High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study

PubMed Central

2013-01-01

Background Demographic bottlenecks can severely reduce the genetic variation of a population or a species. Establishing whether low genetic variation is caused by a bottleneck or a constantly low effective number of individuals is important to understand a species’ ecology and evolution, and it has implications for conservation management. Recent studies have evaluated the power of several statistical methods developed to identify bottlenecks. However, the false positive rate, i.e. the rate with which a bottleneck signal is misidentified in demographically stable populations, has received little attention. We analyse this type of error (type I) in forward computer simulations of stable populations having greater than Poisson variance in reproductive success (i.e., variance in family sizes). The assumption of Poisson variance underlies bottleneck tests, yet it is commonly violated in species with high fecundity. Results With large variance in reproductive success (Vk ≥ 40, corresponding to a ratio between effective and census size smaller than 0.1), tests based on allele frequencies, allelic sizes, and DNA sequence polymorphisms (heterozygosity excess, M-ratio, and Tajima’s D test) tend to show erroneous signals of a bottleneck. Similarly, strong evidence of population decline is erroneously detected when ancestral and current population sizes are estimated with the model based method MSVAR. Conclusions Our results suggest caution when interpreting the results of bottleneck tests in species showing high variance in reproductive success. Particularly in species with high fecundity, computer simulations are recommended to confirm the occurrence of a population bottleneck. PMID:24131797

A New Method for Estimating the Effective Population Size from Allele Frequency Changes

PubMed Central

Pollak, Edward

1983-01-01

A new procedure is proposed for estimating the effective population size, given that information is available on changes in frequencies of the alleles at one or more independently segregating loci and the population is observed at two or more separate times. Approximate expressions are obtained for the variances of the new statistic, as well as others, also based on allele frequency changes, that have been discussed in the literature. This analysis indicates that the new statistic will generally have a smaller variance than the others. Estimates of effective population sizes and of the standard errors of the estimates are computed for data on two fly populations that have been discussed in earlier papers. In both cases, there is evidence that the effective population size is very much smaller than the minimum census size of the population. PMID:17246147

Determining Sample Sizes for Precise Contrast Analysis with Heterogeneous Variances

ERIC Educational Resources Information Center

Jan, Show-Li; Shieh, Gwowen

2014-01-01

The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…

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

PubMed Central

Rast, Philippe; Hofer, Scott M.

2014-01-01

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

Reporting Point and Interval Estimates of Effect-Size for Planned Contrasts: Fixed within Effect Analyses of Variance

ERIC Educational Resources Information Center

Robey, Randall R.

2004-01-01

The purpose of this tutorial is threefold: (a) review the state of statistical science regarding effect-sizes, (b) illustrate the importance of effect-sizes for interpreting findings in all forms of research and particularly for results of clinical-outcome research, and (c) demonstrate just how easily a criterion on reporting effect-sizes in…

Differences in the effective population sizes of males and females do not require differences in their distribution of offspring number.

PubMed

Mendez, Fernando L

2017-04-01

Difference in male and female effective population sizes has, at times, been attributed to both sexes having unequal variance in their number of offspring. Such difference is paralleled by the relative effective sizes of autosomes, sex chromosomes, and mitochondrial DNA. I develop a simple framework to calculate the inbreeding effective population sizes for loci with different modes of inheritance. In this framework, I separate the effects due to mating strategy and those due to genetic transmission. I then show that, in addition to differences in the variance in offspring number, skew in the male/female effective sizes can also be caused by family composition. This approach can be used to illustrate the effect of induced behaviors on the relative male and female effective population sizes. In particular, I show the impact of the one-child policy formerly implemented in the People's Republic of China on the relative male and female effective population sizes. Furthermore, I argue that, under some strong constraints on family structure, the concepts of male and female effective population sizes are invalid. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Where do all the maternal effects go? Variation in offspring body size through ontogeny in the live-bearing fish Poecilia parae.

PubMed

Lindholm, Anna K; Hunt, John; Brooks, Robert

2006-12-22

Maternal effects are an important source of adaptive variation, but little is known about how they vary throughout ontogeny. We estimate the contribution of maternal effects, sire genetic and environmental variation to offspring body size from birth until 1 year of age in the live-bearing fish Poecilia parae. In both the sexes, maternal effects on body size were initially high in juveniles, and then declined to zero at sexual maturity. In sons, this was accompanied by a sharp rise in sire genetic variance, consistent with the expression of Y-linked loci affecting male size. In daughters, all variance components decreased with time, consistent with compensatory growth. There were significant negative among-dam correlations between early body size and the timing of sexual maturity in both sons and daughters. However, there was no relationship between early life maternal effects and adult longevity, suggesting that maternal effects, although important early in life, may not always influence late life-history traits.

Meta-Analysis With Complex Research Designs: Dealing With Dependence From Multiple Measures and Multiple Group Comparisons

PubMed Central

Scammacca, Nancy; Roberts, Greg; Stuebing, Karla K.

2013-01-01

Previous research has shown that treating dependent effect sizes as independent inflates the variance of the mean effect size and introduces bias by giving studies with more effect sizes more weight in the meta-analysis. This article summarizes the different approaches to handling dependence that have been advocated by methodologists, some of which are more feasible to implement with education research studies than others. A case study using effect sizes from a recent meta-analysis of reading interventions is presented to compare the results obtained from different approaches to dealing with dependence. Overall, mean effect sizes and variance estimates were found to be similar, but estimates of indexes of heterogeneity varied. Meta-analysts are advised to explore the effect of the method of handling dependence on the heterogeneity estimates before conducting moderator analyses and to choose the approach to dependence that is best suited to their research question and their data set. PMID:25309002

A geometrical optics approach for modeling aperture averaging in free space optical communication applications

NASA Astrophysics Data System (ADS)

Yuksel, Heba; Davis, Christopher C.

2006-09-01

Intensity fluctuations at the receiver in free space optical (FSO) communication links lead to a received power variance that depends on the size of the receiver aperture. Increasing the size of the receiver aperture reduces the power variance. This effect of the receiver size on power variance is called aperture averaging. If there were no aperture size limitation at the receiver, then there would be no turbulence-induced scintillation. In practice, there is always a tradeoff between aperture size, transceiver weight, and potential transceiver agility for pointing, acquisition and tracking (PAT) of FSO communication links. We have developed a geometrical simulation model to predict the aperture averaging factor. This model is used to simulate the aperture averaging effect at given range by using a large number of rays, Gaussian as well as uniformly distributed, propagating through simulated turbulence into a circular receiver of varying aperture size. Turbulence is simulated by filling the propagation path with spherical bubbles of varying sizes and refractive index discontinuities statistically distributed according to various models. For each statistical representation of the atmosphere, the three-dimensional trajectory of each ray is analyzed using geometrical optics. These Monte Carlo techniques have proved capable of assessing the aperture averaging effect, in particular, the quantitative expected reduction in intensity fluctuations with increasing aperture diameter. In addition, beam wander results have demonstrated the range-cubed dependence of mean-squared beam wander. An effective turbulence parameter can also be determined by correlating beam wander behavior with the path length.

