Sample size of the reference sample in a case-augmented study.

PubMed

Ghosh, Palash; Dewanji, Anup

2017-05-01

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

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

PubMed

Wu, Yu-te; Makuch, Robert W

2010-08-01

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

Developing the Noncentrality Parameter for Calculating Group Sample Sizes in Heterogeneous Analysis of Variance

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…

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…

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

PubMed

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

2008-04-01

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

Sample size calculations for case-control studies

Cancer.gov

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

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

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

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

2014-04-15

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

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

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

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

PubMed

Willan, Andrew R

2016-07-05

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

Design of Phase II Non-inferiority Trials.

PubMed

Jung, Sin-Ho

2017-09-01

With the development of inexpensive treatment regimens and less invasive surgical procedures, we are confronted with non-inferiority study objectives. A non-inferiority phase III trial requires a roughly four times larger sample size than that of a similar standard superiority trial. Because of the large required sample size, we often face feasibility issues to open a non-inferiority trial. Furthermore, due to lack of phase II non-inferiority trial design methods, we do not have an opportunity to investigate the efficacy of the experimental therapy through a phase II trial. As a result, we often fail to open a non-inferiority phase III trial and a large number of non-inferiority clinical questions still remain unanswered. In this paper, we want to develop some designs for non-inferiority randomized phase II trials with feasible sample sizes. At first, we review a design method for non-inferiority phase III trials. Subsequently, we propose three different designs for non-inferiority phase II trials that can be used under different settings. Each method is demonstrated with examples. Each of the proposed design methods is shown to require a reasonable sample size for non-inferiority phase II trials. The three different non-inferiority phase II trial designs are used under different settings, but require similar sample sizes that are typical for phase II trials.

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

PubMed

Wu, Zhichao; Medeiros, Felipe A

2018-03-20

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

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

Treesearch

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

1995-01-01

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

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

DTIC Science & Technology

2016-11-01

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

A multi-stage drop-the-losers design for multi-arm clinical trials.

PubMed

Wason, James; Stallard, Nigel; Bowden, Jack; Jennison, Christopher

2017-02-01

Multi-arm multi-stage trials can improve the efficiency of the drug development process when multiple new treatments are available for testing. A group-sequential approach can be used in order to design multi-arm multi-stage trials, using an extension to Dunnett's multiple-testing procedure. The actual sample size used in such a trial is a random variable that has high variability. This can cause problems when applying for funding as the cost will also be generally highly variable. This motivates a type of design that provides the efficiency advantages of a group-sequential multi-arm multi-stage design, but has a fixed sample size. One such design is the two-stage drop-the-losers design, in which a number of experimental treatments, and a control treatment, are assessed at a prescheduled interim analysis. The best-performing experimental treatment and the control treatment then continue to a second stage. In this paper, we discuss extending this design to have more than two stages, which is shown to considerably reduce the sample size required. We also compare the resulting sample size requirements to the sample size distribution of analogous group-sequential multi-arm multi-stage designs. The sample size required for a multi-stage drop-the-losers design is usually higher than, but close to, the median sample size of a group-sequential multi-arm multi-stage trial. In many practical scenarios, the disadvantage of a slight loss in average efficiency would be overcome by the huge advantage of a fixed sample size. We assess the impact of delay between recruitment and assessment as well as unknown variance on the drop-the-losers designs.

Sampling design and required sample size for evaluating contamination levels of 137Cs in Japanese fir needles in a mixed deciduous forest stand in Fukushima, Japan.

PubMed

Oba, Yurika; Yamada, Toshihiro

2017-05-01

We estimated the sample size (the number of samples) required to evaluate the concentration of radiocesium ( 137 Cs) in Japanese fir (Abies firma Sieb. & Zucc.), 5 years after the outbreak of the Fukushima Daiichi Nuclear Power Plant accident. We investigated the spatial structure of the contamination levels in this species growing in a mixed deciduous broadleaf and evergreen coniferous forest stand. We sampled 40 saplings with a tree height of 150 cm-250 cm in a Fukushima forest community. The results showed that: (1) there was no correlation between the 137 Cs concentration in needles and soil, and (2) the difference in the spatial distribution pattern of 137 Cs concentration between needles and soil suggest that the contribution of root uptake to 137 Cs in new needles of this species may be minor in the 5 years after the radionuclides were released into the atmosphere. The concentration of 137 Cs in needles showed a strong positive spatial autocorrelation in the distance class from 0 to 2.5 m, suggesting that the statistical analysis of data should consider spatial autocorrelation in the case of an assessment of the radioactive contamination of forest trees. According to our sample size analysis, a sample size of seven trees was required to determine the mean contamination level within an error in the means of no more than 10%. This required sample size may be feasible for most sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Shieh, Gwowen

2014-09-01

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

Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis

PubMed Central

Adnan, Tassha Hilda

2016-01-01

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

On Two-Stage Multiple Comparison Procedures When There Are Unequal Sample Sizes in the First Stage.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1984-01-01

Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)

How Big Is Big Enough? Sample Size Requirements for CAST Item Parameter Estimation

ERIC Educational Resources Information Center

Chuah, Siang Chee; Drasgow, Fritz; Luecht, Richard

2006-01-01

Adaptive tests offer the advantages of reduced test length and increased accuracy in ability estimation. However, adaptive tests require large pools of precalibrated items. This study looks at the development of an item pool for 1 type of adaptive administration: the computer-adaptive sequential test. An important issue is the sample size required…

Determining sample size for tree utilization surveys

Treesearch

Stanley J. Zarnoch; James W. Bentley; Tony G. Johnson

2004-01-01

The U.S. Department of Agriculture Forest Service has conducted many studies to determine what proportion of the timber harvested in the South is actually utilized. This paper describes the statistical methods used to determine required sample sizes for estimating utilization ratios for a required level of precision. The data used are those for 515 hardwood and 1,557...

40 CFR 90.706 - Engine sample selection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... = emission test result for an individual engine. x = mean of emission test results of the actual sample. FEL... test with the last test result from the previous model year and then calculate the required sample size.... Test results used to calculate the variables in the following Sample Size Equation must be final...

Study design requirements for RNA sequencing-based breast cancer diagnostics.

PubMed

Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 4 2013-10-01 2013-10-01 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 NYTD...

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

PubMed

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

1998-04-01

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

Approximate sample size formulas for the two-sample trimmed mean test with unequal variances.

PubMed

Luh, Wei-Ming; Guo, Jiin-Huarng

2007-05-01

Yuen's two-sample trimmed mean test statistic is one of the most robust methods to apply when variances are heterogeneous. The present study develops formulas for the sample size required for the test. The formulas are applicable for the cases of unequal variances, non-normality and unequal sample sizes. Given the specified alpha and the power (1-beta), the minimum sample size needed by the proposed formulas under various conditions is less than is given by the conventional formulas. Moreover, given a specified size of sample calculated by the proposed formulas, simulation results show that Yuen's test can achieve statistical power which is generally superior to that of the approximate t test. A numerical example is provided.

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

Treesearch

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

2000-01-01

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

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

PubMed

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

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

Electrofishing effort requirements for estimating species richness in the Kootenai River, Idaho

USGS Publications Warehouse

Watkins, Carson J.; Quist, Michael C.; Shepard, Bradley B.; Ireland, Susan C.

2016-01-01

This study was conducted on the Kootenai River, Idaho to provide insight on sampling requirements to optimize future monitoring effort associated with the response of fish assemblages to habitat rehabilitation. Our objective was to define the electrofishing effort (m) needed to have a 95% probability of sampling 50, 75, and 100% of the observed species richness and to evaluate the relative influence of depth, velocity, and instream woody cover on sample size requirements. Sidechannel habitats required more sampling effort to achieve 75 and 100% of the total species richness than main-channel habitats. The sampling effort required to have a 95% probability of sampling 100% of the species richness was 1100 m for main-channel sites and 1400 m for side-channel sites. We hypothesized that the difference in sampling requirements between main- and side-channel habitats was largely due to differences in habitat characteristics and species richness between main- and side-channel habitats. In general, main-channel habitats had lower species richness than side-channel habitats. Habitat characteristics (i.e., depth, current velocity, and woody instream cover) were not related to sample size requirements. Our guidelines will improve sampling efficiency during monitoring effort in the Kootenai River and provide insight on sampling designs for other large western river systems where electrofishing is used to assess fish assemblages.

An alternative method for determining particle-size distribution of forest road aggregate and soil with large-sized particles

Treesearch

Hakjun Rhee; Randy B. Foltz; James L. Fridley; Finn Krogstad; Deborah S. Page-Dumroese

2014-01-01

Measurement of particle-size distribution (PSD) of soil with large-sized particles (e.g., 25.4 mm diameter) requires a large sample and numerous particle-size analyses (PSAs). A new method is needed that would reduce time, effort, and cost for PSAs of the soil and aggregate material with large-sized particles. We evaluated a nested method for sampling and PSA by...

Sample sizes needed for specified margins of relative error in the estimates of the repeatability and reproducibility standard deviations.

PubMed

McClure, Foster D; Lee, Jung K

2005-01-01

Sample size formulas are developed to estimate the repeatability and reproducibility standard deviations (Sr and S(R)) such that the actual error in (Sr and S(R)) relative to their respective true values, sigmar and sigmaR, are at predefined levels. The statistical consequences associated with AOAC INTERNATIONAL required sample size to validate an analytical method are discussed. In addition, formulas to estimate the uncertainties of (Sr and S(R)) were derived and are provided as supporting documentation. Formula for the Number of Replicates Required for a Specified Margin of Relative Error in the Estimate of the Repeatability Standard Deviation.

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…

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

ERIC Educational Resources Information Center

Shieh, Gwowen; Jan, Show-Li

2013-01-01

The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the…

Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

PubMed Central

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

2011-01-01

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

Sampling designs for contaminant temporal trend analyses using sedentary species exemplified by the snails Bellamya aeruginosa and Viviparus viviparus.

PubMed

Yin, Ge; Danielsson, Sara; Dahlberg, Anna-Karin; Zhou, Yihui; Qiu, Yanling; Nyberg, Elisabeth; Bignert, Anders

2017-10-01

Environmental monitoring typically assumes samples and sampling activities to be representative of the population being studied. Given a limited budget, an appropriate sampling strategy is essential to support detecting temporal trends of contaminants. In the present study, based on real chemical analysis data on polybrominated diphenyl ethers in snails collected from five subsites in Tianmu Lake, computer simulation is performed to evaluate three sampling strategies by the estimation of required sample size, to reach a detection of an annual change of 5% with a statistical power of 80% and 90% with a significant level of 5%. The results showed that sampling from an arbitrarily selected sampling spot is the worst strategy, requiring much more individual analyses to achieve the above mentioned criteria compared with the other two approaches. A fixed sampling site requires the lowest sample size but may not be representative for the intended study object e.g. a lake and is also sensitive to changes of that particular sampling site. In contrast, sampling at multiple sites along the shore each year, and using pooled samples when the cost to collect and prepare individual specimens are much lower than the cost for chemical analysis, would be the most robust and cost efficient strategy in the long run. Using statistical power as criterion, the results demonstrated quantitatively the consequences of various sampling strategies, and could guide users with respect of required sample sizes depending on sampling design for long term monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2017-01-01

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

Probabilistic Design of a Mars Sample Return Earth Entry Vehicle Thermal Protection System

NASA Technical Reports Server (NTRS)

Dec, John A.; Mitcheltree, Robert A.

2002-01-01

The driving requirement for design of a Mars Sample Return mission is to assure containment of the returned samples. Designing to, and demonstrating compliance with, such a requirement requires physics based tools that establish the relationship between engineer's sizing margins and probabilities of failure. The traditional method of determining margins on ablative thermal protection systems, while conservative, provides little insight into the actual probability of an over-temperature during flight. The objective of this paper is to describe a new methodology for establishing margins on sizing the thermal protection system (TPS). Results of this Monte Carlo approach are compared with traditional methods.

Characteristics of randomised trials on diseases in the digestive system registered in ClinicalTrials.gov: a retrospective analysis.

PubMed

Wildt, Signe; Krag, Aleksander; Gluud, Liselotte

2011-01-01

Objectives To evaluate the adequacy of reporting of protocols for randomised trials on diseases of the digestive system registered in http://ClinicalTrials.gov and the consistency between primary outcomes, secondary outcomes and sample size specified in http://ClinicalTrials.gov and published trials. Methods Randomised phase III trials on adult patients with gastrointestinal diseases registered before January 2009 in http://ClinicalTrials.gov were eligible for inclusion. From http://ClinicalTrials.gov all data elements in the database required by the International Committee of Medical Journal Editors (ICMJE) member journals were extracted. The subsequent publications for registered trials were identified. For published trials, data concerning publication date, primary and secondary endpoint, sample size, and whether the journal adhered to ICMJE principles were extracted. Differences between primary and secondary outcomes, sample size and sample size calculations data in http://ClinicalTrials.gov and in the published paper were registered. Results 105 trials were evaluated. 66 trials (63%) were published. 30% of trials were registered incorrectly after their completion date. Several data elements of the required ICMJE data list were not filled in, with missing data in 22% and 11%, respectively, of cases concerning the primary outcome measure and sample size. In 26% of the published papers, data on sample size calculations were missing and discrepancies between sample size reporting in http://ClinicalTrials.gov and published trials existed. Conclusion The quality of registration of randomised controlled trials still needs improvement.

40 CFR 141.858 - Repeat monitoring and E. coli requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Repeat monitoring and E. coli....858 Repeat monitoring and E. coli requirements. (a) Repeat monitoring. (1) If a sample taken under... volume repeat sample(s) in one or more sample containers of any size, as long as the total volume...

Accounting for Incomplete Species Detection in Fish Community Monitoring

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

McManamay, Ryan A; Orth, Dr. Donald J; Jager, Yetta

2013-01-01

Riverine fish assemblages are heterogeneous and very difficult to characterize with a one-size-fits-all approach to sampling. Furthermore, detecting changes in fish assemblages over time requires accounting for variation in sampling designs. We present a modeling approach that permits heterogeneous sampling by accounting for site and sampling covariates (including method) in a model-based framework for estimation (versus a sampling-based framework). We snorkeled during three surveys and electrofished during a single survey in suite of delineated habitats stratified by reach types. We developed single-species occupancy models to determine covariates influencing patch occupancy and species detection probabilities whereas community occupancy models estimated speciesmore » richness in light of incomplete detections. For most species, information-theoretic criteria showed higher support for models that included patch size and reach as covariates of occupancy. In addition, models including patch size and sampling method as covariates of detection probabilities also had higher support. Detection probability estimates for snorkeling surveys were higher for larger non-benthic species whereas electrofishing was more effective at detecting smaller benthic species. The number of sites and sampling occasions required to accurately estimate occupancy varied among fish species. For rare benthic species, our results suggested that higher number of occasions, and especially the addition of electrofishing, may be required to improve detection probabilities and obtain accurate occupancy estimates. Community models suggested that richness was 41% higher than the number of species actually observed and the addition of an electrofishing survey increased estimated richness by 13%. These results can be useful to future fish assemblage monitoring efforts by informing sampling designs, such as site selection (e.g. stratifying based on patch size) and determining effort required (e.g. number of sites versus occasions).« less

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches.

PubMed

Almutairy, Meznah; Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches

PubMed Central

Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method. PMID:29389989

Laboratory theory and methods for sediment analysis

USGS Publications Warehouse

Guy, Harold P.

1969-01-01

The diverse character of fluvial sediments makes the choice of laboratory analysis somewhat arbitrary and the pressing of sediment samples difficult. This report presents some theories and methods used by the Water Resources Division for analysis of fluvial sediments to determine the concentration of suspended-sediment samples and the particle-size distribution of both suspended-sediment and bed-material samples. Other analyses related to these determinations may include particle shape, mineral content, and specific gravity, the organic matter and dissolved solids of samples, and the specific weight of soils. The merits and techniques of both the evaporation and filtration methods for concentration analysis are discussed. Methods used for particle-size analysis of suspended-sediment samples may include the sieve pipet, the VA tube-pipet, or the BW tube-VA tube depending on the equipment available, the concentration and approximate size of sediment in the sample, and the settling medium used. The choice of method for most bed-material samples is usually limited to procedures suitable for sand or to some type of visual analysis for large sizes. Several tested forms are presented to help insure a well-ordered system in the laboratory to handle the samples, to help determine the kind of analysis required for each, to conduct the required processes, and to assist in the required computations. Use of the manual should further 'standardize' methods of fluvial sediment analysis among the many laboratories and thereby help to achieve uniformity and precision of the data.

A Note on Maximized Posttest Contrasts.

ERIC Educational Resources Information Center

Williams, John D.

1979-01-01

Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)

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

PubMed

Backhouse, Martin E

2002-01-01

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

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

USGS Publications Warehouse

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

PubMed

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

PubMed

Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

2012-10-12

Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

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

PubMed

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

2016-03-09

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

Dispersion and sampling of adult Dermacentor andersoni in rangeland in Western North America.

PubMed

Rochon, K; Scoles, G A; Lysyk, T J

2012-03-01

A fixed precision sampling plan was developed for off-host populations of adult Rocky Mountain wood tick, Dermacentor andersoni (Stiles) based on data collected by dragging at 13 locations in Alberta, Canada; Washington; and Oregon. In total, 222 site-date combinations were sampled. Each site-date combination was considered a sample, and each sample ranged in size from 86 to 250 10 m2 quadrats. Analysis of simulated quadrats ranging in size from 10 to 50 m2 indicated that the most precise sample unit was the 10 m2 quadrat. Samples taken when abundance < 0.04 ticks per 10 m2 were more likely to not depart significantly from statistical randomness than samples taken when abundance was greater. Data were grouped into ten abundance classes and assessed for fit to the Poisson and negative binomial distributions. The Poisson distribution fit only data in abundance classes < 0.02 ticks per 10 m2, while the negative binomial distribution fit data from all abundance classes. A negative binomial distribution with common k = 0.3742 fit data in eight of the 10 abundance classes. Both the Taylor and Iwao mean-variance relationships were fit and used to predict sample sizes for a fixed level of precision. Sample sizes predicted using the Taylor model tended to underestimate actual sample sizes, while sample sizes estimated using the Iwao model tended to overestimate actual sample sizes. Using a negative binomial with common k provided estimates of required sample sizes closest to empirically calculated sample sizes.

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

Treesearch

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

2016-01-01

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

Accounting for twin births in sample size calculations for randomised trials.

PubMed

Yelland, Lisa N; Sullivan, Thomas R; Collins, Carmel T; Price, David J; McPhee, Andrew J; Lee, Katherine J

2018-05-04

Including twins in randomised trials leads to non-independence or clustering in the data. Clustering has important implications for sample size calculations, yet few trials take this into account. Estimates of the intracluster correlation coefficient (ICC), or the correlation between outcomes of twins, are needed to assist with sample size planning. Our aims were to provide ICC estimates for infant outcomes, describe the information that must be specified in order to account for clustering due to twins in sample size calculations, and develop a simple tool for performing sample size calculations for trials including twins. ICCs were estimated for infant outcomes collected in four randomised trials that included twins. The information required to account for clustering due to twins in sample size calculations is described. A tool that calculates the sample size based on this information was developed in Microsoft Excel and in R as a Shiny web app. ICC estimates ranged between -0.12, indicating a weak negative relationship, and 0.98, indicating a strong positive relationship between outcomes of twins. Example calculations illustrate how the ICC estimates and sample size calculator can be used to determine the target sample size for trials including twins. Clustering among outcomes measured on twins should be taken into account in sample size calculations to obtain the desired power. Our ICC estimates and sample size calculator will be useful for designing future trials that include twins. Publication of additional ICCs is needed to further assist with sample size planning for future trials. © 2018 John Wiley & Sons Ltd.

Sample size determination for estimating antibody seroconversion rate under stable malaria transmission intensity.

PubMed

Sepúlveda, Nuno; Drakeley, Chris

2015-04-03

In the last decade, several epidemiological studies have demonstrated the potential of using seroprevalence (SP) and seroconversion rate (SCR) as informative indicators of malaria burden in low transmission settings or in populations on the cusp of elimination. However, most of studies are designed to control ensuing statistical inference over parasite rates and not on these alternative malaria burden measures. SP is in essence a proportion and, thus, many methods exist for the respective sample size determination. In contrast, designing a study where SCR is the primary endpoint, is not an easy task because precision and statistical power are affected by the age distribution of a given population. Two sample size calculators for SCR estimation are proposed. The first one consists of transforming the confidence interval for SP into the corresponding one for SCR given a known seroreversion rate (SRR). The second calculator extends the previous one to the most common situation where SRR is unknown. In this situation, data simulation was used together with linear regression in order to study the expected relationship between sample size and precision. The performance of the first sample size calculator was studied in terms of the coverage of the confidence intervals for SCR. The results pointed out to eventual problems of under or over coverage for sample sizes ≤250 in very low and high malaria transmission settings (SCR ≤ 0.0036 and SCR ≥ 0.29, respectively). The correct coverage was obtained for the remaining transmission intensities with sample sizes ≥ 50. Sample size determination was then carried out for cross-sectional surveys using realistic SCRs from past sero-epidemiological studies and typical age distributions from African and non-African populations. For SCR < 0.058, African studies require a larger sample size than their non-African counterparts in order to obtain the same precision. The opposite happens for the remaining transmission intensities. With respect to the second sample size calculator, simulation unravelled the likelihood of not having enough information to estimate SRR in low transmission settings (SCR ≤ 0.0108). In that case, the respective estimates tend to underestimate the true SCR. This problem is minimized by sample sizes of no less than 500 individuals. The sample sizes determined by this second method highlighted the prior expectation that, when SRR is not known, sample sizes are increased in relation to the situation of a known SRR. In contrast to the first sample size calculation, African studies would now require lesser individuals than their counterparts conducted elsewhere, irrespective of the transmission intensity. Although the proposed sample size calculators can be instrumental to design future cross-sectional surveys, the choice of a particular sample size must be seen as a much broader exercise that involves weighting statistical precision with ethical issues, available human and economic resources, and possible time constraints. Moreover, if the sample size determination is carried out on varying transmission intensities, as done here, the respective sample sizes can also be used in studies comparing sites with different malaria transmission intensities. In conclusion, the proposed sample size calculators are a step towards the design of better sero-epidemiological studies. Their basic ideas show promise to be applied to the planning of alternative sampling schemes that may target or oversample specific age groups.

Phase II Trials for Heterogeneous Patient Populations with a Time-to-Event Endpoint.

PubMed

Jung, Sin-Ho

2017-07-01

In this paper, we consider a single-arm phase II trial with a time-to-event end-point. We assume that the study population has multiple subpopulations with different prognosis, but the study treatment is expected to be similarly efficacious across the subpopulations. We review a stratified one-sample log-rank test and present its sample size calculation method under some practical design settings. Our sample size method requires specification of the prevalence of subpopulations. We observe that the power of the resulting sample size is not very sensitive to misspecification of the prevalence.

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

PubMed

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

2017-01-01

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

Capturing heterogeneity: The role of a study area's extent for estimating mean throughfall

NASA Astrophysics Data System (ADS)

Zimmermann, Alexander; Voss, Sebastian; Metzger, Johanna Clara; Hildebrandt, Anke; Zimmermann, Beate

2016-11-01

The selection of an appropriate spatial extent of a sampling plot is one among several important decisions involved in planning a throughfall sampling scheme. In fact, the choice of the extent may determine whether or not a study can adequately characterize the hydrological fluxes of the studied ecosystem. Previous attempts to optimize throughfall sampling schemes focused on the selection of an appropriate sample size, support, and sampling design, while comparatively little attention has been given to the role of the extent. In this contribution, we investigated the influence of the extent on the representativeness of mean throughfall estimates for three forest ecosystems of varying stand structure. Our study is based on virtual sampling of simulated throughfall fields. We derived these fields from throughfall data sampled in a simply structured forest (young tropical forest) and two heterogeneous forests (old tropical forest, unmanaged mixed European beech forest). We then sampled the simulated throughfall fields with three common extents and various sample sizes for a range of events and for accumulated data. Our findings suggest that the size of the study area should be carefully adapted to the complexity of the system under study and to the required temporal resolution of the throughfall data (i.e. event-based versus accumulated). Generally, event-based sampling in complex structured forests (conditions that favor comparatively long autocorrelations in throughfall) requires the largest extents. For event-based sampling, the choice of an appropriate extent can be as important as using an adequate sample size.

Image analysis of representative food structures: application of the bootstrap method.

PubMed

Ramírez, Cristian; Germain, Juan C; Aguilera, José M

2009-08-01

Images (for example, photomicrographs) are routinely used as qualitative evidence of the microstructure of foods. In quantitative image analysis it is important to estimate the area (or volume) to be sampled, the field of view, and the resolution. The bootstrap method is proposed to estimate the size of the sampling area as a function of the coefficient of variation (CV(Bn)) and standard error (SE(Bn)) of the bootstrap taking sub-areas of different sizes. The bootstrap method was applied to simulated and real structures (apple tissue). For simulated structures, 10 computer-generated images were constructed containing 225 black circles (elements) and different coefficient of variation (CV(image)). For apple tissue, 8 images of apple tissue containing cellular cavities with different CV(image) were analyzed. Results confirmed that for simulated and real structures, increasing the size of the sampling area decreased the CV(Bn) and SE(Bn). Furthermore, there was a linear relationship between the CV(image) and CV(Bn) (.) For example, to obtain a CV(Bn) = 0.10 in an image with CV(image) = 0.60, a sampling area of 400 x 400 pixels (11% of whole image) was required, whereas if CV(image) = 1.46, a sampling area of 1000 x 100 pixels (69% of whole image) became necessary. This suggests that a large-size dispersion of element sizes in an image requires increasingly larger sampling areas or a larger number of images.

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

NASA Technical Reports Server (NTRS)

Rao, R. G. S.; Ulaby, F. T.

1977-01-01

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

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

PubMed

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

2011-02-02

In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 x 2 factorial design. We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 x 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the combination trial. Current Controlled Trials ISRCTN61649292.

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…

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali

PubMed Central

2012-01-01

Background Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. Methods We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. Results VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Conclusions Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes. PMID:23057445

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

PubMed

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

Interpolation Approach To Computer-Generated Holograms

NASA Astrophysics Data System (ADS)

Yatagai, Toyohiko

1983-10-01

A computer-generated hologram (CGH) for reconstructing independent NxN resolution points would actually require a hologram made up of NxN sampling cells. For dependent sampling points of Fourier transform CGHs, the required memory size for computation by using an interpolation technique for reconstructed image points can be reduced. We have made a mosaic hologram which consists of K x K subholograms with N x N sampling points multiplied by an appropriate weighting factor. It is shown that the mosaic hologram can reconstruct an image with NK x NK resolution points. The main advantage of the present algorithm is that a sufficiently large size hologram of NK x NK sample points is synthesized by K x K subholograms which are successively calculated from the data of N x N sample points and also successively plotted.

Particle size analysis of sediments, soils and related particulate materials for forensic purposes using laser granulometry.

PubMed

Pye, Kenneth; Blott, Simon J

2004-08-11

Particle size is a fundamental property of any sediment, soil or dust deposit which can provide important clues to nature and provenance. For forensic work, the particle size distribution of sometimes very small samples requires precise determination using a rapid and reliable method with a high resolution. The Coulter trade mark LS230 laser granulometer offers rapid and accurate sizing of particles in the range 0.04-2000 microm for a variety of sample types, including soils, unconsolidated sediments, dusts, powders and other particulate materials. Reliable results are possible for sample weights of just 50 mg. Discrimination between samples is performed on the basis of the shape of the particle size curves and statistical measures of the size distributions. In routine forensic work laser granulometry data can rarely be used in isolation and should be considered in combination with results from other techniques to reach an overall conclusion.

Revisiting sample size: are big trials the answer?

PubMed

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

2012-07-18

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

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials

PubMed Central

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

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

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

PubMed

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

2017-12-04

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

Sample size determination for equivalence assessment with multiple endpoints.

PubMed

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

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

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

PubMed

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

2010-06-30

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

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

PubMed

Alegana, Victor A; Wright, Jim; Bosco, Claudio; Okiro, Emelda A; Atkinson, Peter M; Snow, Robert W; Tatem, Andrew J; Noor, Abdisalan M

2017-11-21

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

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

PubMed

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

2017-08-17

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

An anthropometric analysis of Korean male helicopter pilots for helicopter cockpit design.

PubMed

Lee, Wonsup; Jung, Kihyo; Jeong, Jeongrim; Park, Jangwoon; Cho, Jayoung; Kim, Heeeun; Park, Seikwon; You, Heecheon

2013-01-01

This study measured 21 anthropometric dimensions (ADs) of 94 Korean male helicopter pilots in their 20s to 40s and compared them with corresponding measurements of Korean male civilians and the US Army male personnel. The ADs and the sample size of the anthropometric survey were determined by a four-step process: (1) selection of ADs related to helicopter cockpit design, (2) evaluation of the importance of each AD, (3) calculation of required sample sizes for selected precision levels and (4) determination of an appropriate sample size by considering both the AD importance evaluation results and the sample size requirements. The anthropometric comparison reveals that the Korean helicopter pilots are larger (ratio of means = 1.01-1.08) and less dispersed (ratio of standard deviations = 0.71-0.93) than the Korean male civilians and that they are shorter in stature (0.99), have shorter upper limbs (0.89-0.96) and lower limbs (0.93-0.97), but are taller on sitting height, sitting eye height and acromial height (1.01-1.03), and less dispersed (0.68-0.97) than the US Army personnel. The anthropometric characteristics of Korean male helicopter pilots were compared with those of Korean male civilians and US Army male personnel. The sample size determination process and the anthropometric comparison results presented in this study are useful to design an anthropometric survey and a helicopter cockpit layout, respectively.

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

NASA Astrophysics Data System (ADS)

Yuan, Chao; Chareyre, Bruno; Darve, Félix

2016-09-01

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

QA/QC requirements for physical properties sampling and analysis

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

Innis, B.E.

1993-07-21

This report presents results of an assessment of the available information concerning US Environmental Protection Agency (EPA) quality assurance/quality control (QA/QC) requirements and guidance applicable to sampling, handling, and analyzing physical parameter samples at Comprehensive Environmental Restoration, Compensation, and Liability Act (CERCLA) investigation sites. Geotechnical testing laboratories measure the following physical properties of soil and sediment samples collected during CERCLA remedial investigations (RI) at the Hanford Site: moisture content, grain size by sieve, grain size by hydrometer, specific gravity, bulk density/porosity, saturated hydraulic conductivity, moisture retention, unsaturated hydraulic conductivity, and permeability of rocks by flowing air. Geotechnical testing laboratories alsomore » measure the following chemical parameters of soil and sediment samples collected during Hanford Site CERCLA RI: calcium carbonate and saturated column leach testing. Physical parameter data are used for (1) characterization of vadose and saturated zone geology and hydrogeology, (2) selection of monitoring well screen sizes, (3) to support modeling and analysis of the vadose and saturated zones, and (4) for engineering design. The objectives of this report are to determine the QA/QC levels accepted in the EPA Region 10 for the sampling, handling, and analysis of soil samples for physical parameters during CERCLA RI.« less

Optimal design in pediatric pharmacokinetic and pharmacodynamic clinical studies.

PubMed

Roberts, Jessica K; Stockmann, Chris; Balch, Alfred; Yu, Tian; Ward, Robert M; Spigarelli, Michael G; Sherwin, Catherine M T

2015-03-01

It is not trivial to conduct clinical trials with pediatric participants. Ethical, logistical, and financial considerations add to the complexity of pediatric studies. Optimal design theory allows investigators the opportunity to apply mathematical optimization algorithms to define how to structure their data collection to answer focused research questions. These techniques can be used to determine an optimal sample size, optimal sample times, and the number of samples required for pharmacokinetic and pharmacodynamic studies. The aim of this review is to demonstrate how to determine optimal sample size, optimal sample times, and the number of samples required from each patient by presenting specific examples using optimal design tools. Additionally, this review aims to discuss the relative usefulness of sparse vs rich data. This review is intended to educate the clinician, as well as the basic research scientist, whom plan on conducting a pharmacokinetic/pharmacodynamic clinical trial in pediatric patients. © 2015 John Wiley & Sons Ltd.

Measuring larval nematode contamination on cattle pastures: Comparing two herbage sampling methods.

PubMed

Verschave, S H; Levecke, B; Duchateau, L; Vercruysse, J; Charlier, J

2015-06-15

Assessing levels of pasture larval contamination is frequently used to study the population dynamics of the free-living stages of parasitic nematodes of livestock. Direct quantification of infective larvae (L3) on herbage is the most applied method to measure pasture larval contamination. However, herbage collection remains labour intensive and there is a lack of studies addressing the variation induced by the sampling method and the required sample size. The aim of this study was (1) to compare two different sampling methods in terms of pasture larval count results and time required to sample, (2) to assess the amount of variation in larval counts at the level of sample plot, pasture and season, respectively and (3) to calculate the required sample size to assess pasture larval contamination with a predefined precision using random plots across pasture. Eight young stock pastures of different commercial dairy herds were sampled in three consecutive seasons during the grazing season (spring, summer and autumn). On each pasture, herbage samples were collected through both a double-crossed W-transect with samples taken every 10 steps (method 1) and four random located plots of 0.16 m(2) with collection of all herbage within the plot (method 2). The average (± standard deviation (SD)) pasture larval contamination using sampling methods 1 and 2 was 325 (± 479) and 305 (± 444)L3/kg dry herbage (DH), respectively. Large discrepancies in pasture larval counts of the same pasture and season were often seen between methods, but no significant difference (P = 0.38) in larval counts between methods was found. Less time was required to collect samples with method 2. This difference in collection time between methods was most pronounced for pastures with a surface area larger than 1 ha. The variation in pasture larval counts from samples generated by random plot sampling was mainly due to the repeated measurements on the same pasture in the same season (residual variance component = 6.2), rather than due to pasture (variance component = 0.55) or season (variance component = 0.15). Using the observed distribution of L3, the required sample size (i.e. number of plots per pasture) for sampling a pasture through random plots with a particular precision was simulated. A higher relative precision was acquired when estimating PLC on pastures with a high larval contamination and a low level of aggregation compared to pastures with a low larval contamination when the same sample size was applied. In the future, herbage sampling through random plots across pasture (method 2) seems a promising method to develop further as no significant difference in counts between the methods was found and this method was less time consuming. Copyright © 2015 Elsevier B.V. All rights reserved.

On the role of dimensionality and sample size for unstructured and structured covariance matrix estimation

NASA Technical Reports Server (NTRS)

Morgera, S. D.; Cooper, D. B.

1976-01-01

The experimental observation that a surprisingly small sample size vis-a-vis dimension is needed to achieve good signal-to-interference ratio (SIR) performance with an adaptive predetection filter is explained. The adaptive filter requires estimates as obtained by a recursive stochastic algorithm of the inverse of the filter input data covariance matrix. The SIR performance with sample size is compared for the situations where the covariance matrix estimates are of unstructured (generalized) form and of structured (finite Toeplitz) form; the latter case is consistent with weak stationarity of the input data stochastic process.

Reproducibility of preclinical animal research improves with heterogeneity of study samples

PubMed Central

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

2018-01-01

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

Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate.

PubMed

Sepúlveda, Nuno; Paulino, Carlos Daniel; Drakeley, Chris

2015-12-30

Several studies have highlighted the use of serological data in detecting a reduction in malaria transmission intensity. These studies have typically used serology as an adjunct measure and no formal examination of sample size calculations for this approach has been conducted. A sample size calculator is proposed for cross-sectional surveys using data simulation from a reverse catalytic model assuming a reduction in seroconversion rate (SCR) at a given change point before sampling. This calculator is based on logistic approximations for the underlying power curves to detect a reduction in SCR in relation to the hypothesis of a stable SCR for the same data. Sample sizes are illustrated for a hypothetical cross-sectional survey from an African population assuming a known or unknown change point. Overall, data simulation demonstrates that power is strongly affected by assuming a known or unknown change point. Small sample sizes are sufficient to detect strong reductions in SCR, but invariantly lead to poor precision of estimates for current SCR. In this situation, sample size is better determined by controlling the precision of SCR estimates. Conversely larger sample sizes are required for detecting more subtle reductions in malaria transmission but those invariantly increase precision whilst reducing putative estimation bias. The proposed sample size calculator, although based on data simulation, shows promise of being easily applicable to a range of populations and survey types. Since the change point is a major source of uncertainty, obtaining or assuming prior information about this parameter might reduce both the sample size and the chance of generating biased SCR estimates.

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

USDA-ARS?s Scientific Manuscript database

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...

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

PubMed

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

2017-09-14

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

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

PubMed

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

2016-09-01

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

Statistical Methods in Assembly Quality Management of Multi-Element Products on Automatic Rotor Lines

NASA Astrophysics Data System (ADS)

Pries, V. V.; Proskuriakov, N. E.

2018-04-01

To control the assembly quality of multi-element mass-produced products on automatic rotor lines, control methods with operational feedback are required. However, due to possible failures in the operation of the devices and systems of automatic rotor line, there is always a real probability of getting defective (incomplete) products into the output process stream. Therefore, a continuous sampling control of the products completeness, based on the use of statistical methods, remains an important element in managing the quality of assembly of multi-element mass products on automatic rotor lines. The feature of continuous sampling control of the multi-element products completeness in the assembly process is its breaking sort, which excludes the possibility of returning component parts after sampling control to the process stream and leads to a decrease in the actual productivity of the assembly equipment. Therefore, the use of statistical procedures for continuous sampling control of the multi-element products completeness when assembled on automatic rotor lines requires the use of such sampling plans that ensure a minimum size of control samples. Comparison of the values of the limit of the average output defect level for the continuous sampling plan (CSP) and for the automated continuous sampling plan (ACSP) shows the possibility of providing lower limit values for the average output defects level using the ACSP-1. Also, the average sample size when using the ACSP-1 plan is less than when using the CSP-1 plan. Thus, the application of statistical methods in the assembly quality management of multi-element products on automatic rotor lines, involving the use of proposed plans and methods for continuous selective control, will allow to automating sampling control procedures and the required level of quality of assembled products while minimizing sample size.

A standardized sampling protocol for channel catfish in prairie streams

USGS Publications Warehouse

Vokoun, Jason C.; Rabeni, Charles F.

2001-01-01

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

A general approach for sample size calculation for the three-arm 'gold standard' non-inferiority design.

