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.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

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

Hero, Alfred O.; Rajaratnam, Bala

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Reporting of sample size calculations in analgesic clinical trials: ACTTION systematic review.

PubMed

McKeown, Andrew; Gewandter, Jennifer S; McDermott, Michael P; Pawlowski, Joseph R; Poli, Joseph J; Rothstein, Daniel; Farrar, John T; Gilron, Ian; Katz, Nathaniel P; Lin, Allison H; Rappaport, Bob A; Rowbotham, Michael C; Turk, Dennis C; Dworkin, Robert H; Smith, Shannon M

2015-03-01

Sample size calculations determine the number of participants required to have sufficiently high power to detect a given treatment effect. In this review, we examined the reporting quality of sample size calculations in 172 publications of double-blind randomized controlled trials of noninvasive pharmacologic or interventional (ie, invasive) pain treatments published in European Journal of Pain, Journal of Pain, and Pain from January 2006 through June 2013. Sixty-five percent of publications reported a sample size calculation but only 38% provided all elements required to replicate the calculated sample size. In publications reporting at least 1 element, 54% provided a justification for the treatment effect used to calculate sample size, and 24% of studies with continuous outcome variables justified the variability estimate. Publications of clinical pain condition trials reported a sample size calculation more frequently than experimental pain model trials (77% vs 33%, P < .001) but did not differ in the frequency of reporting all required elements. No significant differences in reporting of any or all elements were detected between publications of trials with industry and nonindustry sponsorship. Twenty-eight percent included a discrepancy between the reported number of planned and randomized participants. This study suggests that sample size calculation reporting in analgesic trial publications is usually incomplete. Investigators should provide detailed accounts of sample size calculations in publications of clinical trials of pain treatments, which is necessary for reporting transparency and communication of pre-trial design decisions. In this systematic review of analgesic clinical trials, sample size calculations and the required elements (eg, treatment effect to be detected; power level) were incompletely reported. A lack of transparency regarding sample size calculations may raise questions about the appropriateness of the calculated sample size. Copyright © 2015 American Pain Society. All rights reserved.

An audit of the statistics and the comparison with the parameter in the population

NASA Astrophysics Data System (ADS)

Bujang, Mohamad Adam; Sa'at, Nadiah; Joys, A. Reena; Ali, Mariana Mohamad

2015-10-01

The sufficient sample size that is needed to closely estimate the statistics for particular parameters are use to be an issue. Although sample size might had been calculated referring to objective of the study, however, it is difficult to confirm whether the statistics are closed with the parameter for a particular population. All these while, guideline that uses a p-value less than 0.05 is widely used as inferential evidence. Therefore, this study had audited results that were analyzed from various sub sample and statistical analyses and had compared the results with the parameters in three different populations. Eight types of statistical analysis and eight sub samples for each statistical analysis were analyzed. Results found that the statistics were consistent and were closed to the parameters when the sample study covered at least 15% to 35% of population. Larger sample size is needed to estimate parameter that involve with categorical variables compared with numerical variables. Sample sizes with 300 to 500 are sufficient to estimate the parameters for medium size of population.

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.

Corpus Callosum Size, Reaction Time Speed and Variability in Mild Cognitive Disorders and in a Normative Sample

ERIC Educational Resources Information Center

Anstey, Kaarin J.; Mack, Holly A.; Christensen, Helen; Li, Shu-Chen; Reglade-Meslin, Chantal; Maller, Jerome; Kumar, Rajeev; Dear, Keith; Easteal, Simon; Sachdev, Perminder

2007-01-01

Intra-individual variability in reaction time increases with age and with neurological disorders, but the neural correlates of this increased variability remain uncertain. We hypothesized that both faster mean reaction time (RT) and less intra-individual RT variability would be associated with larger corpus callosum (CC) size in older adults, and…

Qualitative Meta-Analysis on the Hospital Task: Implications for Research

ERIC Educational Resources Information Center

Noll, Jennifer; Sharma, Sashi

2014-01-01

The "law of large numbers" indicates that as sample size increases, sample statistics become less variable and more closely estimate their corresponding population parameters. Different research studies investigating how people consider sample size when evaluating the reliability of a sample statistic have found a wide range of…

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...

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.

Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data.

PubMed

de Winter, Joost C F; Gosling, Samuel D; Potter, Jeff

2016-09-01

The Pearson product–moment correlation coefficient ( r p ) and the Spearman rank correlation coefficient ( r s ) are widely used in psychological research. We compare r p and r s on 3 criteria: variability, bias with respect to the population value, and robustness to an outlier. Using simulations across low (N = 5) to high (N = 1,000) sample sizes we show that, for normally distributed variables, r p and r s have similar expected values but r s is more variable, especially when the correlation is strong. However, when the variables have high kurtosis, r p is more variable than r s . Next, we conducted a sampling study of a psychometric dataset featuring symmetrically distributed data with light tails, and of 2 Likert-type survey datasets, 1 with light-tailed and the other with heavy-tailed distributions. Consistent with the simulations, r p had lower variability than r s in the psychometric dataset. In the survey datasets with heavy-tailed variables in particular, r s had lower variability than r p , and often corresponded more accurately to the population Pearson correlation coefficient ( R p ) than r p did. The simulations and the sampling studies showed that variability in terms of standard deviations can be reduced by about 20% by choosing r s instead of r p . In comparison, increasing the sample size by a factor of 2 results in a 41% reduction of the standard deviations of r s and r p . In conclusion, r p is suitable for light-tailed distributions, whereas r s is preferable when variables feature heavy-tailed distributions or when outliers are present, as is often the case in psychological research. PsycINFO Database Record (c) 2016 APA, all rights reserved

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...

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

PubMed

Shamey, Renzo; Zubair, Muhammad; Cheema, Hammad

2015-08-01

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

Variable criteria sequential stopping rule: Validity and power with repeated measures ANOVA, multiple correlation, MANOVA and relation to Chi-square distribution.

PubMed

Fitts, Douglas A

2017-09-21

The variable criteria sequential stopping rule (vcSSR) is an efficient way to add sample size to planned ANOVA tests while holding the observed rate of Type I errors, α o , constant. The only difference from regular null hypothesis testing is that criteria for stopping the experiment are obtained from a table based on the desired power, rate of Type I errors, and beginning sample size. The vcSSR was developed using between-subjects ANOVAs, but it should work with p values from any type of F test. In the present study, the α o remained constant at the nominal level when using the previously published table of criteria with repeated measures designs with various numbers of treatments per subject, Type I error rates, values of ρ, and four different sample size models. New power curves allow researchers to select the optimal sample size model for a repeated measures experiment. The criteria held α o constant either when used with a multiple correlation that varied the sample size model and the number of predictor variables, or when used with MANOVA with multiple groups and two levels of a within-subject variable at various levels of ρ. Although not recommended for use with χ 2 tests such as the Friedman rank ANOVA test, the vcSSR produces predictable results based on the relation between F and χ 2 . Together, the data confirm the view that the vcSSR can be used to control Type I errors during sequential sampling with any t- or F-statistic rather than being restricted to certain ANOVA designs.

Sample size and power for cost-effectiveness analysis (part 1).

PubMed

Glick, Henry A

2011-03-01

Basic sample size and power formulae for cost-effectiveness analysis have been established in the literature. These formulae are reviewed and the similarities and differences between sample size and power for cost-effectiveness analysis and for the analysis of other continuous variables such as changes in blood pressure or weight are described. The types of sample size and power tables that are commonly calculated for cost-effectiveness analysis are also described and the impact of varying the assumed parameter values on the resulting sample size and power estimates is discussed. Finally, the way in which the data for these calculations may be derived are discussed.

Fish Assemblage Structure Under Variable Environmental Conditions in the Ouachita Mountains

Treesearch

Christopher M. Taylor; Lance R. Williams; Riccardo A. Fiorillo; R. Brent Thomas; Melvin L. Warren

2004-01-01

Abstract - Spatial and temporal variability of fish assemblages in Ouachita Mountain streams, Arkansas, were examined for association with stream size and flow variability. Fishes and habitat were sampled quarterly for four years at 12 sites (144 samples) in the Ouachita Mountains Ecosystem Management Research Project, Phase III watersheds. Detrended...

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

ERIC Educational Resources Information Center

Svanum, Soren; Bringle, Robert G.

1980-01-01

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

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

PubMed

Usami, Satoshi

2017-03-01

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

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

PubMed

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

2011-02-01

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

Estimation and applications of size-biased distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-biased distributions arise naturally in several contexts in forestry and ecology. Simple power relationships (e.g. basal area and diameter at breast height) between variables are one such area of interest arising from a modelling perspective. Another, probability proportional to size PPS) sampling, is found in the most widely used methods for sampling standing or...

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.

Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

Spatial variability in plankton biomass and hydrographic variables along an axial transect in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Zhang, X.; Roman, M.; Kimmel, D.; McGilliard, C.; Boicourt, W.

2006-05-01

High-resolution, axial sampling surveys were conducted in Chesapeake Bay during April, July, and October from 1996 to 2000 using a towed sampling device equipped with sensors for depth, temperature, conductivity, oxygen, fluorescence, and an optical plankton counter (OPC). The results suggest that the axial distribution and variability of hydrographic and biological parameters in Chesapeake Bay were primarily influenced by the source and magnitude of freshwater input. Bay-wide spatial trends in the water column-averaged values of salinity were linear functions of distance from the main source of freshwater, the Susquehanna River, at the head of the bay. However, spatial trends in the water column-averaged values of temperature, dissolved oxygen, chlorophyll-a and zooplankton biomass were nonlinear along the axis of the bay. Autocorrelation analysis and the residuals of linear and quadratic regressions between each variable and latitude were used to quantify the patch sizes for each axial transect. The patch sizes of each variable depended on whether the data were detrended, and the detrending techniques applied. However, the patch size of each variable was generally larger using the original data compared to the detrended data. The patch sizes of salinity were larger than those for dissolved oxygen, chlorophyll-a and zooplankton biomass, suggesting that more localized processes influence the production and consumption of plankton. This high-resolution quantification of the zooplankton spatial variability and patch size can be used for more realistic assessments of the zooplankton forage base for larval fish species.

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.

Extension of latin hypercube samples with correlated variables.

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

Hora, Stephen Curtis; Helton, Jon Craig; Sallaberry, Cedric J. PhD.

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« less

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

Vigilance behaviour of the year-round territorial vicuña (Vicugna vicugna) outside the breeding season: influence of group size, social factors and distance to a water source.

PubMed

Torres, M Eugenia Mosca; Puig, Silvia; Novillo, Agustina; Ovejero, Ramiro

2015-04-01

We conducted focal observations of vicuña, a year-around territorial mammal, to compare vigilance behaviour between territorial and bachelor males outside the reproductive season. We hypothesized that the time spent vigilant would depend on male social status, considering the potential effects of several variables: sampling year, group size, distances to the nearest neighbour and to a vega (mountain wetland). We fit GLM models to assess how these variables, and their interactions, affected time allocation of territorial and bachelor males. We found non significant differences between territorial and bachelor males in the time devoted to vigilance behaviour. Vigilance of territorial males was influenced by the sampling year and the distance to the vega. In turn, vigilance in bachelor males was influenced mainly by the sampling year, the group size and the distance to the vega. Our results suggest that sampling year and distance to the vega are more important than social factors in conditioning the behaviour of male vicuñas, during the non-reproductive season. Future studies of behaviour in water-dependant ungulates, should consider the influence of water and forage availabilities, and the interactions between group size and other variables. Copyright © 2015 Elsevier B.V. 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.

Alternatives to Three-Mode Factor Analysis: A Case Study with Data Evaluating Perceived Barriers to Medical School Training.

ERIC Educational Resources Information Center

Thomson, William A.; And Others

While educational researchers frequently collect data from a sample of individuals on a sample of variables, they sometimes collect data involving samples of: (1) subjects; (2) variables; and (3) occasions of measurement. A multistage procedure for analyzing such three-mode data is presented, focusing on effect sizes and graphic confidence…

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.

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

PubMed

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

2016-10-01

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

On measuring bird habitat: influence of observer variability and sample size

Treesearch

William M. Block; Kimberly A. With; Michael L. Morrison

1987-01-01

We studied the effects of observer variability when estimating vegetation characteristics at 75 0.04-ha bird plots. Observer estimates were significantly different for 31 of 49 variables. Multivariate analyses showed significant interobserver differences for five of the seven classes of variables studied. Variable classes included the height, number, and diameter of...

Variability in group size and the evolution of collective action.

PubMed

Peña, Jorge; Nöldeke, Georg

2016-01-21

Models of the evolution of collective action typically assume that interactions occur in groups of identical size. In contrast, social interactions between animals occur in groups of widely dispersed size. This paper models collective action problems as two-strategy multiplayer games and studies the effect of variability in group size on the evolution of cooperative behavior under the replicator dynamics. The analysis identifies elementary conditions on the payoff structure of the game implying that the evolution of cooperative behavior is promoted or inhibited when the group size experienced by a focal player is more or less variable. Similar but more stringent conditions are applicable when the confounding effect of size-biased sampling, which causes the group-size distribution experienced by a focal player to differ from the statistical distribution of group sizes, is taken into account. Copyright © 2015 Elsevier Ltd. All rights reserved.

Naltrexone and Cognitive Behavioral Therapy for the Treatment of Alcohol Dependence

PubMed Central

Baros, AM; Latham, PK; Anton, RF

2008-01-01

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

Comparative tests of ectoparasite species richness in seabirds

PubMed Central

Hughes, Joseph; Page, Roderic DM

2007-01-01

Background The diversity of parasites attacking a host varies substantially among different host species. Understanding the factors that explain these patterns of parasite diversity is critical to identifying the ecological principles underlying biodiversity. Seabirds (Charadriiformes, Pelecaniformes and Procellariiformes) and their ectoparasitic lice (Insecta: Phthiraptera) are ideal model groups in which to study correlates of parasite species richness. We evaluated the relative importance of morphological (body size, body weight, wingspan, bill length), life-history (longevity, clutch size), ecological (population size, geographical range) and behavioural (diving versus non-diving) variables as predictors of louse diversity on 413 seabird hosts species. Diversity was measured at the level of louse suborder, genus, and species, and uneven sampling of hosts was controlled for using literature citations as a proxy for sampling effort. Results The only variable consistently correlated with louse diversity was host population size and to a lesser extent geographic range. Other variables such as clutch size, longevity, morphological and behavioural variables including body mass showed inconsistent patterns dependent on the method of analysis. Conclusion The comparative analysis presented herein is (to our knowledge) the first to test correlates of parasite species richness in seabirds. We believe that the comparative data and phylogeny provide a valuable framework for testing future evolutionary hypotheses relating to the diversity and distribution of parasites on seabirds. PMID:18005412

Influence of tree spatial pattern and sample plot type and size on inventory

Treesearch

John-Pascall Berrill; Kevin L. O' Hara

2012-01-01

Sampling with different plot types and sizes was simulated using tree location maps and data collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius circular plots, belt transects, and variable-radius plots were installed by...

VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS

PubMed Central

Huang, Jian; Horowitz, Joel L.; Wei, Fengrong

2010-01-01

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is “small” relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method. PMID:21127739

Characterizing the size distribution of particles in urban stormwater by use of fixed-point sample-collection methods

USGS Publications Warehouse

Selbig, William R.; Bannerman, Roger T.

2011-01-01

The U.S Geological Survey, in cooperation with the Wisconsin Department of Natural Resources (WDNR) and in collaboration with the Root River Municipal Stormwater Permit Group monitored eight urban source areas representing six types of source areas in or near Madison, Wis. in an effort to improve characterization of particle-size distributions in urban stormwater by use of fixed-point sample collection methods. The types of source areas were parking lot, feeder street, collector street, arterial street, rooftop, and mixed use. This information can then be used by environmental managers and engineers when selecting the most appropriate control devices for the removal of solids from urban stormwater. Mixed-use and parking-lot study areas had the lowest median particle sizes (42 and 54 (u or mu)m, respectively), followed by the collector street study area (70 (u or mu)m). Both arterial street and institutional roof study areas had similar median particle sizes of approximately 95 (u or mu)m. Finally, the feeder street study area showed the largest median particle size of nearly 200 (u or mu)m. Median particle sizes measured as part of this study were somewhat comparable to those reported in previous studies from similar source areas. The majority of particle mass in four out of six source areas was silt and clay particles that are less than 32 (u or mu)m in size. Distributions of particles ranging from 500 (u or mu)m were highly variable both within and between source areas. Results of this study suggest substantial variability in data can inhibit the development of a single particle-size distribution that is representative of stormwater runoff generated from a single source area or land use. Continued development of improved sample collection methods, such as the depth-integrated sample arm, may reduce variability in particle-size distributions by mitigating the effect of sediment bias inherent with a fixed-point sampler.

A comparative review of methods for comparing means using partially paired data.

PubMed

Guo, Beibei; Yuan, Ying

2017-06-01

In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired data, including the two-sample t-test, paired t-test, corrected z-test, weighted t-test, pooled t-test, optimal pooled t-test, multiple imputation method, mixed model approach, and the test based on a modified maximum likelihood estimate. We compare the performance of these methods through extensive simulation studies that cover a wide range of scenarios with different effect sizes, sample sizes, and correlations between the paired variables, as well as true underlying distributions. The simulation results suggest that when the sample size is moderate, the test based on the modified maximum likelihood estimator is generally superior to the other approaches when the data is normally distributed and the optimal pooled t-test performs the best when the data is not normally distributed, with well-controlled type I error rates and high statistical power; when the sample size is small, the optimal pooled t-test is to be recommended when both variables have missing data and the paired t-test is to be recommended when only one variable has missing data.

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.

Characterization of the porosity of human dental enamel and shear bond strength in vitro after variable etch times: initial findings using the BET method.

PubMed

Nguyen, Trang T; Miller, Arthur; Orellana, Maria F

2011-07-01

(1) To quantitatively characterize human enamel porosity and surface area in vitro before and after etching for variable etching times; and (2) to evaluate shear bond strength after variable etching times. Specifically, our goal was to identify the presence of any correlation between enamel porosity and shear bond strength. Pore surface area, pore volume, and pore size of enamel from extracted human teeth were analyzed by Brunauer-Emmett-Teller (BET) gas adsorption before and after etching for 15, 30, and 60 seconds with 37% phosphoric acid. Orthodontic brackets were bonded with Transbond to the samples with variable etch times and were subsequently applied to a single-plane lap shear testing system. Pore volume and surface area increased after etching for 15 and 30 seconds. At 60 seconds, this increase was less pronounced. On the contrary, pore size appears to decrease after etching. No correlation was found between variable etching times and shear strength. Samples etched for 15, 30, and 60 seconds all demonstrated clinically viable shear strength values. The BET adsorption method could be a valuable tool in enhancing our understanding of enamel characteristics. Our findings indicate that distinct quantitative changes in enamel pore architecture are evident after etching. Further testing with a larger sample size would have to be carried out for more definitive conclusions to be made.

Optimizing variable radius plot size and LiDAR resolution to model standing volume in conifer forests

Treesearch

Ram Kumar Deo; Robert E. Froese; Michael J. Falkowski; Andrew T. Hudak

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....

Bed-sediment grain-size and morphologic data from Suisun, Grizzly, and Honker Bays, CA, 1998-2002

USGS Publications Warehouse

Hampton, Margaret A.; Snyder, Noah P.; Chin, John L.; Allison, Dan W.; Rubin, David M.

2003-01-01

The USGS Place Based Studies Program for San Francisco Bay investigates this sensitive estuarine system to aid in resource management. As part of the inter-disciplinary research program, the USGS collected side-scan sonar data and bed-sediment samples from north San Francisco Bay to characterize bed-sediment texture and investigate temporal trends in sedimentation. The study area is located in central California and consists of Suisun Bay, and Grizzly and Honker Bays, sub-embayments of Suisun Bay. During the study (1998-2002), the USGS collected three side-scan sonar data sets and approximately 300 sediment samples. The side-scan data revealed predominantly fine-grained material on the bayfloor. We also mapped five different bottom types from the data set, categorized as featureless, furrows, sand waves, machine-made, and miscellaneous. We performed detailed grain-size and statistical analyses on the sediment samples. Overall, we found that grain size ranged from clay to fine sand, with the coarsest material in the channels and finer material located in the shallow bays. Grain-size analyses revealed high spatial variability in size distributions in the channel areas. In contrast, the shallow regions exhibited low spatial variability and consistent sediment size over time.

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

PubMed Central

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

2015-01-01

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

A sequential bioequivalence design with a potential ethical advantage.

PubMed

Fuglsang, Anders

2014-07-01

This paper introduces a two-stage approach for evaluation of bioequivalence, where, in contrast to the designs of Diane Potvin and co-workers, two stages are mandatory regardless of the data obtained at stage 1. The approach is derived from Potvin's method C. It is shown that under circumstances with relatively high variability and relatively low initial sample size, this method has an advantage over Potvin's approaches in terms of sample sizes while controlling type I error rates at or below 5% with a minute occasional trade-off in power. Ethically and economically, the method may thus be an attractive alternative to the Potvin designs. It is also shown that when using the method introduced here, average total sample sizes are rather independent of initial sample size. Finally, it is shown that when a futility rule in terms of sample size for stage 2 is incorporated into this method, i.e., when a second stage can be abolished due to sample size considerations, there is often an advantage in terms of power or sample size as compared to the previously published methods.

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

On the comparison of the strength of morphological integration across morphometric datasets.

PubMed

Adams, Dean C; Collyer, Michael L

2016-11-01

Evolutionary morphologists frequently wish to understand the extent to which organisms are integrated, and whether the strength of morphological integration among subsets of phenotypic variables differ among taxa or other groups. However, comparisons of the strength of integration across datasets are difficult, in part because the summary measures that characterize these patterns (RV coefficient and r PLS ) are dependent both on sample size and on the number of variables. As a solution to this issue, we propose a standardized test statistic (a z-score) for measuring the degree of morphological integration between sets of variables. The approach is based on a partial least squares analysis of trait covariation, and its permutation-based sampling distribution. Under the null hypothesis of a random association of variables, the method displays a constant expected value and confidence intervals for datasets of differing sample sizes and variable number, thereby providing a consistent measure of integration suitable for comparisons across datasets. A two-sample test is also proposed to statistically determine whether levels of integration differ between datasets, and an empirical example examining cranial shape integration in Mediterranean wall lizards illustrates its use. Some extensions of the procedure are also discussed. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Modeling the development of written language

PubMed Central

Puranik, Cynthia S.; Foorman, Barbara; Foster, Elizabeth; Wilson, Laura Gehron; Tschinkel, Erika; Kantor, Patricia Thatcher

2011-01-01

Alternative models of the structure of individual and developmental differences of written composition and handwriting fluency were tested using confirmatory factor analysis of writing samples provided by first- and fourth-grade students. For both groups, a five-factor model provided the best fit to the data. Four of the factors represented aspects of written composition: macro-organization (use of top sentence and number and ordering of ideas), productivity (number and diversity of words used), complexity (mean length of T-unit and syntactic density), and spelling and punctuation. The fifth factor represented handwriting fluency. Handwriting fluency was correlated with written composition factors at both grades. The magnitude of developmental differences between first grade and fourth grade expressed as effect sizes varied for variables representing the five constructs: large effect sizes were found for productivity and handwriting fluency variables; moderate effect sizes were found for complexity and macro-organization variables; and minimal effect sizes were found for spelling and punctuation variables. PMID:22228924

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.

The Effect of Unequal Samples, Heterogeneity of Covariance Matrices, and Number of Variables on Discriminant Analysis Classification Tables and Related Statistics.

ERIC Educational Resources Information Center

Spearing, Debra; Woehlke, Paula

To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size

PubMed Central

Yu, P.; Sun, J.; Wolz, R.; Stephenson, D.; Brewer, J.; Fox, N.C.; Cole, P.E.; Jack, C.R.; Hill, D.L.G.; Schwarz, A.J.

2014-01-01

Objective To evaluate the effect of computational algorithm, measurement variability and cut-point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). Methods We used normal control and amnestic MCI subjects from ADNI-1 as normative reference and screening cohorts. We evaluated the enrichment performance of four widely-used hippocampal segmentation algorithms (FreeSurfer, HMAPS, LEAP and NeuroQuant) in terms of two-year changes in MMSE, ADAS-Cog and CDR-SB. We modeled the effect of algorithm, test-retest variability and cut-point on sample size, screen fail rates and trial cost and duration. Results HCV-based patient selection yielded not only reduced sample sizes (by ~40–60%) but also lower trial costs (by ~30–40%) across a wide range of cut-points. Overall, the dependence on the cut-point value was similar for the three clinical instruments considered. Conclusion These results provide a guide to the choice of HCV cut-point for aMCI clinical trials, allowing an informed trade-off between statistical and practical considerations. PMID:24211008

An Investigation of the Sampling Distribution of the Congruence Coefficient.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.; Elmore, Patricia B.

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

Comparison of Bootstrapping and Markov Chain Monte Carlo for Copula Analysis of Hydrological Droughts

NASA Astrophysics Data System (ADS)

Yang, P.; Ng, T. L.; Yang, W.

2015-12-01

Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.

Use of ancillary data to improve the analysis of forest health indicators

Treesearch

Dave Gartner

2013-01-01

In addition to its standard suite of mensuration variables, the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service also collects data on forest health variables formerly measured by the Forest Health Monitoring program. FIA obtains forest health information on a subset of the base sample plots. Due to the sample size differences, the two sets of...

Variable-Size Bead Layer as Standard Reference for Endothelial Microscopes.

PubMed

Tufo, Simona; Prazzoli, Erica; Ferraro, Lorenzo; Cozza, Federica; Borghesi, Alessandro; Tavazzi, Silvia

2017-02-01

For morphometric analysis of the cell mosaic of corneal endothelium, checking accuracy and precision of instrumentation is a key step. In this study, a standard reference sample is proposed, developed to reproduce the cornea with its shape and the endothelium with its intrinsic variability in the cell size. A polystyrene bead layer (representing the endothelium) was deposited on a lens (representing the cornea). Bead diameters were 20, 25, and 30 μm (fractions in number 55%, 30%, and 15%, respectively). Bead density and hexagonality were simulated to obtain the expected true values and measured using a slit-lamp endothelial microscope applied to 1) a Takagi 700GL slit lamp at 40× magnification (recommended standard setup) and 2) a Takagi 2ZL slit lamp at 25× magnification. The simulation provided the expected bead density 2001 mm and hexagonality 47%. At 40×, density and hexagonality were measured to be 2009 mm (SD 93 mm) and 45% (SD 3%). At 25× on a different slit lamp, the comparison between measured and expected densities provided the factor 1.526 to resize the image and to use the current algorithms of the slit-lamp endothelial microscope for cell recognition. A variable-size polystyrene bead layer on a lens is proposed as a standard sample mimicking the real shape of the cornea and the variability of cell size and cell arrangement of corneal endothelium. The sample is suggested to evaluate accuracy and precision of cell density and hexagonality obtained by different endothelial microscopes, including a slit-lamp endothelial microscope applied to different slit lamps, also at different magnifications.

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator

USGS Publications Warehouse

Siers, Shane R.; Savidge, Julie A.; Reed, Robert

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam’s geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes—particularly males—in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level.

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator

PubMed Central

Siers, Shane R.; Savidge, Julie A.; Reed, Robert N.

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam’s geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes—particularly males—in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level. PMID:28570632

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator.

PubMed

Siers, Shane R; Savidge, Julie A; Reed, Robert N

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam's geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes-particularly males-in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level.

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.

Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

Using known populations of pronghorn to evaluate sampling plans and estimators

USGS Publications Warehouse

Kraft, K.M.; Johnson, D.H.; Samuelson, J.M.; Allen, S.H.

1995-01-01

Although sampling plans and estimators of abundance have good theoretical properties, their performance in real situations is rarely assessed because true population sizes are unknown. We evaluated widely used sampling plans and estimators of population size on 3 known clustered distributions of pronghorn (Antilocapra americana). Our criteria were accuracy of the estimate, coverage of 95% confidence intervals, and cost. Sampling plans were combinations of sampling intensities (16, 33, and 50%), sample selection (simple random sampling without replacement, systematic sampling, and probability proportional to size sampling with replacement), and stratification. We paired sampling plans with suitable estimators (simple, ratio, and probability proportional to size). We used area of the sampling unit as the auxiliary variable for the ratio and probability proportional to size estimators. All estimators were nearly unbiased, but precision was generally low (overall mean coefficient of variation [CV] = 29). Coverage of 95% confidence intervals was only 89% because of the highly skewed distribution of the pronghorn counts and small sample sizes, especially with stratification. Stratification combined with accurate estimates of optimal stratum sample sizes increased precision, reducing the mean CV from 33 without stratification to 25 with stratification; costs increased 23%. Precise results (mean CV = 13) but poor confidence interval coverage (83%) were obtained with simple and ratio estimators when the allocation scheme included all sampling units in the stratum containing most pronghorn. Although areas of the sampling units varied, ratio estimators and probability proportional to size sampling did not increase precision, possibly because of the clumped distribution of pronghorn. Managers should be cautious in using sampling plans and estimators to estimate abundance of aggregated populations.

Spatial Variation in Soil Properties among North American Ecosystems and Guidelines for Sampling Designs

PubMed Central

Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max

2014-01-01

Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior. PMID:24465377

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

Estimation and applications of size-based distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-based distributions arise in several contexts in forestry and ecology. Simple power relationships (e.g., basal area and diameter at breast height) between variables are one such area of interest arising from a modeling perspective. Another, probability proportional to size sampline (PPS), is found in the most widely used methods for sampling standing or dead and...

Sample size for estimating mean and coefficient of variation in species of crotalarias.

PubMed

Toebe, Marcos; Machado, Letícia N; Tartaglia, Francieli L; Carvalho, Juliana O DE; Bandeira, Cirineu T; Cargnelutti Filho, Alberto

2018-04-16

The objective of this study was to determine the sample size necessary to estimate the mean and coefficient of variation in four species of crotalarias (C. juncea, C. spectabilis, C. breviflora and C. ochroleuca). An experiment was carried out for each species during the season 2014/15. At harvest, 1,000 pods of each species were randomly collected. In each pod were measured: mass of pod with and without seeds, length, width and height of pods, number and mass of seeds per pod, and mass of hundred seeds. Measures of central tendency, variability and distribution were calculated, and the normality was verified. The sample size necessary to estimate the mean and coefficient of variation with amplitudes of the confidence interval of 95% (ACI95%) of 2%, 4%, ..., 20% was determined by resampling with replacement. The sample size varies among species and characters, being necessary a larger sample size to estimate the mean in relation of the necessary for the coefficient of variation.

Economic Analysis of a Multi-Site Prevention Program: Assessment of Program Costs and Characterizing Site-level Variability

PubMed Central

Corso, Phaedra S.; Ingels, Justin B.; Kogan, Steven M.; Foster, E. Michael; Chen, Yi-Fu; Brody, Gene H.

2013-01-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95% confidence interval) incremental difference was $2149 ($397, $3901). With the probabilistic sensitivity analysis approach, the incremental difference was $2583 ($778, $4346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention. PMID:23299559

Economic analysis of a multi-site prevention program: assessment of program costs and characterizing site-level variability.

PubMed

Corso, Phaedra S; Ingels, Justin B; Kogan, Steven M; Foster, E Michael; Chen, Yi-Fu; Brody, Gene H

2013-10-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95 % confidence interval) incremental difference was $2,149 ($397, $3,901). With the probabilistic sensitivity analysis approach, the incremental difference was $2,583 ($778, $4,346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention.

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

Simulation on Poisson and negative binomial models of count road accident modeling

NASA Astrophysics Data System (ADS)

Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.

2016-11-01

Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.

A comparison of two nano-sized particle air filtration tests in the diameter range of 10 to 400 nanometers

NASA Astrophysics Data System (ADS)

Japuntich, Daniel A.; Franklin, Luke M.; Pui, David Y.; Kuehn, Thomas H.; Kim, Seong Chan; Viner, Andrew S.

2007-01-01

Two different air filter test methodologies are discussed and compared for challenges in the nano-sized particle range of 10-400 nm. Included in the discussion are test procedure development, factors affecting variability and comparisons between results from the tests. One test system which gives a discrete penetration for a given particle size is the TSI 8160 Automated Filter tester (updated and commercially available now as the TSI 3160) manufactured by the TSI, Inc., Shoreview, MN. Another filter test system was developed utilizing a Scanning Mobility Particle Sizer (SMPS) to sample the particle size distributions downstream and upstream of an air filter to obtain a continuous percent filter penetration versus particle size curve. Filtration test results are shown for fiberglass filter paper of intermediate filtration efficiency. Test variables affecting the results of the TSI 8160 for NaCl and dioctyl phthalate (DOP) particles are discussed, including condensation particle counter stability and the sizing of the selected particle challenges. Filter testing using a TSI 3936 SMPS sampling upstream and downstream of a filter is also shown with a discussion of test variables and the need for proper SMPS volume purging and filter penetration correction procedure. For both tests, the penetration versus particle size curves for the filter media studied follow the theoretical Brownian capture model of decreasing penetration with decreasing particle diameter down to 10 nm with no deviation. From these findings, the authors can say with reasonable confidence that there is no evidence of particle thermal rebound in the size range.

Element enrichment factor calculation using grain-size distribution and functional data regression.

PubMed

Sierra, C; Ordóñez, C; Saavedra, A; Gallego, J R

2015-01-01

In environmental geochemistry studies it is common practice to normalize element concentrations in order to remove the effect of grain size. Linear regression with respect to a particular grain size or conservative element is a widely used method of normalization. In this paper, the utility of functional linear regression, in which the grain-size curve is the independent variable and the concentration of pollutant the dependent variable, is analyzed and applied to detrital sediment. After implementing functional linear regression and classical linear regression models to normalize and calculate enrichment factors, we concluded that the former regression technique has some advantages over the latter. First, functional linear regression directly considers the grain-size distribution of the samples as the explanatory variable. Second, as the regression coefficients are not constant values but functions depending on the grain size, it is easier to comprehend the relationship between grain size and pollutant concentration. Third, regularization can be introduced into the model in order to establish equilibrium between reliability of the data and smoothness of the solutions. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Ratios of total suspended solids to suspended sediment concentrations by particle size

USGS Publications Warehouse

Selbig, W.R.; Bannerman, R.T.

2011-01-01

Wet-sieving sand-sized particles from a whole storm-water sample before splitting the sample into laboratory-prepared containers can reduce bias and improve the precision of suspended-sediment concentrations (SSC). Wet-sieving, however, may alter concentrations of total suspended solids (TSS) because the analytical method used to determine TSS may not have included the sediment retained on the sieves. Measuring TSS is still commonly used by environmental managers as a regulatory metric for solids in storm water. For this reason, a new method of correlating concentrations of TSS and SSC by particle size was used to develop a series of correction factors for SSC as a means to estimate TSS. In general, differences between TSS and SSC increased with greater particle size and higher sand content. Median correction factors to SSC ranged from 0.29 for particles larger than 500m to 0.85 for particles measuring from 32 to 63m. Great variability was observed in each fraction-a result of varying amounts of organic matter in the samples. Wide variability in organic content could reduce the transferability of the correction factors. ?? 2011 American Society of Civil Engineers.

Pedagogical Simulation of Sampling Distributions and the Central Limit Theorem

ERIC Educational Resources Information Center

Hagtvedt, Reidar; Jones, Gregory Todd; Jones, Kari

2007-01-01

Students often find the fact that a sample statistic is a random variable very hard to grasp. Even more mysterious is why a sample mean should become ever more Normal as the sample size increases. This simulation tool is meant to illustrate the process, thereby giving students some intuitive grasp of the relationship between a parent population…

Power of tests of normality for detecting contaminated normal samples

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

Thode, H.C. Jr.; Smith, L.A.; Finch, S.J.

1981-01-01

Seventeen tests of normality or goodness of fit were evaluated for power at detecting a contaminated normal sample. This study used 1000 replications each of samples of size 12, 17, 25, 33, 50, and 100 from six different contaminated normal distributions. The kurtosis test was the most powerful over all sample sizes and contaminations. The Hogg and weighted Kolmogorov-Smirnov tests were second. The Kolmogorov-Smirnov, chi-squared, Anderson-Darling, and Cramer-von-Mises tests had very low power at detecting contaminated normal random variables. Tables of the power of the tests and the power curves of certain tests are given.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

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.

Analytical review based on statistics on good and poor financial performance of LPD in Bangli regency.

NASA Astrophysics Data System (ADS)

Yasa, I. B. A.; Parnata, I. K.; Susilawati, N. L. N. A. S.

2018-01-01

This study aims to apply analytical review model to analyze the influence of GCG, accounting conservatism, financial distress models and company size on good and poor financial performance of LPD in Bangli Regency. Ordinal regression analysis is used to perform analytical review, so that obtained the influence and relationship between variables to be considered further audit. Respondents in this study were LPDs in Bangli Regency, which amounted to 159 LPDs of that number 100 LPDs were determined as randomly selected samples. The test results found GCG and company size have a significant effect on both the good and poor financial performance, while the conservatism and financial distress model has no significant effect. The influence of the four variables on the overall financial performance of 58.8%, while the remaining 41.2% influenced by other variables. Size, FDM and accounting conservatism are variables, which are further recommended to be audited.

Lunar soils grain size catalog

NASA Technical Reports Server (NTRS)

Graf, John C.

1993-01-01

This catalog compiles every available grain size distribution for Apollo surface soils, trench samples, cores, and Luna 24 soils. Original laboratory data are tabled, and cumulative weight distribution curves and histograms are plotted. Standard statistical parameters are calculated using the method of moments. Photos and location comments describe the sample environment and geological setting. This catalog can help researchers describe the geotechnical conditions and site variability of the lunar surface essential to the design of a lunar base.

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

PubMed

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

2012-03-01

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

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

ERIC Educational Resources Information Center

Turgut, Sedat; Temur, Özlem Dogan

2017-01-01

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

Data splitting for artificial neural networks using SOM-based stratified sampling.

PubMed

May, R J; Maier, H R; Dandy, G C

2010-03-01

Data splitting is an important consideration during artificial neural network (ANN) development where hold-out cross-validation is commonly employed to ensure generalization. Even for a moderate sample size, the sampling methodology used for data splitting can have a significant effect on the quality of the subsets used for training, testing and validating an ANN. Poor data splitting can result in inaccurate and highly variable model performance; however, the choice of sampling methodology is rarely given due consideration by ANN modellers. Increased confidence in the sampling is of paramount importance, since the hold-out sampling is generally performed only once during ANN development. This paper considers the variability in the quality of subsets that are obtained using different data splitting approaches. A novel approach to stratified sampling, based on Neyman sampling of the self-organizing map (SOM), is developed, with several guidelines identified for setting the SOM size and sample allocation in order to minimize the bias and variance in the datasets. Using an example ANN function approximation task, the SOM-based approach is evaluated in comparison to random sampling, DUPLEX, systematic stratified sampling, and trial-and-error sampling to minimize the statistical differences between data sets. Of these approaches, DUPLEX is found to provide benchmark performance with good model performance, with no variability. The results show that the SOM-based approach also reliably generates high-quality samples and can therefore be used with greater confidence than other approaches, especially in the case of non-uniform datasets, with the benefit of scalability to perform data splitting on large datasets. Copyright 2009 Elsevier Ltd. All rights reserved.

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

PubMed Central

Vavrek, Matthew J.

2015-01-01

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

Sparse targets in hydroacoustic surveys: Balancing quantity and quality of in situ target strength data

USGS Publications Warehouse

DuFour, Mark R.; Mayer, Christine M.; Kocovsky, Patrick; Qian, Song; Warner, David M.; Kraus, Richard T.; Vandergoot, Christopher

2017-01-01

Hydroacoustic sampling of low-density fish in shallow water can lead to low sample sizes of naturally variable target strength (TS) estimates, resulting in both sparse and variable data. Increasing maximum beam compensation (BC) beyond conventional values (i.e., 3 dB beam width) can recover more targets during data analysis; however, data quality decreases near the acoustic beam edges. We identified the optimal balance between data quantity and quality with increasing BC using a standard sphere calibration, and we quantified the effect of BC on fish track variability, size structure, and density estimates of Lake Erie walleye (Sander vitreus). Standard sphere mean TS estimates were consistent with theoretical values (−39.6 dB) up to 18-dB BC, while estimates decreased at greater BC values. Natural sources (i.e., residual and mean TS) dominated total fish track variation, while contributions from measurement related error (i.e., number of single echo detections (SEDs) and BC) were proportionally low. Increasing BC led to more fish encounters and SEDs per fish, while stability in size structure and density were observed at intermediate values (e.g., 18 dB). Detection of medium to large fish (i.e., age-2+ walleye) benefited most from increasing BC, as proportional changes in size structure and density were greatest in these size categories. Therefore, when TS data are sparse and variable, increasing BC to an optimal value (here 18 dB) will maximize the TS data quantity while limiting lower-quality data near the beam edges.

The widespread misuse of effect sizes.

PubMed

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

2017-05-01

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

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

PubMed

Ozay, Guner; Seyhan, Ferda; Yilmaz, Aysun; Whitaker, Thomas B; Slate, Andrew B; Giesbrecht, Francis

2006-01-01

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

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

Massively parallel rRNA gene sequencing exacerbates the potential for biased community diversity comparisons due to variable library sizes

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

Gihring, Thomas; Green, Stefan; Schadt, Christopher Warren

2011-01-01

Technologies for massively parallel sequencing are revolutionizing microbial ecology and are vastly increasing the scale of ribosomal RNA (rRNA) gene studies. Although pyrosequencing has increased the breadth and depth of possible rRNA gene sampling, one drawback is that the number of reads obtained per sample is difficult to control. Pyrosequencing libraries typically vary widely in the number of sequences per sample, even within individual studies, and there is a need to revisit the behaviour of richness estimators and diversity indices with variable gene sequence library sizes. Multiple reports and review papers have demonstrated the bias in non-parametric richness estimators (e.g.more » Chao1 and ACE) and diversity indices when using clone libraries. However, we found that biased community comparisons are accumulating in the literature. Here we demonstrate the effects of sample size on Chao1, ACE, CatchAll, Shannon, Chao-Shen and Simpson's estimations specifically using pyrosequencing libraries. The need to equalize the number of reads being compared across libraries is reiterated, and investigators are directed towards available tools for making unbiased diversity comparisons.« less

On the absence of a correlation between population size and 'toolkit size' in ethnographic hunter-gatherers.

PubMed

Aoki, Kenichi

2018-04-05

In apparent contradiction to the theoretically predicted effect of population size on the quality/quantity of material culture, statistical analyses on ethnographic hunter-gatherers have shown an absence of correlation between population size and toolkit size. This has sparked a heated, if sometimes tangential, debate as to the usefulness of the theoretical models and as to what modes of cultural transmission humans are capable of and hunter-gatherers rely on. I review the directly relevant theoretical literature and argue that much of the confusion is caused by a mismatch between the theoretical variable and the empirical observable. I then confirm that a model incorporating the appropriate variable does predict a positive association between population size and toolkit size for random oblique, vertical, best-of- K , conformist, anticonformist, success bias and one-to-many cultural transmission, with the caveat that for all populations sampled, the population size has remained constant and toolkit size has reached the equilibrium for this population size. Finally, I suggest three theoretical scenarios, two of them involving variable population size, that would attenuate or eliminate this association and hence help to explain the empirical absence of correlation.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).

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

PubMed

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

2016-06-01

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

Sample Size Limits for Estimating Upper Level Mediation Models Using Multilevel SEM

ERIC Educational Resources Information Center

Li, Xin; Beretvas, S. Natasha

2013-01-01

This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…

Sources of variability and comparability between salmonid stomach contents and isotopic analyses: study design lessons and recommendations

USGS Publications Warehouse

Vinson, M.R.; Budy, P.

2011-01-01

We compared sources of variability and cost in paired stomach content and stable isotope samples from three salmonid species collected in September 2001–2005 and describe the relative information provided by each method in terms of measuring diet overlap and food web study design. Based on diet analyses, diet overlap among brown trout, rainbow trout, and mountain whitefish was high, and we observed little variation in diets among years. In contrast, for sample sizes n ≥ 25, 95% confidence interval (CI) around mean δ15Ν and δ13C for the three target species did not overlap, and species, year, and fish size effects were significantly different, implying that these species likely consumed similar prey but in different proportions. Stable isotope processing costs were US$12 per sample, while stomach content analysis costs averaged US$25.49 ± $2.91 (95% CI) and ranged from US$1.50 for an empty stomach to US$291.50 for a sample with 2330 items. Precision in both δ15Ν and δ13C and mean diet overlap values based on stomach contents increased considerably up to a sample size of n = 10 and plateaued around n = 25, with little further increase in precision.

Statistical Modelling of Temperature and Moisture Uptake of Biochars Exposed to Selected Relative Humidity of Air.

PubMed

Bastistella, Luciane; Rousset, Patrick; Aviz, Antonio; Caldeira-Pires, Armando; Humbert, Gilles; Nogueira, Manoel

2018-02-09

New experimental techniques, as well as modern variants on known methods, have recently been employed to investigate the fundamental reactions underlying the oxidation of biochar. The purpose of this paper was to experimentally and statistically study how the relative humidity of air, mass, and particle size of four biochars influenced the adsorption of water and the increase in temperature. A random factorial design was employed using the intuitive statistical software Xlstat. A simple linear regression model and an analysis of variance with a pairwise comparison were performed. The experimental study was carried out on the wood of Quercus pubescens , Cyclobalanopsis glauca , Trigonostemon huangmosun , and Bambusa vulgaris , and involved five relative humidity conditions (22, 43, 75, 84, and 90%), two mass samples (0.1 and 1 g), and two particle sizes (powder and piece). Two response variables including water adsorption and temperature increase were analyzed and discussed. The temperature did not increase linearly with the adsorption of water. Temperature was modeled by nine explanatory variables, while water adsorption was modeled by eight. Five variables, including factors and their interactions, were found to be common to the two models. Sample mass and relative humidity influenced the two qualitative variables, while particle size and biochar type only influenced the temperature.

Using the Sampling Margin of Error to Assess the Interpretative Validity of Student Evaluations of Teaching

ERIC Educational Resources Information Center

James, David E.; Schraw, Gregory; Kuch, Fred

2015-01-01

We present an equation, derived from standard statistical theory, that can be used to estimate sampling margin of error for student evaluations of teaching (SETs). We use the equation to examine the effect of sample size, response rates and sample variability on the estimated sampling margin of error, and present results in four tables that allow…

Random Distribution Pattern and Non-adaptivity of Genome Size in a Highly Variable Population of Festuca pallens

PubMed Central

Šmarda, Petr; Bureš, Petr; Horová, Lucie

2007-01-01

Background and Aims The spatial and statistical distribution of genome sizes and the adaptivity of genome size to some types of habitat, vegetation or microclimatic conditions were investigated in a tetraploid population of Festuca pallens. The population was previously documented to vary highly in genome size and is assumed as a model for the study of the initial stages of genome size differentiation. Methods Using DAPI flow cytometry, samples were measured repeatedly with diploid Festuca pallens as the internal standard. Altogether 172 plants from 57 plots (2·25 m2), distributed in contrasting habitats over the whole locality in South Moravia, Czech Republic, were sampled. The differences in DNA content were confirmed by the double peaks of simultaneously measured samples. Key Results At maximum, a 1·115-fold difference in genome size was observed. The statistical distribution of genome sizes was found to be continuous and best fits the extreme (Gumbel) distribution with rare occurrences of extremely large genomes (positive-skewed), as it is similar for the log-normal distribution of the whole Angiosperms. Even plants from the same plot frequently varied considerably in genome size and the spatial distribution of genome sizes was generally random and unautocorrelated (P > 0·05). The observed spatial pattern and the overall lack of correlations of genome size with recognized vegetation types or microclimatic conditions indicate the absence of ecological adaptivity of genome size in the studied population. Conclusions These experimental data on intraspecific genome size variability in Festuca pallens argue for the absence of natural selection and the selective non-significance of genome size in the initial stages of genome size differentiation, and corroborate the current hypothetical model of genome size evolution in Angiosperms (Bennetzen et al., 2005, Annals of Botany 95: 127–132). PMID:17565968

A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification.