Does an uneven sample size distribution across settings matter in cross-classified multilevel modeling? Results of a simulation study.

PubMed

Milliren, Carly E; Evans, Clare R; Richmond, Tracy K; Dunn, Erin C

2018-06-06

Recent advances in multilevel modeling allow for modeling non-hierarchical levels (e.g., youth in non-nested schools and neighborhoods) using cross-classified multilevel models (CCMM). Current practice is to cluster samples from one context (e.g., schools) and utilize the observations however they are distributed from the second context (e.g., neighborhoods). However, it is unknown whether an uneven distribution of sample size across these contexts leads to incorrect estimates of random effects in CCMMs. Using the school and neighborhood data structure in Add Health, we examined the effect of neighborhood sample size imbalance on the estimation of variance parameters in models predicting BMI. We differentially assigned students from a given school to neighborhoods within that school's catchment area using three scenarios of (im)balance. 1000 random datasets were simulated for each of five combinations of school- and neighborhood-level variance and imbalance scenarios, for a total of 15,000 simulated data sets. For each simulation, we calculated 95% CIs for the variance parameters to determine whether the true simulated variance fell within the interval. Across all simulations, the "true" school and neighborhood variance parameters were estimated 93-96% of the time. Only 5% of models failed to capture neighborhood variance; 6% failed to capture school variance. These results suggest that there is no systematic bias in the ability of CCMM to capture the true variance parameters regardless of the distribution of students across neighborhoods. Ongoing efforts to use CCMM are warranted and can proceed without concern for the sample imbalance across contexts. Copyright © 2018 Elsevier Ltd. All rights reserved.

Particle sizes in Saturn's rings from UVIS stellar occultations 1. Variations with ring region

NASA Astrophysics Data System (ADS)

Colwell, J. E.; Esposito, L. W.; Cooney, J. H.

2018-01-01

The Cassini spacecraft's Ultraviolet Imaging Spectrograph (UVIS) includes a high speed photometer (HSP) that has observed stellar occultations by Saturn's rings with a radial resolution of ∼10 m. In the absence of intervening ring material, the time series of measurements by the HSP is described by Poisson statistics in which the variance equals the mean. The finite sizes of the ring particles occulting the star lead to a variance that is larger than the mean due to correlations in the blocking of photons due to finite particle size and due to random variations in the number of individual particles in each measurement area. This effect was first exploited by Showalter and Nicholson (1990) with the stellar occultation observed by Voyager 2. At a given optical depth, a larger excess variance corresponds to larger particles or clumps that results in greater variation of the signal from measurement to measurement. Here we present analysis of the excess variance in occultations observed by Cassini UVIS. We observe differences in the best-fitting particle size in different ring regions. The C ring plateaus show a distinctly smaller effective particle size, R, than the background C ring, while the background C ring itself shows a positive correlation between R and optical depth. The innermost 700 km of the B ring has a distribution of excess variance with optical depth that is consistent with the C ring ramp and C ring but not with the remainder of the B1 region. The Cassini Division, while similar to the C ring in spectral and structural properties, has different trends in effective particle size with optical depth. There are discrete jumps in R on either side of the Cassini Division ramp, while the C ring ramp shows a smooth transition in R from the C ring to the B ring. The A ring is dominated by self-gravity wakes whose shadow size depends on the occultation geometry. The spectral ;halo; regions around the strongest density waves in the A ring correspond to decreases in R. There is also a pronounced dip in R at the Mimas 5:3 bending wave corresponding to an increase in optical depth there, suggesting that at these waves small particles are liberated from clumps or self-gravity wakes leading to a reduction in effective particle size and an increase in optical depth.

Bootstrap versus Statistical Effect Size Corrections: A Comparison with Data from the Finding Embedded Figures Test.

ERIC Educational Resources Information Center

Thompson, Bruce; Melancon, Janet G.

Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…

Bias and Precision of Measures of Association for a Fixed-Effect Multivariate Analysis of Variance Model

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

The Importance of Variance in Statistical Analysis: Don't Throw Out the Baby with the Bathwater.

ERIC Educational Resources Information Center

Peet, Martha W.

This paper analyzes what happens to the effect size of a given dataset when the variance is removed by categorization for the purpose of applying "OVA" methods (analysis of variance, analysis of covariance). The dataset is from a classic study by Holzinger and Swinefors (1939) in which more than 20 ability test were administered to 301…

Does Intraspecific Size Variation in a Predator Affect Its Diet Diversity and Top-Down Control of Prey?

PubMed Central

Ingram, Travis; Stutz, William E.; Bolnick, Daniel I.

2011-01-01

It has long been known that intraspecific variation impacts evolutionary processes, but only recently have its potential ecological effects received much attention. Theoretical models predict that genetic or phenotypic variance within species can alter interspecific interactions, and experiments have shown that genotypic diversity in clonal species can impact a wide range of ecological processes. To extend these studies to quantitative trait variation within populations, we experimentally manipulated the variance in body size of threespine stickleback in enclosures in a natural lake environment. We found that body size of stickleback in the lake is correlated with prey size and (to a lesser extent) composition, and that stickleback can exert top-down control on their benthic prey in enclosures. However, a six-fold contrast in body size variance had no effect on the degree of diet variation among individuals, or on the abundance or composition of benthic or pelagic prey. Interestingly, post-hoc analyses revealed suggestive correlations between the degree of diet variation and the strength of top-down control by stickleback. Our negative results indicate that, unless the correlation between morphology and diet is very strong, ecological variation among individuals may be largely decoupled from morphological variance. Consequently we should be cautious in our interpretation both of theoretical models that assume perfect correlations between morphology and diet, and of empirical studies that use morphological variation as a proxy for resource use diversity. PMID:21687670

Does intraspecific size variation in a predator affect its diet diversity and top-down control of prey?

PubMed

Ingram, Travis; Stutz, William E; Bolnick, Daniel I

2011-01-01

It has long been known that intraspecific variation impacts evolutionary processes, but only recently have its potential ecological effects received much attention. Theoretical models predict that genetic or phenotypic variance within species can alter interspecific interactions, and experiments have shown that genotypic diversity in clonal species can impact a wide range of ecological processes. To extend these studies to quantitative trait variation within populations, we experimentally manipulated the variance in body size of threespine stickleback in enclosures in a natural lake environment. We found that body size of stickleback in the lake is correlated with prey size and (to a lesser extent) composition, and that stickleback can exert top-down control on their benthic prey in enclosures. However, a six-fold contrast in body size variance had no effect on the degree of diet variation among individuals, or on the abundance or composition of benthic or pelagic prey. Interestingly, post-hoc analyses revealed suggestive correlations between the degree of diet variation and the strength of top-down control by stickleback. Our negative results indicate that, unless the correlation between morphology and diet is very strong, ecological variation among individuals may be largely decoupled from morphological variance. Consequently we should be cautious in our interpretation both of theoretical models that assume perfect correlations between morphology and diet, and of empirical studies that use morphological variation as a proxy for resource use diversity.

Effective Size of Nonrandom Mating Populations

PubMed Central

Caballero, A.; Hill, W. G.

