well as to the experimental gas electron diffraction data. Classical sampling methods neglecting quantum effects (NH and canonical GLE thermostats) dramatically underestimate vibrational amplitudes for the bonded atom pairs, both C-H and C-C, the resulting radial distribution functions exhibit nonphysically narrow peaks. This deficiency is almost completely removed by taking the quantum effects on the nuclei into account. The quantum GLE thermostat and a posteriori correction to the canonical GLE and NH thermostatted trajectories capture most vibrational quantum effects and closely reproduce computationally expensive PIMD and experimental radial distribution functions. These methods are both computationally feasible and accurate and are therefore recommended for calculations of the observable gas-phase structures. A good performance of the quantum GLE thermostat for the gas-phase calculations is encouraging since its parameters have been originally fitted for the condensed-phase calculations. Very accurate molecular structures can be predicted by combining the equilibrium geometry obtained at a high level of electronic structure theory with vibrational amplitudes and corrections calculated using MD driven by a lower level of electronic structure theory.
The effect of molecular dynamics sampling on the calculated observable gas-phase structures.
Tikhonov, Denis S; Otlyotov, Arseniy A; Rybkin, Vladimir V
2016-07-21
In this study, we compare the performance of various ab initio molecular dynamics (MD) sampling methods for the calculation of the observable vibrationally-averaged gas-phase structures of benzene, naphthalene and anthracene molecules. Nose-Hoover (NH), canonical and quantum generalized-Langevin-equation (GLE) thermostats as well as the a posteriori quantum correction to the classical trajectories have been tested and compared to the accurate path-integral molecular dynamics (PIMD), static anharmonic vibrational calculations as well as to the experimental gas electron diffraction data. Classical sampling methods neglecting quantum effects (NH and canonical GLE thermostats) dramatically underestimate vibrational amplitudes for the bonded atom pairs, both C-H and C-C, the resulting radial distribution functions exhibit nonphysically narrow peaks. This deficiency is almost completely removed by taking the quantum effects on the nuclei into account. The quantum GLE thermostat and a posteriori correction to the canonical GLE and NH thermostatted trajectories capture most vibrational quantum effects and closely reproduce computationally expensive PIMD and experimental radial distribution functions. These methods are both computationally feasible and accurate and are therefore recommended for calculations of the observable gas-phase structures. A good performance of the quantum GLE thermostat for the gas-phase calculations is encouraging since its parameters have been originally fitted for the condensed-phase calculations. Very accurate molecular structures can be predicted by combining the equilibrium geometry obtained at a high level of electronic structure theory with vibrational amplitudes and corrections calculated using MD driven by a lower level of electronic structure theory. PMID:27331660
Form and structural response calculations for NIF neutron exposure sample case assembly design
DiPeso, G.; Serduke, F.; Pillenger, L.
1996-12-31
We describe the calculations used to design an aluminum foam protection layer for a stainless steel neutron exposure sample case. The layer protects the case from impulsive loads generated by a 20 MJ NIF capsule 10 cm from the sample case assembly. Impulse only from ablating x-rays and hohlraum plasma debris is considered. One dimensional CALE foam response calculations and analytic estimates are used to show that 1 cm of aluminum 6101-T6 foam 10 % of solid density is sufficient to attenuate the incoming peak pressure without complete melting on crush-up. Two dimensional DYNA calculations show that a 304 stainless steel spherical shell sample case with an inner radius of 1 cm and a wall thickness of 2 mm encased in 1 cm of foam does not yield to the pressure that is transmitted through the foam by a 220 Pa-sec (2.2 ktap), 2 GPa (20 kbar) load due to recoil of x- ray ablation. An unprotected spherical shell case subjected to a gentler load with peak pressure reduced to 0.2 GPa (2 kbar) not only yields but its effective plastic strain exceeds the failure point of 0.4 in 304 stainless steel after 160 microseconds. Doubling the impulse for the protected case to approximately account for debris loading results in very localized yield and an effective plastic strain that does not exceed 0.014. (U)
Sheehan, Sara; Harris, Kelley; Song, Yun S
2013-07-01
Throughout history, the population size of modern humans has varied considerably due to changes in environment, culture, and technology. More accurate estimates of population size changes, and when they occurred, should provide a clearer picture of human colonization history and help remove confounding effects from natural selection inference. Demography influences the pattern of genetic variation in a population, and thus genomic data of multiple individuals sampled from one or more present-day populations contain valuable information about the past demographic history. Recently, Li and Durbin developed a coalescent-based hidden Markov model, called the pairwise sequentially Markovian coalescent (PSMC), for a pair of chromosomes (or one diploid individual) to estimate past population sizes. This is an efficient, useful approach, but its accuracy in the very recent past is hampered by the fact that, because of the small sample size, only few coalescence events occur in that period. Multiple genomes from the same population contain more information about the recent past, but are also more computationally challenging to study jointly in a coalescent framework. Here, we present a new coalescent-based method that can efficiently infer population size changes from multiple genomes, providing access to a new store of information about the recent past. Our work generalizes the recently developed sequentially Markov conditional sampling distribution framework, which provides an accurate approximation of the probability of observing a newly sampled haplotype given a set of previously sampled haplotypes. Simulation results demonstrate that we can accurately reconstruct the true population histories, with a significant improvement over the PSMC in the recent past. We apply our method, called diCal, to the genomes of multiple human individuals of European and African ancestry to obtain a detailed population size change history during recent times.
Sheehan, Sara; Harris, Kelley; Song, Yun S.
2013-01-01
Throughout history, the population size of modern humans has varied considerably due to changes in environment, culture, and technology. More accurate estimates of population size changes, and when they occurred, should provide a clearer picture of human colonization history and help remove confounding effects from natural selection inference. Demography influences the pattern of genetic variation in a population, and thus genomic data of multiple individuals sampled from one or more present-day populations contain valuable information about the past demographic history. Recently, Li and Durbin developed a coalescent-based hidden Markov model, called the pairwise sequentially Markovian coalescent (PSMC), for a pair of chromosomes (or one diploid individual) to estimate past population sizes. This is an efficient, useful approach, but its accuracy in the very recent past is hampered by the fact that, because of the small sample size, only few coalescence events occur in that period. Multiple genomes from the same population contain more information about the recent past, but are also more computationally challenging to study jointly in a coalescent framework. Here, we present a new coalescent-based method that can efficiently infer population size changes from multiple genomes, providing access to a new store of information about the recent past. Our work generalizes the recently developed sequentially Markov conditional sampling distribution framework, which provides an accurate approximation of the probability of observing a newly sampled haplotype given a set of previously sampled haplotypes. Simulation results demonstrate that we can accurately reconstruct the true population histories, with a significant improvement over the PSMC in the recent past. We apply our method, called diCal, to the genomes of multiple human individuals of European and African ancestry to obtain a detailed population size change history during recent times. PMID:23608192
Size-dependent Turbidimatric Quantification of Mobile Colloids in Field Samples
NASA Astrophysics Data System (ADS)
Yan, J.; Meng, X.; Jin, Y.
2015-12-01
Natural colloids, often defined as entities with sizes < 1.0 μm, have attracted much research attention because of their ability to facilitate the transport of contaminants in the subsurface environment. However, due to their small size and generally low concentrations in field samples, quantification of mobile colloids, especially the smaller fractions (< 0.45 µm), which are operationally defined as dissolved, is largely impeded and hence the natural colloidal pool is greatly overlooked and underestimated. The main objectives of this study are to: (1) develop an experimentally and economically efficient methodology to quantify natural colloids in different size fractions (0.1-0.45 and 0.45-1 µm); (2) quantify mobile colloids including small colloids, < 0.45 µm particularly, in different natural aquatic samples. We measured and generated correlations between mass concentration and turbidity of colloid suspensions, made by extracting and fractionating water dispersible colloids in 37 soils from different areas in the U.S. and Denmark, for colloid size fractions 0.1-0.45 and 0.45-1 µm. Results show that the correlation between turbidity and colloid mass concentration is largely affected by colloid size and iron content, indicating the need to generate different correlations for colloids with constrained size range and iron content. This method enabled quick quantification of colloid concentrations in a large number of field samples collected from freshwater, wetland and estuaries in different size fractions. As a general trend, we observed high concentrations of colloids in the < 0.45 µm fraction, which constitutes a significant percentage of the total mobile colloidal pool (< 1 µm). This observation suggests that the operationally defined cut-off size for "dissolved" phase can greatly underestimate colloid concentration therefore the role that colloids play in the transport of associated contaminants or other elements.
Eberl, D.D.; Drits, V.A.; Srodon, Jan; Nuesch, R.
1996-01-01
Particle size may strongly influence the physical and chemical properties of a substance (e.g. its rheology, surface area, cation exchange capacity, solubility, etc.), and its measurement in rocks may yield geological information about ancient environments (sediment provenance, degree of metamorphism, degree of weathering, current directions, distance to shore, etc.). Therefore mineralogists, geologists, chemists, soil scientists, and others who deal with clay-size material would like to have a convenient method for measuring particle size distributions. Nano-size crystals generally are too fine to be measured by light microscopy. Laser scattering methods give only average particle sizes; therefore particle size can not be measured in a particular crystallographic direction. Also, the particles measured by laser techniques may be composed of several different minerals, and may be agglomerations of individual crystals. Measurement by electron and atomic force microscopy is tedious, expensive, and time consuming. It is difficult to measure more than a few hundred particles per sample by these methods. This many measurements, often taking several days of intensive effort, may yield an accurate mean size for a sample, but may be too few to determine an accurate distribution of sizes. Measurement of size distributions by X-ray diffraction (XRD) solves these shortcomings. An X-ray scan of a sample occurs automatically, taking a few minutes to a few hours. The resulting XRD peaks average diffraction effects from billions of individual nano-size crystals. The size that is measured by XRD may be related to the size of the individual crystals of the mineral in the sample, rather than to the size of particles formed from the agglomeration of these crystals. Therefore one can determine the size of a particular mineral in a mixture of minerals, and the sizes in a particular crystallographic direction of that mineral.
Sample-Size Effects on the Compression Behavior of a Ni-BASED Amorphous Alloy
NASA Astrophysics Data System (ADS)
Liang, Weizhong; Zhao, Guogang; Wu, Linzhi; Yu, Hongjun; Li, Ming; Zhang, Lin
Ni42Cu5Ti20Zr21.5Al8Si3.5 bulk metallic glasses rods with diameters of 1 mm and 3 mm, were prepared by arc melting of composing elements in a Ti-gettered argon atmosphere. The compressive deformation and fracture behavior of the amorphous alloy samples with different size were investigated by testing machine and scanning electron microscope. The compressive stress-strain curves of 1 mm and 3 mm samples exhibited 4.5% and 0% plastic strain, while the compressive fracture strength for 1 mm and 3 mm rod is 4691 MPa and 2631 MPa, respectively. The compressive fracture surface of different size sample consisted of shear zone and non-shear one. Typical vein patterns with some melting drops can be seen on the shear region of 1 mm rod, while fish-bone shape patterns can be observed on 3 mm specimen surface. Some interesting different spacing periodic ripples existed on the non-shear zone of 1 and 3 mm rods. On the side surface of 1 mm sample, high density of shear bands was observed. The skip of shear bands can be seen on 1 mm sample surface. The mechanisms of the effect of sample size on fracture strength and plasticity of the Ni-based amorphous alloy are discussed.
Speckle-suppression in hologram calculation using ray-sampling plane.
Utsugi, Takeru; Yamaguchi, Masahiro
2014-07-14
Speckle noise is an important issue in electro-holographic displays. We propose a new method for suppressing speckle noise in a computer-generated hologram (CGH) for 3D display. In our previous research, we proposed a method for CGH calculation using ray-sampling plane (RS-plane), which enables the application of advanced ray-based rendering techniques to the calculation of hologram that can reconstruct a deep 3D scene in high resolution. Conventional techniques for effective speckle suppression, which utilizes the time-multiplexing of sparse object points, can suppress the speckle noise with high resolution, but it cannot be applied to the CGH calculation using RS-plane because the CGH calculated using RS-plane does not utilize point sources on an object surface. Then, we propose the method to define the point sources from light-ray information and apply the speckle suppression technique using sparse point sources to CGH calculation using RS-plane. The validity of the proposed method was verified by numerical simulations.
Janja Tursic; Irena Grgic; Axel Berner; Jaroslav Skantar; Igor Cuhalev
2008-02-01
A special sampling system for measurements of size-segregated particles directly at the source of emission was designed and constructed. The central part of this system is a low-pressure cascade impactor with 10 collection stages for the size ranges between 15 nm and 16 {mu}m. Its capability and suitability was proven by sampling particles at the stack (100{sup o}C) of a coal-fired power station in Slovenia. These measurements showed very reasonable results in comparison with a commercial cascade impactor for PM10 and PM2.5 and with a plane device for total suspended particulate matter (TSP). The best agreement with the measurements made by a commercial impactor was found for concentrations of TSP above 10 mg m{sup -3}, i.e., the average PM2.5/PM10 ratios obtained by a commercial impactor and by our impactor were 0.78 and 0.80, respectively. Analysis of selected elements in size-segregated emission particles additionally confirmed the suitability of our system. The measurements showed that the mass size distributions were generally bimodal, with the most pronounced mass peak in the 1-2 {mu}m size range. The first results of elemental mass size distributions showed some distinctive differences in comparison to the most common ambient anthropogenic sources (i.e., traffic emissions). For example, trace elements, like Pb, Cd, As, and V, typically related to traffic emissions, are usually more abundant in particles less than 1 {mu}m in size, whereas in our specific case they were found at about 2 {mu}m. Thus, these mass size distributions can be used as a signature of this source. Simultaneous measurements of size-segregated particles at the source and in the surrounding environment can therefore significantly increase the sensitivity of the contribution of a specific source to the actual ambient concentrations. 25 refs., 3 figs., 2 tabs.
Introduction to Sample Size Choice for Confidence Intervals Based on "t" Statistics
ERIC Educational Resources Information Center
Liu, Xiaofeng Steven; Loudermilk, Brandon; Simpson, Thomas
2014-01-01
Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis…
Got Power? A Systematic Review of Sample Size Adequacy in Health Professions Education Research
ERIC Educational Resources Information Center
Cook, David A.; Hatala, Rose
2015-01-01
Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011,…
ERIC Educational Resources Information Center
Sideridis, Georgios; Simos, Panagiotis; Papanicolaou, Andrew; Fletcher, Jack
2014-01-01
The present study assessed the impact of sample size on the power and fit of structural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity during performance of a reading task obtained with magnetoencephalography. Power analysis was first…
Cao, Zhiguo; Xu, Fuchao; Li, Wenchao; Sun, Jianhui; Shen, Mohai; Su, Xianfa; Feng, Jinglan; Yu, Gang; Covaci, Adrian
2015-09-15
Particle size is a significant parameter which determines the environmental fate and the behavior of dust particles and, implicitly, the exposure risk of humans to particle-bound contaminants. Currently, the influence of dust particle size on the occurrence and seasonal variation of hexabromocyclododecanes (HBCDs) remains unclear. While HBCDs are now restricted by the Stockholm Convention, information regarding HBCD contamination in indoor dust in China is still limited. We analyzed composite dust samples from offices (n = 22), hotels (n = 3), kindergartens (n = 2), dormitories (n = 40), and main roads (n = 10). Each composite dust sample (one per type of microenvironment) was fractionated into 9 fractions (F1-F9: 2000-900, 900-500, 500-400, 400-300, 300-200, 200-100, 100-74, 74-50, and <50 μm). Total HBCD concentrations ranged from 5.3 (road dust, F4) to 2580 ng g(-1) (dormitory dust, F4) in the 45 size-segregated samples. The seasonality of HBCDs in indoor dust was investigated in 40 samples from two offices. A consistent seasonal trend of HBCD levels was evident with dust collected in the winter being more contaminated with HBCDs than dust from the summer. Particle size-selection strategy for dust analysis has been found to be influential on the HBCD concentrations, while overestimation or underestimation would occur with improper strategies. PMID:26301772
The Relation among Fit Indexes, Power, and Sample Size in Structural Equation Modeling
ERIC Educational Resources Information Center
Kim, Kevin H.
2005-01-01
The relation among fit indexes, power, and sample size in structural equation modeling is examined. The noncentrality parameter is required to compute power. The 2 existing methods of computing power have estimated the noncentrality parameter by specifying an alternative hypothesis or alternative fit. These methods cannot be implemented easily and…
ERIC Educational Resources Information Center
Kelley, Ken; Rausch, Joseph R.
2006-01-01
Methods for planning sample size (SS) for the standardized mean difference so that a narrow confidence interval (CI) can be obtained via the accuracy in parameter estimation (AIPE) approach are developed. One method plans SS so that the expected width of the CI is sufficiently narrow. A modification adjusts the SS so that the obtained CI is no…
On efficient two-stage adaptive designs for clinical trials with sample size adjustment.
Liu, Qing; Li, Gang; Anderson, Keaven M; Lim, Pilar
2012-01-01
Group sequential designs are rarely used for clinical trials with substantial over running due to fast enrollment or long duration of treatment and follow-up. Traditionally, such trials rely on fixed sample size designs. Recently, various two-stage adaptive designs have been introduced to allow sample size adjustment to increase statistical power or avoid unnecessarily large trials. However, these adaptive designs can be seriously inefficient. To address this infamous problem, we propose a likelihood-based two-stage adaptive design where sample size adjustment is derived from a pseudo group sequential design using cumulative conditional power. We show through numerical examples that this design cannot be improved by group sequential designs. In addition, the approach may uniformly improve any existing two-stage adaptive designs with sample size adjustment. For statistical inference, we provide methods for sequential p-values and confidence intervals, as well as median unbiased and minimum variance unbiased estimates. We show that the claim of inefficiency of adaptive designs by Tsiatis and Mehta ( 2003 ) is logically flawed, and thereby provide a strong defense of Cui et al. ( 1999 ). PMID:22651105
ERIC Educational Resources Information Center
Kim, Su-Young
2012-01-01
Just as growth mixture models are useful with single-phase longitudinal data, multiphase growth mixture models can be used with multiple-phase longitudinal data. One of the practically important issues in single- and multiphase growth mixture models is the sample size requirements for accurate estimation. In a Monte Carlo simulation study, the…
Kelley, Ken
2007-11-01
The accuracy in parameter estimation approach to sample size planning is developed for the coefficient of variation, where the goal of the method is to obtain an accurate parameter estimate by achieving a sufficiently narrow confidence interval. The first method allows researchers to plan sample size so that the expected width of the confidence interval for the population coefficient of variation is sufficiently narrow. A modification allows a desired degree of assurance to be incorporated into the method, so that the obtained confidence interval will be sufficiently narrow with some specified probability (e.g., 85% assurance that the 95 confidence interval width will be no wider than to units). Tables of necessary sample size are provided for a variety of scenarios that may help researchers planning a study where the coefficient of variation is of interest plan an appropriate sample size in order to have a sufficiently narrow confidence interval, optionally with somespecified assurance of the confidence interval being sufficiently narrow. Freely available computer routines have been developed that allow researchers to easily implement all of the methods discussed in the article.