PubMed

Stucke, Kathrin; Kieser, Meinhard

2012-12-10

In the three-arm 'gold standard' non-inferiority design, an experimental treatment, an active reference, and a placebo are compared. This design is becoming increasingly popular, and it is, whenever feasible, recommended for use by regulatory guidelines. We provide a general method to calculate the required sample size for clinical trials performed in this design. As special cases, the situations of continuous, binary, and Poisson distributed outcomes are explored. Taking into account the correlation structure of the involved test statistics, the proposed approach leads to considerable savings in sample size as compared with application of ad hoc methods for all three scale levels. Furthermore, optimal sample size allocation ratios are determined that result in markedly smaller total sample sizes as compared with equal assignment. As optimal allocation makes the active treatment groups larger than the placebo group, implementation of the proposed approach is also desirable from an ethical viewpoint. Copyright © 2012 John Wiley & Sons, Ltd.

40 CFR 86.1845-01 - Manufacturer in-use verification testing requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... of test vehicles in the sample comply with the sample size requirements of this section. Any post... vehicles, light-duty trucks, and complete heavy-duty vehicles shall test, or cause to have tested a...) Low mileage testing. [Reserved] (c) High-mileage testing—(1) Test groups. Testing must be conducted...

40 CFR 86.1845-01 - Manufacturer in-use verification testing requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of test vehicles in the sample comply with the sample size requirements of this section. Any post... vehicles, light-duty trucks, and complete heavy-duty vehicles shall test, or cause to have tested a...) Low mileage testing. [Reserved] (c) High-mileage testing—(1) Test groups. Testing must be conducted...

40 CFR 86.1845-01 - Manufacturer in-use verification testing requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... of test vehicles in the sample comply with the sample size requirements of this section. Any post... vehicles, light-duty trucks, and complete heavy-duty vehicles shall test, or cause to have tested a...) Low mileage testing. [Reserved] (c) High-mileage testing—(1) Test groups. Testing must be conducted...

40 CFR 86.1845-01 - Manufacturer in-use verification testing requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of test vehicles in the sample comply with the sample size requirements of this section. Any post... vehicles, light-duty trucks, and complete heavy-duty vehicles shall test, or cause to have tested a...) Low mileage testing. [Reserved] (c) High-mileage testing—(1) Test groups. Testing must be conducted...

40 CFR 86.1845-04 - Manufacturer in-use verification testing requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of test vehicles in the sample comply with the sample size requirements of this section. Any post... HDV must test, or cause to have tested, a specified number of vehicles. Such testing must be conducted... first test will be considered the official results for the test vehicle, regardless of any test results...

The cost of large numbers of hypothesis tests on power, effect size and sample size.

PubMed

Lazzeroni, L C; Ray, A

2012-01-01

Advances in high-throughput biology and computer science are driving an exponential increase in the number of hypothesis tests in genomics and other scientific disciplines. Studies using current genotyping platforms frequently include a million or more tests. In addition to the monetary cost, this increase imposes a statistical cost owing to the multiple testing corrections needed to avoid large numbers of false-positive results. To safeguard against the resulting loss of power, some have suggested sample sizes on the order of tens of thousands that can be impractical for many diseases or may lower the quality of phenotypic measurements. This study examines the relationship between the number of tests on the one hand and power, detectable effect size or required sample size on the other. We show that once the number of tests is large, power can be maintained at a constant level, with comparatively small increases in the effect size or sample size. For example at the 0.05 significance level, a 13% increase in sample size is needed to maintain 80% power for ten million tests compared with one million tests, whereas a 70% increase in sample size is needed for 10 tests compared with a single test. Relative costs are less when measured by increases in the detectable effect size. We provide an interactive Excel calculator to compute power, effect size or sample size when comparing study designs or genome platforms involving different numbers of hypothesis tests. The results are reassuring in an era of extreme multiple testing.

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

PubMed Central

2011-01-01

Background In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 × 2 factorial design. Methods We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. Results In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Conclusions Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 × 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the combination trial. Trial registration Current Controlled Trials ISRCTN61649292 PMID:21288326

Measures of precision for dissimilarity-based multivariate analysis of ecological communities

PubMed Central

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. PMID:25438826

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2015-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a 'Color-Enhanced' sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2016-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a "Color-Enhanced" sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

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

USGS Publications Warehouse

Ellison, Laura E.; Lukacs, Paul M.

2014-01-01

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

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

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

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

PubMed

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

2017-12-01

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

Glass frit nebulizer for atomic spectrometry

USGS Publications Warehouse

Layman, L.R.

1982-01-01

The nebuilizatlon of sample solutions Is a critical step In most flame or plasma atomic spectrometrlc methods. A novel nebulzatlon technique, based on a porous glass frit, has been Investigated. Basic operating parameters and characteristics have been studied to determine how thte new nebulizer may be applied to atomic spectrometrlc methods. The results of preliminary comparisons with pneumatic nebulizers Indicate several notable differences. The frit nebulizer produces a smaller droplet size distribution and has a higher sample transport efficiency. The mean droplet size te approximately 0.1 ??m, and up to 94% of the sample te converted to usable aerosol. The most significant limitations In the performance of the frit nebulizer are the stow sample equMbratton time and the requirement for wash cycles between samples. Loss of solute by surface adsorption and contamination of samples by leaching from the glass were both found to be limitations only In unusual cases. This nebulizer shows great promise where sample volume te limited or where measurements require long nebullzatlon times.

Sample size considerations for clinical research studies in nuclear cardiology.

PubMed

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.

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

PubMed

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

2009-12-01

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

Methods for flexible sample-size design in clinical trials: Likelihood, weighted, dual test, and promising zone approaches.

PubMed

Shih, Weichung Joe; Li, Gang; Wang, Yining

2016-03-01

Sample size plays a crucial role in clinical trials. Flexible sample-size designs, as part of the more general category of adaptive designs that utilize interim data, have been a popular topic in recent years. In this paper, we give a comparative review of four related methods for such a design. The likelihood method uses the likelihood ratio test with an adjusted critical value. The weighted method adjusts the test statistic with given weights rather than the critical value. The dual test method requires both the likelihood ratio statistic and the weighted statistic to be greater than the unadjusted critical value. The promising zone approach uses the likelihood ratio statistic with the unadjusted value and other constraints. All four methods preserve the type-I error rate. In this paper we explore their properties and compare their relationships and merits. We show that the sample size rules for the dual test are in conflict with the rules of the promising zone approach. We delineate what is necessary to specify in the study protocol to ensure the validity of the statistical procedure and what can be kept implicit in the protocol so that more flexibility can be attained for confirmatory phase III trials in meeting regulatory requirements. We also prove that under mild conditions, the likelihood ratio test still preserves the type-I error rate when the actual sample size is larger than the re-calculated one. Copyright © 2015 Elsevier Inc. All rights reserved.

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

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

PubMed

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

2013-01-01

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

Survival distributions impact the power of randomized placebo-phase design and parallel groups randomized clinical trials.

PubMed

Abrahamyan, Lusine; Li, Chuan Silvia; Beyene, Joseph; Willan, Andrew R; Feldman, Brian M

2011-03-01

The study evaluated the power of the randomized placebo-phase design (RPPD)-a new design of randomized clinical trials (RCTs), compared with the traditional parallel groups design, assuming various response time distributions. In the RPPD, at some point, all subjects receive the experimental therapy, and the exposure to placebo is for only a short fixed period of time. For the study, an object-oriented simulation program was written in R. The power of the simulated trials was evaluated using six scenarios, where the treatment response times followed the exponential, Weibull, or lognormal distributions. The median response time was assumed to be 355 days for the placebo and 42 days for the experimental drug. Based on the simulation results, the sample size requirements to achieve the same level of power were different under different response time to treatment distributions. The scenario where the response times followed the exponential distribution had the highest sample size requirement. In most scenarios, the parallel groups RCT had higher power compared with the RPPD. The sample size requirement varies depending on the underlying hazard distribution. The RPPD requires more subjects to achieve a similar power to the parallel groups design. Copyright © 2011 Elsevier Inc. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Towards a definition of inorganic nanoparticles from an environmental, health and safety perspective.

PubMed

Auffan, Mélanie; Rose, Jérôme; Bottero, Jean-Yves; Lowry, Gregory V; Jolivet, Jean-Pierre; Wiesner, Mark R

2009-10-01

The regulation of engineered nanoparticles requires a widely agreed definition of such particles. Nanoparticles are routinely defined as particles with sizes between about 1 and 100 nm that show properties that are not found in bulk samples of the same material. Here we argue that evidence for novel size-dependent properties alone, rather than particle size, should be the primary criterion in any definition of nanoparticles when making decisions about their regulation for environmental, health and safety reasons. We review the size-dependent properties of a variety of inorganic nanoparticles and find that particles larger than about 30 nm do not in general show properties that would require regulatory scrutiny beyond that required for their bulk counterparts.

Digital simulation of scalar optical diffraction: revisiting chirp function sampling criteria and consequences.

PubMed

Voelz, David G; Roggemann, Michael C

2009-11-10

Accurate simulation of scalar optical diffraction requires consideration of the sampling requirement for the phase chirp function that appears in the Fresnel diffraction expression. We describe three sampling regimes for FFT-based propagation approaches: ideally sampled, oversampled, and undersampled. Ideal sampling, where the chirp and its FFT both have values that match analytic chirp expressions, usually provides the most accurate results but can be difficult to realize in practical simulations. Under- or oversampling leads to a reduction in the available source plane support size, the available source bandwidth, or the available observation support size, depending on the approach and simulation scenario. We discuss three Fresnel propagation approaches: the impulse response/transfer function (angular spectrum) method, the single FFT (direct) method, and the two-step method. With illustrations and simulation examples we show the form of the sampled chirp functions and their discrete transforms, common relationships between the three methods under ideal sampling conditions, and define conditions and consequences to be considered when using nonideal sampling. The analysis is extended to describe the sampling limitations for the more exact Rayleigh-Sommerfeld diffraction solution.

ESTIMATING SAMPLE REQUIREMENTS FOR FIELD EVALUATIONS OF PESTICIDE LEACHING

EPA Science Inventory

A method is presented for estimating the number of samples needed to evaluate pesticide leaching threats to ground water at a desired level of precision. Sample size projections are based on desired precision (exhibited as relative tolerable error), level of confidence (90 or 95%...

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

PubMed

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

2015-06-19

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

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

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

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

PubMed

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

2013-10-26

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

Fish habitat conditions: Using the Northern/Intermountain Regions' inventory procedures for detecting differences on two differently managed watersheds

Treesearch

C. Kerry Overton; Michael A. Radko; Rodger L. Nelson

1993-01-01

Differences in fish habitat variables between two studied watersheds may be related to differences in land management. In using the R1/R4 Watershed-Scale Fish Habitat Inventory Process, for most habitat variables, evaluations of sample sizes of at least 30 habitat units were adequate. Guidelines will help land managers in determining sample sizes required to detect...

Nutrition labeling and value size pricing at fast-food restaurants: a consumer perspective.

PubMed

O'Dougherty, Maureen; Harnack, Lisa J; French, Simone A; Story, Mary; Oakes, J Michael; Jeffery, Robert W

2006-01-01

This pilot study examined nutrition-related attitudes that may affect food choices at fast-food restaurants, including consumer attitudes toward nutrition labeling of fast foods and elimination of value size pricing. A convenience sample of 79 fast-food restaurant patrons aged 16 and above (78.5% white, 55% female, mean age 41.2 [17.1]) selected meals from fast-food restaurant menus that varied as to whether nutrition information was provided and value pricing included and completed a survey and interview on nutrition-related attitudes. Only 57.9% of participants rated nutrition as important when buying fast food. Almost two thirds (62%) supported a law requiring nutrition labeling on restaurant menus. One third (34%) supported a law requiring restaurants to offer lower prices on smaller instead of bigger-sized portions. This convenience sample of fast-food patrons supported nutrition labels on menus. More research is needed with larger samples on whether point-of-purchase nutrition labeling at fast-food restaurants raises perceived importance of nutrition when eating out.

Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

PubMed Central

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

Improving the quality of biomarker discovery research: the right samples and enough of them.

PubMed

Pepe, Margaret S; Li, Christopher I; Feng, Ziding

2015-06-01

Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

PubMed

Brinton, John T; Ringham, Brandy M; Glueck, Deborah H

2015-10-13

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult. To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation. We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial. Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

Reduction of Sample Size Requirements by Bilateral Versus Unilateral Research Designs in Animal Models for Cartilage Tissue Engineering

PubMed Central

Orth, Patrick; Zurakowski, David; Alini, Mauro; Cucchiarini, Magali

2013-01-01

Advanced tissue engineering approaches for articular cartilage repair in the knee joint rely on translational animal models. In these investigations, cartilage defects may be established either in one joint (unilateral design) or in both joints of the same animal (bilateral design). We hypothesized that a lower intraindividual variability following the bilateral strategy would reduce the number of required joints. Standardized osteochondral defects were created in the trochlear groove of 18 rabbits. In 12 animals, defects were produced unilaterally (unilateral design; n=12 defects), while defects were created bilaterally in 6 animals (bilateral design; n=12 defects). After 3 weeks, osteochondral repair was evaluated histologically applying an established grading system. Based on intra- and interindividual variabilities, required sample sizes for the detection of discrete differences in the histological score were determined for both study designs (α=0.05, β=0.20). Coefficients of variation (%CV) of the total histological score values were 1.9-fold increased following the unilateral design when compared with the bilateral approach (26 versus 14%CV). The resulting numbers of joints needed to treat were always higher for the unilateral design, resulting in an up to 3.9-fold increase in the required number of experimental animals. This effect was most pronounced for the detection of small-effect sizes and estimating large standard deviations. The data underline the possible benefit of bilateral study designs for the decrease of sample size requirements for certain investigations in articular cartilage research. These findings might also be transferred to other scoring systems, defect types, or translational animal models in the field of cartilage tissue engineering. PMID:23510128

Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Batista, G. T.

1984-01-01

A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.

Measures of precision for dissimilarity-based multivariate analysis of ecological communities.

PubMed

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

The Army Communications Objectives Measurement System (ACOMS): Survey Design

DTIC Science & Technology

1988-04-01

monthly basis so that the annual sample includes sufficient Hispanics to detect at the .80 power level: (1) Year-to-year changes of 3% in item...Hispanics. The requirements are listed in terms of power level and must be translated into requisite sample sizes. The requirements are expressed as the...annual samples needed to detect certain differences at the 80% power level. Differences in both directions are to be examined, so that a two-tailed

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

PubMed

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

2017-08-15

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

How large a training set is needed to develop a classifier for microarray data?

PubMed

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

A Re-Evaluation of the Size of the White Shark (Carcharodon carcharias) Population off California, USA

PubMed Central

Burgess, George H.; Bruce, Barry D.; Cailliet, Gregor M.; Goldman, Kenneth J.; Grubbs, R. Dean; Lowe, Christopher G.; MacNeil, M. Aaron; Mollet, Henry F.; Weng, Kevin C.; O'Sullivan, John B.

2014-01-01

White sharks are highly migratory and segregate by sex, age and size. Unlike marine mammals, they neither surface to breathe nor frequent haul-out sites, hindering generation of abundance data required to estimate population size. A recent tag-recapture study used photographic identifications of white sharks at two aggregation sites to estimate abundance in “central California” at 219 mature and sub-adult individuals. They concluded this represented approximately one-half of the total abundance of mature and sub-adult sharks in the entire eastern North Pacific Ocean (ENP). This low estimate generated great concern within the conservation community, prompting petitions for governmental endangered species designations. We critically examine that study and find violations of model assumptions that, when considered in total, lead to population underestimates. We also use a Bayesian mixture model to demonstrate that the inclusion of transient sharks, characteristic of white shark aggregation sites, would substantially increase abundance estimates for the adults and sub-adults in the surveyed sub-population. Using a dataset obtained from the same sampling locations and widely accepted demographic methodology, our analysis indicates a minimum all-life stages population size of >2000 individuals in the California subpopulation is required to account for the number and size range of individual sharks observed at the two sampled sites. Even accounting for methodological and conceptual biases, an extrapolation of these data to estimate the white shark population size throughout the ENP is inappropriate. The true ENP white shark population size is likely several-fold greater as both our study and the original published estimate exclude non-aggregating sharks and those that independently aggregate at other important ENP sites. Accurately estimating the central California and ENP white shark population size requires methodologies that account for biases introduced by sampling a limited number of sites and that account for all life history stages across the species' range of habitats. PMID:24932483

A re-evaluation of the size of the white shark (Carcharodon carcharias) population off California, USA.

PubMed

Burgess, George H; Bruce, Barry D; Cailliet, Gregor M; Goldman, Kenneth J; Grubbs, R Dean; Lowe, Christopher G; MacNeil, M Aaron; Mollet, Henry F; Weng, Kevin C; O'Sullivan, John B

2014-01-01

White sharks are highly migratory and segregate by sex, age and size. Unlike marine mammals, they neither surface to breathe nor frequent haul-out sites, hindering generation of abundance data required to estimate population size. A recent tag-recapture study used photographic identifications of white sharks at two aggregation sites to estimate abundance in "central California" at 219 mature and sub-adult individuals. They concluded this represented approximately one-half of the total abundance of mature and sub-adult sharks in the entire eastern North Pacific Ocean (ENP). This low estimate generated great concern within the conservation community, prompting petitions for governmental endangered species designations. We critically examine that study and find violations of model assumptions that, when considered in total, lead to population underestimates. We also use a Bayesian mixture model to demonstrate that the inclusion of transient sharks, characteristic of white shark aggregation sites, would substantially increase abundance estimates for the adults and sub-adults in the surveyed sub-population. Using a dataset obtained from the same sampling locations and widely accepted demographic methodology, our analysis indicates a minimum all-life stages population size of >2000 individuals in the California subpopulation is required to account for the number and size range of individual sharks observed at the two sampled sites. Even accounting for methodological and conceptual biases, an extrapolation of these data to estimate the white shark population size throughout the ENP is inappropriate. The true ENP white shark population size is likely several-fold greater as both our study and the original published estimate exclude non-aggregating sharks and those that independently aggregate at other important ENP sites. Accurately estimating the central California and ENP white shark population size requires methodologies that account for biases introduced by sampling a limited number of sites and that account for all life history stages across the species' range of habitats.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed Central

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

2011-01-01

Preservation of -cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet), repeated 2-hour Mixed Meal Tolerance Tests (MMTT) were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC) of the C-peptide values. The natural log(), log(+1) and square-root transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8–12 years of age, adolescents (13–17 years) and adults (18+ years). The sample size needed to detect a given relative (percentage) difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13–17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(+1) and transformed values in terms of the original units of measurement (pmol/ml). Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab) versus masked placebo. These results provide the information needed to accurately evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes. PMID:22102862

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

PubMed

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

2011-01-01

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

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

PubMed

Mütze, Tobias; Friede, Tim

2017-10-15

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

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

PubMed

Graf, Alexandra C; Bauer, Peter

2011-06-30

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

Improving risk classification of critical illness with biomarkers: a simulation study

PubMed Central

Seymour, Christopher W.; Cooke, Colin R.; Wang, Zheyu; Kerr, Kathleen F.; Yealy, Donald M.; Angus, Derek C.; Rea, Thomas D.; Kahn, Jeremy M.; Pepe, Margaret S.

2012-01-01

Purpose Optimal triage of patients at risk of critical illness requires accurate risk prediction, yet little data exists on the performance criteria required of a potential biomarker to be clinically useful. Materials and Methods We studied an adult cohort of non-arrest, non-trauma emergency medical services encounters transported to a hospital from 2002–2006. We simulated hypothetical biomarkers increasingly associated with critical illness during hospitalization, and determined the biomarker strength and sample size necessary to improve risk classification beyond a best clinical model. Results Of 57,647 encounters, 3,121 (5.4%) were hospitalized with critical illness and 54,526 (94.6%) without critical illness. The addition of a moderate strength biomarker (odds ratio=3.0 for critical illness) to a clinical model improved discrimination (c-statistic 0.85 vs. 0.8, p<0.01), reclassification (net reclassification improvement=0.15, 95%CI: 0.13,0.18), and increased the proportion of cases in the highest risk categoryby+8.6% (95%CI: 7.5,10.8%). Introducing correlation between the biomarker and physiological variables in the clinical risk score did not modify the results. Statistically significant changes in net reclassification required a sample size of at least 1000 subjects. Conclusions Clinical models for triage of critical illness could be significantly improved by incorporating biomarkers, yet, substantial sample sizes and biomarker strength may be required. PMID:23566734

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

PubMed

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

2017-03-07

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

Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel.

PubMed

Khatkar, Mehar S; Nicholas, Frank W; Collins, Andrew R; Zenger, Kyall R; Cavanagh, Julie A L; Barris, Wes; Schnabel, Robert D; Taylor, Jeremy F; Raadsma, Herman W

2008-04-24

The extent of linkage disequilibrium (LD) within a population determines the number of markers that will be required for successful association mapping and marker-assisted selection. Most studies on LD in cattle reported to date are based on microsatellite markers or small numbers of single nucleotide polymorphisms (SNPs) covering one or only a few chromosomes. This is the first comprehensive study on the extent of LD in cattle by analyzing data on 1,546 Holstein-Friesian bulls genotyped for 15,036 SNP markers covering all regions of all autosomes. Furthermore, most studies in cattle have used relatively small sample sizes and, consequently, may have had biased estimates of measures commonly used to describe LD. We examine minimum sample sizes required to estimate LD without bias and loss in accuracy. Finally, relatively little information is available on comparative LD structures including other mammalian species such as human and mouse, and we compare LD structure in cattle with public-domain data from both human and mouse. We computed three LD estimates, D', Dvol and r2, for 1,566,890 syntenic SNP pairs and a sample of 365,400 non-syntenic pairs. Mean D' is 0.189 among syntenic SNPs, and 0.105 among non-syntenic SNPs; mean r2 is 0.024 among syntenic SNPs and 0.0032 among non-syntenic SNPs. All three measures of LD for syntenic pairs decline with distance; the decline is much steeper for r2 than for D' and Dvol. The value of D' and Dvol are quite similar. Significant LD in cattle extends to 40 kb (when estimated as r2) and 8.2 Mb (when estimated as D'). The mean values for LD at large physical distances are close to those for non-syntenic SNPs. Minor allelic frequency threshold affects the distribution and extent of LD. For unbiased and accurate estimates of LD across marker intervals spanning < 1 kb to > 50 Mb, minimum sample sizes of 400 (for D') and 75 (for r2) are required. The bias due to small samples sizes increases with inter-marker interval. LD in cattle is much less extensive than in a mouse population created from crossing inbred lines, and more extensive than in humans. For association mapping in Holstein-Friesian cattle, for a given design, at least one SNP is required for each 40 kb, giving a total requirement of at least 75,000 SNPs for a low power whole-genome scan (median r2 > 0.19) and up to 300,000 markers at 10 kb intervals for a high power genome scan (median r2 > 0.62). For estimation of LD by D' and Dvol with sufficient precision, a sample size of at least 400 is required, whereas for r2 a minimum sample of 75 is adequate.

Biofouling on buoyant marine plastics: An experimental study into the effect of size on surface longevity.

PubMed

Fazey, Francesca M C; Ryan, Peter G

2016-03-01

Recent estimates suggest that roughly 100 times more plastic litter enters the sea than is found floating at the sea surface, despite the buoyancy and durability of many plastic polymers. Biofouling by marine biota is one possible mechanism responsible for this discrepancy. Microplastics (<5 mm in diameter) are more scarce than larger size classes, which makes sense because fouling is a function of surface area whereas buoyancy is a function of volume; the smaller an object, the greater its relative surface area. We tested whether plastic items with high surface area to volume ratios sank more rapidly by submerging 15 different sizes of polyethylene samples in False Bay, South Africa, for 12 weeks to determine the time required for samples to sink. All samples became sufficiently fouled to sink within the study period, but small samples lost buoyancy much faster than larger ones. There was a direct relationship between sample volume (buoyancy) and the time to attain a 50% probability of sinking, which ranged from 17 to 66 days of exposure. Our results provide the first estimates of the longevity of different sizes of plastic debris at the ocean surface. Further research is required to determine how fouling rates differ on free floating debris in different regions and in different types of marine environments. Such estimates could be used to improve model predictions of the distribution and abundance of floating plastic debris globally. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

Donegan, Thomas M.

2018-01-01

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

Improving size estimates of open animal populations by incorporating information on age

USGS Publications Warehouse

Manly, Bryan F.J.; McDonald, Trent L.; Amstrup, Steven C.; Regehr, Eric V.

2003-01-01

Around the world, a great deal of effort is expended each year to estimate the sizes of wild animal populations. Unfortunately, population size has proven to be one of the most intractable parameters to estimate. The capture-recapture estimation models most commonly used (of the Jolly-Seber type) are complicated and require numerous, sometimes questionable, assumptions. The derived estimates usually have large variances and lack consistency over time. In capture–recapture studies of long-lived animals, the ages of captured animals can often be determined with great accuracy and relative ease. We show how to incorporate age information into size estimates for open populations, where the size changes through births, deaths, immigration, and emigration. The proposed method allows more precise estimates of population size than the usual models, and it can provide these estimates from two sample occasions rather than the three usually required. Moreover, this method does not require specialized programs for capture-recapture data; researchers can derive their estimates using the logistic regression module in any standard statistical package.

Monitoring design for assessing compliance with numeric nutrient standards for rivers and streams using geospatial variables.

PubMed

Williams, Rachel E; Arabi, Mazdak; Loftis, Jim; Elmund, G Keith

2014-09-01

Implementation of numeric nutrient standards in Colorado has prompted a need for greater understanding of human impacts on ambient nutrient levels. This study explored the variability of annual nutrient concentrations due to upstream anthropogenic influences and developed a mathematical expression for the number of samples required to estimate median concentrations for standard compliance. A procedure grounded in statistical hypothesis testing was developed to estimate the number of annual samples required at monitoring locations while taking into account the difference between the median concentrations and the water quality standard for a lognormal population. For the Cache La Poudre River in northern Colorado, the relationship between the median and standard deviation of total N (TN) and total P (TP) concentrations and the upstream point and nonpoint concentrations and general hydrologic descriptors was explored using multiple linear regression models. Very strong relationships were evident between the upstream anthropogenic influences and annual medians for TN and TP ( > 0.85, < 0.001) and corresponding standard deviations ( > 0.7, < 0.001). Sample sizes required to demonstrate (non)compliance with the standard depend on the measured water quality conditions. When the median concentration differs from the standard by >20%, few samples are needed to reach a 95% confidence level. When the median is within 20% of the corresponding water quality standard, however, the required sample size increases rapidly, and hundreds of samples may be required. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Does the bathing water classification depend on sampling strategy? A bootstrap approach for bathing water quality assessment, according to Directive 2006/7/EC requirements.

PubMed

López, Iago; Alvarez, César; Gil, José L; Revilla, José A

2012-11-30

Data on the 95th and 90th percentiles of bacteriological quality indicators are used to classify bathing waters in Europe, according to the requirements of Directive 2006/7/EC. However, percentile values and consequently, classification of bathing waters depend both on sampling effort and sample-size, which may undermine an appropriate assessment of bathing water classification. To analyse the influence of sampling effort and sample size on water classification, a bootstrap approach was applied to 55 bacteriological quality datasets of several beaches in the Balearic Islands (Spain). Our results show that the probability of failing the regulatory standards of the Directive is high when sample size is low, due to a higher variability in percentile values. In this way, 49% of the bathing waters reaching an "Excellent" classification (95th percentile of Escherichia coli under 250 cfu/100 ml) can fail the "Excellent" regulatory standard due to sampling strategy, when 23 samples per season are considered. This percentage increases to 81% when 4 samples per season are considered. "Good" regulatory standards can also be failed in bathing waters with an "Excellent" classification as a result of these sampling strategies. The variability in percentile values may affect bathing water classification and is critical for the appropriate design and implementation of bathing water Quality Monitoring and Assessment Programs. Hence, variability of percentile values should be taken into account by authorities if an adequate management of these areas is to be achieved. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

Meta-analysis of multiple outcomes: a multilevel approach.

PubMed

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

2015-12-01

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

Tissue recommendations for precision cancer therapy using next generation sequencing: a comprehensive single cancer center’s experiences

PubMed Central

Hong, Mineui; Bang, Heejin; Van Vrancken, Michael; Kim, Seungtae; Lee, Jeeyun; Park, Se Hoon; Park, Joon Oh; Park, Young Suk; Lim, Ho Yeong; Kang, Won Ki; Sun, Jong-Mu; Lee, Se Hoon; Ahn, Myung-Ju; Park, Keunchil; Kim, Duk Hwan; Lee, Seunggwan; Park, Woongyang; Kim, Kyoung-Mee

2017-01-01

To generate accurate next-generation sequencing (NGS) data, the amount and quality of DNA extracted is critical. We analyzed 1564 tissue samples from patients with metastatic or recurrent solid tumor submitted for NGS according to their sample size, acquisition method, organ, and fixation to propose appropriate tissue requirements. Of the 1564 tissue samples, 481 (30.8%) consisted of fresh-frozen (FF) tissue, and 1,083 (69.2%) consisted of formalin-fixed paraffin-embedded (FFPE) tissue. We obtained successful NGS results in 95.9% of cases. Out of 481 FF biopsies, 262 tissue samples were from lung, and the mean fragment size was 2.4 mm. Compared to lung, GI tract tumor fragments showed a significantly lower DNA extraction failure rate (2.1 % versus 6.1%, p = 0.04). For FFPE biopsy samples, the size of biopsy tissue was similar regardless of tumor type with a mean of 0.8 × 0.3 cm, and the mean DNA yield per one unstained slide was 114 ng. We obtained highest amount of DNA from the colorectum (2353 ng) and the lowest amount from the hepatobiliary tract (760.3 ng) likely due to a relatively smaller biopsy size, extensive hemorrhage and necrosis, and lower tumor volume. On one unstained slide from FFPE operation specimens, the mean size of the specimen was 2.0 × 1.0 cm, and the mean DNA yield per one unstained slide was 1800 ng. In conclusions, we present our experiences on tissue requirements for appropriate NGS workflow: > 1 mm2 for FF biopsy, > 5 unstained slides for FFPE biopsy, and > 1 unstained slide for FFPE operation specimens for successful test results in 95.9% of cases. PMID:28477007

A Monte-Carlo simulation analysis for evaluating the severity distribution functions (SDFs) calibration methodology and determining the minimum sample-size requirements.

PubMed

Shirazi, Mohammadali; Reddy Geedipally, Srinivas; Lord, Dominique

2017-01-01

Severity distribution functions (SDFs) are used in highway safety to estimate the severity of crashes and conduct different types of safety evaluations and analyses. Developing a new SDF is a difficult task and demands significant time and resources. To simplify the process, the Highway Safety Manual (HSM) has started to document SDF models for different types of facilities. As such, SDF models have recently been introduced for freeway and ramps in HSM addendum. However, since these functions or models are fitted and validated using data from a few selected number of states, they are required to be calibrated to the local conditions when applied to a new jurisdiction. The HSM provides a methodology to calibrate the models through a scalar calibration factor. However, the proposed methodology to calibrate SDFs was never validated through research. Furthermore, there are no concrete guidelines to select a reliable sample size. Using extensive simulation, this paper documents an analysis that examined the bias between the 'true' and 'estimated' calibration factors. It was indicated that as the value of the true calibration factor deviates further away from '1', more bias is observed between the 'true' and 'estimated' calibration factors. In addition, simulation studies were performed to determine the calibration sample size for various conditions. It was found that, as the average of the coefficient of variation (CV) of the 'KAB' and 'C' crashes increases, the analyst needs to collect a larger sample size to calibrate SDF models. Taking this observation into account, sample-size guidelines are proposed based on the average CV of crash severities that are used for the calibration process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modified Toxicity Probability Interval Design: A Safer and More Reliable Method Than the 3 + 3 Design for Practical Phase I Trials

PubMed Central

Ji, Yuan; Wang, Sue-Jane

2013-01-01

The 3 + 3 design is the most common choice among clinicians for phase I dose-escalation oncology trials. In recent reviews, more than 95% of phase I trials have been based on the 3 + 3 design. Given that it is intuitive and its implementation does not require a computer program, clinicians can conduct 3 + 3 dose escalations in practice with virtually no logistic cost, and trial protocols based on the 3 + 3 design pass institutional review board and biostatistics reviews quickly. However, the performance of the 3 + 3 design has rarely been compared with model-based designs in simulation studies with matched sample sizes. In the vast majority of statistical literature, the 3 + 3 design has been shown to be inferior in identifying true maximum-tolerated doses (MTDs), although the sample size required by the 3 + 3 design is often orders-of-magnitude smaller than model-based designs. In this article, through comparative simulation studies with matched sample sizes, we demonstrate that the 3 + 3 design has higher risks of exposing patients to toxic doses above the MTD than the modified toxicity probability interval (mTPI) design, a newly developed adaptive method. In addition, compared with the mTPI design, the 3 + 3 design does not yield higher probabilities in identifying the correct MTD, even when the sample size is matched. Given that the mTPI design is equally transparent, costless to implement with free software, and more flexible in practical situations, we highly encourage its adoption in early dose-escalation studies whenever the 3 + 3 design is also considered. We provide free software to allow direct comparisons of the 3 + 3 design with other model-based designs in simulation studies with matched sample sizes. PMID:23569307

Eddy Covariance Measurements of the Sea-Spray Aerosol Flu

NASA Astrophysics Data System (ADS)

Brooks, I. M.; Norris, S. J.; Yelland, M. J.; Pascal, R. W.; Prytherch, J.

2015-12-01

Historically, almost all estimates of the sea-spray aerosol source flux have been inferred through various indirect methods. Direct estimates via eddy covariance have been attempted by only a handful of studies, most of which measured only the total number flux, or achieved rather coarse size segregation. Applying eddy covariance to the measurement of sea-spray fluxes is challenging: most instrumentation must be located in a laboratory space requiring long sample lines to an inlet collocated with a sonic anemometer; however, larger particles are easily lost to the walls of the sample line. Marine particle concentrations are generally low, requiring a high sample volume to achieve adequate statistics. The highly hygroscopic nature of sea salt means particles change size rapidly with fluctuations in relative humidity; this introduces an apparent bias in flux measurements if particles are sized at ambient humidity. The Compact Lightweight Aerosol Spectrometer Probe (CLASP) was developed specifically to make high rate measurements of aerosol size distributions for use in eddy covariance measurements, and the instrument and data processing and analysis techniques have been refined over the course of several projects. Here we will review some of the issues and limitations related to making eddy covariance measurements of the sea spray source flux over the open ocean, summarise some key results from the last decade, and present new results from a 3-year long ship-based measurement campaign as part of the WAGES project. Finally we will consider requirements for future progress.

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

PubMed

van Rijnsoever, Frank J

2017-01-01

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

Influences of sampling size and pattern on the uncertainty of correlation estimation between soil water content and its influencing factors

NASA Astrophysics Data System (ADS)

Lai, Xiaoming; Zhu, Qing; Zhou, Zhiwen; Liao, Kaihua

2017-12-01

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

Sampling and data handling methods for inhalable particulate sampling. Final report nov 78-dec 80

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

Smith, W.B.; Cushing, K.M.; Johnson, J.W.

1982-05-01

The report reviews the objectives of a research program on sampling and measuring particles in the inhalable particulate (IP) size range in emissions from stationary sources, and describes methods and equipment required. A computer technique was developed to analyze data on particle-size distributions of samples taken with cascade impactors from industrial process streams. Research in sampling systems for IP matter included concepts for maintaining isokinetic sampling conditions, necessary for representative sampling of the larger particles, while flowrates in the particle-sizing device were constant. Laboratory studies were conducted to develop suitable IP sampling systems with overall cut diameters of 15 micrometersmore » and conforming to a specified collection efficiency curve. Collection efficiencies were similarly measured for a horizontal elutriator. Design parameters were calculated for horizontal elutriators to be used with impactors, the EPA SASS train, and the EPA FAS train. Two cyclone systems were designed and evaluated. Tests on an Andersen Size Selective Inlet, a 15-micrometer precollector for high-volume samplers, showed its performance to be with the proposed limits for IP samplers. A stack sampling system was designed in which the aerosol is diluted in flow patterns and with mixing times simulating those in stack plumes.« less

Sample size calculation in economic evaluations.

PubMed

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

1998-06-01

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

77 FR 16517 - Agency Information Collection Activities: Proposed Collection; Comment Request-Information...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-21

... children and provide low cost or free school lunch meals to qualified students through subsidies to schools... records to demonstrate compliance with the meal requirements. To the extent practicable, schools ensure... verification of a required sample size), the number of meals served, and data from required reviews conducted...

7 CFR 51.2927 - Marking and packing requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Requirements § 51.2927 Marking and packing requirements. The minimum size or numerical count of the apricots in any package shall be plainly labeled, stenciled, or otherwise marked on the package. (a) Numerical count. When the numerical count is used the fruit in any sample shall not vary more than one-fourth inch...

7 CFR 51.2927 - Marking and packing requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Requirements § 51.2927 Marking and packing requirements. The minimum size or numerical count of the apricots in any package shall be plainly labeled, stenciled, or otherwise marked on the package. (a) Numerical count. When the numerical count is used the fruit in any sample shall not vary more than one-fourth inch...

Sample size and allocation of effort in point count sampling of birds in bottomland hardwood forests

USGS Publications Warehouse

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. Although no interaction was detected between number of points and number of visits, when paired reciprocals were compared, more points invariably yielded a significantly greater cumulative number of species than more visits to a point. Still, 36 point counts per stand during each of two breeding seasons detected only 52 percent of the known available species pool in DEF.

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

PubMed

Seto, Mayumi; Uriu, Koichiro

2015-03-01

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

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

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

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-07-01

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

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

PubMed

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

2015-10-01

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

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

PubMed Central

Moser, Barry Kurt; Halabi, Susan

2013-01-01

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

Heat and Bleach: A Cost-Efficient Method for Extracting Microplastics from Return Activated Sludge.

PubMed

Sujathan, Surya; Kniggendorf, Ann-Kathrin; Kumar, Arun; Roth, Bernhard; Rosenwinkel, Karl-Heinz; Nogueira, Regina

2017-11-01

The extraction of plastic microparticles, so-called microplastics, from sludge is a challenging task due to the complex, highly organic material often interspersed with other benign microparticles. The current procedures for microplastic extraction from sludge are time consuming and require expensive reagents for density separation as well as large volumes of oxidizing agents for organic removal, often resulting in tiny sample sizes and thus a disproportional risk of sample bias. In this work, we present an improved extraction method tested on return activated sludge (RAS). The treatment of 100 ml of RAS requires only 6% hydrogen peroxide (H 2 O 2 ) for bleaching at 70 °C, followed by density separation with sodium nitrate/sodium thiosulfate (SNT) solution, and is completed within 24 h. Extracted particles of all sizes were chemically analyzed with confocal Raman microscopy. An extraction efficiency of 78 ± 8% for plastic particle sizes 20 µm and up was confirmed in a recovery experiment. However, glass shards with a diameter of less than 20 µm remained in the sample despite the density of glass exceeding the density of the separating SNT solution by 1.1 g/cm 3 . This indicates that density separation may be unreliable for particle sizes in the lower micrometer range.