PubMed

Jiang, Wenyu; Simon, Richard

2007-12-20

This paper first provides a critical review on some existing methods for estimating the prediction error in classifying microarray data where the number of genes greatly exceeds the number of specimens. Special attention is given to the bootstrap-related methods. When the sample size n is small, we find that all the reviewed methods suffer from either substantial bias or variability. We introduce a repeated leave-one-out bootstrap (RLOOB) method that predicts for each specimen in the sample using bootstrap learning sets of size ln. We then propose an adjusted bootstrap (ABS) method that fits a learning curve to the RLOOB estimates calculated with different bootstrap learning set sizes. The ABS method is robust across the situations we investigate and provides a slightly conservative estimate for the prediction error. Even with small samples, it does not suffer from large upward bias as the leave-one-out bootstrap and the 0.632+ bootstrap, and it does not suffer from large variability as the leave-one-out cross-validation in microarray applications. Copyright (c) 2007 John Wiley & Sons, Ltd.

Intraspecific variability in the life histories of endemic coral-reef fishes between photic and mesophotic depths across the Central Pacific Ocean

NASA Astrophysics Data System (ADS)

Winston, M. S.; Taylor, B. M.; Franklin, E. C.

2017-06-01

Mesophotic coral ecosystems (MCEs) represent the lowest depth distribution inhabited by many coral reef-associated organisms. Research on fishes associated with MCEs is sparse, leading to a critical lack of knowledge of how reef fish found at mesophotic depths may vary from their shallow reef conspecifics. We investigated intraspecific variability in body condition and growth of three Hawaiian endemics collected from shallow, photic reefs (5-33 m deep) and MCEs (40-75 m) throughout the Hawaiian Archipelago and Johnston Atoll: the detritivorous goldring surgeonfish, Ctenochaetus strigosus, and the planktivorous threespot chromis, Chromis verater, and Hawaiian dascyllus, Dascyllus albisella. Estimates of body condition and size-at-age varied between shallow and mesophotic depths; however, these demographic differences were outweighed by the magnitude of variability found across the latitudinal gradient of locations sampled within the Central Pacific. Body condition and maximum body size were lowest in samples collected from shallow and mesophotic Johnston Atoll sites, with no difference occurring between depths. Samples from the Northwestern Hawaiian Islands tended to have the highest body condition and reached the largest body sizes, with differences between shallow and mesophotic sites highly variable among species. The findings of this study support newly emerging research demonstrating intraspecific variability in the life history of coral-reef fish species whose distributions span shallow and mesophotic reefs. This suggests not only that the conservation and fisheries management should take into consideration differences in the life histories of reef-fish populations across spatial scales, but also that information derived from studies of shallow fishes be applied with caution to conspecific populations in mesophotic coral environments.

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).

Single and simultaneous binary mergers in Wright-Fisher genealogies.

PubMed

Melfi, Andrew; Viswanath, Divakar

2018-05-01

The Kingman coalescent is a commonly used model in genetics, which is often justified with reference to the Wright-Fisher (WF) model. Current proofs of convergence of WF and other models to the Kingman coalescent assume a constant sample size. However, sample sizes have become quite large in human genetics. Therefore, we develop a convergence theory that allows the sample size to increase with population size. If the haploid population size is N and the sample size is N 1∕3-ϵ , ϵ>0, we prove that Wright-Fisher genealogies involve at most a single binary merger in each generation with probability converging to 1 in the limit of large N. Single binary merger or no merger in each generation of the genealogy implies that the Kingman partition distribution is obtained exactly. If the sample size is N 1∕2-ϵ , Wright-Fisher genealogies may involve simultaneous binary mergers in a single generation but do not involve triple mergers in the large N limit. The asymptotic theory is verified using numerical calculations. Variable population sizes are handled algorithmically. It is found that even distant bottlenecks can increase the probability of triple mergers as well as simultaneous binary mergers in WF genealogies. Copyright © 2018 Elsevier Inc. All rights reserved.

Effects of lidar pulse density and sample size on a model-assisted approach to estimate forest inventory variables

Treesearch

Jacob Strunk; Hailemariam Temesgen; Hans-Erik Andersen; James P. Flewelling; Lisa Madsen

2012-01-01

Using lidar in an area-based model-assisted approach to forest inventory has the potential to increase estimation precision for some forest inventory variables. This study documents the bias and precision of a model-assisted (regression estimation) approach to forest inventory with lidar-derived auxiliary variables relative to lidar pulse density and the number of...

Merging National Forest and National Forest Health Inventories to Obtain an Integrated Forest Resource Inventory – Experiences from Bavaria, Slovenia and Sweden

PubMed Central

Kovač, Marko; Bauer, Arthur; Ståhl, Göran

2014-01-01

Backgrounds, Material and Methods To meet the demands of sustainable forest management and international commitments, European nations have designed a variety of forest-monitoring systems for specific needs. While the majority of countries are committed to independent, single-purpose inventorying, a minority of countries have merged their single-purpose forest inventory systems into integrated forest resource inventories. The statistical efficiencies of the Bavarian, Slovene and Swedish integrated forest resource inventory designs are investigated with the various statistical parameters of the variables of growing stock volume, shares of damaged trees, and deadwood volume. The parameters are derived by using the estimators for the given inventory designs. The required sample sizes are derived via the general formula for non-stratified independent samples and via statistical power analyses. The cost effectiveness of the designs is compared via two simple cost effectiveness ratios. Results In terms of precision, the most illustrative parameters of the variables are relative standard errors; their values range between 1% and 3% if the variables’ variations are low (s%<80%) and are higher in the case of higher variations. A comparison of the actual and required sample sizes shows that the actual sample sizes were deliberately set high to provide precise estimates for the majority of variables and strata. In turn, the successive inventories are statistically efficient, because they allow detecting the mean changes of variables with powers higher than 90%; the highest precision is attained for the changes of growing stock volume and the lowest for the changes of the shares of damaged trees. Two indicators of cost effectiveness also show that the time input spent for measuring one variable decreases with the complexity of inventories. Conclusion There is an increasing need for credible information on forest resources to be used for decision making and national and international policy making. Such information can be cost-efficiently provided through integrated forest resource inventories. PMID:24941120

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Role of sediment size and biostratinomy on the development of biofilms in recent avian vertebrate remains

NASA Astrophysics Data System (ADS)

Peterson, Joseph E.; Lenczewski, Melissa E.; Clawson, Steven R.; Warnock, Jonathan P.

2017-04-01

Microscopic soft tissues have been identified in fossil vertebrate remains collected from various lithologies. However, the diagenetic mechanisms to preserve such tissues have remained elusive. While previous studies have described infiltration of biofilms in Haversian and Volkmann’s canals, biostratinomic alteration (e.g., trampling), and iron derived from hemoglobin as playing roles in the preservation processes, the influence of sediment texture has not previously been investigated. This study uses a Kolmogorov Smirnov Goodness-of-Fit test to explore the influence of biostratinomic variability and burial media against the infiltration of biofilms in bone samples. Controlled columns of sediment with bone samples were used to simulate burial and subsequent groundwater flow. Sediments used in this study include clay-, silt-, and sand-sized particles modeled after various fluvial facies commonly associated with fossil vertebrates. Extant limb bone samples obtained from Gallus gallus domesticus (Domestic Chicken) buried in clay-rich sediment exhibit heavy biofilm infiltration, while bones buried in sands and silts exhibit moderate levels. Crushed bones exhibit significantly lower biofilm infiltration than whole bone samples. Strong interactions between biostratinomic alteration and sediment size are also identified with respect to biofilm development. Sediments modeling crevasse splay deposits exhibit considerable variability; whole-bone crevasse splay samples exhibit higher frequencies of high-level biofilm infiltration, and crushed-bone samples in modeled crevasse splay deposits display relatively high frequencies of low-level biofilm infiltration. These results suggest that sediment size, depositional setting, and biostratinomic condition play key roles in biofilm infiltration in vertebrate remains, and may influence soft tissue preservation in fossil vertebrates.

Framework for making better predictions by directly estimating variables' predictivity.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2016-12-13

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the [Formula: see text]-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the [Formula: see text]-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the [Formula: see text]-score on real data to demonstrate the statistic's predictive performance on sample data. We conjecture that using the partition retention and [Formula: see text]-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired.

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.

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

PubMed

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

2008-08-28

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

Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

PubMed

Morgan, Timothy M; Case, L Douglas

2013-07-05

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

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character. 

Semantic size does not matter: "bigger" words are not recognized faster.

PubMed

Kang, Sean H K; Yap, Melvin J; Tse, Chi-Shing; Kurby, Christopher A

2011-06-01

Sereno, O'Donnell, and Sereno (2009) reported that words are recognized faster in a lexical decision task when their referents are physically large than when they are small, suggesting that "semantic size" might be an important variable that should be considered in visual word recognition research and modelling. We sought to replicate their size effect, but failed to find a significant latency advantage in lexical decision for "big" words (cf. "small" words), even though we used the same word stimuli as Sereno et al. and had almost three times as many subjects. We also examined existing data from visual word recognition megastudies (e.g., English Lexicon Project) and found that semantic size is not a significant predictor of lexical decision performance after controlling for the standard lexical variables. In summary, the null results from our lab experiment--despite a much larger subject sample size than Sereno et al.--converged with our analysis of megastudy lexical decision performance, leading us to conclude that semantic size does not matter for word recognition. Discussion focuses on why semantic size (unlike some other semantic variables) is unlikely to play a role in lexical decision.

A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Blum, Linda K.; McComb, Alison C.; Mills, Aaron L.

2002-01-01

Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Passive Sampling to Capture the Spatial Variability of Coarse Particles by Composition in Cleveland, OH

EPA Science Inventory

Passive samplers deployed at 25 sites for three week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM_10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles deter...

Omnibus Tests for Interactions in Repeated Measures Designs with Dichotomous Dependent Variables.

ERIC Educational Resources Information Center

Serlin, Ronald C.; Marascuilo, Leonard A.

When examining a repeated measures design with independent groups for a significant group by trial interaction, classical analysis of variance or multivariate procedures can be used if the assumptions underlying the tests are met. Neither procedure may be justified for designs with small sample sizes and dichotomous dependent variables. An omnibus…

Effects of Missing Data Methods in SEM under Conditions of Incomplete and Nonnormal Data

ERIC Educational Resources Information Center

Li, Jian; Lomax, Richard G.

2017-01-01

Using Monte Carlo simulations, this research examined the performance of four missing data methods in SEM under different multivariate distributional conditions. The effects of four independent variables (sample size, missing proportion, distribution shape, and factor loading magnitude) were investigated on six outcome variables: convergence rate,…

L2 Reading Comprehension and Its Correlates: A Meta-Analysis

ERIC Educational Resources Information Center

Jeon, Eun Hee; Yamashita, Junko

2014-01-01

The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…

Robustness-Based Design Optimization Under Data Uncertainty

NASA Technical Reports Server (NTRS)

Zaman, Kais; McDonald, Mark; Mahadevan, Sankaran; Green, Lawrence

2010-01-01

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

USGS Publications Warehouse

Kumar, S.; Simonson, S.E.; Stohlgren, T.J.

2009-01-01

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 ?? 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike's Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions. ?? 2008 Springer Science+Business Media B.V.

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

NASA Astrophysics Data System (ADS)

Lusiana, Evellin Dewi

2017-12-01

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

Framework for making better predictions by directly estimating variables’ predictivity

PubMed Central

Chernoff, Herman; Lo, Shaw-Hwa

2016-01-01

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the I-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the I-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data. We conjecture that using the partition retention and I-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired. PMID:27911830

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

PubMed Central

2006-01-01

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

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

Conducting Three-Level Longitudinal Analyses

ERIC Educational Resources Information Center

Peugh, James L.; Heck, Ronald H.

2017-01-01

Researchers in the field of early adolescence interested in quantifying the environmental influences on a response variable of interest over time would use cluster sampling (i.e., obtaining repeated measures from students nested within classrooms and/or schools) to obtain the needed sample size. The resulting longitudinal data would be nested at…

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

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

PubMed

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

2013-08-01

The method used to determine choice of standard deviation (SD) is inadequately reported in clinical trials. Underestimations of the population SD may result in underpowered clinical trials. This study demonstrates how using the wrong method to determine population SD can lead to inaccurate sample sizes and underpowered studies, and offers recommendations to maximize the likelihood of achieving adequate statistical power. We review the practice of reporting sample size and its effect on the power of trials published in major journals. Simulated clinical trials were used to compare the effects of different methods of determining SD on power and sample size calculations. Prior to 1996, sample size calculations were reported in just 1%-42% of clinical trials. This proportion increased from 38% to 54% after the initial Consolidated Standards of Reporting Trials (CONSORT) was published in 1996, and from 64% to 95% after the revised CONSORT was published in 2001. Nevertheless, underpowered clinical trials are still common. Our simulated data showed that all minimal and 25th-percentile SDs fell below 44 (the population SD), regardless of sample size (from 5 to 50). For sample sizes 5 and 50, the minimum sample SDs underestimated the population SD by 90.7% and 29.3%, respectively. If only one sample was available, there was less than 50% chance that the actual power equaled or exceeded the planned power of 80% for detecting a median effect size (Cohen's d = 0.5) when using the sample SD to calculate the sample size. The proportions of studies with actual power of at least 80% were about 95%, 90%, 85%, and 80% when we used the larger SD, 80% upper confidence limit (UCL) of SD, 70% UCL of SD, and 60% UCL of SD to calculate the sample size, respectively. When more than one sample was available, the weighted average SD resulted in about 50% of trials being underpowered; the proportion of trials with power of 80% increased from 90% to 100% when the 75th percentile and the maximum SD from 10 samples were used. Greater sample size is needed to achieve a higher proportion of studies having actual power of 80%. This study only addressed sample size calculation for continuous outcome variables. We recommend using the 60% UCL of SD, maximum SD, 80th-percentile SD, and 75th-percentile SD to calculate sample size when 1 or 2 samples, 3 samples, 4-5 samples, and more than 5 samples of data are available, respectively. Using the sample SD or average SD to calculate sample size should be avoided.

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%.

A Q-GERT Model for Determining the Maintenance Crew Size for the SAC command Post Upgrade

DTIC Science & Technology

1983-12-01

time that an equiprment fails. DAY3 A real variable corresponding to the day that an LRU is removed from the equipment. DAY4 A real variable...variable corresponding to the time that an LRU is repaired. TIM5 A real variable corresponaing to Lhe time that an equipment returns to service. TNOW...The current time . UF(IFN) User function IFN. UN(I) A sample from the uniform distri- bution defined by parameter set I. YIlN1 A real variable

Factors Affecting the Adoption of R&D Project Selection Techniques at the Air Force Wright Aeronautical Laboratories

DTIC Science & Technology

1988-09-01

tested. To measure 42 the adequacy of the sample, the Kaiser - Meyer - Olkin measure of sampling adequacy was used. This technique is described in Factor...40 4- 0 - 7 0 0 07 -58d the relatively large number of variables, there was concern about the adequacy of the sample size. A Kaiser - Meyer - Olkin

Evaluation of response variables in computer-simulated virtual cataract surgery

NASA Astrophysics Data System (ADS)

Söderberg, Per G.; Laurell, Carl-Gustaf; Simawi, Wamidh; Nordqvist, Per; Skarman, Eva; Nordh, Leif

2006-02-01

We have developed a virtual reality (VR) simulator for phacoemulsification (phaco) surgery. The current work aimed at evaluating the precision in the estimation of response variables identified for measurement of the performance of VR phaco surgery. We identified 31 response variables measuring; the overall procedure, the foot pedal technique, the phacoemulsification technique, erroneous manipulation, and damage to ocular structures. Totally, 8 medical or optometry students with a good knowledge of ocular anatomy and physiology but naive to cataract surgery performed three sessions each of VR Phaco surgery. For measurement, the surgical procedure was divided into a sculpting phase and an evacuation phase. The 31 response variables were measured for each phase in all three sessions. The variance components for individuals and iterations of sessions within individuals were estimated with an analysis of variance assuming a hierarchal model. The consequences of estimated variabilities for sample size requirements were determined. It was found that generally there was more variability for iterated sessions within individuals for measurements of the sculpting phase than for measurements of the evacuation phase. This resulted in larger required sample sizes for detection of difference between independent groups or change within group, for the sculpting phase as compared to for the evacuation phase. It is concluded that several of the identified response variables can be measured with sufficient precision for evaluation of VR phaco surgery.

Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…

Determination of complex electromechanical coefficients for piezoelectric materials

NASA Astrophysics Data System (ADS)

Du, Xiao-Hong

Sugar maple decline, a result of many possible biotic and abiotic causes, has been a problem in northern Pennsylvania since the early 1980s. Several studies have focused on specific causes, yet few have tried to look at a wide array. The purpose of this research was to investigate stresses in sugar maple forest plots in northern Pennsylvania. Three studies were undertaken. The first study examined the spatial extent of sugar maple on 248 plots in Bailey's ecoregions 212F and 212G, which are glaciated and unglaciated regions, respectively. In addition, a health assessment of sugar maple in Pennsylvania was made, with a resulting separation in population between healthy and unhealthy stands occurring at 20 percent dead sugar maple basal area. The second study was conducted to evaluate a statistical sampling design of 28 forested plots, from the above studies population of plots (248), and to provide data on physical and chemical soil variability and sample size estimation for other researchers. The variability of several soil parameters was examined within plots and between health classes of sugar maple and sample size estimations were derived for these populations. The effect of log-normal transformations on reducing variability and sample sizes was examined and soil descriptions of the plots sampled in 1998 were compared to the USDA Soil Survey mapping unit series descriptions for the plot location. Lastly, the effect of sampling intensity on the detection of significant differences between health class treatments was examined. The last study addressed sugar maple decline in northern Pennsylvania during the same period as the first study (approximately 1979-1989) but on 28 plots chosen from the first studies population. These were the same plots used in the second study on soil variability. Recent literature on sugar maple decline has focused on specific causes and few have tried to look at a wide array. This paper investigates stresses in sugar maple plots related to moisture and how these interact with other stresses such as chemistry, insect defoliation, geology, aspect, slope, topography, and atmospheric deposition.

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.

Drivers and Spatio-Temporal Extent of Hyporheic Patch Variation: Implications for Sampling

PubMed Central

Braun, Alexander; Auerswald, Karl; Geist, Juergen

2012-01-01

The hyporheic zone in stream ecosystems is a heterogeneous key habitat for species across many taxa. Consequently, it attracts high attention among freshwater scientists, but generally applicable guidelines on sampling strategies are lacking. Thus, the objective of this study was to develop and validate such sampling guidelines. Applying geostatistical analysis, we quantified the spatio-temporal variability of parameters, which characterize the physico-chemical substratum conditions in the hyporheic zone. We investigated eight stream reaches in six small streams that are typical for the majority of temperate areas. Data was collected on two occasions in six stream reaches (development data), and once in two additional reaches, after one year (validation data). In this study, the term spatial variability refers to patch contrast (patch to patch variance) and patch size (spatial extent of a patch). Patch contrast of hyporheic parameters (specific conductance, pH and dissolved oxygen) increased with macrophyte cover (r2 = 0.95, p<0.001), while patch size of hyporheic parameters decreased from 6 to 2 m with increasing sinuosity of the stream course (r2 = 0.91, p<0.001), irrespective of the time of year. Since the spatial variability of hyporheic parameters varied between stream reaches, our results suggest that sampling design should be adapted to suit specific stream reaches. The distance between sampling sites should be inversely related to the sinuosity, while the number of samples should be related to macrophyte cover. PMID:22860053

Influence of BMI and dietary restraint on self-selected portions of prepared meals in US women.

PubMed

Labbe, David; Rytz, Andréas; Brunstrom, Jeffrey M; Forde, Ciarán G; Martin, Nathalie

2017-04-01

The rise of obesity prevalence has been attributed in part to an increase in food and beverage portion sizes selected and consumed among overweight and obese consumers. Nevertheless, evidence from observations of adults is mixed and contradictory findings might reflect the use of small or unrepresentative samples. The objective of this study was i) to determine the extent to which BMI and dietary restraint predict self-selected portion sizes for a range of commercially available prepared savoury meals and ii) to consider the importance of these variables relative to two previously established predictors of portion selection, expected satiation and expected liking. A representative sample of female consumers (N = 300, range 18-55 years) evaluated 15 frozen savoury prepared meals. For each meal, participants rated their expected satiation and expected liking, and selected their ideal portion using a previously validated computer-based task. Dietary restraint was quantified using the Dutch Eating Behaviour Questionnaire (DEBQ-R). Hierarchical multiple regression was performed on self-selected portions with age, hunger level, and meal familiarity entered as control variables in the first step of the model, expected satiation and expected liking as predictor variables in the second step, and DEBQ-R and BMI as exploratory predictor variables in the third step. The second and third steps significantly explained variance in portion size selection (18% and 4%, respectively). Larger portion selections were significantly associated with lower dietary restraint and with lower expected satiation. There was a positive relationship between BMI and portion size selection (p = 0.06) and between expected liking and portion size selection (p = 0.06). Our discussion considers future research directions, the limited variance explained by our model, and the potential for portion size underreporting by overweight participants. Copyright © 2016 Nestec S.A. Published by Elsevier Ltd.. All rights reserved.

Evaluation of sampling plans to detect Cry9C protein in corn flour and meal.

PubMed

Whitaker, Thomas B; Trucksess, Mary W; Giesbrecht, Francis G; Slate, Andrew B; Thomas, Francis S

2004-01-01

StarLink is a genetically modified corn that produces an insecticidal protein, Cry9C. Studies were conducted to determine the variability and Cry9C distribution among sample test results when Cry9C protein was estimated in a bulk lot of corn flour and meal. Emphasis was placed on measuring sampling and analytical variances associated with each step of the test procedure used to measure Cry9C in corn flour and meal. Two commercially available enzyme-linked immunosorbent assay kits were used: one for the determination of Cry9C protein concentration and the other for % StarLink seed. The sampling and analytical variances associated with each step of the Cry9C test procedures were determined for flour and meal. Variances were found to be functions of Cry9C concentration, and regression equations were developed to describe the relationships. Because of the larger particle size, sampling variability associated with cornmeal was about double that for corn flour. For cornmeal, the sampling variance accounted for 92.6% of the total testing variability. The observed sampling and analytical distributions were compared with the Normal distribution. In almost all comparisons, the null hypothesis that the Cry9C protein values were sampled from a Normal distribution could not be rejected at 95% confidence limits. The Normal distribution and the variance estimates were used to evaluate the performance of several Cry9C protein sampling plans for corn flour and meal. Operating characteristic curves were developed and used to demonstrate the effect of increasing sample size on reducing false positives (seller's risk) and false negatives (buyer's risk).

Comparison of structural and least-squares lines for estimating geologic relations

USGS Publications Warehouse

Williams, G.P.; Troutman, B.M.

1990-01-01

Two different goals in fitting straight lines to data are to estimate a "true" linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating "true" straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal-predicting the dependent variable-OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples. ?? 1990 International Association for Mathematical Geology.

Exploring the variability of aerosol particle composition in the Arctic: a study from the springtime ACCACIA campaign

NASA Astrophysics Data System (ADS)

Young, G.; Jones, H. M.; Darbyshire, E.; Baustian, K. J.; McQuaid, J. B.; Bower, K. N.; Connolly, P. J.; Gallagher, M. W.; Choularton, T. W.

2015-10-01

Single-particle compositional analysis of filter samples collected on-board the FAAM BAe-146 aircraft is presented for six flights during the springtime Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign (March-April 2013). Scanning electron microscopy was utilised to derive size distributions and size-segregated particle compositions. These data were compared to corresponding data from wing-mounted optical particle counters and reasonable agreement between the calculated number size distributions was found. Significant variability in composition was observed, with differing external and internal mixing identified, between air mass trajectory cases based on HYSPLIT analyses. Dominant particle classes were silicate-based dusts and sea salts, with particles notably rich in K and Ca detected in one case. Source regions varied from the Arctic Ocean and Greenland through to northern Russia and the European continent. Good agreement between the back trajectories was mirrored by comparable compositional trends between samples. Silicate dusts were identified in all cases, and the elemental composition of the dust was consistent for all samples except one. It is hypothesised that long-range, high-altitude transport was primarily responsible for this dust, with likely sources including the Asian arid regions.

Exploring the full natural variability of eruption sizes within probabilistic hazard assessment of tephra dispersal

NASA Astrophysics Data System (ADS)

Selva, Jacopo; Sandri, Laura; Costa, Antonio; Tonini, Roberto; Folch, Arnau; Macedonio, Giovanni

2014-05-01

The intrinsic uncertainty and variability associated to the size of next eruption strongly affects short to long-term tephra hazard assessment. Often, emergency plans are established accounting for the effects of one or a few representative scenarios (meant as a specific combination of eruptive size and vent position), selected with subjective criteria. On the other hand, probabilistic hazard assessments (PHA) consistently explore the natural variability of such scenarios. PHA for tephra dispersal needs the definition of eruptive scenarios (usually by grouping possible eruption sizes and vent positions in classes) with associated probabilities, a meteorological dataset covering a representative time period, and a tephra dispersal model. PHA results from combining simulations considering different volcanological and meteorological conditions through a weight given by their specific probability of occurrence. However, volcanological parameters, such as erupted mass, eruption column height and duration, bulk granulometry, fraction of aggregates, typically encompass a wide range of values. Because of such a variability, single representative scenarios or size classes cannot be adequately defined using single values for the volcanological inputs. Here we propose a method that accounts for this within-size-class variability in the framework of Event Trees. The variability of each parameter is modeled with specific Probability Density Functions, and meteorological and volcanological inputs are chosen by using a stratified sampling method. This procedure allows avoiding the bias introduced by selecting single representative scenarios and thus neglecting most of the intrinsic eruptive variability. When considering within-size-class variability, attention must be paid to appropriately weight events falling within the same size class. While a uniform weight to all the events belonging to a size class is the most straightforward idea, this implies a strong dependence on the thresholds dividing classes: under this choice, the largest event of a size class has a much larger weight than the smallest event of the subsequent size class. In order to overcome this problem, in this study, we propose an innovative solution able to smoothly link the weight variability within each size class to the variability among the size classes through a common power law, and, simultaneously, respect the probability of different size classes conditional to the occurrence of an eruption. Embedding this procedure into the Bayesian Event Tree scheme enables for tephra fall PHA, quantified through hazard curves and maps representing readable results applicable in planning risk mitigation actions, and for the quantification of its epistemic uncertainties. As examples, we analyze long-term tephra fall PHA at Vesuvius and Campi Flegrei. We integrate two tephra dispersal models (the analytical HAZMAP and the numerical FALL3D) into BET_VH. The ECMWF reanalysis dataset are used for exploring different meteorological conditions. The results obtained clearly show that PHA accounting for the whole natural variability significantly differs from that based on a representative scenarios, as in volcanic hazard common practice.

Classification of ROTSE Variable Stars using Machine Learning

NASA Astrophysics Data System (ADS)

Wozniak, P. R.; Akerlof, C.; Amrose, S.; Brumby, S.; Casperson, D.; Gisler, G.; Kehoe, R.; Lee, B.; Marshall, S.; McGowan, K. E.; McKay, T.; Perkins, S.; Priedhorsky, W.; Rykoff, E.; Smith, D. A.; Theiler, J.; Vestrand, W. T.; Wren, J.; ROTSE Collaboration

2001-12-01

We evaluate several Machine Learning algorithms as potential tools for automated classification of variable stars. Using the ROTSE sample of ~1800 variables from a pilot study of 5% of the whole sky, we compare the effectiveness of a supervised technique (Support Vector Machines, SVM) versus unsupervised methods (K-means and Autoclass). There are 8 types of variables in the sample: RR Lyr AB, RR Lyr C, Delta Scuti, Cepheids, detached eclipsing binaries, contact binaries, Miras and LPVs. Preliminary results suggest a very high ( ~95%) efficiency of SVM in isolating a few best defined classes against the rest of the sample, and good accuracy ( ~70-75%) for all classes considered simultaneously. This includes some degeneracies, irreducible with the information at hand. Supervised methods naturally outperform unsupervised methods, in terms of final error rate, but unsupervised methods offer many advantages for large sets of unlabeled data. Therefore, both types of methods should be considered as promising tools for mining vast variability surveys. We project that there are more than 30,000 periodic variables in the ROTSE-I data base covering the entire local sky between V=10 and 15.5 mag. This sample size is already stretching the time capabilities of human analysts.

Sediment loads and transport at constructed chutes along the Missouri River - Upper Hamburg Chute near Nebraska City, Nebraska, and Kansas Chute near Peru, Nebraska

USGS Publications Warehouse

Densmore, Brenda K.; Rus, David L.; Moser, Matthew T.; Hall, Brent M.; Andersen, Michael J.

2016-02-04

Comparisons of concentrations and loads from EWI samples collected from different transects within a study site resulted in few significant differences, but comparisons are limited by small sample sizes and large within-transect variability. When comparing the Missouri River upstream transect to the chute inlet transect, similar results were determined in 2012 as were determined in 2008—the chute inlet affected the amount of sediment entering the chute from the main channel. In addition, the Kansas chute is potentially affecting the sediment concentration within the Missouri River main channel, but small sample size and construction activities within the chute limit the ability to fully understand either the effect of the chute in 2012 or the effect of the chute on the main channel during a year without construction. Finally, some differences in SSC were detected between the Missouri River upstream transects and the chute downstream transects; however, the effect of the chutes on the Missouri River main-channel sediment transport was difficult to isolate because of construction activities and sampling variability.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

PubMed

Yang, Lun; Price, Elvin T; Chang, Ching-Wei; Li, Yan; Huang, Ying; Guo, Li-Wu; Guo, Yongli; Kaput, Jim; Shi, Leming; Ning, Baitang

2013-01-01

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

State-space modeling of population sizes and trends in Nihoa Finch and Millerbird

USGS Publications Warehouse

Gorresen, P. Marcos; Brinck, Kevin W.; Camp, Richard J.; Farmer, Chris; Plentovich, Sheldon M.; Banko, Paul C.

2016-01-01

Both of the 2 passerines endemic to Nihoa Island, Hawai‘i, USA—the Nihoa Millerbird (Acrocephalus familiaris kingi) and Nihoa Finch (Telespiza ultima)—are listed as endangered by federal and state agencies. Their abundances have been estimated by irregularly implemented fixed-width strip-transect sampling from 1967 to 2012, from which area-based extrapolation of the raw counts produced highly variable abundance estimates for both species. To evaluate an alternative survey method and improve abundance estimates, we conducted variable-distance point-transect sampling between 2010 and 2014. We compared our results to those obtained from strip-transect samples. In addition, we applied state-space models to derive improved estimates of population size and trends from the legacy time series of strip-transect counts. Both species were fairly evenly distributed across Nihoa and occurred in all or nearly all available habitat. Population trends for Nihoa Millerbird were inconclusive because of high within-year variance. Trends for Nihoa Finch were positive, particularly since the early 1990s. Distance-based analysis of point-transect counts produced mean estimates of abundance similar to those from strip-transects but was generally more precise. However, both survey methods produced biologically unrealistic variability between years. State-space modeling of the long-term time series of abundances obtained from strip-transect counts effectively reduced uncertainty in both within- and between-year estimates of population size, and allowed short-term changes in abundance trajectories to be smoothed into a long-term trend.

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

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

PubMed

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

2006-01-01

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

Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life

NASA Technical Reports Server (NTRS)

Vlcek, Brian L.; Zaretsky, Erwin V.; Hendricks, Robert C.

2008-01-01

Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.

Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life

NASA Technical Reports Server (NTRS)

Vlcek, Brian L.; Zaretsky, Erwin V.; Hendricks, Robert C.

2012-01-01

Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.

A Systematic Review of the Relationship between Familism and Mental Health Outcomes in Latino Population

PubMed Central

Valdivieso-Mora, Esmeralda; Peet, Casie L.; Garnier-Villarreal, Mauricio; Salazar-Villanea, Monica; Johnson, David K.

2016-01-01

Background: Familismo or familism is a cultural value frequently seen in Hispanic cultures, in which a higher emphasis is placed on the family unit in terms of respect, support, obligation, and reference. Familism has been implicated as a protective factor against mental health problems and may foster the growth and development of children. This study aims at measuring the size of the relationship between familism and mental health outcomes of depression, suicide, substance abuse, internalizing, and externalizing behaviors. Methods: Thirty-nine studies were systematically reviewed to assess the relationship between familism and mental health outcomes. Data from the studies were comprised and organized into five categories: depression, suicide, internalizing symptoms, externalizing symptoms, and substance use. The Cohen's d of each value (dependent variable in comparison to familism) was calculated. Results were weighted based on sample sizes (n) and total effect sizes were then calculated. It was hypothesized that there would be a large effect size in the relationship between familism and depression, suicide, internalizing, and externalizing symptoms and substance use in Hispanics. Results: The meta-analysis showed small effect sizes in the relationship between familism and depression, suicide and internalizing behaviors. And no significant effects for substance abuse and externalizing behaviors. Discussion: The small effects found in this study may be explained by the presence of moderator variables between familism and mental health outcomes (e.g., communication within the family). In addition, variability in the Latino samples and in the measurements used might explain the small and non-significant effects found. PMID:27826269

Microwave Heating of Crystals with Gold Nanoparticles and Synovial Fluid under Synthetic Skin Patches

PubMed Central

2017-01-01

Gout is a disease with elusive treatment options. Reduction of the size of l-alanine crystals as a model crystal for gouty tophi with the use of a monomode solid-state microwave was examined as a possible therapeutic aid. The effect of microwave heating on l-alanine crystals in the presence of gold nanoparticles (Au NPs) in solution and synovial fluid (SF) in a plastic pouch through a synthetic skin patch was investigated. In this regard, three experimental paradigms were employed: Paradigm 1 includes the effect of variable microwave power (5–10 W) and variable heating time (5–60 s) and Au NPs in water (20 nm size, volume of 10 μL) in a plastic pouch (1 × 2 cm2 in size). Paradigm 2 includes the effect of a variable volume of 20 nm Au NPs in a variable volume of SF up to 100 μL in a plastic pouch at a constant microwave power (10 W) for 30 s. Paradigm 3 includes the effect of constant microwave power (10 W) and microwave heating time (30 s), constant volume of Au NPs (100 μL), and variable size of Au NPs (20–200 nm) placed in a plastic pouch through a synthetic skin patch. In these experiments, an average of 60–100% reduction in the size of an l-alanine crystal (initial size = 450 μm) without damage to the synthetic skin or increasing the temperature of the samples beyond the physiological range was reported. PMID:28983527

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

PubMed

McShane, Blakeley B; Böckenholt, Ulf

2014-11-01

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

Using small area estimation and Lidar-derived variables for multivariate prediction of forest attributes

Treesearch

F. Mauro; Vicente Monleon; H. Temesgen

2015-01-01

Small area estimation (SAE) techniques have been successfully applied in forest inventories to provide reliable estimates for domains where the sample size is small (i.e. small areas). Previous studies have explored the use of either Area Level or Unit Level Empirical Best Linear Unbiased Predictors (EBLUPs) in a univariate framework, modeling each variable of interest...

Stock discrimination of spottedtail goby ( Synechogobius ommaturus) in the Yellow Sea by analysis of otolith shape

NASA Astrophysics Data System (ADS)

Wang, Yingjun; Ye, Zhenjiang; Liu, Qun; Cao, Liang

2011-01-01

Otolith shape is species specific and is an ideal marker of fish population affiliation. In this study, otolith shape of spottedtail goby Synechogobius ommaturus is used to identify stocks in different spawning locations in the Yellow Sea. The main objectives of this study are to explore the potential existence of local stocks of spottedtail goby in the Yellow Sea by analysis of otolith shape, and to investigate ambient impacts on otolith shape. Spottedtail goby was sampled in five locations in the Yellow Sea in 2007 and 2008. Otoliths are described using variables correlated to size (otolith area, perimeter, length, width, and weight) and shape (rectangularity, circularity, and 20 Fourier harmonics). Only standardized otolith variables are used so that the effect of otolith size on the shape variables could be eliminated. There is no significant difference among variables of sex, year, and side (left and right). However, the otolith shapes of the spring stocks and the autumn stocks differ significantly. Otolith shape differences are greater among locations than between years. Correct classification rate of spottedtail goby with the otolith shape at different sampling locations range from 29.7%-77.4%.

A Sensory Material Approach for Reducing Variability in Additively Manufactured Metal Parts.

PubMed

Franco, B E; Ma, J; Loveall, B; Tapia, G A; Karayagiz, K; Liu, J; Elwany, A; Arroyave, R; Karaman, I

2017-06-15

Despite the recent growth in interest for metal additive manufacturing (AM) in the biomedical and aerospace industries, variability in the performance, composition, and microstructure of AM parts remains a major impediment to its widespread adoption. The underlying physical mechanisms, which cause variability, as well as the scale and nature of variability are not well understood, and current methods are ineffective at capturing these details. Here, a Nickel-Titanium alloy is used as a sensory material in order to quantitatively, and rather rapidly, observe compositional and/or microstructural variability in selective laser melting manufactured parts; thereby providing a means to evaluate the role of process parameters on the variability. We perform detailed microstructural investigations using transmission electron microscopy at various locations to reveal the origins of microstructural variability in this sensory material. This approach helped reveal how reducing the distance between adjacent laser scans below a critical value greatly reduces both the in-sample and sample-to-sample variability. Microstructural investigations revealed that when the laser scan distance is wide, there is an inhomogeneity in subgrain size, precipitate distribution, and dislocation density in the microstructure, responsible for the observed variability. These results provide an important first step towards understanding the nature of variability in additively manufactured parts.

Error in the Sampling Area of an Optical Disdrometer: Consequences in Computing Rain Variables

PubMed Central

Fraile, R.; Castro, A.; Fernández-Raga, M.; Palencia, C.; Calvo, A. I.

2013-01-01

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. The Z-R relationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006. PMID:23844393

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.

Temporal variability of the chemical composition of surface aerosol in the Moscow region in 1999-2005 from the results of infrared spectroscopy of aerosol samples

NASA Astrophysics Data System (ADS)

Shukurova, L. M.; Gruzdev, A. N.

2010-06-01

The temporal variability of the chemical composition of surface aerosol with particle diameters of 0.7-2 μm is analyzed. This analysis is based on the results of measurements of infrared transmission spectra of aerosol samples collected with the use of a cascade impactor at the Zvenigorod Scientific Station of the Institute of Atmospheric Physics (IAP) in 1999-2005. Seasonal features of the aerosol chemical composition and its dependence on the particle size are revealed. The interdiurnal variability of the aerosol composition depends on the season, and it manifests itself more strongly in winter and spring. Air-mass changes lead to changes in the relation of sulfates and nitrates in the micron fraction of aerosol. The enrichment of samples in nitrates is especially characteristic of the winter and spring seasons. Compounds containing the NO2 group are often met in the samples of aerosol with particle sizes of 0.7-1.3 μm during the cold time of the year. The estimates of the optical thickness of micron aerosol in the sulfate absorption band are obtained, and optical-thickness variations of some scales are detected. The quantitative characteristics of statistical relations between different chemical components of aerosol inside individual fractions and between chemical components of the micron and submicron fractions are obtained and analyzed.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Optimum strata boundaries and sample sizes in health surveys using auxiliary variables

PubMed Central

2018-01-01

Using convenient stratification criteria such as geographical regions or other natural conditions like age, gender, etc., is not beneficial in order to maximize the precision of the estimates of variables of interest. Thus, one has to look for an efficient stratification design to divide the whole population into homogeneous strata that achieves higher precision in the estimation. In this paper, a procedure for determining Optimum Stratum Boundaries (OSB) and Optimum Sample Sizes (OSS) for each stratum of a variable of interest in health surveys is developed. The determination of OSB and OSS based on the study variable is not feasible in practice since the study variable is not available prior to the survey. Since many variables in health surveys are generally skewed, the proposed technique considers the readily-available auxiliary variables to determine the OSB and OSS. This stratification problem is formulated into a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. It is then solved for the OSB by using a dynamic programming (DP) technique. A numerical example with a real data set of a population, aiming to estimate the Haemoglobin content in women in a national Iron Deficiency Anaemia survey, is presented to illustrate the procedure developed in this paper. Upon comparisons with other methods available in literature, results reveal that the proposed approach yields a substantial gain in efficiency over the other methods. A simulation study also reveals similar results. PMID:29621265

Optimum strata boundaries and sample sizes in health surveys using auxiliary variables.

PubMed

Reddy, Karuna Garan; Khan, Mohammad G M; Khan, Sabiha

2018-01-01

Using convenient stratification criteria such as geographical regions or other natural conditions like age, gender, etc., is not beneficial in order to maximize the precision of the estimates of variables of interest. Thus, one has to look for an efficient stratification design to divide the whole population into homogeneous strata that achieves higher precision in the estimation. In this paper, a procedure for determining Optimum Stratum Boundaries (OSB) and Optimum Sample Sizes (OSS) for each stratum of a variable of interest in health surveys is developed. The determination of OSB and OSS based on the study variable is not feasible in practice since the study variable is not available prior to the survey. Since many variables in health surveys are generally skewed, the proposed technique considers the readily-available auxiliary variables to determine the OSB and OSS. This stratification problem is formulated into a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. It is then solved for the OSB by using a dynamic programming (DP) technique. A numerical example with a real data set of a population, aiming to estimate the Haemoglobin content in women in a national Iron Deficiency Anaemia survey, is presented to illustrate the procedure developed in this paper. Upon comparisons with other methods available in literature, results reveal that the proposed approach yields a substantial gain in efficiency over the other methods. A simulation study also reveals similar results.

Variability of the raindrop size distribution at small spatial scales

NASA Astrophysics Data System (ADS)

Berne, A.; Jaffrain, J.

2010-12-01

Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.

Improving the API dissolution rate during pharmaceutical hot-melt extrusion I: Effect of the API particle size, and the co-rotating, twin-screw extruder screw configuration on the API dissolution rate.

PubMed

Li, Meng; Gogos, Costas G; Ioannidis, Nicolas

2015-01-15

The dissolution rate of the active pharmaceutical ingredients in pharmaceutical hot-melt extrusion is the most critical elementary step during the extrusion of amorphous solid solutions - total dissolution has to be achieved within the short residence time in the extruder. Dissolution and dissolution rates are affected by process, material and equipment variables. In this work, we examine the effect of one of the material variables and one of the equipment variables, namely, the API particle size and extruder screw configuration on the API dissolution rate, in a co-rotating, twin-screw extruder. By rapidly removing the extruder screws from the barrel after achieving a steady state, we collected samples along the length of the extruder screws that were characterized by polarized optical microscopy (POM) and differential scanning calorimetry (DSC) to determine the amount of undissolved API. Analyses of samples indicate that reduction of particle size of the API and appropriate selection of screw design can markedly improve the dissolution rate of the API during extrusion. In addition, angle of repose measurements and light microscopy images show that the reduction of particle size of the API can improve the flowability of the physical mixture feed and the adhesiveness between its components, respectively, through dry coating of the polymer particles by the API particles. Copyright © 2014. Published by Elsevier B.V.

Predictor sort sampling and one-sided confidence bounds on quantiles

Treesearch

Steve Verrill; Victoria L. Herian; David W. Green

2002-01-01

Predictor sort experiments attempt to make use of the correlation between a predictor that can be measured prior to the start of an experiment and the response variable that we are investigating. Properly designed and analyzed, they can reduce necessary sample sizes, increase statistical power, and reduce the lengths of confidence intervals. However, if the non- random...

Illiteracy, Sex and Occupational Status in Present-Day China.

ERIC Educational Resources Information Center

Lamontagne, Jacques

This study determined the magnitude of disparity between men and women in China in relation to illiteracy and occupational status. Region and ethnicity are used as control variables. The data collected are from a 10 percent sampling of the 1982 census; the total sample size includes a population of 100,380,000 nationwide. The census questionnaire…

Effects of access to pasture on performance, carcass composition, and meat quality in broilers: a meta-analysis.

PubMed

Sales, J

2014-06-01

Consumer preference for poultry meat from free-range birds is not justified by scientific evidence. Inconsistency in results among studies on the effects of access to pasture on performance, carcass composition, and meat quality has led to a meta-analysis to quantify effects. After identification of studies where response variables were directly compared between birds with and without access to pasture, standardized effect sizes were used to calculate differences. The effect size for growth combined according to a fixed effect model did not present heterogeneity (P = 0.116). However, with feed intake and feed efficiency, variability among studies (heterogeneity with P-values of below 0.10) was influenced by more than sampling error. Carcass yield was the only carcass component that showed heterogeneity (P = 0.008), whereas numerous response variables related to meat quality were not homogenous. The use of subgroup analysis and meta-regression to evaluate the sources of heterogeneity was limited by ill-defined explanatory variables and few values available within response variables. Consequently, between-study variability was accounted for by use of random effects models to combine effect sizes. According to these, few response variables were influenced by pasture access. Fat concentrations in breast (mean effect size = -0.500; 95% CI = -0.825 to -0.175; 11 studies; 14 comparisons), thigh (mean effect size = -0.908; 95% CI = -1.710 to -0.105; 4 studies; 5 comparisons) and drum (mean effect size = -1.223; 95% CI = -2.210 to -0.237; 3 studies; 3 comparisons) muscles were decreased in free-range birds. Access to pasture increased (P < 0.05) or tended to increase (P < 0.10) protein concentrations in the respective commercial cuts. It is concluded that factors other than enhanced meat quality could be responsible for consumer preference for meat from free-range poultry. Poultry Science Association Inc.

Demonstration and evaluation of a method for assessing mediated moderation.

PubMed

Morgan-Lopez, Antonio A; MacKinnon, David P

2006-02-01

Mediated moderation occurs when the interaction between two variables affects a mediator, which then affects a dependent variable. In this article, we describe the mediated moderation model and evaluate it with a statistical simulation using an adaptation of product-of-coefficients methods to assess mediation. We also demonstrate the use of this method with a substantive example from the adolescent tobacco literature. In the simulation, relative bias (RB) in point estimates and standard errors did not exceed problematic levels of +/- 10% although systematic variability in RB was accounted for by parameter size, sample size, and nonzero direct effects. Power to detect mediated moderation effects appears to be severely compromised under one particular combination of conditions: when the component variables that make up the interaction terms are correlated and partial mediated moderation exists. Implications for the estimation of mediated moderation effects in experimental and nonexperimental research are discussed.

Trade off between variable and fixed size normalization in orthogonal polynomials based iris recognition system.

PubMed

Krishnamoorthi, R; Anna Poorani, G

2016-01-01

Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

Estimating population sizes for elusive animals: the forest elephants of Kakum National Park, Ghana.

PubMed

Eggert, L S; Eggert, J A; Woodruff, D S

2003-06-01

African forest elephants are difficult to observe in the dense vegetation, and previous studies have relied upon indirect methods to estimate population sizes. Using multilocus genotyping of noninvasively collected samples, we performed a genetic survey of the forest elephant population at Kakum National Park, Ghana. We estimated population size, sex ratio and genetic variability from our data, then combined this information with field observations to divide the population into age groups. Our population size estimate was very close to that obtained using dung counts, the most commonly used indirect method of estimating the population sizes of forest elephant populations. As their habitat is fragmented by expanding human populations, management will be increasingly important to the persistence of forest elephant populations. The data that can be obtained from noninvasively collected samples will help managers plan for the conservation of this keystone species.

Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size

USGS Publications Warehouse

Buscombe, Daniel; Rubin, David M.; Lacy, Jessica R.; Storlazzi, Curt D.; Hatcher, Gerald; Chezar, Henry; Wyland, Robert; Sherwood, Christopher R.

2014-01-01

We describe a remotely operated video microscope system, designed to provide high-resolution images of seabed sediments. Two versions were developed, which differ in how they raise the camera from the seabed. The first used hydraulics and the second used the energy associated with wave orbital motion. Images were analyzed using automated frequency-domain methods, which following a rigorous partially supervised quality control procedure, yielded estimates to within 20% of the true size as determined by on-screen manual measurements of grains. Long-term grain-size variability at a sandy inner shelf site offshore of Santa Cruz, California, USA, was investigated using the hydraulic system. Eighteen months of high frequency (min to h), high-resolution (μm) images were collected, and grain size distributions compiled. The data constitutes the longest known high-frequency record of seabed-grain size at this sample frequency, at any location. Short-term grain-size variability of sand in an energetic surf zone at Praa Sands, Cornwall, UK was investigated using the ‘wave-powered’ system. The data are the first high-frequency record of grain size at a single location of a highly mobile and evolving bed in a natural surf zone. Using this technology, it is now possible to measure bed-sediment-grain size at a time-scale comparable with flow conditions. Results suggest models of sediment transport at sandy, wave-dominated, nearshore locations should allow for substantial changes in grain-size distribution over time-scales as short as a few hours.