The Influence of Virtual Sample Size on Confidence and Causal-Strength Judgments
ERIC Educational Resources Information Center
Liljeholm, Mimi; Cheng, Patricia W.
2009-01-01
The authors investigated whether confidence in causal judgments varies with virtual sample size--the frequency of cases in which the outcome is (a) absent before the introduction of a generative cause or (b) present before the introduction of a preventive cause. Participants were asked to evaluate the influence of various candidate causes on an…
Size Distributions and Characterization of Native and Ground Samples for Toxicology Studies
NASA Technical Reports Server (NTRS)
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.
The effects of sampling and internal noise on the representation of ensemble average size.
Im, Hee Yeon; Halberda, Justin
2013-02-01
Increasing numbers of studies have explored human observers' ability to rapidly extract statistical descriptions from collections of similar items (e.g., the average size and orientation of a group of tilted Gabor patches). Determining whether these descriptions are generated by mechanisms that are independent from object-based sampling procedures requires that we investigate how internal noise, external noise, and sampling affect subjects' performance. Here we systematically manipulated the external variability of ensembles and used variance summation modeling to estimate both the internal noise and the number of samples that affected the representation of ensemble average size. The results suggest that humans sample many more than one or two items from an array when forming an estimate of the average size, and that the internal noise that affects ensemble processing is lower than the noise that affects the processing of single objects. These results are discussed in light of other recent modeling efforts and suggest that ensemble processing of average size relies on a mechanism that is distinct from segmenting individual items. This ensemble process may be more similar to texture processing.
One-Sided Nonparametric Comparison of Treatments with a Standard for Unequal Sample Sizes.
ERIC Educational Resources Information Center
Chakraborti, S.; Gibbons, Jean D.
1992-01-01
The one-sided problem of comparing treatments with a standard on the basis of data available in the context of a one-way analysis of variance is examined, and the methodology of S. Chakraborti and J. D. Gibbons (1991) is extended to the case of unequal sample sizes. (SLD)
Support vector regression to predict porosity and permeability: Effect of sample size
NASA Astrophysics Data System (ADS)
Al-Anazi, A. F.; Gates, I. D.
2012-02-01
Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function
NASA Astrophysics Data System (ADS)
Nagaya, Yasunobu
2014-06-01
The methods to calculate the kinetics parameters of βeff and Λ with the differential operator sampling have been reviewed. The comparison of the results obtained with the differential operator sampling and iterated fission probability approaches has been performed. It is shown that the differential operator sampling approach gives the same results as the iterated fission probability approach within the statistical uncertainty. In addition, the prediction accuracy of the evaluated nuclear data library JENDL-4.0 for the measured βeff/Λ and βeff values is also examined. It is shown that JENDL-4.0 gives a good prediction except for the uranium-233 systems. The present results imply the need for revisiting the uranium-233 nuclear data evaluation and performing the detailed sensitivity analysis.
Forestry inventory based on multistage sampling with probability proportional to size
NASA Technical Reports Server (NTRS)
Lee, D. C. L.; Hernandez, P., Jr.; Shimabukuro, Y. E.
1983-01-01
A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.
Gutenberg-Richter b-value maximum likelihood estimation and sample size
NASA Astrophysics Data System (ADS)
Nava, F. A.; Márquez-Ramírez, V. H.; Zúñiga, F. R.; Ávila-Barrientos, L.; Quinteros, C. B.
2016-06-01
The Aki-Utsu maximum likelihood method is widely used for estimation of the Gutenberg-Richter b-value, but not all authors are conscious of the method's limitations and implicit requirements. The Aki/Utsu method requires a representative estimate of the population mean magnitude; a requirement seldom satisfied in b-value studies, particularly in those that use data from small geographic and/or time windows, such as b-mapping and b-vs-time studies. Monte Carlo simulation methods are used to determine how large a sample is necessary to achieve representativity, particularly for rounded magnitudes. The size of a representative sample weakly depends on the actual b-value. It is shown that, for commonly used precisions, small samples give meaningless estimations of b. Our results give estimates on the probabilities of getting correct estimates of b for a given desired precision for samples of different sizes. We submit that all published studies reporting b-value estimations should include information about the size of the samples used.
10Be measurements at MALT using reduced-size samples of bulk sediments
NASA Astrophysics Data System (ADS)
Horiuchi, Kazuho; Oniyanagi, Itsumi; Wasada, Hiroshi; Matsuzaki, Hiroyuki
2013-01-01
In order to establish 10Be measurements on reduced-size (1-10 mg) samples of bulk sediments, we investigated four different pretreatment designs using lacustrine and marginal-sea sediments and the AMS system of the Micro Analysis Laboratory, Tandem accelerator (MALT) at The University of Tokyo. The 10Be concentrations obtained from the samples of 1-10 mg agreed within a precision of 3-5% with the values previously determined using corresponding ordinary-size (∼200 mg) samples and the same AMS system. This fact demonstrates reliable determinations of 10Be with milligram levels of recent bulk sediments at MALT. On the other hand, a clear decline of the BeO- beam with tens of micrograms of 9Be carrier suggests that the combination of ten milligrams of sediments and a few hundred micrograms of the 9Be carrier is more convenient at this stage.
Size selective isocyanate aerosols personal air sampling using porous plastic foams
NASA Astrophysics Data System (ADS)
Khanh Huynh, Cong; Duc, Trinh Vu
2009-02-01
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.
Estimating the Correlation in Bivariate Normal Data with Known Variances and Small Sample Sizes1
Fosdick, Bailey K.; Raftery, Adrian E.
2013-01-01
We consider the problem of estimating the correlation in bivariate normal data when the means and variances are assumed known, with emphasis on the small sample case. We consider eight different estimators, several of them considered here for the first time in the literature. In a simulation study, we found that Bayesian estimators using the uniform and arc-sine priors outperformed several empirical and exact or approximate maximum likelihood estimators in small samples. The arc-sine prior did better for large values of the correlation. For testing whether the correlation is zero, we found that Bayesian hypothesis tests outperformed significance tests based on the empirical and exact or approximate maximum likelihood estimators considered in small samples, but that all tests performed similarly for sample size 50. These results lead us to suggest using the posterior mean with the arc-sine prior to estimate the correlation in small samples when the variances are assumed known. PMID:23378667
Enzymatic Kinetic Isotope Effects from First-Principles Path Sampling Calculations.
Varga, Matthew J; Schwartz, Steven D
2016-04-12
In this study, we develop and test a method to determine the rate of particle transfer and kinetic isotope effects in enzymatic reactions, specifically yeast alcohol dehydrogenase (YADH), from first-principles. Transition path sampling (TPS) and normal mode centroid dynamics (CMD) are used to simulate these enzymatic reactions without knowledge of their reaction coordinates and with the inclusion of quantum effects, such as zero-point energy and tunneling, on the transferring particle. Though previous studies have used TPS to calculate reaction rate constants in various model and real systems, it has not been applied to a system as large as YADH. The calculated primary H/D kinetic isotope effect agrees with previously reported experimental results, within experimental error. The kinetic isotope effects calculated with this method correspond to the kinetic isotope effect of the transfer event itself. The results reported here show that the kinetic isotope effects calculated from first-principles, purely for barrier passage, can be used to predict experimental kinetic isotope effects in enzymatic systems.
ERIC Educational Resources Information Center
Shieh, Gwowen
2006-01-01
This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…
Tsai, Pei-Chien; Bell, Jordana T
2015-01-01
Background: Epigenome-wide association scans (EWAS) are under way for many complex human traits, but EWAS power has not been fully assessed. We investigate power of EWAS to detect differential methylation using case-control and disease-discordant monozygotic (MZ) twin designs with genome-wide DNA methylation arrays. Methods and Results: We performed simulations to estimate power under the case-control and discordant MZ twin EWAS study designs, under a range of epigenetic risk effect sizes and conditions. For example, to detect a 10% mean methylation difference between affected and unaffected subjects at a genome-wide significance threshold of P = 1 × 10−6, 98 MZ twin pairs were required to reach 80% EWAS power, and 112 cases and 112 controls pairs were needed in the case-control design. We also estimated the minimum sample size required to reach 80% EWAS power under both study designs. Our analyses highlighted several factors that significantly influenced EWAS power, including sample size, epigenetic risk effect size, the variance of DNA methylation at the locus of interest and the correlation in DNA methylation patterns within the twin sample. Conclusions: We provide power estimates for array-based DNA methylation EWAS under case-control and disease-discordant MZ twin designs, and explore multiple factors that impact on EWAS power. Our results can help guide EWAS experimental design and interpretation for future epigenetic studies. PMID:25972603
Estimating the Size of Populations at High Risk for HIV Using Respondent-Driven Sampling Data
Handcock, Mark S.; Gile, Krista J.; Mar, Corinne M.
2015-01-01
Summary The study of hard-to-reach populations presents significant challenges. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader sampling frames. This is especially true of populations at high risk for HIV/AIDS. Respondent-driven sampling (RDS) is often used in such settings with the primary goal of estimating the prevalence of infection. In such populations, the number of people at risk for infection and the number of people infected are of fundamental importance. This article presents a case-study of the estimation of the size of the hard-to-reach population based on data collected through RDS. We study two populations of female sex workers and men-who-have-sex-with-men in El Salvador. The approach is Bayesian and we consider different forms of prior information, including using the UNAIDS population size guidelines for this region. We show that the method is able to quantify the amount of information on population size available in RDS samples. As separate validation, we compare our results to those estimated by extrapolating from a capture–recapture study of El Salvadorian cities. The results of our case-study are largely comparable to those of the capture–recapture study when they differ from the UNAIDS guidelines. Our method is widely applicable to data from RDS studies and we provide a software package to facilitate this. PMID:25585794
NASA Technical Reports Server (NTRS)
Cavalleri, R. J.; Agnone, A. M.
1972-01-01
A computer program for calculating internal supersonic flow fields with chemical reactions and shock waves typical of supersonic combustion chambers with either wall or mid-stream injectors is described. The usefulness and limitations of the program are indicated. The program manual and listing are presented along with a sample calculation.
Pan, Feng; Tao, Guohua
2013-03-01
Full semiclassical (SC) initial value representation (IVR) for time correlation functions involves a double phase space average over a set of two phase points, each of which evolves along a classical path. Conventionally, the two initial phase points are sampled independently for all degrees of freedom (DOF) in the Monte Carlo procedure. Here, we present an efficient importance sampling scheme by including the path correlation between the two initial phase points for the bath DOF, which greatly improves the performance of the SC-IVR calculations for large molecular systems. Satisfactory convergence in the study of quantum coherence in vibrational relaxation has been achieved for a benchmark system-bath model with up to 21 DOF.
Multiple Approaches to Down Sizing of the Lunar Sample Return Collection
NASA Technical Reports Server (NTRS)
Lofgren, Gary E.; Horz, F.
2010-01-01
Future Lunar missions are planned for at least 7 days, significantly longer than the 3 days of the later Apollo missions. The last of those missions, A-17, returned 111 kg of samples plus another 20 kg of containers. The current Constellation program requirements for return weight for science is 100 kg with the hope of raising that limit to near 250 kg including containers and other non-geological materials. The estimated return weight for rock and soil samples will, at best, be about 175 kg. One method proposed to accomplish down-sizing of the collection is the use of a Geo-Lab in the lunar habitat to complete a preliminary examination of selected samples and facilitate prioritizing the return samples.
Srivastava, S; Das, I; Cheng, C
2014-06-01
Purpose: IMRT has become standard of care for complex treatments to optimize dose to target and spare normal tissues. However, the impact of calculation grid size is not widely known especially dose distribution, tumor control probability (TCP) and normal tissue complication probability (NTCP) which is investigated in this study. Methods: Ten head and neck IMRT patients treated with 6 MV photons were chosen for this study. Using Eclipse TPS, treatment plans were generated for different grid sizes in the range 1–5 mm for the same optimization criterion with specific dose-volume constraints. The dose volume histogram (DVH) was calculated for all IMRT plans and dosimetric data were compared. ICRU-83 dose points such as D2%, D50%, D98%, as well as the homogeneity and conformity indices (HI, CI) were calculated. In addition, TCP and NTCP were calculated from DVH data. Results: The PTV mean dose and TCP decreases with increasing grid size with an average decrease in mean dose by 2% and TCP by 3% respectively. Increasing grid size from 1–5 mm grid size, the average mean dose and NTCP for left parotid was increased by 6.0% and 8.0% respectively. Similar patterns were observed for other OARs such as cochlea, parotids and spinal cord. The HI increases up to 60% and CI decreases on average by 3.5% between 1 and 5 mm grid that resulted in decreased TCP and increased NTCP values. The number of points meeting the gamma criteria of ±3% dose difference and ±3mm DTA was higher with a 1 mm on average (97.2%) than with a 5 mm grid (91.3%). Conclusion: A smaller calculation grid provides superior dosimetry with improved TCP and reduced NTCP values. The effect is more pronounced for smaller OARs. Thus, the smallest possible grid size should be used for accurate dose calculation especially in H and N planning.
Schmidt, Wolf-Peter; Genser, Bernd; Luby, Stephen P; Chalabi, Zaid
2011-08-01
There is an ongoing interest in studying the effect of common recurrent infections and conditions, such as diarrhoea, respiratory infections, and fever, on the nutritional status of children at risk of malnutrition. Epidemiological studies exploring this association need to measure infections with sufficient accuracy to minimize bias in the effect estimates. A versatile model of common recurrent infections was used for exploring how many repeated measurements of disease are required to maximize the power and logistical efficiency of studies investigating the effect of infectious diseases on malnutrition without compromising the validity of the estimates. Depending on the prevalence and distribution of disease within a population, 15-30 repeat measurements per child over one year should be sufficient to provide unbiased estimates of the association between infections and nutritional status. Less-frequent measurements lead to a bias in the effect size towards zero, especially if disease is rare. In contrast, recall error can lead to exaggerated effect sizes. Recall periods of three days or shorter may be preferable compared to longer recall periods. The results showed that accurate estimation of the association between recurrent infections and nutritional status required closer follow-up of study participants than studies using recurrent infections as an outcome measure. The findings of the study provide guidance for choosing an appropriate sampling strategy to explore this association.
Burnup calculations and chemical analysis of irradiated fuel samples studied in LWR-PROTEUS phase II
Grimm, P.; Guenther-Leopold, I.; Berger, H. D.
2006-07-01
The isotopic compositions of 5 UO{sub 2} samples irradiated in a Swiss PWR power plant, which were investigated in the LWR-PROTEUS Phase II programme, were calculated using the CASMO-4 and BOXER assembly codes. The burnups of the samples range from 50 to 90 MWd/kg. The results for a large number of actinide and fission product nuclides were compared to those of chemical analyses performed using a combination of chromatographic separation and mass spectrometry. A good agreement of calculated and measured concentrations is found for many of the nuclides investigated with both codes. The concentrations of the Pu isotopes are mostly predicted within {+-}10%, the two codes giving quite different results, except for {sup 242}Pu. Relatively significant deviations are found for some isotopes of Cs and Sm, and large discrepancies are observed for Eu and Gd. The overall quality of the predictions by the two codes is comparable, and the deviations from the experimental data do not generally increase with burnup. (authors)
Živković, Daniel; Steinrücken, Matthias; Song, Yun S.; Stephan, Wolfgang
2015-01-01
Advances in empirical population genetics have made apparent the need for models that simultaneously account for selection and demography. To address this need, we here study the Wright–Fisher diffusion under selection and variable effective population size. In the case of genic selection and piecewise-constant effective population sizes, we obtain the transition density by extending a recently developed method for computing an accurate spectral representation for a constant population size. Utilizing this extension, we show how to compute the sample frequency spectrum in the presence of genic selection and an arbitrary number of instantaneous changes in the effective population size. We also develop an alternate, efficient algorithm for computing the sample frequency spectrum using a moment-based approach. We apply these methods to answer the following questions: If neutrality is incorrectly assumed when there is selection, what effects does it have on demographic parameter estimation? Can the impact of negative selection be observed in populations that undergo strong exponential growth? PMID:25873633
NASA Technical Reports Server (NTRS)
Hirleman, E. D.; Oechsle, V.; Chigier, N. A.
1984-01-01
The response characteristics of laser diffraction particle sizing instruments were studied theoretically and experimentally. In particular, the extent of optical sample volume and the effects of receiving lens properties were investigated in detail. The experimental work was performed with a particle size analyzer using a calibration reticle containing a two-dimensional array of opaque circular disks on a glass substrate. The calibration slide simulated the forward-scattering characteristics of a Rosin-Rammler droplet size distribution. The reticle was analyzed with collection lenses of 63 mm, 100 mm, and 300 mm focal lengths using scattering inversion software that determined best-fit Rosin-Rammler size distribution parameters. The data differed from the predicted response for the reticle by about 10 percent. A set of calibration factor for the detector elements was determined that corrected for the nonideal response of the instrument. The response of the instrument was also measured as a function of reticle position, and the results confirmed a theoretical optical sample volume model presented here.
A contemporary decennial global Landsat sample of changing agricultural field sizes
NASA Astrophysics Data System (ADS)
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
Type-II generalized family-wise error rate formulas with application to sample size determination.