Instrumentation for Measurement of Gas Permeability of Polymeric Membranes

NASA Technical Reports Server (NTRS)

Upchurch, Billy T.; Wood, George M.; Brown, Kenneth G.; Burns, Karen S.

1993-01-01

A mass spectrometric 'Dynamic Delta' method for the measurement of gas permeability of polymeric membranes has been developed. The method is universally applicable for measurement of the permeability of any gas through polymeric membrane materials. The usual large sample size of more than 100 square centimeters required for other methods is not necessary for this new method which requires a size less than one square centimeter. The new method should fulfill requirements and find applicability for industrial materials such as food packaging, contact lenses and other commercial materials where gas permeability or permselectivity properties are important.

Mixing problems in using indicators for measuring regional blood flow

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

Ushioda, E.; Nuwayhid, B.; Tabsh, K.

A basic requirement for using indicators for measuring blood flow is adequate mixing of the indicator with blood prior to sampling the site. This requirement has been met by depositing the indicator in the heart and sampling from an artery. Recently, authors have injected microspheres into veins and sampled from venous sites. The present studies were designed to investigate the mixing problems in sheep and rabbits by means of Cardio-Green and labeled microspheres. The indicators were injected at different points in the circulatory system, and blood was sampled at different levels of the venous and arterial systems. Results show themore » following: (a) When an indicator of small molecular size (Cardio-Green) is allowed to pass through the heart chambers, adequate mixing is achieved, yielding accurate and reproducible results. (b) When any indicator (Cardio-Green or microspheres) is injected into veins, and sampling is done at any point in the venous system, mixing is inadequate, yielding flow results which are inconsistent and erratic. (c) For an indicator or large molecular size (microspheres), injecting into the left side of the heart and sampling from arterial sites yield accurate and reproducible results regardless of whether blood is sampled continuously or intermittently.« less

Gear and seasonal bias associated with abundance and size structure estimates for lentic freshwater fishes

USGS Publications Warehouse

Fischer, Jesse R.; Quist, Michael C.

2014-01-01

All freshwater fish sampling methods are biased toward particular species, sizes, and sexes and are further influenced by season, habitat, and fish behavior changes over time. However, little is known about gear-specific biases for many common fish species because few multiple-gear comparison studies exist that have incorporated seasonal dynamics. We sampled six lakes and impoundments representing a diversity of trophic and physical conditions in Iowa, USA, using multiple gear types (i.e., standard modified fyke net, mini-modified fyke net, sinking experimental gill net, bag seine, benthic trawl, boat-mounted electrofisher used diurnally and nocturnally) to determine the influence of sampling methodology and season on fisheries assessments. Specifically, we describe the influence of season on catch per unit effort, proportional size distribution, and the number of samples required to obtain 125 stock-length individuals for 12 species of recreational and ecological importance. Mean catch per unit effort generally peaked in the spring and fall as a result of increased sampling effectiveness in shallow areas and seasonal changes in habitat use (e.g., movement offshore during summer). Mean proportional size distribution decreased from spring to fall for white bass Morone chrysops, largemouth bass Micropterus salmoides, bluegill Lepomis macrochirus, and black crappie Pomoxis nigromaculatus, suggesting selectivity for large and presumably sexually mature individuals in the spring and summer. Overall, the mean number of samples required to sample 125 stock-length individuals was minimized in the fall with sinking experimental gill nets, a boat-mounted electrofisher used at night, and standard modified nets for 11 of the 12 species evaluated. Our results provide fisheries scientists with relative comparisons between several recommended standard sampling methods and illustrate the effects of seasonal variation on estimates of population indices that will be critical to the future development of standardized sampling methods for freshwater fish in lentic ecosystems.

Confidence intervals for the population mean tailored to small sample sizes, with applications to survey sampling.

PubMed

Rosenblum, Michael A; Laan, Mark J van der

2009-01-07

The validity of standard confidence intervals constructed in survey sampling is based on the central limit theorem. For small sample sizes, the central limit theorem may give a poor approximation, resulting in confidence intervals that are misleading. We discuss this issue and propose methods for constructing confidence intervals for the population mean tailored to small sample sizes. We present a simple approach for constructing confidence intervals for the population mean based on tail bounds for the sample mean that are correct for all sample sizes. Bernstein's inequality provides one such tail bound. The resulting confidence intervals have guaranteed coverage probability under much weaker assumptions than are required for standard methods. A drawback of this approach, as we show, is that these confidence intervals are often quite wide. In response to this, we present a method for constructing much narrower confidence intervals, which are better suited for practical applications, and that are still more robust than confidence intervals based on standard methods, when dealing with small sample sizes. We show how to extend our approaches to much more general estimation problems than estimating the sample mean. We describe how these methods can be used to obtain more reliable confidence intervals in survey sampling. As a concrete example, we construct confidence intervals using our methods for the number of violent deaths between March 2003 and July 2006 in Iraq, based on data from the study "Mortality after the 2003 invasion of Iraq: A cross sectional cluster sample survey," by Burnham et al. (2006).

Mini-midi-mito: adapting the amplification and sequencing strategy of mtDNA to the degradation state of crime scene samples.

PubMed

Berger, Cordula; Parson, Walther

2009-06-01

The degradation state of some biological traces recovered from the crime scene requires the amplification of very short fragments to attain a useful mitochondrial (mt)DNA sequence. We have previously introduced two mini-multiplex assays that amplify 10 overlapping control region (CR) fragments in two separate multiplex PCRs, which brought successful CR consensus sequences from even highly degraded DNA extracts. This procedure requires a total of 20 sequencing reactions per sample, which is laborious and cost intensive. For only moderately degraded samples that we encounter more frequently with typical mtDNA casework material, we developed two new multiplex assays that use a subset of the mini-amplicon primers but embrace larger fragments (midis) and require only 10 sequencing reactions to build a double-stranded CR consensus sequence. We used a preceding mtDNA quantitation step by real-time PCR with two different target fragments (143 and 283 bp) that roughly correspond to the average fragment sizes of the different multiplex approaches to estimate size-dependent mtDNA quantities and to aid the choice of the appropriate PCR multiplexes with respect to quality of the results and required costs.

Strain Amount Dependent Grain Size and Orientation Developments during Hot Compression of a Polycrystalline Nickel Based Superalloy

PubMed Central

He, Guoai; Tan, Liming; Liu, Feng; Huang, Lan; Huang, Zaiwang; Jiang, Liang

2017-01-01

Controlling grain size in polycrystalline nickel base superalloy is vital for obtaining required mechanical properties. Typically, a uniform and fine grain size is required throughout forging process to realize the superplastic deformation. Strain amount occupied a dominant position in manipulating the dynamic recrystallization (DRX) process and regulating the grain size of the alloy during hot forging. In this article, the high-throughput double cone specimen was introduced to yield wide-range strain in a single sample. Continuous variations of effective strain ranging from 0.23 to 1.65 across the whole sample were achieved after reaching a height reduction of 70%. Grain size is measured to be decreased from the edge to the center of specimen with increase of effective strain. Small misorientation tended to generate near the grain boundaries, which was manifested as piled-up dislocation in micromechanics. After the dislocation density reached a critical value, DRX progress would be initiated at higher deformation region, leading to the refinement of grain size. During this process, the transformations from low angle grain boundaries (LAGBs) to high angle grain boundaries (HAGBs) and from subgrains to DRX grains are found to occur. After the accomplishment of DRX progress, the neonatal grains are presented as having similar orientation inside the grain boundary. PMID:28772514

Driven Boson Sampling.

PubMed

Barkhofen, Sonja; Bartley, Tim J; Sansoni, Linda; Kruse, Regina; Hamilton, Craig S; Jex, Igor; Silberhorn, Christine

2017-01-13

Sampling the distribution of bosons that have undergone a random unitary evolution is strongly believed to be a computationally hard problem. Key to outperforming classical simulations of this task is to increase both the number of input photons and the size of the network. We propose driven boson sampling, in which photons are input within the network itself, as a means to approach this goal. We show that the mean number of photons entering a boson sampling experiment can exceed one photon per input mode, while maintaining the required complexity, potentially leading to less stringent requirements on the input states for such experiments. When using heralded single-photon sources based on parametric down-conversion, this approach offers an ∼e-fold enhancement in the input state generation rate over scattershot boson sampling, reaching the scaling limit for such sources. This approach also offers a dramatic increase in the signal-to-noise ratio with respect to higher-order photon generation from such probabilistic sources, which removes the need for photon number resolution during the heralding process as the size of the system increases.

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

Drawing a representative sample from the NCSS soil database: Building blocks for the national wind erosion network

USDA-ARS?s Scientific Manuscript database

Developing national wind erosion models for the continental United States requires a comprehensive spatial representation of continuous soil particle size distributions (PSD) for model input. While the current coverage of soil survey is nearly complete, the most detailed particle size classes have c...

Spatial distribution and sequential sampling plans for Tuta absoluta (Lepidoptera: Gelechiidae) in greenhouse tomato crops.

PubMed

Cocco, Arturo; Serra, Giuseppe; Lentini, Andrea; Deliperi, Salvatore; Delrio, Gavino

2015-09-01

The within- and between-plant distribution of the tomato leafminer, Tuta absoluta (Meyrick), was investigated in order to define action thresholds based on leaf infestation and to propose enumerative and binomial sequential sampling plans for pest management applications in protected crops. The pest spatial distribution was aggregated between plants, and median leaves were the most suitable sample to evaluate the pest density. Action thresholds of 36 and 48%, 43 and 56% and 60 and 73% infested leaves, corresponding to economic thresholds of 1 and 3% damaged fruits, were defined for tomato cultivars with big, medium and small fruits respectively. Green's method was a more suitable enumerative sampling plan as it required a lower sampling effort. Binomial sampling plans needed lower average sample sizes than enumerative plans to make a treatment decision, with probabilities of error of <0.10. The enumerative sampling plan required 87 or 343 leaves to estimate the population density in extensive or intensive ecological studies respectively. Binomial plans would be more practical and efficient for control purposes, needing average sample sizes of 17, 20 and 14 leaves to take a pest management decision in order to avoid fruit damage higher than 1% in cultivars with big, medium and small fruits respectively. © 2014 Society of Chemical Industry.

Sampling Mars: Analytical requirements and work to do in advance

NASA Technical Reports Server (NTRS)

Koeberl, Christian

1988-01-01

Sending a mission to Mars to collect samples and return them to the Earth for analysis is without doubt one of the most exciting and important tasks for planetary science in the near future. Many scientifically important questions are associated with the knowledge of the composition and structure of Martian samples. Amongst the most exciting questions is the clarification of the SNC problem- to prove or disprove a possible Martian origin of these meteorites. Since SNC meteorites have been used to infer the chemistry of the planet Mars, and its evolution (including the accretion history), it would be important to know if the whole story is true. But before addressing possible scientific results, we have to deal with the analytical requirements, and with possible pre-return work. It is unlikely to expect that a possible Mars sample return mission will bring back anything close to the amount returned by the Apollo missions. It will be more like the amount returned by the Luna missions, or at least in that order of magnitude. This requires very careful sample selection, and very precise analytical techniques. These techniques should be able to use minimal sample sizes and on the other hand optimize the scientific output. The possibility to work with extremely small samples should not obstruct another problem: possible sampling errors. As we know from terrestrial geochemical studies, sampling procedures are quite complicated and elaborate to ensure avoiding sampling errors. The significance of analyzing a milligram or submilligram sized sample and putting that in relationship with the genesis of whole planetary crusts has to be viewed with care. This leaves a dilemma on one hand, to minimize the sample size as far as possible in order to have the possibility of returning as many different samples as possible, and on the other hand to take a sample large enough to be representative. Whole rock samples are very useful, but should not exceed the 20 to 50 g range, except in cases of extreme inhomogeneity, because for larger samples the information tends to become redundant. Soil samples should be in the 2 to 10 g range, permitting the splitting of the returned samples for studies in different laboratories with variety of techniques.

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

PubMed

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

2013-10-01

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

Application of SAXS and SANS in evaluation of porosity, pore size distribution and surface area of coal

USGS Publications Warehouse

Radlinski, A.P.; Mastalerz, Maria; Hinde, A.L.; Hainbuchner, M.; Rauch, H.; Baron, M.; Lin, J.S.; Fan, L.; Thiyagarajan, P.

2004-01-01

This paper discusses the applicability of small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS) techniques for determining the porosity, pore size distribution and internal specific surface area in coals. The method is noninvasive, fast, inexpensive and does not require complex sample preparation. It uses coal grains of about 0.8 mm size mounted in standard pellets as used for petrographic studies. Assuming spherical pore geometry, the scattering data are converted into the pore size distribution in the size range 1 nm (10 A??) to 20 ??m (200,000 A??) in diameter, accounting for both open and closed pores. FTIR as well as SAXS and SANS data for seven samples of oriented whole coals and corresponding pellets with vitrinite reflectance (Ro) values in the range 0.55% to 5.15% are presented and analyzed. Our results demonstrate that pellets adequately represent the average microstructure of coal samples. The scattering data have been used to calculate the maximum surface area available for methane adsorption. Total porosity as percentage of sample volume is calculated and compared with worldwide trends. By demonstrating the applicability of SAXS and SANS techniques to determine the porosity, pore size distribution and surface area in coals, we provide a new and efficient tool, which can be used for any type of coal sample, from a thin slice to a representative sample of a thick seam. ?? 2004 Elsevier B.V. All rights reserved.

EXTENDING THE FLOOR AND THE CEILING FOR ASSESSMENT OF PHYSICAL FUNCTION

PubMed Central

Fries, James F.; Lingala, Bharathi; Siemons, Liseth; Glas, Cees A. W.; Cella, David; Hussain, Yusra N; Bruce, Bonnie; Krishnan, Eswar

2014-01-01

Objective The objective of the current study was to improve the assessment of physical function by improving the precision of assessment at the floor (extremely poor function) and at the ceiling (extremely good health) of the health continuum. Methods Under the NIH PROMIS program, we developed new physical function floor and ceiling items to supplement the existing item bank. Using item response theory (IRT) and the standard PROMIS methodology, we developed 30 floor items and 26 ceiling items and administered them during a 12-month prospective observational study of 737 individuals at the extremes of health status. Change over time was compared across anchor instruments and across items by means of effect sizes. Using the observed changes in scores, we back-calculated sample size requirements for the new and comparison measures. Results We studied 444 subjects with chronic illness and/or extreme age, and 293 generally fit subjects including athletes in training. IRT analyses confirmed that the new floor and ceiling items outperformed reference items (p<0.001). The estimated post-hoc sample size requirements were reduced by a factor of two to four at the floor and a factor of two at the ceiling. Conclusion Extending the range of physical function measurement can substantially improve measurement quality, can reduce sample size requirements and improve research efficiency. The paradigm shift from Disability to Physical Function includes the entire spectrum of physical function, signals improvement in the conceptual base of outcome assessment, and may be transformative as medical goals more closely approach societal goals for health. PMID:24782194

Reporting and methodological quality of sample size calculations in cluster randomized trials could be improved: a review.

PubMed

Rutterford, Clare; Taljaard, Monica; Dixon, Stephanie; Copas, Andrew; Eldridge, Sandra

2015-06-01

To assess the quality of reporting and accuracy of a priori estimates used in sample size calculations for cluster randomized trials (CRTs). We reviewed 300 CRTs published between 2000 and 2008. The prevalence of reporting sample size elements from the 2004 CONSORT recommendations was evaluated and a priori estimates compared with those observed in the trial. Of the 300 trials, 166 (55%) reported a sample size calculation. Only 36 of 166 (22%) reported all recommended descriptive elements. Elements specific to CRTs were the worst reported: a measure of within-cluster correlation was specified in only 58 of 166 (35%). Only 18 of 166 articles (11%) reported both a priori and observed within-cluster correlation values. Except in two cases, observed within-cluster correlation values were either close to or less than a priori values. Even with the CONSORT extension for cluster randomization, the reporting of sample size elements specific to these trials remains below that necessary for transparent reporting. Journal editors and peer reviewers should implement stricter requirements for authors to follow CONSORT recommendations. Authors should report observed and a priori within-cluster correlation values to enable comparisons between these over a wider range of trials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems

PubMed Central

Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.

2016-01-01

Abstract. The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment. PMID:27493982

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

PubMed

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

2017-09-01

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

Validation of fixed sample size plans for monitoring lepidopteran pests of Brassica oleracea crops in North Korea.

PubMed

Hamilton, A J; Waters, E K; Kim, H J; Pak, W S; Furlong, M J

2009-06-01

The combined action of two lepidoteran pests, Plutella xylostella L. (Plutellidae) and Pieris rapae L. (Pieridae),causes significant yield losses in cabbage (Brassica oleracea variety capitata) crops in the Democratic People's Republic of Korea. Integrated pest management (IPM) strategies for these cropping systems are in their infancy, and sampling plans have not yet been developed. We used statistical resampling to assess the performance of fixed sample size plans (ranging from 10 to 50 plants). First, the precision (D = SE/mean) of the plans in estimating the population mean was assessed. There was substantial variation in achieved D for all sample sizes, and sample sizes of at least 20 and 45 plants were required to achieve the acceptable precision level of D < or = 0.3 at least 50 and 75% of the time, respectively. Second, the performance of the plans in classifying the population density relative to an economic threshold (ET) was assessed. To account for the different damage potentials of the two species the ETs were defined in terms of standard insects (SIs), where 1 SI = 1 P. rapae = 5 P. xylostella larvae. The plans were implemented using different economic thresholds (ETs) for the three growth stages of the crop: precupping (1 SI/plant), cupping (0.5 SI/plant), and heading (4 SI/plant). Improvement in the classification certainty with increasing sample sizes could be seen through the increasing steepness of operating characteristic curves. Rather than prescribe a particular plan, we suggest that the results of these analyses be used to inform practitioners of the relative merits of the different sample sizes.

Particle size analysis of amalgam powder and handpiece generated specimens.

PubMed

Drummond, J L; Hathorn, R M; Cailas, M D; Karuhn, R

2001-07-01

The increasing interest in the elimination of amalgam particles from the dental waste (DW) stream, requires efficient devices to remove these particles. The major objective of this project was to perform a comparative evaluation of five basic methods of particle size analysis in terms of the instrument's ability to quantify the size distribution of the various components within the DW stream. The analytical techniques chosen were image analysis via scanning electron microscopy, standard wire mesh sieves, X-ray sedigraphy, laser diffraction, and electrozone analysis. The DW particle stream components were represented by amalgam powders and handpiece/diamond bur generated specimens of enamel; dentin, whole tooth, and condensed amalgam. Each analytical method quantified the examined DW particle stream components. However, X-ray sedigraphy, electrozone, and laser diffraction particle analyses provided similar results for determining particle distributions of DW samples. These three methods were able to more clearly quantify the properties of the examined powder and condensed amalgam samples. Furthermore, these methods indicated that a significant fraction of the DW stream contains particles less than 20 microm. The findings of this study indicated that the electrozone method is likely to be the most effective technique for quantifying the particle size distribution in the DW particle stream. This method required a relative small volume of sample, was not affected by density, shape factors or optical properties, and measured a sufficient number of particles to provide a reliable representation of the particle size distribution curve.

Longitudinal design considerations to optimize power to detect variances and covariances among rates of change: Simulation results based on actual longitudinal studies

PubMed Central

Rast, Philippe; Hofer, Scott M.

2014-01-01

We investigated the power to detect variances and covariances in rates of change in the context of existing longitudinal studies using linear bivariate growth curve models. Power was estimated by means of Monte Carlo simulations. Our findings show that typical longitudinal study designs have substantial power to detect both variances and covariances among rates of change in a variety of cognitive, physical functioning, and mental health outcomes. We performed simulations to investigate the interplay among number and spacing of occasions, total duration of the study, effect size, and error variance on power and required sample size. The relation between growth rate reliability (GRR) and effect size to the sample size required to detect power ≥ .80 was non-linear, with rapidly decreasing sample sizes needed as GRR increases. The results presented here stand in contrast to previous simulation results and recommendations (Hertzog, Lindenberger, Ghisletta, & von Oertzen, 2006; Hertzog, von Oertzen, Ghisletta, & Lindenberger, 2008; von Oertzen, Ghisletta, & Lindenberger, 2010), which are limited due to confounds between study length and number of waves, error variance with GCR, and parameter values which are largely out of bounds of actual study values. Power to detect change is generally low in the early phases (i.e. first years) of longitudinal studies but can substantially increase if the design is optimized. We recommend additional assessments, including embedded intensive measurement designs, to improve power in the early phases of long-term longitudinal studies. PMID:24219544

Sampling plantations to determine white-pine weevil injury

Treesearch

Robert L. Talerico; Robert W., Jr. Wilson

1973-01-01

Use of 1/10-acre square plots to obtain estimates of the proportion of never-weeviled trees necessary for evaluating and scheduling white-pine weevil control is described. The optimum number of trees to observe per plot is estimated from data obtained from sample plantations in the Northeast and a table is given. Of sample size required to achieve a standard error of...

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

PubMed Central

2017-01-01

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

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

PubMed Central

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

2016-01-01

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

Development of sampling plans for cotton bolls injured by stink bugs (Hemiptera: Pentatomidae).

PubMed

Reay-Jones, F P F; Toews, M D; Greene, J K; Reeves, R B

2010-04-01

Cotton, Gossypium hirsutum L., bolls were sampled in commercial fields for stink bug (Hemiptera: Pentatomidae) injury during 2007 and 2008 in South Carolina and Georgia. Across both years of this study, boll-injury percentages averaged 14.8 +/- 0.3 (SEM). At average boll injury treatment levels of 10, 20, 30, and 50%, the percentage of samples with at least one injured boll was 82, 97, 100, and 100%, respectively. Percentage of field-sampling date combinations with average injury < 10, 20, 30, and 50% was 35, 80, 95, and 99%, respectively. At the average of 14.8% boll injury or 2.9 injured bolls per 20-boll sample, 112 samples at Dx = 0.1 (within 10% of the mean) were required for population estimation, compared with only 15 samples at Dx = 0.3. Using a sample size of 20 bolls, our study indicated that, at the 10% threshold and alpha = beta = 0.2 (with 80% confidence), control was not needed when <1.03 bolls were injured. The sampling plan required continued sampling for a range of 1.03-3.8 injured bolls per 20-boll sample. Only when injury was > 3.8 injured bolls per 20-boll sample was a control measure needed. Sequential sampling plans were also determined for thresholds of 20, 30, and 50% injured bolls. Sample sizes for sequential sampling plans were significantly reduced when compared with a fixed sampling plan (n=10) for all thresholds and error rates.

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

PubMed

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

2017-08-28

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

Intraclass Correlation Values for Planning Group-Randomized Trials in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.

2007-01-01

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate…

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

Seasonal and sexual differences in American marten diet in northeastern Oregon.

Treesearch

E.L. Bull

2002-01-01

Information on the diet of the American marten (Martes americana) is vital to understanding habitat requirements of populations of this species. The frequency of occurrence of prey items found in 1014 scat samples associated with 31 radiocollared American martens in northeastern Oregon included: 62.7% vole-sized prey, 28.2% squirrel-sized prey, 22....

Taking Costs and Diagnostic Test Accuracy into Account When Designing Prevalence Studies: An Application to Childhood Tuberculosis Prevalence.

PubMed

Wang, Zhuoyu; Dendukuri, Nandini; Pai, Madhukar; Joseph, Lawrence

2017-11-01

When planning a study to estimate disease prevalence to a pre-specified precision, it is of interest to minimize total testing cost. This is particularly challenging in the absence of a perfect reference test for the disease because different combinations of imperfect tests need to be considered. We illustrate the problem and a solution by designing a study to estimate the prevalence of childhood tuberculosis in a hospital setting. All possible combinations of 3 commonly used tuberculosis tests, including chest X-ray, tuberculin skin test, and a sputum-based test, either culture or Xpert, are considered. For each of the 11 possible test combinations, 3 Bayesian sample size criteria, including average coverage criterion, average length criterion and modified worst outcome criterion, are used to determine the required sample size and total testing cost, taking into consideration prior knowledge about the accuracy of the tests. In some cases, the required sample sizes and total testing costs were both reduced when more tests were used, whereas, in other examples, lower costs are achieved with fewer tests. Total testing cost should be formally considered when designing a prevalence study.

Certification Testing Methodology for Composite Structure. Volume 2. Methodology Development

DTIC Science & Technology

1986-10-01

parameter, sample size and fa- tigue test duration. The required input are 1. Residual strength Weibull shape parameter ( ALPR ) 2. Fatigue life Weibull shape...INPUT STRENGTH ALPHA’) READ(*,*) ALPR ALPRI = 1.O/ ALPR WRITE(*, 2) 2 FORMAT( 2X, ’PLEASE INPUT LIFE ALPHA’) READ(*,*) ALPL ALPLI - 1.0/ALPL WRITE(*, 3...3 FORMAT(2X,’PLEASE INPUT SAMPLE SIZE’) READ(*,*) N AN - N WRITE(*,4) 4 FORMAT(2X,’PLEASE INPUT TEST DURATION’) READ(*,*) T RALP - ALPL/ ALPR ARGR - 1

An Integrated Tool for System Analysis of Sample Return Vehicles

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Maddock, Robert W.; Winski, Richard G.

2012-01-01

The next important step in space exploration is the return of sample materials from extraterrestrial locations to Earth for analysis. Most mission concepts that return sample material to Earth share one common element: an Earth entry vehicle. The analysis and design of entry vehicles is multidisciplinary in nature, requiring the application of mass sizing, flight mechanics, aerodynamics, aerothermodynamics, thermal analysis, structural analysis, and impact analysis tools. Integration of a multidisciplinary problem is a challenging task; the execution process and data transfer among disciplines should be automated and consistent. This paper describes an integrated analysis tool for the design and sizing of an Earth entry vehicle. The current tool includes the following disciplines: mass sizing, flight mechanics, aerodynamics, aerothermodynamics, and impact analysis tools. Python and Java languages are used for integration. Results are presented and compared with the results from previous studies.

Concurrent measurements of size-segregated particulate sulfate, nitrate and ammonium using quartz fiber filters, glass fiber filters and cellulose membranes

NASA Astrophysics Data System (ADS)

Tian, Shili; Pan, Yuepeng; Wang, Jian; Wang, Yuesi

2016-11-01

Current science and policy requirements have focused attention on the need to expand and improve particulate matter (PM) sampling methods. To explore how sampling filter type affects artifacts in PM composition measurements, size-resolved particulate SO42-, NO3- and NH4+ (SNA) were measured on quartz fiber filters (QFF), glass fiber filters (GFF) and cellulose membranes (CM) concurrently in an urban area of Beijing on both clean and hazy days. The results showed that SNA concentrations in most of the size fractions exhibited the following patterns on different filters: CM > QFF > GFF for NH4+; GFF > QFF > CM for SO42-; and GFF > CM > QFF for NO3-. The different patterns in coarse particles were mainly affected by filter acidity, and that in fine particles were mainly affected by hygroscopicity of the filters (especially in size fraction of 0.65-2.1 μm). Filter acidity and hygroscopicity also shifted the peaks of the annual mean size distributions of SNA on QFF from 0.43-0.65 μm on clean days to 0.65-1.1 μm on hazy days. However, this size shift was not as distinct for samples measured with CM and GFF. In addition, relative humidity (RH) and pollution levels are important factors that can enhance particulate size mode shifts of SNA on clean and hazy days. Consequently, the annual mean size distributions of SNA had maxima at 0.65-1.1 μm for QFF samples and 0.43-0.65 μm for GFF and CM samples. Compared with NH4+ and SO42-, NO3- is more sensitive to RH and pollution levels, accordingly, the annual mean size distribution of NO3- exhibited peak at 0.65-1.1 μm for CM samples instead of 0.43-0.65 μm. These methodological uncertainties should be considered when quantifying the concentrations and size distributions of SNA under different RH and haze conditions.

Utility of the AAMC’s Graduation Questionnaire to Study Behavioral and Social Sciences Domains in Undergraduate Medical Education

PubMed Central

Carney, Patricia A.; Rdesinski, Rebecca; Blank, Arthur E.; Graham, Mark; Wimmers, Paul; Chen, H. Carrie; Thompson, Britta; Jackson, Stacey A.; Foertsch, Julie; Hollar, David

2010-01-01

Purpose The Institute of Medicine (IOM) report on social and behavioral sciences (SBS) indicated that 50% of morbidity and mortality in the United States is associated with SBS factors, which the report also found were inadequately taught in medical school. A multischool collaborative explored whether the Association of American Medical Colleges Graduation Questionnaire (GQ) could be used to study changes in the six SBS domains identified in the IOM report. Method A content analysis conducted with the GQ identified 30 SBS variables, which were narrowed to 24 using a modified Delphi approach. Summary data were pooled from nine medical schools for 2006 and 2007, representing 1,126 students. Data were generated on students’ perceptions of curricular experiences, attitudes related to SBS curricula, and confidence with relevant clinical knowledge and skills. The authors determined the sample sizes required for various effect sizes to assess the utility of the GQ. Results The 24 variables were classified into five of six IOM domains representing a total of nine analytic categories with cumulative scale means ranging from 60.8 to 93.4. Taking into account the correlations among measures over time, and assuming a two-sided test, 80% power, alpha at .05, and standard deviation of 4.1, the authors found that 34 medical schools would be required for inclusion to attain an estimated effect size of 0.50 (50%). With a sample size of nine schools, the ability to detect changes would require a very high effect size of 107%. Conclusions Detecting SBS changes associated with curricular innovations would require a large collaborative of medical schools. Using a national measure (the GQ) to assess curricular innovations in most areas of SBS is possible if enough medical schools were involved in such an effort. PMID:20042845

Sampling strategies for radio-tracking coyotes

USGS Publications Warehouse

Smith, G.J.; Cary, J.R.; Rongstad, O.J.

1981-01-01

Ten coyotes radio-tracked for 24 h periods were most active at night and moved little during daylight hours. Home-range size determined from radio-locations of 3 adult coyotes increased with the number of locations until an asymptote was reached at about 35-40 independent day locations or 3 6 nights of hourly radio-locations. Activity of the coyote did not affect the asymptotic nature of the home-range calculations, but home-range sizes determined from more than 3 nights of hourly locations were considerably larger than home-range sizes determined from daylight locations. Coyote home-range sizes were calculated from daylight locations, full-night tracking periods, and half-night tracking periods. Full- and half-lnight sampling strategies involved obtaining hourly radio-locations during 12 and 6 h periods, respectively. The half-night sampling strategy was the best compromise for our needs, as it adequately indexed the home-range size, reduced time and energy spent, and standardized the area calculation without requiring the researcher to become completely nocturnal. Sight tracking also provided information about coyote activity and sociability.

On the influence of crystal size and wavelength on native SAD phasing.

PubMed

Liebschner, Dorothee; Yamada, Yusuke; Matsugaki, Naohiro; Senda, Miki; Senda, Toshiya

2016-06-01

Native SAD is an emerging phasing technique that uses the anomalous signal of native heavy atoms to obtain crystallographic phases. The method does not require specific sample preparation to add anomalous scatterers, as the light atoms contained in the native sample are used as marker atoms. The most abundant anomalous scatterer used for native SAD, which is present in almost all proteins, is sulfur. However, the absorption edge of sulfur is at low energy (2.472 keV = 5.016 Å), which makes it challenging to carry out native SAD phasing experiments as most synchrotron beamlines are optimized for shorter wavelength ranges where the anomalous signal of sulfur is weak; for longer wavelengths, which produce larger anomalous differences, the absorption of X-rays by the sample, solvent, loop and surrounding medium (e.g. air) increases tremendously. Therefore, a compromise has to be found between measuring strong anomalous signal and minimizing absorption. It was thus hypothesized that shorter wavelengths should be used for large crystals and longer wavelengths for small crystals, but no thorough experimental analyses have been reported to date. To study the influence of crystal size and wavelength, native SAD experiments were carried out at different wavelengths (1.9 and 2.7 Å with a helium cone; 3.0 and 3.3 Å with a helium chamber) using lysozyme and ferredoxin reductase crystals of various sizes. For the tested crystals, the results suggest that larger sample sizes do not have a detrimental effect on native SAD data and that long wavelengths give a clear advantage with small samples compared with short wavelengths. The resolution dependency of substructure determination was analyzed and showed that high-symmetry crystals with small unit cells require higher resolution for the successful placement of heavy atoms.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.

PubMed

McDonald, Linda S; Panozzo, Joseph F; Salisbury, Phillip A; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features

PubMed Central

McDonald, Linda S.; Panozzo, Joseph F.; Salisbury, Phillip A.; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective. PMID:27176469

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

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

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

A novel, efficient method for estimating the prevalence of acute malnutrition in resource-constrained and crisis-affected settings: A simulation study.

PubMed

Frison, Severine; Kerac, Marko; Checchi, Francesco; Nicholas, Jennifer

2017-01-01

The assessment of the prevalence of acute malnutrition in children under five is widely used for the detection of emergencies, planning interventions, advocacy, and monitoring and evaluation. This study examined PROBIT Methods which convert parameters (mean and standard deviation (SD)) of a normally distributed variable to a cumulative probability below any cut-off to estimate acute malnutrition in children under five using Middle-Upper Arm Circumference (MUAC). We assessed the performance of: PROBIT Method I, with mean MUAC from the survey sample and MUAC SD from a database of previous surveys; and PROBIT Method II, with mean and SD of MUAC observed in the survey sample. Specifically, we generated sub-samples from 852 survey datasets, simulating 100 surveys for eight sample sizes. Overall the methods were tested on 681 600 simulated surveys. PROBIT methods relying on sample sizes as small as 50 had better performance than the classic method for estimating and classifying the prevalence of acute malnutrition. They had better precision in the estimation of acute malnutrition for all sample sizes and better coverage for smaller sample sizes, while having relatively little bias. They classified situations accurately for a threshold of 5% acute malnutrition. Both PROBIT methods had similar outcomes. PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence based on MUAC, compared to the classic method. Their use would require much lower sample sizes, thus enable great time and resource savings and permit timely and/or locally relevant prevalence estimates of acute malnutrition for a swift and well-targeted response.

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

PubMed

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

2006-04-01

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

7 CFR 70.105 - Procedures for appeal gradings.

Code of Federal Regulations, 2011 CFR

2011-01-01

... PRODUCTS AND RABBIT PRODUCTS Grading of Poultry Products and Rabbit Products Appeal of A Grading Or... sample size for the lot shall consist of double the samples required in § 70.80. (c) Poultry or rabbits... is performed. (d) Overwraps on frozen poultry or rabbits shall be removed from all birds or rabbits...

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

PubMed

Martínez-Ferrer, María Teresa; Ripollés, José Luís; Garcia-Marí, Ferran

2006-06-01

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

Angiographic core laboratory reproducibility analyses: implications for planning clinical trials using coronary angiography and left ventriculography end-points.

PubMed

Steigen, Terje K; Claudio, Cheryl; Abbott, David; Schulzer, Michael; Burton, Jeff; Tymchak, Wayne; Buller, Christopher E; John Mancini, G B

2008-06-01

To assess reproducibility of core laboratory performance and impact on sample size calculations. Little information exists about overall reproducibility of core laboratories in contradistinction to performance of individual technicians. Also, qualitative parameters are being adjudicated increasingly as either primary or secondary end-points. The comparative impact of using diverse indexes on sample sizes has not been previously reported. We compared initial and repeat assessments of five quantitative parameters [e.g., minimum lumen diameter (MLD), ejection fraction (EF), etc.] and six qualitative parameters [e.g., TIMI myocardial perfusion grade (TMPG) or thrombus grade (TTG), etc.], as performed by differing technicians and separated by a year or more. Sample sizes were calculated from these results. TMPG and TTG were also adjudicated by a second core laboratory. MLD and EF were the most reproducible, yielding the smallest sample size calculations, whereas percent diameter stenosis and centerline wall motion require substantially larger trials. Of the qualitative parameters, all except TIMI flow grade gave reproducibility characteristics yielding sample sizes of many 100's of patients. Reproducibility of TMPG and TTG was only moderately good both within and between core laboratories, underscoring an intrinsic difficulty in assessing these. Core laboratories can be shown to provide reproducibility performance that is comparable to performance commonly ascribed to individual technicians. The differences in reproducibility yield huge differences in sample size when comparing quantitative and qualitative parameters. TMPG and TTG are intrinsically difficult to assess and conclusions based on these parameters should arise only from very large trials.

Non-destructive crystal size determination in geological samples of archaeological use by means of infrared spectroscopy.

PubMed

Olivares, M; Larrañaga, A; Irazola, M; Sarmiento, A; Murelaga, X; Etxebarria, N

2012-08-30

The determination of crystal size of chert samples can provide suitable information about the raw material used for the manufacture of archeological items. X-ray diffraction (XRD) has been widely used for this purpose in several scientific areas. However, the historical value of archeological pieces makes this procedure sometimes unfeasible and thus, non-invasive new analytical approaches are required. In this sense, a new method was developed relating the crystal size obtained by means of XRD and infrared spectroscopy (IR) using partial least squares regression. The IR spectra collected from a large amount of different geological chert samples of archeological use were pre-processed following different treatments (i.e., derivatization or sample-wise normalization) to obtain the best regression model. The full cross-validation was satisfactorily validated using real samples and the experimental root mean standard error of precision value was 165 Å whereas the average precision of the estimated size value was 3%. The features of infrared bands were also evaluated in order to know the background of the prediction ability. In the studied case, the variance in the model was associated to the differences in the characteristic stretching and bending infrared bands of SiO(2). Based on this fact, it would be feasible to estimate the crystal size if it is built beforehand a chemometric model relating the size measured by standard methods and the IR spectra. Copyright © 2012 Elsevier B.V. All rights reserved.

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices.

PubMed

Bellier, Edwige; Grøtan, Vidar; Engen, Steinar; Schartau, Ann Kristin; Diserud, Ola H; Finstad, Anders G

2012-10-01

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2011-01-01

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Lower Limits on Aperture Size for an ExoEarth Detecting Coronagraphic Mission

NASA Technical Reports Server (NTRS)

Stark, Christopher C.; Roberge, Aki; Mandell, Avi; Clampin, Mark; Domagal-Goldman, Shawn D.; McElwain, Michael W.; Stapelfeldt, Karl R.