Integrative Lifecourse and Genetic Analysis of Military Working Dogs

DTIC Science & Technology

2015-12-01

done as the samples are collected in order to avoid experimental variability and batch effects . Detailed description and discussion of this task...associated loss of power to detect all associations but those of large effect sizes) and latent variables (e.g., population structure – addressed in...processes associated with tissue development and maintenance are thus grouped with external environmental effects . This in turn suggests how those

When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Vocational Interest as a Correlate of Re-Entry of Girls into School in Edo State, Nigeria: Implications for Counselling

ERIC Educational Resources Information Center

Alika, Ijeoma Henrietta; Egbochuku, Elizabeth Omotunde

2012-01-01

The study investigated the relationship between vocational interest socio-economic status and re-entry of girls into school in Edo State. The research design adopted was correlational because it sought to establish the relationship between the independent variable and the dependent variable. A sample size of 306 girls who re-enrolled in institutes…

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.

Simple and multiple linear regression: sample size considerations.

PubMed

Hanley, James A

2016-11-01

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

Occupancy in continuous habitat

USGS Publications Warehouse

Efford, Murray G.; Dawson, Deanna K.

2012-01-01

The probability that a site has at least one individual of a species ('occupancy') has come to be widely used as a state variable for animal population monitoring. The available statistical theory for estimation when detection is imperfect applies particularly to habitat patches or islands, although it is also used for arbitrary plots in continuous habitat. The probability that such a plot is occupied depends on plot size and home-range characteristics (size, shape and dispersion) as well as population density. Plot size is critical to the definition of occupancy as a state variable, but clear advice on plot size is missing from the literature on the design of occupancy studies. We describe models for the effects of varying plot size and home-range size on expected occupancy. Temporal, spatial, and species variation in average home-range size is to be expected, but information on home ranges is difficult to retrieve from species presence/absence data collected in occupancy studies. The effect of variable home-range size is negligible when plots are very large (>100 x area of home range), but large plots pose practical problems. At the other extreme, sampling of 'point' plots with cameras or other passive detectors allows the true 'proportion of area occupied' to be estimated. However, this measure equally reflects home-range size and density, and is of doubtful value for population monitoring or cross-species comparisons. Plot size is ill-defined and variable in occupancy studies that detect animals at unknown distances, the commonest example being unlimited-radius point counts of song birds. We also find that plot size is ill-defined in recent treatments of "multi-scale" occupancy; the respective scales are better interpreted as temporal (instantaneous and asymptotic) rather than spatial. Occupancy is an inadequate metric for population monitoring when it is confounded with home-range size or detection distance.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic mild cognitive impairment trials: effect of algorithm, test-retest variability, and cut point on trial cost, duration, and sample size.

PubMed

Yu, Peng; Sun, Jia; Wolz, Robin; Stephenson, Diane; Brewer, James; Fox, Nick C; Cole, Patricia E; Jack, Clifford R; Hill, Derek L G; Schwarz, Adam J

2014-04-01

The objective of this study was to evaluate the effect of computational algorithm, measurement variability, and cut point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). We used normal control and amnestic MCI subjects from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) as normative reference and screening cohorts. We evaluated the enrichment performance of 4 widely used hippocampal segmentation algorithms (FreeSurfer, Hippocampus Multi-Atlas Propagation and Segmentation (HMAPS), Learning Embeddings Atlas Propagation (LEAP), and NeuroQuant) in terms of 2-year changes in Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Sum of Boxes (CDR-SB). We modeled the implications for sample size, screen fail rates, and trial cost and duration. HCV based patient selection yielded reduced sample sizes (by ∼40%-60%) and lower trial costs (by ∼30%-40%) across a wide range of cut points. These results provide a guide to the choice of HCV cut point for amnestic MCI clinical trials, allowing an informed tradeoff between statistical and practical considerations. Copyright © 2014 Elsevier Inc. All rights reserved.

DRME: Count-based differential RNA methylation analysis at small sample size scenario.

PubMed

Liu, Lian; Zhang, Shao-Wu; Gao, Fan; Zhang, Yixin; Huang, Yufei; Chen, Runsheng; Meng, Jia

2016-04-15

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation. We developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. We tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies and compared it with Fisher's exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing and PAR-CLIP. The code together with an MeRIP-Seq dataset is available online (https://github.com/lzcyzm/DRME) for evaluation and reproduction of the figures shown in this article. Copyright © 2016 Elsevier Inc. All rights reserved.

Visual Inspection of Surfaces

NASA Technical Reports Server (NTRS)

Hughes, David; Perez, Xavier

2007-01-01

This presentation evaluates the parameters that affect visual inspection of cleanliness. Factors tested include surface reflectance, surface roughness, size of the largest particle, exposure time, inspector and distance from sample surface. It is concluded that distance predictions were not great, particularly because the distance at which contamination is seen may depend on more variables than those tested. Most parameters estimates had confidence of 95% or better, except for exposure and reflectance. Additionally, the distance at which surface is visibly contaminated decreases with increasing reflectance, roughness, and exposure. The distance at which the surface is visually contaminated increased with the largest particle size. These variables were only slightly affected the observer.

Improved population estimates through the use of auxiliary information

USGS Publications Warehouse

Johnson, D.H.; Ralph, C.J.; Scott, J.M.

1981-01-01

When estimating the size of a population of birds, the investigator may have, in addition to an estimator based on a statistical sample, information on one of several auxiliary variables, such as: (1) estimates of the population made on previous occasions, (2) measures of habitat variables associated with the size of the population, and (3) estimates of the population sizes of other species that correlate with the species of interest. Although many studies have described the relationships between each of these kinds of data and the population size to be estimated, very little work has been done to improve the estimator by incorporating such auxiliary information. A statistical methodology termed 'empirical Bayes' seems to be appropriate to these situations. The potential that empirical Bayes methodology has for improved estimation of the population size of the Mallard (Anas platyrhynchos) is explored. In the example considered, three empirical Bayes estimators were found to reduce the error by one-fourth to one-half of that of the usual estimator.

Predicting breeding bird occurrence by stand- and microhabitat-scale features in even-aged stands in the Central Appalachians

USGS Publications Warehouse

McDermott, M.E.; Wood, P.B.; Miller, G.W.; Simpson, B.T.

2011-01-01

Spatial scale is an important consideration when managing forest wildlife habitat, and models can be used to improve our understanding of these habitats at relevant scales. Our objectives were to determine whether stand- or microhabitat-scale variables better predicted bird metrics (diversity, species presence, and abundance) and to examine breeding bird response to clearcut size and age in a highly forested landscape. In 2004-2007, vegetation data were collected from 62 even-aged stands that were 3.6-34.6. ha in size and harvested in 1963-1990 on the Monongahela National Forest, WV, USA. In 2005-2007, we also surveyed birds at vegetation plots. We used classification and regression trees to model breeding bird habitat use with a suite of stand and microhabitat variables. Among stand variables, elevation, stand age, and stand size were most commonly retained as important variables in guild and species models. Among microhabitat variables, medium-sized tree density and tree species diversity most commonly predicted bird presence or abundance. Early successional and generalist bird presence, abundance, and diversity were better predicted by microhabitat variables than stand variables. Thus, more intensive field sampling may be required to predict habitat use for these species, and management may be needed at a finer scale. Conversely, stand-level variables had greater utility in predicting late-successional species occurrence and abundance; thus management decisions and modeling at this scale may be suitable in areas with a uniform landscape, such as our study area. Our study suggests that late-successional breeding bird diversity can be maximized long-term by including harvests >10. ha in size into our study area and by increasing tree diversity. Some harvesting will need to be incorporated regularly, because after 15 years, the study stands did not provide habitat for most early successional breeding specialists. ?? 2010 Elsevier B.V.

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

PubMed

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

2016-10-01

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

Decomposition and model selection for large contingency tables.

PubMed

Dahinden, Corinne; Kalisch, Markus; Bühlmann, Peter

2010-04-01

Large contingency tables summarizing categorical variables arise in many areas. One example is in biology, where large numbers of biomarkers are cross-tabulated according to their discrete expression level. Interactions of the variables are of great interest and are generally studied with log-linear models. The structure of a log-linear model can be visually represented by a graph from which the conditional independence structure can then be easily read off. However, since the number of parameters in a saturated model grows exponentially in the number of variables, this generally comes with a heavy computational burden. Even if we restrict ourselves to models of lower-order interactions or other sparse structures, we are faced with the problem of a large number of cells which play the role of sample size. This is in sharp contrast to high-dimensional regression or classification procedures because, in addition to a high-dimensional parameter, we also have to deal with the analogue of a huge sample size. Furthermore, high-dimensional tables naturally feature a large number of sampling zeros which often leads to the nonexistence of the maximum likelihood estimate. We therefore present a decomposition approach, where we first divide the problem into several lower-dimensional problems and then combine these to form a global solution. Our methodology is computationally feasible for log-linear interaction models with many categorical variables each or some of them having many levels. We demonstrate the proposed method on simulated data and apply it to a bio-medical problem in cancer research.

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.

Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence.

PubMed

Maurer, Willi; Jones, Byron; Chen, Ying

2018-05-10

In a 2×2 crossover trial for establishing average bioequivalence (ABE) of a generic agent and a currently marketed drug, the recommended approach to hypothesis testing is the two one-sided test (TOST) procedure, which depends, among other things, on the estimated within-subject variability. The power of this procedure, and therefore the sample size required to achieve a minimum power, depends on having a good estimate of this variability. When there is uncertainty, it is advisable to plan the design in two stages, with an interim sample size reestimation after the first stage, using an interim estimate of the within-subject variability. One method and 3 variations of doing this were proposed by Potvin et al. Using simulation, the operating characteristics, including the empirical type I error rate, of the 4 variations (called Methods A, B, C, and D) were assessed by Potvin et al and Methods B and C were recommended. However, none of these 4 variations formally controls the type I error rate of falsely claiming ABE, even though the amount of inflation produced by Method C was considered acceptable. A major disadvantage of assessing type I error rate inflation using simulation is that unless all possible scenarios for the intended design and analysis are investigated, it is impossible to be sure that the type I error rate is controlled. Here, we propose an alternative, principled method of sample size reestimation that is guaranteed to control the type I error rate at any given significance level. This method uses a new version of the inverse-normal combination of p-values test, in conjunction with standard group sequential techniques, that is more robust to large deviations in initial assumptions regarding the variability of the pharmacokinetic endpoints. The sample size reestimation step is based on significance levels and power requirements that are conditional on the first-stage results. This necessitates a discussion and exploitation of the peculiar properties of the power curve of the TOST testing procedure. We illustrate our approach with an example based on a real ABE study and compare the operating characteristics of our proposed method with those of Method B of Povin et al. Copyright © 2018 John Wiley & Sons, Ltd.

Simultaneous unbiased estimates of multiple downed wood attributes in perpendicular distance sampling

Treesearch

Mark J. Ducey; Jeffrey H. Gove; Harry T. Valentine

2008-01-01

Perpendicular distance sampling (PDS) is a fast probability-proportional-to-size method for inventory of downed wood. However, previous development of PDS had limited the method to estimating only one variable (such as volume per hectare, or surface area per hectare) at a time. Here, we develop a general design-unbiased estimator for PDS. We then show how that...

Analyzing thematic maps and mapping for accuracy

USGS Publications Warehouse

Rosenfield, G.H.

1982-01-01

Two problems which exist while attempting to test the accuracy of thematic maps and mapping are: (1) evaluating the accuracy of thematic content, and (2) evaluating the effects of the variables on thematic mapping. Statistical analysis techniques are applicable to both these problems and include techniques for sampling the data and determining their accuracy. In addition, techniques for hypothesis testing, or inferential statistics, are used when comparing the effects of variables. A comprehensive and valid accuracy test of a classification project, such as thematic mapping from remotely sensed data, includes the following components of statistical analysis: (1) sample design, including the sample distribution, sample size, size of the sample unit, and sampling procedure; and (2) accuracy estimation, including estimation of the variance and confidence limits. Careful consideration must be given to the minimum sample size necessary to validate the accuracy of a given. classification category. The results of an accuracy test are presented in a contingency table sometimes called a classification error matrix. Usually the rows represent the interpretation, and the columns represent the verification. The diagonal elements represent the correct classifications. The remaining elements of the rows represent errors by commission, and the remaining elements of the columns represent the errors of omission. For tests of hypothesis that compare variables, the general practice has been to use only the diagonal elements from several related classification error matrices. These data are arranged in the form of another contingency table. The columns of the table represent the different variables being compared, such as different scales of mapping. The rows represent the blocking characteristics, such as the various categories of classification. The values in the cells of the tables might be the counts of correct classification or the binomial proportions of these counts divided by either the row totals or the column totals from the original classification error matrices. In hypothesis testing, when the results of tests of multiple sample cases prove to be significant, some form of statistical test must be used to separate any results that differ significantly from the others. In the past, many analyses of the data in this error matrix were made by comparing the relative magnitudes of the percentage of correct classifications, for either individual categories, the entire map or both. More rigorous analyses have used data transformations and (or) two-way classification analysis of variance. A more sophisticated step of data analysis techniques would be to use the entire classification error matrices using the methods of discrete multivariate analysis or of multiviariate analysis of variance.

Zooplankton Grazing Effects on Particle Size Spectra under Different Seasonal Conditions

NASA Astrophysics Data System (ADS)

Stamieszkin, K.; Poulton, N.; Pershing, A. J.

2016-02-01

Oceanic particle size spectra can be used to explain and predict variability in carbon export efficiency, since larger particles are more likely to sink to depth than small particles. The distribution of biogenic particle size in the surface ocean is the result of many variables and processes, including nutrient availability, primary productivity, aggregation, remineralization, and grazing. We conducted a series of grazing experiments to test the hypothesis that mesozooplankton shift particle size spectra toward larger particles, via grazing and egestion of relatively large fecal pellets. These experiments were carried out over several months, and used natural communities of mesozooplankton and their microbial prey, collected offshore of the Damariscotta River in the Gulf of Maine. We analyzed the samples using Fluid Imaging Technologies' FlowCam®, a particle imaging system. With this equipment, we processed live samples, decreasing the likelihood of losing or damaging fragile particles, and thereby lessening sources of error in commonly used preservation and enumeration protocols. Our results show how the plankton size spectrum changes as the Gulf of Maine progresses through a seasonal cycle. We explore the relationship of grazing community size structure to its effect on the overall biogenic particle size spectrum. At some times of year, mesozooplankton grazing does not alter the particle size spectrum, while at others it significantly does, affecting the potential for biogenic flux. We also examine prey selectivity, and find that chain diatoms are the only prey group preferentially consumed. Otherwise, we find that complete mesozooplankton communities are "evolved" to fit their prey such that most prey groups are grazed evenly. We discuss a metabolic numerical model which could be used to universalize the relationships between whole gazer and whole microbial communities, with respect to effects on particle size spectra.

Petroleomics by electrospray ionization FT-ICR mass spectrometry coupled to partial least squares with variable selection methods: prediction of the total acid number of crude oils.

PubMed

Terra, Luciana A; Filgueiras, Paulo R; Tose, Lílian V; Romão, Wanderson; de Souza, Douglas D; de Castro, Eustáquio V R; de Oliveira, Mirela S L; Dias, Júlio C M; Poppi, Ronei J

2014-10-07

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

Contributing to Overall Life Satisfaction: Personality Traits Versus Life Satisfaction Variables Revisited—Is Replication Impossible?

PubMed Central

Lachmann, Bernd; Sariyska, Rayna; Kannen, Christopher; Błaszkiewicz, Konrad; Trendafilov, Boris; Andone, Ionut; Eibes, Mark; Markowetz, Alexander; Li, Mei; Kendrick, Keith M.

2017-01-01

Virtually everybody would agree that life satisfaction is of immense importance in everyday life. Thus, it is not surprising that a considerable amount of research using many different methodological approaches has investigated what the best predictors of life satisfaction are. In the present study, we have focused on several key potential influences on life satisfaction including bottom-up and top-down models, cross-cultural effects, and demographic variables. In four independent (large scale) surveys with sample sizes ranging from N = 488 to 40,297, we examined the associations between life satisfaction and various related variables. Our findings demonstrate that prediction of overall life satisfaction works best when including information about specific life satisfaction variables. From this perspective, satisfaction with leisure showed the highest impact on overall life satisfaction in our European samples. Personality was also robustly associated with life satisfaction, but only when life satisfaction variables were not included in the regression model. These findings could be replicated in all four independent samples, but it was also demonstrated that the relevance of life satisfaction variables changed under the influence of cross-cultural effects. PMID:29295529

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

PubMed

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

2011-12-01

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

Improvements in sub-grid, microphysics averages using quadrature based approaches

NASA Astrophysics Data System (ADS)

Chowdhary, K.; Debusschere, B.; Larson, V. E.

2013-12-01

Sub-grid variability in microphysical processes plays a critical role in atmospheric climate models. In order to account for this sub-grid variability, Larson and Schanen (2013) propose placing a probability density function on the sub-grid cloud microphysics quantities, e.g. autoconversion rate, essentially interpreting the cloud microphysics quantities as a random variable in each grid box. Random sampling techniques, e.g. Monte Carlo and Latin Hypercube, can be used to calculate statistics, e.g. averages, on the microphysics quantities, which then feed back into the model dynamics on the coarse scale. We propose an alternate approach using numerical quadrature methods based on deterministic sampling points to compute the statistical moments of microphysics quantities in each grid box. We have performed a preliminary test on the Kessler autoconversion formula, and, upon comparison with Latin Hypercube sampling, our approach shows an increased level of accuracy with a reduction in sample size by almost two orders of magnitude. Application to other microphysics processes is the subject of ongoing research.

Assessment of the within- and between-lot variability of Whatman™ FTA(®) DMPK and 903(®) DBS papers and their suitability for the quantitative bioanalysis of small molecules.

PubMed

Luckwell, Jacquelynn; Denniff, Philip; Capper, Stephen; Michael, Paul; Spooner, Neil; Mallender, Philip; Johnson, Barry; Clegg, Sarah; Green, Mark; Ahmad, Sheelan; Woodford, Lynsey

2013-11-01

To ensure that PK data generated from DBS samples are of the highest quality, it is important that the paper substrate is uniform and does not unduly contribute to variability. This study investigated any within and between lot variations for four cellulose paper types: Whatman™ FTA(®) DMPK-A, -B and -C, and 903(®) (GE Healthcare, Buckinghamshire, UK). The substrates were tested to demonstrate manufacturing reproducibility (thickness, weight, chemical coating concentration) and its effect on the size of the DBS produced, and the quantitative data derived from the bioanalysis of human DBS samples containing six compounds of varying physicochemical properties. Within and between lot variations in paper thickness, mass and chemical coating concentration were within acceptable manufacturing limits. No variation in the spot size or bioanalytical data was observed. Bioanalytical results obtained for DBS samples containing a number of analytes spanning a range of chemical space are not affected by the lot used or by the location within a lot.

Density dependence and climate effects in Rocky Mountain elk: an application of regression with instrumental variables for population time series with sampling error.

PubMed

Creel, Scott; Creel, Michael

2009-11-01

1. Sampling error in annual estimates of population size creates two widely recognized problems for the analysis of population growth. First, if sampling error is mistakenly treated as process error, one obtains inflated estimates of the variation in true population trajectories (Staples, Taper & Dennis 2004). Second, treating sampling error as process error is thought to overestimate the importance of density dependence in population growth (Viljugrein et al. 2005; Dennis et al. 2006). 2. In ecology, state-space models are used to account for sampling error when estimating the effects of density and other variables on population growth (Staples et al. 2004; Dennis et al. 2006). In econometrics, regression with instrumental variables is a well-established method that addresses the problem of correlation between regressors and the error term, but requires fewer assumptions than state-space models (Davidson & MacKinnon 1993; Cameron & Trivedi 2005). 3. We used instrumental variables to account for sampling error and fit a generalized linear model to 472 annual observations of population size for 35 Elk Management Units in Montana, from 1928 to 2004. We compared this model with state-space models fit with the likelihood function of Dennis et al. (2006). We discuss the general advantages and disadvantages of each method. Briefly, regression with instrumental variables is valid with fewer distributional assumptions, but state-space models are more efficient when their distributional assumptions are met. 4. Both methods found that population growth was negatively related to population density and winter snow accumulation. Summer rainfall and wolf (Canis lupus) presence had much weaker effects on elk (Cervus elaphus) dynamics [though limitation by wolves is strong in some elk populations with well-established wolf populations (Creel et al. 2007; Creel & Christianson 2008)]. 5. Coupled with predictions for Montana from global and regional climate models, our results predict a substantial reduction in the limiting effect of snow accumulation on Montana elk populations in the coming decades. If other limiting factors do not operate with greater force, population growth rates would increase substantially.

Using satellite imagery as ancillary data for increasing the precision of estimates for the Forest Inventory and Analysis program of the USDA Forest Service

Treesearch

Ronald E. McRoberts; Geoffrey R. Holden; Mark D. Nelson; Greg C. Liknes; Dale D. Gormanson

2006-01-01

Forest inventory programs report estimates of forest variables for areas of interest ranging in size from municipalities, to counties, to states or provinces. Because of numerous factors, sample sizes are often insufficient to estimate attributes as precisely as is desired, unless the estimation process is enhanced using ancillary data. Classified satellite imagery has...

Does raising type 1 error rate improve power to detect interactions in linear regression models? A simulation study.

PubMed

Durand, Casey P

2013-01-01

Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

Branching, flowering and fruiting of Jatropha curcas treated with ethephon or benzyladenine and gibberellins.

PubMed

Costa, Anne P; Vendrame, Wagner; Nietsche, Sílvia; Crane, Jonathan; Moore, Kimberly; Schaffer, Bruce

2016-05-31

Jatropha curcas L. has been identified for biofuel production but it presents limited commercial yields due to limited branching and a lack of yield uniformity. The objective of this study was to evaluate the effects of single application of ethephon or a combination of 6-benzyladenine (BA) with gibberellic acid isomers A4 and A7 (GA4+7) on branch induction, flowering and fruit production in jatropha plants with and without leaves. Plants with and without leaves showed differences for growth and reproductive variables. For all variables except inflorescence set, there were no significant statistical interactions between the presence of leaves and plant growth regulators concentration. The total number of flowers per inflorescence was reduced as ethephon concentration was increased. As BA + GA4 +7 concentration increased, seed dry weight increased. Thus, ethephon and BA + GA4 +7 applications appeared to affect flowering and seed production to a greater extent than branching. The inability to discern significant treatment effects for most variables might have been due to the large variability within plant populations studied and thus resulting in an insufficient sample size. Therefore, data collected from this study were used for statistical estimations of sample sizes to provide a reference for future studies.

Comparison of outcomes and other variables between conference abstracts and subsequent peer-reviewed papers involving pre-harvest or abattoir-level interventions against foodborne pathogens.

PubMed

Snedeker, Kate G; Campbell, Mollie; Totton, Sarah C; Guthrie, Alessia; Sargeant, Jan M

2010-11-01

Accuracy in the reporting of studies in conference abstracts is important because the majority of studies in such abstracts are never further detailed in peer-reviewed publications, and data from such abstracts may be used in systematic reviews. Previous research on interventional studies in human biomedicine indicates that there is no guarantee of consistency between a conference abstract and paper in the reporting of results and other key variables. However, no research has been done to determine if this lack of reporting consistency in abstracts and papers extends to interventional studies in pre-harvest/harvest-level food safety. The goal of this study was to compare outcome results and other key variables between conference abstracts and subsequent peer-reviewed publications describing studies of pre-harvest and abattoir-level interventions against foodborne pathogens, and to determine whether the agreement in the results or key variables was associated with the time to full publication. A systematic search identified 59 conference abstracts with matching peer-reviewed papers (matches), and data on variables including outcome measures and results, pathogens, species, interventions, overall efficacy of intervention, sample size and housing were extracted from both the conference abstracts and the papers. The matching of variables between abstracts and papers was described, and logistic regression used to test for associations between variable matching and time to publication. Sample size was only provided for both abstract and paper in 24 matches; the same sample size was reported in 20 of these matches. Most other variables were reported in the majority of abstracts/papers, and with the exception of outcomes and intervention effect, the reporting of variables was relatively consistent. There was no significant difference in the numbers of authors, with the first author the same in 78.3% of matches. Of 231 outcome measures reported in both abstracts and papers, nearly one third (77% or 32.2%) had different results, with 32 changing direction of effect. More than a quarter of matches involved at least one significant change in outcome result. The overall conclusion on the efficacy of the intervention changed in 10.7% of matches. There was a significant association between increased time to publication and differences in the number of authors, and having fewer outcome measures in the abstract reported in the paper. These results suggest that data from conference abstracts should be considered with caution. Copyright © 2010 Elsevier B.V. All rights reserved.

Will Outer Tropical Cyclone Size Change due to Anthropogenic Warming?

NASA Astrophysics Data System (ADS)

Schenkel, B. A.; Lin, N.; Chavas, D. R.; Vecchi, G. A.; Knutson, T. R.; Oppenheimer, M.

2017-12-01

Prior research has shown significant interbasin and intrabasin variability in outer tropical cyclone (TC) size. Moreover, outer TC size has even been shown to vary substantially over the lifetime of the majority of TCs. However, the factors responsible for both setting initial outer TC size and determining its evolution throughout the TC lifetime remain uncertain. Given these gaps in our physical understanding, there remains uncertainty in how outer TC size will change, if at all, due to anthropogenic warming. The present study seeks to quantify whether outer TC size will change significantly in response to anthropogenic warming using data from a high-resolution global climate model and a regional hurricane model. Similar to prior work, the outer TC size metric used in this study is the radius in which the azimuthal-mean surface azimuthal wind equals 8 m/s. The initial results from the high-resolution global climate model data suggest that the distribution of outer TC size shifts significantly towards larger values in each global TC basin during future climates, as revealed by 1) statistically significant increase of the median outer TC size by 5-10% (p<0.05) according to a 1,000-sample bootstrap resampling approach with replacement and 2) statistically significant differences between distributions of outer TC size from current and future climate simulations as shown using two-sample Kolmogorov Smirnov testing (p<<0.01). Additional analysis of the high-resolution global climate model data reveals that outer TC size does not uniformly increase within each basin in future climates, but rather shows substantial locational dependence. Future work will incorporate the regional mesoscale hurricane model data to help focus on identifying the source of the spatial variability in outer TC size increases within each basin during future climates and, more importantly, why outer TC size changes in response to anthropogenic warming.

Catch me if you can: Comparing ballast water sampling skids to traditional net sampling

NASA Astrophysics Data System (ADS)

Bradie, Johanna; Gianoli, Claudio; Linley, Robert Dallas; Schillak, Lothar; Schneider, Gerd; Stehouwer, Peter; Bailey, Sarah

2018-03-01

With the recent ratification of the International Convention for the Control and Management of Ships' Ballast Water and Sediments, 2004, it will soon be necessary to assess ships for compliance with ballast water discharge standards. Sampling skids that allow the efficient collection of ballast water samples in a compact space have been developed for this purpose. We ran 22 trials on board the RV Meteor from June 4-15, 2015 to evaluate the performance of three ballast water sampling devices (traditional plankton net, Triton sampling skid, SGS sampling skid) for three organism size classes: ≥ 50 μm, ≥ 10 μm to < 50 μm, and < 10 μm. Natural sea water was run through the ballast water system and untreated samples were collected using paired sampling devices. Collected samples were analyzed in parallel by multiple analysts using several different analytic methods to quantify organism concentrations. To determine whether there were differences in the number of viable organisms collected across sampling devices, results were standardized and statistically treated to filter out other sources of variability, resulting in an outcome variable representing the mean difference in measurements that can be attributed to sampling devices. These results were tested for significance using pairwise Tukey contrasts. Differences in organism concentrations were found in 50% of comparisons between sampling skids and the plankton net for ≥ 50 μm, and ≥ 10 μm to < 50 μm size classes, with net samples containing either higher or lower densities. There were no differences for < 10 μm organisms. Future work will be required to explicitly examine the potential effects of flow velocity, sampling duration, sampled volume, and organism concentrations on sampling device performance.

Distribution and predictors of wing shape and size variability in three sister species of solitary bees

PubMed Central

Prunier, Jérôme G.; Dewulf, Alexandre; Kuhlmann, Michael; Michez, Denis

2017-01-01

Morphological traits can be highly variable over time in a particular geographical area. Different selective pressures shape those traits, which is crucial in evolutionary biology. Among these traits, insect wing morphometry has already been widely used to describe phenotypic variability at the inter-specific level. On the contrary, fewer studies have focused on intra-specific wing morphometric variability. Yet, such investigations are relevant to study potential convergences of variation that could highlight micro-evolutionary processes. The recent sampling and sequencing of three solitary bees of the genus Melitta across their entire species range provides an excellent opportunity to jointly analyse genetic and morphometric variability. In the present study, we first aim to analyse the spatial distribution of the wing shape and centroid size (used as a proxy for body size) variability. Secondly, we aim to test different potential predictors of this variability at both the intra- and inter-population levels, which includes genetic variability, but also geographic locations and distances, elevation, annual mean temperature and precipitation. The comparison of spatial distribution of intra-population morphometric diversity does not reveal any convergent pattern between species, thus undermining the assumption of a potential local and selective adaptation at the population level. Regarding intra-specific wing shape differentiation, our results reveal that some tested predictors, such as geographic and genetic distances, are associated with a significant correlation for some species. However, none of these predictors are systematically identified for the three species as an important factor that could explain the intra-specific morphometric variability. As a conclusion, for the three solitary bee species and at the scale of this study, our results clearly tend to discard the assumption of the existence of a common pattern of intra-specific signal/structure within the intra-specific wing shape and body size variability. PMID:28273178

Lens-Aided Multi-Angle Spectroscopy (LAMAS) Reveals Small-Scale Outflow Structure in Quasars

NASA Astrophysics Data System (ADS)

Green, Paul J.

2006-06-01

Spectral differences between lensed quasar image components are common. Since lensing is intrinsically achromatic, these differences are typically explained as the effect of either microlensing, or as light path time delays sampling intrinsic quasar spectral variability. Here we advance a novel third hypothesis: some spectral differences are due to small line-of-sight differences through quasar disk wind outflows. In particular, we propose that variable spectral differences seen only in component A of the widest separation lens SDSS J1004+4112 are due to differential absorption along the sight lines. The absorber properties required by this hypothesis are akin to known broad absorption line (BAL) outflows but must have a broader, smoother velocity profile. We interpret the observed C IV emission-line variability as further evidence for spatial fine structure transverse to the line of sight. Since outflows are likely to be rotating, such absorber fine structure can consistently explain some of the UV and X-ray variability seen in AGNs. The implications are many: (1) Spectroscopic differences in other lensed objects may be due to this ``lens-aided multi-angle spectroscopy'' (LAMAS). (2) Outflows have fine structure on size scales of arcseconds, as seen from the nucleus. (3) Assuming either broad absorption line region sizes proposed in recent wind models, or typically assumed continuum emission region sizes, LAMAS and/or variability provide broadly consistent absorber size scale estimates of ~1015 cm. (4) Very broad smooth absorption may be ubiquitous in quasar spectra, even when no obvious troughs are seen.

Surface facial modelling and allometry in relation to sexual dimorphism.

PubMed

Velemínská, J; Bigoni, L; Krajíček, V; Borský, J; Šmahelová, D; Cagáňová, V; Peterka, M

2012-04-01

Sexual dimorphism is responsible for a substantial part of human facial variability, the study of which is essential for many scientific fields ranging from evolution to special biomedical topics. Our aim was to analyse the relationship between size variability and shape facial variability of sexual traits in the young adult Central European population and to construct average surface models of adult males and females. The method of geometric morphometrics allowed not only the identification of dimorphic traits, but also the evaluation of static allometry and the visualisation of sexual facial differences. Facial variability in the studied sample was characterised by a strong relationship between facial size and shape of sexual dimorphic traits. Large size of face was associated with facial elongation and vice versa. Regarding shape sexual dimorphic traits, a wide, vaulted and high forehead in combination with a narrow and gracile lower face were typical for females. Variability in shape dimorphic traits was smaller in females compared to males. For female classification, shape sexual dimorphic traits are more important, while for males the stronger association is with face size. Males generally had a closer inter-orbital distance and a deeper position of the eyes in relation to the facial plane, a larger and wider straight nose and nostrils, and more massive lower face. Using pseudo-colour maps to provide a detailed schematic representation of the geometrical differences between the sexes, we attempted to clarify the reasons underlying the development of such differences. Copyright © 2012 Elsevier GmbH. All rights reserved.

Consultant-Client Relationship and Knowledge Transfer in Small- and Medium-Sized Enterprises Change Processes.

PubMed

Martinez, Luis F; Ferreira, Aristides I; Can, Amina B

2016-04-01

Based on Szulanski's knowledge transfer model, this study examined how the communicational, motivational, and sharing of understanding variables influenced knowledge transfer and change processes in small- and medium-sized enterprises, particularly under projects developed by funded programs. The sample comprised 144 entrepreneurs, mostly male (65.3%) and mostly ages 35 to 45 years (40.3%), who filled an online questionnaire measuring the variables of "sharing of understanding," "motivation," "communication encoding competencies," "source credibility," "knowledge transfer," and "organizational change." Data were collected between 2011 and 2012 and measured the relationship between clients and consultants working in a Portuguese small- and medium-sized enterprise-oriented action learning program. To test the hypotheses, structural equation modeling was conducted to identify the antecedents of sharing of understanding, motivational, and communicational variables, which were positively correlated with the knowledge transfer between consultants and clients. This transfer was also positively correlated with organizational change. Overall, the study provides important considerations for practitioners and academicians and establishes new avenues for future studies concerning the issues of consultant-client relationship and the efficacy of Government-funded programs designed to improve performance of small- and medium-sized enterprises. © The Author(s) 2016.

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.

Spatial patterns of throughfall isotopic composition at the event and seasonal timescales

NASA Astrophysics Data System (ADS)

Allen, Scott T.; Keim, Richard F.; McDonnell, Jeffrey J.

2015-03-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of δ18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative δ18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (δ18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

Planetarium instructional efficacy: A research synthesis

NASA Astrophysics Data System (ADS)

Brazell, Bruce D.

The purpose of the current study was to explore the instructional effectiveness of the planetarium in astronomy education using meta-analysis. A review of the literature revealed 46 studies related to planetarium efficacy. However, only 19 of the studies satisfied selection criteria for inclusion in the meta-analysis. Selected studies were then subjected to coding procedures, which extracted information such as subject characteristics, experimental design, and outcome measures. From these data, 24 effect sizes were calculated in the area of student achievement and five effect sizes were determined in the area of student attitudes using reported statistical information. Mean effect sizes were calculated for both the achievement and the attitude distributions. Additionally, each effect size distribution was subjected to homogeneity analysis. The attitude distribution was found to be homogeneous with a mean effect size of -0.09, which was not significant, p = .2535. The achievement distribution was found to be heterogeneous with a statistically significant mean effect size of +0.28, p < .05. Since the achievement distribution was heterogeneous, the analog to the ANOVA procedure was employed to explore variability in this distribution in terms of the coded variables. The analog to the ANOVA procedure revealed that the variability introduced by the coded variables did not fully explain the variability in the achievement distribution beyond subject-level sampling error under a fixed effects model. Therefore, a random effects model analysis was performed which resulted in a mean effect size of +0.18, which was not significant, p = .2363. However, a large random effect variance component was determined indicating that the differences between studies were systematic and yet to be revealed. The findings of this meta-analysis showed that the planetarium has been an effective instructional tool in astronomy education in terms of student achievement. However, the meta-analysis revealed that the planetarium has not been a very effective tool for improving student attitudes towards astronomy.

An evaluation of the efficiency of minnow traps for estimating the abundance of minnows in desert spring systems

USGS Publications Warehouse

Peterson, James T.; Scheerer, Paul D.; Clements, Shaun

2015-01-01

Desert springs are sensitive aquatic ecosystems that pose unique challenges to natural resource managers and researchers. Among the most important of these is the need to accurately quantify population parameters for resident fish, particularly when the species are of special conservation concern. We evaluated the efficiency of baited minnow traps for estimating the abundance of two at-risk species, Foskett Speckled Dace Rhinichthys osculus ssp. and Borax Lake Chub Gila boraxobius, in desert spring systems in southeastern Oregon. We evaluated alternative sample designs using simulation and found that capture–recapture designs with four capture occasions would maximize the accuracy of estimates and minimize fish handling. We implemented the design and estimated capture and recapture probabilities using the Huggins closed-capture estimator. Trap capture probabilities averaged 23% and 26% for Foskett Speckled Dace and Borax Lake Chub, respectively, but differed substantially among sample locations, through time, and nonlinearly with fish body size. Recapture probabilities for Foskett Speckled Dace were, on average, 1.6 times greater than (first) capture probabilities, suggesting “trap-happy” behavior. Comparison of population estimates from the Huggins model with the commonly used Lincoln–Petersen estimator indicated that the latter underestimated Foskett Speckled Dace and Borax Lake Chub population size by 48% and by 20%, respectively. These biases were due to variability in capture and recapture probabilities. Simulation of fish monitoring that included the range of capture and recapture probabilities observed indicated that variability in capture and recapture probabilities in time negatively affected the ability to detect annual decreases by up to 20% in fish population size. Failure to account for variability in capture and recapture probabilities can lead to poor quality data and study inferences. Therefore, we recommend that fishery researchers and managers employ sample designs and estimators that can account for this variability.

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

ERIC Educational Resources Information Center

Olneck, Michael R.; Bills, David B.

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

Mineral Element Contents in Commercially Valuable Fish Species in Spain

PubMed Central

Peña-Rivas, Luis; Ortega, Eduardo; López-Martínez, Concepción; Olea-Serrano, Fátima; Lorenzo, Maria Luisa

2014-01-01

The aim of this study was to measure selected metal concentrations in Trachurus trachurus, Trachurus picturatus, and Trachurus mediterraneus, which are widely consumed in Spain. Principal component analysis suggested that the variable Cr was the main responsible variable for the identification of T. trachurus, the variables As and Sn for T. mediterraneus, and the rest of variables for T. picturatus. This well-defined discrimination between fish species provided by mineral element allows us to distinguish them on the basis of their metal content. Based on the samples collected, and recognizing the inferential limitation of the sample size of this study, the metal concentrations found are below the proposed limit values for human consumption. However, it should be taken into consideration that there are other dietary sources of these metals. In conclusion, metal contents in the fish species analyzed are acceptable for human consumption from a nutritional and toxicity point of view. PMID:24895678

Re-evaluating the link between brain size and behavioural ecology in primates.

PubMed

Powell, Lauren E; Isler, Karin; Barton, Robert A

2017-10-25

Comparative studies have identified a wide range of behavioural and ecological correlates of relative brain size, with results differing between taxonomic groups, and even within them. In primates for example, recent studies contradict one another over whether social or ecological factors are critical. A basic assumption of such studies is that with sufficiently large samples and appropriate analysis, robust correlations indicative of selection pressures on cognition will emerge. We carried out a comprehensive re-examination of correlates of primate brain size using two large comparative datasets and phylogenetic comparative methods. We found evidence in both datasets for associations between brain size and ecological variables (home range size, diet and activity period), but little evidence for an effect of social group size, a correlation which has previously formed the empirical basis of the Social Brain Hypothesis. However, reflecting divergent results in the literature, our results exhibited instability across datasets, even when they were matched for species composition and predictor variables. We identify several potential empirical and theoretical difficulties underlying this instability and suggest that these issues raise doubts about inferring cognitive selection pressures from behavioural correlates of brain size. © 2017 The Author(s).

Ancestral inference from haplotypes and mutations.

PubMed

Griffiths, Robert C; Tavaré, Simon

2018-04-25

We consider inference about the history of a sample of DNA sequences, conditional upon the haplotype counts and the number of segregating sites observed at the present time. After deriving some theoretical results in the coalescent setting, we implement rejection sampling and importance sampling schemes to perform the inference. The importance sampling scheme addresses an extension of the Ewens Sampling Formula for a configuration of haplotypes and the number of segregating sites in the sample. The implementations include both constant and variable population size models. The methods are illustrated by two human Y chromosome datasets. Copyright © 2018. Published by Elsevier Inc.

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Physician communication in the operating room: expanding application of face-negotiation theory to the health communication context.

PubMed

Kirschbaum, Kristin

2012-01-01

Communication variables that are associated with face-negotiation theory were examined in a sample of operating-room physicians. A survey was administered to anesthesiologists and surgeons at a teaching hospital in the southwestern United States to measure three variables commonly associated with face-negotiation theory: conflict-management style, face concern, and self-construal. The survey instrument that was administered to physicians includes items that measured these three variables in previous face-negotiation research with slight modification of item wording for relevance in the medical setting. The physician data were analyzed using confirmatory factor analysis, Pearson's correlations, and t-tests. Results of this initial investigation showed that variables associated with face-negotiation theory were evident in the sample physician population. In addition, the correlations were similar among variables in the medical sample as those found in previous face-negotiation research. Finally, t-tests suggest variance between anesthesiologists and surgeons on specific communication variables. These findings suggest three implications that warrant further investigation with expanded sample size: (1) An intercultural communication theory and instrument can be utilized for health communication research; (2) as applied in a medical context, face-negotiation theory can be expanded beyond traditional intercultural communication boundaries; and (3) theoretically based communication structures applied in a medical context could help explain physician miscommunication in the operating room to assist future design of communication training programs for operating-room physicians.

Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

USGS Publications Warehouse

Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

2007-01-01

This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than adequate for the majority of sedimentological applications, especially considering that the autocorrelation technique is estimated to be at least 100 times faster than traditional methods.

[Sex as a variable in research in psychotherapy, psychosomatic and medical psychology].

PubMed

Davies-Osterkamp, S

1994-01-01

All empirical studies (n = 113) published in "Psychotherapie, Psychosomatik, medizinische Psychologie" between 1988 and 1992 where analyzed concerning the question whether sex comparisons in at least one of the dependent variables were reported. The main results were that sex composition of the samples was not reported in 17% of the cases and that 62% of the studies did not report on sex comparisons. Only 25% of studies reported on sex differences in a metric which allows using this study for meta-analysis. Except for sample-size and sex-composition there were no study-features which distinguished between studies reporting or not reporting sex comparisons.

Monitoring disease progression with plasma creatinine in amyotrophic lateral sclerosis clinical trials

PubMed Central

van Eijk, Ruben P A; Eijkemans, Marinus J C; Ferguson, Toby A; Nikolakopoulos, Stavros; Veldink, Jan H; van den Berg, Leonard H

2018-01-01

Objectives Plasma creatinine is a predictor of survival in amyotrophic lateral sclerosis (ALS). It remains, however, to be established whether it can monitor disease progression and serve as surrogate endpoint in clinical trials. Methods We used clinical trial data from three cohorts of clinical trial participants in the LITRA, EMPOWER and PROACT studies. Longitudinal associations between functional decline, muscle strength and survival with plasma creatinine were assessed. Results were translated to trial design in terms of sample size and power. Results A total of 13 564 measurements were obtained for 1241 patients. The variability between patients in rate of decline was lower in plasma creatinine than in ALS functional rating scale–Revised (ALSFRS-R; p<0.001). The average rate of decline was faster in the ALSFRS-R, with less between-patient variability at baseline (p<0.001). Plasma creatinine had strong longitudinal correlations with the ALSFRS-R (0.43 (0.39–0.46), p<0.001), muscle strength (0.55 (0.51–0.58), p<0.001) and overall mortality (HR 0.88 (0.86–0.91, p<0.001)). Using plasma creatinine as outcome could reduce the sample size in trials by 21.5% at 18 months. For trials up to 10 months, the ALSFRS-R required a lower sample size. Conclusions Plasma creatinine is an inexpensive and easily accessible biomarker that exhibits less variability between patients with ALS over time and is predictive for the patient’s functional status, muscle strength and mortality risk. Plasma creatinine may, therefore, increase the power to detect treatment effects and could be incorporated in future ALS clinical trials as potential surrogate outcome. PMID:29084868

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

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.

Variable flexure-based fluid filter

DOEpatents

Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

2007-03-13

An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

Small area estimation (SAE) model: Case study of poverty in West Java Province

NASA Astrophysics Data System (ADS)

Suhartini, Titin; Sadik, Kusman; Indahwati

2016-02-01

This paper showed the comparative of direct estimation and indirect/Small Area Estimation (SAE) model. Model selection included resolve multicollinearity problem in auxiliary variable, such as choosing only variable non-multicollinearity and implemented principal component (PC). Concern parameters in this paper were the proportion of agricultural venture poor households and agricultural poor households area level in West Java Province. The approach for estimating these parameters could be performed based on direct estimation and SAE. The problem of direct estimation, three area even zero and could not be conducted by directly estimation, because small sample size. The proportion of agricultural venture poor households showed 19.22% and agricultural poor households showed 46.79%. The best model from agricultural venture poor households by choosing only variable non-multicollinearity and the best model from agricultural poor households by implemented PC. The best estimator showed SAE better then direct estimation both of the proportion of agricultural venture poor households and agricultural poor households area level in West Java Province. The solution overcame small sample size and obtained estimation for small area was implemented small area estimation method for evidence higher accuracy and better precision improved direct estimator.

Combining censored and uncensored data in a U-statistic: design and sample size implications for cell therapy research.

PubMed

Moyé, Lemuel A; Lai, Dejian; Jing, Kaiyan; Baraniuk, Mary Sarah; Kwak, Minjung; Penn, Marc S; Wu, Colon O

2011-01-01

The assumptions that anchor large clinical trials are rooted in smaller, Phase II studies. In addition to specifying the target population, intervention delivery, and patient follow-up duration, physician-scientists who design these Phase II studies must select the appropriate response variables (endpoints). However, endpoint measures can be problematic. If the endpoint assesses the change in a continuous measure over time, then the occurrence of an intervening significant clinical event (SCE), such as death, can preclude the follow-up measurement. Finally, the ideal continuous endpoint measurement may be contraindicated in a fraction of the study patients, a change that requires a less precise substitution in this subset of participants.A score function that is based on the U-statistic can address these issues of 1) intercurrent SCE's and 2) response variable ascertainments that use different measurements of different precision. The scoring statistic is easy to apply, clinically relevant, and provides flexibility for the investigators' prospective design decisions. Sample size and power formulations for this statistic are provided as functions of clinical event rates and effect size estimates that are easy for investigators to identify and discuss. Examples are provided from current cardiovascular cell therapy research.

Population entropies estimates of proteins

NASA Astrophysics Data System (ADS)

Low, Wai Yee

2017-05-01

The Shannon entropy equation provides a way to estimate variability of amino acids sequences in a multiple sequence alignment of proteins. Knowledge of protein variability is useful in many areas such as vaccine design, identification of antibody binding sites, and exploration of protein 3D structural properties. In cases where the population entropies of a protein are of interest but only a small sample size can be obtained, a method based on linear regression and random subsampling can be used to estimate the population entropy. This method is useful for comparisons of entropies where the actual sequence counts differ and thus, correction for alignment size bias is needed. In the current work, an R based package named EntropyCorrect that enables estimation of population entropy is presented and an empirical study on how well this new algorithm performs on simulated dataset of various combinations of population and sample sizes is discussed. The package is available at https://github.com/lloydlow/EntropyCorrect. This article, which was originally published online on 12 May 2017, contained an error in Eq. (1), where the summation sign was missing. The corrected equation appears in the Corrigendum attached to the pdf.

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.

Prospective, randomized, blinded evaluation of donor semen quality provided by seven commercial sperm banks.

PubMed

Carrell, Douglas T; Cartmill, Deborah; Jones, Kirtly P; Hatasaka, Harry H; Peterson, C Matthew

2002-07-01

To evaluate variability in donor semen quality between seven commercial donor sperm banks, within sperm banks, and between intracervical insemination and intrauterine insemination. Prospective, randomized, blind evaluation of commercially available donor semen samples. An academic andrology laboratory. Seventy-five cryopreserved donor semen samples were evaluated. Samples were coded, then blindly evaluated for semen quality. Standard semen quality parameters, including concentration, motility parameters, World Health Organization criteria morphology, and strict criteria morphology. Significant differences were observed between donor semen banks for most semen quality parameters analyzed in intracervical insemination samples. In general, the greatest variability observed between banks was in percentage progressive sperm motility (range, 8.8 +/- 5.8 to 42.4 +/- 5.5) and normal sperm morphology (strict criteria; range, 10.1 +/- 3.3 to 26.6 +/- 4.7). Coefficients of variation within sperm banks were generally high. These data demonstrate the variability of donor semen quality provided by commercial sperm banks, both between banks and within a given bank. No relationship was observed between the size or type of sperm bank and the degree of variability. The data demonstrate the lack of uniformity in the criteria used to screen potential semen donors and emphasize the need for more stringent screening criteria and strict quality control in processing samples.