1992-01-01

Nonrandom mating whereby parents are related is expected to cause a reduction in effective population size because their gene frequencies are correlated and this will increase the genetic drift. The published equation for the variance effective size, N(e), which includes the possibility of nonrandom mating, does not take into account such a correlation, however. Further, previous equations to predict effective sizes in populations with partial sib mating are shown to be different, but also incorrect. In this paper, a corrected form of these equations is derived and checked by stochastic simulation. For the case of stable census number, N, and equal progeny distributions for each sex, the equation is & where S(k)(2) is the variance of family size and α is the departure from Hardy-Weinberg proportions. For a Poisson distribution of family size (S(k)(2) = 2), it reduces to N(e) = N/(1 + α), as when inbreeding is due to selfing. When nonrandom mating occurs because there is a specified system of partial inbreeding every generation, α can be substituted by Wright's F(IS) statistic, to give the effective size as a function of the proportion of inbred mates. PMID:1582565

Meta-Analysis with Complex Research Designs: Dealing with Dependence from Multiple Measures and Multiple Group Comparisons

ERIC Educational Resources Information Center

Scammacca, Nancy; Roberts, Greg; Stuebing, Karla K.

2014-01-01

Previous research has shown that treating dependent effect sizes as independent inflates the variance of the mean effect size and introduces bias by giving studies with more effect sizes more weight in the meta-analysis. This article summarizes the different approaches to handling dependence that have been advocated by methodologists, some of…

A Comparison of Methods for Estimating Confidence Intervals for Omega-Squared Effect Size

ERIC Educational Resources Information Center

Finch, W. Holmes; French, Brian F.

2012-01-01

Effect size use has been increasing in the past decade in many research areas. Confidence intervals associated with effect sizes are encouraged to be reported. Prior work has investigated the performance of confidence interval estimation with Cohen's d. This study extends this line of work to the analysis of variance case with more than two…

The Ecological Genetics of Introduced Populations of the Giant Toad BUFO MARINUS. II. Effective Population Size

PubMed Central

Easteal, Simon

1985-01-01

The allele frequencies are described at ten polymorphic enzyme loci (of a total of 22 loci sampled) in 15 populations of the neotropical giant toad, Bufo marinus, introduced to Hawaii and Australia in the 1930s. The history of establishment of the ten populations is described and used as a framework for the analysis of allele frequency variances. The variances are used to determine the effective sizes of the populations. The estimates obtained (390 and 346) are reasonably precise, homogeneous between localities and much smaller than estimates of neighborhood size obtained previously using ecological methods. This discrepancy is discussed, and it is concluded that the estimates obtained here using genetic methods are the more reliable. PMID:3922852

Maternal-by-environment but not genotype-by-environment interactions in a fish without parental care.

PubMed

Vega-Trejo, Regina; Head, Megan L; Jennions, Michael D; Kruuk, Loeske E B

2018-01-01

The impact of environmental conditions on the expression of genetic variance and on maternal effects variance remains an important question in evolutionary quantitative genetics. We investigate here the effects of early environment on variation in seven adult life history, morphological, and secondary sexual traits (including sperm characteristics) in a viviparous poeciliid fish, the mosquitofish Gambusia holbrooki. Specifically, we manipulated food availability during early development and then assessed additive genetic and maternal effects contributions to the overall phenotypic variance in adults. We found higher heritability for female than male traits, but maternal effects variance for traits in both sexes. An interaction between maternal effects variance and rearing environment affected two adult traits (female age at maturity and male size at maturity), but there was no evidence of trade-offs in maternal effects across environments. Our results illustrate (i) the potential for pre-natal maternal effects to interact with offspring environment during development, potentially affecting traits through to adulthood and (ii) that genotype-by-environment interactions might be overestimated if maternal-by-environment interactions are not accounted for, similar to heritability being overestimated if maternal effects are ignored. We also discuss the potential for dominance genetic variance to contribute to the estimate of maternal effects variance.

Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

PubMed

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

2018-06-10

Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

An Alternative to Cohen's Standardized Mean Difference Effect Size: A Robust Parameter and Confidence Interval in the Two Independent Groups Case

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2005-01-01

The authors argue that a robust version of Cohen's effect size constructed by replacing population means with 20% trimmed means and the population standard deviation with the square root of a 20% Winsorized variance is a better measure of population separation than is Cohen's effect size. The authors investigated coverage probability for…

A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships.

PubMed

Visscher, Peter M; Goddard, Michael E

2015-01-01

Heritability is a population parameter of importance in evolution, plant and animal breeding, and human medical genetics. It can be estimated using pedigree designs and, more recently, using relationships estimated from markers. We derive the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation. We show that well-known results for balanced designs are special cases of a more general unified framework. For pedigree designs, the sampling variance is inversely proportional to the variance of relationship in the pedigree and it is proportional to 1/N, whereas for population samples it is approximately proportional to 1/N(2), where N is the sample size. Variation in relatedness is a key parameter in the quantification of the sampling variance of heritability. Consequently, the sampling variance is high for populations with large recent effective population size (e.g., humans) because this causes low variation in relationship. However, even using human population samples, low sampling variance is possible with high N. Copyright © 2015 by the Genetics Society of America.

The contribution of the mitochondrial genome to sex-specific fitness variance.

PubMed

Smith, Shane R T; Connallon, Tim

2017-05-01

Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Taylor's law and body size in exploited marine ecosystems.

PubMed

Cohen, Joel E; Plank, Michael J; Law, Richard

2012-12-01

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught.

Taylor's law and body size in exploited marine ecosystems

PubMed Central

Cohen, Joel E; Plank, Michael J; Law, Richard

2012-01-01

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught. PMID:23301181

Efficiencies for the statistics of size discrimination.

PubMed

Solomon, Joshua A; Morgan, Michael; Chubb, Charles

2011-10-19

Different laboratories have achieved a consensus regarding how well human observers can estimate the average orientation in a set of N objects. Such estimates are not only limited by visual noise, which perturbs the visual signal of each object's orientation, they are also inefficient: Observers effectively use only √N objects in their estimates (e.g., S. C. Dakin, 2001; J. A. Solomon, 2010). More controversial is the efficiency with which observers can estimate the average size in an array of circles (e.g., D. Ariely, 2001, 2008; S. C. Chong, S. J. Joo, T.-A. Emmanouil, & A. Treisman, 2008; K. Myczek & D. J. Simons, 2008). Of course, there are some important differences between orientation and size; nonetheless, it seemed sensible to compare the two types of estimate against the same ideal observer. Indeed, quantitative evaluation of statistical efficiency requires this sort of comparison (R. A. Fisher, 1925). Our first step was to measure the noise that limits size estimates when only two circles are compared. Our results (Weber fractions between 0.07 and 0.14 were necessary for 84% correct 2AFC performance) are consistent with the visual system adding the same amount of Gaussian noise to all logarithmically transduced circle diameters. We exaggerated this visual noise by randomly varying the diameters in (uncrowded) arrays of 1, 2, 4, and 8 circles and measured its effect on discrimination between mean sizes. Efficiencies inferred from all four observers significantly exceed 25% and, in two cases, approach 100%. More consistent are our measurements of just-noticeable differences in size variance. These latter results suggest between 62 and 75% efficiency for variance discriminations. Although our observers were no more efficient comparing size variances than they were at comparing mean sizes, they were significantly more precise. In other words, our results contain evidence for a non-negligible source of late noise that limits mean discriminations but not variance discriminations.