2015-01-01

The yield of Earth-like planets will likely be a primary science metric for future space-based missions that will drive telescope aperture size. Maximizing the exoEarth candidate yield is therefore critical to minimizing the required aperture. Here we describe a method for exoEarth candidate yield maximization that simultaneously optimizes, for the first time, the targets chosen for observation, the number of visits to each target, the delay time between visits, and the exposure time of every observation. This code calculates both the detection time and multiwavelength spectral characterization time required for planets. We also refine the astrophysical assumptions used as inputs to these calculations, relying on published estimates of planetary occurrence rates as well as theoretical and observational constraints on terrestrial planet sizes and classical habitable zones. Given these astrophysical assumptions, optimistic telescope and instrument assumptions, and our new completeness code that produces the highest yields to date, we suggest lower limits on the aperture size required to detect and characterize a statistically motivated sample of exoEarths.

16 CFR 1616.62 - Policy regarding retail display requirements for items.

Code of Federal Regulations, 2010 CFR

2010-01-01

... FABRICS ACT REGULATIONS STANDARD FOR THE FLAMMABILITY OF CHILDREN'S SLEEPWEAR: SIZES 7 THROUGH 14 (FF 5-74... which was manufactured before May 1, 1975, and for which a retailer has documentary evidence of compliance with all sampling and testing requirements of the Standard (FF 5-74) (subpart A of this part...

7 CFR 91.10 - Information required in connection with an application.

Code of Federal Regulations, 2013 CFR

2013-01-01

... requested, and the size of the sample. In addition, information regarding analysis of the lot by any federal... 7 Agriculture 3 2013-01-01 2013-01-01 false Information required in connection with an application...) COMMODITY LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Application for Services § 91.10...

40 CFR 761.353 - Second level of sample selection.

Code of Federal Regulations, 2012 CFR

2012-07-01

... reduction is to limit the amount of time required to manually cut up larger particles of the waste to pass through a 9.5 millimeter (mm) screen. (a) Selecting a portion of the subsample for particle size reduction... table to select one of these quarters. (b) Reduction of the particle size by the use of a 9.5 mm screen...

40 CFR 761.353 - Second level of sample selection.

Code of Federal Regulations, 2014 CFR

2014-07-01

... reduction is to limit the amount of time required to manually cut up larger particles of the waste to pass through a 9.5 millimeter (mm) screen. (a) Selecting a portion of the subsample for particle size reduction... table to select one of these quarters. (b) Reduction of the particle size by the use of a 9.5 mm screen...

40 CFR 761.353 - Second level of sample selection.

Code of Federal Regulations, 2013 CFR

2013-07-01

... reduction is to limit the amount of time required to manually cut up larger particles of the waste to pass through a 9.5 millimeter (mm) screen. (a) Selecting a portion of the subsample for particle size reduction... table to select one of these quarters. (b) Reduction of the particle size by the use of a 9.5 mm screen...

Capsule- and disk-filter procedure

USGS Publications Warehouse

Skrobialowski, Stanley C.

2016-01-01

Capsule and disk filters are disposable, self-contained units composed of a pleated or woven filter medium encased in a polypropylene or other plastic housing that can be connected inline to a sample-delivery system (such as a submersible or peristaltic pump) that generates sufficient pressure (positive or negative) to force water through the filter. Filter media are available in several pore sizes, but 0.45 µm is the pore size used routinely for most studies at this time. Capsule or disk filters (table 5.2.1.A.1) are required routinely for most studies when filtering samples for trace-element analyses and are recommended when filtering samples for major-ion or other inorganic-constituent analyses.

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

PubMed

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

2016-06-01

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

Quantitative x-ray phase-contrast imaging using a single grating of comparable pitch to sample feature size.

PubMed

Morgan, Kaye S; Paganin, David M; Siu, Karen K W

2011-01-01

The ability to quantitatively retrieve transverse phase maps during imaging by using coherent x rays often requires a precise grating or analyzer-crystal-based setup. Imaging of live animals presents further challenges when these methods require multiple exposures for image reconstruction. We present a simple method of single-exposure, single-grating quantitative phase contrast for a regime in which the grating period is much greater than the effective pixel size. A grating is used to create a high-visibility reference pattern incident on the sample, which is distorted according to the complex refractive index and thickness of the sample. The resolution, along a line parallel to the grating, is not restricted by the grating spacing, and the detector resolution becomes the primary determinant of the spatial resolution. We present a method of analysis that maps the displacement of interrogation windows in order to retrieve a quantitative phase map. Application of this analysis to the imaging of known phantoms shows excellent correspondence.

Vitamin D receptor gene and osteoporosis - author`s response

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

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

1996-04-01

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

Overview of the Mars Sample Return Earth Entry Vehicle

NASA Technical Reports Server (NTRS)

Dillman, Robert; Corliss, James

2008-01-01

NASA's Mars Sample Return (MSR) project will bring Mars surface and atmosphere samples back to Earth for detailed examination. Langley Research Center's MSR Earth Entry Vehicle (EEV) is a core part of the mission, protecting the sample container during atmospheric entry, descent, and landing. Planetary protection requirements demand a higher reliability from the EEV than for any previous planetary entry vehicle. An overview of the EEV design and preliminary analysis is presented, with a follow-on discussion of recommended future design trade studies to be performed over the next several years in support of an MSR launch in 2018 or 2020. Planned topics include vehicle size for impact protection of a range of sample container sizes, outer mold line changes to achieve surface sterilization during re-entry, micrometeoroid protection, aerodynamic stability, thermal protection, and structural materials selection.

Capillary Absorption Spectrometer for 13C Isotopic Composition of Pico to Subpico Molar Sample Quantities

NASA Astrophysics Data System (ADS)

Moran, J.; Kelly, J.; Sams, R.; Newburn, M.; Kreuzer, H.; Alexander, M.

2011-12-01

Quick incorporation of IR spectroscopy based isotope measurements into cutting edge research in biogeochemical cycling attests to the advantages of a spectroscopy versus mass spectrometry method for making some 13C measurements. The simple principles of optical spectroscopy allow field portability and provide a more robust general platform for isotope measurements. We present results with a new capillary absorption spectrometer (CAS) with the capability of reducing the sample size required for high precision isotopic measurements to the picomolar level and potentially the sub-picomolar level. This work was motivated by the minute sample size requirements for laser ablation isotopic studies of carbon cycling in microbial communities but has potential to be a valuable tool in other areas of biological and geological research. The CAS instrument utilizes a capillary waveguide as a sample chamber for interrogating CO2 via near IR laser absorption spectroscopy. The capillary's small volume (~ 0.5 mL) combined with propagation and interaction of the laser mode with the entire sample reduces sample size requirements to a fraction of that accessible with commercially available IR absorption including those with multi-pass or ring-down cavity systems. Using a continuous quantum cascade laser system to probe nearly adjacent rovibrational transitions of different isotopologues of CO2 near 2307 cm-1 permits sample measurement at low analyte pressures (as low as 2 Torr) for further sensitivity improvement. A novel method to reduce cw-fringing noise in the hollow waveguide is presented, which allows weak absorbance features to be studied at the few ppm level after averaging 1,000 scans in 10 seconds. Detection limits down to the 20 picomoles have been observed, a concentration of approximately 400 ppm at 2 Torr in the waveguide with precision and accuracy at or better than 1 %. Improvements in detection and signal averaging electronics and laser power and mode quality are anticipated to reduce the required samples size to a 100-200 femtomoles of carbon. We report the application of the CAS system to a Laser Ablation-Catalytic-Combustion (LA-CC) micro-sampler system for selectively harvesting detailed sections of a solid surface for 13C analysis. This technique results in a three order of magnitude sensitivity improvement reported for our isotope measurement system compared to typical IRMS, providing new opportunities for making detailed investigations into wide ranges of microbial, physical, and chemical systems. The CAS is interfaced directly to the LA CC system currently operating at a 50 μm spatial resolution. We demonstrate that particulates produced by a Nd:YAG laser (λ=266nm) are isotopically homogenous with the parent material as measured by both IRMS and the CAS system. An improved laser ablation system operating at 193 nm with a spatial resolution of 2 microns or better is under development which will demonstrate the utility of the CAS system for sample sizes too low for IRMS. The improved sensitivities and optimized spatial targeting of such a system could interrogate targets as detailed as small cell clusters or intergrain organic deposits and could enhance ability to track biogeochemical carbon cycling.

Decision and function problems based on boson sampling

NASA Astrophysics Data System (ADS)

Nikolopoulos, Georgios M.; Brougham, Thomas

2016-07-01

Boson sampling is a mathematical problem that is strongly believed to be intractable for classical computers, whereas passive linear interferometers can produce samples efficiently. So far, the problem remains a computational curiosity, and the possible usefulness of boson-sampling devices is mainly limited to the proof of quantum supremacy. The purpose of this work is to investigate whether boson sampling can be used as a resource of decision and function problems that are computationally hard, and may thus have cryptographic applications. After the definition of a rather general theoretical framework for the design of such problems, we discuss their solution by means of a brute-force numerical approach, as well as by means of nonboson samplers. Moreover, we estimate the sample sizes required for their solution by passive linear interferometers, and it is shown that they are independent of the size of the Hilbert space.

Body mass estimates of hominin fossils and the evolution of human body size.

PubMed

Grabowski, Mark; Hatala, Kevin G; Jungers, William L; Richmond, Brian G

2015-08-01

Body size directly influences an animal's place in the natural world, including its energy requirements, home range size, relative brain size, locomotion, diet, life history, and behavior. Thus, an understanding of the biology of extinct organisms, including species in our own lineage, requires accurate estimates of body size. Since the last major review of hominin body size based on postcranial morphology over 20 years ago, new fossils have been discovered, species attributions have been clarified, and methods improved. Here, we present the most comprehensive and thoroughly vetted set of individual fossil hominin body mass predictions to date, and estimation equations based on a large (n = 220) sample of modern humans of known body masses. We also present species averages based exclusively on fossils with reliable taxonomic attributions, estimates of species averages by sex, and a metric for levels of sexual dimorphism. Finally, we identify individual traits that appear to be the most reliable for mass estimation for each fossil species, for use when only one measurement is available for a fossil. Our results show that many early hominins were generally smaller-bodied than previously thought, an outcome likely due to larger estimates in previous studies resulting from the use of large-bodied modern human reference samples. Current evidence indicates that modern human-like large size first appeared by at least 3-3.5 Ma in some Australopithecus afarensis individuals. Our results challenge an evolutionary model arguing that body size increased from Australopithecus to early Homo. Instead, we show that there is no reliable evidence that the body size of non-erectus early Homo differed from that of australopiths, and confirm that Homo erectus evolved larger average body size than earlier hominins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

PubMed

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations

PubMed Central

Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2016-01-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under‐ or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re‐assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one‐sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. PMID:27886393

Effect of magnetic anisotropy and particle size distribution on temperature dependent magnetic hyperthermia in Fe3O4 ferrofluids

NASA Astrophysics Data System (ADS)

Palihawadana Arachchige, Maheshika; Nemala, Humeshkar; Naik, Vaman; Naik, Ratna

Magnetic hyperthermia (MHT) has a great potential as a non-invasive cancer therapy technique. Specific absorption rate (SAR) which measures the efficiency of heat generation, mainly depends on magnetic properties of nanoparticles such as saturation magnetization (Ms) and magnetic anisotropy (K) which depend on the size and shape. Therefore, MHT applications of magnetic nanoparticles often require a controllable synthesis to achieve desirable magnetic properties. We have synthesized Fe3O4 nanoparticles using two different methods, co-precipitation (CP) and hydrothermal (HT) techniques to produce similar XRD crystallite size of 12 nm, and subsequently coated with dextran to prepare ferrofluids for MHT. However, TEM measurements show average particle sizes of 13.8 +/-3.6 nm and 14.6 +/-3.6 nm for HT and CP samples, implying the existence of an amorphous surface layer for both. The MHT data show the two samples have very different SAR values of 110 W/g (CP) and 40W/g (HT) at room temperature, although they have similar Ms of 70 +/-4 emu/g regardless of their different TEM sizes. We fitted the temperature dependent SAR using linear response theory to explain the observed results. CP sample shows a larger magnetic core with a narrow size distribution and a higher K value compared to that of HT sample.

Imaging of zymogen granules in fully wet cells: evidence for restricted mechanism of granule growth.

PubMed

Hammel, Ilan; Anaby, Debbie

2007-09-01

The introduction of wet SEM imaging technology permits electron microscopy of wet samples. Samples are placed in sealed specimen capsules and are insulated from the vacuum in the SEM chamber by an impermeable, electron-transparent membrane. The complete insulation of the sample from the vacuum allows direct imaging of fully hydrated, whole-mount tissue. In the current work, we demonstrate direct inspection of thick pancreatic tissue slices (above 400 mum). In the case of scanning of the pancreatic surface, the boundaries of intracellular features are seen directly. Thus no unfolding is required to ascertain the actual particle size distribution based on the sizes of the sections. This method enabled us to investigate the true granule size distribution and confirm early studies of improved conformity to a Poisson-like distribution, suggesting that the homotypic granule growth results from a mechanism, which favors the addition of a single unit granule to mature granules.

Microgravity Testing of a Surface Sampling System for Sample Return from Small Solar System Bodies

NASA Technical Reports Server (NTRS)

Franzen, M. A.; Preble, J.; Schoenoff, M.; Halona, K.; Long, T. E.; Park, T.; Sears, D. W. G.

2004-01-01

The return of samples from solar system bodies is becoming an essential element of solar system exploration. The recent National Research Council Solar System Exploration Decadal Survey identified six sample return missions as high priority missions: South-Aitken Basin Sample Return, Comet Surface Sample Return, Comet Surface Sample Return-sample from selected surface sites, Asteroid Lander/Rover/Sample Return, Comet Nucleus Sample Return-cold samples from depth, and Mars Sample Return [1] and the NASA Roadmap also includes sample return missions [2] . Sample collection methods that have been flown on robotic spacecraft to date return subgram quantities, but many scientific issues (like bulk composition, particle size distributions, petrology, chronology) require tens to hundreds of grams of sample. Many complex sample collection devices have been proposed, however, small robotic missions require simplicity. We present here the results of experiments done with a simple but innovative collection system for sample return from small solar system bodies.

Bivariate mass-size relation as a function of morphology as determined by Galaxy Zoo 2 crowdsourced visual classifications

NASA Astrophysics Data System (ADS)

Beck, Melanie; Scarlata, Claudia; Fortson, Lucy; Willett, Kyle; Galloway, Melanie

2016-01-01

It is well known that the mass-size distribution evolves as a function of cosmic time and that this evolution is different between passive and star-forming galaxy populations. However, the devil is in the details and the precise evolution is still a matter of debate since this requires careful comparison between similar galaxy populations over cosmic time while simultaneously taking into account changes in image resolution, rest-frame wavelength, and surface brightness dimming in addition to properly selecting representative morphological samples.Here we present the first step in an ambitious undertaking to calculate the bivariate mass-size distribution as a function of time and morphology. We begin with a large sample (~3 x 105) of SDSS galaxies at z ~ 0.1. Morphologies for this sample have been determined by Galaxy Zoo crowdsourced visual classifications and we split the sample not only by disk- and bulge-dominated galaxies but also in finer morphology bins such as bulge strength. Bivariate distribution functions are the only way to properly account for biases and selection effects. In particular, we quantify the mass-size distribution with a version of the parametric Maximum Likelihood estimator which has been modified to account for measurement errors as well as upper limits on galaxy sizes.

Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques.

PubMed

Dombrowski, Kirk; Khan, Bilal; Wendel, Travis; McLean, Katherine; Misshula, Evan; Curtis, Ric

2012-12-01

As part of a recent study of the dynamics of the retail market for methamphetamine use in New York City, we used network sampling methods to estimate the size of the total networked population. This process involved sampling from respondents' list of co-use contacts, which in turn became the basis for capture-recapture estimation. Recapture sampling was based on links to other respondents derived from demographic and "telefunken" matching procedures-the latter being an anonymized version of telephone number matching. This paper describes the matching process used to discover the links between the solicited contacts and project respondents, the capture-recapture calculation, the estimation of "false matches", and the development of confidence intervals for the final population estimates. A final population of 12,229 was estimated, with a range of 8235 - 23,750. The techniques described here have the special virtue of deriving an estimate for a hidden population while retaining respondent anonymity and the anonymity of network alters, but likely require larger sample size than the 132 persons interviewed to attain acceptable confidence levels for the estimate.

Analysis of particulates on tape lift samples

NASA Astrophysics Data System (ADS)

Moision, Robert M.; Chaney, John A.; Panetta, Chris J.; Liu, De-Ling

2014-09-01

Particle counts on tape lift samples taken from a hardware surface exceeded threshold requirements in six successive tests despite repeated cleaning of the surface. Subsequent analysis of the particle size distributions of the failed tests revealed that the handling and processing of the tape lift samples may have played a role in the test failures. In order to explore plausible causes for the observed size distribution anomalies, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) were employed to perform chemical analysis on collected particulates. SEM/EDX identified Na and S containing particles on the hardware samples in a size range identified as being responsible for the test failures. ToF-SIMS was employed to further examine the Na and S containing particulates and identified the molecular signature of sodium alkylbenzene sulfonates, a common surfactant used in industrial detergent. The root cause investigation suggests that the tape lift test failures originated from detergent residue left behind on the glass slides used to mount and transport the tape following sampling and not from the hardware surface.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

PubMed

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

Invited Review Small is beautiful: The analysis of nanogram-sized astromaterials

NASA Astrophysics Data System (ADS)

Zolensky, M. E.; Pieters, C.; Clark, B.; Papike, J. J.

2000-01-01

The capability of modern methods to characterize ultra-small samples is well established from analysis of interplanetary dust particles (IDPs), interstellar grains recovered from meteorites, and other materials requiring ultra-sensitive analytical capabilities. Powerful analytical techniques are available that require, under favorable circumstances, single particles of only a few nanograms for entire suites of fairly comprehensive characterizations. A returned sample of >1,000 particles with total mass of just one microgram permits comprehensive quantitative geochemical measurements that are impractical to carry out in situ by flight instruments. The main goal of this paper is to describe the state-of-the-art in microanalysis of astromaterials. Given that we can analyze fantastically small quantities of asteroids and comets, etc., we have to ask ourselves how representative are microscopic samples of bodies that measure a few to many km across? With the Galileo flybys of Gaspra and Ida, it is now recognized that even very small airless bodies have indeed developed a particulate regolith. Acquiring a sample of the bulk regolith, a simple sampling strategy, provides two critical pieces of information about the body. Regolith samples are excellent bulk samples since they normally contain all the key components of the local environment, albeit in particulate form. Furthermore, since this fine fraction dominates remote measurements, regolith samples also provide information about surface alteration processes and are a key link to remote sensing of other bodies. Studies indicate that a statistically significant number of nanogram-sized particles should be able to characterize the regolith of a primitive asteroid, although the presence of larger components within even primitive meteorites (e.g.. Murchison), e.g. chondrules, CAI, large crystal fragments, etc., points out the limitations of using data obtained from nanogram-sized samples to characterize entire primitive asteroids. However, most important asteroidal geological processes have left their mark on the matrix, since this is the finest-grained portion and therefore most sensitive to chemical and physical changes. Thus, the following information can be learned from this fine grain size fraction alone: (1) mineral paragenesis; (2) regolith processes, (3) bulk composition; (4) conditions of thermal and aqueous alteration (if any); (5) relationships to planets, comets, meteorites (via isotopic analyses, including oxygen; (6) abundance of water and hydrated material; (7) abundance of organics; (8) history of volatile mobility, (9) presence and origin of presolar and/or interstellar material. Most of this information can even be obtained from dust samples from bodies for which nanogram-sized samples are not truly representative. Future advances in sensitivity and accuracy of laboratory analytical techniques can be expected to enhance the science value of nano- to microgram sized samples even further. This highlights a key advantage of sample returns - that the most advanced analysis techniques can always be applied in the laboratory, and that well-preserved samples are available for future investigations.

Laboratory Spectrometer for Wear Metal Analysis of Engine Lubricants.

DTIC Science & Technology

1986-04-01

analysis, the acid digestion technique for sample pretreatment is the best approach available to date because of its relatively large sample size (1000...microliters or more). However, this technique has two major shortcomings limiting its application: (1) it requires the use of hydrofluoric acid (a...accuracy. Sample preparation including filtration or acid digestion may increase analysis times by 20 minutes or more. b. Repeatability In the analysis

A microfluidic platform for precision small-volume sample processing and its use to size separate biological particles with an acoustic microdevice [Precision size separation of biological particles in small-volume samples by an acoustic microfluidic system

DOE PAGES

Fong, Erika J.; Huang, Chao; Hamilton, Julie; ...

2015-11-23

Here, a major advantage of microfluidic devices is the ability to manipulate small sample volumes, thus reducing reagent waste and preserving precious sample. However, to achieve robust sample manipulation it is necessary to address device integration with the macroscale environment. To realize repeatable, sensitive particle separation with microfluidic devices, this protocol presents a complete automated and integrated microfluidic platform that enables precise processing of 0.15–1.5 ml samples using microfluidic devices. Important aspects of this system include modular device layout and robust fixtures resulting in reliable and flexible world to chip connections, and fully-automated fluid handling which accomplishes closed-loop sample collection,more » system cleaning and priming steps to ensure repeatable operation. Different microfluidic devices can be used interchangeably with this architecture. Here we incorporate an acoustofluidic device, detail its characterization, performance optimization, and demonstrate its use for size-separation of biological samples. By using real-time feedback during separation experiments, sample collection is optimized to conserve and concentrate sample. Although requiring the integration of multiple pieces of equipment, advantages of this architecture include the ability to process unknown samples with no additional system optimization, ease of device replacement, and precise, robust sample processing.« less

Model Choice and Sample Size in Item Response Theory Analysis of Aphasia Tests

ERIC Educational Resources Information Center

Hula, William D.; Fergadiotis, Gerasimos; Martin, Nadine

2012-01-01

Purpose: The purpose of this study was to identify the most appropriate item response theory (IRT) measurement model for aphasia tests requiring 2-choice responses and to determine whether small samples are adequate for estimating such models. Method: Pyramids and Palm Trees (Howard & Patterson, 1992) test data that had been collected from…

Dimensions of design space: a decision-theoretic approach to optimal research design.

PubMed

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

PubMed

Olives, Casey; Valadez, Joseph J; Pagano, Marcello

2014-03-01

To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria. We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states. Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high. Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size. © 2014 John Wiley & Sons Ltd.

A Simulation Approach to Assessing Sampling Strategies for Insect Pests: An Example with the Balsam Gall Midge

PubMed Central

Carleton, R. Drew; Heard, Stephen B.; Silk, Peter J.

2013-01-01

Estimation of pest density is a basic requirement for integrated pest management in agriculture and forestry, and efficiency in density estimation is a common goal. Sequential sampling techniques promise efficient sampling, but their application can involve cumbersome mathematics and/or intensive warm-up sampling when pests have complex within- or between-site distributions. We provide tools for assessing the efficiency of sequential sampling and of alternative, simpler sampling plans, using computer simulation with “pre-sampling” data. We illustrate our approach using data for balsam gall midge (Paradiplosis tumifex) attack in Christmas tree farms. Paradiplosis tumifex proved recalcitrant to sequential sampling techniques. Midge distributions could not be fit by a common negative binomial distribution across sites. Local parameterization, using warm-up samples to estimate the clumping parameter k for each site, performed poorly: k estimates were unreliable even for samples of n∼100 trees. These methods were further confounded by significant within-site spatial autocorrelation. Much simpler sampling schemes, involving random or belt-transect sampling to preset sample sizes, were effective and efficient for P. tumifex. Sampling via belt transects (through the longest dimension of a stand) was the most efficient, with sample means converging on true mean density for sample sizes of n∼25–40 trees. Pre-sampling and simulation techniques provide a simple method for assessing sampling strategies for estimating insect infestation. We suspect that many pests will resemble P. tumifex in challenging the assumptions of sequential sampling methods. Our software will allow practitioners to optimize sampling strategies before they are brought to real-world applications, while potentially avoiding the need for the cumbersome calculations required for sequential sampling methods. PMID:24376556

40 CFR 52.233 - Review of new sources and modifications.

Code of Federal Regulations, 2011 CFR

2011-07-01

... requiring the source to be provided with: (i) Sampling ports of a size, number, and location as the Administrator may require, (ii) Safe access to each port, (iii) Instrumentation to monitor and record emission... more than 1 MBtu/h (250 Mg-cal/h) and burns only distillate oil; or has a heat input of not more than...

40 CFR 52.233 - Review of new sources and modifications.

Code of Federal Regulations, 2010 CFR

2010-07-01

... requiring the source to be provided with: (i) Sampling ports of a size, number, and location as the Administrator may require, (ii) Safe access to each port, (iii) Instrumentation to monitor and record emission... more than 1 MBtu/h (250 Mg-cal/h) and burns only distillate oil; or has a heat input of not more than...

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

PubMed Central

Thorlund, Kristian; Imberger, Georgina; Walsh, Michael; Chu, Rong; Gluud, Christian; Wetterslev, Jørn; Guyatt, Gordon; Devereaux, Philip J.; Thabane, Lehana

2011-01-01

Background Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. Methods We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. Results The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. Conclusions Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation. PMID:22028777

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

Orphan therapies: making best use of postmarket data.

PubMed

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

2014-08-01

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

Assessing grain-size correspondence between flow and deposits of controlled floods in the Colorado River, USA

USGS Publications Warehouse

Draut, Amy; Rubin, David M.

2013-01-01

Flood-deposited sediment has been used to decipher environmental parameters such as variability in watershed sediment supply, paleoflood hydrology, and channel morphology. It is not well known, however, how accurately the deposits reflect sedimentary processes within the flow, and hence what sampling intensity is needed to decipher records of recent or long-past conditions. We examine these problems using deposits from dam-regulated floods in the Colorado River corridor through Marble Canyon–Grand Canyon, Arizona, U.S.A., in which steady-peaked floods represent a simple end-member case. For these simple floods, most deposits show inverse grading that reflects coarsening suspended sediment (a result of fine-sediment-supply limitation), but there is enough eddy-scale variability that some profiles show normal grading that did not reflect grain-size evolution in the flow as a whole. To infer systemwide grain-size evolution in modern or ancient depositional systems requires sampling enough deposit profiles that the standard error of the mean of grain-size-change measurements becomes small relative to the magnitude of observed changes. For simple, steady-peaked floods, 5–10 profiles or fewer may suffice to characterize grain-size trends robustly, but many more samples may be needed from deposits with greater variability in their grain-size evolution.

A Naturalistic Study of Driving Behavior in Older Adults and Preclinical Alzheimer Disease.

PubMed

Babulal, Ganesh M; Stout, Sarah H; Benzinger, Tammie L S; Ott, Brian R; Carr, David B; Webb, Mollie; Traub, Cindy M; Addison, Aaron; Morris, John C; Warren, David K; Roe, Catherine M

2017-01-01

A clinical consequence of symptomatic Alzheimer's disease (AD) is impaired driving performance. However, decline in driving performance may begin in the preclinical stage of AD. We used a naturalistic driving methodology to examine differences in driving behavior over one year in a small sample of cognitively normal older adults with ( n = 10) and without ( n = 10) preclinical AD. As expected with a small sample size, there were no statistically significant differences between the two groups, but older adults with preclinical AD drove less often, were less likely to drive at night, and had fewer aggressive behaviors such as hard braking, speeding, and sudden acceleration. The sample size required to power a larger study to determine differences was calculated.

Passive vs. Parachute System Architecture for Robotic Sample Return Vehicles

NASA Technical Reports Server (NTRS)

Maddock, Robert W.; Henning, Allen B.; Samareh, Jamshid A.

2016-01-01

The Multi-Mission Earth Entry Vehicle (MMEEV) is a flexible vehicle concept based on the Mars Sample Return (MSR) EEV design which can be used in the preliminary sample return mission study phase to parametrically investigate any trade space of interest to determine the best entry vehicle design approach for that particular mission concept. In addition to the trade space dimensions often considered (e.g. entry conditions, payload size and mass, vehicle size, etc.), the MMEEV trade space considers whether it might be more beneficial for the vehicle to utilize a parachute system during descent/landing or to be fully passive (i.e. not use a parachute). In order to evaluate this trade space dimension, a simplified parachute system model has been developed based on inputs such as vehicle size/mass, payload size/mass and landing requirements. This model works in conjunction with analytical approximations of a mission trade space dataset provided by the MMEEV System Analysis for Planetary EDL (M-SAPE) tool to help quantify the differences between an active (with parachute) and a passive (no parachute) vehicle concept.

A simple method for the analysis of particle sizes of forage and total mixed rations.

PubMed

Lammers, B P; Buckmaster, D R; Heinrichs, A J

1996-05-01

A simple separator was developed to determine the particle sizes of forage and TMR that allows for easy separation of wet forage into three fractions and also allows plotting of the particle size distribution. The device was designed to mimic the laboratory-scale separator for forage particle sizes that was specified by Standard S424 of the American Society of Agricultural Engineers. A comparison of results using the standard device and the newly developed separator indicated no difference in ability to predict fractions of particles with maximum length of less than 8 and 19 mm. The separator requires a small quantity of sample (1.4 L) and is manually operated. The materials on the screens and bottom pan were weighed to obtain the cumulative percentage of sample that was undersize for the two fractions. The results were then plotted using the Weibull distribution, which proved to be the best fit for the data. Convenience samples of haycrop silage, corn silage, and TMR from farms in the northeastern US were analyzed using the forage and TMR separator, and the range of observed values are given.

Power calculation for overall hypothesis testing with high-dimensional commensurate outcomes.

PubMed

Chi, Yueh-Yun; Gribbin, Matthew J; Johnson, Jacqueline L; Muller, Keith E

2014-02-28

The complexity of system biology means that any metabolic, genetic, or proteomic pathway typically includes so many components (e.g., molecules) that statistical methods specialized for overall testing of high-dimensional and commensurate outcomes are required. While many overall tests have been proposed, very few have power and sample size methods. We develop accurate power and sample size methods and software to facilitate study planning for high-dimensional pathway analysis. With an account of any complex correlation structure between high-dimensional outcomes, the new methods allow power calculation even when the sample size is less than the number of variables. We derive the exact (finite-sample) and approximate non-null distributions of the 'univariate' approach to repeated measures test statistic, as well as power-equivalent scenarios useful to generalize our numerical evaluations. Extensive simulations of group comparisons support the accuracy of the approximations even when the ratio of number of variables to sample size is large. We derive a minimum set of constants and parameters sufficient and practical for power calculation. Using the new methods and specifying the minimum set to determine power for a study of metabolic consequences of vitamin B6 deficiency helps illustrate the practical value of the new results. Free software implementing the power and sample size methods applies to a wide range of designs, including one group pre-intervention and post-intervention comparisons, multiple parallel group comparisons with one-way or factorial designs, and the adjustment and evaluation of covariate effects. Copyright © 2013 John Wiley & Sons, Ltd.

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

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

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

Designing group sequential randomized clinical trials with time to event end points using a R function.

PubMed

Filleron, Thomas; Gal, Jocelyn; Kramar, Andrew

2012-10-01

A major and difficult task is the design of clinical trials with a time to event endpoint. In fact, it is necessary to compute the number of events and in a second step the required number of patients. Several commercial software packages are available for computing sample size in clinical trials with sequential designs and time to event endpoints, but there are a few R functions implemented. The purpose of this paper is to describe features and use of the R function. plansurvct.func, which is an add-on function to the package gsDesign which permits in one run of the program to calculate the number of events, and required sample size but also boundaries and corresponding p-values for a group sequential design. The use of the function plansurvct.func is illustrated by several examples and validated using East software. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Development of composite calibration standard for quantitative NDE by ultrasound and thermography

NASA Astrophysics Data System (ADS)

Dayal, Vinay; Benedict, Zach G.; Bhatnagar, Nishtha; Harper, Adam G.

2018-04-01

Inspection of aircraft components for damage utilizing ultrasonic Non-Destructive Evaluation (NDE) is a time intensive endeavor. Additional time spent during aircraft inspections translates to added cost to the company performing them, and as such, reducing this expenditure is of great importance. There is also great variance in the calibration samples from one entity to another due to a lack of a common calibration set. By characterizing damage types, we can condense the required calibration sets and reduce the time required to perform calibration while also providing procedures for the fabrication of these standard sets. We present here our effort to fabricate composite samples with known defects and quantify the size and location of defects, such as delaminations, and impact damage. Ultrasonic and Thermographic images are digitally enhanced to accurately measure the damage size. Ultrasonic NDE is compared with thermography.

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

PubMed Central

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

2017-01-01

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

Phase-contrast x-ray computed tomography for biological imaging

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1997-10-01

We have shown so far that 3D structures in biological sot tissues such as cancer can be revealed by phase-contrast x- ray computed tomography using an x-ray interferometer. As a next step, we aim at applications of this technique to in vivo observation, including radiographic applications. For this purpose, the size of view field is desired to be more than a few centimeters. Therefore, a larger x-ray interferometer should be used with x-rays of higher energy. We have evaluated the optimal x-ray energy from an aspect of does as a function of sample size. Moreover, desired spatial resolution to an image sensor is discussed as functions of x-ray energy and sample size, basing on a requirement in the analysis of interference fringes.

Does Decision Quality (Always) Increase with the Size of Information Samples? Some Vicissitudes in Applying the Law of Large Numbers

ERIC Educational Resources Information Center

Fiedler, Klaus; Kareev, Yaakov

2006-01-01

Adaptive decision making requires that contingencies between decision options and their relative assets be assessed accurately and quickly. The present research addresses the challenging notion that contingencies may be more visible from small than from large samples of observations. An algorithmic account for such a seemingly paradoxical effect…

Convergence between Measures of Work-to-Family and Family-to-Work Conflict: A Meta-Analytic Examination

ERIC Educational Resources Information Center

Mesmer-Magnus, Jessica R.; Viswesvaran, Chockalingam

2005-01-01

The overlap between measures of work-to-family (WFC) and family-to-work conflict (FWC) was meta-analytically investigated. Researchers have assumed WFC and FWC to be distinct, however, this assumption requires empirical verification. Across 25 independent samples (total N=9079) the sample size weighted mean observed correlation was .38 and the…

Wider-Opening Dewar Flasks for Cryogenic Storage

NASA Technical Reports Server (NTRS)

Ruemmele, Warren P.; Manry, John; Stafford, Kristin; Bue, Grant; Krejci, John; Evernden, Bent

2010-01-01

Dewar flasks have been proposed as containers for relatively long-term (25 days) storage of perishable scientific samples or other perishable objects at a temperature of 175 C. The refrigeration would be maintained through slow boiling of liquid nitrogen (LN2). For the purposes of the application for which these containers were proposed, (1) the neck openings of commercial off-the-shelf (COTS) Dewar flasks are too small for most NASA samples; (2) the round shapes of the COTS containers give rise to unacceptably low efficiency of packing in rectangular cargo compartments; and (3) the COTS containers include metal structures that are too thermally conductive, such that they cannot, without exceeding size and weight limits, hold enough LN2 for the required long-term-storage. In comparison with COTS Dewar flasks, the proposed containers would be rectangular, yet would satisfy the long-term storage requirement without exceeding size and weight limits; would have larger neck openings; and would have greater sample volumes, leading to a packing efficiency of about double the sample volume as a fraction of total volume. The proposed containers would be made partly of aerospace- type composite materials and would include vacuum walls, multilayer insulation, and aerogel insulation.

In Situ 3D Coherent X-ray Diffraction Imaging of Shock Experiments: Possible?

NASA Astrophysics Data System (ADS)

Barber, John

2011-03-01

In traditional coherent X-ray diffraction imaging (CXDI), a 2D or quasi-2D object is illuminated by a beam of coherent X-rays to produce a diffraction pattern, which is then manipulated via a process known as iterative phase retrieval to reconstruct an image of the original 2D sample. Recently, there have been dramatic advances in methods for performing fully 3D CXDI of a sample from a single diffraction pattern [Raines et al, Nature 463 214-7 (2010)], and these methods have been used to image samples tens of microns in size using soft X-rays. In this work, I explore the theoretical possibility of applying 3D CXDI techniques to the in situ imaging of the interaction between a shock front and a polycrystal, a far more stringent problem. A delicate trade-off is required between photon energy, spot size, imaging resolution, and the dimensions of the experimental setup. In this talk, I will outline the experimental and computational requirements for performing such an experiment, and I will present images and movies from simulations of one such hypothetical experiment, including both the time-resolved X-ray diffraction patterns and the time-resolved sample imagery.

Estimating the quadratic mean diameters of fine woody debris in forests of the United States

Treesearch

Christopher W. Woodall; Vicente J. Monleon

2010-01-01

Most fine woody debris (FWD) line-intersect sampling protocols and associated estimators require an approximation of the quadratic mean diameter (QMD) of each individual FWD size class. There is a lack of empirically derived QMDs by FWD size class and species/forest type across the U.S. The objective of this study is to evaluate a technique known as the graphical...

Blanks: a computer program for analyzing furniture rough-part needs in standard-size blanks

Treesearch

Philip A. Araman

1983-01-01

A computer program is described that allows a company to determine the number of edge-glued, standard-size blanks required to satisfy its rough-part needs for a given production period. Yield and cost information also is determined by the program. A list of the program inputs, outputs, and uses of outputs is described, and an example analysis with sample output is...

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

PubMed

Ma, Li-Xin; Liu, Jian-Ping

2012-01-01

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

40 CFR 52.780 - Review of new sources and modifications.

Code of Federal Regulations, 2010 CFR

2010-07-01

...,000 Btu per hour (88.2 Mg-cal/h) and 1,500,000 Btu per hour (378.0 MG cal/h), the construction of... requiring the source to be provided with: (i) Sampling ports of a size, number, and location as the Administrator may require, (ii) Safe access to each port, (iii) Instrumentation to monitor and record emission...

40 CFR 52.780 - Review of new sources and modifications.

Code of Federal Regulations, 2011 CFR

2011-07-01

...,000 Btu per hour (88.2 Mg-cal/h) and 1,500,000 Btu per hour (378.0 MG cal/h), the construction of... requiring the source to be provided with: (i) Sampling ports of a size, number, and location as the Administrator may require, (ii) Safe access to each port, (iii) Instrumentation to monitor and record emission...

Design, analysis and presentation of factorial randomised controlled trials

PubMed Central

Montgomery, Alan A; Peters, Tim J; Little, Paul

2003-01-01

Background The evaluation of more than one intervention in the same randomised controlled trial can be achieved using a parallel group design. However this requires increased sample size and can be inefficient, especially if there is also interest in considering combinations of the interventions. An alternative may be a factorial trial, where for two interventions participants are allocated to receive neither intervention, one or the other, or both. Factorial trials require special considerations, however, particularly at the design and analysis stages. Discussion Using a 2 × 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered. Summary Difficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated. PMID:14633287

Study of sample drilling techniques for Mars sample return missions

NASA Technical Reports Server (NTRS)

Mitchell, D. C.; Harris, P. T.