Beamline 10.3.2 at ALS: a hard X-ray microprobe for environmental and materials sciences.

PubMed

Marcus, Matthew A; MacDowell, Alastair A; Celestre, Richard; Manceau, Alain; Miller, Tom; Padmore, Howard A; Sublett, Robert E

2004-05-01

Beamline 10.3.2 at the ALS is a bend-magnet line designed mostly for work on environmental problems involving heavy-metal speciation and location. It offers a unique combination of X-ray fluorescence mapping, X-ray microspectroscopy and micro-X-ray diffraction. The optics allow the user to trade spot size for flux in a size range of 5-17 microm in an energy range of 3-17 keV. The focusing uses a Kirkpatrick-Baez mirror pair to image a variable-size virtual source onto the sample. Thus, the user can reduce the effective size of the source, thereby reducing the spot size on the sample, at the cost of flux. This decoupling from the actual source also allows for some independence from source motion. The X-ray fluorescence mapping is performed with a continuously scanning stage which avoids the time overhead incurred by step-and-repeat mapping schemes. The special features of this beamline are described, and some scientific results shown.

The local environment of ice particles in arctic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Schlenczek, Oliver; Fugal, Jacob P.; Schledewitz, Waldemar; Borrmann, Stephan

2015-04-01

During the RACEPAC field campaign in April and May 2014, research flights were made with the Polar 5 and Polar 6 aircraft from the Alfred Wegener Institute in Arctic clouds near Inuvik, Northwest Territories, Canada. One flight with the Polar 6 aircraft, done on May 16, 2014, flew under precipitating, stratiform, mid-level clouds with several penetrations through cloud base. Measurements with HALOHolo, an airborne digital in-line holographic instrument for cloud particles, show ice particles in a field of other cloud particles in a local three-dimensional sample volume (~14x19x130 mm3 or ~35 cm^3). Each holographic sample volume is a snapshot of a 3-dimensional piece of cloud at the cm-scale with typically thousands of cloud droplets per sample volume, so each sample volume yields a statistically significant droplet size distribution. Holograms are recorded at a rate of six times per second, which provides one volume sample approx. every 12 meters along the flight path. The size resolution limit for cloud droplets is better than 1 µm due to advanced sizing algorithms. Shown are preliminary results of, (1) the ice/liquid water partitioning at the cloud base and the distribution of water droplets around each ice particle, and (2) spatial and temporal variability of the cloud droplet size distributions at cloud base.

Lack of association between ectoparasite intensities and rabies virus neutralizing antibody seroprevalence in wild big brown bats (Eptesicus fuscus), Fort Collins, Colorado

USGS Publications Warehouse

Pearce, R.D.; O'Shea, T.J.; Shankar, V.; Rupprecht, C.E.

2007-01-01

Recently, bat ectoparasites have been demonstrated to harbor pathogens of potential importance to humans. We evaluated antirabies antibody seroprevalence and the presence of ectoparasites in big brown bats (Eptesicus fuscus) sampled in 2002 and 2003 in Colorado to investigate if an association existed between ectoparasite intensity and exposure to rabies virus (RV). We used logistic regression and Akaike's Information Criteria adjusted for sample size (AICc) in a post-hoc analysis to investigate the relative importance of three ectoparasite species, as well as bat colony size, year sampled, age class, colony size, and year interaction on the presence of rabies virus neutralizing antibodies (VNA) in serum of wild E. fuscus. We obtained serum samples and ectoparasite counts from big brown bats simultaneously in 2002 and 2003. Although the presence of ectoparasites (Steatonyssus occidentalis and Spinturnix bakeri) were important in elucidating VNA seroprevalence, their intensities were higher in seronegative bats than in seropositive bats, and the presence of a third ectoparasite (Cimex pilosellus) was inconsequential. Colony size and year sampled were the most important variables in these AICc models. These findings suggest that these ectoparasites do not enhance exposure of big brown bats to RV. ?? 2007 Mary Ann Liebert, Inc.

Investigation to develop a multistage forest sampling inventory system using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. W. (Principal Investigator); Wert, S. L.

1975-01-01

The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.

Bite force estimation and the fiber architecture of felid masticatory muscles.

PubMed

Hartstone-Rose, Adam; Perry, Jonathan M G; Morrow, Caroline J

2012-08-01

Increasingly, analyses of craniodental dietary adaptations take into account mechanical properties of foods. However, masticatory muscle fiber architecture has been described for relatively few lineages, even though an understanding of the scaling of this anatomy can yield important information about adaptations for stretch and strength in the masticatory system. Data on the mandibular adductors of 28 specimens from nine species of felids representing nearly the entire body size range of the family allow us to evaluate the influence of body size and diet on the masticatory apparatus within this lineage. Masticatory muscle masses scale isometrically, tending toward positive allometry, with body mass and jaw length. This allometry becomes significant when the independent variable is a geometric mean of cranial variables. For all three body size proxies, the physiological cross-sectional area and predicted bite forces scale with significant positive allometry. Average fiber lengths (FL) tend toward negative allometry though with wide confidence intervals resulting from substantial scatter. We believe that these FL residuals are affected by dietary signals within the sample; though the mechanical properties of felid diets are relatively similar across species, the most durophagous species in our sample (the jaguar) appears to have relatively higher force production capabilities. The more notable dietary trend in our sample is the relationship between FL and relative prey size: felid species that predominantly consume relatively small prey have short masticatory muscle fibers, and species that regularly consume relatively large prey have relatively long fibers. This suggests an adaptive signal related to gape. Copyright © 2012 Wiley Periodicals, Inc.

Laser system refinements to reduce variability in infarct size in the rat photothrombotic stroke model

PubMed Central

Alaverdashvili, Mariam; Paterson, Phyllis G.; Bradley, Michael P.

2015-01-01

Background The rat photothrombotic stroke model can induce brain infarcts with reasonable biological variability. Nevertheless, we observed unexplained high inter-individual variability despite using a rigorous protocol. Of the three major determinants of infarct volume, photosensitive dye concentration and illumination period were strictly controlled, whereas undetected fluctuation in laser power output was suspected to account for the variability. New method The frequently utilized Diode Pumped Solid State (DPSS) lasers emitting 532 nm (green) light can exhibit fluctuations in output power due to temperature and input power alterations. The polarization properties of the Nd:YAG and Nd:YVO4 crystals commonly used in these lasers are another potential source of fluctuation, since one means of controlling output power uses a polarizer with a variable transmission axis. Thus, the properties of DPSS lasers and the relationship between power output and infarct size were explored. Results DPSS laser beam intensity showed considerable variation. Either a polarizer or a variable neutral density filter allowed adjustment of a polarized laser beam to the desired intensity. When the beam was unpolarized, the experimenter was restricted to using a variable neutral density filter. Comparison with existing method(s) Our refined approach includes continuous monitoring of DPSS laser intensity via beam sampling using a pellicle beamsplitter and photodiode sensor. This guarantees the desired beam intensity at the targeted brain area during stroke induction, with the intensity controlled either through a polarizer or variable neutral density filter. Conclusions Continuous monitoring and control of laser beam intensity is critical for ensuring consistent infarct size. PMID:25840363

COMMUNITY STRESSORS AND SUSCEPTIBILITY TO AIR POLLUTION IN URBAN ASTHMA

EPA Science Inventory

Given our large sample size within and across communities, our unique data on year-round fine-scale variability in multiple air pollutants, and our strong experience in community –based environmental health education and outreach, we believe that our study will provid...

Variability of carotid artery measurements on 3-Tesla MRI and its impact on sample size calculation for clinical research.

PubMed

Syed, Mushabbar A; Oshinski, John N; Kitchen, Charles; Ali, Arshad; Charnigo, Richard J; Quyyumi, Arshed A

2009-08-01

Carotid MRI measurements are increasingly being employed in research studies for atherosclerosis imaging. The majority of carotid imaging studies use 1.5 T MRI. Our objective was to investigate intra-observer and inter-observer variability in carotid measurements using high resolution 3 T MRI. We performed 3 T carotid MRI on 10 patients (age 56 +/- 8 years, 7 male) with atherosclerosis risk factors and ultrasound intima-media thickness > or =0.6 mm. A total of 20 transverse images of both right and left carotid arteries were acquired using T2 weighted black-blood sequence. The lumen and outer wall of the common carotid and internal carotid arteries were manually traced; vessel wall area, vessel wall volume, and average wall thickness measurements were then assessed for intra-observer and inter-observer variability. Pearson and intraclass correlations were used in these assessments, along with Bland-Altman plots. For inter-observer variability, Pearson correlations ranged from 0.936 to 0.996 and intraclass correlations from 0.927 to 0.991. For intra-observer variability, Pearson correlations ranged from 0.934 to 0.954 and intraclass correlations from 0.831 to 0.948. Calculations showed that inter-observer variability and other sources of error would inflate sample size requirements for a clinical trial by no more than 7.9%, indicating that 3 T MRI is nearly optimal in this respect. In patients with subclinical atherosclerosis, 3 T carotid MRI measurements are highly reproducible and have important implications for clinical trial design.

Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil in Moultonborough Bay, Lake Winnipesaukee, New Hampshire, 2005

USGS Publications Warehouse

Argue, Denise M.; Kiah, Richard G.; Denny, Jane F.; Deacon, Jeffrey R.; Danforth, William W.; Johnston, Craig M.; Smagula, Amy P.

2007-01-01

Geophysical, water, and sediment surveys were done to characterize the effects of surficial geology, water and sediment chemistry, and surficial-sediment composition on the distribution of variable leaf water-milfoil in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. Geophysical surveys were conducted in a 180-square-kilometer area, and water-quality and sediment samples were collected from 24 sites in the survey area during July 2005. Swath-bathymetric data revealed that Moultonborough Bay ranged in depth from less than 1 meter (m) to about 15 m and contained three embayments. Seismic-reflection profiles revealed erosion of the underlying bedrock and subsequent deposition of glaciolacustrine and Holocene lacustrine sediments within the survey area. Sediment thickness ranged from 5 m along the shoreward margins to more than 15 m in the embayments. Data from sidescan sonar, surficial-sediment samples, bottom photographs, and video revealed three distinct lake-floor environments: rocky nearshore, mixed nearshore, and muddy basin. Rocky nearshore environments were found in shallow water (less than 5 m deep) and contained sediments ranging from coarse silt to very coarse sand. Mixed nearshore environments also were found in shallow water and contained sediments ranging from silt to coarse sand with different densities of aquatic vegetation. Muddy basin environments contained the finest-grained sediments, ranging from fine to medium silt, and were in the deepest waters of the bay. Acoustic Ground Discrimination Systems (AGDS) survey data revealed that 86 percent of the littoral zone (the area along the margins of the bay and islands that extends from 0 to 4.3 m in water depth) contained submerged aquatic vegetation (SAV) in varying densities: approximately 36 percent contained SAV bottom cover of 25 percent or less, 43 percent contained SAV bottom cover of more than 25 and less than 75 percent, and approximately 7 percent contained SAV bottom cover of more than 75 percent. SAV included variable leaf water-milfoil, native milfoil, bassweed, pipewort, and other species, which were predominantly found near shoreward margins and at depths ranging from less than 1 to 4 m. AGDS data were used in a Geographic Information System to generate an interpolated map that distinguished variable leaf water-milfoil from other SAV. Furthermore, these data were used to isolate areas susceptible to variable leaf water-milfoil growth. Approximately 21 percent of the littoral zone contained dense beds (more than 59 percent bottom cover) of variable leaf water-milfoil, and an additional 44 percent was determined to be susceptible to variable leaf water-milfoil infestation. Depths differed significantly between sites with variable leaf water-milfoil and sites with other SAV (p = 0.04). Variable leaf water-milfoil was found at depths that ranged from 1 to 4 m, and other SAV had a depth range of 1 to 2 m. Although variable leaf water-milfoil was observed at greater depths than other SAV, it was not observed below the photic zone. Analysis of constituent concentrations from the water column, interstitial pore water, and sediment showed little correlation with the presence of variable leaf water-milfoil, with two exceptions. Iron concentrations were significantly lower at variable leaf water-milfoil sites than at other sampling sites (p = 0.04). Similarly, the percentage of total organic carbon also was significantly lower at the variable leaf water-milfoil sites than at other sampling sites (p = 0.04). Surficial-sediment-grain size had the greatest correlation to the presence of variable leaf water-milfoil. Variable leaf water-milfoil was predominantly growing in areas of coarse sand (median grain-size 0.62 millimeters). Surficial-sediment-grain size was also correlated with total ammonia plus organic nitrogen (Rho = 0.47; p = 0.02) and with total phosphorus (Rho = 0.44; p = 0.05) concentrations in interstitial pore-water samples.

Physical activity and body image among men and boys: A meta-analysis.

PubMed

Bassett-Gunter, Rebecca; McEwan, Desmond; Kamarhie, Aria

2017-09-01

Three meta-analytic reviews have concluded that physical activity is positively related to body image. Historically, research regarding physical activity and body image has been disproportionately focused on female samples. For example, the most recent meta-analysis (2009) extracted 56 effect sizes for women and only 12 for men. The current paper provides an update to the literature regarding the relationship between physical activity and body image among men and boys across 84 individual effect sizes. The analysis also provides insight regarding moderator variables including participant age, and physical activity type and intensity. Overall, physical activity was positively related to body image among men and boys with various moderator variables warranting further investigation. Pragmatic implications are discussed as well as the limitations within existing research and need for additional research to further understand moderator and mediator variables. Copyright © 2017 Elsevier Ltd. All rights reserved.

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

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

Nyflot, MJ; Yang, F; Byrd, D

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850,more » 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.« less

The Interannual Stability of Cumulative Frequency Distributions for Convective System Size and Intensity

NASA Technical Reports Server (NTRS)

Mohr, Karen I.; Molinari, John; Thorncroft, Chris D,

2010-01-01

The characteristics of convective system populations in West Africa and the western Pacific tropical cyclone basin were analyzed to investigate whether interannual variability in convective activity in tropical continental and oceanic environments is driven by variations in the number of events during the wet season or by favoring large and/or intense convective systems. Convective systems were defined from TRMM data as a cluster of pixels with an 85 GHz polarization-corrected brightness temperature below 255 K and with an area at least 64 km 2. The study database consisted of convective systems in West Africa from May Sep for 1998-2007 and in the western Pacific from May Nov 1998-2007. Annual cumulative frequency distributions for system minimum brightness temperature and system area were constructed for both regions. For both regions, there were no statistically significant differences among the annual curves for system minimum brightness temperature. There were two groups of system area curves, split by the TRMM altitude boost in 2001. Within each set, there was no statistically significant interannual variability. Sub-setting the database revealed some sensitivity in distribution shape to the size of the sampling area, length of sample period, and climate zone. From a regional perspective, the stability of the cumulative frequency distributions implied that the probability that a convective system would attain a particular size or intensity does not change interannually. Variability in the number of convective events appeared to be more important in determining whether a year is wetter or drier than normal.

Reinforcement Learning Trees

PubMed Central

Zhu, Ruoqing; Zeng, Donglin; Kosorok, Michael R.

2015-01-01

In this paper, we introduce a new type of tree-based method, reinforcement learning trees (RLT), which exhibits significantly improved performance over traditional methods such as random forests (Breiman, 2001) under high-dimensional settings. The innovations are three-fold. First, the new method implements reinforcement learning at each selection of a splitting variable during the tree construction processes. By splitting on the variable that brings the greatest future improvement in later splits, rather than choosing the one with largest marginal effect from the immediate split, the constructed tree utilizes the available samples in a more efficient way. Moreover, such an approach enables linear combination cuts at little extra computational cost. Second, we propose a variable muting procedure that progressively eliminates noise variables during the construction of each individual tree. The muting procedure also takes advantage of reinforcement learning and prevents noise variables from being considered in the search for splitting rules, so that towards terminal nodes, where the sample size is small, the splitting rules are still constructed from only strong variables. Last, we investigate asymptotic properties of the proposed method under basic assumptions and discuss rationale in general settings. PMID:26903687

Response Variability in Commercial MOSFET SEE Qualification

DOE PAGES

George, J. S.; Clymer, D. A.; Turflinger, T. L.; ...

2016-12-01

Single-event effects (SEE) evaluation of five different part types of next generation, commercial trench MOSFETs indicates large part-to-part variation in determining a safe operating area (SOA) for drain-source voltage (V DS) following a test campaign that exposed >50 samples per part type to heavy ions. These results suggest a determination of a SOA using small sample sizes may fail to capture the full extent of the part-to-part variability. An example method is discussed for establishing a Safe Operating Area using a one-sided statistical tolerance limit based on the number of test samples. Finally, burn-in is shown to be a criticalmore » factor in reducing part-to-part variation in part response. Implications for radiation qualification requirements are also explored.« less

Response Variability in Commercial MOSFET SEE Qualification

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

George, J. S.; Clymer, D. A.; Turflinger, T. L.

Single-event effects (SEE) evaluation of five different part types of next generation, commercial trench MOSFETs indicates large part-to-part variation in determining a safe operating area (SOA) for drain-source voltage (V DS) following a test campaign that exposed >50 samples per part type to heavy ions. These results suggest a determination of a SOA using small sample sizes may fail to capture the full extent of the part-to-part variability. An example method is discussed for establishing a Safe Operating Area using a one-sided statistical tolerance limit based on the number of test samples. Finally, burn-in is shown to be a criticalmore » factor in reducing part-to-part variation in part response. Implications for radiation qualification requirements are also explored.« less

Repeatability of automated perimetry: a comparison between standard automated perimetry with stimulus size III and V, matrix, and motion perimetry.

PubMed

Wall, Michael; Woodward, Kimberly R; Doyle, Carrie K; Artes, Paul H

2009-02-01

Standard automated perimetry (SAP) shows a marked increase in variability in damaged areas of the visual field. This study was conducted to test the hypothesis that larger stimuli are associated with more uniform variability, by investigating the retest variability of four perimetry tests: standard automated perimetry size III (SAP III), with the SITA standard strategy; SAP size V (SAP V), with the full-threshold strategy; Matrix (FDT II), and Motion perimetry. One eye each of 120 patients with glaucoma was examined on the same day with these four perimetric tests and retested 1 to 8 weeks later. The decibel scales were adjusted to make the test's scales numerically similar. Retest variability was examined by establishing the distributions of retest threshold estimates, for each threshold level observed at the first test. The 5th and 95th percentiles of the retest distribution were used as point-wise limits of retest variability. Regression analyses were performed to quantify the relationship between visual field sensitivity and variability. With SAP III, the retest variability increased substantially with reducing sensitivity. Corresponding increases with SAP V, Matrix, and Motion perimetry were considerably smaller or absent. With SAP III, sensitivity explained 22% of the retest variability (r(2)), whereas corresponding data for SAP V, Matrix, and Motion perimetry were 12%, 2%, and 2%, respectively. Variability of Matrix and Motion perimetry does not increase as substantially as that of SAP III in damaged areas of the visual field. Increased sampling with the larger stimuli of these techniques is the likely explanation for this finding. These properties may make these stimuli excellent candidates for early detection of visual field progression.

Apatite (U-Th-Sm)/He age dispersion arising from analysis of variable grain sizes and broken crystals - examples from the Scottish Southern Uplands

NASA Astrophysics Data System (ADS)

Łuszczak, Katarzyna; Persano, Cristina; Stuart, Finlay; Brown, Roderick

2016-04-01

Apatite (U-Th-Sm)/He (AHe) thermochronometry is a powerful technique for deciphering denudation of the uppermost crust. However, the age dispersion of single grains from the same rock is typical, and this hampers establishing accurate thermal histories when low grain numbers are analysed. Dispersion arising from the analysis of broken crystal fragments[1] has been proposed as an important cause of age dispersion, along with grain size and radiation damage. A new tool, Helfrag[2], allows constraints to be placed on the low temperature history derived from the analysis of apatite crystal fragments. However, the age dispersion model has not been fully tested on natural samples yet. We have performed AHe analysis of multiple (n = 20-25) grains from four rock samples from the Scottish Southern Uplands, which were subjected to the same exhumation episodes, although, the amount of exhumation varied between the localities. This is evident from the range of AFT ages (˜60 to ˜200 Ma) and variable thermal histories showing either strong, moderate and no support for a rapid cooling event at ˜60 Ma. Different apatite size and fragment geometry were analysed in order to maximise age dispersion. In general, the age dispersion increases with increasing AFT age (from 47% to 127%), consistent with the prediction from the fragmentation model. Thermal histories obtained using Helfrag were compared with those obtained by standard codes based on the spherical approximation. In one case, the Helfrag model was capable of resolving the higher complexity of the thermal history of the rock, constraining several heating/cooling events that are not predicted by the standard models, but are in good agreement with the regional geology. In other cases, the thermal histories are similar for both Helfrag and standard models and the age predictions for the Helfrag are only slightly better than for standard model, implying that the grain size has the dominant role in generating the age dispersion. Rather than suggesting that grain size is the predominant factor in controlling age dispersion in all data sets, our results may be linked to the actual size of the picked grains; for grain widths smaller than 100 μm, the He profile within the crystal may not be differentiated enough to produce a dispersion measureable outside the uncertainty associated with the age. It is also easier for long-thin and short-thick than long-thick and short-thin grains to be preserved; this minimises the age dispersion that can be generated from fragmentation. We suggest, that in order to obtain valuable information from both fragmentation and grain size >20 large (width >100 μm) grain fragments of variable length have to be analyzed, together with a few smaller grains. Our results point to a strategy that favours multiple single-grain AHe ages determinations on carefully selected samples, with good quality apatite crystals of variable dimensions rather than fewer determinations on many samples. [1] Brown, R. et al. 2013.Geochim. Cosmochim. Acta.122, 478-497 [2] Beucher, R. et al. 2013.Geochim. Cosmochim. Acta. 120, 395-416.

The Role of Body Size in Mate Selection among African American Young Adults

PubMed Central

Simons, Leslie G.; Simons, Ronald L.

2016-01-01

A profusion of studies have demonstrated that body size is a major factor in mate selection for both men and women. The particular role played by weight, however, has been subject to some debate, particularly with respect to the types of body sizes deemed most attractive, and scholars have questioned the degree to which body size preferences are constant across groups. In this paper, we drew from two perspectives on this issue, Sexual Strategies Theory and what we termed the cultural variability perspective, and used survey data to examine how body size was associated with both casual dating and serious romantic relationships. We used a United States sample of 386 African American adolescents and young adults between ages 16 and 21, living in the Midwest and Southeast, and who were enrolled in either high school or college. Results showed that overweight women were more likely to report casually dating than women in the thinnest weight category. Body size was not related to dating status among men. Among women, the results suggest stronger support for the cultural variability argument than for Sexual Strategies Theory. Potential explanations for these findings are discussed. PMID:26973377

Validation of the Six Sigma Z-score for the quality assessment of clinical laboratory timeliness.

PubMed

Ialongo, Cristiano; Bernardini, Sergio

2018-03-28

The International Federation of Clinical Chemistry and Laboratory Medicine has introduced in recent times the turnaround time (TAT) as mandatory quality indicator for the postanalytical phase. Classic TAT indicators, namely, average, median, 90th percentile and proportion of acceptable test (PAT), are in use since almost 40 years and to date represent the mainstay for gauging the laboratory timeliness. In this study, we investigated the performance of the Six Sigma Z-score, which was previously introduced as a device for the quantitative assessment of timeliness. A numerical simulation was obtained modeling the actual TAT data set using the log-logistic probability density function. Five thousand replicates for each size of the artificial TAT random sample (n=20, 50, 250 and 1000) were generated, and different laboratory conditions were simulated manipulating the PDF in order to generate more or less variable data. The Z-score and the classic TAT indicators were assessed for precision (%CV), robustness toward right-tailing (precision at different sample variability), sensitivity and specificity. Z-score showed sensitivity and specificity comparable to PAT (≈80% with n≥250), but superior precision that ranged within 20% by moderately small sized samples (n≥50); furthermore, Z-score was less affected by the value of the cutoff used for setting the acceptable TAT, as well as by the sample variability that reflected into the magnitude of right-tailing. The Z-score was a valid indicator of laboratory timeliness and a suitable device to improve as well as to maintain the achieved quality level.

An ultrahigh vacuum fast-scanning and variable temperature scanning tunneling microscope for large scale imaging.

PubMed

Diaconescu, Bogdan; Nenchev, Georgi; de la Figuera, Juan; Pohl, Karsten

2007-10-01

We describe the design and performance of a fast-scanning, variable temperature scanning tunneling microscope (STM) operating from 80 to 700 K in ultrahigh vacuum (UHV), which routinely achieves large scale atomically resolved imaging of compact metallic surfaces. An efficient in-vacuum vibration isolation and cryogenic system allows for no external vibration isolation of the UHV chamber. The design of the sample holder and STM head permits imaging of the same nanometer-size area of the sample before and after sample preparation outside the STM base. Refractory metal samples are frequently annealed up to 2000 K and their cooldown time from room temperature to 80 K is 15 min. The vertical resolution of the instrument was found to be about 2 pm at room temperature. The coarse motor design allows both translation and rotation of the scanner tube. The total scanning area is about 8 x 8 microm(2). The sample temperature can be adjusted by a few tens of degrees while scanning over the same sample area.

Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Physician Responses to Multiple Questionnaire Mailings.

ERIC Educational Resources Information Center

Sobal, Jeffery; And Others

1990-01-01

Three questionnaire mailings to 1,535 physicians that produced 977 responses were analyzed. The only variable significantly different across the mailings was medical specialty. This finding indicates that the more homogeneous the group the greater the response rate. Issues of nonresponse bias and insufficient sample size are discussed. (TJH)

Intrinsic Variability in Shell and Soft Tissue Growth of the Freshwater Mussel Lampsilis siliquoidea

PubMed Central

Larson, James H.; Eckert, Nathan L.; Bartsch, Michelle R.

2014-01-01

Freshwater mussels are ecologically and economically important members of many aquatic ecosystems, but are globally among the most imperiled taxa. Propagation techniques for mussels have been developed and used to boost declining and restore extirpated populations. Here we use a cohort of propagated mussels to estimate the intrinsic variability in size and growth rate of Lampsilis siliquoidea (a commonly propagated species). Understanding the magnitude and pattern of variation in data is critical to determining whether effects observed in nature or experimental treatments are likely to be important. The coefficient of variation (CV) of L. siliquoidea soft tissues (6.0%) was less than the CV of linear shell dimensions (25.1–66.9%). Size-weight relationships were best when mussel width (the maximum left-right dimension with both valves appressed) was used as a predictor, but 95% credible intervals on these predictions for soft tissues were ∼145 mg wide (about 50% of the mean soft tissue mass). Mussels in this study were treated identically, raised from a single cohort and yet variation in soft tissue mass at a particular size class (as determined by shell dimensions) was still high. High variability in mussel size is often acknowledged, but seldom discussed in the context of mussel conservation. High variability will influence the survival of stocked juvenile cohorts, may affect the ability to experimentally detect sublethal stressors and may lead to incongruities between the effects that mussels have on structure (via hard shells) and biogeochemical cycles (via soft tissue metabolism). Given their imperiled status and longevity, there is often reluctance to destructively sample unionid mussel soft tissues even in metabolic studies (e.g., studies of nutrient cycling). High intrinsic variability suggests that using shell dimensions (particularly shell length) as a response variable in studies of sublethal stressors or metabolic processes will make confident identifications of smaller effect sizes difficult. PMID:25411848

Intrinsic variability in shell and soft tissue growth of the freshwater mussel Lampsilis siliquoidea

USGS Publications Warehouse

Larson, James H.; Eckert, Nathan L.; Bartsch, Michelle

2014-01-01

Freshwater mussels are ecologically and economically important members of many aquatic ecosystems, but are globally among the most imperiled taxa. Propagation techniques for mussels have been developed and used to boost declining and restore extirpated populations. Here we use a cohort of propagated mussels to estimate the intrinsic variability in size and growth rate of Lampsilis siliquoidea (a commonly propagated species). Understanding the magnitude and pattern of variation in data is critical to determining whether effects observed in nature or experimental treatments are likely to be important. The coefficient of variation (CV) of L. siliquoidea soft tissues (6.0%) was less than the CV of linear shell dimensions (25.1-66.9%). Size-weight relationships were best when mussel width (the maximum left-right dimension with both valves appressed) was used as a predictor, but 95% credible intervals on these predictions for soft tissues were ~145 mg wide (about 50% of the mean soft tissue mass). Mussels in this study were treated identically, raised from a single cohort and yet variation in soft tissue mass at a particular size class (as determined by shell dimensions) was still high. High variability in mussel size is often acknowledged, but seldom discussed in the context of mussel conservation. High variability will influence the survival of stocked juvenile cohorts, may affect the ability to experimentally detect sublethal stressors and may lead to incongruities between the effects that mussels have on structure (via hard shells) and biogeochemical cycles (via soft tissue metabolism). Given their imperiled status and longevity, there is often reluctance to destructively sample unionid mussel soft tissues even in metabolic studies (e.g., studies of nutrient cycling). High intrinsic variability suggests that using shell dimensions (particularly shell length) as a response variable in studies of sublethal stressors or metabolic processes will make confident identifications of smaller effect sizes difficult.

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

PubMed

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

2017-01-01

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

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

Characteristics associated with organizational independence in consumer-operated service organizations.

PubMed

Tanenbaum, Sandra J

2011-01-01

This research compares two types of consumer organizations in one state in order to explore the significance of organizational independence for internal structure/operations and external relationships. The first type, consumeroperated service organizations (COSOs), are independent and fully self-governing; the second are peer-support service organizations (PSSOs), which are part of larger non-consumer entities. Mail surveys were completed by COSO and PSSO directors of a geographically representative sample of organizations; telephone interviews were conducted with a sub-sample. Owing to small sample size, matched COSO-PSSO pairs were analyzed using non-parametric statistics. COSOs and PSSOs are similar in some ways, e.g., types of services provided, but significantly different on internal variables, such as budget size, and external variables, such as number of relationships with community groups. Organizational independence appears to be a significant characteristic for consumer service organizations and should be encouraged by funders and among participants. Funders might establish administrative and/or programmatic measures to support consumer organizations that are independent or moving toward independence; their participants would also benefit from the provision, by authorities or advocates, of materials to guide organizations toward, for example, 501(c)3 status.

Measuring the specific surface area of natural and manmade glasses: effects of formation process, morphology, and particle size

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

Papelis, Charalambos; Um, Wooyong; Russel, Charles E.

2003-03-28

The specific surface area of natural and manmade solid materials is a key parameter controlling important interfacial processes in natural environments and engineered systems, including dissolution reactions and sorption processes at solid-fluid interfaces. To improve our ability to quantify the release of trace elements trapped in natural glasses, the release of hazardous compounds trapped in manmade glasses, or the release of radionuclides from nuclear melt glass, we measured the specific surface area of natural and manmade glasses as a function of particle size, morphology, and composition. Volcanic ash, volcanic tuff, tektites, obsidian glass, and in situ vitrified rock were analyzed.more » Specific surface area estimates were obtained using krypton as gas adsorbent and the BET model. The range of surface areas measured exceeded three orders of magnitude. A tektite sample had the highest surface area (1.65 m2/g), while one of the samples of in situ vitrified rock had the lowest surf ace area (0.0016 m2/g). The specific surface area of the samples was a function of particle size, decreasing with increasing particle size. Different types of materials, however, showed variable dependence on particle size, and could be assigned to one of three distinct groups: (1) samples with low surface area dependence on particle size and surface areas approximately two orders of magnitude higher than the surface area of smooth spheres of equivalent size. The specific surface area of these materials was attributed mostly to internal porosity and surface roughness. (2) samples that showed a trend of decreasing surface area dependence on particle size as the particle size increased. The minimum specific surface area of these materials was between 0.1 and 0.01 m2/g and was also attributed to internal porosity and surface roughness. (3) samples whose surface area showed a monotonic decrease with increasing particle size, never reaching an ultimate surface area limit within the particle size range examined. The surface area results were consistent with particle morphology, examined by scanning electron microscopy, and have significant implications for the release of radionuclides and toxic metals in the environment.« less

Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

NASA Astrophysics Data System (ADS)

García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

2018-04-01

Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important variable, with Landsat Tasselled Cap Transformation components barely contributing to the models for two of the study sites whereas it had a significant contribution at the third one. Over the temperate conifer forests, Landsat Tasselled Cap variables contributed more than the ALOS-PALSAR HV band to predict the landscape height variability. In all cases, incorporation of multispectral data improved the retrieval of forest canopy height and reduced the estimation uncertainty for tall forests. Finally, we concluded that models trained at one study site had higher uncertainty when applied to other sites, but a model developed from multiple sites performed equally to site-specific models to predict forest canopy height. This result suggest that a biome level model developed from several study sites can be used as a reliable estimator of biome-level forest structure from existing satellite imagery.

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

PubMed

Moustakas, Aristides; Evans, Matthew R

2015-02-28

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

A large-scale investigation of microplastic contamination: Abundance and characteristics of microplastics in European beach sediment.

PubMed

Lots, Froukje A E; Behrens, Paul; Vijver, Martina G; Horton, Alice A; Bosker, Thijs

2017-10-15

Here we present the large-scale distribution of microplastic contamination in beach sediment across Europe. Sediment samples were collected from 23 locations across 13 countries by citizen scientists, and analysed using a standard operating procedure. We found significant variability in the concentrations of microplastics, ranging from 72±24 to 1512±187 microplastics per kg of dry sediment, with high variability within sampling locations. Three hotspots of microplastic accumulation (>700 microplastics per kg of dry sediment) were found. There was limited variability in the physico-chemical characteristics of the plastics across sampling locations. The majority of the microplastics were fibrous, <1mm in size, and blue/black in colour. In addition, using Raman spectrometry we identified particles as polyester, polyethylene, and polypropylene. Our research is the first large spatial-scale analysis of microplastics on European beaches giving insights into the nature and extent of the microplastic challenge. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Effects of Popping Popcorn Under Reduced Pressure

NASA Astrophysics Data System (ADS)

Quinn, Paul; Cooper, Amanda

2008-03-01

In our experiments, we model the popping of popcorn as an adiabatic process and develop a process for improving the efficiency of popcorn production. By lowering the pressure of the popcorn during the popping process, we induce an increase in popcorn size, while decreasing the number of remaining unpopped kernels. In this project we run numerous experiments using three of the most common popping devices, a movie popcorn maker, a stove pot, and a microwave. We specifically examine the effects of varying the pressure on total sample size, flake size and waste. An empirical relationship is found between these variables and the pressure.

Studies in Support of the Application of Statistical Theory to Design and Evaluation of Operational Tests. Annex D. An Application of Bayesian Statistical Methods in the Determination of Sample Size for Operational Testing in the U.S. Army

DTIC Science & Technology

1977-07-01

SIZE C XNI. C UE2 - UTILITY OF EXPERIMENT OF SIZE C XN2. C ICHECK - VARIABLE USLD TO CHECK FOR C TERMINATION, C~C DIMENSION SUBLIM{20),UPLIM(20),UEI(20...1J=UPLIM(K4-I)-XNI (K+1)+SU8LIt1(K+i*. C CHECK FOR TERMINATION. 944 ICHECK =SUBLIM(K)+2 IFIICHECK.GEUPLiHMK.,OR.K.G1.20’ GO TO 930 GO TO 920 930

Experimental design, power and sample size for animal reproduction experiments.

PubMed

Chapman, Phillip L; Seidel, George E

2008-01-01

The present paper concerns statistical issues in the design of animal reproduction experiments, with emphasis on the problems of sample size determination and power calculations. We include examples and non-technical discussions aimed at helping researchers avoid serious errors that may invalidate or seriously impair the validity of conclusions from experiments. Screen shots from interactive power calculation programs and basic SAS power calculation programs are presented to aid in understanding statistical power and computing power in some common experimental situations. Practical issues that are common to most statistical design problems are briefly discussed. These include one-sided hypothesis tests, power level criteria, equality of within-group variances, transformations of response variables to achieve variance equality, optimal specification of treatment group sizes, 'post hoc' power analysis and arguments for the increased use of confidence intervals in place of hypothesis tests.

Temporal dynamics of linkage disequilibrium in two populations of bighorn sheep

PubMed Central

Miller, Joshua M; Poissant, Jocelyn; Malenfant, René M; Hogg, John T; Coltman, David W

2015-01-01

Linkage disequilibrium (LD) is the nonrandom association of alleles at two markers. Patterns of LD have biological implications as well as practical ones when designing association studies or conservation programs aimed at identifying the genetic basis of fitness differences within and among populations. However, the temporal dynamics of LD in wild populations has received little empirical attention. In this study, we examined the overall extent of LD, the effect of sample size on the accuracy and precision of LD estimates, and the temporal dynamics of LD in two populations of bighorn sheep (Ovis canadensis) with different demographic histories. Using over 200 microsatellite loci, we assessed two metrics of multi-allelic LD, D′, and χ′2. We found that both populations exhibited high levels of LD, although the extent was much shorter in a native population than one that was founded via translocation, experienced a prolonged bottleneck post founding, followed by recent admixture. In addition, we observed significant variation in LD in relation to the sample size used, with small sample sizes leading to depressed estimates of the extent of LD but inflated estimates of background levels of LD. In contrast, there was not much variation in LD among yearly cross-sections within either population once sample size was accounted for. Lack of pronounced interannual variability suggests that researchers may not have to worry about interannual variation when estimating LD in a population and can instead focus on obtaining the largest sample size possible. PMID:26380673

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

Specific-age group sex estimation of infants through geometric morphometrics analysis of pubis and ischium.

PubMed

Estévez Campo, Enrique José; López-Lázaro, Sandra; López-Morago Rodríguez, Claudia; Alemán Aguilera, Inmaculada; Botella López, Miguel Cecilio

2018-05-01

Sex determination of unknown individuals is one of the primary goals of Physical and Forensic Anthropology. The adult skeleton can be sexed using both morphological and metric traits on a large number of bones. The human pelvis is often used as an important element of adult sex determination. However, studies carried out about the pelvic bone in subadult individuals present several limitations due the absence of sexually dimorphic characteristics. In this study, we analyse the sexual dimorphism of the immature pubis and ischium bones, attending to their shape (Procrustes residuals) and size (centroid size), using an identified sample of subadult individuals composed of 58 individuals for the pubis and 83 for the ischium, aged between birth and 1year of life, from the Granada osteological collection of identified infants (Granada, Spain). Geometric morphometric methods and discriminant analysis were applied to this study. The results of intra- and inter-observer error showed good and excellent agreement in the location of coordinates of landmarks and semilandmarks, respectively. Principal component analysis performed on shape and size variables showed superposition of the two sexes, suggesting a low degree of sexual dimorphism. Canonical variable analysis did not show significant changes between the male and female shapes. As a consequence, discriminant analysis with leave-one-out cross validation provided low classification accuracy. The results suggested a low degree of sexual dimorphism supported by significant sexual dimorphism in the subadult sample and poor cross-validated classification accuracy. The inclusion of centroid size as a discriminant variable does not imply a significant improvement in the results of the analysis. The similarities found between the sexes prevent consideration of pubic and ischial morphology as a sex estimator in early stages of development. The authors suggest extending this study by analysing the different trajectories of shape and size in later ontogeny between males and females. Copyright © 2018 Elsevier B.V. All rights reserved.

Ecology and shell chemistry of Loxoconcha matagordensis

USGS Publications Warehouse

Cronin, T. M.; Kamiya, T.; Dwyer, G.S.; Belkin, H.; Vann, C.D.; Schwede, S.; Wagner, R.

2005-01-01

Studies of the seasonal ecology and shell chemistry of the ostracode Loxoconcha matagordensis and related species of Loxoconcha from regions off eastern North America reveal that shell size and trace elemental (Mg/Ca ratio) composition are useful in paleothermometry using fossil populations. Seasonal sampling of populations from Chesapeake Bay, augmented by samples from Florida Bay, indicate that shell size is inversely proportional to water temperature and that Mg/Ca ratios are positively correlated with the water temperature in which the adult carapace was secreted. Microprobe analyses of sectioned valves reveal intra-shell variability in Mg/Ca ratios but this does not strongly influence the utility of whole shell Mg/Ca analyses for paleoclimate application.

Efficacy of a strategy for implementing a guideline for the control of cardiovascular risk in a primary healthcare setting: the SIRVA2 study a controlled, blinded community intervention trial randomised by clusters

PubMed Central

2011-01-01

This work describes the methodology used to assess a strategy for implementing clinical practice guidelines (CPG) for cardiovascular risk control in a health area of Madrid. Background The results on clinical practice of introducing CPGs have been little studied in Spain. The strategy used to implement a CPG is known to influence its final use. Strategies based on the involvement of opinion leaders and that are easily executed appear to be among the most successful. Aim The main aim of the present work was to compare the effectiveness of two strategies for implementing a CPG designed to reduce cardiovascular risk in the primary healthcare setting, measured in terms of improvements in the recording of calculated cardiovascular risk or specific risk factors in patients' medical records, the control of cardiovascular risk factors, and the incidence of cardiovascular events. Methods This study involved a controlled, blinded community intervention in which the 21 health centres of the Number 2 Health Area of Madrid were randomly assigned by clusters to be involved in either a proposed CPG implementation strategy to reduce cardiovascular risk, or the normal dissemination strategy. The study subjects were patients ≥ 45 years of age whose health cards showed them to belong to the studied health area. The main variable examined was the proportion of patients whose medical histories included the calculation of their cardiovascular risk or that explicitly mentioned the presence of variables necessary for its calculation. The sample size was calculated for a comparison of proportions with alpha = 0.05 and beta = 0.20, and assuming that the intervention would lead to a 15% increase in the measured variables. Corrections were made for the design effect, assigning a sample size to each cluster proportional to the size of the population served by the corresponding health centre, and assuming losses of 20%. This demanded a final sample size of 620 patients. Data were analysed using summary measures for each cluster, both in making estimates and for hypothesis testing. Analysis of the variables was made on an intention-to-treat basis. Trial Registration ClinicalTrials.gov: NCT01270022 PMID:21504570

Supercritical Fluid Extraction and Analysis of Tropospheric Aerosol Particles

NASA Astrophysics Data System (ADS)

Hansen, Kristen J.

An integrated sampling and supercritical fluid extraction (SFE) cell has been designed for whole-sample analysis of organic compounds on tropospheric aerosol particles. The low-volume extraction cell has been interfaced with a sampling manifold for aerosol particle collection in the field. After sample collection, the entire SFE cell was coupled to a gas chromatograph; after on-line extraction, the cryogenically -focused sample was separated and the volatile compounds detected with either a mass spectrometer or a flame ionization detector. A 20-minute extraction at 450 atm and 90 ^circC with pure supercritical CO _2 is sufficient for quantitative extraction of most volatile compounds in aerosol particle samples. A comparison between SFE and thermal desorption, the traditional whole-sample technique for analyses of this type, was performed using ambient aerosol particle samples, as well as samples containing known amounts of standard analytes. The results of these studies indicate that SFE of atmospheric aerosol particles provides quantitative measurement of several classes of organic compounds. SFE provides information that is complementary to that gained by the thermal desorption analysis. The results also indicate that SFE with CO _2 can be validated as an alternative to thermal desorption for quantitative recovery of several organic compounds. In 1989, the organic constituents of atmospheric aerosol particles collected at Niwot Ridge, Colorado, along with various physical and meteorological data, were measured during a collaborative field study. Temporal changes in the composition of samples collected during summertime at the rural site were studied. Thermal desorption-GC/FID was used to quantify selected compounds in samples collected during the field study. The statistical analysis of the 1989 Niwot Ridge data set is presented in this work. Principal component analysis was performed on thirty-one variables selected from the data set in order to ascertain different source and process components, and to examine concentration changes in groups of variables with respect to time of day and meteorological conditions. Seven orthogonal groups of variables resulted from the statistical analysis; the groups serve as molecular markers for different biologic and anthropogenic emission sources. In addition, the results of the statistical analysis were used to investigate how several emission source contributions vary with respect to local atmospheric dynamics. Field studies were conducted in the urban environment in and around Boulder, CO. to characterize the dynamics, chemistry, and emission sources which affect the composition and concentration of different size-fractions of aerosol particles in the Boulder air mass. Relationships between different size fractions of particles and some gas-phase pollutants were elucidated. These field studies included an investigation of seasonal variations in the organic content and concentration of aerosol particles, and how these characteristics are related to local meteorology and to the concentration of some gas-phase pollutants. The elemental and organic composition of aerosol particles was investigated according to particle size in preliminary studies of size-differentiated samples of aerosol particles. In order to aid in future studies of urban aerosol particles, samples were collected at a forest fire near Boulder. Molecular markers specific to wood burning processes will be useful indicators of residential wood burning activities in future field studies.

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.

Effect of Differential Item Functioning on Test Equating

ERIC Educational Resources Information Center

Kabasakal, Kübra Atalay; Kelecioglu, Hülya

2015-01-01

This study examines the effect of differential item functioning (DIF) items on test equating through multilevel item response models (MIRMs) and traditional IRMs. The performances of three different equating models were investigated under 24 different simulation conditions, and the variables whose effects were examined included sample size, test…

Min and Max Exponential Extreme Interval Values and Statistics

ERIC Educational Resources Information Center

Jance, Marsha; Thomopoulos, Nick

2009-01-01

The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…

Seasonal changes in the body size of two rotifer species living in activated sludge follow the Temperature-Size Rule.

PubMed

Kiełbasa, Anna; Walczyńska, Aleksandra; Fiałkowska, Edyta; Pajdak-Stós, Agnieszka; Kozłowski, Jan

2014-12-01

Temperature-Size Rule (TSR) is a phenotypic body size response of ectotherms to changing temperature. It is known from the laboratory studies, but seasonal patterns in the field were not studied so far. We examined the body size changes in time of rotifers inhabiting activated sludge. We hypothesize that temperature is the most influencing parameter in sludge environment, leading sludge rotifers to seasonally change their body size according to TSR, and that oxygen content also induces the size response. The presence of TSR in Lecane inermis rotifer was tested in a laboratory study with two temperature and two food-type treatments. The effect of interaction between temperature and food was significant; L. inermis followed TSR in one food type only. The seasonal variability in the body sizes of the rotifers L. inermis and Cephalodella gracilis was estimated by monthly sampling and analyzed by multiple regression, in relation to the sludge parameters selected as the most influential by multivariate analysis, and predicted to alter rotifer body size (temperature and oxygen). L. inermis varied significantly in size throughout the year, and this variability is explained by temperature as predicted by the TSR, but not by oxygen availability. C. gracilis also varied in size, though this variability was explained by both temperature and oxygen. We suggest that sludge age acts as a mortality factor in activated sludge. It may have a seasonal effect on the body size of L. inermis and modify a possible effect of oxygen. Activated sludge habitat is driven by both biological processes and human regulation, yet its resident organisms follow general evolutionary rule as they do in other biological systems. The interspecific response patterns differ, revealing the importance of taking species-specific properties into account. Our findings are applicable to sludge properties enhancement through optimizing the conditions for its biological component.

Short time-scale optical variability properties of the largest AGN sample observed with Kepler/K2

NASA Astrophysics Data System (ADS)

Aranzana, E.; Körding, E.; Uttley, P.; Scaringi, S.; Bloemen, S.

2018-05-01

We present the first short time-scale (˜hours to days) optical variability study of a large sample of active galactic nuclei (AGNs) observed with the Kepler/K2 mission. The sample contains 252 AGN observed over four campaigns with ˜30 min cadence selected from the Million Quasar Catalogue with R magnitude <19. We performed time series analysis to determine their variability properties by means of the power spectral densities (PSDs) and applied Monte Carlo techniques to find the best model parameters that fit the observed power spectra. A power-law model is sufficient to describe all the PSDs of our sample. A variety of power-law slopes were found indicating that there is not a universal slope for all AGNs. We find that the rest-frame amplitude variability in the frequency range of 6 × 10-6-10-4 Hz varies from 1to10 per cent with an average of 1.7 per cent. We explore correlations between the variability amplitude and key parameters of the AGN, finding a significant correlation of rest-frame short-term variability amplitude with redshift. We attribute this effect to the known `bluer when brighter' variability of quasars combined with the fixed bandpass of Kepler data. This study also enables us to distinguish between Seyferts and blazars and confirm AGN candidates. For our study, we have compared results obtained from light curves extracted using different aperture sizes and with and without detrending. We find that limited detrending of the optimal photometric precision light curve is the best approach, although some systematic effects still remain present.