Accounting for One-Group Clustering in Effect-Size Estimation

ERIC Educational Resources Information Center

Citkowicz, Martyna; Hedges, Larry V.

2013-01-01

In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…

Ingredients of the Eddy Soup: A Geometric Decomposition of Eddy-Mean Flow Interactions

NASA Astrophysics Data System (ADS)

Waterman, S.; Lilly, J. M.

2014-12-01

Understanding eddy-mean flow interactions is a long-standing problem in geophysical fluid dynamics with modern relevance to the task of representing eddy effects in coarse resolution models while preserving their dependence on the underlying dynamics of the flow field. Exploiting the recognition that the velocity covariance matrix/eddy stress tensor that describes eddy fluxes, also encodes information about eddy size, shape and orientation through its geometric representation in the form of the so-called variance ellipse, suggests a potentially fruitful way forward. Here we present a new framework that describes eddy-mean flow interactions in terms of a geometric description of the eddy motion, and illustrate it with an application to an unstable jet. Specifically we show that the eddy vorticity flux divergence F, a key dynamical quantity describing the average effect of fluctuations on the time-mean flow, may be decomposed into two components with distinct geometric interpretations: 1. variations in variance ellipse orientation; and 2. variations in the anisotropic part of the eddy kinetic energy, a function of the variance ellipse size and shape. Application of the divergence theorem shows that F integrated over a region is explained entirely by variations in these two quantities around the region's periphery. This framework has the potential to offer new insights into eddy-mean flow interactions in a number of ways. It identifies the ingredients of the eddy motion that have a mean flow forcing effect, it links eddy effects to spatial patterns of variance ellipse geometry that can suggest the mechanisms underpinning these effects, and finally it illustrates the importance of resolving eddy shape and orientation, and not just eddy size/energy, to accurately represent eddy feedback effects. These concepts will be both discussed and illustrated.

Methods to estimate effective population size using pedigree data: Examples in dog, sheep, cattle and horse

PubMed Central

2013-01-01

Background Effective population sizes of 140 populations (including 60 dog breeds, 40 sheep breeds, 20 cattle breeds and 20 horse breeds) were computed using pedigree information and six different computation methods. Simple demographical information (number of breeding males and females), variance of progeny size, or evolution of identity by descent probabilities based on coancestry or inbreeding were used as well as identity by descent rate between two successive generations or individual identity by descent rate. Results Depending on breed and method, effective population sizes ranged from 15 to 133 056, computation method and interaction between computation method and species showing a significant effect on effective population size (P < 0.0001). On average, methods based on number of breeding males and females and variance of progeny size produced larger values (4425 and 356, respectively), than those based on identity by descent probabilities (average values between 93 and 203). Since breeding practices and genetic substructure within dog breeds increased inbreeding, methods taking into account the evolution of inbreeding produced lower effective population sizes than those taking into account evolution of coancestry. The correlation level between the simplest method (number of breeding males and females, requiring no genealogical information) and the most sophisticated one ranged from 0.44 to 0.60 according to species. Conclusions When choosing a method to compute effective population size, particular attention should be paid to the species and the specific genetic structure of the population studied. PMID:23281913

Environmental, biological and anthropogenic effects on grizzly bear body size: temporal and spatial considerations.

PubMed

Nielsen, Scott E; Cattet, Marc R L; Boulanger, John; Cranston, Jerome; McDermid, Greg J; Shafer, Aaron B A; Stenhouse, Gordon B

2013-09-08

Individual body growth is controlled in large part by the spatial and temporal heterogeneity of, and competition for, resources. Grizzly bears (Ursus arctos L.) are an excellent species for studying the effects of resource heterogeneity and maternal effects (i.e. silver spoon) on life history traits such as body size because their habitats are highly variable in space and time. Here, we evaluated influences on body size of grizzly bears in Alberta, Canada by testing six factors that accounted for spatial and temporal heterogeneity in environments during maternal, natal and 'capture' (recent) environments. After accounting for intrinsic biological factors (age, sex), we examined how body size, measured in mass, length and body condition, was influenced by: (a) population density; (b) regional habitat productivity; (c) inter-annual variability in productivity (including silver spoon effects); (d) local habitat quality; (e) human footprint (disturbances); and (f) landscape change. We found sex and age explained the most variance in body mass, condition and length (R(2) from 0.48-0.64). Inter-annual variability in climate the year before and of birth (silver spoon effects) had detectable effects on the three-body size metrics (R(2) from 0.04-0.07); both maternal (year before birth) and natal (year of birth) effects of precipitation and temperature were related with body size. Local heterogeneity in habitat quality also explained variance in body mass and condition (R(2) from 0.01-0.08), while annual rate of landscape change explained additional variance in body length (R(2) of 0.03). Human footprint and population density had no observed effect on body size. These results illustrated that body size patterns of grizzly bears, while largely affected by basic biological characteristics (age and sex), were also influenced by regional environmental gradients the year before, and of, the individual's birth thus illustrating silver spoon effects. The magnitude of the silver spoon effects was on par with the influence of contemporary regional habitat productivity, which showed that both temporal and spatial influences explain in part body size patterns in grizzly bears. Because smaller bears were found in colder and less-productive environments, we hypothesize that warming global temperatures may positively affect body mass of interior bears.

Useful Effect Size Interpretations for Single Case Research

ERIC Educational Resources Information Center

Parker, Richard I.; Hagan-Burke, Shanna

2007-01-01

An obstacle to broader acceptability of effect sizes in single case research is their lack of intuitive and useful interpretations. Interpreting Cohen's d as "standard deviation units difference" and R[superscript 2] as "percent of variance accounted for" do not resound with most visual analysts. In fact, the only comparative analysis widely…

An Analytic Comparison of Effect Sizes for Differential Item Functioning

ERIC Educational Resources Information Center

Demars, Christine E.

2011-01-01

Three types of effects sizes for DIF are described in this exposition: log of the odds-ratio (differences in log-odds), differences in probability-correct, and proportion of variance accounted for. Using these indices involves conceptualizing the degree of DIF in different ways. This integrative review discusses how these measures are impacted in…

The variance of dispersion measure of high-redshift transient objects as a probe of ionized bubble size during reionization

NASA Astrophysics Data System (ADS)

Yoshiura, Shintaro; Takahashi, Keitaro

2018-01-01

The dispersion measure (DM) of high-redshift (z ≳ 6) transient objects such as fast radio bursts can be a powerful tool to probe the intergalactic medium during the Epoch of Reionization. In this paper, we study the variance of the DMs of objects with the same redshift as a potential probe of the size distribution of ionized bubbles. We calculate the DM variance with a simple model with randomly distributed spherical bubbles. It is found that the DM variance reflects the characteristics of the probability distribution of the bubble size. We find that the variance can be measured precisely enough to obtain the information on the typical size with a few hundred sources at a single redshift.