1980-01-01

To demonstrate the feasibility of acquiring various surface samples for a Mars sample return mission the following tasks were performed: (1) design of a Mars rover-mounted drill system capable of acquiring crystalline rock cores; prediction of performance, mass, and power requirements for various size systems, and the generation of engineering drawings; (2) performance of simulated permafrost coring tests using a residual Apollo lunar surface drill, (3) design of a rock breaker system which can be used to produce small samples of rock chips from rocks which are too large to return to Earth, but too small to be cored with the Rover-mounted drill; (4)design of sample containers for the selected regolith cores, rock cores, and small particulate or rock samples; and (5) design of sample handling and transfer techniques which will be required through all phase of sample acquisition, processing, and stowage on-board the Earth return vehicle. A preliminary design of a light-weight Rover-mounted sampling scoop was also developed.

ALCHEMY: a reliable method for automated SNP genotype calling for small batch sizes and highly homozygous populations

PubMed Central

Wright, Mark H.; Tung, Chih-Wei; Zhao, Keyan; Reynolds, Andy; McCouch, Susan R.; Bustamante, Carlos D.

2010-01-01

Motivation: The development of new high-throughput genotyping products requires a significant investment in testing and training samples to evaluate and optimize the product before it can be used reliably on new samples. One reason for this is current methods for automated calling of genotypes are based on clustering approaches which require a large number of samples to be analyzed simultaneously, or an extensive training dataset to seed clusters. In systems where inbred samples are of primary interest, current clustering approaches perform poorly due to the inability to clearly identify a heterozygote cluster. Results: As part of the development of two custom single nucleotide polymorphism genotyping products for Oryza sativa (domestic rice), we have developed a new genotype calling algorithm called ‘ALCHEMY’ based on statistical modeling of the raw intensity data rather than modelless clustering. A novel feature of the model is the ability to estimate and incorporate inbreeding information on a per sample basis allowing accurate genotyping of both inbred and heterozygous samples even when analyzed simultaneously. Since clustering is not used explicitly, ALCHEMY performs well on small sample sizes with accuracy exceeding 99% with as few as 18 samples. Availability: ALCHEMY is available for both commercial and academic use free of charge and distributed under the GNU General Public License at http://alchemy.sourceforge.net/ Contact: mhw6@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20926420

Thermal probe design for Europa sample acquisition

NASA Astrophysics Data System (ADS)

Horne, Mera F.

2018-01-01

The planned lander missions to the surface of Europa will access samples from the subsurface of the ice in a search for signs of life. A small thermal drill (probe) is proposed to meet the sample requirement of the Science Definition Team's (SDT) report for the Europa mission. The probe is 2 cm in diameter and 16 cm in length and is designed to access the subsurface to 10 cm deep and to collect five ice samples of 7 cm3 each, approximately. The energy required to penetrate the top 10 cm of ice in a vacuum is 26 Wh, approximately, and to melt 7 cm3 of ice is 1.2 Wh, approximately. The requirement stated in the SDT report of collecting samples from five different sites can be accommodated with repeated use of the same thermal drill. For smaller sample sizes, a smaller probe of 1.0 cm in diameter with the same length of 16 cm could be utilized that would require approximately 6.4 Wh to penetrate the top 10 cm of ice, and 0.02 Wh to collect 0.1 g of sample. The thermal drill has the advantage of simplicity of design and operations and the ability to penetrate ice over a range of densities and hardness while maintaining sample integrity.

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

The Effect of Size Fraction in Analyses of Benthic Foraminifera Assemblages: A Case Study Comparing Assemblages from the >125 μm and >150 μm Size Fractions

NASA Astrophysics Data System (ADS)

Weinkauf, Manuel F. G.; Milker, Yvonne

2018-05-01

Benthic Foraminifera assemblages are employed for past environmental reconstructions, as well as for biomonitoring studies in recent environments. Despite their established status for such applications, and existing protocols for sample treatment, not all studies using benthic Foraminifera employ the same methodology. For instance, there is no broad practical consensus whether to use the >125 µm or >150 µm size fraction for benthic foraminiferal assemblage analyses. Here, we use early Pleistocene material from the Pefka E section on the Island of Rhodes (Greece), which has been counted in both size fractions, to investigate whether a 25 µm difference in the counted fraction is already sufficient to have an impact on ecological studies. We analysed the influence of the difference in size fraction on studies of biodiversity as well as multivariate assemblage analyses of the sample material. We found that for both types of studies, the general trends remain the same regardless of the chosen size fraction, but in detail significant differences emerge which are not consistently distributed between samples. Studies which require a high degree of precision can thus not compare results from analyses that used different size fractions, and the inconsistent distribution of differences makes it impossible to develop corrections for this issue. We therefore advocate the consistent use of the >125 µm size fraction for benthic foraminiferal studies in the future.

Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015

USGS Publications Warehouse

Zelt, Ronald B.; Hobza, Christopher M.; Burton, Bethany L.; Schaepe, Nathaniel J.; Piatak, Nadine

2017-11-16

Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded. For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively). For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points.

Level of Service Program for INDOT Operations : APPENDIX B Sub-District Sample Sizes

DOT National Transportation Integrated Search

2012-01-01

INDOT has used an inspection program named Maintenance Quality Survey (MQS) to perform a statewide inspection of their roadway assets, rightofway to rightofway. This inspection requires two twoperson teams approximately 18 months to...

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

Estimating the breeding population of long-billed curlew in the United States

USGS Publications Warehouse

Stanley, T.R.; Skagen, S.K.

2007-01-01

Determining population size and long-term trends in population size for species of high concern is a priority of international, national, and regional conservation plans. Long-billed curlews (Numenius americanus) are a species of special concern in North America due to apparent declines in their population. Because long-billed curlews are not adequately monitored by existing programs, we undertook a 2-year study with the goals of 1) determining present long-billed curlew distribution and breeding population size in the United States and 2) providing recommendations for a long-term long-billed curlew monitoring protocol. We selected a stratified random sample of survey routes in 16 western states for sampling in 2004 and 2005, and we analyzed count data from these routes to estimate detection probabilities and abundance. In addition, we evaluated habitat along roadsides to determine how well roadsides represented habitat throughout the sampling units. We estimated there were 164,515 (SE = 42,047) breeding long-billed curlews in 2004, and 109,533 (SE = 31,060) breeding individuals in 2005. These estimates far exceed currently accepted estimates based on expert opinion. We found that habitat along roadsides was representative of long-billed curlew habitat in general. We make recommendations for improving sampling methodology, and we present power curves to provide guidance on minimum sample sizes required to detect trends in abundance.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation

PubMed Central

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-01-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037

Determining the linkage of disease-resistance genes to molecular markers: the LOD-SCORE method revisited with regard to necessary sample sizes.

PubMed

Hühn, M

1995-05-01

Some approaches to molecular marker-assisted linkage detection for a dominant disease-resistance trait based on a segregating F2 population are discussed. Analysis of two-point linkage is carried out by the traditional measure of maximum lod score. It depends on (1) the maximum-likelihood estimate of the recombination fraction between the marker and the disease-resistance gene locus, (2) the observed absolute frequencies, and (3) the unknown number of tested individuals. If one replaces the absolute frequencies by expressions depending on the unknown sample size and the maximum-likelihood estimate of recombination value, the conventional rule for significant linkage (maximum lod score exceeds a given linkage threshold) can be resolved for the sample size. For each sub-population used for linkage analysis [susceptible (= recessive) individuals, resistant (= dominant) individuals, complete F2] this approach gives a lower bound for the necessary number of individuals required for the detection of significant two-point linkage by the lod-score method.

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

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

Valid approximation of spatially distributed grain size distributions - A priori information encoded to a feedforward network

NASA Astrophysics Data System (ADS)

Berthold, T.; Milbradt, P.; Berkhahn, V.

2018-04-01

This paper presents a model for the approximation of multiple, spatially distributed grain size distributions based on a feedforward neural network. Since a classical feedforward network does not guarantee to produce valid cumulative distribution functions, a priori information is incor porated into the model by applying weight and architecture constraints. The model is derived in two steps. First, a model is presented that is able to produce a valid distribution function for a single sediment sample. Although initially developed for sediment samples, the model is not limited in its application; it can also be used to approximate any other multimodal continuous distribution function. In the second part, the network is extended in order to capture the spatial variation of the sediment samples that have been obtained from 48 locations in the investigation area. Results show that the model provides an adequate approximation of grain size distributions, satisfying the requirements of a cumulative distribution function.

Characterization of fish assemblages and population structure of freshwater fish in two Tunisian reservoirs: implications for fishery management.

PubMed

Mili, Sami; Ennouri, Rym; Dhib, Amel; Laouar, Houcine; Missaoui, Hechmi; Aleya, Lotfi

2016-06-01

To monitor and assess the state of Tunisian freshwater fisheries, two surveys were undertaken at Ghezala and Lahjar reservoirs. Samples were taken in April and May 2013, a period when the fish catchability is high. The selected reservoirs have different surface areas and bathymetries. Using multi-mesh gill nets (EN 14575 amended) designed for sampling fish in lakes, standard fishing methods were applied to estimate species composition, abundance, biomass, and size distribution. Four species were caught in the two reservoirs: barbel, mullet, pike-perch, and roach. Fish abundance showed significant change according to sampling sites, depth strata, and the different mesh sizes used. From the reservoir to the tributary, it was concluded that fish biomass distribution was governed by depth and was most abundant in the upper water layers. Species size distribution differed significantly between the two reservoirs, exceeding the length at first maturity. Species composition and abundance were greater in Lahjar reservoir than in Ghezala. Both reservoirs require support actions to improve fish productivity.

A Powder Delivery System (PoDS) for Mars in situ Science

NASA Astrophysics Data System (ADS)

Bryson, C.; Blake, D.; Saha, C.; Sarrazin, P.

2004-12-01

Many instruments proposed for in situ Mars science investigations work best with fine-grained samples of rocks or soils. Such instruments include the mineral analyzer CheMin [1] and any instrument that requires samples having high surface areas (e.g., mass spectrometers, organic analyzers, etc). The Powder Delivery System (PoDS) is designed to deliver powders of selected grain sizes from a sample acquisition device such as an arm-deployed robotic driller or corer to an instrument suite located on the body of a rover/lander. PoDS is capable of size-selective sampling of crushed rocks, soil or drill powder for delivery to instruments that require specific grain sizes (e.g. 5-50 mg of less than150 micron powder for CheMin). Sample material is transported as an aerosol of particles and gas by vacuum advection. In the laboratory a venturi pump driven by compressed air provides the impulse. On Mars, the ambient atmosphere is a source of CO2 that can be captured and compressed by adsorption pumping during diurnal temperature cycling [2]. The lower atmospheric pressure on the surface of Mars (7 torr) will affect fundamental parameters of gas-particle interaction such as Reynolds, Stocks and Knudsen numbers [3]. However, calculations show that the PoDS will operate under both Martian and terrestrial atmospheric conditions. Cyclone separators with appropriate particle size selection ranges remove particles from the aerosol stream. The vortex flow inside the cyclone causes grains larger than a specific size to be collected, while smaller grains remain entrained in the gas. Cyclones are very efficient inertial and centrifugal particle separators with cut sizes (d50) as low as 4 microns. Depending on the particle size ranges desired, a series of cyclones with descending cut sizes may be used, the simplest case being a single cyclone for particle deposition without mass separation. Transmission / membrane filters of appropriate pore sizes may also be used to collect powder from the aerosol stream. Results of a number of tests of the prototype PoDS will be presented. [1] Blake D. F., Sarrazin P., Bish D. L., Feldman S., Chipera S. J, Vaniman D.T., and Collins S., 2004, Definitive Mineralogical Analysis of Mars Analog Rocks Using the CheMin XRD/XRF Instrument, LPSC XXXV abstr. #1794 (CD-ROM). [2] Finn J. E., McKay C. P. and Sridhar R. K., 1999, Martian Atmosphere Utilization by Temperature-Swing Adsorption, University of Arizona, Publication No.961597, http://stl.ame.arizona.edu/publications/961597.pdf [3] Hinds W. C., 1999, Aerosol Technology - Properties, Behavior, and Measurement of Airborne Particles, Second edition, John Wiley & Sons, Inc., pp 15-67, 111-136.

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

PubMed

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

2017-02-01

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

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

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

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

2014-09-22

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

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Estimation of within-stratum variance for sample allocation: Foreign commodity production forecasting

NASA Technical Reports Server (NTRS)

Chhikara, R. S.; Perry, C. R., Jr. (Principal Investigator)

1980-01-01

The problem of determining the stratum variances required for an optimum sample allocation for remotely sensed crop surveys is investigated with emphasis on an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical statistics is developed for obtaining initial estimates of stratum variances. The procedure is applied to variance for wheat in the U.S. Great Plains and is evaluated based on the numerical results obtained. It is shown that the proposed technique is viable and performs satisfactorily with the use of a conservative value (smaller than the expected value) for the field size and with the use of crop statistics from the small political division level.

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

PubMed

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

2017-11-01

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

The Influence of Mark-Recapture Sampling Effort on Estimates of Rock Lobster Survival

PubMed Central

Kordjazi, Ziya; Frusher, Stewart; Buxton, Colin; Gardner, Caleb; Bird, Tomas

2016-01-01

Five annual capture-mark-recapture surveys on Jasus edwardsii were used to evaluate the effect of sample size and fishing effort on the precision of estimated survival probability. Datasets of different numbers of individual lobsters (ranging from 200 to 1,000 lobsters) were created by random subsampling from each annual survey. This process of random subsampling was also used to create 12 datasets of different levels of effort based on three levels of the number of traps (15, 30 and 50 traps per day) and four levels of the number of sampling-days (2, 4, 6 and 7 days). The most parsimonious Cormack-Jolly-Seber (CJS) model for estimating survival probability shifted from a constant model towards sex-dependent models with increasing sample size and effort. A sample of 500 lobsters or 50 traps used on four consecutive sampling-days was required for obtaining precise survival estimations for males and females, separately. Reduced sampling effort of 30 traps over four sampling days was sufficient if a survival estimate for both sexes combined was sufficient for management of the fishery. PMID:26990561

Minimum and Maximum Times Required to Obtain Representative Suspended Sediment Samples

NASA Astrophysics Data System (ADS)

Gitto, A.; Venditti, J. G.; Kostaschuk, R.; Church, M. A.

2014-12-01

Bottle sampling is a convenient method of obtaining suspended sediment measurements for the development of sediment budgets. While these methods are generally considered to be reliable, recent analysis of depth-integrated sampling has identified considerable uncertainty in measurements of grain-size concentration between grain-size classes of multiple samples. Point-integrated bottle sampling is assumed to represent the mean concentration of suspended sediment but the uncertainty surrounding this method is not well understood. Here we examine at-a-point variability in velocity, suspended sediment concentration, grain-size distribution, and grain-size moments to determine if traditional point-integrated methods provide a representative sample of suspended sediment. We present continuous hour-long observations of suspended sediment from the sand-bedded portion of the Fraser River at Mission, British Columbia, Canada, using a LISST laser-diffraction instrument. Spectral analysis suggests that there are no statistically significant peak in energy density, suggesting the absence of periodic fluctuations in flow and suspended sediment. However, a slope break in the spectra at 0.003 Hz corresponds to a period of 5.5 minutes. This coincides with the threshold between large-scale turbulent eddies that scale with channel width/mean velocity and hydraulic phenomena related to channel dynamics. This suggests that suspended sediment samples taken over a period longer than 5.5 minutes incorporate variability that is larger scale than turbulent phenomena in this channel. Examination of 5.5-minute periods of our time series indicate that ~20% of the time a stable mean value of volumetric concentration is reached within 30 seconds, a typical bottle sample duration. In ~12% of measurements a stable mean was not reached over the 5.5 minute sample duration. The remaining measurements achieve a stable mean in an even distribution over the intervening interval.

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

High-resolution observations of low-luminosity gigahertz-peaked spectrum and compact steep-spectrum sources

NASA Astrophysics Data System (ADS)

Collier, J. D.; Tingay, S. J.; Callingham, J. R.; Norris, R. P.; Filipović, M. D.; Galvin, T. J.; Huynh, M. T.; Intema, H. T.; Marvil, J.; O'Brien, A. N.; Roper, Q.; Sirothia, S.; Tothill, N. F. H.; Bell, M. E.; For, B.-Q.; Gaensler, B. M.; Hancock, P. J.; Hindson, L.; Hurley-Walker, N.; Johnston-Hollitt, M.; Kapińska, A. D.; Lenc, E.; Morgan, J.; Procopio, P.; Staveley-Smith, L.; Wayth, R. B.; Wu, C.; Zheng, Q.; Heywood, I.; Popping, A.

2018-06-01

We present very long baseline interferometry observations of a faint and low-luminosity (L1.4 GHz < 1027 W Hz-1) gigahertz-peaked spectrum (GPS) and compact steep-spectrum (CSS) sample. We select eight sources from deep radio observations that have radio spectra characteristic of a GPS or CSS source and an angular size of θ ≲ 2 arcsec, and detect six of them with the Australian Long Baseline Array. We determine their linear sizes, and model their radio spectra using synchrotron self-absorption (SSA) and free-free absorption (FFA) models. We derive statistical model ages, based on a fitted scaling relation, and spectral ages, based on the radio spectrum, which are generally consistent with the hypothesis that GPS and CSS sources are young and evolving. We resolve the morphology of one CSS source with a radio luminosity of 10^{25} W Hz^{-1}, and find what appear to be two hotspots spanning 1.7 kpc. We find that our sources follow the turnover-linear size relation, and that both homogeneous SSA and an inhomogeneous FFA model can account for the spectra with observable turnovers. All but one of the FFA models do not require a spectral break to account for the radio spectrum, while all but one of the alternative SSA and power-law models do require a spectral break to account for the radio spectrum. We conclude that our low-luminosity sample is similar to brighter samples in terms of their spectral shape, turnover frequencies, linear sizes, and ages, but cannot test for a difference in morphology.

Compact ultrahigh vacuum sample environments for x-ray nanobeam diffraction and imaging.

PubMed

Evans, P G; Chahine, G; Grifone, R; Jacques, V L R; Spalenka, J W; Schülli, T U

2013-11-01

X-ray nanobeams present the opportunity to obtain structural insight in materials with small volumes or nanoscale heterogeneity. The effective spatial resolution of the information derived from nanobeam techniques depends on the stability and precision with which the relative position of the x-ray optics and sample can be controlled. Nanobeam techniques include diffraction, imaging, and coherent scattering, with applications throughout materials science and condensed matter physics. Sample positioning is a significant mechanical challenge for x-ray instrumentation providing vacuum or controlled gas environments at elevated temperatures. Such environments often have masses that are too large for nanopositioners capable of the required positional accuracy of the order of a small fraction of the x-ray spot size. Similarly, the need to place x-ray optics as close as 1 cm to the sample places a constraint on the overall size of the sample environment. We illustrate a solution to the mechanical challenge in which compact ion-pumped ultrahigh vacuum chambers with masses of 1-2 kg are integrated with nanopositioners. The overall size of the environment is sufficiently small to allow their use with zone-plate focusing optics. We describe the design of sample environments for elevated-temperature nanobeam diffraction experiments demonstrate in situ diffraction, reflectivity, and scanning nanobeam imaging of the ripening of Au crystallites on Si substrates.

Compact ultrahigh vacuum sample environments for x-ray nanobeam diffraction and imaging

NASA Astrophysics Data System (ADS)

Evans, P. G.; Chahine, G.; Grifone, R.; Jacques, V. L. R.; Spalenka, J. W.; Schülli, T. U.

2013-11-01

X-ray nanobeams present the opportunity to obtain structural insight in materials with small volumes or nanoscale heterogeneity. The effective spatial resolution of the information derived from nanobeam techniques depends on the stability and precision with which the relative position of the x-ray optics and sample can be controlled. Nanobeam techniques include diffraction, imaging, and coherent scattering, with applications throughout materials science and condensed matter physics. Sample positioning is a significant mechanical challenge for x-ray instrumentation providing vacuum or controlled gas environments at elevated temperatures. Such environments often have masses that are too large for nanopositioners capable of the required positional accuracy of the order of a small fraction of the x-ray spot size. Similarly, the need to place x-ray optics as close as 1 cm to the sample places a constraint on the overall size of the sample environment. We illustrate a solution to the mechanical challenge in which compact ion-pumped ultrahigh vacuum chambers with masses of 1-2 kg are integrated with nanopositioners. The overall size of the environment is sufficiently small to allow their use with zone-plate focusing optics. We describe the design of sample environments for elevated-temperature nanobeam diffraction experiments demonstrate in situ diffraction, reflectivity, and scanning nanobeam imaging of the ripening of Au crystallites on Si substrates.

A Multi-Week Behavioral Sampling Tag for Sound Effects Studies: Design Trade-Offs and Prototype Evaluation

DTIC Science & Technology

2013-09-30

performance of algorithms detecting dives, strokes , clicks, respiration and gait changes. (ii) Calibration errors: Size and power constraints in...acceptance parameters used to detect and classify events. For example, swim stroke detection requires parameters defining the minimum magnitude and the min...and max duration of a stroke . Species dependent parameters can be selected from existing DTAG data but other parameters depend on the size of the

Particulate Removal Using a CO2 Composite Spray Cleaning System

NASA Technical Reports Server (NTRS)

Chen, Nicole; Lin, Ying; Jackson, David; Chung, Shirley

2016-01-01

The Planetary Protection surface cleanliness requirements for potential Mars Sample Return hardware that would come in contact with Martian samples may be stricter than previous missions. The Jet Propulsion Laboratory has developed a new technology that will enable us to remove sub-micron size particles from critical hardware surfaces. A hand-held CO2 composite cleaning system was tested to verify its cleaning capabilities. This convenient, portable device can be used in cleanrooms for cleaning after rework or during spacecraft integration and assembly. It is environmentally safe and easy to use. This cleaning concept has the potential to be further developed into a robotic cleaning device on a Mars Lander to be used to clean sample acquisition or sample handling devices in situ. Contaminants of known sizes and concentrations, such as fluorescent microspheres and spores were deposited on common spacecraft material surfaces. The cleaning efficiency results will be presented and discussed.

Function approximation and documentation of sampling data using artificial neural networks.

PubMed

Zhang, Wenjun; Barrion, Albert

2006-11-01

Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field. Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors. BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.

Emperical Tests of Acceptance Sampling Plans

NASA Technical Reports Server (NTRS)

White, K. Preston, Jr.; Johnson, Kenneth L.

2012-01-01

Acceptance sampling is a quality control procedure applied as an alternative to 100% inspection. A random sample of items is drawn from a lot to determine the fraction of items which have a required quality characteristic. Both the number of items to be inspected and the criterion for determining conformance of the lot to the requirement are given by an appropriate sampling plan with specified risks of Type I and Type II sampling errors. In this paper, we present the results of empirical tests of the accuracy of selected sampling plans reported in the literature. These plans are for measureable quality characteristics which are known have either binomial, exponential, normal, gamma, Weibull, inverse Gaussian, or Poisson distributions. In the main, results support the accepted wisdom that variables acceptance plans are superior to attributes (binomial) acceptance plans, in the sense that these provide comparable protection against risks at reduced sampling cost. For the Gaussian and Weibull plans, however, there are ranges of the shape parameters for which the required sample sizes are in fact larger than the corresponding attributes plans, dramatically so for instances of large skew. Tests further confirm that the published inverse-Gaussian (IG) plan is flawed, as reported by White and Johnson (2011).

Avoiding drying-artifacts in transmission electron microscopy: Characterizing the size and colloidal state of nanoparticles

PubMed Central

Michen, Benjamin; Geers, Christoph; Vanhecke, Dimitri; Endes, Carola; Rothen-Rutishauser, Barbara; Balog, Sandor; Petri-Fink, Alke

2015-01-01

Standard transmission electron microscopy nanoparticle sample preparation generally requires the complete removal of the suspending liquid. Drying often introduces artifacts, which can obscure the state of the dispersion prior to drying and preclude automated image analysis typically used to obtain number-weighted particle size distribution. Here we present a straightforward protocol for prevention of the onset of drying artifacts, thereby allowing the preservation of in-situ colloidal features of nanoparticles during TEM sample preparation. This is achieved by adding a suitable macromolecular agent to the suspension. Both research- and economically-relevant particles with high polydispersity and/or shape anisotropy are easily characterized following our approach (http://bsa.bionanomaterials.ch), which allows for rapid and quantitative classification in terms of dimensionality and size: features that are major targets of European Union recommendations and legislation. PMID:25965905

Beyond Gorilla and Pongo: alternative models for evaluating variation and sexual dimorphism in fossil hominoid samples.

PubMed

Scott, Jeremiah E; Schrein, Caitlin M; Kelley, Jay

2009-10-01

Sexual size dimorphism in the postcanine dentition of the late Miocene hominoid Lufengpithecus lufengensis exceeds that in Pongo pygmaeus, demonstrating that the maximum degree of molar size dimorphism in apes is not represented among the extant Hominoidea. It has not been established, however, that the molars of Pongo are more dimorphic than those of any other living primate. In this study, we used resampling-based methods to compare molar dimorphism in Gorilla, Pongo, and Lufengpithecus to that in the papionin Mandrillus leucophaeus to test two hypotheses: (1) Pongo possesses the most size-dimorphic molars among living primates and (2) molar size dimorphism in Lufengpithecus is greater than that in the most dimorphic living primates. Our results show that M. leucophaeus exceeds great apes in its overall level of dimorphism and that L. lufengensis is more dimorphic than the extant species. Using these samples, we also evaluated molar dimorphism and taxonomic composition in two other Miocene ape samples--Ouranopithecus macedoniensis from Greece, specimens of which can be sexed based on associated canines and P(3)s, and the Sivapithecus sample from Haritalyangar, India. Ouranopithecus is more dimorphic than the extant taxa but is similar to Lufengpithecus, demonstrating that the level of molar dimorphism required for the Greek fossil sample under the single-species taxonomy is not unprecedented when the comparative framework is expanded to include extinct primates. In contrast, the Haritalyangar Sivapithecus sample, if itrepresents a single species, exhibits substantially greater molar dimorphism than does Lufengpithecus. Given these results, the taxonomic status of this sample remains equivocal.

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

PubMed Central

Hemming, Karla; Taljaard, Monica

2016-01-01

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

How conservative is Fisher's exact test? A quantitative evaluation of the two-sample comparative binomial trial.

PubMed

Crans, Gerald G; Shuster, Jonathan J

2008-08-15

The debate as to which statistical methodology is most appropriate for the analysis of the two-sample comparative binomial trial has persisted for decades. Practitioners who favor the conditional methods of Fisher, Fisher's exact test (FET), claim that only experimental outcomes containing the same amount of information should be considered when performing analyses. Hence, the total number of successes should be fixed at its observed level in hypothetical repetitions of the experiment. Using conditional methods in clinical settings can pose interpretation difficulties, since results are derived using conditional sample spaces rather than the set of all possible outcomes. Perhaps more importantly from a clinical trial design perspective, this test can be too conservative, resulting in greater resource requirements and more subjects exposed to an experimental treatment. The actual significance level attained by FET (the size of the test) has not been reported in the statistical literature. Berger (J. R. Statist. Soc. D (The Statistician) 2001; 50:79-85) proposed assessing the conservativeness of conditional methods using p-value confidence intervals. In this paper we develop a numerical algorithm that calculates the size of FET for sample sizes, n, up to 125 per group at the two-sided significance level, alpha = 0.05. Additionally, this numerical method is used to define new significance levels alpha(*) = alpha+epsilon, where epsilon is a small positive number, for each n, such that the size of the test is as close as possible to the pre-specified alpha (0.05 for the current work) without exceeding it. Lastly, a sample size and power calculation example are presented, which demonstrates the statistical advantages of implementing the adjustment to FET (using alpha(*) instead of alpha) in the two-sample comparative binomial trial. 2008 John Wiley & Sons, Ltd

Applications of remote sensing, volume 1

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. ECHO successfully exploits the redundancy of states characteristics of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The information required to produce ECHO classifications are cell size, cell homogeneity, cell-to-field annexation parameters, input data, and a class conditional marginal density statistics deck.

A U-statistics based approach to sample size planning of two-arm trials with discrete outcome criterion aiming to establish either superiority or noninferiority.

PubMed

Wellek, Stefan

2017-02-28

In current practice, the most frequently applied approach to the handling of ties in the Mann-Whitney-Wilcoxon (MWW) test is based on the conditional distribution of the sum of mid-ranks, given the observed pattern of ties. Starting from this conditional version of the testing procedure, a sample size formula was derived and investigated by Zhao et al. (Stat Med 2008). In contrast, the approach we pursue here is a nonconditional one exploiting explicit representations for the variances of and the covariance between the two U-statistics estimators involved in the Mann-Whitney form of the test statistic. The accuracy of both ways of approximating the sample sizes required for attaining a prespecified level of power in the MWW test for superiority with arbitrarily tied data is comparatively evaluated by means of simulation. The key qualitative conclusions to be drawn from these numerical comparisons are as follows: With the sample sizes calculated by means of the respective formula, both versions of the test maintain the level and the prespecified power with about the same degree of accuracy. Despite the equivalence in terms of accuracy, the sample size estimates obtained by means of the new formula are in many cases markedly lower than that calculated for the conditional test. Perhaps, a still more important advantage of the nonconditional approach based on U-statistics is that it can be also adopted for noninferiority trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The interplay of various sources of noise on reliability of species distribution models hinges on ecological specialisation.

PubMed

Soultan, Alaaeldin; Safi, Kamran

2017-01-01

Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Robustness of methods for blinded sample size re-estimation with overdispersed count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-09-20

Counts of events are increasingly common as primary endpoints in randomized clinical trials. With between-patient heterogeneity leading to variances in excess of the mean (referred to as overdispersion), statistical models reflecting this heterogeneity by mixtures of Poisson distributions are frequently employed. Sample size calculation in the planning of such trials requires knowledge on the nuisance parameters, that is, the control (or overall) event rate and the overdispersion parameter. Usually, there is only little prior knowledge regarding these parameters in the design phase resulting in considerable uncertainty regarding the sample size. In this situation internal pilot studies have been found very useful and very recently several blinded procedures for sample size re-estimation have been proposed for overdispersed count data, one of which is based on an EM-algorithm. In this paper we investigate the EM-algorithm based procedure with respect to aspects of their implementation by studying the algorithm's dependence on the choice of convergence criterion and find that the procedure is sensitive to the choice of the stopping criterion in scenarios relevant to clinical practice. We also compare the EM-based procedure to other competing procedures regarding their operating characteristics such as sample size distribution and power. Furthermore, the robustness of these procedures to deviations from the model assumptions is explored. We find that some of the procedures are robust to at least moderate deviations. The results are illustrated using data from the US National Heart, Lung and Blood Institute sponsored Asymptomatic Cardiac Ischemia Pilot study. Copyright © 2013 John Wiley & Sons, Ltd.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

Designing clinical trials to test disease-modifying agents: application to the treatment trials of Alzheimer's disease.

PubMed

Xiong, Chengjie; van Belle, Gerald; Miller, J Philip; Morris, John C

2011-02-01

Therapeutic trials of disease-modifying agents on Alzheimer's disease (AD) require novel designs and analyses involving switch of treatments for at least a portion of subjects enrolled. Randomized start and randomized withdrawal designs are two examples of such designs. Crucial design parameters such as sample size and the time of treatment switch are important to understand in designing such clinical trials. The purpose of this article is to provide methods to determine sample sizes and time of treatment switch as well as optimum statistical tests of treatment efficacy for clinical trials of disease-modifying agents on AD. A general linear mixed effects model is proposed to test the disease-modifying efficacy of novel therapeutic agents on AD. This model links the longitudinal growth from both the placebo arm and the treatment arm at the time of treatment switch for these in the delayed treatment arm or early withdrawal arm and incorporates the potential correlation on the rate of cognitive change before and after the treatment switch. Sample sizes and the optimum time for treatment switch of such trials as well as optimum test statistic for the treatment efficacy are determined according to the model. Assuming an evenly spaced longitudinal design over a fixed duration, the optimum treatment switching time in a randomized start or a randomized withdrawal trial is half way through the trial. With the optimum test statistic for the treatment efficacy and over a wide spectrum of model parameters, the optimum sample size allocations are fairly close to the simplest design with a sample size ratio of 1:1:1 among the treatment arm, the delayed treatment or early withdrawal arm, and the placebo arm. The application of the proposed methodology to AD provides evidence that much larger sample sizes are required to adequately power disease-modifying trials when compared with those for symptomatic agents, even when the treatment switch time and efficacy test are optimally chosen. The proposed method assumes that the only and immediate effect of treatment switch is on the rate of cognitive change. Crucial design parameters for the clinical trials of disease-modifying agents on AD can be optimally chosen. Government and industry officials as well as academia researchers should consider the optimum use of the clinical trials design for disease-modifying agents on AD in their effort to search for the treatments with the potential to modify the underlying pathophysiology of AD.

Thermophoretic separation of aerosol particles from a sampled gas stream

DOEpatents

Postma, A.K.

1984-09-07

This disclosure relates to separation of aerosol particles from gas samples withdrawn from within a contained atmosphere, such as containment vessels for nuclear reactors or other process equipment where remote gaseous sampling is required. It is specifically directed to separation of dense aerosols including particles of any size and at high mass loadings and high corrosivity. The United States Government has rights in this invention pursuant to Contract DE-AC06-76FF02170 between the US Department of Energy and Westinghouse Electric Corporation.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Towards well-defined gold nanomaterials via diafiltration and aptamer mediated synthesis

NASA Astrophysics Data System (ADS)

Sweeney, Scott Francis

Gold nanoparticles have garnered recent attention due to their intriguing size- and shape-dependent properties. Routine access to well-defined gold nanoparticle samples in terms of core diameter, shape, peripheral functionality and purity is required in order to carry out fundamental studies of their properties and to utilize these properties in future applications. For this reason, the development of methods for preparing well-defined gold nanoparticle samples remains an area of active research in materials science. In this dissertation, two methods, diafiltration and aptamer mediated synthesis, are explored as possible routes towards well-defined gold nanoparticle samples. It is shown that diafiltration has considerable potential for the efficient and convenient purification and size separation of water-soluble nanoparticles. The suitability of diafiltration for (i) the purification of water-soluble gold nanoparticles, (ii) the separation of a bimodal distribution of nanoparticles into fractions, (iii) the fractionation of a polydisperse sample and (iv) the isolation of [rimers from monomers and aggregates is studied. NMR, thermogravimetric analysis (TGA), and X-ray photoelectron spectroscopy (XPS) measurements demonstrate that diafiltration produces highly pure nanoparticles. UV-visible spectroscopic and transmission electron microscopic analyses show that diafiltration offers the ability to separate nanoparticles of disparate core size, including linked nanoparticles. These results demonstrate the applicability of diafiltration for the rapid and green preparation of high-purity gold nanoparticle samples and the size separation of heterogeneous nanoparticle samples. In the second half of the dissertation, the identification of materials specific aptamers and their use to synthesize shaped gold nanoparticles is explored. The use of in vitro selection for identifying materials specific peptide and oligonucleotide aptamers is reviewed, outlining the specific requirements of in vitro selection for materials and the ways in which the field can be advanced. A promising new technique, in vitro selection on surfaces (ISOS), is developed and the discovery using ISOS of RNA aptamers that bind to evaporated gold is discussed. Analysis of the isolated gold binding RNA aptamers indicates that they are highly structured with single-stranded polyadenosine binding motifs. These aptamers, and similarly isolated peptide aptamers, are briefly explored for their ability to synthesize gold nanoparticles. This dissertation contains both previously published and unpublished co-authored material.

Sample preparation techniques for the determination of trace residues and contaminants in foods.

PubMed

Ridgway, Kathy; Lalljie, Sam P D; Smith, Roger M

2007-06-15

The determination of trace residues and contaminants in complex matrices, such as food, often requires extensive sample extraction and preparation prior to instrumental analysis. Sample preparation is often the bottleneck in analysis and there is a need to minimise the number of steps to reduce both time and sources of error. There is also a move towards more environmentally friendly techniques, which use less solvent and smaller sample sizes. Smaller sample size becomes important when dealing with real life problems, such as consumer complaints and alleged chemical contamination. Optimal sample preparation can reduce analysis time, sources of error, enhance sensitivity and enable unequivocal identification, confirmation and quantification. This review considers all aspects of sample preparation, covering general extraction techniques, such as Soxhlet and pressurised liquid extraction, microextraction techniques such as liquid phase microextraction (LPME) and more selective techniques, such as solid phase extraction (SPE), solid phase microextraction (SPME) and stir bar sorptive extraction (SBSE). The applicability of each technique in food analysis, particularly for the determination of trace organic contaminants in foods is discussed.

Performance monitoring in hip fracture surgery--how big a database do we really need?

PubMed

Edwards, G A D; Metcalfe, A J; Johansen, A; O'Doherty, D

2010-04-01

Systems for collecting information about patient care are increasingly common in orthopaedic practice. Databases can allow various comparisons to be made over time. Significant decisions regarding service delivery and clinical practice may be made based on their results. We set out to determine the number of cases needed for comparison of 30-day mortality, inpatient wound infection rates and mean hospital length of stay, with a power of 80% for the demonstration of an effect at a significance level of p<0.05. We analysed 2 years of prospectively collected data on 1050 hip fracture patients admitted to a city teaching hospital. Detection of a 10% difference in 30-day mortality would require 14,065 patients in each arm of any comparison, demonstration of a 50% difference would require 643 patients in each arm; for wound infections, demonstration of a 10% difference in incidence would require 23,921 patients in each arm and 1127 patients for demonstration of a 50% difference; for length of stay, a difference of 10% would require 1479 patients and 6660 patients for a 50% difference. This study demonstrates the importance of considering the population sizes before comparisons are made on the basis of basic hip fracture outcome data. Our data also help illustrate the impact of sample size considerations when interpreting the results of performance monitoring. Many researchers will be used to the fact that rare outcomes such as inpatient mortality or wound infection require large sample sizes before differences can be reliably demonstrated between populations. This study gives actual figures that researchers could use when planning studies. Statistically meaningful analyses will only be possible with major multi-centre collaborations, as will be possible if hospital Trusts participate in the National Hip Fracture Database. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Catch of channel catfish with tandem-set hoop nets and gill nets in lentic systems of Nebraska

USGS Publications Warehouse

Richters, Lindsey K.; Pope, Kevin L.