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. PMID:26914402
Jiang, Shengyu; Wang, Chun; Weiss, David J
2016-01-01
Likert types of rating scales in which a respondent chooses a response from an ordered set of response options are used to measure a wide variety of psychological, educational, and medical outcome variables. The most appropriate item response theory model for analyzing and scoring these instruments when they provide scores on multiple scales is the multidimensional graded response model (MGRM) A simulation study was conducted to investigate the variables that might affect item parameter recovery for the MGRM. Data were generated based on different sample sizes, test lengths, and scale intercorrelations. Parameter estimates were obtained through the flexMIRT software. The quality of parameter recovery was assessed by the correlation between true and estimated parameters as well as bias and root-mean-square-error. Results indicated that for the vast majority of cases studied a sample size of N = 500 provided accurate parameter estimates, except for tests with 240 items when 1000 examinees were necessary to obtain accurate parameter estimates. Increasing sample size beyond N = 1000 did not increase the accuracy of MGRM parameter estimates. PMID:26903916
Quantifying Density Fluctuations in Volumes of All Shapes and Sizes Using Indirect Umbrella Sampling
NASA Astrophysics Data System (ADS)
Patel, Amish J.; Varilly, Patrick; Chandler, David; Garde, Shekhar
2011-10-01
Water density fluctuations are an important statistical mechanical observable and are related to many-body correlations, as well as hydrophobic hydration and interactions. Local water density fluctuations at a solid-water surface have also been proposed as a measure of its hydrophobicity. These fluctuations can be quantified by calculating the probability, P v ( N), of observing N waters in a probe volume of interest v. When v is large, calculating P v ( N) using molecular dynamics simulations is challenging, as the probability of observing very few waters is exponentially small, and the standard procedure for overcoming this problem (umbrella sampling in N) leads to undesirable impulsive forces. Patel et al. (J. Phys. Chem. B 114:1632, 2010) have recently developed an indirect umbrella sampling (INDUS) method, that samples a coarse-grained particle number to obtain P v ( N) in cuboidal volumes. Here, we present and demonstrate an extension of that approach to volumes of other basic shapes, like spheres and cylinders, as well as to collections of such volumes. We further describe the implementation of INDUS in the NPT ensemble and calculate P v ( N) distributions over a broad range of pressures. Our method may be of particular interest in characterizing the hydrophobicity of interfaces of proteins, nanotubes and related systems.
Ge, Yunfei; Zhang, Yuan; Booth, Jamie A; Weaver, Jonathan M R; Dobson, Phillip S
2016-08-12
We report a method for quantifying scanning thermal microscopy (SThM) probe-sample thermal interactions in air using a novel temperature calibration device. This new device has been designed, fabricated and characterised using SThM to provide an accurate and spatially variable temperature distribution that can be used as a temperature reference due to its unique design. The device was characterised by means of a microfabricated SThM probe operating in passive mode. This data was interpreted using a heat transfer model, built to describe the thermal interactions during a SThM thermal scan. This permitted the thermal contact resistance between the SThM tip and the device to be determined as 8.33 × 10(5) K W(-1). It also permitted the probe-sample contact radius to be clarified as being the same size as the probe's tip radius of curvature. Finally, the data were used in the construction of a lumped-system steady state model for the SThM probe and its potential applications were addressed. PMID:27363896
NASA Astrophysics Data System (ADS)
Ge, Yunfei; Zhang, Yuan; Booth, Jamie A.; Weaver, Jonathan M. R.; Dobson, Phillip S.
2016-08-01
We report a method for quantifying scanning thermal microscopy (SThM) probe-sample thermal interactions in air using a novel temperature calibration device. This new device has been designed, fabricated and characterised using SThM to provide an accurate and spatially variable temperature distribution that can be used as a temperature reference due to its unique design. The device was characterised by means of a microfabricated SThM probe operating in passive mode. This data was interpreted using a heat transfer model, built to describe the thermal interactions during a SThM thermal scan. This permitted the thermal contact resistance between the SThM tip and the device to be determined as 8.33 × 105 K W-1. It also permitted the probe-sample contact radius to be clarified as being the same size as the probe’s tip radius of curvature. Finally, the data were used in the construction of a lumped-system steady state model for the SThM probe and its potential applications were addressed.
NASA Astrophysics Data System (ADS)
Ge, Yunfei; Zhang, Yuan; Booth, Jamie A.; Weaver, Jonathan M. R.; Dobson, Phillip S.
2016-08-01
We report a method for quantifying scanning thermal microscopy (SThM) probe–sample thermal interactions in air using a novel temperature calibration device. This new device has been designed, fabricated and characterised using SThM to provide an accurate and spatially variable temperature distribution that can be used as a temperature reference due to its unique design. The device was characterised by means of a microfabricated SThM probe operating in passive mode. This data was interpreted using a heat transfer model, built to describe the thermal interactions during a SThM thermal scan. This permitted the thermal contact resistance between the SThM tip and the device to be determined as 8.33 × 105 K W‑1. It also permitted the probe–sample contact radius to be clarified as being the same size as the probe’s tip radius of curvature. Finally, the data were used in the construction of a lumped-system steady state model for the SThM probe and its potential applications were addressed.
Sub-sampling genetic data to estimate black bear population size: A case study
Tredick, C.A.; Vaughan, M.R.; Stauffer, D.F.; Simek, S.L.; Eason, T.
2007-01-01
Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the southeastern United States to explore how reducing costs of analysis by sub-sampling affected precision and accuracy of resulting population estimates. We used several sub-sampling scenarios to create subsets of the full datasets and compared summary statistics, population estimates, and precision of estimates generated from these subsets to estimates generated from the complete datasets. Our results suggested that bias and precision of estimates improved as the proportion of total samples used increased, and heterogeneity models (e.g., Mh[CHAO]) were more robust to reduced sample sizes than other models (e.g., behavior models). We recommend that only high-quality samples (>5 hair follicles) be used when budgets are constrained, and efforts should be made to maximize capture and recapture rates in the field.
Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors
Riva-Murray, Karen; Bradley, Paul M.; Journey, Celeste A.; Brigham, Mark E.; Scudder Eikenberry, Barbara C.; Knightes, Christopher; Button, Daniel T.
2013-01-01
Mercury (Hg) bioaccumulation factors (BAFs) for game fishes are widely employed for monitoring, assessment, and regulatory purposes. Mercury BAFs are calculated as the fish Hg concentration (Hgfish) divided by the water Hg concentration (Hgwater) and, consequently, are sensitive to sampling and analysis artifacts for fish and water. We evaluated the influence of water sample timing, filtration, and mercury species on the modeled relation between game fish and water mercury concentrations across 11 streams and rivers in five states in order to identify optimum Hgwater sampling approaches. Each model included fish trophic position, to account for a wide range of species collected among sites, and flow-weighted Hgwater estimates. Models were evaluated for parsimony, using Akaike’s Information Criterion. Better models included filtered water methylmercury (FMeHg) or unfiltered water methylmercury (UMeHg), whereas filtered total mercury did not meet parsimony requirements. Models including mean annual FMeHg were superior to those with mean FMeHg calculated over shorter time periods throughout the year. FMeHg models including metrics of high concentrations (80th percentile and above) observed during the year performed better, in general. These higher concentrations occurred most often during the growing season at all sites. Streamflow was significantly related to the probability of achieving higher concentrations during the growing season at six sites, but the direction of influence varied among sites. These findings indicate that streamwater Hg collection can be optimized by evaluating site-specific FMeHg - UMeHg relations, intra-annual temporal variation in their concentrations, and streamflow-Hg dynamics.
Küme, Tuncay; Şişman, Ali Rıza; Solak, Ahmet; Tuğlu, Birsen; Çinkooğlu, Burcu; Çoker, Canan
2012-01-01
Introductıon: We evaluated the effect of different syringe volume, needle size and sample volume on blood gas analysis in syringes washed with heparin. Materials and methods: In this multi-step experimental study, percent dilution ratios (PDRs) and final heparin concentrations (FHCs) were calculated by gravimetric method for determining the effect of syringe volume (1, 2, 5 and 10 mL), needle size (20, 21, 22, 25 and 26 G) and sample volume (0.5, 1, 2, 5 and 10 mL). The effect of different PDRs and FHCs on blood gas and electrolyte parameters were determined. The erroneous results from nonstandardized sampling were evaluated according to RiliBAK’s TEa. Results: The increase of PDRs and FHCs was associated with the decrease of syringe volume, the increase of needle size and the decrease of sample volume: from 2.0% and 100 IU/mL in 10 mL-syringe to 7.0% and 351 IU/mL in 1 mL-syringe; from 4.9% and 245 IU/mL in 26G to 7.6% and 380 IU/mL in 20 G with combined 1 mL syringe; from 2.0% and 100 IU/mL in full-filled sample to 34% and 1675 IU/mL in 0.5 mL suctioned sample into 10 mL-syringe. There was no statistical difference in pH; but the percent decreasing in pCO2, K+, iCa2+, iMg2+; the percent increasing in pO2 and Na+ were statistical significance compared to samples full-filled in syringes. The all changes in pH and pO2 were acceptable; but the changes in pCO2, Na+, K+ and iCa2+ were unacceptable according to TEa limits except fullfilled-syringes. Conclusions: The changes in PDRs and FHCs due nonstandardized sampling in syringe washed with liquid heparin give rise to erroneous test results for pCO2 and electrolytes. PMID:22838185
NASA Astrophysics Data System (ADS)
Jha, Anjani K.
Particulate materials are routinely handled in large quantities by industries such as, agriculture, electronic, ceramic, chemical, cosmetic, fertilizer, food, nutraceutical, pharmaceutical, power, and powder metallurgy. These industries encounter segregation due to the difference in physical and mechanical properties of particulates. The general goal of this research was to study percolation segregation in multi-size and multi-component particulate mixtures, especially measurement, sampling, and modeling. A second generation primary segregation shear cell (PSSC-II), an industrial vibrator, a true cubical triaxial tester, and two samplers (triers) were used as primary test apparatuses for quantifying segregation and flowability; furthermore, to understand and propose strategies to mitigate segregation in particulates. Toward this end, percolation segregation in binary, ternary, and quaternary size mixtures for two particulate types: urea (spherical) and potash (angular) were studied. Three coarse size ranges 3,350-4,000 mum (mean size = 3,675 mum), 2,800-3,350 mum (3,075 mum), and 2,360-2,800 mum (2,580 mum) and three fines size ranges 2,000-2,360 mum (2,180 mum), 1,700-2,000 mum (1,850 mum), and 1,400-1,700 mum (1,550 mum) for angular-shaped and spherical-shaped were selected for tests. Since the fines size 1,550 mum of urea was not available in sufficient quantity; therefore, it was not included in tests. Percolation segregation in fertilizer bags was tested also at two vibration frequencies of 5 Hz and 7Hz. The segregation and flowability of binary mixtures of urea under three equilibrium relative humidities (40%, 50%, and 60%) were also tested. Furthermore, solid fertilizer sampling was performed to compare samples obtained from triers of opening widths 12.7 mm and 19.1 mm and to determine size segregation in blend fertilizers. Based on experimental results, the normalized segregation rate (NSR) of binary mixtures was dependent on size ratio, mixing ratio
Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials
Verhey, Leonard H.; Signori, Alessio; Arnold, Douglas L.; Bar-Or, Amit; Sadovnick, A. Dessa; Marrie, Ruth Ann; Banwell, Brenda
2013-01-01
Objective: To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints. Methods: Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best-fitting model of new T2 lesion count, number of relapses, or TTFR, under various assumptions of the effect size, trial duration, and model parameters. Results: Assuming a 50% reduction in new T2 lesions over 6 months, 90 patients/arm are required, whereas 165 patients/arm are required for a 40% treatment effect. Sample sizes for 2-year trials using relapse-related endpoints are lower than that for 1-year trials. For 2-year trials and a conservative assumption of overdispersion (ϑ), sample sizes range from 70 patients/arm (using ARR) to 105 patients/arm (TTFR) for a 50% reduction in relapses, and 230 patients/arm (ARR) to 365 patients/arm (TTFR) for a 30% relapse reduction. Assuming a less conservative ϑ, 2-year trials using ARR require 45 patients/arm (60 patients/arm for TTFR) for a 50% reduction in relapses and 145 patients/arm (200 patients/arm for TTFR) for a 30% reduction. Conclusion: Six-month phase II trials using new T2 lesion count as an endpoint are feasible in the pediatric MS population; however, trials powered on ARR or TTFR will need to be 2 years in duration and will require multicentered collaboration. PMID:23966255
Forest inventory using multistage sampling with probability proportional to size. [Brazil
NASA Technical Reports Server (NTRS)
Parada, N. D. J. (Principal Investigator); Lee, D. C. L.; Hernandezfilho, P.; Shimabukuro, Y. E.; Deassis, O. R.; Demedeiros, J. S.
1984-01-01
A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.
Subspace Leakage Analysis and Improved DOA Estimation With Small Sample Size
NASA Astrophysics Data System (ADS)
Shaghaghi, Mahdi; Vorobyov, Sergiy A.
2015-06-01
Classical methods of DOA estimation such as the MUSIC algorithm are based on estimating the signal and noise subspaces from the sample covariance matrix. For a small number of samples, such methods are exposed to performance breakdown, as the sample covariance matrix can largely deviate from the true covariance matrix. In this paper, the problem of DOA estimation performance breakdown is investigated. We consider the structure of the sample covariance matrix and the dynamics of the root-MUSIC algorithm. The performance breakdown in the threshold region is associated with the subspace leakage where some portion of the true signal subspace resides in the estimated noise subspace. In this paper, the subspace leakage is theoretically derived. We also propose a two-step method which improves the performance by modifying the sample covariance matrix such that the amount of the subspace leakage is reduced. Furthermore, we introduce a phenomenon named as root-swap which occurs in the root-MUSIC algorithm in the low sample size region and degrades the performance of the DOA estimation. A new method is then proposed to alleviate this problem. Numerical examples and simulation results are given for uncorrelated and correlated sources to illustrate the improvement achieved by the proposed methods. Moreover, the proposed algorithms are combined with the pseudo-noise resampling method to further improve the performance.
Particle size conditions water repellency in sand samples hydrophobized with stearic acid
NASA Astrophysics Data System (ADS)
González-Peñaloza, F. A.; Jordán, A.; Bellinfante, N.; Bárcenas-Moreno, G.; Mataix-Solera, J.; Granged, A. J. P.; Gil, J.; Zavala, L. M.
2012-04-01
The main objective of this research is to study the effects of particle size and soil moisture on water repellency (WR) from hydrophobized sand samples. Quartz sand samples were collected from the top 15 cm of sandy soils, homogenised and divided in different sieve fractions: 0.5 - 2 mm (coarse sand), 0.25 - 0.5 mm (medium sand), and 0.05 - 0.25 mm (fine sand). WR was artificially induced in sand samples using different concentrations of stearic acid (SA; 0.5, 1, 5, 10, 20 and 30 g kg-1). Sand samples were placed in Petri plates and moistened with distilled water until 10% water content in weight. After a period of 30 min, soil WR was determined using the water drop penetration time (WDPT) test. A set of sub-samples was placed in an oven (50 oC) during the experimental period, and the rest was left air-drying at standard laboratory conditions. Water repellent soil samples were used as control, and the same treatments were applied. WR was determined every 24 h. No changes in WR were observed after 6 days of treatment. As expected, air-dried fine sand samples showed WR increasing with SA concentration and decreasing with soil moisture. In contrast, oven-dried samples remained wettable at SA concentrations below 5 g kg-1. Fine sand oven-dried samples showed extreme WR after just one day of treatment, but air-dried samples did not show extreme repellency until three days after treatment. SA concentrations above 5 g kg-1 always induced extreme WR. Medium sand air-dried samples showed hydrophilic properties when moist and low SA concentration (£1 g kg-1), but strong to extreme WR was induced by higher SA concentrations. In the case of oven-dried samples, medium sand showed severe to extreme WR regardless of soil moisture. Coarse sand showed the longest WDPTs, independently of soil moisture content or SA concentration. This behaviour may be caused by super-hydrophobicity. Also, it is suggested that movements of sand particles during wetting, contribute to expose new
Statistical characterization of a large geochemical database and effect of sample size
Zhang, C.; Manheim, F. T.; Hinde, J.; Grossman, J.N.
2005-01-01
smaller numbers of data points showed that few elements passed standard statistical tests for normality or log-normality until sample size decreased to a few hundred data points. Large sample size enhances the power of statistical tests, and leads to rejection of most statistical hypotheses for real data sets. For large sample sizes (e.g., n > 1000), graphical methods such as histogram, stem-and-leaf, and probability plots are recommended for rough judgement of probability distribution if needed. ?? 2005 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Holmes, Jesse Curtis
established that depends on uncertainties in the physics models and methodology employed to produce the DOS. Through Monte Carlo sampling of perturbations from the reference phonon spectrum, an S(alpha, beta) covariance matrix may be generated. In this work, density functional theory and lattice dynamics in the harmonic approximation are used to calculate the phonon DOS for hexagonal crystalline graphite. This form of graphite is used as an example material for the purpose of demonstrating procedures for analyzing, calculating and processing thermal neutron inelastic scattering uncertainty information. Several sources of uncertainty in thermal neutron inelastic scattering calculations are examined, including sources which cannot be directly characterized through a description of the phonon DOS uncertainty, and their impacts are evaluated. Covariances for hexagonal crystalline graphite S(alpha, beta) data are quantified by coupling the standard methodology of LEAPR with a Monte Carlo sampling process. The mechanics of efficiently representing and processing this covariance information is also examined. Finally, with appropriate sensitivity information, it is shown that an S(alpha, beta) covariance matrix can be propagated to generate covariance data for integrated cross sections, secondary energy distributions, and coupled energy-angle distributions. This approach enables a complete description of thermal neutron inelastic scattering cross section uncertainties which may be employed to improve the simulation of nuclear systems.
Saccenti, Edoardo; Timmerman, Marieke E
2016-08-01
Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA. PMID:27322847
Saccenti, Edoardo; Timmerman, Marieke E
2016-08-01
Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA.
Adjustable virtual pore-size filter for automated sample preparation using acoustic radiation force
Jung, B; Fisher, K; Ness, K; Rose, K; Mariella, R
2008-05-22
We present a rapid and robust size-based separation method for high throughput microfluidic devices using acoustic radiation force. We developed a finite element modeling tool to predict the two-dimensional acoustic radiation force field perpendicular to the flow direction in microfluidic devices. Here we compare the results from this model with experimental parametric studies including variations of the PZT driving frequencies and voltages as well as various particle sizes and compressidensities. These experimental parametric studies also provide insight into the development of an adjustable 'virtual' pore-size filter as well as optimal operating conditions for various microparticle sizes. We demonstrated the separation of Saccharomyces cerevisiae and MS2 bacteriophage using acoustic focusing. The acoustic radiation force did not affect the MS2 viruses, and their concentration profile remained unchanged. With optimized design of our microfluidic flow system we were able to achieve yields of > 90% for the MS2 with > 80% of the S. cerevisiae being removed in this continuous-flow sample preparation device.
Yamano, N.; Brockmann, J.E.
1989-05-01
This report describes the features and use of the Aerosol Sampling and Transport Efficiency Calculation (ASTEC) Code. The ASTEC code has been developed to assess aerosol transport efficiency source term experiments at Sandia National Laboratories. This code also has broad application for aerosol sampling and transport efficiency calculations in general as well as for aerosol transport considerations in nuclear reactor safety issues. 32 refs., 31 figs., 7 tabs.