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;

Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast‑growing Eucalyptus forest plantation using airborne LiDAR data

Treesearch

Carlos Alberto Silva; Andrew Thomas Hudak; Carine Klauberg; Lee Alexandre Vierling; Carlos Gonzalez‑Benecke; Samuel de Padua Chaves Carvalho; Luiz Carlos Estraviz Rodriguez; Adrian Cardil

2017-01-01

LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m− 2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations...

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Impact of multicollinearity on small sample hydrologic regression models

NASA Astrophysics Data System (ADS)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

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

Little effect of climate change on body size of herbivorous beetles.

PubMed

Baar, Yuval; Friedman, Ariel Leib Leonid; Meiri, Shai; Scharf, Inon

2018-04-01

Ongoing climate change affects various aspects of an animal's life, with important effects on distribution range and phenology. The relationship between global warming and body size changes in mammals and birds has been widely studied, with most findings indicating a decline in body size over time. Nevertheless, little data exist on similar size change patterns of invertebrates in general and insects in particular, and it is unclear whether insects should decrease in size or not with climate warming. We measured over 4000 beetle specimens, belonging to 29 beetle species in 8 families, collected in Israel during the last 100 years. The sampled species are all herbivorous. We examined whether beetle body size had changed over the years, while also investigating the relationships between body size and annual temperature, precipitation, net primary productivity (NPP) at the collection site and collection month. None of the environmental variables, including the collection year, was correlated with the size of most of the studied beetle species, while there were strong interactions of all variables with species. Our results, though mostly negative, suggest that the effect of climate change on insect body size is species-specific and by no means a general macro-ecological rule. They also suggest that the intrapopulation variance in body size of insects collected as adults in the field is large enough to conceal intersite environmental effects on body size, such as the effect of temperature and NPP. © 2016 Institute of Zoology, Chinese Academy of Sciences.

A comparison of the sensitivity, specificity, and molecular weight accuracy of three different commercially available Hyaluronan ELISA-like assays.

PubMed

Haserodt, Sarah; Aytekin, Metin; Dweik, Raed A

2011-02-01

Hyaluronan (HA) is a glycosaminoglycan found in the extracellular matrix and ranges from several thousand to millions of daltons in size. HA has importance in various pathological conditions and is known to be elevated in several diseases. Three commonly used, commercially available HA enzyme-linked immunosorbent assay (ELISA)-like assays (from Corgenix, Echelon and R&D) were compared on the basis of accuracy, sample variability and ability to measure a range of HA sizes. The Corgenix HA ELISA-like assay displayed the lowest intra-assay variability [coefficient of variation (CV) = 11.7 ± 3.6%], followed by R&D (CV = 12.3 ± 4.6%) and Echelon (CV = 18.9 ± 9.2%). Interassay variability was also lowest for the Corgenix assay (CV = 6.0%), intermediate for the Echelon assay (9.5%) and highest for the R&D assay (CV = 34.1%). The high interassay variability seen for the R&D assay may have been due to the effect of dilution, since the dilution-independent interassay variability was 15.5%. The concentration of the standard HA was overestimated by the Echelon assay by 85% and underestimated by the R&D and Corgenix assays by 34 and 32%, respectively. The Echelon HA ELISA-like assay was the most effective at measuring all sizes of HA tested (2 MDa and 132, 66 and 6.4 kDa), whereas the Corgenix and R&D assays were unable to detect 6.4 kDa HA. These findings suggest that the Echelon HA ELISA-like assay is better suited for size-sensitive HA measurements but has a relatively high variability. The Corgenix and R&D HA ELISA-like assays have low variability and high accuracy but are not suitable for detecting low-molecular-weight HA.

[Effects of forest gap size on the architecture of Quercus variablis seedlings on the south slope of Qinling Mountains, west China].

PubMed

Yu, Bi-yun; Zhang, Wen-hui; He, Ting; You, Jian-jian; Li, Gang

2014-12-01

Typical sampling method was conducted to survey the effects of forest gap size on branch architecture, leaf characteristics and their vertical distribution of Quercus variablis seedlings from different size gaps in natural secondary Q. variablis thinning forest, on the south slope of Qinling Mountains. The results showed that gap size significantly affected the diameter, crown area of Q. variablis seedlings. The gap size positively correlated with diameter and negatively correlated with crown area, while it had no significant impact on seedling height, crown length and crown rates. The overall bifurcation ratio, stepwise bifurcation ratio, and ratio of branch diameter followed as large gap > middle gap > small gap > understory. The vertical distribution of first-order branches under different size gaps mainly concentrated at the middle and upper part of trunk, larger diameter first-order branches were mainly distributed at the lower part of trunk, and the angle of first-order branch increased at first and then declined with the increasing seedling height. With the increasing forest gap size, the leaf length, leaf width and average leaf area of seedlings all gradually declined, while the average leaf number per plant and relative total leaf number increased, the leaf length-width ratio kept stable, the relative leaf number was mainly distributed at the middle and upper parts of trunk, the changes of leaf area index was consistent with the change of the relative total number of leaves. There was no significant difference between the diameters of middle gap and large gap seedlings, but the diameter of middle gap seedlings was higher than that of large gap, suggesting the middle gap would benefit the seedlings regeneration and high-quality timber cultivation. To promote the regeneration of Q. variabilis seedlings, and to cultivate high-quality timber, appropriate thinning should be taken to increase the number of middle gaps in the management of Q. variabilis forest.

Grain size tuning of nanostructured Cu{sub 2}O films through vapour phase supersaturation control and their characterization for practical applications

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

Anu, A.; Abdul Khadar, M., E-mail: mabdulkhadar@rediffmail.com

2015-09-15

A strategy for creating nanostructured films is the alignment of nanoparticles into ordered superstructures as living organisms synthesize biomaterials with superior physical properties using nanoparticle building blocks. We synthesized nanostructured films of Cu{sub 2}O of variable grain size by establishing the condition of supersaturation for creation of nanoparticles of copper which deposited as nanograined films and which was then oxidized. This technique has the advantage of being compatible with conventional vacuum processes for electronic device fabrication. The Cu{sub 2}O film samples consisted of a secondary structure of spherical particles of almost uniform size, each particle being an agglomerate of primarymore » nanocrystals. Fractal analysis of the AFM images of the samples is carried out for studying the aggregation mechanism. Grain size tuning of the nanostructured Cu{sub 2}O films has been studied using XRD, and micro-Raman and photoluminescence spectroscopy.« less

Instrumental neutron activation analysis for studying size-fractionated aerosols

NASA Astrophysics Data System (ADS)

Salma, Imre; Zemplén-Papp, Éva

1999-10-01

Instrumental neutron activation analysis (INAA) was utilized for studying aerosol samples collected into a coarse and a fine size fraction on Nuclepore polycarbonate membrane filters. As a result of the panoramic INAA, 49 elements were determined in an amount of about 200-400 μg of particulate matter by two irradiations and four γ-spectrometric measurements. The analytical calculations were performed by the absolute ( k0) standardization method. The calibration procedures, application protocol and the data evaluation process are described and discussed. They make it possible now to analyse a considerable number of samples, with assuring the quality of the results. As a means of demonstrating the system's analytical capabilities, the concentration ranges, median or mean atmospheric concentrations and detection limits are presented for an extensive series of aerosol samples collected within the framework of an urban air pollution study in Budapest. For most elements, the precision of the analysis was found to be beyond the uncertainty represented by the sampling techniques and sample variability.

[Sequential sampling plans to Orthezia praelonga Douglas (Hemiptera: Sternorrhyncha, Ortheziidae) in citrus].

PubMed

Costa, Marilia G; Barbosa, José C; Yamamoto, Pedro T

2007-01-01

The sequential sampling is characterized by using samples of variable sizes, and has the advantage of reducing sampling time and costs if compared to fixed-size sampling. To introduce an adequate management for orthezia, sequential sampling plans were developed for orchards under low and high infestation. Data were collected in Matão, SP, in commercial stands of the orange variety 'Pêra Rio', at five, nine and 15 years of age. Twenty samplings were performed in the whole area of each stand by observing the presence or absence of scales on plants, being plots comprised of ten plants. After observing that in all of the three stands the scale population was distributed according to the contagious model, fitting the Negative Binomial Distribution in most samplings, two sequential sampling plans were constructed according to the Sequential Likelihood Ratio Test (SLRT). To construct these plans an economic threshold of 2% was adopted and the type I and II error probabilities were fixed in alpha = beta = 0.10. Results showed that the maximum numbers of samples expected to determine control need were 172 and 76 samples for stands with low and high infestation, respectively.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification

PubMed Central

Huang, Lingkang; Zhang, Hao Helen; Zeng, Zhao-Bang; Bushel, Pierre R.

2013-01-01

Background Microarray techniques provide promising tools for cancer diagnosis using gene expression profiles. However, molecular diagnosis based on high-throughput platforms presents great challenges due to the overwhelming number of variables versus the small sample size and the complex nature of multi-type tumors. Support vector machines (SVMs) have shown superior performance in cancer classification due to their ability to handle high dimensional low sample size data. The multi-class SVM algorithm of Crammer and Singer provides a natural framework for multi-class learning. Despite its effective performance, the procedure utilizes all variables without selection. In this paper, we propose to improve the procedure by imposing shrinkage penalties in learning to enforce solution sparsity. Results The original multi-class SVM of Crammer and Singer is effective for multi-class classification but does not conduct variable selection. We improved the method by introducing soft-thresholding type penalties to incorporate variable selection into multi-class classification for high dimensional data. The new methods were applied to simulated data and two cancer gene expression data sets. The results demonstrate that the new methods can select a small number of genes for building accurate multi-class classification rules. Furthermore, the important genes selected by the methods overlap significantly, suggesting general agreement among different variable selection schemes. Conclusions High accuracy and sparsity make the new methods attractive for cancer diagnostics with gene expression data and defining targets of therapeutic intervention. Availability: The source MATLAB code are available from http://math.arizona.edu/~hzhang/software.html. PMID:23966761

Statistics 101 for Radiologists.

PubMed

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics

PubMed Central

Lin, Wei; Feng, Rui; Li, Hongzhe

2014-01-01

In genetical genomics studies, it is important to jointly analyze gene expression data and genetic variants in exploring their associations with complex traits, where the dimensionality of gene expressions and genetic variants can both be much larger than the sample size. Motivated by such modern applications, we consider the problem of variable selection and estimation in high-dimensional sparse instrumental variables models. To overcome the difficulty of high dimensionality and unknown optimal instruments, we propose a two-stage regularization framework for identifying and estimating important covariate effects while selecting and estimating optimal instruments. The methodology extends the classical two-stage least squares estimator to high dimensions by exploiting sparsity using sparsity-inducing penalty functions in both stages. The resulting procedure is efficiently implemented by coordinate descent optimization. For the representative L1 regularization and a class of concave regularization methods, we establish estimation, prediction, and model selection properties of the two-stage regularized estimators in the high-dimensional setting where the dimensionality of co-variates and instruments are both allowed to grow exponentially with the sample size. The practical performance of the proposed method is evaluated by simulation studies and its usefulness is illustrated by an analysis of mouse obesity data. Supplementary materials for this article are available online. PMID:26392642

Measuring the environmental effects of organic farming: A meta-analysis of structural variables in empirical research.

PubMed

Lee, Ki Song; Choe, Young Chan; Park, Sung Hee

2015-10-01

This study examined the structural variables affecting the environmental effects of organic farming compared to those of conventional farming. A meta-analysis based on 107 studies and 360 observations published from 1977 to 2012 compared energy efficiency (EE) and greenhouse gas emissions (GHGE) for organic and conventional farming. The meta-analysis systematically analyzed the results of earlier comparative studies and used logistic regression to identify the structural variables that contributed to differences in the effects of organic and conventional farming on the environment. The statistical evidence identified characteristics that differentiated the environmental effects of organic and conventional farming, which is controversial. The results indicated that data sources, sample size and product type significantly affected EE, whereas product type, cropping pattern and measurement unit significantly affected the GHGE of organic farming compared to conventional farming. Superior effects of organic farming on the environment were more likely to appear for larger samples, primary data rather than secondary data, monocropping rather than multicropping, and crops other than fruits and vegetables. The environmental effects of organic farming were not affected by the study period, geographic location, farm size, cropping pattern, or measurement method. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Neandertal talus bones from El Sidrón site (Asturias, Spain): A 3D geometric morphometrics analysis.

PubMed

Rosas, Antonio; Ferrando, Anabel; Bastir, Markus; García-Tabernero, Antonio; Estalrrich, Almudena; Huguet, Rosa; García-Martínez, Daniel; Pastor, Juan Francisco; de la Rasilla, Marco

2017-10-01

The El Sidrón tali sample is assessed in an evolutionary framework. We aim to explore the relationship between Neandertal talus morphology and body size/shape. We test the hypothesis 1: talar Neandertal traits are influenced by body size, and the hypothesis 2: shape variables independent of body size correspond to inherited primitive features. We quantify 35 landmarks through 3D geometric morphometrics techniques to describe H. neanderthalensis-H. sapiens shape variation, by Mean Shape Comparisons, Principal Component, Phenetic Clusters, Minimum spanning tree analyses and partial least square and regression of talus shape on body variables. Shape variation correlated to body size is compared to Neandertals-Modern Humans (MH) evolutionary shape variation. The Neandertal sample is compared to early hominins. Neandertal talus presents trochlear hypertrophy, a larger equality of trochlear rims, a shorter neck, a more expanded head, curvature and an anterior location of the medial malleolar facet, an expanded and projected lateral malleolar facet and laterally expanded posterior calcaneal facet compared to MH. The Neandertal talocrural joint morphology is influenced by body size. The other Neandertal talus traits do not co-vary with it or not follow the same co-variation pattern as MH. Besides, the trochlear hypertrophy, the trochlear rims equality and the short neck could be inherited primitive features; the medial malleolar facet morphology could be an inherited primitive feature or a secondarily primitive trait; and the calcaneal posterior facet would be an autapomorphic feature of the Neandertal lineage. © 2017 Wiley Periodicals, Inc.

ICP-MS Analysis of Lanthanide-Doped Nanoparticles as a Non-Radiative, Multiplex Approach to Quantify Biodistribution and Blood Clearance

PubMed Central

Crayton, Samuel H.; Elias, Andrew; Al-Zaki, Ajlan; Cheng, Zhiliang; Tsourkas, Andrew

2011-01-01

Recent advances in material science and chemistry have led to the development of nanoparticles with diverse physicochemical properties, e.g. size, charge, shape, and surface chemistry. Evaluating which physicochemical properties are best for imaging and therapeutic studies is challenging not only because of the multitude of samples to evaluate, but also because of the large experimental variability associated with in vivo studies (e.g. differences in tumor size, injected dose, subject weight, etc.). To address this issue, we have developed a lanthanide-doped nanoparticle system and analytical method that allows for the quantitative comparison of multiple nanoparticle compositions simultaneously. Specifically, superparamagnetic iron oxide (SPIO) with a range of different sizes and charges were synthesized, each with a unique lanthanide dopant. Following the simultaneous injection of the various SPIO compositions into tumor-bearing mice, inductively coupled plasma mass spectroscopy (ICP-MS) was used to quantitatively and orthogonally assess the concentration of each SPIO composition in serial blood samples and the resected tumor and organs. The method proved generalizable to other nanoparticle platforms, including dendrimers, liposomes, and polymersomes. This approach provides a simple, cost-effective, and non-radiative method to quantitatively compare tumor localization, biodistribution, and blood clearance of more than 10 nanoparticle compositions simultaneously, removing subject-to-subject variability. PMID:22100983

Fieldpath Lunar Meteorite Graves Nunataks 06157, a Magnesian Piece of the Lunar Highlands Crust

NASA Technical Reports Server (NTRS)

Zeigler, Ryan A.; Korotev, R. L.; Korotev, R. L.

2012-01-01

To date, 49 feldspathic lunar meteorites (FLMs) have been recovered, likely representing a minimum of 35 different sample locations in the lunar highlands. The compositional variability among FLMs far exceeds the variability observed among highland samples in the Apollo and Luna sample suites. Here we will discuss in detail one of the compositional end members of the FLM suite, Graves Nunataks (GRA) 06157, which was collected by the 2006-2007 ANSMET field team. At 0.79 g, GRA 06157 is the smallest lunar meteorite so far recovered. Despite its small size, its highly feldspathic and highly magnesian composition are intriguing. Although preliminary bulk compositions have been reported, thus far no petrographic descriptions are in the literature. Here we expand upon the bulk compositional data, including major-element compositions, and provide a detailed petrographic description of GRA 06157.

Towards Monitoring Biodiversity in Amazonian Forests: How Regular Samples Capture Meso-Scale Altitudinal Variation in 25 km2 Plots

PubMed Central

Norris, Darren; Fortin, Marie-Josée; Magnusson, William E.

2014-01-01

Background Ecological monitoring and sampling optima are context and location specific. Novel applications (e.g. biodiversity monitoring for environmental service payments) call for renewed efforts to establish reliable and robust monitoring in biodiversity rich areas. As there is little information on the distribution of biodiversity across the Amazon basin, we used altitude as a proxy for biological variables to test whether meso-scale variation can be adequately represented by different sample sizes in a standardized, regular-coverage sampling arrangement. Methodology/Principal Findings We used Shuttle-Radar-Topography-Mission digital elevation values to evaluate if the regular sampling arrangement in standard RAPELD (rapid assessments (“RAP”) over the long-term (LTER [“PELD” in Portuguese])) grids captured patters in meso-scale spatial variation. The adequacy of different sample sizes (n = 4 to 120) were examined within 32,325 km2/3,232,500 ha (1293×25 km2 sample areas) distributed across the legal Brazilian Amazon. Kolmogorov-Smirnov-tests, correlation and root-mean-square-error were used to measure sample representativeness, similarity and accuracy respectively. Trends and thresholds of these responses in relation to sample size and standard-deviation were modeled using Generalized-Additive-Models and conditional-inference-trees respectively. We found that a regular arrangement of 30 samples captured the distribution of altitude values within these areas. Sample size was more important than sample standard deviation for representativeness and similarity. In contrast, accuracy was more strongly influenced by sample standard deviation. Additionally, analysis of spatially interpolated data showed that spatial patterns in altitude were also recovered within areas using a regular arrangement of 30 samples. Conclusions/Significance Our findings show that the logistically feasible sample used in the RAPELD system successfully recovers meso-scale altitudinal patterns. This suggests that the sample size and regular arrangement may also be generally appropriate for quantifying spatial patterns in biodiversity at similar scales across at least 90% (≈5 million km2) of the Brazilian Amazon. PMID:25170894

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

PubMed

Tipples, Jason; Pecchinenda, Anna

2018-04-30

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

Preparation of metallic nanoparticles by irradiation in starch aqueous solution

NASA Astrophysics Data System (ADS)

NemÅ£anu, Monica R.; Braşoveanu, Mirela; Iacob, Nicuşor

2014-11-01

Colloidal silver nanoparticles (AgNPs) were synthesized in a single step by electron beam irradiation reduction of silver ions in aqueous solution containing starch. The nanoparticles were characterized by spectrophotocolorimetry and compared with those obtained by chemical (thermal) reduction method. The results showed that the smaller sizes of AgNPs were prepared with higher yields as the irradiation dose increased. The broadening of particle size distribution occurred by increasing of irradiation dose and dose rate. Chromatic parameters such as b* (yellow-blue coordinate), C* (chroma) and ΔEab (total color difference) could characterize the nanoparticles with respect of their concentration. Hue angle ho was correlated to the particle size distribution. Experimental data of the irradiated samples were also subjected to factor analysis using principal component extraction and varimax rotation in order to reveal the relation between dependent variables and independent variables and to reduce their number. The radiation-based method provided silver nanoparticles with higher concentration and narrower size distribution than those produced by chemical reduction method. Therefore, the electron beam irradiation is effective for preparation of silver nanoparticles using starch aqueous solution as dispersion medium.

The variability of the rainfall rate as a function of area

NASA Astrophysics Data System (ADS)

Jameson, A. R.; Larsen, M. L.

2016-01-01

Distributions of drop sizes can be expressed as DSD = Nt × PSD, where Nt is the total number of drops in a sample and PSD is the frequency distribution of drop diameters (D). Their discovery permitted remote sensing techniques for rainfall estimation using radars and satellites measuring over large domains of several kilometers. Because these techniques depend heavily on higher moments of the PSD, there has been a bias toward attributing the variability of the intrinsic rainfall rates R over areas (σR) to the variability of the PSDs. While this variability does increase up to a point with increasing domain dimension L, the variability of the rainfall rate R also depends upon the variability in the total number of drops Nt. We show that while the importance of PSDs looms large for small domains used in past studies, it is the variability of Nt that dominates the variability of R as L increases to 1 km and beyond. The PSDs contribute to the variability of R through the relative dispersion of χ = D3Vt, where Vt is the terminal fall speed of drops of diameter D. However, the variability of χ is inherently limited because drop sizes and fall speeds are physically limited. In contrast, it is shown that the variance of Nt continuously increases as the domain expands for physical reasons explained below. Over domains larger than around 1 km, it is shown that Nt dominates the variance of the rainfall rate with increasing L regardless of the PSD.

Design and implementation of a dental caries prevention trial in remote Canadian Aboriginal communities.

PubMed

Harrison, Rosamund; Veronneau, Jacques; Leroux, Brian

2010-05-13

The goal of this cluster randomized trial is to test the effectiveness of a counseling approach, Motivational Interviewing, to control dental caries in young Aboriginal children. Motivational Interviewing, a client-centred, directive counseling style, has not yet been evaluated as an approach for promotion of behaviour change in indigenous communities in remote settings. Aboriginal women were hired from the 9 communities to recruit expectant and new mothers to the trial, administer questionnaires and deliver the counseling to mothers in the test communities. The goal is for mothers to receive the intervention during pregnancy and at their child's immunization visits. Data on children's dental health status and family dental health practices will be collected when children are 30-months of age. The communities were randomly allocated to test or control group by a random "draw" over community radio. Sample size and power were determined based on an anticipated 20% reduction in caries prevalence. Randomization checks were conducted between groups. In the 5 test and 4 control communities, 272 of the original target sample size of 309 mothers have been recruited over a two-and-a-half year period. A power calculation using the actual attained sample size showed power to be 79% to detect a treatment effect. If an attrition fraction of 4% per year is maintained, power will remain at 80%. Power will still be > 90% to detect a 25% reduction in caries prevalence. The distribution of most baseline variables was similar for the two randomized groups of mothers. However, despite the random assignment of communities to treatment conditions, group differences exist for stage of pregnancy and prior tooth extractions in the family. Because of the group imbalances on certain variables, control of baseline variables will be done in the analyses of treatment effects. This paper explains the challenges of conducting randomized trials in remote settings, the importance of thorough community collaboration, and also illustrates the likelihood that some baseline variables that may be clinically important will be unevenly split in group-randomized trials when the number of groups is small. This trial is registered as ISRCTN41467632.

Design and implementation of a dental caries prevention trial in remote Canadian Aboriginal communities

PubMed Central

2010-01-01

Background The goal of this cluster randomized trial is to test the effectiveness of a counseling approach, Motivational Interviewing, to control dental caries in young Aboriginal children. Motivational Interviewing, a client-centred, directive counseling style, has not yet been evaluated as an approach for promotion of behaviour change in indigenous communities in remote settings. Methods/design Aboriginal women were hired from the 9 communities to recruit expectant and new mothers to the trial, administer questionnaires and deliver the counseling to mothers in the test communities. The goal is for mothers to receive the intervention during pregnancy and at their child's immunization visits. Data on children's dental health status and family dental health practices will be collected when children are 30-months of age. The communities were randomly allocated to test or control group by a random "draw" over community radio. Sample size and power were determined based on an anticipated 20% reduction in caries prevalence. Randomization checks were conducted between groups. Discussion In the 5 test and 4 control communities, 272 of the original target sample size of 309 mothers have been recruited over a two-and-a-half year period. A power calculation using the actual attained sample size showed power to be 79% to detect a treatment effect. If an attrition fraction of 4% per year is maintained, power will remain at 80%. Power will still be > 90% to detect a 25% reduction in caries prevalence. The distribution of most baseline variables was similar for the two randomized groups of mothers. However, despite the random assignment of communities to treatment conditions, group differences exist for stage of pregnancy and prior tooth extractions in the family. Because of the group imbalances on certain variables, control of baseline variables will be done in the analyses of treatment effects. This paper explains the challenges of conducting randomized trials in remote settings, the importance of thorough community collaboration, and also illustrates the likelihood that some baseline variables that may be clinically important will be unevenly split in group-randomized trials when the number of groups is small. Trial registration This trial is registered as ISRCTN41467632. PMID:20465831

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

Measurement of Vibrated Bulk Density of Coke Particle Blends Using Image Texture Analysis

NASA Astrophysics Data System (ADS)

Azari, Kamran; Bogoya-Forero, Wilinthon; Duchesne, Carl; Tessier, Jayson

2017-09-01

A rapid and nondestructive machine vision sensor was developed for predicting the vibrated bulk density (VBD) of petroleum coke particles based on image texture analysis. It could be used for making corrective adjustments to a paste plant operation to reduce green anode variability (e.g., changes in binder demand). Wavelet texture analysis (WTA) and gray level co-occurrence matrix (GLCM) algorithms were used jointly for extracting the surface textural features of coke aggregates from images. These were correlated with the VBD using partial least-squares (PLS) regression. Coke samples of several sizes and from different sources were used to test the sensor. Variations in the coke surface texture introduced by coke size and source allowed for making good predictions of the VBD of individual coke samples and mixtures of them (blends involving two sources and different sizes). Promising results were also obtained for coke blends collected from an industrial-baked carbon anode manufacturer.

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

PubMed

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

2018-01-01

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

Hindlimb muscle architecture in non-human great apes and a comparison of methods for analysing inter-species variation

PubMed Central

Myatt, Julia P; Crompton, Robin H; Thorpe, Susannah K S

2011-01-01

By relating an animal's morphology to its functional role and the behaviours performed, we can further develop our understanding of the selective factors and constraints acting on the adaptations of great apes. Comparison of muscle architecture between different ape species, however, is difficult because only small sample sizes are ever available. Further, such samples are often comprised of different age–sex classes, so studies have to rely on scaling techniques to remove body mass differences. However, the reliability of such scaling techniques has been questioned. As datasets increase in size, more reliable statistical analysis may eventually become possible. Here we employ geometric and allometric scaling techniques, and ancovas (a form of general linear model, GLM) to highlight and explore the different methods available for comparing functional morphology in the non-human great apes. Our results underline the importance of regressing data against a suitable body size variable to ascertain the relationship (geometric or allometric) and of choosing appropriate exponents by which to scale data. ancova models, while likely to be more robust than scaling for species comparisons when sample sizes are high, suffer from reduced power when sample sizes are low. Therefore, until sample sizes are radically increased it is preferable to include scaling analyses along with ancovas in data exploration. Overall, the results obtained from the different methods show little significant variation, whether in muscle belly mass, fascicle length or physiological cross-sectional area between the different species. This may reflect relatively close evolutionary relationships of the non-human great apes; a universal influence on morphology of generalised orthograde locomotor behaviours or, quite likely, both. PMID:21507000

The Interannual Stability of Cumulative Frequency Distributions for Convective System Size and Intensity

NASA Technical Reports Server (NTRS)

Mohr, Karen I.; Molinari, John; Thorncroft, Chris

2009-01-01

The characteristics of convective system populations in West Africa and the western Pacific tropical cyclone basin were analyzed to investigate whether interannual variability in convective activity in tropical continental and oceanic environments is driven by variations in the number of events during the wet season or by favoring large and/or intense convective systems. Convective systems were defined from Tropical Rainfall Measuring Mission (TRMM) data as a cluster of pixels with an 85-GHz polarization-corrected brightness temperature below 255 K and with an area of at least 64 square kilometers. The study database consisted of convective systems in West Africa from May to September 1998-2007, and in the western Pacific from May to November 1998-2007. Annual cumulative frequency distributions for system minimum brightness temperature and system area were constructed for both regions. For both regions, there were no statistically significant differences between the annual curves for system minimum brightness temperature. There were two groups of system area curves, split by the TRMM altitude boost in 2001. Within each set, there was no statistically significant interannual variability. Subsetting the database revealed some sensitivity in distribution shape to the size of the sampling area, the length of the sample period, and the climate zone. From a regional perspective, the stability of the cumulative frequency distributions implied that the probability that a convective system would attain a particular size or intensity does not change interannually. Variability in the number of convective events appeared to be more important in determining whether a year is either wetter or drier than normal.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

The choice of product indicators in latent variable interaction models: post hoc analyses.

PubMed

Foldnes, Njål; Hagtvet, Knut Arne

2014-09-01

The unconstrained product indicator (PI) approach is a simple and popular approach for modeling nonlinear effects among latent variables. This approach leaves the practitioner to choose the PIs to be included in the model, introducing arbitrariness into the modeling. In contrast to previous Monte Carlo studies, we evaluated the PI approach by 3 post hoc analyses applied to a real-world case adopted from a research effort in social psychology. The measurement design applied 3 and 4 indicators for the 2 latent 1st-order variables, leaving the researcher with a choice among more than 4,000 possible PI configurations. Sixty so-called matched-pair configurations that have been recommended in previous literature are of special interest. In the 1st post hoc analysis we estimated the interaction effect for all PI configurations, keeping the real-world sample fixed. The estimated interaction effect was substantially affected by the choice of PIs, also across matched-pair configurations. Subsequently, a post hoc Monte Carlo study was conducted, with varying sample sizes and data distributions. Convergence, bias, Type I error and power of the interaction test were investigated for each matched-pair configuration and the all-pairs configuration. Variation in estimates across matched-pair configurations for a typical sample was substantial. The choice of specific configuration significantly affected convergence and the interaction test's outcome. The all-pairs configuration performed overall better than the matched-pair configurations. A further advantage of the all-pairs over the matched-pairs approach is its unambiguity. The final study evaluates the all-pairs configuration for small sample sizes and compares it to the non-PI approach of latent moderated structural equations. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A multilevel analysis of aggressive behaviors among nursing home residents.

PubMed

Cassie, Kimberly M

2012-01-01

Individual and organizational characteristics associated with aggressive behavior among nursing home residents were examined among a sample of 5,494 residents from 23 facilities using the Minimum Data Set 2.0 and the Organizational Social Context scale. On admission, some individual level variables (age, sex, depression, activities of daily life [ADL] impairments, and cognitive impairments) and no organizational level variables were associated with aggressive behaviors. Over time, aggressive behaviors were linked with some individual characteristics (age, sex, and ADL impairments) and several organizational level variables (stressful climates, less rigid cultures, more resistant cultures, geographic location, facility size and staffing patterns). Findings suggest multi-faceted change strategies are needed.

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

Crowder, Stephen V.

This document outlines a statistical framework for establishing a shelf-life program for components whose performance is measured by the value of a continuous variable such as voltage or function time. The approach applies to both single measurement devices and repeated measurement devices, although additional process control charts may be useful in the case of repeated measurements. The approach is to choose a sample size that protects the margin associated with a particular variable over the life of the component. Deviations from expected performance of the measured variable are detected prior to the complete loss of margin. This ensures the reliabilitymore » of the component over its lifetime.« less

On the Power of Multivariate Latent Growth Curve Models to Detect Correlated Change

ERIC Educational Resources Information Center

Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von

2006-01-01

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…

Estimating Children’s Soil/Dust Ingestion Rates through Retrospective Analyses of Blood Lead Biomonitoring from the Bunker Hill Superfund Site in Idaho

EPA Science Inventory

Background: Soil/dust ingestion rates are important variables in assessing children’s health risks in contaminated environments. Current estimates are based largely on soil tracer methodology, which is limited by analytical uncertainty, small sample size, and short study du...

Correlates of Sexual Abuse and Smoking among French Adults

ERIC Educational Resources Information Center

King, Gary; Guilbert, Philippe; Ward, D. Gant; Arwidson, Pierre; Noubary, Farzad

2006-01-01

Objective: The goal of this study was to examine the association between sexual abuse (SA) and initiation, cessation, and current cigarette smoking among a large representative adult population in France. Method: A random sample size of 12,256 adults (18-75 years of age) was interviewed by telephone concerning demographic variables, health…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

Structural Features of Sibling Dyads and Attitudes toward Sibling Relationships in Young Adulthood

ERIC Educational Resources Information Center

Riggio, Heidi R.

2006-01-01

This study examined sibling-dyad structural variables (sex composition, age difference, current coresidence, position adjacency, family size, respondent and/or sibling ordinal position) and attitudes toward adult sibling relationships. A sample of 1,053 young adults (M age = 22.1 years) described one sibling using the Lifespan Sibling Relationship…

Electronic Resource Expenditure and the Decline in Reference Transaction Statistics in Academic Libraries

ERIC Educational Resources Information Center

Dubnjakovic, Ana

2012-01-01

The current study investigates factors influencing increase in reference transactions in a typical week in academic libraries across the United States of America. Employing multiple regression analysis and general linear modeling, variables of interest from the "Academic Library Survey (ALS) 2006" survey (sample size 3960 academic libraries) were…

A Structural Equation Model for Predicting Business Student Performance

ERIC Educational Resources Information Center

Pomykalski, James J.; Dion, Paul; Brock, James L.

2008-01-01

In this study, the authors developed a structural equation model that accounted for 79% of the variability of a student's final grade point average by using a sample size of 147 students. The model is based on student grades in 4 foundational business courses: introduction to business, macroeconomics, statistics, and using databases. Educators and…

Sample size calculations for the design of cluster randomized trials: A summary of methodology.

PubMed

Gao, Fei; Earnest, Arul; Matchar, David B; Campbell, Michael J; Machin, David

2015-05-01

Cluster randomized trial designs are growing in popularity in, for example, cardiovascular medicine research and other clinical areas and parallel statistical developments concerned with the design and analysis of these trials have been stimulated. Nevertheless, reviews suggest that design issues associated with cluster randomized trials are often poorly appreciated and there remain inadequacies in, for example, describing how the trial size is determined and the associated results are presented. In this paper, our aim is to provide pragmatic guidance for researchers on the methods of calculating sample sizes. We focus attention on designs with the primary purpose of comparing two interventions with respect to continuous, binary, ordered categorical, incidence rate and time-to-event outcome variables. Issues of aggregate and non-aggregate cluster trials, adjustment for variation in cluster size and the effect size are detailed. The problem of establishing the anticipated magnitude of between- and within-cluster variation to enable planning values of the intra-cluster correlation coefficient and the coefficient of variation are also described. Illustrative examples of calculations of trial sizes for each endpoint type are included. Copyright © 2015 Elsevier Inc. All rights reserved.

RNA-seq: technical variability and sampling

PubMed Central

2011-01-01

Background RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. PMID:21645359

Quantifying Grain-Size Variability of Metal Pollutants in Road-Deposited Sediments Using the Coefficient of Variation

PubMed Central

Wang, Xiaoxue; Li, Xuyong

2017-01-01

Particle grain size is an important indicator for the variability in physical characteristics and pollutants composition of road-deposited sediments (RDS). Quantitative assessment of the grain-size variability in RDS amount, metal concentration, metal load and GSFLoad is essential to elimination of the uncertainty it causes in estimation of RDS emission load and formulation of control strategies. In this study, grain-size variability was explored and quantified using the coefficient of variation (Cv) of the particle size compositions, metal concentrations, metal loads, and GSFLoad values in RDS. Several trends in grain-size variability of RDS were identified: (i) the medium class (105–450 µm) variability in terms of particle size composition, metal loads, and GSFLoad values in RDS was smaller than the fine (<105 µm) and coarse (450–2000 µm) class; (ii) The grain-size variability in terms of metal concentrations increased as the particle size increased, while the metal concentrations decreased; (iii) When compared to the Lorenz coefficient (Lc), the Cv was similarly effective at describing the grain-size variability, whereas it is simpler to calculate because it did not require the data to be pre-processed. The results of this study will facilitate identification of the uncertainty in modelling RDS caused by grain-size class variability. PMID:28788078

The intra-individual reproducibility of flash-evoked potentials in a sample of children.

PubMed

Schellberg, D; Gasser, T; Köhler, W

1987-07-01

Visual evoked potentials (VEPs) to flash stimuli were recorded twice from 26 children aged 10-13 years, with an intersession interval of about 10 months. Test-retest reliability was poor for recordings taken from scalp locations overlying non-specific cortex and somewhat better for specific cortex. The size of consistency coefficients (i.e. correlations within session) showed that noise and artefacts were not the decisive factors which lower reliability. A comparison with retest correlations of broad band parameters of the EEG at rest for the same sample showed, to our surprise, smaller retest reliability for VEP parameters. Variability of the VEP in children over time seems to be a substantial as its well-known inter-individual variability.

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.

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

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.

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.

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

Mercury in fishes from Wrangell-St. Elias National Park and Preserve, Alaska

USGS Publications Warehouse

Kowalski, Brandon M.; Willacker, James J.; Zimmerman, Christian E.; Eagles-Smith, Collin A.

2014-01-01

In this study, mercury (Hg) concentrations were examined in fishes from Wrangell-St. Elias National Park and Preserve, Alaska, the largest and one of the most remote units in the national park system. The goals of the study were to (1) examine the distribution of Hg in select lakes of Wrangell-St. Elias National Park and Preserve; (2) evaluate the differences in Hg concentrations among fish species and with fish age and size; and (3) assess the potential ecological risks of Hg to park fishes, wildlife, and human consumers by comparing Hg concentrations to a series of risk benchmarks. Total Hg concentrations ranged from 17.9 to 616.4 nanograms per gram wet weight (ng/g ww), with a mean (± standard error) of 180.0 ±17.9 across the 83 individuals sampled. Without accounting for the effects of size, Hg concentrations varied by a factor of 10.9 across sites and species. After accounting for the effects of size, Hg concentrations were even more variable, differing by a factor of as much as 13.2 within a single species sampled from two lakes. Such inter-site variation suggests that site characteristics play an important role in determining fish Hg concentrations and that more intensive sampling may be necessary to adequately characterize Hg contamination in the park. Size-normalized Hg concentrations also differed among three species sampled from Tanada Lake, and Hg concentrations were strongly correlated with age. Furthermore, potential risks to park fish, wildlife, and human users were variable across lakes and species. Although no fish from two of the lakes studied (Grizzly Lake and Summit Lake) had Hg concentrations exceeding any of the benchmarks used, concentrations in Copper Lake and Tanada Lake exceeded conservative benchmarks for bird (90 ng/g ww in whole-body) and human (150 ng/g ww in muscle) consumption. In Tanada Lake, concentrations in most fishes also exceeded benchmarks for risk to moderate- and low-sensitivity avian consumers (180 and 270 ng/g ww in whole-body, respectively), as well as the concentration at which Alaska State guidelines suggest at-risk groups limit fish consumption to 3 meals per week (320 ng/g). However, the relationship between Hg concentrations and fish size in Tanada Lake suggests that consumption of smaller-sized fishes could reduce Hg exposure in human consumers.

Variable pixel size ionospheric tomography

NASA Astrophysics Data System (ADS)

Zheng, Dunyong; Zheng, Hongwei; Wang, Yanjun; Nie, Wenfeng; Li, Chaokui; Ao, Minsi; Hu, Wusheng; Zhou, Wei

2017-06-01

A novel ionospheric tomography technique based on variable pixel size was developed for the tomographic reconstruction of the ionospheric electron density (IED) distribution. In variable pixel size computerized ionospheric tomography (VPSCIT) model, the IED distribution is parameterized by a decomposition of the lower and upper ionosphere with different pixel sizes. Thus, the lower and upper IED distribution may be very differently determined by the available data. The variable pixel size ionospheric tomography and constant pixel size tomography are similar in most other aspects. There are some differences between two kinds of models with constant and variable pixel size respectively, one is that the segments of GPS signal pay should be assigned to the different kinds of pixel in inversion; the other is smoothness constraint factor need to make the appropriate modified where the pixel change in size. For a real dataset, the variable pixel size method distinguishes different electron density distribution zones better than the constant pixel size method. Furthermore, it can be non-chided that when the effort is spent to identify the regions in a model with best data coverage. The variable pixel size method can not only greatly improve the efficiency of inversion, but also produce IED images with high fidelity which are the same as a used uniform pixel size method. In addition, variable pixel size tomography can reduce the underdetermined problem in an ill-posed inverse problem when the data coverage is irregular or less by adjusting quantitative proportion of pixels with different sizes. In comparison with constant pixel size tomography models, the variable pixel size ionospheric tomography technique achieved relatively good results in a numerical simulation. A careful validation of the reliability and superiority of variable pixel size ionospheric tomography was performed. Finally, according to the results of the statistical analysis and quantitative comparison, the proposed method offers an improvement of 8% compared with conventional constant pixel size tomography models in the forward modeling.

Technical note: Alternatives to reduce adipose tissue sampling bias.

PubMed

Cruz, G D; Wang, Y; Fadel, J G

2014-10-01

Understanding the mechanisms by which nutritional and pharmaceutical factors can manipulate adipose tissue growth and development in production animals has direct and indirect effects in the profitability of an enterprise. Adipocyte cellularity (number and size) is a key biological response that is commonly measured in animal science research. The variability and sampling of adipocyte cellularity within a muscle has been addressed in previous studies, but no attempt to critically investigate these issues has been proposed in the literature. The present study evaluated 2 sampling techniques (random and systematic) in an attempt to minimize sampling bias and to determine the minimum number of samples from 1 to 15 needed to represent the overall adipose tissue in the muscle. Both sampling procedures were applied on adipose tissue samples dissected from 30 longissimus muscles from cattle finished either on grass or grain. Briefly, adipose tissue samples were fixed with osmium tetroxide, and size and number of adipocytes were determined by a Coulter Counter. These results were then fit in a finite mixture model to obtain distribution parameters of each sample. To evaluate the benefits of increasing number of samples and the advantage of the new sampling technique, the concept of acceptance ratio was used; simply stated, the higher the acceptance ratio, the better the representation of the overall population. As expected, a great improvement on the estimation of the overall adipocyte cellularity parameters was observed using both sampling techniques when sample size number increased from 1 to 15 samples, considering both techniques' acceptance ratio increased from approximately 3 to 25%. When comparing sampling techniques, the systematic procedure slightly improved parameters estimation. The results suggest that more detailed research using other sampling techniques may provide better estimates for minimum sampling.

Effect sizes and cut-off points: a meta-analytical review of burnout in latin American countries.

PubMed

García-Arroyo, Jose; Osca Segovia, Amparo

2018-05-02

Burnout is a highly prevalent globalized health issue that causes significant physical and psychological health problems. In Latin America research on this topic has increased in recent years, however there are no studies comparing results across countries, nor normative reference cut-offs. The present meta-analysis examines the intensity of burnout (emotional exhaustion, cynicism and personal accomplishment) in 58 adult nonclinical samples from 8 countries (Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru and Venezuela). We found low intensity of burnout but there are significant differences between countries in emotional exhaustion explained by occupation and language. Social and human service professionals (police officers, social workers, public administration staff) are more exhausted than health professionals (physicians, nurses) or teachers. The samples with Portuguese language score higher in emotional exhaustion than Spanish, supporting the theory of cultural relativism. Demographics (sex, age) and study variables (sample size, instrument), were not found significant to predict burnout. The effect size and confidence intervals found are proposed as a useful baseline for research and medical diagnosis of burnout in Latin American countries.

The size distribution of inhabited planets

NASA Astrophysics Data System (ADS)

Simpson, Fergus

2016-02-01

Earth-like planets are expected to provide the greatest opportunity for the detection of life beyond the Solar system. However, our planet cannot be considered a fair sample, especially if intelligent life exists elsewhere. Just as a person's country of origin is a biased sample among countries, so too their planet of origin may be a biased sample among planets. The magnitude of this effect can be substantial: over 98 per cent of the world's population live in a country larger than the median. In the context of a simple model where the mean population density is invariant to planet size, we infer that a given inhabited planet (such as our nearest neighbour) has a radius r < 1.2r⊕ (95 per cent confidence bound). We show that this result is likely to hold not only for planets hosting advanced life, but also for those which harbour primitive life forms. Further, inferences may be drawn for any variable which influences population size. For example, since population density is widely observed to decline with increasing body mass, we conclude that most intelligent species are expected to exceed 300 kg.

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration). In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS

PubMed Central

Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

2013-01-01

Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power as the percentage of cases in which an estimate of interest is significantly different from zero. Examples of power calculation for commonly used mediational models are provided. Power analyses for the single mediator, multiple mediators, three-path mediation, mediation with latent variables, moderated mediation, and mediation in longitudinal designs are described. Annotated sample syntax for Mplus is appended and tabled values of required sample sizes are shown for some models. PMID:23935262

In Vivo Single-Cell Fluorescence and Size Scaling of Phytoplankton Chlorophyll Content.

PubMed

Álvarez, Eva; Nogueira, Enrique; López-Urrutia, Ángel

2017-04-01

In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have explored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus includes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments confirm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based processes and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size dependence of chlorophyll content in response to environmental variables affecting primary production. IMPORTANCE The chlorophyll concentrations in phytoplankton register physiological adjustments in cellular pigmentation arising mainly from changes in light conditions. The extent of these adjustments is constrained by the size of the phytoplankton cells, even within single populations. Hence, variations in community chlorophyll derived from photoacclimation are also dependent on the phytoplankton size distribution. Copyright © 2017 American Society for Microbiology.

In Vivo Single-Cell Fluorescence and Size Scaling of Phytoplankton Chlorophyll Content

PubMed Central

Nogueira, Enrique; López-Urrutia, Ángel

2017-01-01

ABSTRACT In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have explored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus includes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments confirm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based processes and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size dependence of chlorophyll content in response to environmental variables affecting primary production. IMPORTANCE The chlorophyll concentrations in phytoplankton register physiological adjustments in cellular pigmentation arising mainly from changes in light conditions. The extent of these adjustments is constrained by the size of the phytoplankton cells, even within single populations. Hence, variations in community chlorophyll derived from photoacclimation are also dependent on the phytoplankton size distribution. PMID:28115378

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.

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.

BRDF of Salt Pan Regolith Samples

NASA Technical Reports Server (NTRS)

Georgiev, Georgi T.; Gatebe, Charles K.; Butler, James J.; King, Michael D.

2008-01-01

Laboratory Bi-directional Reflectance Distribution Function (BRDF) measurements of salt pan regolith samples are presented in this study in an effort to understand the role of spatial and spectral variability of the natural biome. The samples were obtained from Etosha Pan, Namibia (19.20 deg S, 15.93 deg E, alt. 1100 m). It is shown how the BRDF depends on the measurement geometry - incident and scatter angles and on the sample particle sizes. As a demonstration of the application of the results, airborne BRDF measurements acquires with NASA's Cloud Absorption Radiometer (CAR) over the same general site where the regolith samples were collected are compared with the laboratory results. Good agreement between laboratory measured and field measured BRDF is reported.

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.

PubMed

Frömke, Cornelia; Hothorn, Ludwig A; Kropf, Siegfried

2008-01-27

In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

Reiki Therapy for Symptom Management in Children Receiving Palliative Care: A Pilot Study.

PubMed

Thrane, Susan E; Maurer, Scott H; Ren, Dianxu; Danford, Cynthia A; Cohen, Susan M

2017-05-01

Pain may be reported in one-half to three-fourths of children with cancer and other terminal conditions and anxiety in about one-third of them. Pharmacologic methods do not always give satisfactory symptom relief. Complementary therapies such as Reiki may help children manage symptoms. This pre-post mixed-methods single group pilot study examined feasibility, acceptability, and the outcomes of pain, anxiety, and relaxation using Reiki therapy with children receiving palliative care. A convenience sample of children ages 7 to 16 and their parents were recruited from a palliative care service. Two 24-minute Reiki sessions were completed at the children's home. Paired t tests or Wilcoxon signed-rank tests were calculated to compare change from pre to post for outcome variables. Significance was set at P < .10. Cohen d effect sizes were calculated. The final sample included 8 verbal and 8 nonverbal children, 16 mothers, and 1 nurse. All mean scores for outcome variables decreased from pre- to posttreatment for both sessions. Significant decreases for pain for treatment 1 in nonverbal children ( P = .063) and for respiratory rate for treatment 2 in verbal children ( P = .009). Cohen d effect sizes were medium to large for most outcome measures. Decreased mean scores for outcome measures indicate that Reiki therapy did decrease pain, anxiety, heart, and respiratory rates, but small sample size deterred statistical significance. This preliminary work suggests that complementary methods of treatment such as Reiki may be beneficial to support traditional methods to manage pain and anxiety in children receiving palliative care.