2011-01-01

Twenty-six Nebraska water bodies representing two ecosystem types (small standing waters and large standing waters) were surveyed during 2008 and 2009 with tandem-set hoop nets and experimental gill nets to determine if similar trends existed in catch rates and size structures of channel catfish Ictalurus punctatus captured with these gears. Gear efficiency was assessed as the number of sets (nets) that would be required to capture 100 channel catfish given observed catch per unit effort (CPUE). Efficiency of gill nets was not correlated with efficiency of hoop nets for capturing channel catfish. Small sample sizes prohibited estimation of proportional size distributions in most surveys; in the four surveys for which sample size was sufficient to quantify length-frequency distributions of captured channel catfish, distributions differed between gears. The CPUE of channel catfish did not differ between small and large water bodies for either gear. While catch rates of hoop nets were lower than rates recorded in previous studies, this gear was more efficient than gill nets at capturing channel catfish. However, comparisons of size structure between gears may be problematic.

A Bayesian nonparametric method for prediction in EST analysis

PubMed Central

Lijoi, Antonio; Mena, Ramsés H; Prünster, Igor

2007-01-01

Background Expressed sequence tags (ESTs) analyses are a fundamental tool for gene identification in organisms. Given a preliminary EST sample from a certain library, several statistical prediction problems arise. In particular, it is of interest to estimate how many new genes can be detected in a future EST sample of given size and also to determine the gene discovery rate: these estimates represent the basis for deciding whether to proceed sequencing the library and, in case of a positive decision, a guideline for selecting the size of the new sample. Such information is also useful for establishing sequencing efficiency in experimental design and for measuring the degree of redundancy of an EST library. Results In this work we propose a Bayesian nonparametric approach for tackling statistical problems related to EST surveys. In particular, we provide estimates for: a) the coverage, defined as the proportion of unique genes in the library represented in the given sample of reads; b) the number of new unique genes to be observed in a future sample; c) the discovery rate of new genes as a function of the future sample size. The Bayesian nonparametric model we adopt conveys, in a statistically rigorous way, the available information into prediction. Our proposal has appealing properties over frequentist nonparametric methods, which become unstable when prediction is required for large future samples. EST libraries, previously studied with frequentist methods, are analyzed in detail. Conclusion The Bayesian nonparametric approach we undertake yields valuable tools for gene capture and prediction in EST libraries. The estimators we obtain do not feature the kind of drawbacks associated with frequentist estimators and are reliable for any size of the additional sample. PMID:17868445

Escherichia coli sampling reliability at a frequently closed Chicago beach: monitoring and management implications

USGS Publications Warehouse

Whitman, Richard L.; Nevers, Meredith B.

2004-01-01

Monitoring beaches for recreational water quality is becoming more common, but few sampling designs or policy approaches have evaluated the efficacy of monitoring programs. The authors intensively sampled water for E. coli (N=1770) at 63rd Street Beach, Chicago for 6 months in 2000 in order to (1) characterize spatial-temporal trends, (2) determine between and within transect variation, and (3) estimate sample size requirements and determine sampling reliability.E. coli counts were highly variable within and between sampling sites but spatially and diurnally autocorrelated. Variation in counts decreased with water depth and time of day. Required number of samples was high for 70% precision around the critical closure level (i.e., 6 within or 24 between transect replicates). Since spatial replication may be cost prohibitive, composite sampling is an alternative once sources of error have been well defined. The results suggest that beach monitoring programs may be requiring too few samples to fulfill management objectives desired. As the recreational water quality national database is developed, it is important that sampling strategies are empirically derived from a thorough understanding of the sources of variation and the reliability of collected data. Greater monitoring efficacy will yield better policy decisions, risk assessments, programmatic goals, and future usefulness of the information.

Declustering of clustered preferential sampling for histogram and semivariogram inference

USGS Publications Warehouse

Olea, R.A.

2007-01-01

Measurements of attributes obtained more as a consequence of business ventures than sampling design frequently result in samplings that are preferential both in location and value, typically in the form of clusters along the pay. Preferential sampling requires preprocessing for the purpose of properly inferring characteristics of the parent population, such as the cumulative distribution and the semivariogram. Consideration of the distance to the nearest neighbor allows preparation of resampled sets that produce comparable results to those from previously proposed methods. Clustered sampling of size 140, taken from an exhaustive sampling, is employed to illustrate this approach. ?? International Association for Mathematical Geology 2007.

Systems and methods for analyzing liquids under vacuum

DOEpatents

Yu, Xiao-Ying; Yang, Li; Cowin, James P.; Iedema, Martin J.; Zhu, Zihua

2013-10-15

Systems and methods for supporting a liquid against a vacuum pressure in a chamber can enable analysis of the liquid surface using vacuum-based chemical analysis instruments. No electrical or fluid connections are required to pass through the chamber walls. The systems can include a reservoir, a pump, and a liquid flow path. The reservoir contains a liquid-phase sample. The pump drives flow of the sample from the reservoir, through the liquid flow path, and back to the reservoir. The flow of the sample is not substantially driven by a differential between pressures inside and outside of the liquid flow path. An aperture in the liquid flow path exposes a stable portion of the liquid-phase sample to the vacuum pressure within the chamber. The radius, or size, of the aperture is less than or equal to a critical value required to support a meniscus of the liquid-phase sample by surface tension.

A planar near-field scanning technique for bistatic radar cross section measurements

NASA Technical Reports Server (NTRS)

Tuhela-Reuning, S.; Walton, E. K.

1990-01-01

A progress report on the development of a bistatic radar cross section (RCS) measurement range is presented. A technique using one parabolic reflector and a planar scanning probe antenna is analyzed. The field pattern in the test zone is computed using a spatial array of signal sources. It achieved an illumination pattern with 1 dB amplitude and 15 degree phase ripple over the target zone. The required scan plane size is found to be proportional to the size of the desired test target. Scan plane probe sample spacing can be increased beyond the Nyquist lambda/2 limit permitting constant probe sample spacing over a range of frequencies.

Embedding clinical interventions into observational studies

PubMed Central

Newman, Anne B.; Avilés-Santa, M. Larissa; Anderson, Garnet; Heiss, Gerardo; Howard, Wm. James; Krucoff, Mitchell; Kuller, Lewis H.; Lewis, Cora E.; Robinson, Jennifer G.; Taylor, Herman; Treviño, Roberto P.; Weintraub, William

2017-01-01

Novel approaches to observational studies and clinical trials could improve the cost-effectiveness and speed of translation of research. Hybrid designs that combine elements of clinical trials with observational registries or cohort studies should be considered as part of a long-term strategy to transform clinical trials and epidemiology, adapting to the opportunities of big data and the challenges of constrained budgets. Important considerations include study aims, timing, breadth and depth of the existing infrastructure that can be leveraged, participant burden, likely participation rate and available sample size in the cohort, required sample size for the trial, and investigator expertise. Community engagement and stakeholder (including study participants) support are essential for these efforts to succeed. PMID:26611435

Sample size and number of outcome measures of veterinary randomised controlled trials of pharmaceutical interventions funded by different sources, a cross-sectional study.

PubMed

Wareham, K J; Hyde, R M; Grindlay, D; Brennan, M L; Dean, R S

2017-10-04

Randomised controlled trials (RCTs) are a key component of the veterinary evidence base. Sample sizes and defined outcome measures are crucial components of RCTs. To describe the sample size and number of outcome measures of veterinary RCTs either funded by the pharmaceutical industry or not, published in 2011. A structured search of PubMed identified RCTs examining the efficacy of pharmaceutical interventions. Number of outcome measures, number of animals enrolled per trial, whether a primary outcome was identified, and the presence of a sample size calculation were extracted from the RCTs. The source of funding was identified for each trial and groups compared on the above parameters. Literature searches returned 972 papers; 86 papers comprising 126 individual trials were analysed. The median number of outcomes per trial was 5.0; there were no significant differences across funding groups (p = 0.133). The median number of animals enrolled per trial was 30.0; this was similar across funding groups (p = 0.302). A primary outcome was identified in 40.5% of trials and was significantly more likely to be stated in trials funded by a pharmaceutical company. A very low percentage of trials reported a sample size calculation (14.3%). Failure to report primary outcomes, justify sample sizes and the reporting of multiple outcome measures was a common feature in all of the clinical trials examined in this study. It is possible some of these factors may be affected by the source of funding of the studies, but the influence of funding needs to be explored with a larger number of trials. Some veterinary RCTs provide a weak evidence base and targeted strategies are required to improve the quality of veterinary RCTs to ensure there is reliable evidence on which to base clinical decisions.

Magnetic Resonance Biomarkers in Neonatal Encephalopathy (MARBLE): a prospective multicountry study.

PubMed

Lally, Peter J; Pauliah, Shreela; Montaldo, Paolo; Chaban, Badr; Oliveira, Vania; Bainbridge, Alan; Soe, Aung; Pattnayak, Santosh; Clarke, Paul; Satodia, Prakash; Harigopal, Sundeep; Abernethy, Laurence J; Turner, Mark A; Huertas-Ceballos, Angela; Shankaran, Seetha; Thayyil, Sudhin

2015-09-30

Despite cooling, adverse outcomes are seen in up to half of the surviving infants after neonatal encephalopathy. A number of novel adjunct drug therapies with cooling have been shown to be highly neuroprotective in animal studies, and are currently awaiting clinical translation. Rigorous evaluation of these therapies in phase II trials using surrogate MR biomarkers may speed up their bench to bedside translation. A recent systematic review of single-centre studies has suggested that MR spectroscopy biomarkers offer the best promise; however, the prognostic accuracy of these biomarkers in cooled encephalopathic babies in a multicentre setting using different MR scan makers is not known. The MR scanners (3 T; Philips, Siemens, GE) in all the participating sites will be harmonised using phantom experiments and healthy adult volunteers before the start of the study. We will then recruit 180 encephalopathic infants treated with whole body cooling from the participating centres. MRI and spectroscopy will be performed within 2 weeks of birth. Neurodevelopmental outcomes will be assessed at 18-24 months of age. Agreement between MR cerebral biomarkers and neurodevelopmental outcome will be reported. The sample size is calculated using the 'rule of 10', generally used to calculate the sample size requirements for developing prognostic models. Considering 9 parameters, we require 9×10 adverse events, which suggest that a total sample size of 180 is required. Human Research Ethics Committee approvals have been received from Brent Research Ethics Committee (London), and from Imperial College London (Sponsor). We will submit the results of the study to relevant journals and offer national and international presentations. Clinical Trials.gov Number: NCT01309711. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Sound absorption by suspensions of nonspherical particles: Measurements compared with predictions using various particle sizing techniques

NASA Astrophysics Data System (ADS)

Richards, Simon D.; Leighton, Timothy G.; Brown, Niven R.

2003-10-01

Knowledge of the particle size distribution is required in order to predict ultrasonic absorption in polydisperse particulate suspensions. This paper shows that the method used to measure the particle size distribution can lead to important differences in the predicted absorption. A reverberation technique developed for measuring ultrasonic absorption by suspended particles is used to measure the absorption in suspensions of nonspherical particles. Two types of particulates are studied: (i) kaolin (china clay) particles which are platelike in form; and (ii) calcium carbonate particles which are more granular. Results are compared to theoretical predictions of visco-inertial absorption by suspensions of spherical particles. The particle size distributions, which are required for these predictions, are measured by laser diffraction, gravitational sedimentation and centrifugal sedimentation, all of which assume spherical particles. For a given sample, each sizing technique yields a different size distribution, leading to differences in the predicted absorption. The particle size distributions obtained by gravitational and centrifugal sedimentation are reinterpreted to yield a representative size distribution of oblate spheroids, and predictions for absorption by these spheroids are compared with the measurements. Good agreement between theory and measurement for the flat kaolin particles is obtained, demonstrating that these particles can be adequately represented by oblate spheroids.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Exploiting Size-Dependent Drag and Magnetic Forces for Size-Specific Separation of Magnetic Nanoparticles

PubMed Central

Rogers, Hunter B.; Anani, Tareq; Choi, Young Suk; Beyers, Ronald J.; David, Allan E.

2015-01-01

Realizing the full potential of magnetic nanoparticles (MNPs) in nanomedicine requires the optimization of their physical and chemical properties. Elucidation of the effects of these properties on clinical diagnostic or therapeutic properties, however, requires the synthesis or purification of homogenous samples, which has proved to be difficult. While initial simulations indicated that size-selective separation could be achieved by flowing magnetic nanoparticles through a magnetic field, subsequent in vitro experiments were unable to reproduce the predicted results. Magnetic field-flow fractionation, however, was found to be an effective method for the separation of polydisperse suspensions of iron oxide nanoparticles with diameters greater than 20 nm. While similar methods have been used to separate magnetic nanoparticles before, no previous work has been done with magnetic nanoparticles between 20 and 200 nm. Both transmission electron microscopy (TEM) and dynamic light scattering (DLS) analysis were used to confirm the size of the MNPs. Further development of this work could lead to MNPs with the narrow size distributions necessary for their in vitro and in vivo optimization. PMID:26307980

A comprehensive algorithm for determining whether a run-in strategy will be a cost-effective design modification in a randomized clinical trial.

PubMed

Schechtman, K B; Gordon, M E

1993-01-30

In randomized clinical trials, poor compliance and treatment intolerance lead to reduced between-group differences, increased sample size requirements, and increased cost. A run-in strategy is intended to reduce these problems. In this paper, we develop a comprehensive set of measures specifically sensitive to the effect of a run-in on cost and sample size requirements, both before and after randomization. Using these measures, we describe a step-by-step algorithm through which one can estimate the cost-effectiveness of a potential run-in. Because the cost-effectiveness of a run-in is partly mediated by its effect on sample size, we begin by discussing the likely impact of a planned run-in on the required number of randomized, eligible, and screened subjects. Run-in strategies are most likely to be cost-effective when: (1) per patient costs during the post-randomization as compared to the screening period are high; (2) poor compliance is associated with a substantial reduction in response to treatment; (3) the number of screened patients needed to identify a single eligible patient is small; (4) the run-in is inexpensive; (5) for most patients, the run-in compliance status is maintained following randomization and, most importantly, (6) many subjects excluded by the run-in are treatment intolerant or non-compliant to the extent that we expect little or no treatment response. Our analysis suggests that conditions for the cost-effectiveness of run-in strategies are stringent. In particular, if the only purpose of a run-in is to exclude ordinary partial compliers, the run-in will frequently add to the cost of the trial. Often, the cost-effectiveness of a run-in requires that one can identify and exclude a substantial number of treatment intolerant or otherwise unresponsive subjects.

Variable aperture-based ptychographical iterative engine method

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-02-01

A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches.

Computer re-sampling for demographically representative user populations in anthropometry: a case of doorway and clear floor space widths.

PubMed

Paquet, Victor; Joseph, Caroline; D'Souza, Clive

2012-01-01

Anthropometric studies typically require a large number of individuals that are selected in a manner so that demographic characteristics that impact body size and function are proportionally representative of a user population. This sampling approach does not allow for an efficient characterization of the distribution of body sizes and functions of sub-groups within a population and the demographic characteristics of user populations can often change with time, limiting the application of the anthropometric data in design. The objective of this study is to demonstrate how demographically representative user populations can be developed from samples that are not proportionally representative in order to improve the application of anthropometric data in design. An engineering anthropometry problem of door width and clear floor space width is used to illustrate the value of the approach.

The design and assembly of aluminum mirrors of a three-mirror-anastigmat telescope

NASA Astrophysics Data System (ADS)

Chang, Shenq-Tsong; Lin, Yu-Chuan; Wu, Kun-Huan; Lien, Chun-Chieh; Huang, Ting-Ming; Tsay, Ho-Lin; Chan, Chia-Yen

2017-09-01

Better ground sampling distance (GSD) has been a trend for earth observation satellites. A long-focal-length telescope is required accordingly in systematic point of view. On the other hand, there is size constraint for such long-focal-length telescope especially in space projects. Three-mirror-anastigmat (TMA) was proven to have excellent features of correcting aberrations, wide spectral range and shorter physical requirement [1-3].

Colloidal-facilitated transport of inorganic contaminants in ground water: part 1, sampling considerations

USGS Publications Warehouse

Puls, Robert W.; Eychaner, James H.; Powell, Robert M.

1996-01-01

Investigations at Pinal Creek, Arizona, evaluated routine sampling procedures for determination of aqueous inorganic geochemistry and assessment of contaminant transport by colloidal mobility. Sampling variables included pump type and flow rate, collection under air or nitrogen, and filter pore diameter. During well purging and sample collection, suspended particle size and number as well as dissolved oxygen, temperature, specific conductance, pH, and redox potential were monitored. Laboratory analyses of both unfiltered samples and the filtrates were performed by inductively coupled argon plasma, atomic absorption with graphite furnace, and ion chromatography. Scanning electron microscopy with Energy Dispersive X-ray was also used for analysis of filter particulates. Suspended particle counts consistently required approximately twice as long as the other field-monitored indicators to stabilize. High-flow-rate pumps entrained normally nonmobile particles. Difference in elemental concentrations using different filter-pore sizes were generally not large with only two wells having differences greater than 10 percent in most wells. Similar differences (>10%) were observed for some wells when samples were collected under nitrogen rather than in air. Fe2+/Fe3+ ratios for air-collected samples were smaller than for samples collected under a nitrogen atmosphere, reflecting sampling-induced oxidation.

78 FR 74175 - Agency Information Collection Activities: Proposed Collection; Comment Request; Generic Clearance...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-10

... precision requirements or power calculations that justify the proposed sample size, the expected response...: Proposed Collection; Comment Request; Generic Clearance for the Collection of Qualitative Feedback on... Information Collection Request (Generic ICR): ``Generic Clearance for the Collection of Qualitative Feedback...

Bayesian assurance and sample size determination in the process validation life-cycle.

PubMed

Faya, Paul; Seaman, John W; Stamey, James D

2017-01-01

Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key role in the assurance of drug quality, safety, and efficacy. The FDA guidance on process validation recommends a life-cycle approach which involves process design, qualification, and verification. The European Medicines Agency makes similar recommendations. The main purpose of process validation is to establish scientific evidence that a process is capable of consistently delivering a quality product. A major challenge faced by manufacturers is the determination of the number of batches to be used for the qualification stage. In this article, we present a Bayesian assurance and sample size determination approach where prior process knowledge and data are used to determine the number of batches. An example is presented in which potency uniformity data is evaluated using a process capability metric. By using the posterior predictive distribution, we simulate qualification data and make a decision on the number of batches required for a desired level of assurance.

Accounting for randomness in measurement and sampling in studying cancer cell population dynamics.

PubMed

Ghavami, Siavash; Wolkenhauer, Olaf; Lahouti, Farshad; Ullah, Mukhtar; Linnebacher, Michael

2014-10-01

Knowing the expected temporal evolution of the proportion of different cell types in sample tissues gives an indication about the progression of the disease and its possible response to drugs. Such systems have been modelled using Markov processes. We here consider an experimentally realistic scenario in which transition probabilities are estimated from noisy cell population size measurements. Using aggregated data of FACS measurements, we develop MMSE and ML estimators and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes. Our numerical results show that the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach for noisy measurements. This provides support for our argument that for the analysis of FACS data one should consider the observed state as a random variable. The second problem we address is about the consequences of estimating the probability of a cell being in a particular state from measurements of small population of cells. We show how the uncertainty arising from small sample sizes can be captured by a distribution for the state probability.

“Nanofiltration” Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples

NASA Astrophysics Data System (ADS)

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R.

2016-02-01

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation.

"Nanofiltration" Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples.

PubMed

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R

2016-02-15

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation.

“Nanofiltration” Enabled by Super-Absorbent Polymer Beads for Concentrating Microorganisms in Water Samples

PubMed Central

Xie, Xing; Bahnemann, Janina; Wang, Siwen; Yang, Yang; Hoffmann, Michael R.

2016-01-01

Detection and quantification of pathogens in water is critical for the protection of human health and for drinking water safety and security. When the pathogen concentrations are low, large sample volumes (several liters) are needed to achieve reliable quantitative results. However, most microbial identification methods utilize relatively small sample volumes. As a consequence, a concentration step is often required to detect pathogens in natural waters. Herein, we introduce a novel water sample concentration method based on superabsorbent polymer (SAP) beads. When SAP beads swell with water, small molecules can be sorbed within the beads, but larger particles are excluded and, thus, concentrated in the residual non-sorbed water. To illustrate this approach, millimeter-sized poly(acrylamide-co-itaconic acid) (P(AM-co-IA)) beads are synthesized and successfully applied to concentrate water samples containing two model microorganisms: Escherichia coli and bacteriophage MS2. Experimental results indicate that the size of the water channel within water swollen P(AM-co-IA) hydrogel beads is on the order of several nanometers. The millimeter size coupled with a negative surface charge of the beads are shown to be critical in order to achieve high levels of concentration. This new concentration procedure is very fast, effective, scalable, and low-cost with no need for complex instrumentation. PMID:26876979

On-chip collection of particles and cells by AC electroosmotic pumping and dielectrophoresis using asymmetric microelectrodes.

PubMed

Melvin, Elizabeth M; Moore, Brandon R; Gilchrist, Kristin H; Grego, Sonia; Velev, Orlin D

2011-09-01

The recent development of microfluidic "lab on a chip" devices requiring sample sizes <100 μL has given rise to the need to concentrate dilute samples and trap analytes, especially for surface-based detection techniques. We demonstrate a particle collection device capable of concentrating micron-sized particles in a predetermined area by combining AC electroosmosis (ACEO) and dielectrophoresis (DEP). The planar asymmetric electrode pattern uses ACEO pumping to induce equal, quadrilateral flow directed towards a stagnant region in the center of the device. A number of system parameters affecting particle collection efficiency were investigated including electrode and gap width, chamber height, applied potential and frequency, and number of repeating electrode pairs and electrode geometry. The robustness of the on-chip collection design was evaluated against varying electrolyte concentrations, particle types, and particle sizes. These devices are amenable to integration with a variety of detection techniques such as optical evanescent waveguide sensing.

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

PubMed

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

2018-05-10

Monitoring hydrophobic contaminants in surface freshwaters requires measuring contaminant concentrations in the particulate fraction (sediment or suspended particulate matter, SPM) of the water column. Particle traps (PTs) have been recently developed to sample SPM as cost-efficient, easy to operate and time-integrative tools. But the representativeness of SPM collected with PTs is not fully understood, notably in terms of grain size distribution and particulate organic carbon (POC) content, which could both skew particulate contaminant concentrations. The aim of this study was to evaluate the representativeness of SPM characteristics (i.e. grain size distribution and POC content) and associated contaminants (i.e. polychlorinated biphenyls, PCBs; mercury, Hg) in samples collected in a large river using PTs for differing hydrological conditions. Samples collected using PTs (n = 74) were compared with samples collected during the same time period by continuous flow centrifugation (CFC). The grain size distribution of PT samples shifted with increasing water discharge: the proportion of very fine silts (2-6 μm) decreased while that of coarse silts (27-74 μm) increased. Regardless of water discharge, POC contents were different likely due to integration by PT of high POC-content phytoplankton blooms or low POC-content flood events. Differences in PCBs and Hg concentrations were usually within the range of analytical uncertainties and could not be related to grain size or POC content shifts. Occasional Hg-enriched inputs may have led to higher Hg concentrations in a few PT samples (n = 4) which highlights the time-integrative capacity of the PTs. The differences of annual Hg and PCB fluxes calculated either from PT samples or CFC samples were generally below 20%. Despite some inherent limitations (e.g. grain size distribution bias), our findings suggest that PT sampling is a valuable technique to assess reliable spatial and temporal trends of particulate contaminants such as PCBs and Hg within a river monitoring network. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

Lang, Andreas

2004-01-01

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

Change-in-ratio methods for estimating population size

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.; McCullough, Dale R.; Barrett, Reginald H.

2002-01-01

Change-in-ratio (CIR) methods can provide an effective, low cost approach for estimating the size of wildlife populations. They rely on being able to observe changes in proportions of population subclasses that result from the removal of a known number of individuals from the population. These methods were first introduced in the 1940’s to estimate the size of populations with 2 subclasses under the assumption of equal subclass encounter probabilities. Over the next 40 years, closed population CIR models were developed to consider additional subclasses and use additional sampling periods. Models with assumptions about how encounter probabilities vary over time, rather than between subclasses, also received some attention. Recently, all of these CIR models have been shown to be special cases of a more general model. Under the general model, information from additional samples can be used to test assumptions about the encounter probabilities and to provide estimates of subclass sizes under relaxations of these assumptions. These developments have greatly extended the applicability of the methods. CIR methods are attractive because they do not require the marking of individuals, and subclass proportions often can be estimated with relatively simple sampling procedures. However, CIR methods require a carefully monitored removal of individuals from the population, and the estimates will be of poor quality unless the removals induce substantial changes in subclass proportions. In this paper, we review the state of the art for closed population estimation with CIR methods. Our emphasis is on the assumptions of CIR methods and on identifying situations where these methods are likely to be effective. We also identify some important areas for future CIR research.

Novel Insights in the Fecal Egg Count Reduction Test for Monitoring Drug Efficacy against Soil-Transmitted Helminths in Large-Scale Treatment Programs

PubMed Central

Levecke, Bruno; Speybroeck, Niko; Dobson, Robert J.; Vercruysse, Jozef; Charlier, Johannes

2011-01-01

Background The fecal egg count reduction test (FECRT) is recommended to monitor drug efficacy against soil-transmitted helminths (STHs) in public health. However, the impact of factors inherent to study design (sample size and detection limit of the fecal egg count (FEC) method) and host-parasite interactions (mean baseline FEC and aggregation of FEC across host population) on the reliability of FECRT is poorly understood. Methodology/Principal Findings A simulation study was performed in which FECRT was assessed under varying conditions of the aforementioned factors. Classification trees were built to explore critical values for these factors required to obtain conclusive FECRT results. The outcome of this analysis was subsequently validated on five efficacy trials across Africa, Asia, and Latin America. Unsatisfactory (<85.0%) sensitivity and specificity results to detect reduced efficacy were found if sample sizes were small (<10) or if sample sizes were moderate (10–49) combined with highly aggregated FEC (k<0.25). FECRT remained inconclusive under any evaluated condition for drug efficacies ranging from 87.5% to 92.5% for a reduced-efficacy-threshold of 90% and from 92.5% to 97.5% for a threshold of 95%. The most discriminatory study design required 200 subjects independent of STH status (including subjects who are not excreting eggs). For this sample size, the detection limit of the FEC method and the level of aggregation of the FEC did not affect the interpretation of the FECRT. Only for a threshold of 90%, mean baseline FEC <150 eggs per gram of stool led to a reduced discriminatory power. Conclusions/Significance This study confirms that the interpretation of FECRT is affected by a complex interplay of factors inherent to both study design and host-parasite interactions. The results also highlight that revision of the current World Health Organization guidelines to monitor drug efficacy is indicated. We, therefore, propose novel guidelines to support future monitoring programs. PMID:22180801

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

PubMed

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

2013-01-01

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

Size Matters: FTIR Spectral Analysis of Apollo Regolith Samples Exhibits Grain Size Dependence.

NASA Astrophysics Data System (ADS)

Martin, Dayl; Joy, Katherine; Pernet-Fisher, John; Wogelius, Roy; Morlok, Andreas; Hiesinger, Harald

2017-04-01

The Mercury Thermal Infrared Spectrometer (MERTIS) on the upcoming BepiColombo mission is designed to analyse the surface of Mercury in thermal infrared wavelengths (7-14 μm) to investigate the physical properties of the surface materials [1]. Laboratory analyses of analogue materials are useful for investigating how various sample properties alter the resulting infrared spectrum. Laboratory FTIR analysis of Apollo fine (<1mm) soil samples 14259,672, 15401,147, and 67481,96 have provided an insight into how grain size, composition, maturity (i.e., exposure to space weathering processes), and proportion of glassy material affect their average infrared spectra. Each of these samples was analysed as a bulk sample and five size fractions: <25, 25-63, 63-125, 125-250, and <250 μm. Sample 14259,672 is a highly mature highlands regolith with a large proportion of agglutinates [2]. The high agglutinate content (>60%) causes a 'flattening' of the spectrum, with reduced reflectance in the Reststrahlen Band region (RB) as much as 30% in comparison to samples that are dominated by a high proportion of crystalline material. Apollo 15401,147 is an immature regolith with a high proportion of volcanic glass pyroclastic beads [2]. The high mafic mineral content results in a systematic shift in the Christiansen Feature (CF - the point of lowest reflectance) to longer wavelength: 8.6 μm. The glass beads dominate the spectrum, displaying a broad peak around the main Si-O stretch band (at 10.8 μm). As such, individual mineral components of this sample cannot be resolved from the average spectrum alone. Apollo 67481,96 is a sub-mature regolith composed dominantly of anorthite plagioclase [2]. The CF position of the average spectrum is shifted to shorter wavelengths (8.2 μm) due to the higher proportion of felsic minerals. Its average spectrum is dominated by anorthite reflectance bands at 8.7, 9.1, 9.8, and 10.8 μm. The average reflectance is greater than the other samples due to a lower proportion of glassy material. In each soil, the smallest fractions (0-25 and 25-63 μm) have CF positions 0.1-0.4 μm higher than the larger grain sizes. Also, the bulk-sample spectra mostly closely resemble the 0-25 μm sieved size fraction spectrum, indicating that this size fraction of each sample dominates the bulk spectrum regardless of other physical properties. This has implications for surface analyses of other Solar System bodies where some mineral phases or components could be concentrated in a particular size fraction. For example, the anorthite grains in 67481,96 are dominantly >25 μm in size and therefore may not contribute proportionally to the bulk average spectrum (compared to the <25 μm fraction). The resulting bulk spectrum of 67481,96 has a CF position 0.2 μm higher than all size fractions >25 microns and therefore does not represent a true average composition of the sample. Further investigation of how grain size and composition alters the average spectrum is required to fully understand infrared spectra of planetary surfaces. [1] - Hiesinger H., Helbert J., and MERTIS Co-I Team. (2010). The Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) for the BepiColombo Mission. Planetary and Space Science. 58, 144-165. [2] - NASA Lunar Sample Compendium. https://curator.jsc.nasa.gov/lunar/lsc/

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2016-05-30

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

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

PubMed Central

Zeng, Yaohui; Singh, Sachinkumar; Wang, Kai

2017-01-01

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

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

PubMed

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

2013-12-01

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

Foreign body detection in food materials using compton scattered x-rays

NASA Astrophysics Data System (ADS)

McFarlane, Nigel James Bruce

This thesis investigated the application of X-ray Compton scattering to the problem of foreign body detection in food. The methods used were analytical modelling, simulation and experiment. A criterion was defined for detectability, and a model was developed for predicting the minimum time required for detection. The model was used to predict the smallest detectable cubes of air, glass, plastic and steel. Simulations and experiments were performed on voids and glass in polystyrene phantoms, water, coffee and muesli. Backscatter was used to detect bones in chicken meat. The effects of geometry and multiple scatter on contrast, signal-to-noise, and detection time were simulated. Compton scatter was compared with transmission, and the effect of inhomogeneity was modelled. Spectral shape was investigated as a means of foreign body detection. A signal-to-noise ratio of 7.4 was required for foreign body detection in food. A 0.46 cm cube of glass or a 1.19 cm cube of polystyrene were detectable in a 10 cm cube of water in one second. The minimum time to scan a whole sample varied as the 7th power of the foreign body size, and the 5th power of the sample size. Compton scatter inspection produced higher contrasts than transmission, but required longer measurement times because of the low number of photon counts. Compton scatter inspection of whole samples was very slow compared to production line speeds in the food industry. There was potential for Compton scatter in applications which did not require whole-sample scanning, such as surface inspection. There was also potential in the inspection of inhomogeneous samples. The multiple scatter fraction varied from 25% to 55% for 2 to 10 cm cubes of water, but did not have a large effect on the detection time. The spectral shape gave good contrasts and signal-to-noise ratios in the detection of chicken bones.

Sampling effort and estimates of species richness based on prepositioned area electrofisher samples

USGS Publications Warehouse

Bowen, Z.H.; Freeman, Mary C.

1998-01-01

Estimates of species richness based on electrofishing data are commonly used to describe the structure of fish communities. One electrofishing method for sampling riverine fishes that has become popular in the last decade is the prepositioned area electrofisher (PAE). We investigated the relationship between sampling effort and fish species richness at seven sites in the Tallapoosa River system, USA based on 1,400 PAE samples collected during 1994 and 1995. First, we estimated species richness at each site using the first-order jackknife and compared observed values for species richness and jackknife estimates of species richness to estimates based on historical collection data. Second, we used a permutation procedure and nonlinear regression to examine rates of species accumulation. Third, we used regression to predict the number of PAE samples required to collect the jackknife estimate of species richness at each site during 1994 and 1995. We found that jackknife estimates of species richness generally were less than or equal to estimates based on historical collection data. The relationship between PAE electrofishing effort and species richness in the Tallapoosa River was described by a positive asymptotic curve as found in other studies using different electrofishing gears in wadable streams. Results from nonlinear regression analyses indicted that rates of species accumulation were variable among sites and between years. Across sites and years, predictions of sampling effort required to collect jackknife estimates of species richness suggested that doubling sampling effort (to 200 PAEs) would typically increase observed species richness by not more than six species. However, sampling effort beyond about 60 PAE samples typically increased observed species richness by < 10%. We recommend using historical collection data in conjunction with a preliminary sample size of at least 70 PAE samples to evaluate estimates of species richness in medium-sized rivers. Seventy PAE samples should provide enough information to describe the relationship between sampling effort and species richness and thus facilitate evaluation of a sampling effort.

A New Model of Size-graded Soil Veneer on the Lunar Surface

NASA Technical Reports Server (NTRS)

Basu, Abhijit; McKay, David S.

2005-01-01

Introduction. We propose a new model of distribution of submillimeter sized lunar soil grains on the lunar surface. We propose that in the uppermost millimeter or two of the lunar surface, soil-grains are size graded with the finest nanoscale dust on top and larger micron-scale particles below. This standard state is perturbed by ejecta deposition of larger grains at the lunar surface, which have a coating of dusty layer that may not have substrates of intermediate sizes. Distribution of solar wind elements (SWE), agglutinates, vapor deposited nanophase Fe0 in size fractions of lunar soils and ir spectra of size fractions of lunar soils are compatible with this model. A direct test of this model requires bringing back glue-impregnated tubes of lunar soil samples to be dissected and examined on Earth.

A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data. M.S. Thesis - 21 Jul. 1983

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Moreira, M. A.

1983-01-01

Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.

Adequacy of laser diffraction for soil particle size analysis

PubMed Central

Fisher, Peter; Aumann, Colin; Chia, Kohleth; O'Halloran, Nick; Chandra, Subhash

2017-01-01

Sedimentation has been a standard methodology for particle size analysis since the early 1900s. In recent years laser diffraction is beginning to replace sedimentation as the prefered technique in some industries, such as marine sediment analysis. However, for the particle size analysis of soils, which have a diverse range of both particle size and shape, laser diffraction still requires evaluation of its reliability. In this study, the sedimentation based sieve plummet balance method and the laser diffraction method were used to measure the particle size distribution of 22 soil samples representing four contrasting Australian Soil Orders. Initially, a precise wet riffling methodology was developed capable of obtaining representative samples within the recommended obscuration range for laser diffraction. It was found that repeatable results were obtained even if measurements were made at the extreme ends of the manufacturer’s recommended obscuration range. Results from statistical analysis suggested that the use of sample pretreatment to remove soil organic carbon (and possible traces of calcium-carbonate content) made minor differences to the laser diffraction particle size distributions compared to no pretreatment. These differences were found to be marginally statistically significant in the Podosol topsoil and Vertosol subsoil. There are well known reasons why sedimentation methods may be considered to ‘overestimate’ plate-like clay particles, while laser diffraction will ‘underestimate’ the proportion of clay particles. In this study we used Lin’s concordance correlation coefficient to determine the equivalence of laser diffraction and sieve plummet balance results. The results suggested that the laser diffraction equivalent thresholds corresponding to the sieve plummet balance cumulative particle sizes of < 2 μm, < 20 μm, and < 200 μm, were < 9 μm, < 26 μm, < 275 μm respectively. The many advantages of laser diffraction for soil particle size analysis, and the empirical results of this study, suggest that deployment of laser diffraction as a standard test procedure can provide reliable results, provided consistent sample preparation is used. PMID:28472043

Ethics and Animal Numbers: Informal Analyses, Uncertain Sample Sizes, Inefficient Replications, and Type I Errors

PubMed Central

2011-01-01

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. PMID:21838970

A Review of ETS Differential Item Functioning Assessment Procedures: Flagging Rules, Minimum Sample Size Requirements, and Criterion Refinement. Research Report. ETS RR-12-08

ERIC Educational Resources Information Center

Zwick, Rebecca

2012-01-01

Differential item functioning (DIF) analysis is a key component in the evaluation of the fairness and validity of educational tests. The goal of this project was to review the status of ETS DIF analysis procedures, focusing on three aspects: (a) the nature and stringency of the statistical rules used to flag items, (b) the minimum sample size…

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Change-in-ratio estimators for populations with more than two subclasses

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.

1991-01-01

Change-in-ratio methods have been developed to estimate the size of populations with two or three population subclasses. Most of these methods require the often unreasonable assumption of equal sampling probabilities for individuals in all subclasses. This paper presents new models based on the weaker assumption that ratios of sampling probabilities are constant over time for populations with three or more subclasses. Estimation under these models requires that a value be assumed for one of these ratios when there are two samples. Explicit expressions are given for the maximum likelihood estimators under models for two samples with three or more subclasses and for three samples with two subclasses. A numerical method using readily available statistical software is described for obtaining the estimators and their standard errors under all of the models. Likelihood ratio tests that can be used in model selection are discussed. Emphasis is on the two-sample, three-subclass models for which Monte-Carlo simulation results and an illustrative example are presented.

Design considerations for case series models with exposure onset measurement error.

PubMed

Mohammed, Sandra M; Dalrymple, Lorien S; Sentürk, Damla; Nguyen, Danh V

2013-02-28

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely. In this work, we propose a method for power/sample size determination for the measurement error case series model. Extensive simulation studies are used to assess the accuracy of the proposed sample size formulas. We also examine the magnitude of the relative loss of power due to exposure onset measurement error, compared with the ideal situation where the time of exposure is measured precisely. To facilitate the design of case series studies, we provide publicly available web-based tools for determining power/sample size for both the measurement error case series model as well as the standard case series model. Copyright © 2012 John Wiley & Sons, Ltd.

Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

USGS Publications Warehouse

Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

2011-01-01

Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials.

PubMed

Mi, Michael Y; Betensky, Rebecca A

2013-04-01

Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample-size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo. Because the basic SPCD already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and whether we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones. Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample-size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power. From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample-size re-estimation, up to 25% power was recovered from underestimated sample-size scenarios. Given the numerous possible test parameters that could have been chosen for the simulations, the study's results are limited to situations described by the parameters that were used and may not generalize to all possible scenarios. Furthermore, dropout of patients is not considered in this study. It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments.