Stevens, June; Bryant, Maria; Wang, Chin-Hua; Cai, Jianwen; Bentley, Margaret E.
2012-01-01
Measurement of the home food environment is of interest to researchers because it affects food intake and is a feasible target for nutrition interventions. The objective of this study was to provide estimates to aid the calculation of sample size and number of repeated measures needed in studies of nutrients and foods in the home. We inventoried all foods in the homes of 80 African-American first-time mothers and determined 6 nutrient-related attributes. Sixty-three households were measured 3 times, 11 were measured twice, and 6 were measured once, producing 217 inventories collected at ~2-mo intervals. Following log transformations, number of foods, total energy, dietary fiber, and fat required only one measurement per household to achieve a correlation of 0.8 between the observed and true values. For percent energy from fat and energy density, 3 and 2 repeated measurements, respectively, were needed to achieve a correlation of 0.8. A sample size of 252 was needed to detect a difference of 25% of an SD in total energy with one measurement compared with 213 with 3 repeated measurements. Macronutrient characteristics of household foods appeared relatively stable over a 6-mo period and only 1 or 2 repeated measures of households may be sufficient for an efficient study design. PMID:22535753
Stevens, June; Bryant, Maria; Wang, Chin-Hua; Cai, Jianwen; Bentley, Margaret E
2012-06-01
Measurement of the home food environment is of interest to researchers because it affects food intake and is a feasible target for nutrition interventions. The objective of this study was to provide estimates to aid the calculation of sample size and number of repeated measures needed in studies of nutrients and foods in the home. We inventoried all foods in the homes of 80 African-American first-time mothers and determined 6 nutrient-related attributes. Sixty-three households were measured 3 times, 11 were measured twice, and 6 were measured once, producing 217 inventories collected at ~2-mo intervals. Following log transformations, number of foods, total energy, dietary fiber, and fat required only one measurement per household to achieve a correlation of 0.8 between the observed and true values. For percent energy from fat and energy density, 3 and 2 repeated measurements, respectively, were needed to achieve a correlation of 0.8. A sample size of 252 was needed to detect a difference of 25% of an SD in total energy with one measurement compared with 213 with 3 repeated measurements. Macronutrient characteristics of household foods appeared relatively stable over a 6-mo period and only 1 or 2 repeated measures of households may be sufficient for an efficient study design.
Stevens, June; Bryant, Maria; Wang, Chin-Hua; Cai, Jianwen; Bentley, Margaret E
2012-06-01
Measurement of the home food environment is of interest to researchers because it affects food intake and is a feasible target for nutrition interventions. The objective of this study was to provide estimates to aid the calculation of sample size and number of repeated measures needed in studies of nutrients and foods in the home. We inventoried all foods in the homes of 80 African-American first-time mothers and determined 6 nutrient-related attributes. Sixty-three households were measured 3 times, 11 were measured twice, and 6 were measured once, producing 217 inventories collected at ~2-mo intervals. Following log transformations, number of foods, total energy, dietary fiber, and fat required only one measurement per household to achieve a correlation of 0.8 between the observed and true values. For percent energy from fat and energy density, 3 and 2 repeated measurements, respectively, were needed to achieve a correlation of 0.8. A sample size of 252 was needed to detect a difference of 25% of an SD in total energy with one measurement compared with 213 with 3 repeated measurements. Macronutrient characteristics of household foods appeared relatively stable over a 6-mo period and only 1 or 2 repeated measures of households may be sufficient for an efficient study design. PMID:22535753
NASA Astrophysics Data System (ADS)
Zommer, L.; Jablonski, A.
2010-07-01
Recent advances in nanotechnology are a driving force for the improvement of lateral resolution in advanced analytical techniques such as scanning electron microscopy or scanning Auger microscopy (SAM). Special samples with multilayers which are perpendicular to their surface are presently proposed for testing the lateral resolution, as discussed in recent works of Senoner et al (2004 Surf. Interface Anal. 36 1423). The relevant experiment needs a theoretical description based on recent progress in the theory. Monte Carlo simulations of electron trajectories make possible an accurate description of the considered system. We selected exemplary samples, with layers perpendicular to the surface. The layer materials are elemental solids with high, medium and low atomic numbers, i.e. Au|Cu|Au and Au|Si|Au. For these systems calculations of the Auger current versus beam position were performed. We found that, for a system with layers consisting of elements of considerably different atomic numbers, the relation can have an unexpected extreme. This observation can be important in analysis of SAM pictures.
An In Situ Method for Sizing Insoluble Residues in Precipitation and Other Aqueous Samples
Axson, Jessica L.; Creamean, Jessie M.; Bondy, Amy L.; Capracotta, Sonja S.; Warner, Katy Y.; Ault, Andrew P.
2015-01-01
Particles are frequently incorporated into clouds or precipitation, influencing climate by acting as cloud condensation or ice nuclei, taking up coatings during cloud processing, and removing species through wet deposition. Many of these particles, particularly ice nuclei, can remain suspended within cloud droplets/crystals as insoluble residues. While previous studies have measured the soluble or bulk mass of species within clouds and precipitation, no studies to date have determined the number concentration and size distribution of insoluble residues in precipitation or cloud water using in situ methods. Herein, for the first time we demonstrate that Nanoparticle Tracking Analysis (NTA) is a powerful in situ method for determining the total number concentration, number size distribution, and surface area distribution of insoluble residues in precipitation, both of rain and melted snow. The method uses 500 μL or less of liquid sample and does not require sample modification. Number concentrations for the insoluble residues in aqueous precipitation samples ranged from 2.0–3.0(±0.3)×108 particles cm−3, while surface area ranged from 1.8(±0.7)–3.2(±1.0)×107 μm2 cm−3. Number size distributions peaked between 133–150 nm, with both single and multi-modal character, while surface area distributions peaked between 173–270 nm. Comparison with electron microscopy of particles up to 10 μm show that, by number, > 97% residues are <1 μm in diameter, the upper limit of the NTA. The range of concentration and distribution properties indicates that insoluble residue properties vary with ambient aerosol concentrations, cloud microphysics, and meteorological dynamics. NTA has great potential for studying the role that insoluble residues play in critical atmospheric processes. PMID:25705069
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA
Kelly, Brendan J.; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D.; Collman, Ronald G.; Bushman, Frederic D.; Li, Hongzhe
2015-01-01
Motivation: The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence–absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. Results: We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. Availability and implementation: http://github.com/brendankelly/micropower. Contact: brendank@mail.med.upenn.edu or hongzhe@upenn.edu PMID:25819674
ERIC Educational Resources Information Center
Ross, Sarah Gwen
2012-01-01
Response to intervention (RTI) is increasingly being used in educational settings to make high-stakes, special education decisions. Because of this, the accurate use and analysis of single-case designs to monitor intervention effectiveness has become important to the RTI process. Effect size methods for single-case designs provide a useful way to…
On the calculation of the gauge volume size for energy-dispersive X-ray diffraction.
Rowles, Matthew R
2011-11-01
Equations for the calculation of the dimensions of a gauge volume, also known as the active volume or diffraction lozenge, in an energy-dispersive diffraction experiment where the detector is collimated by two ideal slits have been developed. Equations are given for equatorially divergent and parallel incident X-ray beams, assuming negligible axial divergence. PMID:21997921
Reagan, Jennifer K; Selmic, Laura E; Garrett, Laura D; Singh, Kuldeep
2016-09-01
OBJECTIVE To evaluate effects of anatomic location, histologic processing, and sample size on shrinkage of excised canine skin samples. SAMPLE Skin samples from 15 canine cadavers. PROCEDURES Elliptical samples of the skin, underlying subcutaneous fat, and muscle fascia were collected from the head, hind limb, and lumbar region of each cadaver. Two samples (10 mm and 30 mm) were collected at each anatomic location of each cadaver (one from the left side and the other from the right side). Measurements of length, width, depth, and surface area were collected prior to excision (P1) and after fixation in neutral-buffered 10% formalin for 24 to 48 hours (P2). Length and width were also measured after histologic processing (P3). RESULTS Length and width decreased significantly at all anatomic locations and for both sample sizes at each processing stage. Hind limb samples had the greatest decrease in length, compared with results for samples obtained from other locations, across all processing stages for both sample sizes. The 30-mm samples had a greater percentage change in length and width between P1 and P2 than did the 10-mm samples. Histologic processing (P2 to P3) had a greater effect on the percentage shrinkage of 10-mm samples. For all locations and both sample sizes, percentage change between P1 and P3 ranged from 24.0% to 37.7% for length and 18.0% to 22.8% for width. CONCLUSIONS AND CLINICAL RELEVANCE Histologic processing, anatomic location, and sample size affected the degree of shrinkage of a canine skin sample from excision to histologic assessment. PMID:27580116
Berlinger, B; Bugge, M D; Ulvestad, B; Kjuus, H; Kandler, K; Ellingsen, D G
2015-12-01
Air samples were collected by personal sampling with five stage Sioutas cascade impactors and respirable cyclones in parallel among tappers and crane operators in two manganese (Mn) alloy smelters in Norway to investigate PM fractions. The mass concentrations of PM collected by using the impactors and the respirable cyclones were critically evaluated by comparing the results of the parallel measurements. The geometric mean (GM) mass concentrations of the respirable fraction and the <10 μm PM fraction were 0.18 and 0.39 mg m(-3), respectively. Particle size distributions were determined using the impactor data in the range from 0 to 10 μm and by stationary measurements by using a scanning mobility particle sizer in the range from 10 to 487 nm. On average 50% of the particulate mass in the Mn alloy smelters was in the range from 2.5 to 10 μm, while the rest was distributed between the lower stages of the impactors. On average 15% of the particulate mass was found in the <0.25 μm PM fraction. The comparisons of the different PM fraction mass concentrations related to different work tasks or different workplaces, showed in many cases statistically significant differences, however, the particle size distribution of PM in the fraction <10 μm d(ae) was independent of the plant, furnace or work task. PMID:26498986
Fitts, Douglas A
2011-07-01
To obtain approval for the use vertebrate animals in research, an investigator must assure an ethics committee that the proposed number of animals is the minimum necessary to achieve a scientific goal. How does an investigator make that assurance? A power analysis is most accurate when the outcome is known before the study, which it rarely is. A 'pilot study' is appropriate only when the number of animals used is a tiny fraction of the numbers that will be invested in the main study because the data for the pilot animals cannot legitimately be used again in the main study without increasing the rate of type I errors (false discovery). Traditional significance testing requires the investigator to determine the final sample size before any data are collected and then to delay analysis of any of the data until all of the data are final. An investigator often learns at that point either that the sample size was larger than necessary or too small to achieve significance. Subjects cannot be added at this point in the study without increasing type I errors. In addition, journal reviewers may require more replications in quantitative studies than are truly necessary. Sequential stopping rules used with traditional significance tests allow incremental accumulation of data on a biomedical research problem so that significance, replicability, and use of a minimal number of animals can be assured without increasing type I errors.
Robust reverse engineering of dynamic gene networks under sample size heterogeneity.
Parikh, Ankur P; Wu, Wei; Xing, Eric P
2014-01-01
Simultaneously reverse engineering a collection of condition-specific gene networks from gene expression microarray data to uncover dynamic mechanisms is a key challenge in systems biology. However, existing methods for this task are very sensitive to variations in the size of the microarray samples across different biological conditions (which we term sample size heterogeneity in network reconstruction), and can potentially produce misleading results that can lead to incorrect biological interpretation. In this work, we develop a more robust framework that addresses this novel problem. Just like microarray measurements across conditions must undergo proper normalization on their magnitudes before entering subsequent analysis, we argue that networks across conditions also need to be "normalized" on their density when they are constructed, and we provide an algorithm that allows such normalization to be facilitated while estimating the networks. We show the quantitative advantages of our approach on synthetic and real data. Our analysis of a hematopoietic stem cell dataset reveals interesting results, some of which are confirmed by previously validated results.
ERIC Educational Resources Information Center
Foley, Brett Patrick
2010-01-01
The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using…
Johnson, David R; Bachan, Lauren K
2013-08-01
In a recent article, Regan, Lakhanpal, and Anguiano (2012) highlighted the lack of evidence for different relationship outcomes between arranged and love-based marriages. Yet the sample size (n = 58) used in the study is insufficient for making such inferences. This reply discusses and demonstrates how small sample sizes reduce the utility of this research.
ERIC Educational Resources Information Center
In'nami, Yo; Koizumi, Rie
2013-01-01
The importance of sample size, although widely discussed in the literature on structural equation modeling (SEM), has not been widely recognized among applied SEM researchers. To narrow this gap, we focus on second language testing and learning studies and examine the following: (a) Is the sample size sufficient in terms of precision and power of…
ERIC Educational Resources Information Center
Hedges, Larry V.
1984-01-01
If the quantitative result of a study is observed only when the mean difference is statistically significant, the observed mean difference, variance, and effect size are biased estimators of corresponding population parameters. The exact distribution of sample effect size and the maximum likelihood estimator of effect size are derived. (Author/BW)
Wang, Jixian
2010-09-01
Sample size reestimation (SSRE) provides a useful tool to change the sample size when an interim look reveals that the original sample size is inadequate. To control the overall type I error, for testing one hypothesis, several approaches have been proposed to construct a statistic so that its distribution is independent to the SSRE under the null hypothesis. We considered a similar approach for comparisons between multiple treatment arms and placebo, allowing the change of sample sizes in all arms depending on interim information. A construction of statistics similar to that for a single hypothesis test is proposed. When the changes of sample sizes in different arms are proportional, we show that one-step and stepwise Dunnett tests can be used directly on statistics constructed in the proposed way. The approach can also be applied to clinical trials with SSRE and treatment selection at interim. The proposed approach is evaluated with simulations under different situations.
Stepwise linear discriminant analysis in computer-aided diagnosis: the effect of finite sample size
NASA Astrophysics Data System (ADS)
Sahiner, Berkman; Chan, Heang-Ping; Petrick, Nicholas; Wagner, Robert F.; Hadjiiski, Lubomir M.
1999-05-01
In computer-aided diagnosis, a frequently-used approach is to first extract several potentially useful features from a data set. Effective features are then selected from this feature space, and a classifier is designed using the selected features. In this study, we investigated the effect of finite sample size on classifier accuracy when classifier design involves feature selection. The feature selection and classifier coefficient estimation stages of classifier design were implemented using stepwise feature selection and Fisher's linear discriminant analysis, respectively. The two classes used in our simulation study were assumed to have multidimensional Gaussian distributions, with a large number of features available for feature selection. We investigated the effect of different covariance matrices and means for the two classes on feature selection performance, and compared two strategies for sample space partitioning for classifier design and testing. Our results indicated that the resubstitution estimate was always optimistically biased, except in cases where too few features were selected by the stepwise procedure. When feature selection was performed using only the design samples, the hold-out estimate was always pessimistically biased. When feature selection was performed using the entire finite sample space, and the data was subsequently partitioned into design and test groups, the hold-out estimates could be pessimistically or optimistically biased, depending on the number of features available for selection, number of available samples, and their statistical distribution. All hold-out estimates exhibited a pessimistic bias when the parameters of the simulation were obtained from texture features extracted from mammograms in a previous study.
Monte Carlo sampling can be used to determine the size and shape of the steady-state flux space.
Wiback, Sharon J; Famili, Iman; Greenberg, Harvey J; Palsson, Bernhard Ø
2004-06-21
Constraint-based modeling results in a convex polytope that defines a solution space containing all possible steady-state flux distributions. The properties of this polytope have been studied extensively using linear programming to find the optimal flux distribution under various optimality conditions and convex analysis to define its extreme pathways (edges) and elementary modes. The work presented herein further studies the steady-state flux space by defining its hyper-volume. In low dimensions (i.e. for small sample networks), exact volume calculation algorithms were used. However, due to the #P-hard nature of the vertex enumeration and volume calculation problem in high dimensions, random Monte Carlo sampling was used to characterize the relative size of the solution space of the human red blood cell metabolic network. Distributions of the steady-state flux levels for each reaction in the metabolic network were generated to show the range of flux values for each reaction in the polytope. These results give insight into the shape of the high-dimensional solution space. The value of measuring uptake and secretion rates in shrinking the steady-state flux solution space is illustrated through singular value decomposition of the randomly sampled points. The V(max) of various reactions in the network are varied to determine the sensitivity of the solution space to the maximum capacity constraints. The methods developed in this study are suitable for testing the implication of additional constraints on a metabolic network system and can be used to explore the effects of single nucleotide polymorphisms (SNPs) on network capabilities. PMID:15178193
Mörlein, Daniel; Christensen, Rune Haubo Bojesen; Gertheiss, Jan
2015-02-01
To prevent impaired consumer acceptance due to insensitive sensory quality control, it is of primary importance to periodically validate the performance of the assessors. This communication show cases how the uncertainty of sensitivity and specificity estimates is influenced by the total number of assessed samples and the prevalence of positive (here: boar tainted) samples. Furthermore, a statistically sound approach to determining the sample size that is necessary for performance validation is provided. Results show that a small sample size is associated with large uncertainty, i.e., confidence intervals and thus compromising the point estimates for assessor sensitivity. In turn, to reliably identify sensitive assessors with sufficient test power, a large sample size is needed given a certain level of confidence. Easy-to-use tables for sample size estimations are provided. PMID:25460131
NASA Astrophysics Data System (ADS)
Pawcenis, Dominika; Koperska, Monika A.; Milczarek, Jakub M.; Łojewski, Tomasz; Łojewska, Joanna
2014-02-01
A direct goal of this paper was to improve the methods of sample preparation and separation for analyses of fibroin polypeptide with the use of size exclusion chromatography (SEC). The motivation for the study arises from our interest in natural polymers included in historic textile and paper artifacts, and is a logical response to the urgent need for developing rationale-based methods for materials conservation. The first step is to develop a reliable analytical tool which would give insight into fibroin structure and its changes caused by both natural and artificial ageing. To investigate the influence of preparation conditions, two sets of artificially aged samples were prepared (with and without NaCl in sample solution) and measured by the means of SEC with multi angle laser light scattering detector. It was shown that dialysis of fibroin dissolved in LiBr solution allows removal of the salt which destroys stacks chromatographic columns and prevents reproducible analyses. Salt rich (NaCl) water solutions of fibroin improved the quality of chromatograms.