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

PubMed

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

2005-03-01

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

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

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

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

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

PubMed

van Schie, S; Moerbeek, M

2014-08-30

Often only a limited number of clusters can be obtained in cluster randomised trials, although many potential participants can be recruited within each cluster. Thus, active recruitment is feasible within the clusters. To obtain an efficient sample size in a cluster randomised trial, the cluster level and individual level variance should be known before the study starts, but this is often not the case. We suggest using an internal pilot study design to address this problem of unknown variances. A pilot can be useful to re-estimate the variances and re-calculate the sample size during the trial. Using simulated data, it is shown that an initially low or high power can be adjusted using an internal pilot with the type I error rate remaining within an acceptable range. The intracluster correlation coefficient can be re-estimated with more precision, which has a positive effect on the sample size. We conclude that an internal pilot study design may be used if active recruitment is feasible within a limited number of clusters. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

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

Body size and lower limb posture during walking in humans.

PubMed

Hora, Martin; Soumar, Libor; Pontzer, Herman; Sládek, Vladimír

2017-01-01

We test whether locomotor posture is associated with body mass and lower limb length in humans and explore how body size and posture affect net joint moments during walking. We acquired gait data for 24 females and 25 males using a three-dimensional motion capture system and pressure-measuring insoles. We employed the general linear model and commonality analysis to assess the independent effect of body mass and lower limb length on flexion angles at the hip, knee, and ankle while controlling for sex and velocity. In addition, we used inverse dynamics to model the effect of size and posture on net joint moments. At early stance, body mass has a negative effect on knee flexion (p < 0.01), whereas lower limb length has a negative effect on hip flexion (p < 0.05). Body mass uniquely explains 15.8% of the variance in knee flexion, whereas lower limb length uniquely explains 5.4% of the variance in hip flexion. Both of the detected relationships between body size and posture are consistent with the moment moderating postural adjustments predicted by our model. At late stance, no significant relationship between body size and posture was detected. Humans of greater body size reduce the flexion of the hip and knee at early stance, which results in the moderation of net moments at these joints.

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

The Efficacy of Two Improvement-over-Chance Effect Sizes for Two-Group Univariate Comparisons under Variance Heterogeneity and Nonnormality.

ERIC Educational Resources Information Center

Hess, Brian; Olejnik, Stephen; Huberty, Carl J.

2001-01-01

Studied the efficacy of two improvement-over-chance or "I" effect sizes derived from predictive discriminant analysis and logistic regression analysis for two-group univariate mean comparisons through simulation. Discusses the ways in which the usefulness of each of the indices depends on the population characteristics. (SLD)

Multisite Reliability of Cognitive BOLD Data

PubMed Central

Brown, Gregory G.; Mathalon, Daniel H.; Stern, Hal; Ford, Judith; Mueller, Bryon; Greve, Douglas N.; McCarthy, Gregory; Voyvodic, Jim; Glover, Gary; Diaz, Michele; Yetter, Elizabeth; Burak Ozyurt, I.; Jorgensen, Kasper W.; Wible, Cynthia G.; Turner, Jessica A.; Thompson, Wesley K.; Potkin, Steven G.

2010-01-01

Investigators perform multi-site functional magnetic resonance imaging studies to increase statistical power, to enhance generalizability, and to improve the likelihood of sampling relevant subgroups. Yet undesired site variation in imaging methods could off-set these potential advantages. We used variance components analysis to investigate sources of variation in the blood oxygen level dependent (BOLD) signal across four 3T magnets in voxelwise and region of interest (ROI) analyses. Eighteen participants traveled to four magnet sites to complete eight runs of a working memory task involving emotional or neutral distraction. Person variance was more than 10 times larger than site variance for five of six ROIs studied. Person-by-site interactions, however, contributed sizable unwanted variance to the total. Averaging over runs increased between-site reliability, with many voxels showing good to excellent between-site reliability when eight runs were averaged and regions of interest showing fair to good reliability. Between-site reliability depended on the specific functional contrast analyzed in addition to the number of runs averaged. Although median effect size was correlated with between-site reliability, dissociations were observed for many voxels. Brain regions where the pooled effect size was large but between-site reliability was poor were associated with reduced individual differences. Brain regions where the pooled effect size was small but between-site reliability was excellent were associated with a balance of participants who displayed consistently positive or consistently negative BOLD responses. Although between-site reliability of BOLD data can be good to excellent, acquiring highly reliable data requires robust activation paradigms, ongoing quality assurance, and careful experimental control. PMID:20932915

Liquid Water Cloud Properties During the Polarimeter Definition Experiment (PODEX)

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Wasilewski, Andrzei P.; Ackerman, Andrew S.; McGill, Matthew J.; Yorks, John E.; Hlavka, Dennis L.; Platnick, Steven; Arnold, George; Van Diedenhoven, Bastiaan;

Estimation of (co)variances for genomic regions of flexible sizes: application to complex infectious udder diseases in dairy cattle

PubMed Central

2012-01-01

Background Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related traits such as mammary disease traits in dairy cattle. Methods Data on progeny means of six traits related to mastitis resistance in dairy cattle (general mastitis resistance and five pathogen-specific mastitis resistance traits) were analyzed using a bivariate Bayesian SNP-based genomic model with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level, per chromosome, and in regions of 100 SNP on a chromosome. Results Genomic proportions of the total variance differed between traits. Genomic correlations were lower than pedigree-based genetic correlations and they were highest between general mastitis and pathogen-specific traits because of the part-whole relationship between these traits. The chromosome-wise genomic proportions of the total variance differed between traits, with some chromosomes explaining higher or lower values than expected in relation to chromosome size. Few chromosomes showed pleiotropic effects and only chromosome 19 had a clear effect on all traits, indicating the presence of QTL with a general effect on mastitis resistance. The region-wise patterns of genomic variances differed between traits. Peaks indicating QTL were identified but were not very distinctive because a common prior for the marker effects was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. Conclusions The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances of mastitis resistance traits in dairy cattle using multivariate genomic models. PMID:22640006

Determining Size Distribution at the Phoenix Landing Site

NASA Astrophysics Data System (ADS)

Mason, E. L.; Lemmon, M. T.

2016-12-01

Dust aerosols play a crucial role in determining atmospheric radiative heating on Mars through absorption and scattering of sunlight. How dust scatters and absorbs light is dependent on size, shape, composition, and quantity. Optical properties of the dust have been well constrained in the visible and near infrared wavelengths using various methods [Wolff et al. 2009, Lemmon et al. 2004]. In addition, the dust is nonspherical, and irregular shapes have shown to work well in determining effective particle size [Pollack et al. 1977]. Variance of the size distribution is less constrained but constitutes an important parameter in fully describing the dust. The Phoenix Lander's Surface Stereo Imager performed several cross-sky brightness surveys to determine the size distribution and scattering properties of dust in the wavelength range of 400 to 1000 nm. In combination with a single-layer radiative transfer model, these surveys can be used to help constrain variance of the size distribution. We will present a discussion of seasonal size distribution as it pertains to the Phoenix landing site.