An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials

PubMed Central

Mi, Michael Y.; Betensky, Rebecca A.

2013-01-01

Background Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo. Purpose Because the basic SPCD design already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and if we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones. Methods Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power. Results From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample size re-estimation, up to 25% power was recovered from underestimated sample size scenarios. Limitations Given the numerous possible test parameters that could have been chosen for the simulations, the study’s results are limited to situations described by the parameters that were used, and may not generalize to all possible scenarios. Furthermore, drop-out of patients is not considered in this study. Conclusions It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments. PMID:23283576

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Heritabilities of measured and mid-infrared predicted milk fat globule size, milk fat and protein percentages, and their genetic correlations.

PubMed

Fleming, A; Schenkel, F S; Koeck, A; Malchiodi, F; Ali, R A; Corredig, M; Mallard, B; Sargolzaei, M; Miglior, F

2017-05-01

The objective of this study was to estimate the heritability of milk fat globule (MFG) size and mid-infrared (MIR) predicted MFG size in Holstein cattle. The genetic correlations between measured and predicted MFG size with milk fat and protein percentage were also investigated. Average MFG size was measured in 1,583 milk samples taken from 254 Holstein cows from 29 herds across Canada. Size was expressed as volume moment mean (D[4,3]) and surface moment mean (D[3,2]). Analyzed milk samples also had average MFG size predicted from their MIR spectral records. Fat and protein percentages were obtained for all test-day milk samples in the cow's lactation. Univariate and bivariate repeatability animal models were used to estimate heritability and genetic correlations. Moderate heritabilities of 0.364 and 0.466 were found for D[4,3] and D[3,2], respectively, and a strong genetic correlation was found between the 2 traits (0.98). The heritabilities for the MIR-predicted MFG size were lower than those estimated for the measured MFG size at 0.300 for predicted D[4,3] and 0.239 for predicted D[3,2]. The genetic correlation between measured and predicted D[4,3] was 0.685; the correlation was slightly higher between measured and predicted D[3,2] at 0.764, likely due to the better prediction accuracy of D[3,2]. Milk fat percentage had moderate genetic correlations with both D[4,3] and D[3,2] (0.538 and 0.681, respectively). The genetic correlation between predicted MFG size and fat percentage was much stronger (greater than 0.97 for both predicted D[4,3] and D[3,2]). The stronger correlation suggests a limitation for the use of the predicted values of MFG size as indicator traits for true average MFG size in milk in selection programs. Larger samples sizes are required to provide better evidence of the estimated genetic parameters. A genetic component appears to exist for the average MFG size in bovine milk, and the variation could be exploited in selection programs. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

NASA Astrophysics Data System (ADS)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for Heritability.

PubMed

Schweiger, Regev; Fisher, Eyal; Rahmani, Elior; Shenhav, Liat; Rosset, Saharon; Halperin, Eran

2018-06-22

Estimation of heritability is an important task in genetics. The use of linear mixed models (LMMs) to determine narrow-sense single-nucleotide polymorphism (SNP)-heritability and related quantities has received much recent attention, due of its ability to account for variants with small effect sizes. Typically, heritability estimation under LMMs uses the restricted maximum likelihood (REML) approach. The common way to report the uncertainty in REML estimation uses standard errors (SEs), which rely on asymptotic properties. However, these assumptions are often violated because of the bounded parameter space, statistical dependencies, and limited sample size, leading to biased estimates and inflated or deflated confidence intervals (CIs). In addition, for larger data sets (e.g., tens of thousands of individuals), the construction of SEs itself may require considerable time, as it requires expensive matrix inversions and multiplications. Here, we present FIESTA (Fast confidence IntErvals using STochastic Approximation), a method for constructing accurate CIs. FIESTA is based on parametric bootstrap sampling, and, therefore, avoids unjustified assumptions on the distribution of the heritability estimator. FIESTA uses stochastic approximation techniques, which accelerate the construction of CIs by several orders of magnitude, compared with previous approaches as well as to the analytical approximation used by SEs. FIESTA builds accurate CIs rapidly, for example, requiring only several seconds for data sets of tens of thousands of individuals, making FIESTA a very fast solution to the problem of building accurate CIs for heritability for all data set sizes.

Sample size, power calculations, and their implications for the cost of thorough studies of drug induced QT interval prolongation.

PubMed

Malik, Marek; Hnatkova, Katerina; Batchvarov, Velislav; Gang, Yi; Smetana, Peter; Camm, A John

2004-12-01

Regulatory authorities require new drugs to be investigated using a so-called "thorough QT/QTc study" to identify compounds with a potential of influencing cardiac repolarization in man. Presently drafted regulatory consensus requires these studies to be powered for the statistical detection of QTc interval changes as small as 5 ms. Since this translates into a noticeable drug development burden, strategies need to be identified allowing the size and thus the cost of thorough QT/QTc studies to be minimized. This study investigated the influence of QT and RR interval data quality and the precision of heart rate correction on the sample sizes of thorough QT/QTc studies. In 57 healthy subjects (26 women, age range 19-42 years), a total of 4,195 drug-free digital electrocardiograms (ECG) were obtained (65-84 ECGs per subject). All ECG parameters were measured manually using the most accurate approach with reconciliation of measurement differences between different cardiologists and aligning the measurements of corresponding ECG patterns. From the data derived in this measurement process, seven different levels of QT/RR data quality were obtained, ranging from the simplest approach of measuring 3 beats in one ECG lead to the most exact approach. Each of these QT/RR data-sets was processed with eight different heart rate corrections ranging from Bazett and Fridericia corrections to the individual QT/RR regression modelling with optimization of QT/RR curvature. For each combination of data quality and heart rate correction, standard deviation of individual mean QTc values and mean of individual standard deviations of QTc values were calculated and used to derive the size of thorough QT/QTc studies with an 80% power to detect 5 ms QTc changes at the significance level of 0.05. Irrespective of data quality and heart rate corrections, the necessary sample sizes of studies based on between-subject comparisons (e.g., parallel studies) are very substantial requiring >140 subjects per group. However, the required study size may be substantially reduced in investigations based on within-subject comparisons (e.g., crossover studies or studies of several parallel groups each crossing over an active treatment with placebo). While simple measurement approaches with ad-hoc heart rate correction still lead to requirements of >150 subjects, the combination of best data quality with most accurate individualized heart rate correction decreases the variability of QTc measurements in each individual very substantially. In the data of this study, the average of standard deviations of QTc values calculated separately in each individual was only 5.2 ms. Such a variability in QTc data translates to only 18 subjects per study group (e.g., the size of a complete one-group crossover study) to detect 5 ms QTc change with an 80% power. Cost calculations show that by involving the most stringent ECG handling and measurement, the cost of a thorough QT/QTc study may be reduced to approximately 25%-30% of the cost imposed by the simple ECG reading (e.g., three complexes in one lead only).

Sample size calculation for studies with grouped survival data.

PubMed

Li, Zhiguo; Wang, Xiaofei; Wu, Yuan; Owzar, Kouros

2018-06-10

Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples. Copyright © 2018 John Wiley & Sons, Ltd.

Embedding clinical interventions into observational studies.

PubMed

Newman, Anne B; Avilés-Santa, M Larissa; Anderson, Garnet; Heiss, Gerardo; Howard, Wm James; Krucoff, Mitchell; Kuller, Lewis H; Lewis, Cora E; Robinson, Jennifer G; Taylor, Herman; Treviño, Roberto P; Weintraub, William

2016-01-01

Novel approaches to observational studies and clinical trials could improve the cost-effectiveness and speed of translation of research. Hybrid designs that combine elements of clinical trials with observational registries or cohort studies should be considered as part of a long-term strategy to transform clinical trials and epidemiology, adapting to the opportunities of big data and the challenges of constrained budgets. Important considerations include study aims, timing, breadth and depth of the existing infrastructure that can be leveraged, participant burden, likely participation rate and available sample size in the cohort, required sample size for the trial, and investigator expertise. Community engagement and stakeholder (including study participants) support are essential for these efforts to succeed. Copyright © 2015. Published by Elsevier Inc.

Super-resolution imaging based on the temperature-dependent electron-phonon collision frequency effect of metal thin films

NASA Astrophysics Data System (ADS)

Ding, Chenliang; Wei, Jingsong; Xiao, Mufei

2018-05-01

We herein propose a far-field super-resolution imaging with metal thin films based on the temperature-dependent electron-phonon collision frequency effect. In the proposed method, neither fluorescence labeling nor any special properties are required for the samples. The 100 nm lands and 200 nm grooves on the Blu-ray disk substrates were clearly resolved and imaged through a laser scanning microscope of wavelength 405 nm. The spot size was approximately 0.80 μm , and the imaging resolution of 1/8 of the laser spot size was experimentally obtained. This work can be applied to the far-field super-resolution imaging of samples with neither fluorescence labeling nor any special properties.

ELIPGRID-PC: A PC program for calculating hot spot probabilities

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

Davidson, J.R.

1994-10-01

ELIPGRID-PC, a new personal computer program has been developed to provide easy access to Singer`s 1972 ELIPGRID algorithm for hot-spot detection probabilities. Three features of the program are the ability to determine: (1) the grid size required for specified conditions, (2) the smallest hot spot that can be sampled with a given probability, and (3) the approximate grid size resulting from specified conditions and sampling cost. ELIPGRID-PC also provides probability of hit versus cost data for graphing with spread-sheets or graphics software. The program has been successfully tested using Singer`s published ELIPGRID results. An apparent error in the original ELIPGRIDmore » code has been uncovered and an appropriate modification incorporated into the new program.« less

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

PubMed

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

Experimental Effects on IR Reflectance Spectra: Particle Size and Morphology

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

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

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

Evaluation of OMNIgene®•SPUTUM-stabilised sputum for long-term transport and Xpert® MTB/RIF testing in Nepal.

PubMed

Maharjan, B; Kelly-Cirino, C D; Weirich, A; Curry, P S; Hoffman, H; Avsar, K; Shrestha, B

2016-12-01

German Nepal TB Project, National Tuberculosis Reference Laboratory, Kathmandu, Nepal. To evaluate whether transporting samples in OMNIgene®•SPUTUM (OM-S) reagent from a peripheral collection site to a central laboratory in Nepal can improve tuberculosis (TB) detection and increase the sensitivity of Xpert® MTB/RIF testing. One hundred sputum samples were split manually. Each portion was assigned to the OM-S group (OM-S added at collection, airline-couriered without cold chain, no other processing required) or the standard-of-care (SOC) group (samples airline-couriered on ice, sodium hydroxide + N-acetyl-L-cysteine processing required at the laboratory). Smear microscopy and Xpert testing were performed. Transport time was 2-13 days. Overall smear results were comparable (respectively 58% and 56% smear-negative results in the OM-S and SOC groups). The rate of smear-positive, Mycobacterium tuberculosis-positive (MTB+) sample detection was identical for both treatment groups, at 95%. More smear-negative MTB+ samples were detected in the OM-S group (17% vs. 13%, P = 0.0655). Sputum samples treated with OM-S can undergo multiday ambient-temperature transport and yield comparable smear and Xpert results to those of SOC samples. Further investigation with larger sample sizes is required to assess whether treating sputum samples with OM-S could increase the sensitivity of Xpert testing in smear-negative samples.

Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter

PubMed Central

Huang, Lei

2015-01-01

To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409

Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty.

PubMed

Skaltsa, Konstantina; Jover, Lluís; Carrasco, Josep Lluís

2010-10-01

Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.

Ciguatoxic Potential of Brown-Marbled Grouper in Relation to Fish Size and Geographical Origin

PubMed Central

Chan, Thomas Y. K.

2015-01-01

To determine the ciguatoxic potential of brown-marbled grouper (Epinephelus fuscoguttatus) in relation to fish size and geographical origin, this review systematically analyzed: 1) reports of large ciguatera outbreaks and outbreaks with description of the fish size; 2) Pacific ciguatoxin (P-CTX) profiles and levels and mouse bioassay results in fish samples from ciguatera incidents; 3) P-CTX profiles and levels and risk of toxicity in relation to fish size and origin; 4) regulatory measures restricting fish trade and fish size preference of the consumers. P-CTX levels in flesh and size dependency of toxicity indicate that the risk of ciguatera after eating E. fuscoguttatus varies with its geographical origin. For a large-sized grouper, it is necessary to establish legal size limits and control measures to protect public health and prevent overfishing. More risk assessment studies are required for E. fuscoguttatus to determine the size threshold above which the risk of ciguatera significantly increases. PMID:26324735

Trial Sequential Analysis in systematic reviews with meta-analysis.

PubMed

Wetterslev, Jørn; Jakobsen, Janus Christian; Gluud, Christian

2017-03-06

Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors) and too many false negative conclusions (type II errors). We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D 2 ) measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in systematic reviews with traditional meta-analyses can be reduced using Trial Sequential Analysis. Several empirical studies have demonstrated that the Trial Sequential Analysis provides better control of type I errors and of type II errors than the traditional naïve meta-analysis. Trial Sequential Analysis represents analysis of meta-analytic data, with transparent assumptions, and better control of type I and type II errors than the traditional meta-analysis using naïve unadjusted confidence intervals.

The minimum area requirements (MAR) for giant panda: an empirical study

PubMed Central

Qing, Jing; Yang, Zhisong; He, Ke; Zhang, Zejun; Gu, Xiaodong; Yang, Xuyu; Zhang, Wen; Yang, Biao; Qi, Dunwu; Dai, Qiang

2016-01-01

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population’s long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km2 based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive. PMID:27929520

The minimum area requirements (MAR) for giant panda: an empirical study.

PubMed

Qing, Jing; Yang, Zhisong; He, Ke; Zhang, Zejun; Gu, Xiaodong; Yang, Xuyu; Zhang, Wen; Yang, Biao; Qi, Dunwu; Dai, Qiang

2016-12-08

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population's long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km 2 based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive.

Applying information theory to small groups assessment: emotions and well-being at work.

PubMed

García-Izquierdo, Antonio León; Moreno, Blanca; García-Izquierdo, Mariano

2010-05-01

This paper explores and analyzes the relations between emotions and well-being in a sample of aviation personnel, passenger crew (flight attendants). There is an increasing interest in studying the influence of emotions and its role as psychosocial factors in the work environment as they are able to act as facilitators or shock absorbers. The contrast of the theoretical models by using traditional parametric techniques requires a large sample size to the efficient estimation of the coefficients that quantify the relations between variables. Since the available sample that we have is small, the most common size in European enterprises, we used the maximum entropy principle to explore the emotions that are involved in the psychosocial risks. The analyses show that this method takes advantage of the limited information available and guarantee an optimal estimation, the results of which are coherent with theoretical models and numerous empirical researches about emotions and well-being.

Classification of urine sediment based on convolution neural network

NASA Astrophysics Data System (ADS)

Pan, Jingjing; Jiang, Cunbo; Zhu, Tiantian

2018-04-01

By designing a new convolution neural network framework, this paper breaks the constraints of the original convolution neural network framework requiring large training samples and samples of the same size. Move and cropping the input images, generate the same size of the sub-graph. And then, the generated sub-graph uses the method of dropout, increasing the diversity of samples and preventing the fitting generation. Randomly select some proper subset in the sub-graphic set and ensure that the number of elements in the proper subset is same and the proper subset is not the same. The proper subsets are used as input layers for the convolution neural network. Through the convolution layer, the pooling, the full connection layer and output layer, we can obtained the classification loss rate of test set and training set. In the red blood cells, white blood cells, calcium oxalate crystallization classification experiment, the classification accuracy rate of 97% or more.

Variable aperture-based ptychographical iterative engine method.

PubMed

Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-02-01

A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

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Unique technical innovations for short rotation woody crops research and development

Treesearch

Adam H. Wiese; Ronald S., Jr. Zalesny

2006-01-01

Often technology that is available to conduct short rotation woody crops (SRWC) research is too expensive, difficult to operate, cumbersome, and/or impractical for meeting sample size requirements. Thus, we have designed, constructed, and tested technical innovations that have allowed us to meet our specific experimental needs.

THE POWER TO DETECT A DIFFERENCE: DETERMINING SAMPLE SIZE REQUIREMENTS FOR EVALUATION OF REPRODUCTIVE/DEVELOPMENTAL EFFECTS FROM EXPOSURE TO COMPLEX MIXTURES OF DISINFECTION BYPRODUCTS

EPA Science Inventory

Toxicological assessment of environmentally-realistic complex mixtures of drinking-water disinfection byproducts (DBPs) are needed to address concerns raised by some epidemiological studies showing associations between exposure to chemically disinfected water and adverse reproduc...

Class Extraction and Classification Accuracy in Latent Class Models

ERIC Educational Resources Information Center

Wu, Qiong

2009-01-01

Despite the increasing popularity of latent class models (LCM) in educational research, methodological studies have not yet accumulated much information on the appropriate application of this modeling technique, especially with regard to requirement on sample size and number of indicators. This dissertation study represented an initial attempt to…

Quantifying viruses and bacteria in wastewater - results, quality control, and interpretation methods

USDA-ARS?s Scientific Manuscript database

Membrane bioreactors (MBR), used for wastewater treatment in Ohio and elsewhere in the United States, have pore sizes large enough to theoretically reduce concentrations of protozoa and bacteria, but not viruses. Sampling for viruses in wastewater is seldom done and not required. Instead, the bac...

High-concentration zeta potential measurements using light-scattering techniques

PubMed Central

Kaszuba, Michael; Corbett, Jason; Watson, Fraser Mcneil; Jones, Andrew

2010-01-01

Zeta potential is the key parameter that controls electrostatic interactions in particle dispersions. Laser Doppler electrophoresis is an accepted method for the measurement of particle electrophoretic mobility and hence zeta potential of dispersions of colloidal size materials. Traditionally, samples measured by this technique have to be optically transparent. Therefore, depending upon the size and optical properties of the particles, many samples will be too concentrated and will require dilution. The ability to measure samples at or close to their neat concentration would be desirable as it would minimize any changes in the zeta potential of the sample owing to dilution. However, the ability to measure turbid samples using light-scattering techniques presents a number of challenges. This paper discusses electrophoretic mobility measurements made on turbid samples at high concentration using a novel cell with reduced path length. Results are presented on two different sample types, titanium dioxide and a polyurethane dispersion, as a function of sample concentration. For both of the sample types studied, the electrophoretic mobility results show a gradual decrease as the sample concentration increases and the possible reasons for these observations are discussed. Further, a comparison of the data against theoretical models is presented and discussed. Conclusions and recommendations are made from the zeta potential values obtained at high concentrations. PMID:20732896

Brief communication: the relation between standard error of the estimate and sample size of histomorphometric aging methods.

PubMed

Hennig, Cheryl; Cooper, David

2011-08-01

Histomorphometric aging methods report varying degrees of precision, measured through Standard Error of the Estimate (SEE). These techniques have been developed from variable samples sizes (n) and the impact of n on reported aging precision has not been rigorously examined in the anthropological literature. This brief communication explores the relation between n and SEE through a review of the literature (abstracts, articles, book chapters, theses, and dissertations), predictions based upon sampling theory and a simulation. Published SEE values for age prediction, derived from 40 studies, range from 1.51 to 16.48 years (mean 8.63; sd: 3.81 years). In general, these values are widely distributed for smaller samples and the distribution narrows as n increases--a pattern expected from sampling theory. For the two studies that have samples in excess of 200 individuals, the SEE values are very similar (10.08 and 11.10 years) with a mean of 10.59 years. Assuming this mean value is a 'true' characterization of the error at the population level, the 95% confidence intervals for SEE values from samples of 10, 50, and 150 individuals are on the order of ± 4.2, 1.7, and 1.0 years, respectively. While numerous sources of variation potentially affect the precision of different methods, the impact of sample size cannot be overlooked. The uncertainty associated with SEE values derived from smaller samples complicates the comparison of approaches based upon different methodology and/or skeletal elements. Meaningful comparisons require larger samples than have frequently been used and should ideally be based upon standardized samples. Copyright © 2011 Wiley-Liss, Inc.

Sources of variability in collection and preparation of paint and lead-coating samples.

PubMed

Harper, S L; Gutknecht, W F

2001-06-01

Chronic exposure of children to lead (Pb) can result in permanent physiological impairment. Since surfaces coated with lead-containing paints and varnishes are potential sources of exposure, it is extremely important that reliable methods for sampling and analysis be available. The sources of variability in the collection and preparation of samples were investigated to improve the performance and comparability of methods and to ensure that data generated will be adequate for its intended use. Paint samples of varying sizes (areas and masses) were collected at different locations across a variety of surfaces including metal, plaster, concrete, and wood. A variety of grinding techniques were compared. Manual mortar and pestle grinding for at least 1.5 min and mechanized grinding techniques were found to generate similar homogenous particle size distributions required for aliquots as small as 0.10 g. When 342 samples were evaluated for sample weight loss during mortar and pestle grinding, 4% had 20% or greater loss with a high of 41%. Homogenization and sub-sampling steps were found to be the principal sources of variability related to the size of the sample collected. Analysis of samples from different locations on apparently identical surfaces were found to vary by more than a factor of two both in Pb concentration (mg cm-2 or %) and areal coating density (g cm-2). Analyses of substrates were performed to determine the Pb remaining after coating removal. Levels as high as 1% Pb were found in some substrate samples, corresponding to more than 35 mg cm-2 Pb. In conclusion, these sources of variability must be considered in development and/or application of any sampling and analysis methodologies.

The Impact of Accelerating Faster than Exponential Population Growth on Genetic Variation

PubMed Central

Reppell, Mark; Boehnke, Michael; Zöllner, Sebastian

2014-01-01

Current human sequencing projects observe an abundance of extremely rare genetic variation, suggesting recent acceleration of population growth. To better understand the impact of such accelerating growth on the quantity and nature of genetic variation, we present a new class of models capable of incorporating faster than exponential growth in a coalescent framework. Our work shows that such accelerated growth affects only the population size in the recent past and thus large samples are required to detect the models’ effects on patterns of variation. When we compare models with fixed initial growth rate, models with accelerating growth achieve very large current population sizes and large samples from these populations contain more variation than samples from populations with constant growth. This increase is driven almost entirely by an increase in singleton variation. Moreover, linkage disequilibrium decays faster in populations with accelerating growth. When we instead condition on current population size, models with accelerating growth result in less overall variation and slower linkage disequilibrium decay compared to models with exponential growth. We also find that pairwise linkage disequilibrium of very rare variants contains information about growth rates in the recent past. Finally, we demonstrate that models of accelerating growth may substantially change estimates of present-day effective population sizes and growth times. PMID:24381333

The impact of accelerating faster than exponential population growth on genetic variation.

PubMed

Reppell, Mark; Boehnke, Michael; Zöllner, Sebastian

2014-03-01

Current human sequencing projects observe an abundance of extremely rare genetic variation, suggesting recent acceleration of population growth. To better understand the impact of such accelerating growth on the quantity and nature of genetic variation, we present a new class of models capable of incorporating faster than exponential growth in a coalescent framework. Our work shows that such accelerated growth affects only the population size in the recent past and thus large samples are required to detect the models' effects on patterns of variation. When we compare models with fixed initial growth rate, models with accelerating growth achieve very large current population sizes and large samples from these populations contain more variation than samples from populations with constant growth. This increase is driven almost entirely by an increase in singleton variation. Moreover, linkage disequilibrium decays faster in populations with accelerating growth. When we instead condition on current population size, models with accelerating growth result in less overall variation and slower linkage disequilibrium decay compared to models with exponential growth. We also find that pairwise linkage disequilibrium of very rare variants contains information about growth rates in the recent past. Finally, we demonstrate that models of accelerating growth may substantially change estimates of present-day effective population sizes and growth times.

Extracting samples of high diversity from thematic collections of large gene banks using a genetic-distance based approach

PubMed Central

2010-01-01

Background Breeding programs are usually reluctant to evaluate and use germplasm accessions other than the elite materials belonging to their advanced populations. The concept of core collections has been proposed to facilitate the access of potential users to samples of small sizes, representative of the genetic variability contained within the gene pool of a specific crop. The eventual large size of a core collection perpetuates the problem it was originally proposed to solve. The present study suggests that, in addition to the classic core collection concept, thematic core collections should be also developed for a specific crop, composed of a limited number of accessions, with a manageable size. Results The thematic core collection obtained meets the minimum requirements for a core sample - maintenance of at least 80% of the allelic richness of the thematic collection, with, approximately, 15% of its size. The method was compared with other methodologies based on the M strategy, and also with a core collection generated by random sampling. Higher proportions of retained alleles (in a core collection of equal size) or similar proportions of retained alleles (in a core collection of smaller size) were detected in the two methods based on the M strategy compared to the proposed methodology. Core sub-collections constructed by different methods were compared regarding the increase or maintenance of phenotypic diversity. No change on phenotypic diversity was detected by measuring the trait "Weight of 100 Seeds", for the tested sampling methods. Effects on linkage disequilibrium between unlinked microsatellite loci, due to sampling, are discussed. Conclusions Building of a thematic core collection was here defined by prior selection of accessions which are diverse for the trait of interest, and then by pairwise genetic distances, estimated by DNA polymorphism analysis at molecular marker loci. The resulting thematic core collection potentially reflects the maximum allele richness with the smallest sample size from a larger thematic collection. As an example, we used the development of a thematic core collection for drought tolerance in rice. It is expected that such thematic collections increase the use of germplasm by breeding programs and facilitate the study of the traits under consideration. The definition of a core collection to study drought resistance is a valuable contribution towards the understanding of the genetic control and the physiological mechanisms involved in water use efficiency in plants. PMID:20576152

Cost-efficient designs for three-arm trials with treatment delivered by health professionals: Sample sizes for a combination of nested and crossed designs

PubMed Central

Moerbeek, Mirjam

2018-01-01

Background This article studies the design of trials that compare three treatment conditions that are delivered by two types of health professionals. The one type of health professional delivers one treatment, and the other type delivers two treatments, hence, this design is a combination of a nested and crossed design. As each health professional treats multiple patients, the data have a nested structure. This nested structure has thus far been ignored in the design of such trials, which may result in an underestimate of the required sample size. In the design stage, the sample sizes should be determined such that a desired power is achieved for each of the three pairwise comparisons, while keeping costs or sample size at a minimum. Methods The statistical model that relates outcome to treatment condition and explicitly takes the nested data structure into account is presented. Mathematical expressions that relate sample size to power are derived for each of the three pairwise comparisons on the basis of this model. The cost-efficient design achieves sufficient power for each pairwise comparison at lowest costs. Alternatively, one may minimize the total number of patients. The sample sizes are found numerically and an Internet application is available for this purpose. The design is also compared to a nested design in which each health professional delivers just one treatment. Results Mathematical expressions show that this design is more efficient than the nested design. For each pairwise comparison, power increases with the number of health professionals and the number of patients per health professional. The methodology of finding a cost-efficient design is illustrated using a trial that compares treatments for social phobia. The optimal sample sizes reflect the costs for training and supervising psychologists and psychiatrists, and the patient-level costs in the three treatment conditions. Conclusion This article provides the methodology for designing trials that compare three treatment conditions while taking the nesting of patients within health professionals into account. As such, it helps to avoid underpowered trials. To use the methodology, a priori estimates of the total outcome variances and intraclass correlation coefficients must be obtained from experts’ opinions or findings in the literature. PMID:29316807

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

PubMed

Bergh, Daniel

2015-01-01

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

Securing quality of camera-based biomedical optics

NASA Astrophysics Data System (ADS)

Guse, Frank; Kasper, Axel; Zinter, Bob

2009-02-01

As sophisticated optical imaging technologies move into clinical applications, manufacturers need to guarantee their products meet required performance criteria over long lifetimes and in very different environmental conditions. A consistent quality management marks critical components features derived from end-users requirements in a top-down approach. Careful risk analysis in the design phase defines the sample sizes for production tests, whereas first article inspection assures the reliability of the production processes. We demonstrate the application of these basic quality principles to camera-based biomedical optics for a variety of examples including molecular diagnostics, dental imaging, ophthalmology and digital radiography, covering a wide range of CCD/CMOS chip sizes and resolutions. Novel concepts in fluorescence detection and structured illumination are also highlighted.

Fixed-Precision Sequential Sampling Plans for Estimating Alfalfa Caterpillar, Colias lesbia, Egg Density in Alfalfa, Medicago sativa, Fields in Córdoba, Argentina

PubMed Central

Serra, Gerardo V.; Porta, Norma C. La; Avalos, Susana; Mazzuferi, Vilma

2013-01-01

The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies. PMID:23909840

Interval estimation and optimal design for the within-subject coefficient of variation for continuous and binary variables

PubMed Central

Shoukri, Mohamed M; Elkum, Nasser; Walter, Stephen D

2006-01-01

Background In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements for the within-subject coefficient of variation for continuous and binary variables. Methods We investigate the validity of the approximate normal confidence interval by Monte Carlo simulations. In designing a reliability study, a crucial issue is the balance between the number of subjects to be recruited and the number of repeated measurements per subject. We discuss efficiency of estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated by an example on Magnetic Resonance Imaging (MRI). We also discuss the issue of sample size estimation for dichotomous responses with two examples. Results For the continuous variable we found that the variance stabilizing transformation improves the asymptotic coverage probabilities on the within-subject coefficient of variation for the continuous variable. The maximum like estimation and sample size estimation based on pre-specified width of confidence interval are novel contribution to the literature for the binary variable. Conclusion Using the sample size formulas, we hope to help clinical epidemiologists and practicing statisticians to efficiently design reliability studies using the within-subject coefficient of variation, whether the variable of interest is continuous or binary. PMID:16686943

THE CHALLENGE OF DETECTING CLASSICAL SWINE FEVER VIRUS CIRCULATION IN WILD BOAR (SUS SCROFA): SIMULATION OF SAMPLING OPTIONS.

PubMed

Sonnenburg, Jana; Schulz, Katja; Blome, Sandra; Staubach, Christoph

2016-10-01

Classical swine fever (CSF) is one of the most important viral diseases of domestic pigs ( Sus scrofa domesticus) and wild boar ( Sus scrofa ). For at least 4 decades, several European Union member states were confronted with outbreaks among wild boar and, as it had been shown that infected wild boar populations can be a major cause of primary outbreaks in domestic pigs, strict control measures for both species were implemented. To guarantee early detection and to demonstrate freedom from disease, intensive surveillance is carried out based on a hunting bag sample. In this context, virologic investigations play a major role in the early detection of new introductions and in regions immunized with a conventional vaccine. The required financial resources and personnel for reliable testing are often large, and sufficient sample sizes to detect low virus prevalences are difficult to obtain. We conducted a simulation to model the possible impact of changes in sample size and sampling intervals on the probability of CSF virus detection based on a study area of 65 German hunting grounds. A 5-yr period with 4,652 virologic investigations was considered. Results suggest that low prevalences could not be detected with a justifiable effort. The simulation of increased sample sizes per sampling interval showed only a slightly better performance but would be unrealistic in practice, especially outside the main hunting season. Further studies on other approaches such as targeted or risk-based sampling for virus detection in connection with (marker) antibody surveillance are needed.

Sensor Technologies for Particulate Detection and Characterization

NASA Technical Reports Server (NTRS)

Greenberg, Paul S.

2008-01-01

Planned Lunar missions have resulted in renewed attention to problems attributable to fine particulates. While the difficulties experienced during the sequence of Apollo missions did not prove critical in all cases, the comparatively long duration of impending missions may present a different situation. This situation creates the need for a spectrum of particulate sensing technologies. From a fundamental perspective, an improved understanding of the properties of the dust fraction is required. Described here is laboratory-based reference instrumentation for the measurement of fundamental particle size distribution (PSD) functions from 2.5 nanometers to 20 micrometers. Concomitant efforts for separating samples into fractional size bins are also presented. A requirement also exists for developing mission compatible sensors. Examples include provisions for air quality monitoring in spacecraft and remote habitation modules. Required sensor attributes such as low mass, volume, and power consumption, autonomy of operation, and extended reliability cannot be accommodated by existing technologies.

Inactivation of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice by pulsed light. Influence of initial contamination and required reduction levels.

PubMed

Ferrario, Mariana I; Guerrero, Sandra N

The purpose of this study was to analyze the response of different initial contamination levels of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice as affected by pulsed light treatment (PL, batch mode, xenon lamp, 3pulses/s, 0-71.6J/cm 2 ). Biphasic and Weibull frequency distribution models were used to characterize the relationship between inoculum size and treatment time with the reductions achieved after PL exposure. Additionally, a second order polynomial model was computed to relate required PL processing time to inoculum size and requested log reductions. PL treatment caused up to 3.0-3.5 log reductions, depending on the initial inoculum size. Inactivation curves corresponding to PL-treated samples were adequately characterized by both Weibull and biphasic models (R adj 2 94-96%), and revealed that lower initial inoculum sizes were associated with higher inactivation rates. According to the polynomial model, the predicted time for PL treatment increased exponentially with inoculum size. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

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

USGS Publications Warehouse

Arthur, Steve M.; Schwartz, Charles C.

1999-01-01

We equipped 9 brown bears (Ursus arctos) on the Kenai Peninsula, Alaska, with collars containing both conventional very-high-frequency (VHF) transmitters and global positioning system (GPS) receivers programmed to determine an animal's position at 5.75-hr intervals. We calculated minimum convex polygon (MCP) and fixed and adaptive kernel home ranges for randomly-selected subsets of the GPS data to examine the effects of sample size on accuracy and precision of home range estimates. We also compared results obtained by weekly aerial radiotracking versus more frequent GPS locations to test for biases in conventional radiotracking data. Home ranges based on the MCP were 20-606 km2 (x = 201) for aerial radiotracking data (n = 12-16 locations/bear) and 116-1,505 km2 (x = 522) for the complete GPS data sets (n = 245-466 locations/bear). Fixed kernel home ranges were 34-955 km2 (x = 224) for radiotracking data and 16-130 km2 (x = 60) for the GPS data. Differences between means for radiotracking and GPS data were due primarily to the larger samples provided by the GPS data. Means did not differ between radiotracking data and equivalent-sized subsets of GPS data (P > 0.10). For the MCP, home range area increased and variability decreased asymptotically with number of locations. For the kernel models, both area and variability decreased with increasing sample size. Simulations suggested that the MCP and kernel models required >60 and >80 locations, respectively, for estimates to be both accurate (change in area <1%/additional location) and precise (CV < 50%). Although the radiotracking data appeared unbiased, except for the relationship between area and sample size, these data failed to indicate some areas that likely were important to bears. Our results suggest that the usefulness of conventional radiotracking data may be limited by potential biases and variability due to small samples. Investigators that use home range estimates in statistical tests should consider the effects of variability of those estimates. Use of GPS-equipped collars can facilitate obtaining larger samples of unbiased data and improve accuracy and precision of home range estimates.

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

NASA Astrophysics Data System (ADS)

Lowery, C.; Fraass, A. J.

2016-02-01

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

New Measurements of the Particle Size Distribution of Apollo 11 Lunar Soil 10084

NASA Technical Reports Server (NTRS)

McKay, D.S.; Cooper, B.L.; Riofrio, L.M.

2009-01-01

We have initiated a major new program to determine the grain size distribution of nearly all lunar soils collected in the Apollo program. Following the return of Apollo soil and core samples, a number of investigators including our own group performed grain size distribution studies and published the results [1-11]. Nearly all of these studies were done by sieving the samples, usually with a working fluid such as Freon(TradeMark) or water. We have measured the particle size distribution of lunar soil 10084,2005 in water, using a Microtrac(TradeMark) laser diffraction instrument. Details of our own sieving technique and protocol (also used in [11]). are given in [4]. While sieving usually produces accurate and reproducible results, it has disadvantages. It is very labor intensive and requires hours to days to perform properly. Even using automated sieve shaking devices, four or five days may be needed to sieve each sample, although multiple sieve stacks increases productivity. Second, sieving is subject to loss of grains through handling and weighing operations, and these losses are concentrated in the finest grain sizes. Loss from handling becomes a more acute problem when smaller amounts of material are used. While we were able to quantitatively sieve into 6 or 8 size fractions using starting soil masses as low as 50mg, attrition and handling problems limit the practicality of sieving smaller amounts. Third, sieving below 10 or 20microns is not practical because of the problems of grain loss, and smaller grains sticking to coarser grains. Sieving is completely impractical below about 5- 10microns. Consequently, sieving gives no information on the size distribution below approx.10 microns which includes the important submicrometer and nanoparticle size ranges. Finally, sieving creates a limited number of size bins and may therefore miss fine structure of the distribution which would be revealed by other methods that produce many smaller size bins.

Study design options in evaluating gene-environment interactions: practical considerations for a planned case-control study of pediatric leukemia.

PubMed

Goodman, Michael; Dana Flanders, W

2007-04-01

We compare methodological approaches for evaluating gene-environment interaction using a planned study of pediatric leukemia as a practical example. We considered three design options: a full case-control study (Option I), a case-only study (Option II), and a partial case-control study (Option III), in which information on controls is limited to environmental exposure only. For each design option we determined its ability to measure the main effects of environmental factor E and genetic factor G, and the interaction between E and G. Using the leukemia study example, we calculated sample sizes required to detect and odds ratio (OR) of 2.0 for E alone, an OR of 10 for G alone and an interaction G x E of 3. Option I allows measuring both main effects and interaction, but requires a total sample size of 1,500 cases and 1,500 controls. Option II allows measuring only interaction, but requires just 121 cases. Option III allows calculating the main effect of E, and interaction, but not the main effect of G, and requires a total of 156 cases and 133 controls. In this case, the partial case-control study (Option III) appears to be more efficient with respect to its ability to answer the research questions for the amount of resources required. The design options considered in this example are not limited to observational epidemiology and may be applicable in studies of pharmacogenomics, survivorship, and other areas of pediatric ALL research.

Progress in Developing Transfer Functions for Surface Scanning Eddy Current Inspections

NASA Astrophysics Data System (ADS)

Shearer, J.; Heebl, J.; Brausch, J.; Lindgren, E.

2009-03-01

As US Air Force (USAF) aircraft continue to age, additional inspections are required for structural components. The validation of new inspections typically requires a capability demonstration of the method using representative structure with representative damage. To minimize the time and cost required to prepare such samples, Electric Discharge machined (EDM) notches are commonly used to represent fatigue cracks in validation studies. However, the sensitivity to damage typically changes as a function of damage type. This requires a mathematical relationship to be developed between the responses from the two different flaw types to enable the use of EDM notched samples to validate new inspections. This paper reviews progress to develop transfer functions for surface scanning eddy current inspections of aluminum and titanium alloys found in structural aircraft components. Multiple samples with well characterized grown fatigue cracks and master gages with EDM notches, both with a range of flaw sizes, were used to collect flaw signals with USAF field inspection equipment. Analysis of this empirical data was used to develop a transfer function between the response from the EDM notches and grown fatigue cracks.