What about N? A methodological study of sample-size reporting in focus group studies
2011-01-01
Background Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. Results We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96). Thirty seven (17%) studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Conclusions Based on these findings we suggest that journals adopt more stringent requirements for focus group method reporting. The often poor and
Ellery, Adam J; Baker, Ruth E; Simpson, Matthew J
2015-01-01
Random walk models are often used to interpret experimental observations of the motion of biological cells and molecules. A key aim in applying a random walk model to mimic an in vitro experiment is to estimate the Fickian diffusivity (or Fickian diffusion coefficient), D. However, many in vivo experiments are complicated by the fact that the motion of cells and molecules is hindered by the presence of obstacles. Crowded transport processes have been modeled using repeated stochastic simulations in which a motile agent undergoes a random walk on a lattice that is populated by immobile obstacles. Early studies considered the most straightforward case in which the motile agent and the obstacles are the same size. More recent studies considered stochastic random walk simulations describing the motion of an agent through an environment populated by obstacles of different shapes and sizes. Here, we build on previous simulation studies by analyzing a general class of lattice-based random walk models with agents and obstacles of various shapes and sizes. Our analysis provides exact calculations of the Fickian diffusivity, allowing us to draw conclusions about the role of the size, shape and density of the obstacles, as well as examining the role of the size and shape of the motile agent. Since our analysis is exact, we calculate D directly without the need for random walk simulations. In summary, we find that the shape, size and density of obstacles has a major influence on the exact Fickian diffusivity. Furthermore, our results indicate that the difference in diffusivity for symmetric and asymmetric obstacles is significant. PMID:26599468
Analyzing insulin samples by size-exclusion chromatography: a column degradation study.
Teska, Brandon M; Kumar, Amit; Carpenter, John F; Wempe, Michael F
2015-04-01
Investigating insulin analogs and probing their intrinsic stability at physiological temperature, we observed significant degradation in the size-exclusion chromatography (SEC) signal over a moderate number of insulin sample injections, which generated concerns about the quality of the separations. Therefore, our research goal was to identify the cause(s) for the observed signal degradation and attempt to mitigate the degradation in order to extend SEC column lifespan. In these studies, we used multiangle light scattering, nuclear magnetic resonance, and gas chromatography-mass spectrometry methods to evaluate column degradation. The results from these studies illustrate: (1) that zinc ions introduced by the insulin product produced the observed column performance issues; and (2) that including ethylenediaminetetraacetic acid, a zinc chelator, in the mobile phase helped to maintain column performance.
Willan, A R
2001-06-01
Stinnett and Mullahy recently introduced the concept of net health benefit as an alternative to cost-effectiveness ratios for the statistical analysis of patient-level data on the costs and health effects of competing interventions. Net health benefit addresses a number of problems associated with cost-effectiveness ratios by assuming a value for the willingness-to-pay for a unit of effectiveness. We extend the concept of net health benefit to demonstrate that standard statistical procedures can be used for the analysis, power, and sample size determinations of cost-effectiveness data. We also show that by varying the value of the willingness-to-pay, the point estimate and confidence interval for the incremental cost-effectiveness ratio can be determined. An example is provided.
A bootstrap test for comparing two variances: simulation of size and power in small samples.
Sun, Jiajing; Chernick, Michael R; LaBudde, Robert A
2011-11-01
An F statistic was proposed by Good and Chernick ( 1993 ) in an unpublished paper, to test the hypothesis of the equality of variances from two independent groups using the bootstrap; see Hall and Padmanabhan ( 1997 ), for a published reference where Good and Chernick ( 1993 ) is discussed. We look at various forms of bootstrap tests that use the F statistic to see whether any or all of them maintain the nominal size of the test over a variety of population distributions when the sample size is small. Chernick and LaBudde ( 2010 ) and Schenker ( 1985 ) showed that bootstrap confidence intervals for variances tend to provide considerably less coverage than their theoretical asymptotic coverage for skewed population distributions such as a chi-squared with 10 degrees of freedom or less or a log-normal distribution. The same difficulties may be also be expected when looking at the ratio of two variances. Since bootstrap tests are related to constructing confidence intervals for the ratio of variances, we simulated the performance of these tests when the population distributions are gamma(2,3), uniform(0,1), Student's t distribution with 10 degrees of freedom (df), normal(0,1), and log-normal(0,1) similar to those used in Chernick and LaBudde ( 2010 ). We find, surprisingly, that the results for the size of the tests are valid (reasonably close to the asymptotic value) for all the various bootstrap tests. Hence we also conducted a power comparison, and we find that bootstrap tests appear to have reasonable power for testing equivalence of variances.
Multicategory nets of single-layer perceptrons: complexity and sample-size issues.
Raudys, Sarunas; Kybartas, Rimantas; Zavadskas, Edmundas Kazimieras
2010-05-01
The standard cost function of multicategory single-layer perceptrons (SLPs) does not minimize the classification error rate. In order to reduce classification error, it is necessary to: 1) refuse the traditional cost function, 2) obtain near to optimal pairwise linear classifiers by specially organized SLP training and optimal stopping, and 3) fuse their decisions properly. To obtain better classification in unbalanced training set situations, we introduce the unbalance correcting term. It was found that fusion based on the Kulback-Leibler (K-L) distance and the Wu-Lin-Weng (WLW) method result in approximately the same performance in situations where sample sizes are relatively small. The explanation for this observation is by theoretically known verity that an excessive minimization of inexact criteria becomes harmful at times. Comprehensive comparative investigations of six real-world pattern recognition (PR) problems demonstrated that employment of SLP-based pairwise classifiers is comparable and as often as not outperforming the linear support vector (SV) classifiers in moderate dimensional situations. The colored noise injection used to design pseudovalidation sets proves to be a powerful tool for facilitating finite sample problems in moderate-dimensional PR tasks.
Weighted piecewise LDA for solving the small sample size problem in face verification.
Kyperountas, Marios; Tefas, Anastasios; Pitas, Ioannis
2007-03-01
A novel algorithm that can be used to boost the performance of face-verification methods that utilize Fisher's criterion is presented and evaluated. The algorithm is applied to similarity, or matching error, data and provides a general solution for overcoming the "small sample size" (SSS) problem, where the lack of sufficient training samples causes improper estimation of a linear separation hyperplane between the classes. Two independent phases constitute the proposed method. Initially, a set of weighted piecewise discriminant hyperplanes are used in order to provide a more accurate discriminant decision than the one produced by the traditional linear discriminant analysis (LDA) methodology. The expected classification ability of this method is investigated throughout a series of simulations. The second phase defines proper combinations for person-specific similarity scores and describes an outlier removal process that further enhances the classification ability. The proposed technique has been tested on the M2VTS and XM2VTS frontal face databases. Experimental results indicate that the proposed framework greatly improves the face-verification performance.
Thrane, Susan; Cohen, Susan M.
2013-01-01
Objective To calculate the effect of Reiki therapy for pain and anxiety in randomized clinical trials. Data Sources A systematic search of PubMed, ProQuest, Cochrane, PsychInfo, CINAHL, Web of Science, Global Health, and Medline databases was conducted using the search terms pain, anxiety, and Reiki. The Center for Reiki Research was also examined for articles. Study Selection Studies that used randomization and a control or usual care group, used Reiki therapy in one arm of the study, published in 2000 or later in peer-reviewed journals in English, and measured pain or anxiety were included. Results After removing duplicates, 49 articles were examined and 12 articles received full review. Seven studies met the inclusion criteria: four articles studied cancer patients; one examined post-surgical patients; and two analyzed community dwelling older adults. Effect sizes were calculated for all studies using Cohen’s d statistic. Effect sizes for within group differences ranged from d=0.24 for decrease in anxiety in women undergoing breast biopsy to d=2.08 for decreased pain in community dwelling adults. The between group differences ranged from d=0.32 for decrease of pain in a Reiki versus rest intervention for cancer patients to d=4.5 for decrease in pain in community dwelling adults. Conclusions While the number of studies is limited, based on the size Cohen’s d statistics calculated in this review, there is evidence to suggest that Reiki therapy may be effective for pain and anxiety. Continued research using Reiki therapy with larger sample sizes, consistently randomized groups, and standardized treatment protocols is recommended. PMID:24582620
Thrane, Susan; Cohen, Susan M
2014-12-01
The objective of this study was to calculate the effect of Reiki therapy for pain and anxiety in randomized clinical trials. A systematic search of PubMed, ProQuest, Cochrane, PsychInfo, CINAHL, Web of Science, Global Health, and Medline databases was conducted using the search terms pain, anxiety, and Reiki. The Center for Reiki Research also was examined for articles. Studies that used randomization and a control or usual care group, used Reiki therapy in one arm of the study, were published in 2000 or later in peer-reviewed journals in English, and measured pain or anxiety were included. After removing duplicates, 49 articles were examined and 12 articles received full review. Seven studies met the inclusion criteria: four articles studied cancer patients, one examined post-surgical patients, and two analyzed community dwelling older adults. Effect sizes were calculated for all studies using Cohen's d statistic. Effect sizes for within group differences ranged from d = 0.24 for decrease in anxiety in women undergoing breast biopsy to d = 2.08 for decreased pain in community dwelling adults. The between group differences ranged from d = 0.32 for decrease of pain in a Reiki versus rest intervention for cancer patients to d = 4.5 for decrease in pain in community dwelling adults. Although the number of studies is limited, based on the size Cohen's d statistics calculated in this review, there is evidence to suggest that Reiki therapy may be effective for pain and anxiety. Continued research using Reiki therapy with larger sample sizes, consistently randomized groups, and standardized treatment protocols is recommended. PMID:24582620
Shen, You-xin; Liu, Wei-li; Li, Yu-hui; Guan, Hui-lin
2014-01-01
A large number of small-sized samples invariably shows that woody species are absent from forest soil seed banks, leading to a large discrepancy with the seedling bank on the forest floor. We ask: 1) Does this conventional sampling strategy limit the detection of seeds of woody species? 2) Are large sample areas and sample sizes needed for higher recovery of seeds of woody species? We collected 100 samples that were 10 cm (length) × 10 cm (width) × 10 cm (depth), referred to as larger number of small-sized samples (LNSS) in a 1 ha forest plot, and placed them to germinate in a greenhouse, and collected 30 samples that were 1 m × 1 m × 10 cm, referred to as small number of large-sized samples (SNLS) and placed them (10 each) in a nearby secondary forest, shrub land and grass land. Only 15.7% of woody plant species of the forest stand were detected by the 100 LNSS, contrasting with 22.9%, 37.3% and 20.5% woody plant species being detected by SNLS in the secondary forest, shrub land and grassland, respectively. The increased number of species vs. sampled areas confirmed power-law relationships for forest stand, the LNSS and SNLS at all three recipient sites. Our results, although based on one forest, indicate that conventional LNSS did not yield a high percentage of detection for woody species, but SNLS strategy yielded a higher percentage of detection for woody species in the seed bank if samples were exposed to a better field germination environment. A 4 m2 minimum sample area derived from power equations is larger than the sampled area in most studies in the literature. Increased sample size also is needed to obtain an increased sample area if the number of samples is to remain relatively low. PMID:25140738
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.
McCarthy, K.
2008-01-01
Semipermeable membrane devices (SPMDs) were deployed in the Columbia Slough, near Portland, Oregon, on three separate occasions to measure the spatial and seasonal distribution of dissolved polycyclic aromatic hydrocarbons (PAHs) and organochlorine compounds (OCs) in the slough. Concentrations of PAHs and OCs in SPMDs showed spatial and seasonal differences among sites and indicated that unusually high flows in the spring of 2006 diluted the concentrations of many of the target contaminants. However, the same PAHs - pyrene, fluoranthene, and the alkylated homologues of phenanthrene, anthracene, and fluorene - and OCs - polychlorinated biphenyls, pentachloroanisole, chlorpyrifos, dieldrin, and the metabolites of dichlorodiphenyltrichloroethane (DDT) - predominated throughout the system during all three deployment periods. The data suggest that storm washoff may be a predominant source of PAHs in the slough but that OCs are ubiquitous, entering the slough by a variety of pathways. Comparison of SPMDs deployed on the stream bed with SPMDs deployed in the overlying water column suggests that even for the very hydrophobic compounds investigated, bed sediments may not be a predominant source in this system. Perdeuterated phenanthrene (phenanthrene-d10). spiked at a rate of 2 ??g per SPMD, was shown to be a reliable performance reference compound (PRC) under the conditions of these deployments. Post-deployment concentrations of the PRC revealed differences in sampling conditions among sites and between seasons, but indicate that for SPMDs deployed throughout the main slough channel, differences in sampling rates were small enough to make site-to-site comparisons of SPMD concentrations straightforward. ?? Springer Science+Business Media B.V. 2007.
Mevik, Kjersti; Griffin, Frances A; Hansen, Tonje E; Deilkås, Ellen T; Vonen, Barthold
2016-01-01
Objectives 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. Design Retrospective observational study. Setting A Norwegian 524-bed general hospital trust. Participants 1920 medical records selected from 1 January to 31 December 2010. Primary outcomes Rate, type and severity of adverse events identified in two different samples sizes of records selected as 10 and 70 records, bi-weekly. Results 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. Conclusions 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. PMID:27113238
Jain, Prashant K; Lee, Kyeong Seok; El-Sayed, Ivan H; El-Sayed, Mostafa A
2006-04-13
The selection of nanoparticles for achieving efficient contrast for biological and cell imaging applications, as well as for photothermal therapeutic applications, is based on the optical properties of the nanoparticles. We use Mie theory and discrete dipole approximation method to calculate absorption and scattering efficiencies and optical resonance wavelengths for three commonly used classes of nanoparticles: gold nanospheres, silica-gold nanoshells, and gold nanorods. The calculated spectra clearly reflect the well-known dependence of nanoparticle optical properties viz. the resonance wavelength, the extinction cross-section, and the ratio of scattering to absorption, on the nanoparticle dimensions. A systematic quantitative study of the various trends is presented. By increasing the size of gold nanospheres from 20 to 80 nm, the magnitude of extinction as well as the relative contribution of scattering to the extinction rapidly increases. Gold nanospheres in the size range commonly employed ( approximately 40 nm) show an absorption cross-section 5 orders higher than conventional absorbing dyes, while the magnitude of light scattering by 80-nm gold nanospheres is 5 orders higher than the light emission from strongly fluorescing dyes. The variation in the plasmon wavelength maximum of nanospheres, i.e., from approximately 520 to 550 nm, is however too limited to be useful for in vivo applications. Gold nanoshells are found to have optical cross-sections comparable to and even higher than the nanospheres. Additionally, their optical resonances lie favorably in the near-infrared region. The resonance wavelength can be rapidly increased by either increasing the total nanoshell size or increasing the ratio of the core-to-shell radius. The total extinction of nanoshells shows a linear dependence on their total size, however, it is independent of the core/shell radius ratio. The relative scattering contribution to the extinction can be rapidly increased by increasing
Sampson, Andrew; Le, Yi; Williamson, Jeffrey F.
2012-01-01
Purpose: To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. Methods: CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, ΔD, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 125I seeds. The breast case consisted of 87 Model-200 103Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D90, as well as for various anatomical regions. Results: Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 × 1 × 1 mm3 dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses
Rowley, R.; Chu, H.
2002-01-01
High densities and small grain size of alumina ceramic bodies provide high strength and better mechanical properties than lower density and larger grain size bodies. The final sintered density and grain size of slip-cast, alumina samples depends greatly on the processing of the slip and the alumina powder, as well as the sintering schedule. There were many different variables explored that include initial powder particle size, slurry solids percent, amount and type of dispersant used, amount and type of binder used, and sintering schedule. Although the experimentation is not complete, to this point the sample with the highest density and smallest grain size has been a SM8/Nano mixture with Darvan C as the dispersant and Polyvinyl Alcohol (PVA) as the binder, with a solids loading of 70 wt% and a 1500 C for 2 hours sintering schedule. The resultant density was 98.81% of theoretical and the average grain size was approximately 2.5 {micro}m.
Oh, Suk Yung; Bae, Young Chan
2010-07-15
The method presented in this paper was developed to predict liquid-liquid equilibria in ternary liquid mixtures by using a combination of a thermodynamic model and molecular dynamics simulations. In general, common classical thermodynamic models have many parameters which are determined by fitting a model with experimental data. This proposed method, however, provides a simple procedure for calculating liquid-liquid equilibria utilizing binary interaction parameters and molecular size parameters determined from molecular dynamics simulations. This method was applied to mixtures containing water, hydrocarbons, alcohols, chlorides, ketones, acids, and other organic liquids over various temperature ranges. The predicted results agree well with the experimental data without the use of adjustable parameters.
Optimizing Stream Water Mercury Sampling for Calculation of Fish Bioaccumulation Factors
Mercury (Hg) bioaccumulation factors (BAFs) for game fishes are widely employed for monitoring, assessment, and regulatory purposes. Mercury BAFs are calculated as the fish Hg concentration (Hgfish) divided by the water Hg concentration (Hgwater) and, consequently, are sensitive ...
Methods for calculating dietary energy density in a nationally representative sample.
Vernarelli, Jacqueline A; Mitchell, Diane C; Rolls, Barbara J; Hartman, Terryl J
2013-01-01
There has been a growing interest in examining dietary energy density (ED, kcal/g) as it relates to various health outcomes. Consuming a diet low in ED has been recommended in the 2010 Dietary Guidelines, as well as by other agencies, as a dietary approach for disease prevention. Translating this recommendation into practice; however, is difficult. Currently there is no standardized method for calculating dietary ED; as dietary ED can be calculated with foods alone, or with a combination of foods and beverages. Certain items may be defined as either a food or a beverage (e.g., meal replacement shakes) and require special attention. National survey data are an excellent resource for evaluating factors that are important to dietary ED calculation. The National Health and Nutrition Examination Survey (NHANES) nutrient and food database does not include an ED variable, thus researchers must independently calculate ED. The objective of this study was to provide information that will inform the selection of a standardized ED calculation method by comparing and contrasting methods for ED calculation. The present study evaluates all consumed items and defines foods and beverages based on both USDA food codes and how the item was consumed. Results are presented as mean EDs for the different calculation methods stratified by population demographics (e.g. age, sex). Using United State Department of Agriculture (USDA) food codes in the 2005-2008 NHANES, a standardized method for calculating dietary ED can be derived. This method can then be adapted by other researchers for consistency across studies.
Methods for calculating dietary energy density in a nationally representative sample
Vernarelli, Jacqueline A.; Mitchell, Diane C.; Rolls, Barbara J.; Hartman, Terryl J.