Physiological, Behavioral and Maternal Factors That Contribute to Size Variation in Larval Amphibian Populations

PubMed Central

Warne, Robin W.; Kardon, Adam; Crespi, Erica J.

2013-01-01

Size variance among similarly aged individuals within populations is a pattern common to many organisms that is a result of interactions between intrinsic and extrinsic traits of individuals. While genetic and maternal effects, as well as physiological and behavioral traits have been shown to contribute to size variation in animal populations, teasing apart the influence of such factors on individual growth rates remain a challenge. Furthermore, tracing the effects of these interactions across life stages and in shaping adult phenotypes also requires further exploration. In this study we investigated the relationship between genetics, hatching patterns, behaviors, neuroendocrine stress axis activity and variance in growth and metamorphosis among same-aged larval amphibians. Through parallel experiments we found that in the absence of conspecific interactions, hatch time and to a lesser extent egg clutch identity (i.e. genetics and maternal effects) influenced the propensity for growth and development in individual tadpoles and determined metamorphic traits. Within experimental groups we found that variance in growth rates was associated with size-dependent foraging behaviors and responses to food restriction. We also found an inverse relationship between glucocorticoid (GC) hormone levels and body mass and developmental stage among group-reared tadpoles, which suggests that GC expression plays a role in regulating differing within-population growth trajectories in response to density-dependent conditions. Taken together these findings suggest that factors that influence hatching conditions can have long-term effects on growth and development. These results also raise compelling questions regarding the extent to which maternal and genetic factors influence physiological and behavioral profiles in amphibians. PMID:24143188

Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items.

PubMed

Yang, Yi; Tokita, Midori; Ishiguchi, Akira

2018-01-01

A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed.

On the impact of relatedness on SNP association analysis.

PubMed

Gross, Arnd; Tönjes, Anke; Scholz, Markus

2017-12-06

When testing for SNP (single nucleotide polymorphism) associations in related individuals, observations are not independent. Simple linear regression assuming independent normally distributed residuals results in an increased type I error and the power of the test is also affected in a more complicate manner. Inflation of type I error is often successfully corrected by genomic control. However, this reduces the power of the test when relatedness is of concern. In the present paper, we derive explicit formulae to investigate how heritability and strength of relatedness contribute to variance inflation of the effect estimate of the linear model. Further, we study the consequences of variance inflation on hypothesis testing and compare the results with those of genomic control correction. We apply the developed theory to the publicly available HapMap trio data (N=129), the Sorbs (a self-contained population with N=977 characterised by a cryptic relatedness structure) and synthetic family studies with different sample sizes (ranging from N=129 to N=999) and different degrees of relatedness. We derive explicit and easily to apply approximation formulae to estimate the impact of relatedness on the variance of the effect estimate of the linear regression model. Variance inflation increases with increasing heritability. Relatedness structure also impacts the degree of variance inflation as shown for example family structures. Variance inflation is smallest for HapMap trios, followed by a synthetic family study corresponding to the trio data but with larger sample size than HapMap. Next strongest inflation is observed for the Sorbs, and finally, for a synthetic family study with a more extreme relatedness structure but with similar sample size as the Sorbs. Type I error increases rapidly with increasing inflation. However, for smaller significance levels, power increases with increasing inflation while the opposite holds for larger significance levels. When genomic control is applied, type I error is preserved while power decreases rapidly with increasing variance inflation. Stronger relatedness as well as higher heritability result in increased variance of the effect estimate of simple linear regression analysis. While type I error rates are generally inflated, the behaviour of power is more complex since power can be increased or reduced in dependence on relatedness and the heritability of the phenotype. Genomic control cannot be recommended to deal with inflation due to relatedness. Although it preserves type I error, the loss in power can be considerable. We provide a simple formula for estimating variance inflation given the relatedness structure and the heritability of a trait of interest. As a rule of thumb, variance inflation below 1.05 does not require correction and simple linear regression analysis is still appropriate.

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.

Conserving genomic variability in large mammals: Effect of population fluctuations and variance in male reproductive success on variability in Yellowstone bison

Treesearch

Andres Perez-Figueroa; Rick L. Wallen; Tiago Antao; Jason A. Coombs; Michael K. Schwartz; P. J. White; Gordon Luikart

2012-01-01

Loss of genetic variation through genetic drift can reduce population viability. However, relatively little is known about loss of variation caused by the combination of fluctuating population size and variance in reproductive success in age structured populations. We built an individual-based computer simulation model to examine how actual culling and hunting...

Body size and lower limb posture during walking in humans

PubMed Central

Hora, Martin; Soumar, Libor; Pontzer, Herman; Sládek, Vladimír

2017-01-01

We test whether locomotor posture is associated with body mass and lower limb length in humans and explore how body size and posture affect net joint moments during walking. We acquired gait data for 24 females and 25 males using a three-dimensional motion capture system and pressure-measuring insoles. We employed the general linear model and commonality analysis to assess the independent effect of body mass and lower limb length on flexion angles at the hip, knee, and ankle while controlling for sex and velocity. In addition, we used inverse dynamics to model the effect of size and posture on net joint moments. At early stance, body mass has a negative effect on knee flexion (p < 0.01), whereas lower limb length has a negative effect on hip flexion (p < 0.05). Body mass uniquely explains 15.8% of the variance in knee flexion, whereas lower limb length uniquely explains 5.4% of the variance in hip flexion. Both of the detected relationships between body size and posture are consistent with the moment moderating postural adjustments predicted by our model. At late stance, no significant relationship between body size and posture was detected. Humans of greater body size reduce the flexion of the hip and knee at early stance, which results in the moderation of net moments at these joints. PMID:28192522

A diffusion-based approach to stochastic individual growth and energy budget, with consequences to life-history optimization and population dynamics.

PubMed

Filin, I

2009-06-01

Using diffusion processes, I model stochastic individual growth, given exogenous hazards and starvation risk. By maximizing survival to final size, optimal life histories (e.g. switching size for habitat/dietary shift) are determined by two ratios: mean growth rate over growth variance (diffusion coefficient) and mortality rate over mean growth rate; all are size dependent. For example, switching size decreases with either ratio, if both are positive. I provide examples and compare with previous work on risk-sensitive foraging and the energy-predation trade-off. I then decompose individual size into reversibly and irreversibly growing components, e.g. reserves and structure. I provide a general expression for optimal structural growth, when reserves grow stochastically. I conclude that increased growth variance of reserves delays structural growth (raises threshold size for its commencement) but may eventually lead to larger structures. The effect depends on whether the structural trait is related to foraging or defence. Implications for population dynamics are discussed.

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

PubMed

Liu, Jingxia; Colditz, Graham A

2018-05-01

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

40 CFR 142.303 - Which size public water systems can receive a small system variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Which size public water systems can receive a small system variance? 142.303 Section 142.303 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System General...

40 CFR 142.303 - Which size public water systems can receive a small system variance?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Which size public water systems can receive a small system variance? 142.303 Section 142.303 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System General...