Time multiplexing super-resolution nanoscopy based on the Brownian motion of gold nanoparticles

NASA Astrophysics Data System (ADS)

Ilovitsh, Tali; Ilovitsh, Asaf; Wagner, Omer; Zalevsky, Zeev

2017-02-01

Super-resolution localization microscopy can overcome the diffraction limit and achieve a tens of order improvement in resolution. It requires labeling the sample with fluorescent probes followed with their repeated cycles of activation and photobleaching. This work presents an alternative approach that is free from direct labeling and does not require the activation and photobleaching cycles. Fluorescently labeled gold nanoparticles in a solution are distributed on top of the sample. The nanoparticles move in a random Brownian motion, and interact with the sample. By obscuring different areas in the sample, the nanoparticles encode the sub-wavelength features. A sequence of images of the sample is captured and decoded by digital post processing to create the super-resolution image. The achievable resolution is limited by the additive noise and the size of the nanoparticles. Regular nanoparticles with diameter smaller than 100nm are barely seen in a conventional bright field microscope, thus fluorescently labeled gold nanoparticles were used, with proper

Transparency and oversight in local wellness policies.

PubMed

Chriqui, Jamie F; Chaloupka, Frank J

2011-02-01

Advocates have called for increased wellness policy transparency and oversight through the use of health advisory councils. This study examines (1) wellness policy transparency, (2) advisory council requirements, (3) factors associated with each, and (4) whether transparency or advisory council requirements are indicative of a stronger policy addressing nutrition and physical activity. Policies for school year 2007-2008 were obtained from a nationally representative sample of 641 districts and analyzed for their applicability to elementary, middle, and high school levels. Main outcome measures included (1) policy transparency (online availability), (2) advisory council requirements, and (3) overall policy strength. T-tests assessed variability in policy strength by transparency and advisory council requirements. Multivariate logistic and linear regression analyses controlled for district size, socioeconomic status, race/ethnicity, region, and locale; models of advisory council/policy strength relationships also controlled for state advisory council requirements. More than 41% of districts posted wellness policies online and more than 43% required advisory councils. Transparency was less likely in small-/medium-sized and non-southern districts; and, for elementary school policies, most common in majority Hispanic districts. Advisory council requirements were less likely in small-/medium-sized districts for middle/high school policies and more likely in majority Hispanic districts for elementary school policies. After adjusting for all covariates, transparency was not associated with policy strength, but advisory council requirements significantly predicted policy strength. Transparency may facilitate awareness, but it does not mean that wellness policies will be stronger; however, advisory council requirements may be a marker for stronger policies. © 2011, American School Health Association.

SIproc: an open-source biomedical data processing platform for large hyperspectral images.

PubMed

Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

2017-04-10

There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

Population size and stopover duration estimation using mark–resight data and Bayesian analysis of a superpopulation model

USGS Publications Warehouse

Lyons, James E.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Andres, Brad A.; Buchanan, Joseph B.

2016-01-01

We present a novel formulation of a mark–recapture–resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state–space formulation of the Jolly–Seber mark–recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state–space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.

Methane Leaks from Natural Gas Systems Follow Extreme Distributions.

PubMed

Brandt, Adam R; Heath, Garvin A; Cooley, Daniel

2016-11-15

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH 4 ) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ∼15 000 measurements from 18 prior studies, we show that all available natural gas leakage data sets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of the total leakage volume. While prior studies used log-normal model distributions, we show that log-normal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH 4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of data sets to increase sample size is not recommended due to apparent deviation between sampled populations. Understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.

Effect of Reheating Temperature and Cooling Treatment on the Microstructure, Texture, and Impact Transition Behavior of Heat-Treated Naval Grade HSLA Steel

NASA Astrophysics Data System (ADS)

Sk, Md. Basiruddin; Ghosh, A.; Rarhi, N.; Balamuralikrishnan, R.; Chakrabarti, D.

2017-07-01

In order to achieve the desired mechanical properties [YS > 390 MPa, total elongation >16 pct and Charpy impact toughness of 78 J at 213 K (-60 °C)] for naval application, samples from a low-carbon microalloyed steel have been subjected to different austenitization (1223 K to 1523 K) (950 °C to 1250 °C) and cooling treatments (furnace, air, or water cooling). The as-rolled steel and the sample air cooled from 1223 K (950 °C) could only achieve the required tensile properties, while the sample furnace cooled from 1223 K (950 °C) showed the best Charpy impact properties. Water quenching from 1223 K (950 °C) certainly contributed to the strength but affected the impact toughness. Overall, predominantly ferrite matrix with fine effective grain size and intense gamma-fiber texture was found to be beneficial for impact toughness as well as impact transition behavior. Small size and fraction of precipitates (like TiN, Nb, and V carbonitrides) eliminated the possibility of particle-controlled crack propagation and grain size-controlled crack propagation led to cleavage fracture. A simplified analytical approach has been used to explain the difference in impact transition behavior of the investigated samples.

Methane Leaks from Natural Gas Systems Follow Extreme Distributions

DOE PAGES

Brandt, Adam R.; Heath, Garvin A.; Cooley, Daniel

2016-10-14

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH 4) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ~15,000 measurements from 18 prior studies, we show that all available natural gas leakage datasets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of themore » total leakage volume. While prior studies used lognormal model distributions, we show that lognormal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH 4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of datasets to increase sample size is not recommended due to apparent deviation between sampled populations. Finally, understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.« less

Methane Leaks from Natural Gas Systems Follow Extreme Distributions

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

Brandt, Adam R.; Heath, Garvin A.; Cooley, Daniel

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH 4) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ~15,000 measurements from 18 prior studies, we show that all available natural gas leakage datasets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of themore » total leakage volume. While prior studies used lognormal model distributions, we show that lognormal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH 4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of datasets to increase sample size is not recommended due to apparent deviation between sampled populations. Finally, understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.« less

Sampling benthic macroinvertebrates in a large flood-plain river: Considerations of study design, sample size, and cost

USGS Publications Warehouse

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 required to sample benthic macroinvertebrates during our sampling period depended on the study objective and ranged from 18 to more than 40 sites per stratum. No single sampling regime would efficiently and adequately sample all components of the macroinvertebrate community.

The effects of sample scheduling and sample numbers on estimates of the annual fluxes of suspended sediment in fluvial systems

USGS Publications Warehouse

Horowitz, Arthur J.; Clarke, Robin T.; Merten, Gustavo Henrique

2015-01-01

Since the 1970s, there has been both continuing and growing interest in developing accurate estimates of the annual fluvial transport (fluxes and loads) of suspended sediment and sediment-associated chemical constituents. This study provides an evaluation of the effects of manual sample numbers (from 4 to 12 year−1) and sample scheduling (random-based, calendar-based and hydrology-based) on the precision, bias and accuracy of annual suspended sediment flux estimates. The evaluation is based on data from selected US Geological Survey daily suspended sediment stations in the USA and covers basins ranging in area from just over 900 km2 to nearly 2 million km2 and annual suspended sediment fluxes ranging from about 4 Kt year−1 to about 200 Mt year−1. The results appear to indicate that there is a scale effect for random-based and calendar-based sampling schemes, with larger sample numbers required as basin size decreases. All the sampling schemes evaluated display some level of positive (overestimates) or negative (underestimates) bias. The study further indicates that hydrology-based sampling schemes are likely to generate the most accurate annual suspended sediment flux estimates with the fewest number of samples, regardless of basin size. This type of scheme seems most appropriate when the determination of suspended sediment concentrations, sediment-associated chemical concentrations, annual suspended sediment and annual suspended sediment-associated chemical fluxes only represent a few of the parameters of interest in multidisciplinary, multiparameter monitoring programmes. The results are just as applicable to the calibration of autosamplers/suspended sediment surrogates currently used to measure/estimate suspended sediment concentrations and ultimately, annual suspended sediment fluxes, because manual samples are required to adjust the sample data/measurements generated by these techniques so that they provide depth-integrated and cross-sectionally representative data. 

Alternative sample sizes for verification dose experiments and dose audits

NASA Astrophysics Data System (ADS)

Taylor, W. A.; Hansen, J. M.

1999-01-01

ISO 11137 (1995), "Sterilization of Health Care Products—Requirements for Validation and Routine Control—Radiation Sterilization", provides sampling plans for performing initial verification dose experiments and quarterly dose audits. Alternative sampling plans are presented which provide equivalent protection. These sampling plans can significantly reduce the cost of testing. These alternative sampling plans have been included in a draft ISO Technical Report (type 2). This paper examines the rational behind the proposed alternative sampling plans. The protection provided by the current verification and audit sampling plans is first examined. Then methods for identifying equivalent plans are highlighted. Finally, methods for comparing the cost associated with the different plans are provided. This paper includes additional guidance for selecting between the original and alternative sampling plans not included in the technical report.

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

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

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested withmore » real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.« less

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

PubMed

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

2017-06-01

A systematic review of nonspecific low back pain trials published between 1980 and 2012. To explore what proportion of trials have been powered to detect different bands of effect size; whether there is evidence that sample size in low back pain trials has been increasing; what proportion of trial reports include a sample size calculation; and whether likelihood of reporting sample size calculations has increased. Clinical trials should have a sample size sufficient to detect a minimally important difference for a given power and type I error rate. An underpowered trial is one within which probability of type II error is too high. Meta-analyses do not mitigate underpowered trials. Reviewers independently abstracted data on sample size at point of analysis, whether a sample size calculation was reported, and year of publication. Descriptive analyses were used to explore ability to detect effect sizes, and regression analyses to explore the relationship between sample size, or reporting sample size calculations, and time. We included 383 trials. One-third were powered to detect a standardized mean difference of less than 0.5, and 5% were powered to detect less than 0.3. The average sample size was 153 people, which increased only slightly (∼4 people/yr) from 1980 to 2000, and declined slightly (∼4.5 people/yr) from 2005 to 2011 (P < 0.00005). Sample size calculations were reported in 41% of trials. The odds of reporting a sample size calculation (compared to not reporting one) increased until 2005 and then declined (Equation is included in full-text article.). Sample sizes in back pain trials and the reporting of sample size calculations may need to be increased. It may be justifiable to power a trial to detect only large effects in the case of novel interventions. 3.

Geostatistics and the representative elementary volume of gamma ray tomography attenuation in rocks cores

USGS Publications Warehouse

Vogel, J.R.; Brown, G.O.

2003-01-01

Semivariograms of samples of Culebra Dolomite have been determined at two different resolutions for gamma ray computed tomography images. By fitting models to semivariograms, small-scale and large-scale correlation lengths are determined for four samples. Different semivariogram parameters were found for adjacent cores at both resolutions. Relative elementary volume (REV) concepts are related to the stationarity of the sample. A scale disparity factor is defined and is used to determine sample size required for ergodic stationarity with a specified correlation length. This allows for comparison of geostatistical measures and representative elementary volumes. The modifiable areal unit problem is also addressed and used to determine resolution effects on correlation lengths. By changing resolution, a range of correlation lengths can be determined for the same sample. Comparison of voxel volume to the best-fit model correlation length of a single sample at different resolutions reveals a linear scaling effect. Using this relationship, the range of the point value semivariogram is determined. This is the range approached as the voxel size goes to zero. Finally, these results are compared to the regularization theory of point variables for borehole cores and are found to be a better fit for predicting the volume-averaged range.

Direct Analysis of Low-Volatile Molecular Marker Extract from Airborne Particulate Matter Using Sensitivity Correction Method

PubMed Central

Irei, Satoshi

2016-01-01

Molecular marker analysis of environmental samples often requires time consuming preseparation steps. Here, analysis of low-volatile nonpolar molecular markers (5-6 ring polycyclic aromatic hydrocarbons or PAHs, hopanoids, and n-alkanes) without the preseparation procedure is presented. Analysis of artificial sample extracts was directly conducted by gas chromatography-mass spectrometry (GC-MS). After every sample injection, a standard mixture was also analyzed to make a correction on the variation of instrumental sensitivity caused by the unfavorable matrix contained in the extract. The method was further validated for the PAHs using the NIST standard reference materials (SRMs) and then applied to airborne particulate matter samples. Tests with the SRMs showed that overall our methodology was validated with the uncertainty of ~30%. The measurement results of airborne particulate matter (PM) filter samples showed a strong correlation between the PAHs, implying the contributions from the same emission source. Analysis of size-segregated PM filter samples showed that their size distributions were found to be in the PM smaller than 0.4 μm aerodynamic diameter. The observations were consistent with our expectation of their possible sources. Thus, the method was found to be useful for molecular marker studies. PMID:27127511

25 CFR 226.32 - Well records and reports.

Code of Federal Regulations, 2010 CFR

2010-04-01

... LANDS FOR OIL AND GAS MINING Requirements of Lessees § 226.32 Well records and reports. (a) Lessee shall... and character of oil, gas, or water in each formation, and the kind, weight, size, landed depth and... pressure or fluid sample surveys, temperature surveys, directional surveys, and the like; the materials and...

76 FR 31575 - United States Standards for Grades of Frozen Onions

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-01

... processors of frozen onions in the United States. The petition provided information on style, sample size... change in the style designations for minced style, and a correction to the text. The members agreed with the proposed section concerning requirements for Styles, Type I, Whole onions and Type II, Pearl...

Cinematic Creativity and Production Budgets: Does Money Make the Movie?

ERIC Educational Resources Information Center

Simonton, Dean Keith

2005-01-01

Although filmmaking requires substantial capital investment, it is not known whether cinematic creativity is positively correlated with the size of the film's budget. Therefore, budgetary impact was investigated in a sample of feature films released between 1997 and 2001. Although production costs were positively related to box office success (as…

Minimum Sample Size Requirements for Mokken Scale Analysis

ERIC Educational Resources Information Center

Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

The Power of the Test for Treatment Effects in Three-Level Block Randomized Designs

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2008-01-01

Experiments that involve nested structures may assign treatment conditions either to subgroups (such as classrooms) or individuals within subgroups (such as students). The design of such experiments requires knowledge of the intraclass correlation structure to compute the sample sizes necessary to achieve adequate power to detect the treatment…

Characterizing dispersal patterns in a threatened seabird with limited genetic structure

Treesearch

Laurie A. Hall; Per J. Palsboll; Steven R. Beissinger; James T. Harvey; Martine Berube; Martin G. Raphael; Kim Nelson; Richard T. Golightly; Laura McFarlane-Tranquilla; Scott H. Newman; M. Zachariah Peery

2009-01-01

Genetic assignment methods provide an appealing approach for characterizing dispersal patterns on ecological time scales, but require sufficient genetic differentiation to accurately identify migrants and a large enough sample size of migrants to, for example, compare dispersal between sexes or age classes. We demonstrate that assignment methods can be rigorously used...

How to Measure the Onset of Babbling Reliably?

ERIC Educational Resources Information Center

Molemans, Inge; van den Berg, Renate; van Severen, Lieve; Gillis, Steven

2012-01-01

Various measures for identifying the onset of babbling have been proposed in the literature, but a formal definition of the exact procedure and a thorough validation of the sample size required for reliably establishing babbling onset is lacking. In this paper the reliability of five commonly used measures is assessed using a large longitudinal…

76 FR 2442 - Reports, Forms, and Record Keeping Requirements

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-13

... interviews over a period of approximately 26 months. The survey will ask questions about drinking behavior... wave of telephone interviews with residents in 3 program sites and 2 comparison sites not carrying out... will be 1,200 while sample size for the comparisons sites will be 500, totaling 23,000 interviews...

How many stakes are required to measure the mass balance of a glacier?

USGS Publications Warehouse

Fountain, A.G.; Vecchia, A.

1999-01-01

Glacier mass balance is estimated for South Cascade Glacier and Maclure Glacier using a one-dimensional regression of mass balance with altitude as an alternative to the traditional approach of contouring mass balance values. One attractive feature of regression is that it can be applied to sparse data sets where contouring is not possible and can provide an objective error of the resulting estimate. Regression methods yielded mass balance values equivalent to contouring methods. The effect of the number of mass balance measurements on the final value for the glacier showed that sample sizes as small as five stakes provided reasonable estimates, although the error estimates were greater than for larger sample sizes. Different spatial patterns of measurement locations showed no appreciable influence on the final value as long as different surface altitudes were intermittently sampled over the altitude range of the glacier. Two different regression equations were examined, a quadratic, and a piecewise linear spline, and comparison of results showed little sensitivity to the type of equation. These results point to the dominant effect of the gradient of mass balance with altitude of alpine glaciers compared to transverse variations. The number of mass balance measurements required to determine the glacier balance appears to be scale invariant for small glaciers and five to ten stakes are sufficient.

An empirical Bayes approach to analyzing recurring animal surveys

USGS Publications Warehouse

Johnson, D.H.

1989-01-01

Recurring estimates of the size of animal populations are often required by biologists or wildlife managers. Because of cost or other constraints, estimates frequently lack the accuracy desired but cannot readily be improved by additional sampling. This report proposes a statistical method employing empirical Bayes (EB) estimators as alternatives to those customarily used to estimate population size, and evaluates them by a subsampling experiment on waterfowl surveys. EB estimates, especially a simple limited-translation version, were more accurate and provided shorter confidence intervals with greater coverage probabilities than customary estimates.

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Accuracy of remotely sensed data: Sampling and analysis procedures

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Oderwald, R. G.; Mead, R. A.

1982-01-01

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.

Modulated error diffusion CGHs for neural nets

NASA Astrophysics Data System (ADS)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

Micrometeoroid and Lunar Secondary Ejecta Flux Measurements: Comparison of Three Acoustic Systems

NASA Technical Reports Server (NTRS)

Corsaro, R. D.; Giovane, F.; Liou, Jer-Chyi; Burtchell, M.; Pisacane, V.; Lagakos, N.; Williams, E.; Stansbery, E.

2010-01-01

This report examines the inherent capability of three large-area acoustic sensor systems and their applicability for micrometeoroids (MM) and lunar secondary ejecta (SE) detection and characterization for future lunar exploration activities. Discussion is limited to instruments that can be fabricated and deployed with low resource requirements. Previously deployed impact detection probes typically have instrumented capture areas less than 0.2 square meters. Since the particle flux decreases rapidly with increased particle size, such small-area sensors rarely encounter particles in the size range above 50 microns, and even their sampling the population above 10 microns is typically limited. Characterizing the sparse dust population in the size range above 50 microns requires a very large-area capture instrument. However it is also important that such an instrument simultaneously measures the population of the smaller particles, so as to provide a complete instantaneous snapshot of the population. For lunar or planetary surface studies, the system constraints are significant. The instrument must be as large as possible to sample the population of the largest MM. This is needed to reliably assess the particle impact risks and to develop cost-effective shielding designs for habitats, astronauts, and critical instrument. The instrument should also have very high sensitivity to measure the flux of small and slow SE particles. is the SE environment is currently poorly characterized, and possess a contamination risk to machinery and personnel involved in exploration. Deployment also requires that the instrument add very little additional mass to the spacecraft. Three acoustic systems are being explored for this application.

Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants.

PubMed

Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J

2011-06-01

Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.

There is More than a Power Law in Zipf

PubMed Central

Cristelli, Matthieu; Batty, Michael; Pietronero, Luciano

2012-01-01

The largest cities, the most frequently used words, the income of the richest countries, and the most wealthy billionaires, can be all described in terms of Zipf’s Law, a rank-size rule capturing the relation between the frequency of a set of objects or events and their size. It is assumed to be one of many manifestations of an underlying power law like Pareto’s or Benford’s, but contrary to popular belief, from a distribution of, say, city sizes and a simple random sampling, one does not obtain Zipf’s law for the largest cities. This pathology is reflected in the fact that Zipf’s Law has a functional form depending on the number of events N. This requires a fundamental property of the sample distribution which we call ‘coherence’ and it corresponds to a ‘screening’ between various elements of the set. We show how it should be accounted for when fitting Zipf’s Law. PMID:23139862

Fabrication of low thermal expansion SiC/ZrW2O8 porous ceramics

NASA Astrophysics Data System (ADS)

Poowancum, A.; Matsumaru, K.; Juárez-Ramírez, I.; Torres-Martínez, L. M.; Fu, Z. Y.; Lee, S. W.; Ishizaki, K.

2011-03-01

Low or zero thermal expansion porous ceramics are required for several applications. In this work near zero thermal expansion porous ceramics were fabricated by using SiC and ZrW2O8 as positive and negative thermal expansion materials, respectively, bonded by soda lime glass. The mixture of SiC, ZrW2O8 and soda lime glass was sintered by Pulsed Electric Current Sintering (PECS, or sometimes called Spark Plasma Sintering, SPS) at 700 °C. Sintered samples with ZrW2O8 particle size smaller than 25 μm have high thermal expansion coefficient, because ZrW2O8 has the reaction with soda lime glass to form Na2ZrW3O12 during sintering process. The reaction between soda lime glass and ZrW2O8 is reduced by increasing particle size of ZrW2O8. Sintered sample with ZrW2O8 particle size 45-90 μm shows near zero thermal expansion.

On-chip collection of particles and cells by AC electroosmotic pumping and dielectrophoresis using asymmetric microelectrodes

PubMed Central

Melvin, Elizabeth M.; Moore, Brandon R.; Gilchrist, Kristin H.; Grego, Sonia; Velev, Orlin D.

2011-01-01

The recent development of microfluidic “lab on a chip” devices requiring sample sizes <100 μL has given rise to the need to concentrate dilute samples and trap analytes, especially for surface-based detection techniques. We demonstrate a particle collection device capable of concentrating micron-sized particles in a predetermined area by combining AC electroosmosis (ACEO) and dielectrophoresis (DEP). The planar asymmetric electrode pattern uses ACEO pumping to induce equal, quadrilateral flow directed towards a stagnant region in the center of the device. A number of system parameters affecting particle collection efficiency were investigated including electrode and gap width, chamber height, applied potential and frequency, and number of repeating electrode pairs and electrode geometry. The robustness of the on-chip collection design was evaluated against varying electrolyte concentrations, particle types, and particle sizes. These devices are amenable to integration with a variety of detection techniques such as optical evanescent waveguide sensing. PMID:22662040

Experimental investigation of amount of nano-Al2O3 on mechanical properties of Al-based nano-composites fabricated by powder metallurgy (PM)

NASA Astrophysics Data System (ADS)

Razzaqi, A.; Liaghat, Gh.; Razmkhah, O.

2017-10-01

In this paper, mechanical properties of Aluminum (Al) matrix nano-composites, fabricated by Powder Metallurgy (PM) method, has been investigated. Alumina (Al2O3) nano particles were added in amounts of 0, 2.5, 5, 7.5 and 10 weight percentages (wt%). For this purpose, Al powder (particle size: 20 µm) and nano-Al2O3 (particle size: 20 nm) in various weight percentages were mixed and milled in a blade mixer for 15 minutes in 1500 rpm. Then, the obtained mixture, compacted by means of a two piece die and uniaxial cold press of about 600 MPa and cold iso-static press (CIP), required for different tests. After that, the samples sintered in 600°C for 90 minutes. Compression and three-point bending tests performed on samples and the results, led us to obtain the optimized particle size for achieving best mechanical properties.

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

PubMed Central

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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

Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size.

PubMed

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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

Structure and properties of clinical coralline implants measured via 3D imaging and analysis.

PubMed

Knackstedt, Mark Alexander; Arns, Christoph H; Senden, Tim J; Gross, Karlis

2006-05-01

The development and design of advanced porous materials for biomedical applications requires a thorough understanding of how material structure impacts on mechanical and transport properties. This paper illustrates a 3D imaging and analysis study of two clinically proven coral bone graft samples (Porites and Goniopora). Images are obtained from X-ray micro-computed tomography (micro-CT) at a resolution of 16.8 microm. A visual comparison of the two images shows very different structure; Porites has a homogeneous structure and consistent pore size while Goniopora has a bimodal pore size and a strongly disordered structure. A number of 3D structural characteristics are measured directly on the images including pore volume-to-surface-area, pore and solid size distributions, chord length measurements and tortuosity. Computational results made directly on the digitized tomographic images are presented for the permeability, diffusivity and elastic modulus of the coral samples. The results allow one to quantify differences between the two samples. 3D digital analysis can provide a more thorough assessment of biomaterial structure including the pore wall thickness, local flow, mechanical properties and diffusion pathways. We discuss the implications of these results to the development of optimal scaffold design for tissue ingrowth.

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

PubMed

Shieh, Gwowen

2016-04-01

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

Exploration of time-course combinations of outcome scales for use in a global test of stroke recovery.

PubMed

Goldie, Fraser C; Fulton, Rachael L; Dawson, Jesse; Bluhmki, Erich; Lees, Kennedy R

2014-08-01

Clinical trials for acute ischemic stroke treatment require large numbers of participants and are expensive to conduct. Methods that enhance statistical power are therefore desirable. We explored whether this can be achieved by a measure incorporating both early and late measures of outcome (e.g. seven-day NIH Stroke Scale combined with 90-day modified Rankin scale). We analyzed sensitivity to treatment effect, using proportional odds logistic regression for ordinal scales and generalized estimating equation method for global outcomes, with all analyses adjusted for baseline severity and age. We ran simulations to assess relations between sample size and power for ordinal scales and corresponding global outcomes. We used R version 2·12·1 (R Development Core Team. R Foundation for Statistical Computing, Vienna, Austria) for simulations and SAS 9·2 (SAS Institute Inc., Cary, NC, USA) for all other analyses. Each scale considered for combination was sensitive to treatment effect in isolation. The mRS90 and NIHSS90 had adjusted odds ratio of 1·56 and 1·62, respectively. Adjusted odds ratio for global outcomes of the combination of mRS90 with NIHSS7 and NIHSS90 with NIHSS7 were 1·69 and 1·73, respectively. The smallest sample sizes required to generate statistical power ≥80% for mRS90, NIHSS7, and global outcomes of mRS90 and NIHSS7 combined and NIHSS90 and NIHSS7 combined were 500, 490, 400, and 380, respectively. When data concerning both early and late outcomes are combined into a global measure, there is increased sensitivity to treatment effect compared with solitary ordinal scales. This delivers a 20% reduction in required sample size at 80% power. Combining early with late outcomes merits further consideration. © 2013 The Authors. International Journal of Stroke © 2013 World Stroke Organization.

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

PubMed

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

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

Generation of monodisperse cell-sized microdroplets using a centrifuge-based axisymmetric co-flowing microfluidic device.

PubMed

Yamashita, Hitoyoshi; Morita, Masamune; Sugiura, Haruka; Fujiwara, Kei; Onoe, Hiroaki; Takinoue, Masahiro

2015-04-01

We report an easy-to-use generation method of biologically compatible monodisperse water-in-oil microdroplets using a glass-capillary-based microfluidic device in a tabletop mini-centrifuge. This device does not require complicated microfabrication; furthermore, only a small sample volume is required in experiments. Therefore, we believe that this method will assist biochemical and cell-biological experiments. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Fossil shrews from Honduras and their significance for late glacial evolution in body size (Mammalia: Soricidae: Cryptotis)

USGS Publications Warehouse

Woodman, N.; Croft, D.A.

2005-01-01

Our study of mammalian remains excavated in the 1940s from McGrew Cave, north of Copan, Honduras, yielded an assemblage of 29 taxa that probably accumulated predominantly as the result of predation by owls. Among the taxa present are three species of small-eared shrews, genus Cryptotis. One species, Cryptotis merriami, is relatively rare among the fossil remains. The other two shrews, Cryptotis goodwini and Cryptotis orophila, are abundant and exhibit morpho metrical variation distinguishing them from modern populations. Fossils of C. goodwini are distinctly and consistently smaller than modern members of the species. To quantify the size differences, we derived common measures of body size for fossil C. goodwini using regression models based on modern samples of shrews in the Cryptotis mexicana-group. Estimated mean length of head and body for the fossil sample is 72-79 mm, and estimated mean mass is 7.6-9.6 g. These numbers indicate that the fossil sample averaged 6-14% smaller in head and body length and 39-52% less in mass than the modern sample and that increases of 6-17% in head and body length and 65-108% in mass occurred to achieve the mean body size of the modern sample. Conservative estimates of fresh (wet) food intake based on mass indicate that such a size increase would require a 37-58% increase in daily food consumption. In contrast to C. goodwini, fossil C. orophila from the cave is not different in mean body size from modern samples. The fossil sample does, however, show slightly greater variation in size than is currently present throughout the modern geographical distribution of the taxon. Moreover, variation in some other dental and mandibular characters is more constrained, exhibiting a more direct relationship to overall size. Our study of these species indicates that North American shrews have not all been static in size through time, as suggested by some previous work with fossil soricids. Lack of stratigraphic control within the site and our failure to obtain reliable radiometric dates on remains restrict our opportunities to place the site in a firm temporal context. However, the morphometrical differences we document for fossil C. orophila and C. goodwini show them to be distinct from modern populations of these shrews. Some other species of fossil mammals from McGrew Cave exhibit distinct size changes of the magnitudes experienced by many northern North American and some Mexican mammals during the transition from late glacial to Holocene environmental conditions, and it is likely that at least some of the remains from the cave are late Pleistocene in age. One curious factor is that, whereas most mainland mammals that exhibit large-scale size shifts during the late glacial/postglacial transition experienced dwarfing, C. goodwini increased in size. The lack of clinal variation in modern C. goodwini supports the hypothesis that size evolution can result from local selection rather than from cline translocation. Models of size change in mammals indicate that increased size, such as that observed for C. goodwini, are a likely consequence of increased availability of resources and, thereby, a relaxation of selection during critical times of the year.

Globule-size distribution in injectable 20% lipid emulsions: Compliance with USP requirements.

PubMed

Driscoll, David F

2007-10-01

The compliance of injectable 20% lipid emulsions with the globule-size limits in chapter 729 of the U.S. Pharmacopeia (USP) was examined. As established in chapter 729, dynamic light scattering was applied to determine mean droplet diameter (MDD), with an upper limit of 500 nm. Light obscuration was used to determine the size of fat globules found in the large-diameter tail, expressed as the volume-weighted percent fat exceeding 5 microm (PFAT(5)), with an upper limit of 0.05%. Compliance of seven different emulsions, six of which were stored in plastic bags, with USP limits was assessed. To avoid reaching coincidence limits during the application of method II from overly concentrated emulsion samples, a variable dilution scheme was used to optimize the globule-size measurements for each emulsion. One-way analysis of variance of globule-size distribution (GSD) data was conducted if any results of method I or II exceeded the respective upper limits. Most injectable lipid emulsions complied with limits established by USP chapter 729, with the exception of those of one manufacturer, which failed limits as proposed for to meet the PFAT(5) three of the emulsions tested. In contrast, all others studied (one packaged in glass and three packaged in plastic) met both criteria. Among seven injectable lipid emulsions tested for GSD, all met USP chapter 729 MDD requirements and three, all from the same manufacturer and packaged in plastic, did not meet PFAT(5) requirements.

Validating a biometric authentication system: sample size requirements.

PubMed

Dass, Sarat C; Zhu, Yongfang; Jain, Anil K

2006-12-01

Authentication systems based on biometric features (e.g., fingerprint impressions, iris scans, human face images, etc.) are increasingly gaining widespread use and popularity. Often, vendors and owners of these commercial biometric systems claim impressive performance that is estimated based on some proprietary data. In such situations, there is a need to independently validate the claimed performance levels. System performance is typically evaluated by collecting biometric templates from n different subjects, and for convenience, acquiring multiple instances of the biometric for each of the n subjects. Very little work has been done in 1) constructing confidence regions based on the ROC curve for validating the claimed performance levels and 2) determining the required number of biometric samples needed to establish confidence regions of prespecified width for the ROC curve. To simplify the analysis that address these two problems, several previous studies have assumed that multiple acquisitions of the biometric entity are statistically independent. This assumption is too restrictive and is generally not valid. We have developed a validation technique based on multivariate copula models for correlated biometric acquisitions. Based on the same model, we also determine the minimum number of samples required to achieve confidence bands of desired width for the ROC curve. We illustrate the estimation of the confidence bands as well as the required number of biometric samples using a fingerprint matching system that is applied on samples collected from a small population.

Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review.

PubMed

Hislop, Jenni; Adewuyi, Temitope E; Vale, Luke D; Harrild, Kirsten; Fraser, Cynthia; Gurung, Tara; Altman, Douglas G; Briggs, Andrew H; Fayers, Peter; Ramsay, Craig R; Norrie, John D; Harvey, Ian M; Buckley, Brian; Cook, Jonathan A

2014-05-01

Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified-anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts.

High frequency mesozooplankton monitoring: Can imaging systems and automated sample analysis help us describe and interpret changes in zooplankton community composition and size structure — An example from a coastal site

NASA Astrophysics Data System (ADS)

Romagnan, Jean Baptiste; Aldamman, Lama; Gasparini, Stéphane; Nival, Paul; Aubert, Anaïs; Jamet, Jean Louis; Stemmann, Lars

2016-10-01

The present work aims to show that high throughput imaging systems can be useful to estimate mesozooplankton community size and taxonomic descriptors that can be the base for consistent large scale monitoring of plankton communities. Such monitoring is required by the European Marine Strategy Framework Directive (MSFD) in order to ensure the Good Environmental Status (GES) of European coastal and offshore marine ecosystems. Time and cost-effective, automatic, techniques are of high interest in this context. An imaging-based protocol has been applied to a high frequency time series (every second day between April 2003 to April 2004 on average) of zooplankton obtained in a coastal site of the NW Mediterranean Sea, Villefranche Bay. One hundred eighty four mesozooplankton net collected samples were analysed with a Zooscan and an associated semi-automatic classification technique. The constitution of a learning set designed to maximize copepod identification with more than 10,000 objects enabled the automatic sorting of copepods with an accuracy of 91% (true positives) and a contamination of 14% (false positives). Twenty seven samples were then chosen from the total copepod time series for detailed visual sorting of copepods after automatic identification. This method enabled the description of the dynamics of two well-known copepod species, Centropages typicus and Temora stylifera, and 7 other taxonomically broader copepod groups, in terms of size, biovolume and abundance-size distributions (size spectra). Also, total copepod size spectra underwent significant changes during the sampling period. These changes could be partially related to changes in the copepod assemblage taxonomic composition and size distributions. This study shows that the use of high throughput imaging systems is of great interest to extract relevant coarse (i.e. total abundance, size structure) and detailed (i.e. selected species dynamics) descriptors of zooplankton dynamics. Innovative zooplankton analyses are therefore proposed and open the way for further development of zooplankton community indicators of changes.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions

NASA Astrophysics Data System (ADS)

Dong, Miao L.; Goyal, Kashika G.; Worth, Bradley W.; Makkar, Sorab S.; Calhoun, William R.; Bali, Lalit M.; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions.

PubMed

Dong, Miao L; Goyal, Kashika G; Worth, Bradley W; Makkar, Sorab S; Calhoun, William R; Bali, Lalit M; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Using solvent-free sample preparation to promote protonation of poly(ethylene oxide)s with labile end-groups in matrix-assisted laser desorption/ionisation.

PubMed

Mazarin, Michael; Phan, Trang N T; Charles, Laurence

2008-12-01

Protonation is usually required to observe intact ions during matrix-assisted laser desorption/ionization (MALDI) of polymers containing fragile end-groups while cation adduction induces chain-end degradation. These polymers, generally obtained via living free radical polymerization techniques, are terminated with a functionality in which a bond is prone to homolytic cleavage, as required by the polymerization process. A solvent-free sample preparation method was used here to avoid salt contaminant from the solvent traditionally used in the dried-droplet MALDI procedure. Solvent-based and solvent-free sample preparations were compared for a series of three poly(ethylene oxide) polymers functionalized with a labile end-group in a nitroxide-mediated polymerization reaction, using 2,4,6-trihydroxyacetophenone (THAP) as the matrix without any added salt. Intact oligomer ions could only be produced as protonated molecules in solvent-free MALDI while sodium adducts of degraded polymers were formed from the dried-droplet samples. Although MALDI analysis was performed at the laser threshold, fragmentation of protonated macromolecules was still observed to occur. However, in contrast to sodiated molecules, dissociation of protonated oligomers does not involve the labile C--ON bond of the end-group. As the macromolecule size increased, protonation appeared to be less efficient and sodium adduction became the dominant ionization process, although no sodium salt was added in the preparation. Formation of sodiated degraded macromolecules would be dictated by increasing cation affinity as the size of the oligomers increases and would reveal the presence of salts at trace levels in the MALDI samples.

Confidence intervals for population allele frequencies: the general case of sampling from a finite diploid population of any size.

PubMed

Fung, Tak; Keenan, Kevin

2014-01-01

The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (> or = 95%), a sample size of > 30 is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive > or = 98.3% confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint > or = 95% confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a > or = 95%% confidence interval for Jost's D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management.

Effects of sources of variability on sample sizes required for RCTs, applied to trials of lipid-altering therapies on carotid artery intima-media thickness.

PubMed

Gould, A Lawrence; Koglin, Joerg; Bain, Raymond P; Pinto, Cathy-Anne; Mitchel, Yale B; Pasternak, Richard C; Sapre, Aditi

2009-08-01

Studies measuring progression of carotid artery intima-media thickness (cIMT) have been used to estimate the effect of lipid-modifying therapies cardiovascular event risk. The likelihood that future cIMT clinical trials will detect a true treatment effect is estimated by leveraging results from prior studies. The present analyses assess the impact of between- and within-study variability based on currently published data from prior clinical studies on the likelihood that ongoing or future cIMT trials will detect the true treatment effect of lipid-modifying therapies. Published data from six contemporary cIMT studies (ASAP, ARBITER 2, RADIANCE 1, RADIANCE 2, ENHANCE, and METEOR) including data from a total of 3563 patients were examined. Bayesian and frequentist methods were used to assess the impact of between study variability on the likelihood of detecting true treatment effects on 1-year cIMT progression/regression and to provide a sample size estimate that would specifically compensate for the effect of between-study variability. In addition to the well-described within-study variability, there is considerable between-study variability associated with the measurement of annualized change in cIMT. Accounting for the additional between-study variability decreases the power for existing study designs. In order to account for the added between-study variability, it is likely that future cIMT studies would require a large increase in sample size in order to provide substantial probability (> or =90%) to have 90% power of detecting a true treatment effect.Limitation Analyses are based on study level data. Future meta-analyses incorporating patient-level data would be useful for confirmation. Due to substantial within- and between-study variability in the measure of 1-year change of cIMT, as well as uncertainty about progression rates in contemporary populations, future study designs evaluating the effect of new lipid-modifying therapies on atherosclerotic disease progression are likely to be challenged by large sample sizes in order to demonstrate a true treatment effect.

Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field

PubMed Central

Petrovskaya, Natalia B.; Forbes, Emily; Petrovskii, Sergei V.; Walters, Keith F. A.

2018-01-01

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid. PMID:29495513

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

PubMed

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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