2013-01-01
There has been a growing interest in examining dietary energy density (ED, kcal/g) as it relates to various health outcomes. Consuming a diet low in ED has been recommended in the 2010 Dietary Guidelines, as well as by other agencies, as a dietary approach for disease prevention. Translating this recommendation into practice; however, is difficult. Currently there is no standardized method for calculating dietary ED; as dietary ED can be calculated with foods alone, or with a combination of foods and beverages. Certain items may be defined as either a food or a beverage (e.g., meal replacement shakes) and require special attention. National survey data are an excellent resource for evaluating factors that are important to dietary ED calculation. The National Health and Nutrition Examination Survey (NHANES) nutrient and food database does not include an ED variable, thus researchers must independently calculate ED. The objective of this study was to provide information that will inform the selection of a standardized ED calculation method by comparing and contrasting methods for ED calculation. The present study evaluates all consumed items and defines foods and beverages based on both USDA food codes and how the item was consumed. Results are presented as mean EDs for the different calculation methods stratified by population demographics (e.g. age, sex). Using United State Department of Agriculture (USDA) food codes in the 2005–2008 NHANES, a standardized method for calculating dietary ED can be derived. This method can then be adapted by other researchers for consistency across studies. PMID:24432201
Data with Hierarchical Structure: Impact of Intraclass Correlation and Sample Size on Type-I Error
Musca, Serban C.; Kamiejski, Rodolphe; Nugier, Armelle; Méot, Alain; Er-Rafiy, Abdelatif; Brauer, Markus
2011-01-01
Least squares analyses (e.g., ANOVAs, linear regressions) of hierarchical data leads to Type-I error rates that depart severely from the nominal Type-I error rate assumed. Thus, when least squares methods are used to analyze hierarchical data coming from designs in which some groups are assigned to the treatment condition, and others to the control condition (i.e., the widely used “groups nested under treatment” experimental design), the Type-I error rate is seriously inflated, leading too often to the incorrect rejection of the null hypothesis (i.e., the incorrect conclusion of an effect of the treatment). To highlight the severity of the problem, we present simulations showing how the Type-I error rate is affected under different conditions of intraclass correlation and sample size. For all simulations the Type-I error rate after application of the popular Kish (1965) correction is also considered, and the limitations of this correction technique discussed. We conclude with suggestions on how one should collect and analyze data bearing a hierarchical structure. PMID:21687445
NASA Technical Reports Server (NTRS)
Clanton, U. S.; Fletcher, C. R.
1976-01-01
The paper describes a Monte Carlo model for simulation of two-dimensional representations of thin sections of some of the more common igneous rock textures. These representations are extrapolated to three dimensions to develop a volume of 'rock'. The model (here applied to a medium-grained high-Ti basalt) can be used to determine a statistically significant sample for a lunar rock or to predict the probable errors in the oxide contents that can occur during the analysis of a sample that is not representative of the parent rock.
Park, Justin C.; Li, Jonathan G.; Arhjoul, Lahcen; Yan, Guanghua; Lu, Bo; Fan, Qiyong; Liu, Chihray
2015-04-15
Purpose: The use of sophisticated dose calculation procedure in modern radiation therapy treatment planning is inevitable in order to account for complex treatment fields created by multileaf collimators (MLCs). As a consequence, independent volumetric dose verification is time consuming, which affects the efficiency of clinical workflow. In this study, the authors present an efficient adaptive beamlet-based finite-size pencil beam (AB-FSPB) dose calculation algorithm that minimizes the computational procedure while preserving the accuracy. Methods: The computational time of finite-size pencil beam (FSPB) algorithm is proportional to the number of infinitesimal and identical beamlets that constitute an arbitrary field shape. In AB-FSPB, dose distribution from each beamlet is mathematically modeled such that the sizes of beamlets to represent an arbitrary field shape no longer need to be infinitesimal nor identical. As a result, it is possible to represent an arbitrary field shape with combinations of different sized and minimal number of beamlets. In addition, the authors included the model parameters to consider MLC for its rounded edge and transmission. Results: Root mean square error (RMSE) between treatment planning system and conventional FSPB on a 10 × 10 cm{sup 2} square field using 10 × 10, 2.5 × 2.5, and 0.5 × 0.5 cm{sup 2} beamlet sizes were 4.90%, 3.19%, and 2.87%, respectively, compared with RMSE of 1.10%, 1.11%, and 1.14% for AB-FSPB. This finding holds true for a larger square field size of 25 × 25 cm{sup 2}, where RMSE for 25 × 25, 2.5 × 2.5, and 0.5 × 0.5 cm{sup 2} beamlet sizes were 5.41%, 4.76%, and 3.54% in FSPB, respectively, compared with RMSE of 0.86%, 0.83%, and 0.88% for AB-FSPB. It was found that AB-FSPB could successfully account for the MLC transmissions without major discrepancy. The algorithm was also graphical processing unit (GPU) compatible to maximize its computational speed. For an intensity modulated radiation therapy (
Technology Transfer Automated Retrieval System (TEKTRAN)
About 100 countries have established regulatory limits for aflatoxin in food and feeds. Because these limits vary widely among regulating countries, the Codex Committee on Food Additives and Contaminants (CCFAC) began work in 2004 to harmonize aflatoxin limits and sampling plans for aflatoxin in alm...
NASA Astrophysics Data System (ADS)
Alexander, Louise; Snape, Joshua F.; Joy, Katherine H.; Downes, Hilary; Crawford, Ian A.
2016-07-01
Lunar mare basalts provide insights into the compositional diversity of the Moon's interior. Basalt fragments from the lunar regolith can potentially sample lava flows from regions of the Moon not previously visited, thus, increasing our understanding of lunar geological evolution. As part of a study of basaltic diversity at the Apollo 12 landing site, detailed petrological and geochemical data are provided here for 13 basaltic chips. In addition to bulk chemistry, we have analyzed the major, minor, and trace element chemistry of mineral phases which highlight differences between basalt groups. Where samples contain olivine, the equilibrium parent melt magnesium number (Mg#; atomic Mg/[Mg + Fe]) can be calculated to estimate parent melt composition. Ilmenite and plagioclase chemistry can also determine differences between basalt groups. We conclude that samples of approximately 1-2 mm in size can be categorized provided that appropriate mineral phases (olivine, plagioclase, and ilmenite) are present. Where samples are fine-grained (grain size <0.3 mm), a "paired samples t-test" can provide a statistical comparison between a particular sample and known lunar basalts. Of the fragments analyzed here, three are found to belong to each of the previously identified olivine and ilmenite basalt suites, four to the pigeonite basalt suite, one is an olivine cumulate, and two could not be categorized because of their coarse grain sizes and lack of appropriate mineral phases. Our approach introduces methods that can be used to investigate small sample sizes (i.e., fines) from future sample return missions to investigate lava flow diversity and petrological significance.
NASA Astrophysics Data System (ADS)
Alexander, Louise; Snape, Joshua F.; Joy, Katherine H.; Downes, Hilary; Crawford, Ian A.
2016-09-01
Lunar mare basalts provide insights into the compositional diversity of the Moon's interior. Basalt fragments from the lunar regolith can potentially sample lava flows from regions of the Moon not previously visited, thus, increasing our understanding of lunar geological evolution. As part of a study of basaltic diversity at the Apollo 12 landing site, detailed petrological and geochemical data are provided here for 13 basaltic chips. In addition to bulk chemistry, we have analyzed the major, minor, and trace element chemistry of mineral phases which highlight differences between basalt groups. Where samples contain olivine, the equilibrium parent melt magnesium number (Mg#; atomic Mg/[Mg + Fe]) can be calculated to estimate parent melt composition. Ilmenite and plagioclase chemistry can also determine differences between basalt groups. We conclude that samples of approximately 1-2 mm in size can be categorized provided that appropriate mineral phases (olivine, plagioclase, and ilmenite) are present. Where samples are fine-grained (grain size <0.3 mm), a "paired samples t-test" can provide a statistical comparison between a particular sample and known lunar basalts. Of the fragments analyzed here, three are found to belong to each of the previously identified olivine and ilmenite basalt suites, four to the pigeonite basalt suite, one is an olivine cumulate, and two could not be categorized because of their coarse grain sizes and lack of appropriate mineral phases. Our approach introduces methods that can be used to investigate small sample sizes (i.e., fines) from future sample return missions to investigate lava flow diversity and petrological significance.
Rapallo, Arnaldo
2006-03-01
In this article an algorithm is proposed to efficiently perform the uniform sampling of an iso-energy surface corresponding to a fixed potential energy U of a molecular system, and for calculating averages of certain quantities over microstates having this energy (microcanonical averages). The developed sampling technique is based upon the combination of a recently proposed method for performing constant potential energy molecular dynamics simulations [Rapallo, A. J Chem Phys 2004, 121, 4033] with well-established thermostatting techniques used in the framework of standard molecular dynamics simulations, such as the Andersen thermostat, and the Nose-Hoover chain thermostat. The proposed strategy leads to very accurate and drift-free potential energy conservation during the whole sampling process, and, very important, specially when dealing with high-dimensional or complicated potential functions, it does not require the calculation of the potential energy function hessian. The technique proved to be very reliable for sampling both low- and high-dimensional surfaces.
ERIC Educational Resources Information Center
Kelley, Ken
2008-01-01
Methods of sample size planning are developed from the accuracy in parameter approach in the multiple regression context in order to obtain a sufficiently narrow confidence interval for the population squared multiple correlation coefficient when regressors are random. Approximate and exact methods are developed that provide necessary sample size…
Martín Andrés, A.; Herranz Tejedor, I.; Álvarez Hernández, M.
2015-01-01
The Mantel-Haenszel test is the most frequent asymptotic test used for analyzing stratified 2 × 2 tables. Its exact alternative is the test of Birch, which has recently been reconsidered by Jung. Both tests have a conditional origin: Pearson's chi-squared test and Fisher's exact test, respectively. But both tests have the same drawback that the result of global test (the stratified test) may not be compatible with the result of individual tests (the test for each stratum). In this paper, we propose to carry out the global test using a multiple comparisons method (MC method) which does not have this disadvantage. By refining the method (MCB method) an alternative to the Mantel-Haenszel and Birch tests may be obtained. The new MC and MCB methods have the advantage that they may be applied from an unconditional view, a methodology which until now has not been applied to this problem. We also propose some sample size calculation methods. PMID:26075012
ERIC Educational Resources Information Center
Burton, Megan; Mims, Patricia
2012-01-01
Learning through meaningful problem solving is integral in any successful mathematics program (Carpenter et al. 1999). The National Council of Teachers of Mathematics (NCTM) promotes the use of problem solving as a means to deepen understanding of all content areas within mathematics (NCTM 2000). This article describes a first-grade lesson that…
Kostoulas, P; Nielsen, S S; Browne, W J; Leontides, L
2013-06-01
Disease cases are often clustered within herds or generally groups that share common characteristics. Sample size formulae must adjust for the within-cluster correlation of the primary sampling units. Traditionally, the intra-cluster correlation coefficient (ICC), which is an average measure of the data heterogeneity, has been used to modify formulae for individual sample size estimation. However, subgroups of animals sharing common characteristics, may exhibit excessively less or more heterogeneity. Hence, sample size estimates based on the ICC may not achieve the desired precision 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 subsp. paratuberculosis infection, in Danish dairy cattle and a study on critical control points for Salmonella cross-contamination of pork, in Greek slaughterhouses.
Mielke, Steven L; Truhlar, Donald G
2016-01-21
Using Feynman path integrals, a molecular partition function can be written as a double integral with the inner integral involving all closed paths centered at a given molecular configuration, and the outer integral involving all possible molecular configurations. In previous work employing Monte Carlo methods to evaluate such partition functions, we presented schemes for importance sampling and stratification in the molecular configurations that constitute the path centroids, but we relied on free-particle paths for sampling the path integrals. At low temperatures, the path sampling is expensive because the paths can travel far from the centroid configuration. We now present a scheme for importance sampling of whole Feynman paths based on harmonic information from an instantaneous normal mode calculation at the centroid configuration, which we refer to as harmonically guided whole-path importance sampling (WPIS). We obtain paths conforming to our chosen importance function by rejection sampling from a distribution of free-particle paths. Sample calculations on CH4 demonstrate that at a temperature of 200 K, about 99.9% of the free-particle paths can be rejected without integration, and at 300 K, about 98% can be rejected. We also show that it is typically possible to reduce the overhead associated with the WPIS scheme by sampling the paths using a significantly lower-order path discretization than that which is needed to converge the partition function.
Mielke, Steven L; Truhlar, Donald G
2016-01-21
Using Feynman path integrals, a molecular partition function can be written as a double integral with the inner integral involving all closed paths centered at a given molecular configuration, and the outer integral involving all possible molecular configurations. In previous work employing Monte Carlo methods to evaluate such partition functions, we presented schemes for importance sampling and stratification in the molecular configurations that constitute the path centroids, but we relied on free-particle paths for sampling the path integrals. At low temperatures, the path sampling is expensive because the paths can travel far from the centroid configuration. We now present a scheme for importance sampling of whole Feynman paths based on harmonic information from an instantaneous normal mode calculation at the centroid configuration, which we refer to as harmonically guided whole-path importance sampling (WPIS). We obtain paths conforming to our chosen importance function by rejection sampling from a distribution of free-particle paths. Sample calculations on CH4 demonstrate that at a temperature of 200 K, about 99.9% of the free-particle paths can be rejected without integration, and at 300 K, about 98% can be rejected. We also show that it is typically possible to reduce the overhead associated with the WPIS scheme by sampling the paths using a significantly lower-order path discretization than that which is needed to converge the partition function. PMID:26801023
Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian; Tiedje, James M.
2016-01-01
We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5, and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI) were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungal community structure, replicate dispersion and the number of operational taxonomic units (OTUs) retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation. PMID:27313569
Gibertini, Michael; Nations, Kari R; Whitaker, John A
2012-03-01
The high failure rate of antidepressant trials has spurred exploration of the factors that affect trial sensitivity. In the current analysis, Food and Drug Administration antidepressant drug registration trial data compiled by Turner et al. is extended to include the most recently approved antidepressants. The expanded dataset is examined to further establish the likely population effect size (ES) for monoaminergic antidepressants and to demonstrate the relationship between observed ES and sample size in trials on compounds with proven efficacy. Results indicate that the overall underlying ES for antidepressants is approximately 0.30, and that the variability in observed ES across trials is related to the sample size of the trial. The current data provide a unique real-world illustration of an often underappreciated statistical truism: that small N trials are more likely to mislead than to inform, and that by aligning sample size to the population ES, risks of both erroneously high and low effects are minimized. The results in the current study make this abstract concept concrete and will help drug developers arrive at informed gate decisions with greater confidence and fewer risks, improving the odds of success for future antidepressant trials.
Penton, C. Ryan; Gupta, Vadakattu V. S. R.; Yu, Julian; Tiedje, James M.
2016-06-02
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 fungalmore » 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.« less
[Tobacco smoking in a sample of middle-size city inhabitants aged 35-55].
Maniecka-Bryła, Irena; Maciak, Aleksandra; Kowalska, Alina; Bryła, Marek
2008-01-01
Tobacco smoking constitutes a common risk factor for the majority of civilization diseases, such as cardiovascular system diseases, malignant neoplasms and digestion and respiratory system disorders as well. Tobacco-related disorders relate to exacerbation of chronic diseases, for example diabetes and multiple sclerosis. Poland is one of those countries, where the prevalence of smoking is especially widespread. In Poland 42% of men and 25% of women smoke cigarettes and the amount of addicted people amounts to approximately 10 million. The latest data from the year 2003 show that the amount of cigarettes smoked by a particular citizen in Poland has risen fourfold since the beginning of 21st century. This paper presents an analysis of prevalence of tobacco smoking among inhabitants of a middle-size city in the Lodz province aged 35-55 years. The study sample comprised 124 people, including 75 females and 49 males. The tool of the research was a questionnaire survey containing questions concerning cigarette smoking. The study found out that 39.5% of respondents (41.3% of females and 36.7% of males) smoked cigarettes. The percentage of former smokers amounted to 15.3% and the percentage of non-smokers was higher than regular smokers and amounted to 44.8%. The study results showed that the majority of smokers were in the age interval of 45 to 49. Cigarette smoking influenced on smokers' health. The blood pressure and lipid balance was higher among smokers than among people who did not smoke cigarettes. The results of the conducted study confirm that there is a strong need of implementation of programmes towards limiting tobacco smoking, which may contribute to lowering the risk of tobacco-related diseases. PMID:19189562
Importance of Sample Size for the Estimation of Repeater F Waves in Amyotrophic Lateral Sclerosis
Fang, Jia; Liu, Ming-Sheng; Guan, Yu-Zhou; Cui, Bo; Cui, Li-Ying
2015-01-01
Background: In amyotrophic lateral sclerosis (ALS), repeater F waves are increased. Accurate assessment of repeater F waves requires an adequate sample size. Methods: We studied the F waves of left ulnar nerves in ALS patients. Based on the presence or absence of pyramidal signs in the left upper limb, the ALS patients were divided into two groups: One group with pyramidal signs designated as P group and the other without pyramidal signs designated as NP group. The Index repeating neurons (RN) and Index repeater F waves (Freps) were compared among the P, NP and control groups following 20 and 100 stimuli respectively. For each group, the Index RN and Index Freps obtained from 20 and 100 stimuli were compared. Results: In the P group, the Index RN (P = 0.004) and Index Freps (P = 0.001) obtained from 100 stimuli were significantly higher than from 20 stimuli. For F waves obtained from 20 stimuli, no significant differences were identified between the P and NP groups for Index RN (P = 0.052) and Index Freps (P = 0.079); The Index RN (P < 0.001) and Index Freps (P < 0.001) of the P group were significantly higher than the control group; The Index RN (P = 0.002) of the NP group was significantly higher than the control group. For F waves obtained from 100 stimuli, the Index RN (P < 0.001) and Index Freps (P < 0.001) of the P group were significantly higher than the NP group; The Index RN (P < 0.001) and Index Freps (P < 0.001) of the P and NP groups were significantly higher than the control group. Conclusions: Increased repeater F waves reflect increased excitability of motor neuron pool and indicate upper motor neuron dysfunction in ALS. For an accurate evaluation of repeater F waves in ALS patients especially those with moderate to severe muscle atrophy, 100 stimuli would be required. PMID:25673456
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 3 2010-01-01 2010-01-01 false Sample Calculations of Generic Repayment Estimates and Actual Repayment Disclosures M3 Appendix M3 to Part 226 Banks and Banking FEDERAL RESERVE SYSTEM (CONTINUED) BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM TRUTH IN LENDING (REGULATION Z)...