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.

Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items

PubMed Central

Yang, Yi; Tokita, Midori; Ishiguchi, Akira

2018-01-01

A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed. PMID:29399318

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

PubMed

Heidel, R Eric

2016-01-01

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

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

Treesearch

Daniele Tonina; Alberto Bellin

2008-01-01

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

Comparing Students With and Without Reading Difficulties on Reading Comprehension Assessments: A Meta-Analysis.

PubMed

Collins, Alyson A; Lindström, Esther R; Compton, Donald L

Researchers have increasingly investigated sources of variance in reading comprehension test scores, particularly with students with reading difficulties (RD). The purpose of this meta-analysis was to determine if the achievement gap between students with RD and typically developing (TD) students varies as a function of different reading comprehension response formats (e.g., multiple choice, cloze). A systematic literature review identified 82 eligible studies. All studies administered reading comprehension assessments to students with RD and TD students in Grades K-12. Hedge's g standardized mean difference effect sizes were calculated, and random effects robust variance estimation techniques were used to aggregate average weighted effect sizes for each response format. Results indicated that the achievement gap between students with RD and TD students was larger for some response formats (e.g., picture selection ES g = -1.80) than others (e.g., retell ES g = -0.60). Moreover, for multiple-choice, cloze, and open-ended question response formats, single-predictor metaregression models explored potential moderators of heterogeneity in effect sizes. No clear patterns, however, emerged in regard to moderators of heterogeneity in effect sizes across response formats. Findings suggest that the use of different response formats may lead to variability in the achievement gap between students with RD and TD students.

R2 effect-size measures for mediation analysis

PubMed Central

Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.

2010-01-01

R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189

R2 effect-size measures for mediation analysis.

PubMed

Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B

2009-05-01

R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.

Incorporating Functional Genomic Information in Genetic Association Studies Using an Empirical Bayes Approach.

PubMed

Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2016-04-01

There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study

PubMed Central

Kim, Minjung; Lamont, Andrea E.; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M. Lee

2015-01-01

Regression mixture models are a novel approach for modeling heterogeneous effects of predictors on an outcome. In the model building process residual variances are often disregarded and simplifying assumptions made without thorough examination of the consequences. This simulation study investigated the impact of an equality constraint on the residual variances across latent classes. We examine the consequence of constraining the residual variances on class enumeration (finding the true number of latent classes) and parameter estimates under a number of different simulation conditions meant to reflect the type of heterogeneity likely to exist in applied analyses. Results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted estimated class sizes and showed the potential to greatly impact parameter estimates in each class. Results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions were made. PMID:26139512

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

ERIC Educational Resources Information Center

Shieh, Gwowen; Jan, Show-Li

2013-01-01

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

Properties of hypothesis testing techniques and (Bayesian) model selection for exploration-based and theory-based (order-restricted) hypotheses.

PubMed

Kuiper, Rebecca M; Nederhoff, Tim; Klugkist, Irene

2015-05-01

In this paper, the performance of six types of techniques for comparisons of means is examined. These six emerge from the distinction between the method employed (hypothesis testing, model selection using information criteria, or Bayesian model selection) and the set of hypotheses that is investigated (a classical, exploration-based set of hypotheses containing equality constraints on the means, or a theory-based limited set of hypotheses with equality and/or order restrictions). A simulation study is conducted to examine the performance of these techniques. We demonstrate that, if one has specific, a priori specified hypotheses, confirmation (i.e., investigating theory-based hypotheses) has advantages over exploration (i.e., examining all possible equality-constrained hypotheses). Furthermore, examining reasonable order-restricted hypotheses has more power to detect the true effect/non-null hypothesis than evaluating only equality restrictions. Additionally, when investigating more than one theory-based hypothesis, model selection is preferred over hypothesis testing. Because of the first two results, we further examine the techniques that are able to evaluate order restrictions in a confirmatory fashion by examining their performance when the homogeneity of variance assumption is violated. Results show that the techniques are robust to heterogeneity when the sample sizes are equal. When the sample sizes are unequal, the performance is affected by heterogeneity. The size and direction of the deviations from the baseline, where there is no heterogeneity, depend on the effect size (of the means) and on the trend in the group variances with respect to the ordering of the group sizes. Importantly, the deviations are less pronounced when the group variances and sizes exhibit the same trend (e.g., are both increasing with group number). © 2014 The British Psychological Society.

Confidence intervals and sample size calculations for the standardized mean difference effect size between two normal populations under heteroscedasticity.

PubMed

Shieh, G

2013-12-01

The use of effect sizes and associated confidence intervals in all empirical research has been strongly emphasized by journal publication guidelines. To help advance theory and practice in the social sciences, this article describes an improved procedure for constructing confidence intervals of the standardized mean difference effect size between two independent normal populations with unknown and possibly unequal variances. The presented approach has advantages over the existing formula in both theoretical justification and computational simplicity. In addition, simulation results show that the suggested one- and two-sided confidence intervals are more accurate in achieving the nominal coverage probability. The proposed estimation method provides a feasible alternative to the most commonly used measure of Cohen's d and the corresponding interval procedure when the assumption of homogeneous variances is not tenable. To further improve the potential applicability of the suggested methodology, the sample size procedures for precise interval estimation of the standardized mean difference are also delineated. The desired precision of a confidence interval is assessed with respect to the control of expected width and to the assurance probability of interval width within a designated value. Supplementary computer programs are developed to aid in the usefulness and implementation of the introduced techniques.

Inequality and City Size*

PubMed Central

Baum-Snow, Nathaniel; Pavan, Ronni

2013-01-01

Between 1979 and 2007 a strong positive monotonic relationship between wage inequality and city size has developed. This paper investigates the links between this emergent city size inequality premium and the contemporaneous nationwide increase in wage inequality. After controlling for the skill composition of the workforce across cities of different sizes, we show that at least 23 percent of the overall increase in the variance of log hourly wages in the United States from 1979 to 2007 is explained by the more rapid growth in the variance of log wages in larger locations relative to smaller locations. This influence occurred throughout the wage distribution and was most prevalent during the 1990s. More rapid growth in within skill group inequality in larger cities has been by far the most important force driving these city size specific patterns in the data. Differences in the industrial composition of cities of different sizes explain up to one-third of this city size effect. These results suggest an important role for agglomeration economies in generating changes in the wage structure during the study period. PMID:24954958

Previous Estimates of Mitochondrial DNA Mutation Level Variance Did Not Account for Sampling Error: Comparing the mtDNA Genetic Bottleneck in Mice and Humans

PubMed Central

Wonnapinij, Passorn; Chinnery, Patrick F.; Samuels, David C.

2010-01-01

In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference. PMID:20362273

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

PubMed

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

2017-02-01

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

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

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

PubMed

Luh, Wei-Ming; Guo, Jiin-Huarng

2007-05-01

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

On the validity of within-nuclear-family genetic association analysis in samples of extended families.