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

Development of a Multiple-Stage Differential Mobility Analyzer (MDMA)

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

Chen, Da-Ren; Cheng, Mengdawn

2007-01-01

A new DMA column has been designed with the capability of simultaneously extracting monodisperse particles of different sizes in multiple stages. We call this design a multistage DMA, or MDMA. A prototype MDMA has been constructed and experimentally evaluated in this study. The new column enables the fast measurement of particles in a wide size range, while preserving the powerful particle classification function of a DMA. The prototype MDMA has three sampling stages, capable of classifying monodisperse particles of three different sizes simultaneously. The scanning voltage operation of a DMA can be applied to this new column. Each stage ofmore » MDMA column covers a fraction of the entire particle size range to be measured. The covered size fractions of two adjacent stages of the MDMA are designed somewhat overlapped. The arrangement leads to the reduction of scanning voltage range and thus the cycling time of the measurement. The modular sampling stage design of the MDMA allows the flexible configuration of desired particle classification lengths and variable number of stages in the MDMA. The design of our MDMA also permits operation at high sheath flow, enabling high-resolution particle size measurement and/or reduction of the lower sizing limit. Using the tandem DMA technique, the performance of the MDMA, i.e., sizing accuracy, resolution, and transmission efficiency, was evaluated at different ratios of aerosol and sheath flowrates. Two aerosol sampling schemes were investigated. One was to extract aerosol flows at an evenly partitioned flowrate at each stage, and the other was to extract aerosol at a rate the same as the polydisperse aerosol flowrate at each stage. We detail the prototype design of the MDMA and the evaluation result on the transfer functions of the MDMA at different particle sizes and operational conditions.« less

Overweight in Adolescents: Differences per Type of Education. Does One Size Fit All?

ERIC Educational Resources Information Center

Vissers, Dirk; Devoogdt, Nele; Gebruers, Nick; Mertens, Ilse; Truijen, Steven; Van Gaal, Luc

2008-01-01

Objective: To assess the lifestyle and prevalence of overweight among 16- to 18-year-old adolescents attending 4 different types of secondary education (SE). Design: Cross-sectional school-based survey. Participants: A community sample of 994 adolescents (body mass index [BMI]: 15-43 kg/m[superscript 2]). Variables Measured: Overweight and obesity…

Spatial and temporal patterns in fish assemblages of upper coastal plain streams, Mississippi, USA

Treesearch

Susan B. Adams; Melvin L. Warren; Wendell R. Haag

2004-01-01

We assessed spatial, seasonal, and annual variation in fish assemblages over 17 months in three small- to medium-sized, incised streams characteristic of northwestern Mississippi streams. We sampled 17 962 fish representing 52 species and compared assemblages within and among streams. Although annual and seasonal variability inassemblage structure was high, fish...

Sex Differences in the Development of Moral Reasoning: A Rejoinder to Baumrind.

ERIC Educational Resources Information Center

Walker, Lawrence J.

1986-01-01

Addresses the criticisms of Diana Baumrind's review of his research on sex differences in moral reasoning development. Discusses issues such as the nature of moral development, the focus on adulthood, the choice of statistics, the effect of differing sample sizes and scoring systems, and the role of sexual experiences in explaining variability in…

Height and seasonal growth pattern of jack pine full-sib families

Treesearch

Don E. Riemenschneider

1981-01-01

Total tree height, seasonal shoot elongation, dates of growth initiation and cessation, and mean daily growth rate were measured and analyzed for a population of jack pine full-sib families derived from inter-provenance crosses. Parental provenance had no effect on these variables although this may have been due to small sample size. Progenies differed significantly...

A new flexible forest inventory in France

Treesearch

C. Vidal; T. Belouard; J.-C. Herve; N. Robert; J. Wolsack

2007-01-01

The French National Forest Inventory was created in 1958 to assess metropolitan forest resources. To stick to new national and international requirements as well as to enhance reactivity, a new inventory method was implemented in 2004. This new method is based on a systematic sampling grid covering the whole territory every year. The size of the mesh is variable,...

Evaluating Classified MODIS Satellite Imagery as a Stratification Tool

Treesearch

Greg C. Liknes; Mark D. Nelson; Ronald E. McRoberts

2004-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service collects forest attribute data on permanent plots arranged on a hexagonal network across all 50 states and Puerto Rico. Due to budget constraints, sample sizes sufficient to satisfy national FIA precision standards are seldom achieved for most inventory variables unless the estimation process is...

Kernel and Traditional Equipercentile Equating with Degrees of Presmoothing. Research Report. ETS RR-07-15

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul

2007-01-01

The purpose of this study was to empirically evaluate the impact of loglinear presmoothing accuracy on equating bias and variability across chained and post-stratification equating methods, kernel and percentile-rank continuization methods, and sample sizes. The results of evaluating presmoothing on equating accuracy generally agreed with those of…

Modifying Spearman's Attenuation Equation to Yield Partial Corrections for Measurement Error--With Application to Sample Size Calculations

ERIC Educational Resources Information Center

Nicewander, W. Alan

2018-01-01

Spearman's correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman's equation removes all measurement error from a correlation coefficient which translates into "increasing the reliability of…

A Field Study of Performance Among Embarked Infantry Personnel Exposed to Waterborne Motion

DTIC Science & Technology

2012-09-01

was designed with four groups with 16 participants per group to accommodate the calculated sample size and the maximum seating capacity of the...25  A.  APPROACH TO THE EXPERIMENTAL DESIGN .................................25  B.  VARIABLES...39  viii 1.  Design of the Training Period ...........................................................39  2.  Training Period

Constancy and asynchrony of Osmoderma eremita populations in tree hollows.

PubMed

Ranius, Thomas

2001-01-01

A species rich beetle fauna is associated with old, hollow trees. Many of these species are regarded as endangered, but there is little understanding of the population structure and extinction risks of these species. In this study I show that one of the most endangered beetles, Osmoderma eremita, has a population structure which conforms to that of a metapopulation, with each tree possibly sustaining a local population. This was revealed by performing a mark-release-recapture experiment in 26 trees over a 5-year period. The spatial variability between trees was much greater than temporal variability between years. The population size was on average 11 adults tree -1 year -1 , but differed widely between trees (0-85 adults tree -1 year -1 ). The population size in each tree varied moderately between years [mean coefficient of variation (C.V.)=0.51], but more widely than from sampling errors alone (P=0.008, Monte Carlo simulation). The population size variability in all trees combined, however, was not larger than expected from sampling errors alone in a constant population (C.V.=0.15, P=0.335, Monte Carlo simulation). Thus, the fluctuations of local populations cancel each other out when they are added together. This pattern can arise only when the fluctuations occur asynchronously between trees. The asynchrony of the fluctuations justifies the assumption usually made in metapopulation modelling, that local populations within a metapopulation fluctuate independently of one another. The asynchrony might greatly increase persistence time at the metapopulation level (per stand), compared to the local population level (per tree). The total population size of O. eremita in the study area was estimated to be 3,900 individuals. Other localities sustaining O. eremita are smaller in area, and most of these must be enlarged to allow long-term metapopulation persistence and to satisfy genetic considerations of the O. eremita populations.

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion

PubMed Central

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-01-01

Introduction Crowdsourcing has become an increasingly important tool to address many problems – from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. Methods We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. Results The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14–16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94–0.96). Conclusions Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45–55 experts. PMID:27350874

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion.

PubMed

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-06-01

Crowdsourcing has become an increasingly important tool to address many problems - from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14-16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94-0.96). Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45-55 experts.

Study of vesicle size distribution dependence on pH value based on nanopore resistive pulse method

NASA Astrophysics Data System (ADS)

Lin, Yuqing; Rudzevich, Yauheni; Wearne, Adam; Lumpkin, Daniel; Morales, Joselyn; Nemec, Kathleen; Tatulian, Suren; Lupan, Oleg; Chow, Lee

2013-03-01

Vesicles are low-micron to sub-micron spheres formed by a lipid bilayer shell and serve as potential vehicles for drug delivery. The size of vesicle is proposed to be one of the instrumental variables affecting delivery efficiency since the size is correlated to factors like circulation and residence time in blood, the rate for cell endocytosis, and efficiency in cell targeting. In this work, we demonstrate accessible and reliable detection and size distribution measurement employing a glass nanopore device based on the resistive pulse method. This novel method enables us to investigate the size distribution dependence of pH difference across the membrane of vesicles with very small sample volume and rapid speed. This provides useful information for optimizing the efficiency of drug delivery in a pH sensitive environment.

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.

Long-term erosion rates of Panamanian drainage basins determined using in situ 10Be

NASA Astrophysics Data System (ADS)

Gonzalez, Veronica Sosa; Bierman, Paul R.; Nichols, Kyle K.; Rood, Dylan H.

2016-12-01

Erosion rates of tropical landscapes are poorly known. Using measurements of in situ-produced 10Be in quartz extracted from river and landslide sediment samples, we calculate long-term erosion rates for many physiographic regions of Panama. We collected river sediment samples from a wide variety of watersheds (n = 35), and then quantified 24 landscape-scale variables (physiographic, climatic, seismic, geologic, and land-use proxies) for each watershed before determining the relationship between these variables and long-term erosion rates using linear regression, multiple regression, and analysis of variance (ANOVA). We also used grain-size-specific 10Be analysis to infer the effect of landslides on the concentration of 10Be in fluvial sediment and thus on erosion rates. Cosmogenic 10Be-inferred, background erosion rates in Panama range from 26 to 595 m My- 1, with an arithmetic average of 201 m My- 1, and an area-weighted average of 144 m My- 1. The strongest and most significant relationship in the dataset was between erosion rate and silicate weathering rate, the mass of material leaving the basin in solution. None of the topographic variables showed a significant relationship with erosion rate at the 95% significance level; we observed weak but significant correlation between erosion rates and several climatic variables related to precipitation and temperature. On average, erosion rates in Panama are higher than other cosmogenically-derived erosion rates in tropical climates including those from Puerto Rico, Madagascar, Australia and Sri Lanka, likely the result of Panama's active tectonic setting and thus high rates of seismicity and uplift. Contemporary sediment yield and cosmogenically-derived erosion rates for three of the rivers we studied are similar, suggesting that human activities are not increasing sediment yield above long-term erosion rate averages in Panama. 10Be concentration is inversely proportional to grain size in landslide and fluvial samples from Panama; finer grain sizes from landslide material have lower 10Be concentration than fine-grained fluvial sediment. Large grains from both landslide and stream sediments have similarly low 10Be concentrations. These data suggest that fluvial gravel is delivered to the channel by landslides whereas sand is preferentially delivered by soil creep and bank collapse. Furthermore, the difference in 10Be concentration in sand-sized material delivered by soil creep and that delivered by landsliding suggests that the frequency and intensity of landslides influence basin scale erosion rates.

Adaptive significance of small body size: strength and motor performance of school children in Mexico and Papua New Guinea.

PubMed

Malina, R M; Little, B B; Shoup, R F; Buschang, P H

1987-08-01

The postulated superior functional efficiency in association with reduced body size under conditions of chronic protein-energy undernutrition was considered in school children from rural Mexico and coastal Papua New Guinea. Grip strength and three measures of motor performance were measured in cross-sectional samples of children 6-16 years of age from a rural agricultural community in Oaxaca, Mexico, and from the coastal community Pere on Manus Island, Papua New Guinea. The strength and performance of a mixed-longitudinal sample of well nourished children from Philadelphia was used as a reference. The Oaxaca and Pere children are significantly shorter and lighter and are not as strong as the well nourished children. Motor performances of Pere children compare favorably to those of the better-nourished Philadelphia children, whereas those of the Oaxaca children are poorer. Throwing performance is more variable. When expressed relative to body size, strength is similar in the three samples, but the running and jumping performances of Pere children per unit body size are better than the relative performances of Oaxaca and Philadelphia children. Throwing performance per unit body size is better in the undernourished children. The influence of age, stature, and weight on the performance of Oaxaca and Pere children is generally similar to that for well nourished children. These results suggest that the hypothesized adaptive significance of small body size for the functional efficiency of populations living under conditions of chronic undernutrition varies between populations and with performance tasks.

Variation in aluminum, iron, and particle concentrations in oxic ground-water samples collected by use of tangential-flow ultrafiltration with low-flow sampling

USGS Publications Warehouse

Szabo, Z.; Oden, J.H.; Gibs, J.; Rice, D.E.; Ding, Y.; ,

2001-01-01

Particulates that move with ground water and those that are artificially mobilized during well purging could be incorporated into water samples during collection and could cause trace-element concentrations to vary in unfiltered samples, and possibly in filtered samples (typically 0.45-um (micron) pore size) as well, depending on the particle-size fractions present. Therefore, measured concentrations may not be representative of those in the aquifer. Ground water may contain particles of various sizes and shapes that are broadly classified as colloids, which do not settle from water, and particulates, which do. In order to investigate variations in trace-element concentrations in ground-water samples as a function of particle concentrations and particle-size fractions, the U.S. Geological Survey, in cooperation with the U.S. Air Force, collected samples from five wells completed in the unconfined, oxic Kirkwood-Cohansey aquifer system of the New Jersey Coastal Plain. Samples were collected by purging with a portable pump at low flow (0.2-0.5 liters per minute and minimal drawdown, ideally less than 0.5 foot). Unfiltered samples were collected in the following sequence: (1) within the first few minutes of pumping, (2) after initial turbidity declined and about one to two casing volumes of water had been purged, and (3) after turbidity values had stabilized at less than 1 to 5 Nephelometric Turbidity Units. Filtered samples were split concurrently through (1) a 0.45-um pore size capsule filter, (2) a 0.45-um pore size capsule filter and a 0.0029-um pore size tangential-flow filter in sequence, and (3), in selected cases, a 0.45-um and a 0.05-um pore size capsule filter in sequence. Filtered samples were collected concurrently with the unfiltered sample that was collected when turbidity values stabilized. Quality-assurance samples consisted of sequential duplicates (about 25 percent) and equipment blanks. Concentrations of particles were determined by light scattering. Variations in concentrations aluminum and iron (1 -74 and 1-199 ug/L (micrograms per liter), respectively), common indicators of the presence of particulate-borne trace elements, were greatest in sample sets from individual wells with the greatest variations in turbidity and particle concentration. Differences in trace-element concentrations in sequentially collected unfiltered samples with variable turbidity were 5 to 10 times as great as those in concurrently collected samples that were passed through various filters. These results indicate that turbidity must be both reduced and stabilized even when low-flow sample-collection techniques are used in order to obtain water samples that do not contain considerable particulate artifacts. Currently (2001) available techniques need to be refined to ensure that the measured trace-element concentrations are representative of those that are mobile in the aquifer water.

ICP-MS analysis of lanthanide-doped nanoparticles as a non-radiative, multiplex approach to quantify biodistribution and blood clearance.

PubMed

Crayton, Samuel H; Elias, Drew R; Al Zaki, Ajlan; Cheng, Zhiliang; Tsourkas, Andrew

2012-02-01

Recent advances in material science and chemistry have led to the development of nanoparticles with diverse physicochemical properties, e.g. size, charge, shape, and surface chemistry. Evaluating which physicochemical properties are best for imaging and therapeutic studies is challenging not only because of the multitude of samples to evaluate, but also because of the large experimental variability associated with in vivo studies (e.g. differences in tumor size, injected dose, subject weight, etc.). To address this issue, we have developed a lanthanide-doped nanoparticle system and analytical method that allows for the quantitative comparison of multiple nanoparticle compositions simultaneously. Specifically, superparamagnetic iron oxide (SPIO) with a range of different sizes and charges were synthesized, each with a unique lanthanide dopant. Following the simultaneous injection of the various SPIO compositions into tumor-bearing mice, inductively coupled plasma mass spectroscopy (ICP-MS) was used to quantitatively and orthogonally assess the concentration of each SPIO composition in serial blood samples and the resected tumor and organs. The method proved generalizable to other nanoparticle platforms, including dendrimers, liposomes, and polymersomes. This approach provides a simple, cost-effective, and non-radiative method to quantitatively compare tumor localization, biodistribution, and blood clearance of more than 10 nanoparticle compositions simultaneously, removing subject-to-subject variability. Copyright © 2011 Elsevier Ltd. All rights reserved.

Does stereotype threat influence performance of girls in stereotyped domains? A meta-analysis.

PubMed

Flore, Paulette C; Wicherts, Jelte M

2015-02-01

Although the effect of stereotype threat concerning women and mathematics has been subject to various systematic reviews, none of them have been performed on the sub-population of children and adolescents. In this meta-analysis we estimated the effects of stereotype threat on performance of girls on math, science and spatial skills (MSSS) tests. Moreover, we studied publication bias and four moderators: test difficulty, presence of boys, gender equality within countries, and the type of control group that was used in the studies. We selected study samples when the study included girls, samples had a mean age below 18years, the design was (quasi-)experimental, the stereotype threat manipulation was administered between-subjects, and the dependent variable was a MSSS test related to a gender stereotype favoring boys. To analyze the 47 effect sizes, we used random effects and mixed effects models. The estimated mean effect size equaled -0.22 and significantly differed from 0. None of the moderator variables was significant; however, there were several signs for the presence of publication bias. We conclude that publication bias might seriously distort the literature on the effects of stereotype threat among schoolgirls. We propose a large replication study to provide a less biased effect size estimate. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Using a respiratory navigator significantly reduces variability when quantifying left ventricular torsion with cardiovascular magnetic resonance.

PubMed

Hamlet, Sean M; Haggerty, Christopher M; Suever, Jonathan D; Wehner, Gregory J; Andres, Kristin N; Powell, David K; Charnigo, Richard J; Fornwalt, Brandon K

2017-03-01

Left ventricular (LV) torsion is an important indicator of cardiac function that is limited by high inter-test variability (50% of the mean value). We hypothesized that this high inter-test variability is partly due to inconsistent breath-hold positions during serial image acquisitions, which could be significantly improved by using a respiratory navigator for cardiovascular magnetic resonance (CMR) based quantification of LV torsion. We assessed respiratory-related variability in measured LV torsion with two distinct experimental protocols. First, 17 volunteers were recruited for CMR with cine displacement encoding with stimulated echoes (DENSE) in which a respiratory navigator was used to measure and then enforce variability in end-expiratory position between all LV basal and apical acquisitions. From these data, we quantified the inter-test variability of torsion in the absence and presence of enforced end-expiratory position variability, which established an upper bound for the expected torsion variability. For the second experiment (in 20 new, healthy volunteers), 10 pairs of cine DENSE basal and apical images were each acquired from consecutive breath-holds and consecutive navigator-gated scans (with a single acceptance position). Inter-test variability of torsion was compared between the breath-hold and navigator-gated scans to quantify the variability due to natural breath-hold variation. To demonstrate the importance of these variability reductions, we quantified the reduction in sample size required to detect a clinically meaningful change in LV torsion with the use of a respiratory navigator. The mean torsion was 3.4 ± 0.2°/cm. From the first experiment, enforced variability in end-expiratory position translated to considerable variability in measured torsion (0.56 ± 0.34°/cm), whereas inter-test variability with consistent end-expiratory position was 57% lower (0.24 ± 0.16°/cm, p < 0.001). From the second experiment, natural respiratory variability from consecutive breath-holds translated to a variability in torsion of 0.24 ± 0.10°/cm, which was significantly higher than the variability from navigator-gated scans (0.18 ± 0.06°/cm, p = 0.02). By using a respiratory navigator with DENSE, theoretical sample sizes were reduced from 66 to 16 and 26 to 15 as calculated from the two experiments. A substantial portion (22-57%) of the inter-test variability of LV torsion can be reduced by using a respiratory navigator to ensure a consistent breath-hold position between image acquisitions.

Signal or noise? Separating grain size-dependent Nd isotope variability from provenance shifts in Indus delta sediments, Pakistan

NASA Astrophysics Data System (ADS)

Jonell, T. N.; Li, Y.; Blusztajn, J.; Giosan, L.; Clift, P. D.

2017-12-01

Rare earth element (REE) radioisotope systems, such as neodymium (Nd), have been traditionally used as powerful tracers of source provenance, chemical weathering intensity, and sedimentary processes over geologic timescales. More recently, the effects of physical fractionation (hydraulic sorting) of sediments during transport have called into question the utility of Nd isotopes as a provenance tool. Is source terrane Nd provenance resolvable if sediment transport strongly induces noise? Can grain-size sorting effects be quantified? This study works to address such questions by utilizing grain size analysis, trace element geochemistry, and Nd isotope geochemistry of bulk and grain-size fractions (<63μm, 63-125 μm, 125-250 μm) from the Indus delta of Pakistan. Here we evaluate how grain size effects drive Nd isotope variability and further resolve the total uncertainties associated with Nd isotope compositions of bulk sediments. Results from the Indus delta indicate bulk sediment ɛNd compositions are most similar to the <63 µm fraction as a result of strong mineralogical control on bulk compositions by silt- to clay-sized monazite and/or allanite. Replicate analyses determine that the best reproducibility (± 0.15 ɛNd points) is observed in the 125-250 µm fraction. The bulk and finest fractions display the worst reproducibility (±0.3 ɛNd points). Standard deviations (2σ) indicate that bulk sediment uncertainties are no more than ±1.0 ɛNd points. This argues that excursions of ≥1.0 ɛNd points in any bulk Indus delta sediments must in part reflect an external shift in provenance irrespective of sample composition, grain size, and grain size distribution. Sample standard deviations (2s) estimate that any terrigenous bulk sediment composition should vary no greater than ±1.1 ɛNd points if provenance remains constant. Findings from this study indicate that although there are grain-size dependent Nd isotope effects, they are minimal in the Indus delta such that resolvable provenance-driven trends can be identified in bulk sediment ɛNd compositions over the last 20 k.y., and that overall provenance trends remain consistent with previous findings.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

USGS Publications Warehouse

Keiter, David A.; Cunningham, Fred L.; Rhodes, Olin E.; Irwin, Brian J.; Beasley, James

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

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

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Optimization of Scat Detection Methods for a Social Ungulate, the Wild Pig, and Experimental Evaluation of Factors Affecting Detection of Scat.

PubMed

Keiter, David A; Cunningham, Fred L; Rhodes, Olin E; Irwin, Brian J; Beasley, James C

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

DOE PAGES

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.; ...

2016-05-25

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Extent of height variability explained by known height-associated genetic variants in an isolated population of the Adriatic coast of Croatia.

PubMed

Zhang, Ge; Karns, Rebekah; Sun, Guangyun; Indugula, Subba Rao; Cheng, Hong; Havas-Augustin, Dubravka; Novokmet, Natalija; Rudan, Dusko; Durakovic, Zijad; Missoni, Sasa; Chakraborty, Ranajit; Rudan, Pavao; Deka, Ranjan

2011-01-01

Human height is a classical example of a polygenic quantitative trait. Recent large-scale genome-wide association studies (GWAS) have identified more than 200 height-associated loci, though these variants explain only 2∼10% of overall variability of normal height. The objective of this study was to investigate the variance explained by these loci in a relatively isolated population of European descent with limited admixture and homogeneous genetic background from the Adriatic coast of Croatia. In a sample of 1304 individuals from the island population of Hvar, Croatia, we performed genome-wide SNP typing and assessed the variance explained by genetic scores constructed from different panels of height-associated SNPs extracted from five published studies. The combined information of the 180 SNPs reported by Lango Allen el al. explained 7.94% of phenotypic variation in our sample. Genetic scores based on 20~50 SNPs reported by the remaining individual GWA studies explained 3~5% of height variance. These percentages of variance explained were within ranges comparable to the original studies and heterogeneity tests did not detect significant differences in effect size estimates between our study and the original reports, if the estimates were obtained from populations of European descent. We have evaluated the portability of height-associated loci and the overall fitting of estimated effect sizes reported in large cohorts to an isolated population. We found proportions of explained height variability were comparable to multiple reference GWAS in cohorts of European descent. These results indicate similar genetic architecture and comparable effect sizes of height loci among populations of European descent. © 2011 Zhang et al.

Masses, Dimensionless Kerr Parameters, and Emission Regions in GeV Gamma-Ray-loud Blazars

NASA Astrophysics Data System (ADS)

Xie, G.-Z.; Ma, L.; Liang, E.-W.; Zhou, S.-B.; Xie, Z.-H.

2003-11-01

We have compiled sample of 17 GeV γ-ray-loud blazars, for which rapid optical variability and γ-ray fluxes are well observed, from the literature. We derive estimates of the masses, the minimum Kerr parameters amin, and the size of the emission regions of the supermassive black holes (SMBHs) for the blazars in the sample from their minimum optical variability timescales and γ-ray fluxes. The results show that (1) the masses derived from the optical variability timescale (MH) are significantly correlated with the masses from the γ-ray luminosity (MKNH); (2) the values of amin of the SMBHs with masses MH>=108.3 Msolar (three out of 17 objects) range from ~0.5 to ~1.0, suggesting that these SMBHs are likely to be Kerr black holes. For the SMBHs with MH<108.3 Msolar, however, amin=0, suggesting that a nonrotating black hole model cannot be ruled out for these objects. In addition, the values of the size of the emission region, r*, for the two kinds of SMBHs are significantly different. For the SMBHs with amin>0, the sizes of the emission regions are almost within the horizon (2rG) and marginally bound orbit (4rG), while for those with amin=0 they are in the range (4.3-66.4)rG, extending beyond the marginally stable orbit (6rG). These results may imply that (1) the rotational state, the radiating regions, and the physical processes in the inner regions for the two kinds of SMBH are significantly different and (2) the emission mechanisms of GeV γ-ray blazars are related to the SMBHs in their centers but are not related to the two different kinds of SMBH.

Subjective Memory Complaints in healthy older adults: Fewer complaints associated with depression and perceived health, more complaints also associated with lower memory performance.

PubMed

Montejo Carrasco, Pedro; Montenegro-Peña, Mercedes; López-Higes, Ramón; Estrada, Eduardo; Prada Crespo, David; Montejo Rubio, Christian; García Azorín, David

(i) To analyze if general cognitive performance, perceived health and depression are predictors of Subjective Memory Complaints (SMC) contrasting their effect sizes; (ii) to analyze the relationship between SMC and objective memory by comparing a test that measures memory in daily life and a classical test of associated pairs; (iii) to examine if different subgroups, formed according to the MFE score, might have different behaviors regarding the studied variables. Sample: 3921 community-dwelling people (mean age 70.41±4.70) without cognitive impairment. Consecutive non-probabilistic recruitment. Mini Cognitive Exam (MCE), daily memory Rivermead Behavioural Memory Test (RBMT), Paired Associates Learning (PAL), Geriatric Depression Scale (GDS), Nottingham Health Profile (NHP). Dependent variable: Memory Failures Everyday Questionnaire (MFE). Two different dimensions to explain SMC were found: One subjective (MFE, GDS, NHP) and other objective (RBMT, PAL, MCE), the first more strongly associated with SMC. SMC predictors were NHP, GDS, RBMT and PAL, in this order according to effect size. Considering MFE scores we subdivided the sample into three groups (low, medium, higher scores): low MFE group was associated with GDS; medium, with GDS, NPH and RBMT, and higher, with age as well. Effect size for every variable tended to grow as the MFE score was higher. SMC were associated with both health profile and depressive symptoms and, in a lesser degree, with memory and overall cognitive performance. In people with fewer SMC, these are only associated with depressive symptomatology. More SMC are associated with depression, poor health perception and lower memory. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Allometric modelling of peak oxygen uptake in male soccer players of 8-18 years of age.

PubMed

Valente-Dos-Santos, João; Coelho-E-Silva, Manuel J; Tavares, Óscar M; Brito, João; Seabra, André; Rebelo, António; Sherar, Lauren B; Elferink-Gemser, Marije T; Malina, Robert M

2015-03-01

Peak oxygen uptake (VO2peak) is routinely scaled as mL O2 per kilogram body mass despite theoretical and statistical limitations of using ratios. To examine the contribution of maturity status and body size descriptors to age-associated inter-individual variability in VO2peak and to present static allometric models to normalize VO2peak in male youth soccer players. Total body and estimates of total and regional lean mass were measured with dual energy X-ray absorptiometry in a cross-sectional sample of Portuguese male soccer players. The sample was divided into three age groups for analysis: 8-12 years, 13-15 years and 16-18 years. VO2peak was estimated using an incremental maximal exercise test on a motorized treadmill. Static allometric models were used to normalize VO2peak. The independent variables with the best statistical fit explained 72% in the younger group (lean body mass: k = 1.07), 52% in mid-adolescent players (lean body mass: k = 0.93) and 31% in the older group (body mass: k = 0.51) of variance in VO2peak. The inclusion of the exponential term pubertal status marginally increased the explained variance in VO2peak (adjusted R(2 )= 36-75%) and provided statistical adjustments to the size descriptors coefficients. The allometric coefficients and exponents evidenced the varying inter-relationship among size descriptors and maturity status with aerobic fitness from early to late-adolescence. Lean body mass, lean lower limbs mass and body mass combined with pubertal status explain most of the inter-individual variability in VO2peak among youth soccer players.

Relationship between turbidity and total suspended solids concentration within a combined sewer system.

PubMed

Hannouche, A; Chebbo, G; Ruban, G; Tassin, B; Lemaire, B J; Joannis, C

2011-01-01

This article confirms the existence of a strong linear relationship between turbidity and total suspended solids (TSS) concentration. However, the slope of this relation varies between dry and wet weather conditions, as well as between sites. The effect of this variability on estimating the instantaneous wet weather TSS concentration is assessed on the basis of the size of the calibration dataset used to establish the turbidity - TSS relationship. Results obtained indicate limited variability both between sites and during dry weather, along with a significant inter-event variability. Moreover, turbidity allows an evaluation of TSS concentrations with an acceptable level of accuracy for a reasonable rainfall event sampling campaign effort.

MHC class I and MHC class II DRB gene variability in wild and captive Bengal tigers (Panthera tigris tigris).

PubMed

Pokorny, Ina; Sharma, Reeta; Goyal, Surendra Prakash; Mishra, Sudanshu; Tiedemann, Ralph

2010-10-01

Bengal tigers are highly endangered and knowledge on adaptive genetic variation can be essential for efficient conservation and management. Here we present the first assessment of allelic variation in major histocompatibility complex (MHC) class I and MHC class II DRB genes for wild and captive tigers from India. We amplified, cloned, and sequenced alpha-1 and alpha-2 domain of MHC class I and beta-1 domain of MHC class II DRB genes in 16 tiger specimens of different geographic origin. We detected high variability in peptide-binding sites, presumably resulting from positive selection. Tigers exhibit a low number of MHC DRB alleles, similar to other endangered big cats. Our initial assessment-admittedly with limited geographic coverage and sample size-did not reveal significant differences between captive and wild tigers with regard to MHC variability. In addition, we successfully amplified MHC DRB alleles from scat samples. Our characterization of tiger MHC alleles forms a basis for further in-depth analyses of MHC variability in this illustrative threatened mammal.

Joint inversion of NMR and SIP data to estimate pore size distribution of geomaterials

NASA Astrophysics Data System (ADS)

Niu, Qifei; Zhang, Chi

2018-03-01

There are growing interests in using geophysical tools to characterize the microstructure of geomaterials because of the non-invasive nature and the applicability in field. In these applications, multiple types of geophysical data sets are usually processed separately, which may be inadequate to constrain the key feature of target variables. Therefore, simultaneous processing of multiple data sets could potentially improve the resolution. In this study, we propose a method to estimate pore size distribution by joint inversion of nuclear magnetic resonance (NMR) T2 relaxation and spectral induced polarization (SIP) spectra. The petrophysical relation between NMR T2 relaxation time and SIP relaxation time is incorporated in a nonlinear least squares problem formulation, which is solved using Gauss-Newton method. The joint inversion scheme is applied to a synthetic sample and a Berea sandstone sample. The jointly estimated pore size distributions are very close to the true model and results from other experimental method. Even when the knowledge of the petrophysical models of the sample is incomplete, the joint inversion can still capture the main features of the pore size distribution of the samples, including the general shape and relative peak positions of the distribution curves. It is also found from the numerical example that the surface relaxivity of the sample could be extracted with the joint inversion of NMR and SIP data if the diffusion coefficient of the ions in the electrical double layer is known. Comparing to individual inversions, the joint inversion could improve the resolution of the estimated pore size distribution because of the addition of extra data sets. The proposed approach might constitute a first step towards a comprehensive joint inversion that can extract the full pore geometry information of a geomaterial from NMR and SIP data.

Grain size effect on the electrical and magneto-transport properties of nanosized Pr0.67Sr0.33MnO3

NASA Astrophysics Data System (ADS)

Ng, S. W.; Lim, K. P.; Halim, S. A.; Jumiah, H.

2018-06-01

In this study, nanosized of Pr0.67Sr0.33MnO3 prepared via sol-gel method followed by heat treatment at 600-1000 °C in intervals of 100 °C were synthesized. The structure, surface morphology, electrical, magneto-transport and magnetic properties of the samples were investigated. Rietveld refinements of X-ray diffraction patterns confirm that single phase orthorhombic crystal structure with the space group of Pnma (62) is formed at 600 °C. A strong dependence of surface morphology, electrical and magneto-transport properties on grain size have been observed in this manganites system. Both grain size and crystallite size are increases with the sintering temperature due to the congregation effect. Upon increasing grain size, the paramagnetic-ferromagnetic transition temperature increases from 278 K to 295 K. The resistivity drops and the metal-insulator transition temperature shifted from 184 K to 248 K with increases of grain size due to the grain growth and reduction of grain boundary. Below metal-insulator transition temperature, the samples fit well to the combination of resistivity due to grain or domain boundaries, electron-electron scattering process and electron-phonon interaction. The resistivity data above the metal-insulator transition temperature is well described using small polaron hopping and variable range hopping models. It is found that the negative magnetoresistance also increases with larger grain size where the highest %MR of - 26% can be observed for sample sintered at 1000 °C (245 nm).

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards

PubMed Central

Nyflot, Matthew J.; Yang, Fei; Byrd, Darrin; Bowen, Stephen R.; Sandison, George A.; Kinahan, Paul E.

2015-01-01

Abstract. Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes. PMID:26251842

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

PubMed

Nyflot, Matthew J; Yang, Fei; Byrd, Darrin; Bowen, Stephen R; Sandison, George A; Kinahan, Paul E

2015-10-01

Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes.

Microdiamond grade as a regionalised variable - some basic requirements for successful local microdiamond resource estimation of kimberlites

NASA Astrophysics Data System (ADS)

Stiefenhofer, Johann; Thurston, Malcolm L.; Bush, David E.

2018-04-01

Microdiamonds offer several advantages as a resource estimation tool, such as access to deeper parts of a deposit which may be beyond the reach of large diameter drilling (LDD) techniques, the recovery of the total diamond content in the kimberlite, and a cost benefit due to the cheaper treatment cost compared to large diameter samples. In this paper we take the first step towards local estimation by showing that micro-diamond samples can be treated as a regionalised variable suitable for use in geostatistical applications and we show examples of such output. Examples of microdiamond variograms are presented, the variance-support relationship for microdiamonds is demonstrated and consistency of the diamond size frequency distribution (SFD) is shown with the aid of real datasets. The focus therefore is on why local microdiamond estimation should be possible, not how to generate such estimates. Data from our case studies and examples demonstrate a positive correlation between micro- and macrodiamond sample grades as well as block estimates. This relationship can be demonstrated repeatedly across multiple mining operations. The smaller sample support size for microdiamond samples is a key difference between micro- and macrodiamond estimates and this aspect must be taken into account during the estimation process. We discuss three methods which can be used to validate or reconcile the estimates against macrodiamond data, either as estimates or in the form of production grades: (i) reconcilliation using production data, (ii) by comparing LDD-based grade estimates against microdiamond-based estimates and (iii) using simulation techniques.

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

PubMed

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

Size-segregated compositional analysis of aerosol particles collected in the European Arctic during the ACCACIA campaign

NASA Astrophysics Data System (ADS)

Young, G.; Jones, H. M.; Darbyshire, E.; Baustian, K. J.; McQuaid, J. B.; Bower, K. N.; Connolly, P. J.; Gallagher, M. W.; Choularton, T. W.

2016-03-01

Single-particle compositional analysis of filter samples collected on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft is presented for six flights during the springtime Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign (March-April 2013). Scanning electron microscopy was utilised to derive size-segregated particle compositions and size distributions, and these were compared to corresponding data from wing-mounted optical particle counters. Reasonable agreement between the calculated number size distributions was found. Significant variability in composition was observed, with differing external and internal mixing identified, between air mass trajectory cases based on HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analyses. Dominant particle classes were silicate-based dusts and sea salts, with particles notably rich in K and Ca detected in one case. Source regions varied from the Arctic Ocean and Greenland through to northern Russia and the European continent. Good agreement between the back trajectories was mirrored by comparable compositional trends between samples. Silicate dusts were identified in all cases, and the elemental composition of the dust was consistent for all samples except one. It is hypothesised that long-range, high-altitude transport was primarily responsible for this dust, with likely sources including the Asian arid regions.

Electrical conductivity and magnetic field dependent current-voltage characteristics of nanocrystalline nickel ferrite

NASA Astrophysics Data System (ADS)

Ghosh, P.; Bhowmik, R. N.; Das, M. R.; Mitra, P.

2017-04-01

We have studied the grain size dependent electrical conductivity, dielectric relaxation and magnetic field dependent current voltage (I - V) characteristics of nickel ferrite (NiFe2O4) . The material has been synthesized by sol-gel self-combustion technique, followed by ball milling at room temperature in air environment to control the grain size. The material has been characterized using X-ray diffraction (refined with MAUD software analysis) and Transmission electron microscopy. Impedance spectroscopy and I - V characteristics in the presence of variable magnetic fields have confirmed the increase of resistivity for the fine powdered samples (grain size 5.17±0.6 nm), resulted from ball milling of the chemical routed sample. Activation energy of the material for electrical charge hopping process has increased with the decrease of grain size by mechanical milling of chemical routed sample. The I - V curves showed many highly non-linear and irreversible electrical features, e.g., I - V loop and bi-stable electronic states (low resistance state-LRS and high resistance state-HRS) on cycling the electrical bias voltage direction during I-V curve measurement. The electrical dc resistance for the chemically routed (without milled) sample in HRS (∼3.4876×104 Ω) at 20 V in presence of magnetic field 10 kOe has enhanced to ∼3.4152×105 Ω for the 10 h milled sample. The samples exhibited an unusual negative differential resistance (NDR) effect that gradually decreased on decreasing the grain size of the material. The magneto-resistance of the samples at room temperature has been found substantially large (∼25-65%). The control of electrical charge transport properties under magnetic field, as observed in the present ferrimagnetic material, indicate the magneto-electric coupling in the materials and the results could be useful in spintronics applications.

Differences in rocky reef habitats related to human disturbances across a latitudinal gradient.

PubMed

Glasby, Tim M; Gibson, Peter T; Cruz-Motta, Juan J

2017-08-01

This study tested for differences in the composition of intertidal and shallow subtidal rocky reef habitats subjected to a range of human pressures across ∼1000 km of coastline in New South Wales, Australia over 5 years. Percentage covers of habitats were sampled using aerial photography and a large grain size (20 m 2 intertidal; 800 m 2 subtidal) in a nested hierarchical design. Results were consistent with anthropogenic impacts on habitat structure only around estuaries with the most heavily urbanised or agriculturally-intense catchments. The most convincing relationships documented here related to environmental variables such as SST, latitude, reef width and proximity to large estuaries irrespective of human disturbance levels. Moreover, there were suggestions that any influences of estuarine waters (be they anthropogenic or natural) on reef assemblages could potentially extend 10s of kilometres from major estuaries. In general, our results supported those of studies that utilised smaller grain sizes (greatest variability often at smallest spatial scales), but we found that variability over scales of 100s of km can be similar to or greater than variability over scales of 10s of metres. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preparation of metallic nanoparticles by irradiation in starch aqueous solution

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

Nemţanu, Monica R., E-mail: monica.nemtanu@inflpr.ro; Braşoveanu, Mirela, E-mail: monica.nemtanu@inflpr.ro; Iacob, Nicuşor, E-mail: monica.nemtanu@inflpr.ro

Colloidal silver nanoparticles (AgNPs) were synthesized in a single step by electron beam irradiation reduction of silver ions in aqueous solution containing starch. The nanoparticles were characterized by spectrophotocolorimetry and compared with those obtained by chemical (thermal) reduction method. The results showed that the smaller sizes of AgNPs were prepared with higher yields as the irradiation dose increased. The broadening of particle size distribution occurred by increasing of irradiation dose and dose rate. Chromatic parameters such as b* (yellow-blue coordinate), C* (chroma) and ΔE{sub ab} (total color difference) could characterize the nanoparticles with respect of their concentration. Hue angle h{supmore » o} was correlated to the particle size distribution. Experimental data of the irradiated samples were also subjected to factor analysis using principal component extraction and varimax rotation in order to reveal the relation between dependent variables and independent variables and to reduce their number. The radiation-based method provided silver nanoparticles with higher concentration and narrower size distribution than those produced by chemical reduction method. Therefore, the electron beam irradiation is effective for preparation of silver nanoparticles using starch aqueous solution as dispersion medium.« less

Temporal variability and memory in sediment transport in an experimental step-pool channel

NASA Astrophysics Data System (ADS)

Saletti, Matteo; Molnar, Peter; Zimmermann, André; Hassan, Marwan A.; Church, Michael

2015-11-01

Temporal dynamics of sediment transport in steep channels using two experiments performed in a steep flume (8%) with natural sediment composed of 12 grain sizes are studied. High-resolution (1 s) time series of sediment transport were measured for individual grain-size classes at the outlet of the flume for different combinations of sediment input rates and flow discharges. Our aim in this paper is to quantify (a) the relation of discharge and sediment transport and (b) the nature and strength of memory in grain-size-dependent transport. None of the simple statistical descriptors of sediment transport (mean, extreme values, and quantiles) display a clear relation with water discharge, in fact a large variability between discharge and sediment transport is observed. Instantaneous transport rates have probability density functions with heavy tails. Bed load bursts have a coarser grain-size distribution than that of the entire experiment. We quantify the strength and nature of memory in sediment transport rates by estimating the Hurst exponent and the autocorrelation coefficient of the time series for different grain sizes. Our results show the presence of the Hurst phenomenon in transport rates, indicating long-term memory which is grain-size dependent. The short-term memory in coarse grain transport increases with temporal aggregation and this reveals the importance of the sampling duration of bed load transport rates in natural streams, especially for large fractions.

Variability of Stimulant Levels in Nine Sports Supplements Over a 9-Month Period.

PubMed

Attipoe, Selasi; Cohen, Pieter A; Eichner, Amy; Deuster, Patricia A

2016-10-01

Many studies have found that some dietary supplement product labels do not accurately reflect the actual ingredients. However, studies have not been performed to determine if ingredients in the same dietary supplement product vary over time. The objective of this study was to assess the consistency of stimulant ingredients in popular sports supplements sold in the United States over a 9-month period. Three samples of nine popular sports supplements were purchased over the 9-month period. The 27 samples were analyzed for caffeine and several other stimulants (including adulterants). The identity and quantity of stimulants were compared with stimulants listed on the label and stimulants found at earlier time points to determine the variability in individual products over the 9-month period. The primary outcome measure was the variability of stimulant amounts in the products examined. Many supplements did not contain the same number and quantity of stimulants at all time points over the 9-month period. Caffeine content varied widely in five of the six caffeinated supplements compared with the initial measurement (-7% to +266%). In addition, the stimulants-synephrine, octopamine, cathine, ephedrine, pseudoephedrine, strychnine, and methylephedrine-occurred in variable amounts in eight of the nine products. The significance of these findings is uncertain: the sample size was insufficient to support statistical analysis. In our sample of nine popular sports supplements, the presence and quantity of stimulants varied over a 9-month period. However, future studies are warranted to determine if the variability found is significant and generalizable to other supplements.

Increasing precision of turbidity-based suspended sediment concentration and load estimates.

PubMed

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

Erosion Modeling in Central China - Soil Data Acquisition by Conditioned Latin Hypercube Sampling and Incorporation of Legacy Data

NASA Astrophysics Data System (ADS)

Stumpf, Felix; Schönbrodt-Stitt, Sarah; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2013-04-01

The Three Gorges Dam at the Yangtze River in Central China outlines a prominent example of human-induced environmental impacts. Throughout one year the water table at the main river fluctuates about 30m due to impoundment and drainage activities. The dynamic water table implicates a range of georisks such as soil erosion, mass movements, sediment transport and diffuse matter inputs into the reservoir. Within the framework of the joint Sino-German project YANGTZE GEO, the subproject "Soil Erosion" deals with soil erosion risks and sediment transport pathways into the reservoir. The study site is a small catchment (4.8 km²) in Badong, approximately 100 km upstream the dam. It is characterized by scattered plots of agricultural landuse and resettlements in a largely wooded, steep sloping and mountainous area. Our research is focused on data acquisition and processing to develop a process-oriented erosion model. Hereby, area-covering knowledge of specific soil properties in the catchment is an intrinsic input parameter. This will be acquired by means of digital soil mapping (DSM). Thereby, soil properties are estimated by covariates. The functions are calibrated by soil property samples. The DSM approach is based on an appropriate sample design, which reflects the heterogeneity of the catchment, regarding the covariates with influence on the relevant soil properties. In this approach the covariates, processed by a digital terrain analysis, are outlined by the slope, altitude, profile curvature, plane curvature, and the aspect. For the development of the sample design, we chose the Conditioned Latin Hypercube Sampling (cLHS) procedure (Minasny and McBratney, 2006). It provides an efficient method of sampling variables from their multivariate distribution. Thereby, a sample size n from multiple variables is drawn such that for each variable the sample is marginally maximally stratified. The method ensures the maximal stratification by two features: First, number of strata equals the sample size n and secondly, the probability of falling in each of the strata is n-¹ (McKay et al., 1979). We extended the classical cLHS with extremes (Schmidt et al., 2012) approach by incorporating legacy data of previous field campaigns. Instead of identifying precise sample locations by CLHS, we demarcate the multivariate attribute space of the samples based on the histogram borders of each stratum. This widens the spatial scope of the actual CLHS sample locations and allows the incorporation of legacy data lying within that scope. Furthermore, this approach provides an extended potential regarding the accessibility of sample sites in the field.

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

USGS Publications Warehouse

Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad

2013-01-01

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Kinetics of phase transformation in glass forming systems

NASA Technical Reports Server (NTRS)

Ray, Chandra S.

1994-01-01

The objectives of this research were to (1) develop computer models for realistic simulations of nucleation and crystal growth in glasses, which would also have the flexibility to accomodate the different variables related to sample characteristics and experimental conditions, and (2) design and perform nucleation and crystallization experiments using calorimetric measurements, such as differential scanning calorimetry (DSC) and differential thermal analysis (DTA) to verify these models. The variables related to sample characteristics mentioned in (1) above include size of the glass particles, nucleating agents, and the relative concentration of the surface and internal nuclei. A change in any of these variables changes the mode of the transformation (crystallization) kinetics. A variation in experimental conditions includes isothermal and nonisothermal DSC/DTA measurements. This research would lead to develop improved, more realistic methods for analysis of the DSC/DTA peak profiles to determine the kinetic parameters for nucleation and crystal growth as well as to assess the relative merits and demerits of the thermoanalytical models presently used to study the phase transformation in glasses.

A New Approach of Juvenile Age Estimation using Measurements of the Ilium and Multivariate Adaptive Regression Splines (MARS) Models for Better Age Prediction.

PubMed

Corron, Louise; Marchal, François; Condemi, Silvana; Chaumoître, Kathia; Adalian, Pascal

2017-01-01

Juvenile age estimation methods used in forensic anthropology generally lack methodological consistency and/or statistical validity. Considering this, a standard approach using nonparametric Multivariate Adaptive Regression Splines (MARS) models were tested to predict age from iliac biometric variables of male and female juveniles from Marseilles, France, aged 0-12 years. Models using unidimensional (length and width) and bidimensional iliac data (module and surface) were constructed on a training sample of 176 individuals and validated on an independent test sample of 68 individuals. Results show that MARS prediction models using iliac width, module and area give overall better and statistically valid age estimates. These models integrate punctual nonlinearities of the relationship between age and osteometric variables. By constructing valid prediction intervals whose size increases with age, MARS models take into account the normal increase of individual variability. MARS models can qualify as a practical and standardized approach for juvenile age estimation. © 2016 American Academy of Forensic Sciences.

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.