NASA Astrophysics Data System (ADS)
Duncanson, L.; Dubayah, R.
2015-12-01
Lidar remote sensing is widely applied for mapping forest carbon stocks, and technological advances have improved our ability to capture structural details from forests, even resolving individual trees. Despite these advancements, the accuracy of forest aboveground biomass models remains limited by the quality of field estimates of biomass. The accuracies of field estimates are inherently dependent on the accuracy of the allometric equations used to relate measurable attributes to biomass. These equations are calibrated with relatively small samples of often spatially clustered trees. This research focuses on one of many issues involving allometric equations - understanding how sensitive allometric parameters are to the sample sizes used to fit them. We capitalize on recent advances in lidar remote sensing to extract individual tree structural information from six high-resolution airborne lidar datasets in the United States. We remotely measure millions of tree heights and crown radii, and fit allometric equations to the relationship between tree height and radius at a 'population' level, in each site. We then extract samples from our tree database, and build allometries on these smaller samples of trees, with varying sample sizes. We show that for the allometric relationship between tree height and crown radius, small sample sizes produce biased allometric equations that overestimate height for a given crown radius. We extend this analysis using translations from the literature to address potential implications for biomass, showing that site-level biomass may be greatly overestimated when applying allometric equations developed with the typically small sample sizes used in popular allometric equations for biomass.
12 CFR Appendix M2 to Part 226 - Sample Calculations of Repayment Disclosures
Code of Federal Regulations, 2011 CFR
2011-01-01
...; * calculate periodic rate; end; if expm gt 0 then xperrate1a=(expm/36)*xperrate1+(1-(expm/36))*(rrate/365...+perrate(I)),0.01); end; fc=xxxbal1+xxxbal2+xxxbal3−tbal; if pmt gt (tbal+fc) then do; do I=1 to 3; if cbal(I) gt 0 then pmt=round(cbal(I)*(1+perrate(I)),0.01); * set final payment amount; end; end; if pmt...
Esseiva, Pierre; Anglada, Frederic; Dujourdy, Laurence; Taroni, Franco; Margot, Pierre; Pasquier, Eric Du; Dawson, Michael; Roux, Claude; Doble, Philip
2005-08-15
Artificial neural networks (ANNs) were utilised to validate illicit drug classification in the profiling method used at "Institut de Police Scientifique" of the University of Lausanne (IPS). This method established links between samples using a combination of principal component analysis (PCA) and calculation of a correlation value between samples. Heroin seizures sent to the IPS laboratory were analysed using gas chromatography (GC) to separate the major alkaloids present in illicit heroin. Statistical analysis was then performed on 3371 samples. Initially, PCA was performed as a preliminary screen to identify samples of a similar chemical profile. A correlation value was then calculated for each sample previously identified with PCA. This correlation value was used to determine links between drug samples. These links were then recorded in an Ibase((R)) database. From this database the notion of "chemical class" arises, where samples with similar chemical profiles are grouped together. Currently, about 20 "chemical classes" have been identified. The normalised peak areas of six target compounds were then used to train an ANN to classify each sample into its appropriate class. Four hundred and sixty-eight samples were used as a training data set. Sixty samples were treated as blinds and 370 as non-linked samples. The results show that in 96% of cases the neural network attributed the seizure to the right "chemical class". The application of a neural network was found to be a useful tool to validate the classification of new drug seizures in existing chemical classes. This tool should be increasingly used in such situations involving profile comparisons and classifications.
Malm, W.C.
1995-12-31
Optical properties of aerosols are very dependent on composition and morphology as a function of particle size. To investigate sulfur optical properties at a number of national parks, both in the East and West a Davis Rotating-drum Universal-size-cut (DRUM) impactor was employed to measure size resolved sulfur concentrations during three intensive monitoring periods at Grand Canyon and Meadview, Arizona and at Shenandoah National Park. Eighty-eight measurements at Grand Canyon were made during January and February, 1988, 83 at Meadview during July, August, and September, 1992, and 315 at Shenandoah during the summer of 1990. The DRUM impactor is designed to collect aerosols between 0.07 and 15.0 PM in eight size ranges. The sampler is designed to allow impaction of particles onto drums that rotate at a rate of one revolution per month. Focused beam PIXE analysis of the aerosol deposits results in a time history of size resolved elemental composition of varied temporal resolution. As part of the quality assurance protocol a standard 0-2.5 {mu}m particle monitor was operated simultaneously alongside the DRUM sampler. It consisted of a size selective inlet, a cyclone to provide a particle size cutoff, a Teflon collection substrate, and a critical orifice for flow control. The samples were also submitted to PIXE analysis. Summing the sulfur mass concentration derived from the five DRUM stages that are below 2.5 {mu}m and comparing these values to the 0-2.5 {mu}m sampler showed little deviation between the two samplers. On the average the DRUM and 0-2.5 {mu}m sampler compared to within 1% for the Grand Canyon and Meadview data sets while at Shenandoah the DRUM was approximately 15% lower than the cyclone sampler. The average sulfur mass interpreted as ammonium sulfate was 0.67, 2.3, and 11.1 {mu}g/m{sup 3} at Grand Canyon, Meadview, and Shenandoah respectively.
Leifer, R. Z.; Jacob, E. M.; Marschke, S. F.; Pranitis, D. M.; Jaw, H-R. Kristina
2000-03-01
A rotating drum impactor was co-located with a high volume air sampler for ~ 1 y at the fence line of the U. S. Department of Energy’s Fernald Environmental Management Project site. Data on the size distribution of uranium bearing atmospheric aerosols from 0.065 mm to 100 mm in diameter were obtained and used to compute dose using several different models. During most of the year, the mass of ^{238}U above 15 mm exceeded 70% of the total uranium mass from all particulates. Above 4.3 µm, the ^{238}U mass exceeded 80% of the total uranium mass from all particulates. During any sampling period the size distribution was bimodal. In the winter/spring period, the modes appeared at 0.29 µm and 3.2 µm. During the summer period, the lower mode shifted up to ~ 0.45 mm. In the fall/winter, the upper mode shifted to ~ 1.7 µm, while the lower mode stayed at 0.45 mm. These differences reflect the changes in site activities. Thorium concentrations were comparable to the uranium concentrations during the late spring and summer period and decreased to ~25% of the ^{238}U concentration in the late summer. The thorium size distribution trend also differed from the uranium trend. The current calculational method used to demonstrate compliance with regulations assumes that the airborne particulates are characterized by an activity median diameter of 1 µm. This assumption results in an overestimate of the dose to offsite receptors by as much as a factor of seven relative to values derived using the latest ICRP 66 lung model with more appropriate particle sizes. Further evaluation of the size distribution for each radionuclide would substantially improve the dose estimates.
Uyaguari-Diaz, Miguel I; Slobodan, Jared R; Nesbitt, Matthew J; Croxen, Matthew A; Isaac-Renton, Judith; Prystajecky, Natalie A; Tang, Patrick
2015-04-17
Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA libraries are needed for optimal results from next-generation sequencing. Environmental samples such as water may have low quality and quantities of DNA as well as contaminants that co-precipitate with DNA. The mechanical and enzymatic processes involved in extraction and library preparation may further damage the DNA. Gel size selection enables purification and recovery of DNA fragments of a defined size for sequencing applications. Nevertheless, this task is one of the most time-consuming steps in the DNA library preparation workflow. The protocol described here enables complete automation of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments. In this study, we describe a high-throughput approach to prepare high quality DNA libraries from freshwater samples that can be applied also to other environmental samples. We used an indirect approach to concentrate bacterial cells from environmental freshwater samples; DNA was extracted using a commercially available DNA extraction kit, and DNA libraries were prepared using a commercial transposon-based protocol. DNA fragments of 500 to 800 bp were gel size selected using Ranger Technology, an automated electrophoresis workstation. Sequencing of the size-selected DNA libraries demonstrated significant improvements to read length and quality of the sequencing reads.
Hammerstrom, Kamille K; Ranasinghe, J Ananda; Weisberg, Stephen B; Oliver, John S; Fairey, W Russell; Slattery, Peter N; Oakden, James M
2012-10-01
Benthic macrofauna are used extensively for environmental assessment, but the area sampled and sieve sizes used to capture animals often differ among studies. Here, we sampled 80 sites using 3 different sized sampling areas (0.1, 0.05, 0.0071 m(2)) and sieved those sediments through each of 2 screen sizes (0.5, 1 mm) to evaluate their effect on number of individuals, number of species, dominance, nonmetric multidimensional scaling (MDS) ordination, and benthic community condition indices that are used to assess sediment quality in California. Sample area had little effect on abundance but substantially affected numbers of species, which are not easily scaled to a standard area. Sieve size had a substantial effect on both measures, with the 1-mm screen capturing only 74% of the species and 68% of the individuals collected in the 0.5-mm screen. These differences, though, had little effect on the ability to differentiate samples along gradients in ordination space. Benthic indices generally ranked sample condition in the same order regardless of gear, although the absolute scoring of condition was affected by gear type. The largest differences in condition assessment were observed for the 0.0071-m(2) gear. Benthic indices based on numbers of species were more affected than those based on relative abundance, primarily because we were unable to scale species number to a common area as we did for abundance. PMID:20938972
Grazing-incidence XRF analysis of layered samples: Detailed study of amplitude calculation
NASA Astrophysics Data System (ADS)
Miqueles, Eduardo X.; Pérez, Carlos A.; Suárez, Vanessa I.; Vescovi, Rafael F. C.
2015-09-01
In this article, we propose a new mathematical approach for the computation of electromagnetic wave amplitudes in grazing incidence X-ray fluorescence (GIXRF)-an analytical method for surface and near-surface layer analysis. The new contribution comes from an applied point of view, in order to have stable and fast algorithms to simulate the fluorescence intensity from a stacking of thin layer films. The calculation of transmitted/reflected amplitudes is an important part of the direct and/or inverse problem. An analysis of the amplitude versus layer thickness is also given.
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
Core size effect on the dry and saturated ultrasonic pulse velocity of limestone samples.
Ercikdi, Bayram; Karaman, Kadir; Cihangir, Ferdi; Yılmaz, Tekin; Aliyazıcıoğlu, Şener; Kesimal, Ayhan
2016-12-01
This study presents the effect of core length on the saturated (UPVsat) and dry (UPVdry) P-wave velocities of four different biomicritic limestone samples, namely light grey (BL-LG), dark grey (BL-DG), reddish (BL-R) and yellow (BL-Y), using core samples having different lengths (25-125mm) at a constant diameter (54.7mm). The saturated P-wave velocity (UPVsat) of all core samples generally decreased with increasing the sample length. However, the dry P-wave velocity (UPVdry) of samples obtained from BL-LG and BL-Y limestones increased with increasing the sample length. In contrast to the literature, the dry P-wave velocity (UPVdry) values of core samples having a length of 75, 100 and 125mm were consistently higher (2.8-46.2%) than those of saturated (UPVsat). Chemical and mineralogical analyses have shown that the P wave velocity is very sensitive to the calcite and clay minerals potentially leading to the weakening/disintegration of rock samples in the presence of water. Severe fluctuations in UPV values were observed to occur between 25 and 75mm sample lengths, thereafter, a trend of stabilization was observed. The maximum variation of UPV values between the sample length of 75mm and 125mm was only 7.3%. Therefore, the threshold core sample length was interpreted as 75mm for UPV measurement in biomicritic limestone samples used in this study.
Core size effect on the dry and saturated ultrasonic pulse velocity of limestone samples.
Ercikdi, Bayram; Karaman, Kadir; Cihangir, Ferdi; Yılmaz, Tekin; Aliyazıcıoğlu, Şener; Kesimal, Ayhan
2016-12-01
This study presents the effect of core length on the saturated (UPVsat) and dry (UPVdry) P-wave velocities of four different biomicritic limestone samples, namely light grey (BL-LG), dark grey (BL-DG), reddish (BL-R) and yellow (BL-Y), using core samples having different lengths (25-125mm) at a constant diameter (54.7mm). The saturated P-wave velocity (UPVsat) of all core samples generally decreased with increasing the sample length. However, the dry P-wave velocity (UPVdry) of samples obtained from BL-LG and BL-Y limestones increased with increasing the sample length. In contrast to the literature, the dry P-wave velocity (UPVdry) values of core samples having a length of 75, 100 and 125mm were consistently higher (2.8-46.2%) than those of saturated (UPVsat). Chemical and mineralogical analyses have shown that the P wave velocity is very sensitive to the calcite and clay minerals potentially leading to the weakening/disintegration of rock samples in the presence of water. Severe fluctuations in UPV values were observed to occur between 25 and 75mm sample lengths, thereafter, a trend of stabilization was observed. The maximum variation of UPV values between the sample length of 75mm and 125mm was only 7.3%. Therefore, the threshold core sample length was interpreted as 75mm for UPV measurement in biomicritic limestone samples used in this study. PMID:27529138
Multiscale sampling of plant diversity: Effects of minimum mapping unit size
Stohlgren, T.J.; Chong, G.W.; Kalkhan, M.A.; Schell, L.D.
1997-01-01
Only a small portion of any landscape can be sampled for vascular plant diversity because of constraints of cost (salaries, travel time between sites, etc.). Often, the investigator decides to reduce the cost of creating a vegetation map by increasing the minimum mapping unit (MMU), and/or by reducing the number of vegetation classes to be considered. Questions arise about what information is sacrificed when map resolution is decreased. We compared plant diversity patterns from vegetation maps made with 100-ha, 50-ha, 2-ha, and 0.02-ha MMUs in a 754-ha study area in Rocky Mountain National Park, Colorado, United States, using four 0.025-ha and 21 0.1-ha multiscale vegetation plots. We developed and tested species-log(area) curves, correcting the curves for within-vegetation type heterogeneity with Jaccard's coefficients. Total species richness in the study area was estimated from vegetation maps at each resolution (MMU), based on the corrected species-area curves, total area of the vegetation type, and species overlap among vegetation types. With the 0.02-ha MMU, six vegetation types were recovered, resulting in an estimated 552 species (95% CI = 520-583 species) in the 754-ha study area (330 plant species were observed in the 25 plots). With the 2-ha MMU, five vegetation types were recognized, resulting in an estimated 473 species for the study area. With the 50-ha MMU, 439 plant species were estimated for the four vegetation types recognized in the study area. With the 100-ha MMU, only three vegetation types were recognized, resulting in an estimated 341 plant species for the study area. Locally rare species and keystone ecosystems (areas of high or unique plant diversity) were missed at the 2-ha, 50-ha, and 100-ha scales. To evaluate the effects of minimum mapping unit size requires: (1) an initial stratification of homogeneous, heterogeneous, and rare habitat types; and (2) an evaluation of within-type and between-type heterogeneity generated by environmental
Deduction of aerosol size distribution from particle sampling by whisker collectors
NASA Astrophysics Data System (ADS)
Schäfer, H. J.; Pfeifer, H. J.
1983-12-01
A method of deducing airborne particle size distributions from the deposition on a collector is described. The method basically consists in collecting submicron-sized particles on whisker filters for subsequent electron-microscopic examination. The empirical size distributions on the collectors can be approximated by log-normal functions. Moreover, it has been found that the variation in particle distribution across a four-stage whisker filter can be interpreted on the basis of a simple model of the collection process. The effective absorption coefficient derived from this modeling is used to correct the empirical data for the effect of a selective collection characteristic.
A guide for calculation of spot size to determine power density for free fiber irradiation of tissue
NASA Astrophysics Data System (ADS)
Tate, Lloyd P., Jr.; Blikslager, Anthony T.
2005-04-01
Transendoscopic laser treatment for upper airway disorders has been performed in the horse for over twenty years. Endoscopic laser transmission utilizing flexible fiber optics is limited to certain discreet wavelengths. Initially, the laser of choice was the Nd: YAG laser (1064nm), but in the early 1990's, diode lasers (810nm, 980nm) were introduced to veterinary medicine and are currently used in private practice and universities. Precise application of laser irradiation is dependent on the user knowing the laser's output as well as the amount of energy that is delivered to tissue. Knowledge of dosimetry is important to the veterinarian for keeping accurate medical records by being able to describe very specific treatment regimes. The applied energy is best described as power density or energy density. Calculation of this energy is dependent upon the users ability to determine the laser's spot size when irradiating tissue in a non-contact mode. The charts derived from this study provide the veterinarian the ability to estimate spot size for a number of commonly used lasers with the fiber positioned at various distances from the target.
NASA Astrophysics Data System (ADS)
Liu, Hao; Yue, Jiguang; Su, Yongqing; Zhan, Xingqun
2016-11-01
Global Navigation Satellite System (GNSS) data have been used in ionospheric irregularity and scintillation research for decades. However, routine GNSS data lacks raw amplitude data. To deal with the absence of the raw amplitude data, phase data can be used to estimate amplitude scintillation index S4 by phase screen model. The accuracy of the estimation depends on the phase screens constructed from sufficiently sampled phase data. Nevertheless, routine GNSS phase data and equivalent total electron content (TEC) data are all under-sampled. In order to exploit 1-Hz TEC data for accurate S4 estimations, a multiple phase screen compensation method is developed in this paper to compensate for the deficiencies in sampling rates. The multiple screen configuration technique involved in the compensation method determines whether the estimated S4 from the compensation results approximates to the measured S4 . As for the quasi-measured screens from the TEC data, both the line screen in one-dimension (1-D) and the square screen in two-dimension (2-D) have fine S4 estimations by means of the compensation method. Furthermore, power law phase screen simulations are introduced into the validation of the compensation method. The performance of artificially decimated power law screens in terms of S4 estimations is improved by the compensation method as well. In view of the TEC data involved in this paper, the compensation method identifies and fills a gap in the utilization of the under-sampled second-level phase data for estimating S4 , and thus enables routine GNSS phase measurement to trace the ionospheric irregularities at a small or intermediate scale. The multiple screen configuration, meanwhile, renders the compensation method appropriate to weak or moderate scintillations.
NASA Astrophysics Data System (ADS)
Anam, C.; Haryanto, F.; Widita, R.; Arif, I.; Dougherty, G.
2016-03-01
The purpose of this study is to automatically calculate and then investigate the size- specific dose estimate (SSDE) in thoracic and head CT examinations undertaken using standard imaging protocols. The effective diameter (Deff ), the water equivalent diameter (Dw ), and the SSDE were calculated automatically from patient images. We investigated sixteen adult patients who underwent a CT head examination and thirty adult patients who underwent a CT thorax examination. Our results showed that the Dw value in the thoracic region was 4.5% lower than the value of Deff , while the Dw value in the head region was 8.6% higher than the value of Deff . The relationships between diameter (Deff and Dw ) and CTDIvol were distinctive. In the head region, decreasing the patient diameter resulted in a constant CTDIvol due to the tube current modulation (TCM) being off, while in the thoracic region decreasing the patient diameter resulted in a decrease in value of CTDIvol due to TCM being on. In the head region, decreasing the patient diameter resulted in an increase in the value of SSDE, while in the thoracic region decreasing the patient diameter resulted in a decrease in the value of SSDE.