Contemporary and historic factors influence differently genetic differentiation and diversity in a tropical palm

PubMed Central

da Silva Carvalho, C; Ribeiro, M C; Côrtes, M C; Galetti, M; Collevatti, R G

2015-01-01

Population genetics theory predicts loss in genetic variability because of drift and inbreeding in isolated plant populations; however, it has been argued that long-distance pollination and seed dispersal may be able to maintain gene flow, even in highly fragmented landscapes. We tested how historical effective population size, historical migration and contemporary landscape structure, such as forest cover, patch isolation and matrix resistance, affect genetic variability and differentiation of seedlings in a tropical palm (Euterpe edulis) in a human-modified rainforest. We sampled 16 sites within five landscapes in the Brazilian Atlantic forest and assessed genetic variability and differentiation using eight microsatellite loci. Using a model selection approach, none of the covariates explained the variation observed in inbreeding coefficients among populations. The variation in genetic diversity among sites was best explained by historical effective population size. Allelic richness was best explained by historical effective population size and matrix resistance, whereas genetic differentiation was explained by matrix resistance. Coalescence analysis revealed high historical migration between sites within landscapes and constant historical population sizes, showing that the genetic differentiation is most likely due to recent changes caused by habitat loss and fragmentation. Overall, recent landscape changes have a greater influence on among-population genetic variation than historical gene flow process. As immediate restoration actions in landscapes with low forest amount, the development of more permeable matrices to allow the movement of pollinators and seed dispersers may be an effective strategy to maintain microevolutionary processes. PMID:25873150

Seed and vegetative production of shrubs and growth of understory conifer regeneration

USGS Publications Warehouse

Wender, B.; Harrington, C.; Tappeiner, J. C.

2004-01-01

We observed flower and fruit production for nine understory shrub species in western Washington and Oregon and examined the relationships between shrub reproductive output and plant size, plant age, site factors, and overstory density to determine the factors that control flowering or fruiting in understory shrubs. In Washington, 50 or more shrubs or microplots (for rhizomatous species) were sampled for each of eight species. The variables examined were more useful for explaining abundance of flowers or fruit on shrubs than they were for explaining the probability that a shrub would produce flowers or fruit. Plant size was consistently the most useful predictor of flower/fruit abundance in all species; plant age was also a good predictor of abundance and was strongly correlated with plant size. Site variables (e.g., slope) and overstory competition variables (e.g., presence/absence of a canopy gap) also helped explain flower/fruit abundance for some species. At two Oregon sites, the responses of five species to four levels of thinning were observed for 2-4 yr (15 shrubs or microplots per treatment per year). Thinning increased the probability and abundance of flowering/fruiting for two species, had no effect on one species, and responses for two other species were positive but inconsistent between sites or from year to year. We believe reducing overstory density or creating canopy gaps may be useful tools for enhancing shrub size and vigor, thus, increasing the probability and abundance of fruiting in some understory shrub species.

Flower and fruit production of understory shrubs in western Washington and Oregon

USGS Publications Warehouse

Wender, B.; Harrington, C.; Tappeiner, J. C.

2004-01-01

We observed flower and fruit production for nine understory shrub species in western Washington and Oregon and examined the relationships between shrub reproductive output and plant size, plant age, site factors, and overstory density to determine the factors that control flowering or fruiting in understory shrubs. In Washington, 50 or more shrubs or microplots (for rhizomatous species) were sampled for each of eight species. The variables examined were more useful for explaining abundance of flowers or fruit on shrubs than they were for explaining the probability that a shrub would produce flowers or fruit. Plant size was consistently the most useful predictor of flower/fruit abundance in all species; plant age was also a good predictor of abundance and was strongly correlated with plant size. Site variables (e.g., slope) and overstory competition variables (e.g., presence/absence of a canopy gap) also helped explain flower/fruit abundance for some species. At two Oregon sites, the responses of five species to four levels of thinning were observed for 2-4 yr (15 shrubs or microplots per treatment per year). Thinning increased the probability and abundance of flowering/fruiting for two species, had no effect on one species, and responses for two other species were positive but inconsistent between sites or from year to year. We believe reducing overstory density or creating canopy gaps may be useful tools for enhancing shrub size and vigor, thus, increasing the probability and abundance of fruiting in some understory shrub species.

Poverty, Pregnancy, and Birth Outcomes: A Study of the Earned Income Tax Credit.

PubMed

Hamad, Rita; Rehkopf, David H

2015-09-01

Economic interventions are increasingly recognised as a mechanism to address perinatal health outcomes among disadvantaged groups. In the US, the earned income tax credit (EITC) is the largest poverty alleviation programme. Little is known about its effects on perinatal health among recipients and their children. We exploit quasi-random variation in the size of EITC payments to examine the effects of income on perinatal health. The study sample includes women surveyed in the 1979 National Longitudinal Survey of Youth (n = 2985) and their children born during 1986-2000 (n = 4683). Outcome variables include utilisation of prenatal and postnatal care, use of alcohol and tobacco during pregnancy, term birth, birthweight, and breast-feeding status. We first examine the health effects of both household income and EITC payment size using multivariable linear regressions. We then employ instrumental variables analysis to estimate the causal effect of income on perinatal health, using EITC payment size as an instrument for household income. We find that EITC payment size is associated with better levels of several indicators of perinatal health. Instrumental variables analysis, however, does not reveal a causal association between household income and these health measures. Our findings suggest that associations between income and perinatal health may be confounded by unobserved characteristics, but that EITC income improves perinatal health. Future studies should continue to explore the impacts of economic interventions on perinatal health outcomes, and investigate how different forms of income transfers may have different impacts. © 2015 John Wiley & Sons Ltd.

Impact of Sample Size and Variability on the Power and Type I Error Rates of Equivalence Tests: A Simulation Study

ERIC Educational Resources Information Center

Rusticus, Shayna A.; Lovato, Chris Y.

2014-01-01

The question of equivalence between two or more groups is frequently of interest to many applied researchers. Equivalence testing is a statistical method designed to provide evidence that groups are comparable by demonstrating that the mean differences found between groups are small enough that they are considered practically unimportant. Few…

Describing wildland surface fuel loading for fire management: A review of approaches, methods and systems

Treesearch

Robert E. Keane

2013-01-01

Wildland fuelbeds are exceptionally complex, consisting of diverse particles of many sizes, types and shapes with abundances and properties that are highly variable in time and space. This complexity makes it difficult to accurately describe, classify, sample and map fuels for wildland fire research and management. As a result, many fire behaviour and effects software...

Explaining Comfort with Homosexuality among Social Work Students: The Impact of Demographic, Contextual, and Attitudinal Factors

ERIC Educational Resources Information Center

Swank, Eric; Raiz, Lisa

2007-01-01

While recent research explores the determinants of homophobia among college students, only a few studies look at the perceptions of homosexuals among social work students. Unfortunately these rare studies generally present a modest list of predictor variables or small sample sizes. To address this gap, this research explores the ways in which…

Predicting Meaningful Employment for Refugees: The Influence of Personal Characteristics and Developmental Factors on Employment Status and Hourly Wages

ERIC Educational Resources Information Center

Codell, Jonathan D.; Hill, Robert D.; Woltz, Dan J.; Gore, Paul A.

2011-01-01

Refugee demographic and developmental variables were evaluated as predictors of employment outcomes following a six-month non-governmental organization (NGO) directed resettlement period. The sample consisted of 85 refugee adults (18 to 54 years) who were resettling in a medium sized urban setting in the western United States. Demographics…

Variable temperature sensitivity of soil organic carbon in North American forests

Treesearch

Cinzia Fissore; Christian P. Giardina; Christopher W. Swanston; Gary M. King; Randall K. Kolka

2009-01-01

We investigated mean residence time (MRT) for soil organic carbon (SOC) sampled from paired hardwood and pine forests located along a 22 °C mean annual temperature (MAT) gradient in North America. We used acid hydrolysis fractionation, radiocarbon analyses, long-term laboratory incubations (525-d), and a three-pool model to describe the size and kinetics of...

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.

Analysis of Genetic Algorithm for Rule-Set Production (GARP) modeling approach for predicting distributions of fleas implicated as vectors of plague, Yersinia pestis, in California.

PubMed

Adjemian, Jennifer C Z; Girvetz, Evan H; Beckett, Laurel; Foley, Janet E

2006-01-01

More than 20 species of fleas in California are implicated as potential vectors of Yersinia pestis. Extremely limited spatial data exist for plague vectors-a key component to understanding where the greatest risks for human, domestic animal, and wildlife health exist. This study increases the spatial data available for 13 potential plague vectors by using the ecological niche modeling system Genetic Algorithm for Rule-Set Production (GARP) to predict their respective distributions. Because the available sample sizes in our data set varied greatly from one species to another, we also performed an analysis of the robustness of GARP by using the data available for flea Oropsylla montana (Baker) to quantify the effects that sample size and the chosen explanatory variables have on the final species distribution map. GARP effectively modeled the distributions of 13 vector species. Furthermore, our analyses show that all of these modeled ranges are robust, with a sample size of six fleas or greater not significantly impacting the percentage of the in-state area where the flea was predicted to be found, or the testing accuracy of the model. The results of this study will help guide the sampling efforts of future studies focusing on plague vectors.

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

Predicting crappie recruitment in Ohio reservoirs with spawning stock size, larval density, and chlorophyll concentrations

USGS Publications Warehouse

Bunnell, David B.; Hale, R. Scott; Vanni, Michael J.; Stein, Roy A.

2006-01-01

Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.

Interannual variations in the hatching pattern, larval growth and otolith size of a sand-dwelling fish from central Chile

NASA Astrophysics Data System (ADS)

Rodríguez-Valentino, Camilo; Landaeta, Mauricio F.; Castillo-Hidalgo, Gissella; Bustos, Claudia A.; Plaza, Guido; Ojeda, F. Patricio

2015-09-01

The interannual variation (2010-2013) of larval abundance, growth and hatching patterns of the Chilean sand stargazer Sindoscopus australis (Pisces: Dactyloscopidae) was investigated through otolith microstructure analysis from samples collected nearshore (<500 m from shore) during austral late winter-early spring off El Quisco bay, central Chile. In the studied period, the abundance of larval stages in the plankton samples varied from 2.2 to 259.3 ind. 1000 m-3; larval abundance was similar between 2010 and 2011, and between 2012 and 2013, but increased significantly from 2011 to 2012. The estimated growth rates increased twice, from 0.09 to 0.21 mm day-1, between 2011 and 2013. Additionally, otolith size (radius, perimeter and area), related to body length of larvae, significantly decreased from 2010 to 2012, but increases significantly in 2013. Although the mean values of microincrement widths of sagitta otoliths were similar between 2010 and 2011 (around 0.6-0.7 μm), the interindividual variability increases in 2011 and 2013, suggesting large environmental variability experienced by larvae during these years. Finally, the hatching pattern of S. australis changed significantly from semi-lunar to lunar cycle after 2012.

A simulation study on Bayesian Ridge regression models for several collinearity levels

NASA Astrophysics Data System (ADS)

Efendi, Achmad; Effrihan

2017-12-01

When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.

Discovering human germ cell mutagens with whole genome sequencing: Insights from power calculations reveal the importance of controlling for between-family variability.

PubMed

Webster, R J; Williams, A; Marchetti, F; Yauk, C L

2018-07-01

Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

USGS Publications Warehouse

Menke, S.B.; Holway, D.A.; Fisher, R.N.; Jetz, W.

2009-01-01

Aim: Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location: California, USA. Methods: We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results: We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions: These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing.

Rarity and Incomplete Sampling in DNA-Based Species Delimitation.

PubMed

Ahrens, Dirk; Fujisawa, Tomochika; Krammer, Hans-Joachim; Eberle, Jonas; Fabrizi, Silvia; Vogler, Alfried P

2016-05-01

DNA-based species delimitation may be compromised by limited sampling effort and species rarity, including "singleton" representatives of species, which hampers estimates of intra- versus interspecies evolutionary processes. In a case study of southern African chafers (beetles in the family Scarabaeidae), many species and subclades were poorly represented and 48.5% of species were singletons. Using cox1 sequences from >500 specimens and ∼100 species, the Generalized Mixed Yule Coalescent (GMYC) analysis as well as various other approaches for DNA-based species delimitation (Automatic Barcode Gap Discovery (ABGD), Poisson tree processes (PTP), Species Identifier, Statistical Parsimony), frequently produced poor results if analyzing a narrow target group only, but the performance improved when several subclades were combined. Hence, low sampling may be compensated for by "clade addition" of lineages outside of the focal group. Similar findings were obtained in reanalysis of published data sets of taxonomically poorly known species assemblages of insects from Madagascar. The low performance of undersampled trees is not due to high proportions of singletons per se, as shown in simulations (with 13%, 40% and 52% singletons). However, the GMYC method was highly sensitive to variable effective population size ([Formula: see text]), which was exacerbated by variable species abundances in the simulations. Hence, low sampling success and rarity of species affect the power of the GMYC method only if they reflect great differences in [Formula: see text] among species. Potential negative effects of skewed species abundances and prevalence of singletons are ultimately an issue about the variation in [Formula: see text] and the degree to which this is correlated with the census population size and sampling success. Clade addition beyond a limited study group can overcome poor sampling for the GMYC method in particular under variable [Formula: see text] This effect was less pronounced for methods of species delimitation not based on coalescent models. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The comparison of automated clustering algorithms for resampling representative conformer ensembles with RMSD matrix.

PubMed

Kim, Hyoungrae; Jang, Cheongyun; Yadav, Dharmendra K; Kim, Mi-Hyun

2017-03-23

The accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate enough conformers, however model building methods relies on explicit number of common conformers. In this work, we have attempted to make clustering algorithms, which could find reasonable number of representative conformer ensembles automatically with asymmetric dissimilarity matrix generated from openeye tool kit. RMSD was the important descriptor (variable) of each column of the N × N matrix considered as N variables describing the relationship (network) between the conformer (in a row) and the other N conformers. This approach used to evaluate the performance of the well-known clustering algorithms by comparison in terms of generating representative conformer ensembles and test them over different matrix transformation functions considering the stability. In the network, the representative conformer group could be resampled for four kinds of algorithms with implicit parameters. The directed dissimilarity matrix becomes the only input to the clustering algorithms. Dunn index, Davies-Bouldin index, Eta-squared values and omega-squared values were used to evaluate the clustering algorithms with respect to the compactness and the explanatory power. The evaluation includes the reduction (abstraction) rate of the data, correlation between the sizes of the population and the samples, the computational complexity and the memory usage as well. Every algorithm could find representative conformers automatically without any user intervention, and they reduced the data to 14-19% of the original values within 1.13 s per sample at the most. The clustering methods are simple and practical as they are fast and do not ask for any explicit parameters. RCDTC presented the maximum Dunn and omega-squared values of the four algorithms in addition to consistent reduction rate between the population size and the sample size. The performance of the clustering algorithms was consistent over different transformation functions. Moreover, the clustering method can also be applied to molecular dynamics sampling simulation results.

Bone Marrow Stem Cells and Ear Framework Reconstruction.

PubMed

Karimi, Hamid; Emami, Seyed-Abolhassan; Olad-Gubad, Mohammad-Kazem

2016-11-01

Repair of total human ear loss or congenital lack of ears is one of the challenging issues in plastic and reconstructive surgery. The aim of the present study was 3D reconstruction of the human ear with cadaveric ear cartilages seeded with human mesenchymal stem cells. We used cadaveric ear cartilages with preserved perichondrium. The samples were divided into 2 groups: group A (cartilage alone) and group B (cartilage seeded with a mixture of fibrin powder and mesenchymal stem cell [1,000,000 cells/cm] used and implanted in back of 10 athymic rats). After 12 weeks, the cartilages were removed and shape, size, weight, flexibility, and chondrocyte viability were evaluated. P value <0.05 was considered significant. In group A, size and weight of cartilages clearly reduced (P < 0.05) and then shape and flexibility (torsion of cartilages in clockwise and counterclockwise directions) were evaluated, which were found to be significantly reduced (P > 0.05). After staining with hematoxylin and eosin and performing microscopic examination, very few live chondrocytes were found in group A. In group B, size and weight of samples were not changed (P < 0.05); the shape and flexibility of samples were well maintained (P < 0.05) and on performing microscopic examination of cartilage samples, many live chondrocytes were found in cartilage (15-20 chondrocytes in each microscopic field). In samples with human stem cell, all variables (size, shape, weight, and flexibility) were significantly maintained and abundant live chondrocytes were found on performing microscopic examination. This method may be used for reconstruction of full defect of auricles in humans.

Age as a Risk Factor for Burnout Syndrome in Nursing Professionals: A Meta-Analytic Study.

PubMed

Gómez-Urquiza, José L; Vargas, Cristina; De la Fuente, Emilia I; Fernández-Castillo, Rafael; Cañadas-De la Fuente, Guillermo A

2017-04-01

Although past research has highlighted the possibility of a direct relationship between the age of nursing professionals and burnout syndrome, results have been far from conclusive. The aim of this study was to conduct a wider analysis of the influence of age on the three dimensions of burnout syndrome (emotional exhaustion, depersonalization, and personal accomplishment) in nurses. We performed a meta-analysis of 51 publications extracted from health sciences and psychology databases that fulfilled the inclusion criteria. There were 47 reports of information on emotional exhaustion in 50 samples, 39 reports on depersonalization for 42 samples, and 31 reports on personal accomplishment in 34 samples. The mean effect sizes indicated that younger age was a significant factor in the emotional exhaustion and depersonalization of nurses, although it was somewhat less influential in the dimension of personal accomplishment. Because of heterogeneity in the effect sizes, moderating variables that might explain the association between age and burnout were also analyzed. Gender, marital status, and study characteristics moderated the relationship between age and burnout and may be crucial for the identification of high-risk groups. More research is needed on other variables for which there were only a small number of studies. Identification of burnout risk factors will facilitate establishment of burnout prevention programs for nurses. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Length Variation and Heteroplasmy Are Frequent in Mitochondrial DNA from Parthenogenetic and Bisexual Lizards (Genus Cnemidophorus)

PubMed Central

Densmore, Llewellyn D.; Wright, John W.; Brown, Wesley M.

1985-01-01

Samples of mtDNA isolated from each of 92 lizards representing all color pattern classes of Cnemidophorus tesselatus and two populations of C. tigris marmoratus were digested with the restriction endonucleases MboI, TaqI, RsaI and MspI. The mtDNA fragment sizes were compared after radioactive labeling and gel electrophoresis. Three features were notable in the comparisons: (1) there was little variation due to gain or loss of cleavage sites, (2) two fragments varied noticeably in length among the samples, one by a variable amount up to a maximum difference of ∼370 base pairs (bp) and the other by a discrete amount of 35 bp, (3) these two fragments occasionally varied within, as well as between, samples. Two regions that corresponded in size to these variants were identified by restriction endonuclease cleavage mapping. One of these is adjacent to the D-loop. Heteroplasmy, heretofore rarely observed, occurred frequently in these same two regions. Variability in the copy number of a tandemly repeated 64-bp sequence appears to be one component of the variation, but others (e.g. , base substitutions or small additions/deletions) must also be involved. The frequent occurrence of these length variations suggests either that they can be generated rapidly or that they were inherited from a highly polymorphic ancestor. The former interpretation is favored. PMID:2993100

Factors associated to acceptable treatment adherence among children with chronic kidney disease in Guatemala

PubMed Central

Cerón, Alejandro; Méndez-Alburez, Luis Pablo; Lou-Meda, Randall

2017-01-01

Pediatric patients with Chronic Kidney Disease face several barriers to medication adherence that, if addressed, may improve clinical care outcomes. A cross sectional questionnaire was administered in the Foundation for Children with Kidney Disease (FUNDANIER, Guatemala City) from September of 2015 to April of 2016 to identify the predisposing factors, enabling factors and need factors related to medication adherence. Sample size was calculated using simple random sampling with a confidence level of 95%, confidence interval of 0.05 and a proportion of 87%. A total of 103 participants responded to the questionnaire (calculated sample size was 96). Independent variables were defined and described, and the bivariate relationship to dependent variables was determined using Odds Ratio. Multivariate analysis was carried out using logistic regression. The mean adherence of study population was 78% (SD 0.08, max = 96%, min = 55%). The mean adherence in transplant patients was 82% (SD 7.8, max 96%, min 63%), and the mean adherence in dialysis patients was 76% (SD 7.8 max 90%, min 55%). Adherence was positively associated to the mother’s educational level and to higher monthly household income. Together predisposing, enabling and need factors illustrate the complexities surrounding adherence in this pediatric CKD population. Public policy strategies aimed at improving access to comprehensive treatment regimens may facilitate treatment access, alleviating economic strain on caregivers and may improve adherence outcomes. PMID:29036228

Factors associated to acceptable treatment adherence among children with chronic kidney disease in Guatemala.

PubMed

Ramay, Brooke M; Cerón, Alejandro; Méndez-Alburez, Luis Pablo; Lou-Meda, Randall

2017-01-01

Pediatric patients with Chronic Kidney Disease face several barriers to medication adherence that, if addressed, may improve clinical care outcomes. A cross sectional questionnaire was administered in the Foundation for Children with Kidney Disease (FUNDANIER, Guatemala City) from September of 2015 to April of 2016 to identify the predisposing factors, enabling factors and need factors related to medication adherence. Sample size was calculated using simple random sampling with a confidence level of 95%, confidence interval of 0.05 and a proportion of 87%. A total of 103 participants responded to the questionnaire (calculated sample size was 96). Independent variables were defined and described, and the bivariate relationship to dependent variables was determined using Odds Ratio. Multivariate analysis was carried out using logistic regression. The mean adherence of study population was 78% (SD 0.08, max = 96%, min = 55%). The mean adherence in transplant patients was 82% (SD 7.8, max 96%, min 63%), and the mean adherence in dialysis patients was 76% (SD 7.8 max 90%, min 55%). Adherence was positively associated to the mother's educational level and to higher monthly household income. Together predisposing, enabling and need factors illustrate the complexities surrounding adherence in this pediatric CKD population. Public policy strategies aimed at improving access to comprehensive treatment regimens may facilitate treatment access, alleviating economic strain on caregivers and may improve adherence outcomes.

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

Urban catchments are typically characterised by a more flashy nature of the hydrological response compared to natural catchments. Predicting flow changes associated with urbanisation is not straightforward, as they are influenced by interactions between impervious cover, basin size, drainage connectivity and stormwater management infrastructure. In this study, we present an alternative approach to statistical analysis of hydrological response variability and basin flashiness, based on the distribution of inter-amount times. We analyse inter-amount time distributions of high-resolution streamflow time series for 17 (semi-)urbanised basins in North Carolina, USA, ranging from 13 to 238 km2 in size. We show that in the inter-amount-time framework, sampling frequency is tuned to the local variability of the flow pattern, resulting in a different representation and weighting of high and low flow periods in the statistical distribution. This leads to important differences in the way the distribution quantiles, mean, coefficient of variation and skewness vary across scales and results in lower mean intermittency and improved scaling. Moreover, we show that inter-amount-time distributions can be used to detect regulation effects on flow patterns, identify critical sampling scales and characterise flashiness of hydrological response. The possibility to use both the classical approach and the inter-amount-time framework to identify minimum observable scales and analyse flow data opens up interesting areas for future research.

Particle size distributions of lead measured in battery manufacturing and secondary smelter facilities and implications in setting workplace lead exposure limits.

PubMed

Petito Boyce, Catherine; Sax, Sonja N; Cohen, Joel M

2017-08-01

Inhalation plays an important role in exposures to lead in airborne particulate matter in occupational settings, and particle size determines where and how much of airborne lead is deposited in the respiratory tract and how much is subsequently absorbed into the body. Although some occupational airborne lead particle size data have been published, limited information is available reflecting current workplace conditions in the U.S. To address this data gap, the Battery Council International (BCI) conducted workplace monitoring studies at nine lead acid battery manufacturing facilities (BMFs) and five secondary smelter facilities (SSFs) across the U.S. This article presents the results of the BCI studies focusing on the particle size distributions calculated from Personal Marple Impactor sampling data and particle deposition estimates in each of the three major respiratory tract regions derived using the Multiple-Path Particle Dosimetry model. The BCI data showed the presence of predominantly larger-sized particles in the work environments evaluated, with average mass median aerodynamic diameters (MMADs) ranging from 21-32 µm for the three BMF job categories and from 15-25 µm for the five SSF job categories tested. The BCI data also indicated that the percentage of lead mass measured at the sampled facilities in the submicron range (i.e., <1 µm, a particle size range associated with enhanced absorption of associated lead) was generally small. The estimated average percentages of lead mass in the submicron range for the tested job categories ranged from 0.8-3.3% at the BMFs and from 0.44-6.1% at the SSFs. Variability was observed in the particle size distributions across job categories and facilities, and sensitivity analyses were conducted to explore this variability. The BCI results were compared with results reported in the scientific literature. Screening-level analyses were also conducted to explore the overall degree of lead absorption potentially associated with the observed particle size distributions and to identify key issues associated with applying such data to set occupational exposure limits for lead.

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.

Discriminant function sexing of fragmentary and complete femora: standards for contemporary Croatia.

PubMed

Slaus, Mario; Strinović, Davor; Skavić, Josip; Petrovecki, Vedrana

2003-05-01

Determining sex is one of the first and most important steps in identifying decomposed corpses or skeletal remains. Previous studies have demonstrated that populations differ from each other in size and proportion and that these differences can affect metric assessment of sex. This paper establishes standards for determining sex from fragmentary and complete femurs in a modern Croatian population. The sample is composed of 195 femora (104 male and 91 female) from positively identified victims of the 1991 War in Croatia. Six discriminant functions were generated. one using seven variables, three using two variables, and two employing one variable. Results show that complete femora can be sexed with 94.4% accuracy. The same overall accuracy, with slight differences in male/female accuracy, was achieved using a combination of two variables defining the epiphyses, and with the variable maximum diameter of the femoral head.

Daily Physical Activity and Cognitive Function Variability in Older Adults.

PubMed

Phillips, Christine B; Edwards, Jerri D; Andel, Ross; Kilpatrick, Marcus

2016-04-01

Physical activity (PA) is believed to preserve cognitive function in older adulthood, though little is known about these relationships within the context of daily life. The present microlongitudinal pilot study explored within- and between-person relationships between daily PA and cognitive function and also examined within-person effect sizes in a sample of community-dwelling older adults. Fifty-one healthy participants (mean age = 70.1 years) wore an accelerometer and completed a cognitive assessment battery for five days. There were no significant associations between cognitive task performance and participants' daily or average PA over the study period. Effect size estimates indicated that PA explained 0-24% of within-person variability in cognitive function, depending on cognitive task and PA dose. Results indicate that PA may have near-term cognitive effects and should be explored as a possible strategy to enhance older adults' ability to perform cognitively complex activities within the context of daily living.

Determinants of corporate dividend policy in Indonesia

NASA Astrophysics Data System (ADS)

Lestari, H. S.

2018-01-01

This study aims to investigate the determinants factors that effect the dividend policy. The sample used in this research is manufacture companies listed in Indonesia Stock Exchange (IDX) and the period 2011 - 2015. There are independent variables such as earning, cash flow, free cash flow, debt, growth opportunities, investment opportunities, firm size, largest shareholder, firm risk, lagged dividend and dividend policy used as dependent variable. The study examines a total of 32 manufacture companies. After analyzing the data using the program software Eviews 9.0 by multiples regression analysis reveal that earning, cash flow, free cash flow, firm size, and lagged dividend have significant effect on dividend policy, whereas debt, growth opportunities, investment opportunities, largest shareholder, and firm risk have no significant effect on dividend policy. The results of this study are expected to be implemented by the financial managers in improving corporate profits and basic information as return on investment decisions.

Contribution of ants in modifying of soil acidity and particle size distribution

NASA Astrophysics Data System (ADS)

Morgun, Alexandra; Golichenkov, Maxim

2015-04-01

Being a natural body, formed by the influence of biota on the upper layers of the Earth's crust, the soil is the most striking example of biogenic-abiogenic interactions in the biosphere. Invertebrates (especially ants that build soil nests) are important agents that change soil properties in well developed terrestrial ecosystems. Impact of soil microorganisms on soil properties is particularly described in numerous literature and concerns mainly chemical properties and general indicators of soil biological activity. Influence of ants (as representatives of the soil mesofauna) mostly appears as mechanical movement of soil particles and aggregates, and chemical effects caused by concentration of organic matter within the ant's nest. The aim of this research was to evaluate the effect of ants on physical and chemical soil attributes such as particle size distribution and soil acidity. The samples were taken from aerial parts of Lasius niger nests, selected on different elements of the relief (summit position, slope, terrace and floodplain) in the Arkhangelsk region (north of the European part of Russia) and compared with the specimens of the upper horizons of the reference soils. Particle size distribution was determined by laser diffraction method using laser diffraction particle size analyzer «Analysette 22 comfort» (FRITSCH, Germany). The acidity (pH) was determined by potentiometry in water suspension. Particle size distribution of the samples from the nests is more variable as compared to the control samples. For example, the content of 5-10 μm fraction ranges from 9% to 12% in reference soils, while in the anthill samples the variation is from 8% to 15%. Similarly, for 50-250 μm fraction - it ranges from 15% to 18% in reference soils, whereas in anthills - from 6% to 29%. The results of particle size analysis showed that the reference sample on the terrace has silty loam texture and nests soil L. niger are medium loam. The reference soil on the slope is characterized as medium loam, and ant's nest material has silty loam texture. The control samples of soil and ants nests on the summit position are similar and have medium loam texture. Generally we outline that the particle size distribution of anthill samples shows more variability. We assume that ants operate with small soil aggregates, in which fine fractions may link together coarser particles. pH measurements show that the reference soils have a strongly acidic reaction on the summit position (pH 4.6), slightly acidic on the slope (pH 5.5) and neutral on the terrace and on the floodplain (pH 7.2). While the material of the anthills tends to be slightly alkalinized on the summit (pH 4.8) and alkalinized on the slope (pH 7.2), but acidified to neutral on the floodplain and terrace (pH 6.4 and 5.7). Therefore, the ants form specific physico-chemical conditions that are different from the surrounding (native) soil, significantly increasing the complexity of soil cover structure. This is a clear example of ecosystem engineering functions of ants in nature. Increased complexity of soil pattern is the result of variations in pH and particle size distribution. Both cause the preconditions for the formation of new environmental niches and enhance biodiversity in natural ecosystems.

Semiquantitative analysis of gaps in microbiological performance of fish processing sector implementing current food safety management systems: a case study.

PubMed

Onjong, Hillary Adawo; Wangoh, John; Njage, Patrick Murigu Kamau

2014-08-01

Fish processing plants still face microbial food safety-related product rejections and the associated economic losses, although they implement legislation, with well-established quality assurance guidelines and standards. We assessed the microbial performance of core control and assurance activities of fish exporting processors to offer suggestions for improvement using a case study. A microbiological assessment scheme was used to systematically analyze microbial counts in six selected critical sampling locations (CSLs). Nine small-, medium- and large-sized companies implementing current food safety management systems (FSMS) were studied. Samples were collected three times on each occasion (n = 324). Microbial indicators representing food safety, plant and personnel hygiene, and overall microbiological performance were analyzed. Microbiological distribution and safety profile levels for the CSLs were calculated. Performance of core control and assurance activities of the FSMS was also diagnosed using an FSMS diagnostic instrument. Final fish products from 67% of the companies were within the legally accepted microbiological limits. Salmonella was absent in all CSLs. Hands or gloves of workers from the majority of companies were highly contaminated with Staphylococcus aureus at levels above the recommended limits. Large-sized companies performed better in Enterobacteriaceae, Escherichia coli, and S. aureus than medium- and small-sized ones in a majority of the CSLs, including receipt of raw fish material, heading and gutting, and the condition of the fish processing tables and facilities before cleaning and sanitation. Fish products of 33% (3 of 9) of the companies and handling surfaces of 22% (2 of 9) of the companies showed high variability in Enterobacteriaceae counts. High variability in total viable counts and Enterobacteriaceae was noted on fish products and handling surfaces. Specific recommendations were made in core control and assurance activities associated with sampling locations showing poor performance.

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species.

PubMed

Gravel, Dominique; Beaudet, Marilou; Messier, Christian

2008-10-01

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.

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.

Investigating parameters participating in the infant respiratory control system attractor.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2008-01-01

Theoretically, any participating parameter in a non-linear system represents the dynamics of the whole system. Taken's time delay embedding theory provides the fundamental basis for allowing non-linear analysis to be performed on physiological, time-series data. In practice, only one measurable parameter is required to be measured to convey an accurate representation of the system dynamics. In this paper, the infant respiratory control system is represented using three variables-a digitally sampled respiratory inductive plethysmography waveform, and the derived parameters tidal volume and inter-breath interval time series data. For 14 healthy infants, these data streams were analysed using recurrence plot analysis across one night of sleep. The measured attractor size of these variables followed the same qualitative trends across the nights study. Results suggest that the attractor size measures of the derived IBI and tidal volume are representative surrogates for the raw respiratory waveform. The extent to which the relative attractor sizes of IBI and tidal volume remain constant through changing sleep state could potentially be used to quantify pathology, or maturation of breathing control.

Comparing Bilingual to Monolingual Learners on English Spelling: A Meta-analytic Review.

PubMed

Zhao, Jing; Quiroz, Blanca; Dixon, L Quentin; Joshi, R Malatesha

2016-08-01

This study reports on a meta-analysis to examine how bilingual learners compare with English monolingual learners on two English spelling outcomes: real-word spelling and pseudo-word spelling. Eighteen studies published in peer-reviewed journals between 1990 and 2014 were retrieved. The study-level variables and characteristics (e.g. sample size, study design and research instruments) were coded, and 29 independent effect sizes across the 18 retrieved studies were analysed. We found that bilinguals outperformed monolinguals on real-word spelling overall and more so in early grades, but monolinguals outperformed bilinguals on pseudo-word spelling. Further, bilinguals at risk for reading difficulties did better on real-word spelling than monolinguals at risk for reading difficulties. Having investigated systematic sources of variability in effect sizes, we conclude that in comparison with their monolingual peers, bilingual learners, especially those from alphabetic L1 backgrounds, are able to master constrained skills, such as English spelling, in the current instructional context. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

NASA Technical Reports Server (NTRS)

Brown, A. M.

1998-01-01

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

Effects of pre-analytical variables on flow cytometric diagnosis of canine lymphoma: A retrospective study (2009-2015).

PubMed

Comazzi, S; Cozzi, M; Bernardi, S; Zanella, D R; Aresu, L; Stefanello, D; Marconato, L; Martini, V

2018-02-01

Flow cytometry (FC) is increasingly being used for immunophenotyping and staging of canine lymphoma. The aim of this retrospective study was to assess pre-analytical variables that might influence the diagnostic utility of FC of lymph node (LN) fine needle aspirate (FNA) specimens from dogs with lymphoproliferative diseases. The study included 987 cases with LN FNA specimens sent for immunophenotyping that were submitted to a diagnostic laboratory in Italy from 2009 to 2015. Cases were grouped into 'diagnostic' and 'non-diagnostic'. Pre-analytical factors analysed by univariate and multivariate analyses were animal-related factors (breed, age, sex, size), operator-related factors (year, season, shipping method, submitting veterinarian) and sample-related factors (type of sample material, cellular concentration, cytological smears, artefacts). The submitting veterinarian, sample material, sample cellularity and artefacts affected the likelihood of having a diagnostic sample. The availability of specimens from different sites and of cytological smears increased the odds of obtaining a diagnostic result. Major artefacts affecting diagnostic utility included poor cellularity and the presence of dead cells. Flow cytometry on LN FNA samples yielded conclusive results in more than 90% of cases with adequate sample quality and sampling conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Physicochemical Characterization of Capstone Depleted Uranium Aerosols II: Particle Size Distributions as a Function of Time

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

Cheng, Yung-Sung; Kenoyer, Judson L.; Guilmette, Raymond A.

2009-03-01

The Capstone Depleted Uranium (DU) Aerosol Study, which generated and characterized aerosols containing depleted uranium from perforation of armored vehicles with large-caliber DU penetrators, incorporated a sampling protocol to evaluated particle size distributions. Aerosol particle size distribution is an important parameter that influences aerosol transport and deposition processes as well as the dosimetry of the inhaled particles. These aerosols were collected on cascade impactor substrates using a pre-established time sequence following the firing event to analyze the uranium concentration and particle size of the aerosols as a function of time. The impactor substrates were analyzed using beta spectrometry, and themore » derived uranium content of each served as input to the evaluation of particle size distributions. Activity median aerodynamic diameters (AMADs) of the particle size distributions were evaluated using unimodal and bimodal models. The particle size data from the impactor measurements was quite variable. Most size distributions measured in the test based on activity had bimodal size distributions with a small particle size mode in the range of between 0.2 and 1.2 um and a large size mode between 2 and 15 um. In general, the evolution of particle size over time showed an overall decrease of average particle size from AMADs of 5 to 10 um shortly after perforation to around 1 um at the end of the 2-hr sampling period. The AMADs generally decreased over time because of settling. Additionally, the median diameter of the larger size mode decreased with time. These results were used to estimate the dosimetry of inhaled DU particles.« less

The predictors of chemistry achievement of 12th grade students in secondary schools in the United Arab Emirates

NASA Astrophysics Data System (ADS)

Khalaf, Ali Khalfan

2000-10-01

The purpose of this study is to explore variables related to chemistry achievement of 12th grade science students in the United Arab Emirates (UAE). The focus is to identify student, teacher, and school variables that predict chemistry achievement. The analysis sample included 204 males and 252 females in 66 classes in 60 schools from 10 districts or bureaus of education in the UAE. Thirty-two male and 33 female chemistry teachers and 60 school principals were included. The Khalaf Chemistry Achievement Test, GALT, the Student Questionnaire, Teacher Questionnaire, and School Information Questionnaire were administered. Descriptive statistics, correlations, analyses of variance, factor analysis, and stepwise multiple linear regression analyses were done. The results indicate that demographic, home environment, prior knowledge, scholastic ability, attitudes and perceptions related to chemistry and science, and student perception of instructional practices variables correlated with student chemistry achievement. The amount of help teachers received from the supervisor, class size, and courses in geology were teacher variables that correlated with class chemistry achievement. Nine school variables involving school, division, and class sizes correlated with school chemistry achievement. Analyses of variance revealed significant interaction effects: district by school size and district by student gender. In two districts, students in small schools achieved better than those in large schools. Generally female students achieved equal to or better than males. Three factors from the factor analysis: School Size, Prior Student Achievement, and Student Perception of Teacher Effectiveness, correlated with school chemistry achievement. The results of the multiple linear regression indicated that the factors of Prior Student Achievement, Student Perception of Teacher Effectiveness, and Teacher Experience and Expertise accounted for 45% of the variance in school chemistry achievement. Results indicate that the strongest predictors of chemistry achievement are prior achievement in science, Arabic language, and mathematics; student perception of teacher effectiveness; and teacher experience and expertise. Females tend to achieve better in chemistry than males. No nationality differences were found and the relationship of school size to chemistry achievement was inconclusive. Recommendations related to chemistry and science are presented. These include curriculum, school practice, teacher professional development, and future research.

Soil Sampling Techniques For Alabama Grain Fields

NASA Technical Reports Server (NTRS)

Thompson, A. N.; Shaw, J. N.; Mask, P. L.; Touchton, J. T.; Rickman, D.

2003-01-01

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations.

PubMed

Che, W W; Frey, H Christopher; Lau, Alexis K H

2016-08-16

A sequential measurement method is demonstrated for quantifying the variability in exposure concentration during public transportation. This method was applied in Hong Kong by measuring PM2.5 and CO concentrations along a route connecting 13 transportation-related microenvironments within 3-4 h. The study design takes into account ventilation, proximity to local sources, area-wide air quality, and meteorological conditions. Portable instruments were compacted into a backpack to facilitate measurement under crowded transportation conditions and to quantify personal exposure by sampling at nose level. The route included stops next to three roadside monitors to enable comparison of fixed site and exposure concentrations. PM2.5 exposure concentrations were correlated with the roadside monitors, despite differences in averaging time, detection method, and sampling location. Although highly correlated in temporal trend, PM2.5 concentrations varied significantly among microenvironments, with mean concentration ratios versus roadside monitor ranging from 0.5 for MTR train to 1.3 for bus terminal. Measured inter-run variability provides insight regarding the sample size needed to discriminate between microenvironments with increased statistical significance. The study results illustrate the utility of sequential measurement of microenvironments and policy-relevant insights for exposure mitigation and management.

Non-lethal sampling of walleye for stable isotope analysis: a comparison of three tissues

USGS Publications Warehouse

Chipps, Steven R.; VanDeHey, J.A.; Fincel, M.J.

2012-01-01

Stable isotope analysis of fishes is often performed using muscle or organ tissues that require sacrificing animals. Non-lethal sampling provides an alternative for evaluating isotopic composition for species of concern or individuals of exceptional value. Stable isotope values of white muscle (lethal) were compared with those from fins and scales (non-lethal) in walleye, Sander vitreus (Mitchill), from multiple systems, size classes and across a range of isotopic values. Isotopic variability was also compared among populations to determine the potential of non-lethal tissues for diet-variability analyses. Muscle-derived isotope values were enriched compared with fins and depleted relative to scales. A split-sample validation technique and linear regression found that isotopic composition of walleye fins and scales was significantly related to that in muscle tissue for both δ13C and δ15N (r2 = 0.79–0.93). However, isotopic variability was significantly different between tissue types in two of six populations for δ15N and three of six populations for δ13C. Although species and population specific, these findings indicate that isotopic measures obtained from non-lethal tissues are indicative of those obtained from muscle.

Portfolio of automated trading systems: complexity and learning set size issues.

PubMed

Raudys, Sarunas

2013-03-01

In this paper, we consider using profit/loss histories of multiple automated trading systems (ATSs) as N input variables in portfolio management. By means of multivariate statistical analysis and simulation studies, we analyze the influences of sample size (L) and input dimensionality on the accuracy of determining the portfolio weights. We find that degradation in portfolio performance due to inexact estimation of N means and N(N - 1)/2 correlations is proportional to N/L; however, estimation of N variances does not worsen the result. To reduce unhelpful sample size/dimensionality effects, we perform a clustering of N time series and split them into a small number of blocks. Each block is composed of mutually correlated ATSs. It generates an expert trading agent based on a nontrainable 1/N portfolio rule. To increase the diversity of the expert agents, we use training sets of different lengths for clustering. In the output of the portfolio management system, the regularized mean-variance framework-based fusion agent is developed in each walk-forward step of an out-of-sample portfolio validation experiment. Experiments with the real financial data (2003-2012) confirm the effectiveness of the suggested approach.

Repopulation of calibrations with samples from the target site: effect of the size of the calibration.

NASA Astrophysics Data System (ADS)

Guerrero, C.; Zornoza, R.; Gómez, I.; Mataix-Solera, J.; Navarro-Pedreño, J.; Mataix-Beneyto, J.; García-Orenes, F.

2009-04-01

Near infrared (NIR) reflectance spectroscopy offers important advantages because is a non-destructive technique, the pre-treatments needed in samples are minimal, and the spectrum of the sample is obtained in less than 1 minute without the needs of chemical reagents. For these reasons, NIR is a fast and cost-effective method. Moreover, NIR allows the analysis of several constituents or parameters simultaneously from the same spectrum once it is obtained. For this, a needed steep is the development of soil spectral libraries (set of samples analysed and scanned) and calibrations (using multivariate techniques). The calibrations should contain the variability of the target site soils in which the calibration is to be used. Many times this premise is not easy to fulfil, especially in libraries recently developed. A classical way to solve this problem is through the repopulation of libraries and the subsequent recalibration of the models. In this work we studied the changes in the accuracy of the predictions as a consequence of the successive addition of samples to repopulation. In general, calibrations with high number of samples and high diversity are desired. But we hypothesized that calibrations with lower quantities of samples (lower size) will absorb more easily the spectral characteristics of the target site. Thus, we suspect that the size of the calibration (model) that will be repopulated could be important. For this reason we also studied this effect in the accuracy of predictions of the repopulated models. In this study we used those spectra of our library which contained data of soil Kjeldahl Nitrogen (NKj) content (near to 1500 samples). First, those spectra from the target site were removed from the spectral library. Then, different quantities of samples of the library were selected (representing the 5, 10, 25, 50, 75 and 100% of the total library). These samples were used to develop calibrations with different sizes (%) of samples. We used partial least squares regression, and leave-one-out cross validation as methods of calibration. Two methods were used to select the different quantities (size of models) of samples: (1) Based on Characteristics of Spectra (BCS), and (2) Based on NKj Values of Samples (BVS). Both methods tried to select representative samples. Each of the calibrations (containing the 5, 10, 25, 50, 75 or 100% of the total samples of the library) was repopulated with samples from the target site and then recalibrated (by leave-one-out cross validation). This procedure was sequential. In each step, 2 samples from the target site were added to the models, and then recalibrated. This process was repeated successively 10 times, being 20 the total number of samples added. A local model was also created with the 20 samples used for repopulation. The repopulated, non-repopulated and local calibrations were used to predict the NKj content in those samples from the target site not included in repopulations. For the measurement of the accuracy of the predictions, the r2, RMSEP and slopes were calculated comparing predicted with analysed NKj values. This scheme was repeated for each of the four target sites studied. In general, scarce differences can be found between results obtained with BCS and BVS models. We observed that the repopulation of models increased the r2 of the predictions in sites 1 and 3. The repopulation caused scarce changes of the r2 of the predictions in sites 2 and 4, maybe due to the high initial values (using non-repopulated models r2 >0.90). As consequence of repopulation, the RMSEP decreased in all the sites except in site 2, where a very low RMESP was obtained before the repopulation (0.4 g×kg-1). The slopes trended to approximate to 1, but this value was reached only in site 4 and after the repopulation with 20 samples. In sites 3 and 4, accurate predictions were obtained using the local models. Predictions obtained with models using similar size of samples (similar %) were averaged with the aim to describe the main patterns. The r2 of predictions obtained with models of higher size were not more accurate than those obtained with models of lower size. After repopulation, the RMSEP of predictions using models with lower sizes (5, 10 and 25% of samples of the library) were lower than RMSEP obtained with higher sizes (75 and 100%), indicating that small models can easily integrate the variability of the soils from the target site. The results suggest that calibrations of small size could be repopulated and "converted" in local calibrations. According to this, we can focus most of the efforts in the obtainment of highly accurate analytical values in a reduced set of samples (including some samples from the target sites). The patterns observed here are in opposition with the idea of global models. These results could encourage the expansion of this technique, because very large data based seems not to be needed. Future studies with very different samples will help to confirm the robustness of the patterns observed. Authors acknowledge to "Bancaja-UMH" for the financial support of the project "NIRPROS".

Phenotypic plasticity of life-history traits of a calanoid copepod in a tropical lake: Is the magnitude of thermal plasticity related to thermal variability?

PubMed

Ortega-Mayagoitia, Elizabeth; Hernández-Martínez, Osvaldo; Ciros-Pérez, Jorge

2018-01-01

According to the Climatic Variability Hypothesis [CVH], thermal plasticity should be wider in organisms from temperate environments, but is unlikely to occur in tropical latitudes where temperature fluctuations are narrow. In copepods, food availability has been suggested as the main driver of phenotypic variability in adult size if the range of temperature change is less than 14°C. Leptodiaptomus garciai is a calanoid copepod inhabiting Lake Alchichica, a monomictic, tropical lake in Mexico that experiences regular, narrow temperature fluctuations but wide changes in phytoplankton availability. We investigated whether the seasonal fluctuations of temperature and food produce phenotypic variation in the life-history traits of this tropical species. We sampled L. garciai throughout a year and measured female size, egg size and number, and hatching success, along with temperature and phytoplankton biomass. The amplitude of the plastic responses was estimated with the Phenotypic Plasticity Index. This index was also computed for a published dataset of 84 copepod populations to look if there is a relationship between the amplitude of the phenotypic plasticity of adult size and seasonal change in temperature. The temperature annual range in Lake Alchichica was 3.2°C, whereas phytoplankton abundance varied 17-fold. A strong pattern of thermal plasticity in egg size and adult female size followed the inverse relationship with temperature commonly observed in temperate environments, although its adaptive value was not demonstrated. Egg number, relative reproductive effort and number of nauplii per female were clearly plastic to food availability, allowing organisms to increase their fitness. When comparing copepod species from different latitudes, we found that the magnitude of thermal plasticity of adult size is not related to the range of temperature variation; furthermore, thermal plasticity exists even in environments of limited temperature variation, where the response is more intense compared to temperate populations.

Phenotypic plasticity of life-history traits of a calanoid copepod in a tropical lake: Is the magnitude of thermal plasticity related to thermal variability?

PubMed Central

Hernández-Martínez, Osvaldo; Ciros-Pérez, Jorge

2018-01-01

According to the Climatic Variability Hypothesis [CVH], thermal plasticity should be wider in organisms from temperate environments, but is unlikely to occur in tropical latitudes where temperature fluctuations are narrow. In copepods, food availability has been suggested as the main driver of phenotypic variability in adult size if the range of temperature change is less than 14°C. Leptodiaptomus garciai is a calanoid copepod inhabiting Lake Alchichica, a monomictic, tropical lake in Mexico that experiences regular, narrow temperature fluctuations but wide changes in phytoplankton availability. We investigated whether the seasonal fluctuations of temperature and food produce phenotypic variation in the life-history traits of this tropical species. We sampled L. garciai throughout a year and measured female size, egg size and number, and hatching success, along with temperature and phytoplankton biomass. The amplitude of the plastic responses was estimated with the Phenotypic Plasticity Index. This index was also computed for a published dataset of 84 copepod populations to look if there is a relationship between the amplitude of the phenotypic plasticity of adult size and seasonal change in temperature. The temperature annual range in Lake Alchichica was 3.2°C, whereas phytoplankton abundance varied 17-fold. A strong pattern of thermal plasticity in egg size and adult female size followed the inverse relationship with temperature commonly observed in temperate environments, although its adaptive value was not demonstrated. Egg number, relative reproductive effort and number of nauplii per female were clearly plastic to food availability, allowing organisms to increase their fitness. When comparing copepod species from different latitudes, we found that the magnitude of thermal plasticity of adult size is not related to the range of temperature variation; furthermore, thermal plasticity exists even in environments of limited temperature variation, where the response is more intense compared to temperate populations. PMID:29708999

Design and Field Procedures in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A)

PubMed Central

Kessler, Ronald C.; Avenevoli, Shelli; Costello, E. Jane; Green, Jennifer Greif; Gruber, Michael J.; Heeringa, Steven; Merikangas, Kathleen R.; Pennell, Beth-Ellen; Sampson, Nancy A.; Zaslavsky, Alan M.

2009-01-01

An overview is presented of the design and field procedures of the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A), a US face-to-face household survey of the prevalence and correlates of DSM-IV mental disorders. The survey was based on a dual-frame design that included 904 adolescent residents of the households that participated in the US National Comorbidity Survey Replication (85.9% response rate) and 9,244 adolescent students selected from a nationally representative sample of 320 schools (74.7% response rate). After expositing the logic of dual-frame designs, comparisons are presented of sample and population distributions on Census socio-demographic variables and, in the school sample, school characteristics. These document only minor differences between the samples and the population. The results of statistical analysis of the bias-efficiency trade-off in weight trimming are then presented. These show that modest trimming meaningfully reduces mean squared error. Analysis of comparative sample efficiency shows that the household sample is more efficient than the school sample, leading to the household sample getting a higher weight relative to its size in the consolidated sample relative to the school sample. Taken together, these results show that the NCS-A is an efficient sample of the target population with good representativeness on a range of socio-demographic and geographic variables. PMID:19507169

Feasibility of Recruiting a Diverse Sample of Men Who Have Sex with Men: Observation from Nanjing, China

PubMed Central

Tang, Weiming; Yang, Haitao; Mahapatra, Tanmay; Huan, Xiping; Yan, Hongjing; Li, Jianjun; Fu, Gengfeng; Zhao, Jinkou; Detels, Roger

2013-01-01

Background Respondent-driven-sampling (RDS) has well been recognized as a method for sampling from most hard-to-reach populations like commercial sex workers, drug users and men who have sex with men. However the feasibility of this sampling strategy in terms of recruiting a diverse spectrum of these hidden populations has not been understood well yet in developing countries. Methods In a cross sectional study in Nanjing city of Jiangsu province of China, 430 MSM were recruited including 9 seeds in 14 weeks of study period using RDS. Information regarding socio-demographic characteristics and sexual risk behavior were collected and testing was done for HIV and syphilis. Duration, completion, participant characteristics and the equilibrium of key factors were used for assessing feasibility of RDS. Homophily of key variables, socio-demographic distribution and social network size were used as the indicators of diversity. Results In the study sample, adjusted HIV and syphilis prevalence were 6.6% and 14.6% respectively. Majority (96.3%) of the participants were recruited by members of their own social network. Although there was a tendency for recruitment within the same self-identified group (homosexuals recruited 60.0% homosexuals), considerable cross-group recruitment (bisexuals recruited 52.3% homosexuals) was also seen. Homophily of the self-identified sexual orientations was 0.111 for homosexuals. Upon completion of the recruitment process, participant characteristics and the equilibrium of key factors indicated that RDS was feasible for sampling MSM in Nanjing. Participants recruited by RDS were found to be diverse after assessing the homophily of key variables in successive waves of recruitment, the proportion of characteristics after reaching equilibrium and the social network size. The observed design effects were nearly the same or even better than the theoretical design effect of 2. Conclusion RDS was found to be an efficient and feasible sampling method for recruiting a diverse sample of MSM in a reasonable time. PMID:24244280

jsc2018m000314_Spinning_Science_Multi-use_Variable-g_Platform_Arrives_at_the_Space_Station-MP4

NASA Image and Video Library

2018-05-09

Spinning Science: Multi-use Variable-g Platform Arrives at the Space Station --- The Multi-use Variable-gravity Platform (MVP) Validation mission will install and test the MVP, a new hardware platform developed and owned by Techshot Inc., on the International Space Station (ISS). Though the MVP is designed for research with many different kinds of organisms and cell types, this validation mission will focus on Drosophila melanogaster, more commonly known as the fruit fly. This platform will be especially important for fruit fly research, as it will allow researchers to study larger sample sizes of Drosophila melanogaster than in other previous hardware utilizing centrifuges and it will be able to support fly colonies for multiple generations.

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

Indexing the relative abundance of age-0 white sturgeons in an impoundment of the lower Columbia River from highly skewed trawling data

USGS Publications Warehouse

Counihan, T.D.; Miller, Allen I.; Parsley, M.J.

1999-01-01

The development of recruitment monitoring programs for age-0 white sturgeons Acipenser transmontanus is complicated by the statistical properties of catch-per-unit-effort (CPUE) data. We found that age-0 CPUE distributions from bottom trawl surveys violated assumptions of statistical procedures based on normal probability theory. Further, no single data transformation uniformly satisfied these assumptions because CPUE distribution properties varied with the sample mean (??(CPUE)). Given these analytic problems, we propose that an additional index of age-0 white sturgeon relative abundance, the proportion of positive tows (Ep), be used to estimate sample sizes before conducting age-0 recruitment surveys and to evaluate statistical hypothesis tests comparing the relative abundance of age-0 white sturgeons among years. Monte Carlo simulations indicated that Ep was consistently more precise than ??(CPUE), and because Ep is binomially rather than normally distributed, surveys can be planned and analyzed without violating the assumptions of procedures based on normal probability theory. However, we show that Ep may underestimate changes in relative abundance at high levels and confound our ability to quantify responses to management actions if relative abundance is consistently high. If data suggest that most samples will contain age-0 white sturgeons, estimators of relative abundance other than Ep should be considered. Because Ep may also obscure correlations to climatic and hydrologic variables if high abundance levels are present in time series data, we recommend ??(CPUE) be used to describe relations to environmental variables. The use of both Ep and ??(CPUE) will facilitate the evaluation of hypothesis tests comparing relative abundance levels and correlations to variables affecting age-0 recruitment. Estimated sample sizes for surveys should therefore be based on detecting predetermined differences in Ep, but data necessary to calculate ??(CPUE) should also be collected.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Interpreting survival data from clinical trials of surgery versus stereotactic body radiation therapy in operable Stage I non-small cell lung cancer patients.

PubMed

Samson, Pamela; Keogan, Kathleen; Crabtree, Traves; Colditz, Graham; Broderick, Stephen; Puri, Varun; Meyers, Bryan

2017-01-01

To identify the variability of short- and long-term survival outcomes among closed Phase III randomized controlled trials with small sample sizes comparing SBRT (stereotactic body radiation therapy) and surgical resection in operable clinical Stage I non-small cell lung cancer (NSCLC) patients. Clinical Stage I NSCLC patients who underwent surgery at our institution meeting the inclusion/exclusion criteria for STARS (Randomized Study to Compare CyberKnife to Surgical Resection in Stage I Non-small Cell Lung Cancer), ROSEL (Trial of Either Surgery or Stereotactic Radiotherapy for Early Stage (IA) Lung Cancer), or both were identified. Bootstrapping analysis provided 10,000 iterations to depict 30-day mortality and three-year overall survival (OS) in cohorts of 16 patients (to simulate the STARS surgical arm), 27 patients (to simulate the pooled surgical arms of STARS and ROSEL), and 515 (to simulate the goal accrual for the surgical arm of STARS). From 2000 to 2012, 749/873 (86%) of clinical Stage I NSCLC patients who underwent resection were eligible for STARS only, ROSEL only, or both studies. When patients eligible for STARS only were repeatedly sampled with a cohort size of 16, the 3-year OS rates ranged from 27 to 100%, and 30-day mortality varied from 0 to 25%. When patients eligible for ROSEL or for both STARS and ROSEL underwent bootstrapping with n=27, the 3-year OS ranged from 46 to 100%, while 30-day mortality varied from 0 to 15%. Finally, when patients eligible for STARS were repeatedly sampled in groups of 515, 3-year OS narrowed to 70-85%, with 30-day mortality varying from 0 to 4%. Short- and long-term survival outcomes from trials with small sample sizes are extremely variable and unreliable for extrapolation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Mock juror sampling issues in jury simulation research: A meta-analysis.

PubMed

Bornstein, Brian H; Golding, Jonathan M; Neuschatz, Jeffrey; Kimbrough, Christopher; Reed, Krystia; Magyarics, Casey; Luecht, Katherine

2017-02-01

The advantages and disadvantages of jury simulation research have often been debated in the literature. Critics chiefly argue that jury simulations lack verisimilitude, particularly through their use of student mock jurors, and that this limits the generalizabilty of the findings. In the present article, the question of sample differences (student v. nonstudent) in jury research was meta-analyzed for 6 dependent variables: 3 criminal (guilty verdicts, culpability, and sentencing) and 3 civil (liability verdicts, continuous liability, and damages). In total, 53 studies (N = 17,716) were included in the analysis (40 criminal and 13 civil). The results revealed that guilty verdicts, culpability ratings, and damage awards did not vary with sample. Furthermore, the variables that revealed significant or marginally significant differences, sentencing and liability judgments, had small or contradictory effect sizes (e.g., effects on dichotomous and continuous liability judgments were in opposite directions). In addition, with the exception of trial presentation medium, moderator effects were small and inconsistent. These results may help to alleviate concerns regarding the use of student samples in jury simulation research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Phylogenetic analysis of Bolivian bat trypanosomes of the subgenus schizotrypanum based on cytochrome B sequence and minicircle analyses.

PubMed

García, Lineth; Ortiz, Sylvia; Osorio, Gonzalo; Torrico, Mary Cruz; Torrico, Faustino; Solari, Aldo

2012-01-01

The aim of this study was to establish the phylogenetic relationships of trypanosomes present in blood samples of Bolivian Carollia bats. Eighteen cloned stocks were isolated from 115 bats belonging to Carollia perspicillata (Phyllostomidae) from three Amazonian areas of the Chapare Province of Bolivia and studied by xenodiagnosis using the vectors Rhodnius robustus and Triatoma infestans (Trypanosoma cruzi marenkellei) or haemoculture (Trypanosoma dionisii). The PCR DNA amplified was analyzed by nucleotide sequences of maxicircles encoding cytochrome b and by means of the molecular size of hyper variable regions of minicircles. Ten samples were classified as Trypanosoma cruzi marinkellei and 8 samples as Trypanosoma dionisii. The two species have a different molecular size profile with respect to the amplified regions of minicircles and also with respect to Trypanosoma cruzi and Trypanosoma rangeli used for comparative purpose. We conclude the presence of two species of bat trypanosomes in these samples, which can clearly be identified by the methods used in this study. The presence of these trypanosomes in Amazonian bats is discussed.

Phylogenetic Analysis of Bolivian Bat Trypanosomes of the Subgenus Schizotrypanum Based on Cytochrome b Sequence and Minicircle Analyses

PubMed Central

García, Lineth; Ortiz, Sylvia; Osorio, Gonzalo; Torrico, Mary Cruz; Torrico, Faustino; Solari, Aldo

2012-01-01

The aim of this study was to establish the phylogenetic relationships of trypanosomes present in blood samples of Bolivian Carollia bats. Eighteen cloned stocks were isolated from 115 bats belonging to Carollia perspicillata (Phyllostomidae) from three Amazonian areas of the Chapare Province of Bolivia and studied by xenodiagnosis using the vectors Rhodnius robustus and Triatoma infestans (Trypanosoma cruzi marenkellei) or haemoculture (Trypanosoma dionisii). The PCR DNA amplified was analyzed by nucleotide sequences of maxicircles encoding cytochrome b and by means of the molecular size of hyper variable regions of minicircles. Ten samples were classified as Trypanosoma cruzi marinkellei and 8 samples as Trypanosoma dionisii. The two species have a different molecular size profile with respect to the amplified regions of minicircles and also with respect to Trypanosoma cruzi and Trypanosoma rangeli used for comparative purpose. We conclude the presence of two species of bat trypanosomes in these samples, which can clearly be identified by the methods used in this study. The presence of these trypanosomes in Amazonian bats is discussed. PMID:22590570

A comparison of exact tests for trend with binary endpoints using Bartholomew's statistic.

PubMed

Consiglio, J D; Shan, G; Wilding, G E

2014-01-01

Tests for trend are important in a number of scientific fields when trends associated with binary variables are of interest. Implementing the standard Cochran-Armitage trend test requires an arbitrary choice of scores assigned to represent the grouping variable. Bartholomew proposed a test for qualitatively ordered samples using asymptotic critical values, but type I error control can be problematic in finite samples. To our knowledge, use of the exact probability distribution has not been explored, and we study its use in the present paper. Specifically we consider an approach based on conditioning on both sets of marginal totals and three unconditional approaches where only the marginal totals corresponding to the group sample sizes are treated as fixed. While slightly conservative, all four tests are guaranteed to have actual type I error rates below the nominal level. The unconditional tests are found to exhibit far less conservatism than the conditional test and thereby gain a power advantage.

Reproductive traits of tropical deep-water pandalid shrimps ( Heterocarpus ensifer) from the SW Gulf of Mexico

NASA Astrophysics Data System (ADS)

Briones-Fourzán, Patricia; Barradas-Ortíz, Cecilia; Negrete-Soto, Fernando; Lozano-Álvarez, Enrique

2010-08-01

Heterocarpus ensifer is a tropical deep-water pandalid shrimp whose reproductive features are poorly known. We examined reproductive traits of a population of H. ensifer inhabiting the continental slope (311-715 m in depth) off the Yucatan Peninsula, Mexico (SW Gulf of Mexico). Size range of the total sample ( n=816) was 10.4-38.9 mm carapace length. Females grow larger than males, but both sexes mature at 57% of their maximum theoretical size and at ˜30% of their total lifespan. Among adult females, the proportion of ovigerous females was high in all seasons, indicating year-round reproduction. Most females carrying embryos in advanced stages of development had ovaries in advanced stages of maturation, indicating production of successive spawns. In the autumn, however, the proportion of ovigerous females and the condition index of these females were lower compared to other seasons. This pattern potentially reflects a reduction in food resources following the summer minimum in particulate organic carbon flux to the deep benthos, as reported in previous studies. Spawns consisting of large numbers (16024±5644, mean±SD) of small eggs (0.045±0.009 mm 3) are consistent with extended planktotrophic larval development, an uncommon feature in deep-water carideans. Egg number increased as a power function of female size but with substantial variability, and egg size varied widely within and between females. There was no apparent trade-off between egg number and egg size and neither of these two variables was influenced by female condition. These results indicate iteroparity and a high and variable reproductive effort, reflecting a reproductive strategy developed to compensate for high larval mortality. The present study provides a baseline to compare reproductive traits between Atlantic populations of this tropical deep-water pandalid.

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

USGS Publications Warehouse

Perles, Stephanie J.; Wagner, Tyler; Irwin, Brian J.; Manning, Douglas R.; Callahan, Kristina K.; Marshall, Matthew R.

2014-01-01

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of theVital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year−1 for all indicators and is appropriate for detecting a 1 % trend·year−1 in most indicators.

Multidrug resistance among new tuberculosis cases: detecting local variation through lot quality-assurance sampling.

PubMed

Hedt, Bethany Lynn; van Leth, Frank; Zignol, Matteo; Cobelens, Frank; van Gemert, Wayne; Nhung, Nguyen Viet; Lyepshina, Svitlana; Egwaga, Saidi; Cohen, Ted

2012-03-01

Current methodology for multidrug-resistant tuberculosis (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored 3 classification systems- two-way static, three-way static, and three-way truncated sequential sampling-at 2 sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired.

The Relationship between Baseline Drinking Status, Peer Motivational Interviewing Microskills, and Drinking Outcomes in a Brief Alcohol Intervention for Matriculating College Students: A Replication

ERIC Educational Resources Information Center

Tollison, Sean J.; Mastroleo, Nadine R.; Mallett, Kimberly A.; Witkiewitz, Katie; Lee, Christine M.; Ray, Anne E.; Larimer, Mary E.

2013-01-01

The purpose of this study was to replicate and extend previous findings (Tollison et al., 2008) on the association between peer facilitator adherence to motivational interviewing (MI) microskills and college student drinking behavior. This study used a larger sample size, multiple follow-up time-points, and latent variable analyses allowing for…

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.

Needs and Challenges of Daily Life for People with Down Syndrome Residing in the City of Rome, Italy

ERIC Educational Resources Information Center

Bertoli, M.; Biasini, G.; Calignano, M. T.; Celani, G.; De Grossi, G.; Digilio, M. C.; Fermariello, C. C.; Loffredo, G.; Luchino, F.; Marchese, A.; Mazotti, S.; Menghi, B.; Razzano, C.; Tiano, C.; Zambon Hobart, A.; Zampino, G.; Zuccala, G.

2011-01-01

Background: Population-based surveys on the quality of life of people with Down syndrome (DS) are difficult to perform because of ethical and legal policies regarding privacy and confidential information, but they are essential for service planning. Little is known about the sample size and variability of quality of life of people with DS living…

Risk and Protective Factors of Internet Addiction: A Meta-Analysis of Empirical Studies in Korea

PubMed Central

Koo, Hoon Jung

2014-01-01

Purpose A meta-analysis of empirical studies performed in Korea was conducted to systematically investigate the associations between the indices of Internet addiction (IA) and psychosocial variables. Materials and Methods Systematic literature searches were carried out using the Korean Studies Information Service System, Research Information Sharing Service, Science Direct, Google Scholar, and references in review articles. The key words were Internet addiction, (Internet) game addiction, and pathological, problematic, and excessive Internet use. Only original research papers using Korean samples published from 1999 to 2012 and officially reviewed by peers were included for analysis. Ninety-five studies meeting the inclusion criteria were identified. Results The magnitude of the overall effect size of the intrapersonal variables associated with internet addiction was significantly higher than that of interpersonal variables. Specifically, IA demonstrated a medium to strong association with "escape from self" and "self-identity" as self-related variables. "Attention problem", "self-control", and "emotional regulation" as control and regulation-relation variables; "addiction and absorption traits" as temperament variables; "anger" and "aggression" as emotion and mood and variables; "negative stress coping" as coping variables were also associated with comparably larger effect sizes. Contrary to our expectation, the magnitude of the correlations between relational ability and quality, parental relationships and family functionality, and IA were found to be small. The strength of the association between IA and the risk and protective factors was found to be higher in younger age groups. Conclusion The findings highlight a need for closer examination of psychosocial factors, especially intrapersonal variables when assessing high-risk individuals and designing intervention strategies for both general IA and Internet game addiction. PMID:25323910

Nest size is predicted by female identity and the local environment in the blue tit (Cyanistes caeruleus), but is not related to the nest size of the genetic or foster mother

PubMed Central

Parker, Timothy H.; Griffith, Simon C.

2018-01-01

The potential for animals to respond to changing climates has sparked interest in intraspecific variation in avian nest structure since this may influence nest microclimate and protect eggs and offspring from inclement weather. However, there have been relatively few large-scale attempts to examine variation in nests or the determinates of individual variation in nest structure within populations. Using a set of mostly pre-registered analyses, we studied potential predictors of variation in the size of a large sample (803) of blue tit (Cyanistes caeruleus) nests across three breeding seasons at Wytham Woods, UK. While our pre-registered analyses found that individual females built very similar nests across years, there was no evidence in follow-up (post hoc) analyses that their nest size correlated to that of their genetic mother or, in a cross-fostering experiment, to the nest where they were reared. In further pre-registered analyses, spatial environmental variability explained nest size variability at relatively broad spatial scales, and especially strongly at the scale of individual nest boxes. Our study indicates that nest structure is a characteristic of individuals, but is not strongly heritable, indicating that it will not respond rapidly to selection. Explaining the within-individual and within-location repeatability we observed requires further study. PMID:29765658

Overweight/obesity is associated with food choices related to rice and beans, colors of salads, and portion size among consumers at a restaurant serving buffet-by-weight in Brazil.

PubMed

Rodrigues, Alline Gouvea Martins; Proença, Rossana Pacheco da Costa; Calvo, Maria Cristina Marino; Fiates, Giovanna Medeiros Rataichesck

2012-10-01

The present study investigated the prevalence of overweight/obesity and its relationship with behavioral and food choice characteristics among consumers at a restaurant serving buffet-by-weight in the city of Florianopolis, southern Brazil, during lunch time. An analytical cross-sectional survey of 675 consumers aged 16-81 years was conducted. The measures included anthropometric, socio-demographic, and behavioral characteristics, as well as portion size and a photographic record of the plate chosen by the consumer. The results indicated a prevalence of overweight/obesity in the sample of 33.8%. Overall, after an adjustment for other variables (sex, age, schooling, marital status, and food choice variables), overweight/obesity was positively associated with not choosing rice and beans (PR=1.11) and larger portion sizes (PR=1.08 for a portion size of 347-462 g and PR=1.16 for a portion size of 463 g or more). Moreover, choosing 1-2 colors of salads showed a positive association when compared with choosing 3 or more colors of salads (PR=1.06). Efforts in helping consumers make healthier food choices when eating out and thereby possibly reduce weight gain should address those aspects along with socio-demographic factors. Copyright © 2012 Elsevier Ltd. All rights reserved.

The enigmatic molar from Gondolin, South Africa: implications for Paranthropus paleobiology.

PubMed

Grine, Frederick E; Jacobs, Rachel L; Reed, Kaye E; Plavcan, J Michael

2012-10-01

The specific attribution of the large hominin M(2) (GDA-2) from Gondolin has significant implications for the paleobiology of Paranthropus. If it is a specimen of Paranthropus robustus it impacts that species' size range, and if it belongs to Paranthropus boisei it has important biogeographic implications. We evaluate crown size, cusp proportions and the likelihood of encountering a large-bodied mammal species in both East and South Africa in the Early Pleistocene. The tooth falls well outside the P. robustus sample range, and comfortably within that for penecontemporaneous P. boisei. Analyses of sample range, distribution and variability suggest that it is possible, albeit unlikely to find a M(2) of this size in the current P. robustus sample. However, taphonomic agents - carnivore (particularly leopard) feeding behaviors - have likely skewed the size distribution of the Swartkrans and Drimolen P. robustus assemblage. In particular, assemblages of large-bodied mammals accumulated by leopards typically display high proportions of juveniles and smaller adults. The skew in the P. robustus sample is consistent with this type of assemblage. Morphological evidence in the form of cusp proportions is congruent with GDA-2 representing P. robustus rather than P. boisei. The comparatively small number of large-bodied mammal species common to both South and East Africa in the Early Pleistocene suggests a low probability of encountering an herbivorous australopith in both. Our results are most consistent with the interpretation of the Gondolin molar as a very large specimen of P. robustus. This, in turn, suggests that large, presumptive male, specimens are rare, and that the levels of size variation (sexual dimorphism) previously ascribed to this species are likely to be gross underestimates. Copyright © 2012 Elsevier Ltd. All rights reserved.

Quantifying ADHD classroom inattentiveness, its moderators, and variability: a meta-analytic review.

PubMed

Kofler, Michael J; Rapport, Mark D; Alderson, R Matt

2008-01-01

Most classroom observation studies have documented significant deficiencies in the classroom attention of children with attention-deficit/hyperactivity disorder (ADHD) compared to their typically developing peers. The magnitude of these differences, however, varies considerably and may be influenced by contextual, sampling, diagnostic, and observational differences. Meta-analysis of 23 between-group classroom observation studies using weighted regression, publication bias, goodness of fit, best case, and original metric analyses. Across studies, a large effect size (ES = .73) was found prior to consideration of potential moderators. Weighted regression, best case, and original metric estimation indicate that this effect may be an underestimation of the classroom visual attention deficits of children with ADHD. Several methodological factors-classroom environment, sample characteristics, diagnostic procedures, and observational coding schema-differentially affect observed rates of classroom attentive behavior for children with ADHD and typically developing children. After accounting for these factors, children with ADHD were on-task approximately 75% of the time compared to 88% for their classroom peers (ES = 1.40). Children with ADHD were also more variable in their attentive behavior across studies. The present study confirmed that children with ADHD exhibit deficient and more variable visual attending to required stimuli in classroom settings and provided an aggregate estimation of the magnitude of these deficits at the group level. It also demonstrated the impact of situational, sampling, diagnostic, and observational variables on observed rates of on-task behavior.

Determination of supplier-to-supplier and lot-to-lot variability in glycation of recombinant human serum albumin expressed in Oryza sativa.

PubMed

Frahm, Grant E; Smith, Daryl G S; Kane, Anita; Lorbetskie, Barry; Cyr, Terry D; Girard, Michel; Johnston, Michael J W

2014-01-01

The use of different expression systems to produce the same recombinant human protein can result in expression-dependent chemical modifications (CMs) leading to variability of structure, stability and immunogenicity. Of particular interest are recombinant human proteins expressed in plant-based systems, which have shown particularly high CM variability. In studies presented here, recombinant human serum albumins (rHSA) produced in Oryza sativa (Asian rice) (OsrHSA) from a number of suppliers have been extensively characterized and compared to plasma-derived HSA (pHSA) and rHSA expressed in yeast (Pichia pastoris and Saccharomyces cerevisiae). The heterogeneity of each sample was evaluated using size exclusion chromatography (SEC), reversed-phase high-performance liquid chromatography (RP-HPLC) and capillary electrophoresis (CE). Modifications of the samples were identified by liquid chromatography-mass spectrometry (LC-MS). The secondary and tertiary structure of the albumin samples were assessed with far U/V circular dichroism spectropolarimetry (far U/V CD) and fluorescence spectroscopy, respectively. Far U/V CD and fluorescence analyses were also used to assess thermal stability and drug binding. High molecular weight aggregates in OsrHSA samples were detected with SEC and supplier-to-supplier variability and, more critically, lot-to-lot variability in one manufactures supplied products were identified. LC-MS analysis identified a greater number of hexose-glycated arginine and lysine residues on OsrHSA compared to pHSA or rHSA expressed in yeast. This analysis also showed supplier-to-supplier and lot-to-lot variability in the degree of glycation at specific lysine and arginine residues for OsrHSA. Both the number of glycated residues and the degree of glycation correlated positively with the quantity of non-monomeric species and the chromatographic profiles of the samples. Tertiary structural changes were observed for most OsrHSA samples which correlated well with the degree of arginine/lysine glycation. The extensive glycation of OsrHSA from multiple suppliers may have further implications for the use of OsrHSA as a therapeutic product.

Assessing residential exposure to urban noise using environmental models: does the size of the local living neighborhood matter?

PubMed

Tenailleau, Quentin M; Bernard, Nadine; Pujol, Sophie; Houot, Hélène; Joly, Daniel; Mauny, Frédéric

2015-01-01

Environmental epidemiological studies rely on the quantification of the exposure level in a surface defined as the subject's exposure area. For residential exposure, this area is often the subject's neighborhood. However, the variability of the size and nature of the neighborhoods makes comparison of the findings across studies difficult. This article examines the impact of the neighborhood's definition on environmental noise exposure levels obtained from four commonly used sampling techniques: address point, façade, buffers, and official zoning. A high-definition noise model, built on a middle-sized French city, has been used to estimate LAeq,24 h exposure in the vicinity of 10,825 residential buildings. Twelve noise exposure indicators have been used to assess inhabitants' exposure. Influence of urban environmental factors was analyzed using multilevel modeling. When the sampled area increases, the average exposure increases (+3.9 dB), whereas the SD decreases (-1.6 dB) (P<0.01). Most of the indicators differ statistically. When comparing indicators from the 50-m and 400-m radius buffers, the assigned LAeq,24 h level varies across buildings from -9.4 to +22.3 dB. This variation is influenced by urban environmental characteristics (P<0.01). On the basis of this study's findings, sampling technique, neighborhood size, and environmental composition should be carefully considered in further exposure studies.

Salix transect of Europe: variation in ploidy and genome size in willow-associated common nettle, Urtica dioica L. sens. lat., from Greece to arctic Norway

PubMed Central

Hidalgo, Oriane; Pellicer, Jaume; Percy, Diana; Leitch, Ilia J.

2016-01-01

Abstract Background The common stinging nettle, Urtica dioica L. sensu lato, is an invertebrate "superhost", its clonal patches maintaining large populations of insects and molluscs. It is extremely widespread in Europe and highly variable, and two ploidy levels (diploid and tetraploid) are known. However, geographical patterns in cytotype variation require further study. New information We assembled a collection of nettles in conjunction with a transect of Europe from the Aegean to Arctic Norway (primarily conducted to examine the diversity of Salix and Salix-associated insects). Using flow cytometry to measure genome size, our sample of 29 plants reveals 5 diploids and 24 tetraploids. Two diploids were found in SE Europe (Bulgaria and Romania) and three diploids in S. Finland. More detailed cytotype surveys in these regions are suggested. The tetraploid genome size (2C value) varied between accessions from 2.36 to 2.59 pg. The diploids varied from 1.31 to 1.35 pg per 2C nucleus, equivalent to a haploid genome size of c. 650 Mbp. Within the tetraploids, we find that the most northerly samples (from N. Finland and arctic Norway) have a generally higher genome size. This is possibly indicative of a distinct population in this region. PMID:27932918

Salix transect of Europe: variation in ploidy and genome size in willow-associated common nettle, Urtica dioica L. sens. lat., from Greece to arctic Norway.

PubMed

Cronk, Quentin; Hidalgo, Oriane; Pellicer, Jaume; Percy, Diana; Leitch, Ilia J

2016-01-01

The common stinging nettle, Urtica dioica L. sensu lato, is an invertebrate "superhost", its clonal patches maintaining large populations of insects and molluscs. It is extremely widespread in Europe and highly variable, and two ploidy levels (diploid and tetraploid) are known. However, geographical patterns in cytotype variation require further study. We assembled a collection of nettles in conjunction with a transect of Europe from the Aegean to Arctic Norway (primarily conducted to examine the diversity of Salix and Salix -associated insects). Using flow cytometry to measure genome size, our sample of 29 plants reveals 5 diploids and 24 tetraploids. Two diploids were found in SE Europe (Bulgaria and Romania) and three diploids in S. Finland. More detailed cytotype surveys in these regions are suggested. The tetraploid genome size (2C value) varied between accessions from 2.36 to 2.59 pg. The diploids varied from 1.31 to 1.35 pg per 2C nucleus, equivalent to a haploid genome size of c. 650 Mbp. Within the tetraploids, we find that the most northerly samples (from N. Finland and arctic Norway) have a generally higher genome size. This is possibly indicative of a distinct population in this region.

The use of mini-samples in palaeomagnetism

NASA Astrophysics Data System (ADS)

Böhnel, Harald; Michalk, Daniel; Nowaczyk, Norbert; Naranjo, Gildardo Gonzalez

2009-10-01

Rock cores of ~25 mm diameter are widely used in palaeomagnetism. Occasionally smaller diameters have been used as well which represents distinct advantages in terms of throughput, weight of equipment and core collections. How their orientation precision compares to 25 mm cores, however, has not been evaluated in detail before. Here we compare the site mean directions and their statistical parameters for 12 lava flows sampled with 25 mm cores (standard samples, typically 8 cores per site) and with 12 mm drill cores (mini-samples, typically 14 cores per site). The site-mean directions for both sample sizes appear to be indistinguishable in most cases. For the mini-samples, site dispersion parameters k on average are slightly lower than for the standard samples reflecting their larger orienting and measurement errors. Applying the Wilcoxon signed-rank test the probability that k or α95 have the same distribution for both sizes is acceptable only at the 17.4 or 66.3 per cent level, respectively. The larger mini-core numbers per site appears to outweigh the lower k values yielding also slightly smaller confidence limits α95. Further, both k and α95 are less variable for mini-samples than for standard size samples. This is interpreted also to result from the larger number of mini-samples per site, which better averages out the detrimental effect of undetected abnormal remanence directions. Sampling of volcanic rocks with mini-samples therefore does not present a disadvantage in terms of the overall obtainable uncertainty of site mean directions. Apart from this, mini-samples do present clear advantages during the field work, as about twice the number of drill cores can be recovered compared to 25 mm cores, and the sampled rock unit is then more widely covered, which reduces the contribution of natural random errors produced, for example, by fractures, cooling joints, and palaeofield inhomogeneities. Mini-samples may be processed faster in the laboratory, which is of particular advantage when carrying out palaeointensity experiments.

Laboratory evaluation of a protocol for personal sampling of airborne particles in welding and allied processes.

PubMed

Chung, K Y; Carter, G J; Stancliffe, J D

1999-02-01

A new European/International Standard (ISOprEN 10882-1) on the sampling of airborne particulates generated during welding and allied processes has been proposed. The use of a number of samplers and sampling procedures is allowable within the defined protocol. The influence of these variables on welding fume exposures measured during welding and grinding of stainless and mild steel using the gas metal arc (GMA) and flux-cored arc (FCA) and GMA welding of aluminium has been examined. Results show that use of any of the samplers will not give significantly different measured exposures. The effect on exposure measurement of placing the samplers on either side of the head was variable; consequently, sampling position cannot be meaningfully defined. All samplers collected significant amounts of grinding dust. Therefore, gravimetric determination of welding fume exposure in atmospheres containing grinding dust will be inaccurate. The use of a new size selective sampler can, to some extent, be used to give a more accurate estimate of exposure. The reliability of fume analysis data of welding consumables has caused concern; and the reason for differences that existed between the material safety data sheet and the analysis of fume samples collected requires further investigation.

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Experimental Design in Clinical 'Omics Biomarker Discovery.

PubMed

Forshed, Jenny

2017-11-03

This tutorial highlights some issues in the experimental design of clinical 'omics biomarker discovery, how to avoid bias and get as true quantities as possible from biochemical analyses, and how to select samples to improve the chance of answering the clinical question at issue. This includes the importance of defining clinical aim and end point, knowing the variability in the results, randomization of samples, sample size, statistical power, and how to avoid confounding factors by including clinical data in the sample selection, that is, how to avoid unpleasant surprises at the point of statistical analysis. The aim of this Tutorial is to help translational clinical and preclinical biomarker candidate research and to improve the validity and potential of future biomarker candidate findings.

Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes

USGS Publications Warehouse

Mollenhauer, Robert; Mouser, Joshua B.; Brewer, Shannon K.

2018-01-01

Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.

Indian Craniometric Variability and Affinities

PubMed Central

Raghavan, Pathmanathan; Bulbeck, David; Pathmanathan, Gayathiri; Rathee, Suresh Kanta

2013-01-01

Recently published craniometric and genetic studies indicate a predominantly indigenous ancestry of Indian populations. We address this issue with a fuller coverage of Indian craniometrics than any done before. We analyse metrical variability within Indian series, Indians' sexual dimorphism, differences between northern and southern Indians, index-based differences of Indian males from other series, and Indians' multivariate affinities. The relationship between a variable's magnitude and its variability is log-linear. This relationship is strengthened by excluding cranial fractions and series with a sample size less than 30. Male crania are typically larger than female crania, but there are also shape differences. Northern Indians differ from southern Indians in various features including narrower orbits and less pronounced medial protrusion of the orbits. Indians resemble Veddas in having small crania and similar cranial shape. Indians' wider geographic affinities lie with “Caucasoid” populations to the northwest, particularly affecting northern Indians. The latter finding is confirmed from shape-based Mahalanobis-D distances calculated for the best sampled male and female series. Demonstration of a distinctive South Asian craniometric profile and the intermediate status of northern Indians between southern Indians and populations northwest of India confirm the predominantly indigenous ancestry of northern and especially southern Indians. PMID:24455409

Evaluation of genetic variability in a small, insular population of spruce grouse

USGS Publications Warehouse

O'Connell, A.F.; Rhymer, Judith; Keppie, D.M.; Svenson, K.L.; Paigan, B.J.

2002-01-01

Using microsatellite markers we determined genetic variability for two populations of spruce grouse in eastern North America, one on a coastal Maine island where breeding habitat is limited and highly fragmented, the other in central New Brunswick (NB), where suitable breeding habitat is generally contiguous across the region. We examined six markers for both populations and all were polymorphic. Although the number of alleles per locus and the proportion of unique alleles were lower in the island population, and probably a result of small sample.size, heterozygosity and a breeding coefficient (Fis) indicated slightly more variability in the island population. Deviation from Hardy-Weinberg equilibrium also was more evident in loci for the mainland population. Several traits previously documented in the island population: relatively long natal dispersal distances, reproductive success, territoriality, adult survival, and longevity support the maintenance of hetrerzygosity, at least in the short-term. Sample collection from two small (500 ha), separate areas in NB, and the predicted importance of immigration density to supplement this population demonstrate the need for behavioral and ecological information when interpreting genetic variation. We discuss the relevance of these issues with respect to genetic variability and viability.

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

Use of care management practices in small- and medium-sized physician groups: do public reporting of physician quality and financial incentives matter?

PubMed

Alexander, Jeffrey A; Maeng, Daniel; Casalino, Lawrence P; Rittenhouse, Diane

2013-04-01

To examine the effect of public reporting (PR) and financial incentives tied to quality performance on the use of care management practices (CMPs) among small- and medium-sized physician groups. Survey data from The National Study of Small and Medium-sized Physician Practices were used. Primary data collection was also conducted to assess community-level PR activities. The final sample included 643 practices engaged in quality reporting; about half of these practices were subject to PR. We used a treatment effects model. The instrumental variables were the community-level variables that capture the level of PR activity in each community in which the practices operate. (1) PR is associated with increased use of CMPs, but the estimate is not statistically significant; (2) financial incentives are associated with greater use of CMPs; (3) practices' awareness/sensitivity to quality reports is positively related to their use of CMPs; and (4) combined PR and financial incentives jointly affect CMP use to a greater degree than either of these factors alone. Small- to medium-sized practices appear to respond to PR and financial incentives by greater use of CMPs. Future research needs to investigate the appropriate mix and type of incentive arrangements and quality reporting. © Health Research and Educational Trust.

Variability of 137Cs inventory at a reference site in west-central Iran.

PubMed

Bazshoushtari, Nasim; Ayoubi, Shamsollah; Abdi, Mohammad Reza; Mohammadi, Mohammad

2016-12-01

137 Cs technique has been widely used for the evaluation rates and patterns of soil erosion and deposition. This technique requires an accurate estimate of the values of 137 Cs inventory at the reference site. This study was conducted to evaluate the variability of the inventory of 137 Cs regarding to the sampling program including sample size, distance and sampling method at a reference site located in vicinity of Fereydan district in Isfahan province, west-central Iran. Two 3 × 8 grids were established comprising large grid (35 m length and 8 m width), and small grid (24 m length and 6 m width). At each grid intersection two soil samples were collected from 0 to 15 cm and 15-30 cm depths, totally 96 soil samples from 48 sampling points. Coefficients of variation for 137 Cs inventory in the soil samples was relatively low (CV = 15%), and the sampling distance and methods used did not significantly affect the 137 Cs inventories across the studied reference site. To obtain a satisfactory estimate of the mean 137 Cs activity in the reference sites, particularly those located in the semiarid regions, it is recommended to collect at least four samples along in a grid pattern 3 m apart. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing readability formula differences with written health information materials: application, results, and recommendations.

PubMed

Wang, Lih-Wern; Miller, Michael J; Schmitt, Michael R; Wen, Frances K

2013-01-01

Readability formulas are often used to guide the development and evaluation of literacy-sensitive written health information. However, readability formula results may vary considerably as a result of differences in software processing algorithms and how each formula is applied. These variations complicate interpretations of reading grade level estimates, particularly without a uniform guideline for applying and interpreting readability formulas. This research sought to (1) identify commonly used readability formulas reported in the health care literature, (2) demonstrate the use of the most commonly used readability formulas on written health information, (3) compare and contrast the differences when applying common readability formulas to identical selections of written health information, and (4) provide recommendations for choosing an appropriate readability formula for written health-related materials to optimize their use. A literature search was conducted to identify the most commonly used readability formulas in health care literature. Each of the identified formulas was subsequently applied to word samples from 15 unique examples of written health information about the topic of depression and its treatment. Readability estimates from common readability formulas were compared based on text sample size, selection, formatting, software type, and/or hand calculations. Recommendations for their use were provided. The Flesch-Kincaid formula was most commonly used (57.42%). Readability formulas demonstrated variability up to 5 reading grade levels on the same text. The Simple Measure of Gobbledygook (SMOG) readability formula performed most consistently. Depending on the text sample size, selection, formatting, software, and/or hand calculations, the individual readability formula estimated up to 6 reading grade levels of variability. The SMOG formula appears best suited for health care applications because of its consistency of results, higher level of expected comprehension, use of more recent validation criteria for determining reading grade level estimates, and simplicity of use. To improve interpretation of readability results, reporting reading grade level estimates from any formula should be accompanied with information about word sample size, location of word sampling in the text, formatting, and method of calculation. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-06-30

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

Prediction of Hematopoietic Stem Cell Transplantation Related Mortality- Lessons Learned from the In-Silico Approach: A European Society for Blood and Marrow Transplantation Acute Leukemia Working Party Data Mining Study.

PubMed

Shouval, Roni; Labopin, Myriam; Unger, Ron; Giebel, Sebastian; Ciceri, Fabio; Schmid, Christoph; Esteve, Jordi; Baron, Frederic; Gorin, Norbert Claude; Savani, Bipin; Shimoni, Avichai; Mohty, Mohamad; Nagler, Arnon

2016-01-01

Models for prediction of allogeneic hematopoietic stem transplantation (HSCT) related mortality partially account for transplant risk. Improving predictive accuracy requires understating of prediction limiting factors, such as the statistical methodology used, number and quality of features collected, or simply the population size. Using an in-silico approach (i.e., iterative computerized simulations), based on machine learning (ML) algorithms, we set out to analyze these factors. A cohort of 25,923 adult acute leukemia patients from the European Society for Blood and Marrow Transplantation (EBMT) registry was analyzed. Predictive objective was non-relapse mortality (NRM) 100 days following HSCT. Thousands of prediction models were developed under varying conditions: increasing sample size, specific subpopulations and an increasing number of variables, which were selected and ranked by separate feature selection algorithms. Depending on the algorithm, predictive performance plateaued on a population size of 6,611-8,814 patients, reaching a maximal area under the receiver operator characteristic curve (AUC) of 0.67. AUCs' of models developed on specific subpopulation ranged from 0.59 to 0.67 for patients in second complete remission and receiving reduced intensity conditioning, respectively. Only 3-5 variables were necessary to achieve near maximal AUCs. The top 3 ranking variables, shared by all algorithms were disease stage, donor type, and conditioning regimen. Our findings empirically demonstrate that with regards to NRM prediction, few variables "carry the weight" and that traditional HSCT data has been "worn out". "Breaking through" the predictive boundaries will likely require additional types of inputs.

Dietary Correlates of Primate Masticatory Muscle Fiber Architecture.

PubMed

Hartstone-Rose, Adam; Deutsch, Ashley R; Leischner, Carissa L; Pastor, Francisco

2018-02-01

Analyses of masticatory muscle architecture-specifically fascicle length (FL; a correlate of muscle stretch and contraction speed) and physiological cross-sectional area (PCSA; a correlate of force)-reveal soft-tissue dietary adaptations. For instance, consumers of large, soft foods are expected to have relatively long FL, while consumers of obdurate foods are expected to have relatively high PCSA. Unfortunately, only a few studies have analyzed these variables across large primate samples-an order of particular interest because it is our own. Previous studies found that, in strepsirrhines, force variables (PCSA and muscle masses; MM) scale with isometry or slight positive allometry, while the body size corrected FL residuals correlate with food sizes. However, a study of platyrrhines using different methods (in which the authors physically cut muscles between fascicles) found very different trends: negative allometry for both the stretch and force variables. Here, we apply the methods used in the strepsirrhine study (chemical dissection of fascicles to ensure full length measurements) to reevaluate these trends in platyrrhines and extend this research to include catarrhines. Our results conform to the previous strepsirrhine trends: there is no evidence of negative allometry in platyrrhines. Rather, in primates broadly and catarrhines specifically, MM and PCSA scale with isometry or positive allometry. When examining size-adjusted variables, it is clear that fascicle lengths (especially those of the temporalis muscle) correlate with diet: species that consume soft, larger, foods have longer masticatory fiber lengths which would allow them to open their jaws to wider gape angles. Anat Rec, 301:311-324, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Shape variation in the human pelvis and limb skeleton: Implications for obstetric adaptation.

PubMed

Kurki, Helen K; Decrausaz, Sarah-Louise

2016-04-01

Under the obstetrical dilemma (OD) hypothesis, selection acts on the human female pelvis to ensure a sufficiently sized obstetric canal for birthing a large-brained, broad shouldered neonate, while bipedal locomotion selects for a narrower and smaller pelvis. Despite this female-specific stabilizing selection, variability of linear dimensions of the pelvic canal and overall size are not reduced in females, suggesting shape may instead be variable among females of a population. Female canal shape has been shown to vary among populations, while male canal shape does not. Within this context, we examine within-population canal shape variation in comparison with that of noncanal aspects of the pelvis and the limbs. Nine skeletal samples (total female n = 101, male n = 117) representing diverse body sizes and shapes were included. Principal components analysis was applied to size-adjusted variables of each skeletal region. A multivariate variance was calculated using the weighted PC scores for all components in each model and F-ratios used to assess differences in within-population variances between sexes and skeletal regions. Within both sexes, multivariate canal shape variance is significantly greater than noncanal pelvis and limb variances, while limb variance is greater than noncanal pelvis variance in some populations. Multivariate shape variation is not consistently different between the sexes in any of the skeletal regions. Diverse selective pressures, including obstetrics, locomotion, load carrying, and others may act on canal shape, as well as genetic drift and plasticity, thus increasing variation in morphospace while protecting obstetric sufficiency. © 2015 Wiley Periodicals, Inc.

The relationship between mother to child calories served and maternal perception of hunger.

PubMed

Stromberg, S E; Janicke, D M

2016-06-01

Research has examined self-serving portions in adults and children and has shown that larger portion size is related to more calories consumed. The present study examines factors that may influence the portion sizes a mother serves her child at a mealtime. The present observational study included a community-based sample of 29 mother-child dyads. Dyads attended a 1-h session in which they shared a meal together. A buffet of food was provided and the mother was asked to serve her child and herself. The amount of food served and consumed by the child was recorded. Main independent variables of interest included maternal body mass index (BMI), child BMI Z-score, and maternal perception of personal and child hunger. The primary dependent variable was the total calories the mother served her child. Regression models and a moderated mediation were used to examine the relation between variables. Calories served to the child was positively associated with calories consumed by the child. Maternal perception of her own hunger was related to her perception of her child's hunger. Furthermore, maternal perception of child hunger explained the relationship between maternal perception of personal hunger and total calories served to the child, although only for obese mothers. Mothers may be serving their children larger portion sizes based on their personal weight and their perception of their child's hunger. To help children obtain or maintain a healthy weight, obesity prevention and intervention programmes should help mothers serve more appropriate serving sizes to their children. © 2015 The British Dietetic Association Ltd.