Persoon, Carolyn; Hornbuckle, Keri C.
2009-01-01
Passive sampling has become a practical way of sampling persistent organic pollutants over large spatial and remote areas; however, its ease in use is also coupled with some uncertainty in calculating air concentrations from accumulated mass. Here we report a comparison study of polyurethane-foam-based passive samplers (PUF-PAS) for quantitatively determining the sampling rates of polychlorinated biphenyls (PCBs) from air. We measured both uptake of native PCBs and loss of depuration compounds and determined the sampling rates (R-values) for multiple samplers harvested at three different time periods. The uptake of native PCBs in the linear phase was similar to the loss of depuration compounds for indoor air and behaved as predicted. A single R- value of 2.6 m3d−1 was calculated from the mean of 12 samplers deployed indoors from three harvest dates with a range of 2.0 to 3.4 m3d−1 for both uptake of native PCBs and loss of depuration compounds. Loss of depuration compounds in outdoor air also followed the predicted linear behavior with a range of calculated R-value of 4.4 – 8.4 m3d−1. Uptake of native PCBs behavior was extremely variable, probably due to changes in ambient air concentrations and resulted in R-values of 1.6–11.5 m3d−1 with greater variation seen in higher chlorinated homolog groups. PMID:19068264
Wang, Qing; Xue, Tuo; Song, Chunnian; Wang, Yan; Chen, Guangju
2016-01-01
Free energy calculations of the potential of mean force (PMF) based on the combination of targeted molecular dynamics (TMD) simulations and umbrella samplings as a function of physical coordinates have been applied to explore the detailed pathways and the corresponding free energy profiles for the conformational transition processes of the butane molecule and the 35-residue villin headpiece subdomain (HP35). The accurate PMF profiles for describing the dihedral rotation of butane under both coordinates of dihedral rotation and root mean square deviation (RMSD) variation were obtained based on the different umbrella samplings from the same TMD simulations. The initial structures for the umbrella samplings can be conveniently selected from the TMD trajectories. For the application of this computational method in the unfolding process of the HP35 protein, the PMF calculation along with the coordinate of the radius of gyration (Rg) presents the gradual increase of free energies by about 1 kcal/mol with the energy fluctuations. The feature of conformational transition for the unfolding process of the HP35 protein shows that the spherical structure extends and the middle α-helix unfolds firstly, followed by the unfolding of other α-helices. The computational method for the PMF calculations based on the combination of TMD simulations and umbrella samplings provided a valuable strategy in investigating detailed conformational transition pathways for other allosteric processes. PMID:27171075
Arzola-Alvarez, C; Bocanegra-Viezca, J A; Murphy, M R; Salinas-Chavira, J; Corral-Luna, A; Romanos, A; Ruíz-Barrera, O; Rodríguez-Muela, C
2010-09-01
Four dairy farms were used to determine the effects of water addition to diets and sample collection location on the particle size distribution and chemical composition of total mixed rations (TMR). Samples were collected weekly from the mixing wagon and from 3 locations in the feed bunk (top, middle, and bottom) for 5 mo (April, May, July, August, and October). Samples were partially dried to determine the effect of moisture on particle size distribution. Particle size distribution was measured using the Penn State Particle Size Separator. Crude protein, neutral detergent fiber, and acid detergent fiber contents were also analyzed. Particle fractions 19 to 8, 8 to 1.18, and <1.18 mm were judged adequate in all TMR for rumen function and milk yield; however, the percentage of material>19 mm was greater than recommended for TMR, according to the guidelines of Cooperative Extension of Pennsylvania State University. The particle size distribution in April differed from that in October, but intermediate months (May, July, and August) had similar particle size distributions. Samples from the bottom of the feed bunk had the highest percentage of particles retained on the 19-mm sieve. Samples from the top and middle of the feed bunk were similar to that from the mixing wagon. Higher percentages of particles were retained on >19, 19 to 8, and 8 to 1.18 mm sieves for wet than dried samples. The reverse was found for particles passing the 1.18-mm sieve. Mean particle size was higher for wet than dried samples. The crude protein, neutral detergent fiber, and acid detergent fiber contents of TMR varied with month of sampling (18-21, 40-57, and 21-34%, respectively) but were within recommended ranges for high-yielding dairy cows. Analyses of TMR particle size distributions are useful for proper feed bunk management and formulation of diets that maintain rumen function and maximize milk production and quality. Water addition may help reduce dust associated with feeding TMR. PMID
Burild, Anders; Frandsen, Henrik L; Poulsen, Morten; Jakobsen, Jette
2014-10-01
Most methods for the quantification of physiological levels of vitamin D3 and 25-hydroxyvitamin D3 are developed for food analysis where the sample size is not usually a critical parameter. In contrast, in life science studies sample sizes are often limited. A very sensitive liquid chromatography with tandem mass spectrometry method was developed to quantify vitamin D3 and 25-hydroxyvitamin D3 simultaneously in porcine tissues. A sample of 0.2-1 g was saponified followed by liquid-liquid extraction and normal-phase solid-phase extraction. The analytes were derivatized with 4-phenyl-1,2,4-triazoline-3,5-dione to improve the ionization efficiency by electrospray ionization. The method was validated in porcine liver and adipose tissue, and the accuracy was determined to be 72-97% for vitamin D3 and 91-124% for 25-hydroxyvitamin D3 . The limit of quantification was <0.1 ng/g, and the precision varied between 1.4 and 16% depending on the level of spiking. The small sample size required for the described method enables quantification of vitamin D3 and 25-hydroxyvitamin D3 in tissues from studies where sample sizes are limited.
Shen, Ping-Ping; Zhou, Hong; Zhao, Zhenye; Yu, Xiao-Zhang; Gu, Ji-Dong
2012-08-01
In this study, two types of sediment cores with different diameters were used to collect sediment samples from an intertidal mudflat in Hong Kong to investigate the influence of sampling unit on the quantitative assessment of benthic macroinfaunal communities. Both univariate and multivariate analyses were employed to detect differences in sampling efficiencies by the two samplers through total abundance and biomass, species richness and diversity, community structure, relative abundance of major taxa of the infaunal community. The species-area curves were further compared to find out the influence of the sampling units. Results showed that the two sampling devices provided similar information on the estimates of species diversity, density and species composition of the benthos in main part of the mudflat where the sediment was fine and homogenous; but at the station which contained coarse sand and gravels, the significant differences were detected between the quantitative assessments of macrobenthic infauna by the two samplers. Most importantly, the species-area curves indicated that more and smaller samples were better in capturing more species than less large ones when comparing an equal sampling area. Therefore, the efficiency of the sampler largely depended on the sediment properties, and sampling devices must be chosen based on the physical conditions and desired levels of precision on the organisms of the sampling program. PMID:22766844
Shen, Ping-Ping; Zhou, Hong; Zhao, Zhenye; Yu, Xiao-Zhang; Gu, Ji-Dong
2012-08-01
In this study, two types of sediment cores with different diameters were used to collect sediment samples from an intertidal mudflat in Hong Kong to investigate the influence of sampling unit on the quantitative assessment of benthic macroinfaunal communities. Both univariate and multivariate analyses were employed to detect differences in sampling efficiencies by the two samplers through total abundance and biomass, species richness and diversity, community structure, relative abundance of major taxa of the infaunal community. The species-area curves were further compared to find out the influence of the sampling units. Results showed that the two sampling devices provided similar information on the estimates of species diversity, density and species composition of the benthos in main part of the mudflat where the sediment was fine and homogenous; but at the station which contained coarse sand and gravels, the significant differences were detected between the quantitative assessments of macrobenthic infauna by the two samplers. Most importantly, the species-area curves indicated that more and smaller samples were better in capturing more species than less large ones when comparing an equal sampling area. Therefore, the efficiency of the sampler largely depended on the sediment properties, and sampling devices must be chosen based on the physical conditions and desired levels of precision on the organisms of the sampling program.
Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric
2016-01-01
Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles. PMID:26943927
Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric
2016-03-01
Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Bochicchio, Davide; Panizon, Emanuele; Ferrando, Riccardo; Monticelli, Luca; Rossi, Giulia
2015-10-14
We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time. PMID:26472364
NASA Astrophysics Data System (ADS)
Bochicchio, Davide; Panizon, Emanuele; Ferrando, Riccardo; Monticelli, Luca; Rossi, Giulia
2015-10-01
We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.
Bochicchio, Davide; Panizon, Emanuele; Ferrando, Riccardo; Rossi, Giulia; Monticelli, Luca
2015-10-14
We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.
Leinonen, Merja R; Raekallio, Marja R; Vainio, Outi M; Ruohoniemi, Mirja O; O'Brien, Robert T
2011-01-01
Contrast-enhanced ultrasound can be used to quantify tissue perfusion based on region of interest (ROI) analysis. The effect of the location and size of the ROI on the obtained perfusion parameters has been described in phantom, ex vivo and in vivo studies. We assessed the effects of location and size of the ROI on perfusion parameters in the renal cortex of 10 healthy, anesthetized cats using Definity contrast-enhanced ultrasound to estimate the importance of the ROI on quantification of tissue perfusion with contrast-enhanced ultrasound. Three separate sets of ROIs were placed in the renal cortex, varying in location, size or depth. There was a significant inverse association between increased depth or increased size of the ROI and peak intensity (P < 0.05). There was no statistically significant difference in the peak intensity between the ROIs placed in a row in the near field cortex. There was no significant difference in the ROIs with regard to arrival time, time to peak intensity and wash-in rate. When comparing two different ROIs in a patient with focal lesions, such as suspected neoplasia or infarction, the ROIs should always be placed at same depth and be as similar in size as possible.
Selbig, William R.; Bannerman, Roger T.
2011-01-01
The U.S Geological Survey, in cooperation with the Wisconsin Department of Natural Resources (WDNR) and in collaboration with the Root River Municipal Stormwater Permit Group monitored eight urban source areas representing six types of source areas in or near Madison, Wis. in an effort to improve characterization of particle-size distributions in urban stormwater by use of fixed-point sample collection methods. The types of source areas were parking lot, feeder street, collector street, arterial street, rooftop, and mixed use. This information can then be used by environmental managers and engineers when selecting the most appropriate control devices for the removal of solids from urban stormwater. Mixed-use and parking-lot study areas had the lowest median particle sizes (42 and 54 (u or mu)m, respectively), followed by the collector street study area (70 (u or mu)m). Both arterial street and institutional roof study areas had similar median particle sizes of approximately 95 (u or mu)m. Finally, the feeder street study area showed the largest median particle size of nearly 200 (u or mu)m. Median particle sizes measured as part of this study were somewhat comparable to those reported in previous studies from similar source areas. The majority of particle mass in four out of six source areas was silt and clay particles that are less than 32 (u or mu)m in size. Distributions of particles ranging from 500 (u or mu)m were highly variable both within and between source areas. Results of this study suggest substantial variability in data can inhibit the development of a single particle-size distribution that is representative of stormwater runoff generated from a single source area or land use. Continued development of improved sample collection methods, such as the depth-integrated sample arm, may reduce variability in particle-size distributions by mitigating the effect of sediment bias inherent with a fixed-point sampler.
Confidence intervals for two sample means: Calculation, interpretation, and a few simple rules
Pfister, Roland; Janczyk, Markus
2013-01-01
Valued by statisticians, enforced by editors, and confused by many authors, standard errors (SEs) and confidence intervals (CIs) remain a controversial issue in the psychological literature. This is especially true for the proper use of CIs for within-subjects designs, even though several recent publications elaborated on possible solutions for this case. The present paper presents a short and straightforward introduction to the basic principles of CI construction, in an attempt to encourage students and researchers in cognitive psychology to use CIs in their reports and presentations. Focusing on a simple but prevalent case of statistical inference, the comparison of two sample means, we describe possible CIs for between- and within-subjects designs. In addition, we give hands-on examples of how to compute these CIs and discuss their relation to classical t-tests. PMID:23826038
Method to study sample object size limit of small-angle x-ray scattering computed tomography
NASA Astrophysics Data System (ADS)
Choi, Mina; Ghammraoui, Bahaa; Badal, Andreu; Badano, Aldo
2016-03-01
Small-angle x-ray scattering (SAXS) imaging is an emerging medical tool that can be used for in vivo detailed tissue characterization and has the potential to provide added contrast to conventional x-ray projection and CT imaging. We used a publicly available MC-GPU code to simulate x-ray trajectories in a SAXS-CT geometry for a target material embedded in a water background material with varying sample sizes (1, 3, 5, and 10 mm). Our target materials were water solution of gold nanoparticle (GNP) spheres with a radius of 6 nm and a water solution with dissolved serum albumin (BSA) proteins due to their well-characterized scatter profiles at small angles and highly scattering properties. The background material was water. Our objective is to study how the reconstructed scatter profile degrades at larger target imaging depths and increasing sample sizes. We have found that scatter profiles of the GNP in water can still be reconstructed at depths up to 5 mm embedded at the center of a 10 mm sample. Scatter profiles of BSA in water were also reconstructed at depths up to 5 mm in a 10 mm sample but with noticeable signal degradation as compared to the GNP sample. This work presents a method to study the sample size limits for future SAXS-CT imaging systems.
The accuracy of instrumental neutron activation analysis of kilogram-size inhomogeneous samples.
Blaauw, M; Lakmaker, O; van Aller, P
1997-07-01
The feasibility of quantitative instrumental neutron activation analysis (INAA) of samples in the kilogram range without internal standardization has been demonstrated by Overwater et al. (Anal. Chem. 1996, 68, 341). In their studies, however, they demonstrated only the agreement between the "corrected" γ ray spectrum of homogeneous large samples and that of small samples of the same material. In this paper, the k(0) calibration of the IRI facilities for large samples is described, and, this time in terms of (trace) element concentrations, some of Overwater's results for homogeneous materials are presented again, as well as results obtained from inhomogeneous materials and subsamples thereof. It is concluded that large-sample INAA can be as accurate as ordinary INAA, even when applied to inhomogeneous materials.
Ryman, Nils; Allendorf, Fred W; Jorde, Per Erik; Laikre, Linda; Hössjer, Ola
2014-01-01
Many empirical studies estimating effective population size apply the temporal method that provides an estimate of the variance effective size through the amount of temporal allele frequency change under the assumption that the study population is completely isolated. This assumption is frequently violated, and the magnitude of the resulting bias is generally unknown. We studied how gene flow affects estimates of effective size obtained by the temporal method when sampling from a population system and provide analytical expressions for the expected estimate under an island model of migration. We show that the temporal method tends to systematically underestimate both local and global effective size when populations are connected by gene flow, and the bias is sometimes dramatic. The problem is particularly likely to occur when sampling from a subdivided population where high levels of gene flow obscure identification of subpopulation boundaries. In such situations, sampling in a manner that prevents biased estimates can be difficult. This phenomenon might partially explain the frequently reported unexpectedly low effective population sizes of marine populations that have raised concern regarding the genetic vulnerability of even exceptionally large populations. PMID:24034449
NASA Astrophysics Data System (ADS)
Luquot, Linda; Hebert, Vanessa; Rodriguez, Olivier
2016-04-01
The aim of this study is to compare the structural, geometrical and transport parameters of a limestone rock sample determined by X-ray microtomography (XMT) images and laboratory experiments. Total and effective porosity, surface-to-volume ratio, pore size distribution, permeability, tortuosity and effective diffusion coeffcient have been estimated. Sensitivity analyses of the segmentation parameters have been performed. The limestone rock sample studied here have been characterized using both approaches before and after a reactive percolation experiment. Strong dissolution process occured during the percolation, promoting a wormhole formation. This strong heterogeneity formed after the percolation step allows to apply our methodology to two different samples and enhance the use of experimental techniques or XMT images depending on the rock heterogeneity. We established that for most of the parameters calculated here, the values obtained by computing XMT images are in agreement with the classical laboratory measurements. We demonstrated that the computational porosity is more informative than the laboratory one. We observed that pore size distributions obtained by XMT images and laboratory experiments are slightly different but complementary. Regarding the effective diffusion coeffcient, we concluded that both approaches are valuable and give similar results. Nevertheless, we wrapped up that computing XMT images to determine transport, geometrical and petrophysical parameters provides similar results than the one measured at the laboratory but with much shorter durations.
NASA Astrophysics Data System (ADS)
Luquot, Linda; Hebert, Vanessa; Rodriguez, Olivier
2016-03-01
The aim of this study is to compare the structural, geometrical and transport parameters of a limestone rock sample determined by X-ray microtomography (XMT) images and laboratory experiments. Total and effective porosity, pore-size distribution, tortuosity, and effective diffusion coefficient have been estimated. Sensitivity analyses of the segmentation parameters have been performed. The limestone rock sample studied here has been characterized using both approaches before and after a reactive percolation experiment. Strong dissolution process occurred during the percolation, promoting a wormhole formation. This strong heterogeneity formed after the percolation step allows us to apply our methodology to two different samples and enhance the use of experimental techniques or XMT images depending on the rock heterogeneity. We established that for most of the parameters calculated here, the values obtained by computing XMT images are in agreement with the classical laboratory measurements. We demonstrated that the computational porosity is more informative than the laboratory measurement. We observed that pore-size distributions obtained by XMT images and laboratory experiments are slightly different but complementary. Regarding the effective diffusion coefficient, we concluded that both approaches are valuable and give similar results. Nevertheless, we concluded that computing XMT images to determine transport, geometrical, and petrophysical parameters provide similar results to those measured at the laboratory but with much shorter durations.
NASA Technical Reports Server (NTRS)
Heymann, D.; Lakatos, S.; Walton, J. R.
1973-01-01
Review of the results of inert gas measurements performed on six grain-size fractions and two single particles from four samples of Luna 20 material. Presented and discussed data include the inert gas contents, element and isotope systematics, radiation ages, and Ar-36/Ar-40 systematics.
ERIC Educational Resources Information Center
Algina, James; Keselman, H. J.
2008-01-01
Applications of distribution theory for the squared multiple correlation coefficient and the squared cross-validation coefficient are reviewed, and computer programs for these applications are made available. The applications include confidence intervals, hypothesis testing, and sample size selection. (Contains 2 tables.)