PubMed

Bureau, Alexandre; Duchesne, Thierry

2015-12-01

Splitting extended families into their component nuclear families to apply a genetic association method designed for nuclear families is a widespread practice in familial genetic studies. Dependence among genotypes and phenotypes of nuclear families from the same extended family arises because of genetic linkage of the tested marker with a risk variant or because of familial specificity of genetic effects due to gene-environment interaction. This raises concerns about the validity of inference conducted under the assumption of independence of the nuclear families. We indeed prove theoretically that, in a conditional logistic regression analysis applicable to disease cases and their genotyped parents, the naive model-based estimator of the variance of the coefficient estimates underestimates the true variance. However, simulations with realistic effect sizes of risk variants and variation of this effect from family to family reveal that the underestimation is negligible. The simulations also show the greater efficiency of the model-based variance estimator compared to a robust empirical estimator. Our recommendation is therefore, to use the model-based estimator of variance for inference on effects of genetic variants.

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

PubMed

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

2015-10-01

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

Estimation of population size using open capture-recapture models

USGS Publications Warehouse

McDonald, T.L.; Amstrup, Steven C.

2001-01-01

One of the most important needs for wildlife managers is an accurate estimate of population size. Yet, for many species, including most marine species and large mammals, accurate and precise estimation of numbers is one of the most difficult of all research challenges. Open-population capture-recapture models have proven useful in many situations to estimate survival probabilities but typically have not been used to estimate population size. We show that open-population models can be used to estimate population size by developing a Horvitz-Thompson-type estimate of population size and an estimator of its variance. Our population size estimate keys on the probability of capture at each trap occasion and therefore is quite general and can be made a function of external covariates measured during the study. Here we define the estimator and investigate its bias, variance, and variance estimator via computer simulation. Computer simulations make extensive use of real data taken from a study of polar bears (Ursus maritimus) in the Beaufort Sea. The population size estimator is shown to be useful because it was negligibly biased in all situations studied. The variance estimator is shown to be useful in all situations, but caution is warranted in cases of extreme capture heterogeneity.

A more powerful test based on ratio distribution for retention noninferiority hypothesis.

PubMed

Deng, Ling; Chen, Gang

2013-03-11

Rothmann et al. ( 2003 ) proposed a method for the statistical inference of fraction retention noninferiority (NI) hypothesis. A fraction retention hypothesis is defined as a ratio of the new treatment effect verse the control effect in the context of a time to event endpoint. One of the major concerns using this method in the design of an NI trial is that with a limited sample size, the power of the study is usually very low. This makes an NI trial not applicable particularly when using time to event endpoint. To improve power, Wang et al. ( 2006 ) proposed a ratio test based on asymptotic normality theory. Under a strong assumption (equal variance of the NI test statistic under null and alternative hypotheses), the sample size using Wang's test was much smaller than that using Rothmann's test. However, in practice, the assumption of equal variance is generally questionable for an NI trial design. This assumption is removed in the ratio test proposed in this article, which is derived directly from a Cauchy-like ratio distribution. In addition, using this method, the fundamental assumption used in Rothmann's test, that the observed control effect is always positive, that is, the observed hazard ratio for placebo over the control is greater than 1, is no longer necessary. Without assuming equal variance under null and alternative hypotheses, the sample size required for an NI trial can be significantly reduced if using the proposed ratio test for a fraction retention NI hypothesis.

Conditional Optimal Design in Three- and Four-Level Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.; Borenstein, Michael

2014-01-01

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

Revealing life-history traits by contrasting genetic estimations with predictions of effective population size.

PubMed

Greenbaum, Gili; Renan, Sharon; Templeton, Alan R; Bouskila, Amos; Saltz, David; Rubenstein, Daniel I; Bar-David, Shirli

2017-12-22

Effective population size, a central concept in conservation biology, is now routinely estimated from genetic surveys and can also be theoretically predicted from demographic, life-history, and mating-system data. By evaluating the consistency of theoretical predictions with empirically estimated effective size, insights can be gained regarding life-history characteristics and the relative impact of different life-history traits on genetic drift. These insights can be used to design and inform management strategies aimed at increasing effective population size. We demonstrated this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimated the variance effective size (N ev ) from genetic data (N ev =24.3) and formulated predictions for the impacts on N ev of demography, polygyny, female variance in lifetime reproductive success (RS), and heritability of female RS. By contrasting the genetic estimation with theoretical predictions, we found that polygyny was the strongest factor affecting genetic drift because only when accounting for polygyny were predictions consistent with the genetically measured N ev . The comparison of effective-size estimation and predictions indicated that 10.6% of the males mated per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in N ev ) and 19.5% mated when female RS was accounted for (polygyny responsible for 67% decrease in N ev ). Heritability of female RS also affected N ev ; hf2=0.91 (heritability responsible for 41% decrease in N ev ). The low effective size is of concern, and we suggest that management actions focus on factors identified as strongly affecting Nev, namely, increasing the availability of artificial water sources to increase number of dominant males contributing to the gene pool. This approach, evaluating life-history hypotheses in light of their impact on effective population size, and contrasting predictions with genetic measurements, is a general, applicable strategy that can be used to inform conservation practice. © 2017 Society for Conservation Biology.

Genetic consequences of polygyny and social structure in an Indian fruit bat, Cynopterus sphinx. II. Variance in male mating success and effective population size.

PubMed

Storz, J F; Bhat, H R; Kunz, T H

2001-06-01

Variance in reproductive success is a primary determinant of genetically effective population size (Ne), and thus has important implications for the role of genetic drift in the evolutionary dynamics of animal taxa characterized by polygynous mating systems. Here we report the results of a study designed to test the hypothesis that polygynous mating results in significantly reduced Ne in an age-structured population. This hypothesis was tested in a natural population of a harem-forming fruit bat, Cynopterus sphinx (Chiroptera: Pteropodidae), in western India. The influence of the mating system on the ratio of variance Ne to adult census number (N) was assessed using a mathematical model designed for age-structured populations that incorporated demographic and genetic data. Male mating success was assessed by means of direct and indirect paternity analysis using 10-locus microsatellite genotypes of adults and progeny from two consecutive breeding periods (n = 431 individually marked bats). Combined results from both analyses were used to infer the effective number of male parents in each breeding period. The relative proportion of successfully reproducing males and the size distribution of paternal sibships comprising each offspring cohort revealed an extremely high within-season variance in male mating success (up to 9.2 times higher than Poisson expectation). The resultant estimate of Ne/N for the C. sphinx study population was 0.42. As a result of polygynous mating, the predicted rate of drift (1/2Ne per generation) was 17.6% higher than expected from a Poisson distribution of male mating success. However, the estimated Ne/N was well within the 0.25-0.75 range expected for age-structured populations under normal demographic conditions. The life-history schedule of C. sphinx is characterized by a disproportionately short sexual maturation period scaled to adult life span. Consequently, the influence of polygynous mating on Ne/N is mitigated by the extensive overlap of generations. In C. sphinx, turnover of breeding males between seasons ensures a broader sampling of the adult male gamete pool than expected from the variance in mating success within a single breeding period.

Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study.

PubMed

Kim, Minjung; Lamont, Andrea E; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M Lee

2016-06-01

Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.

Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

PubMed

Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

2013-01-01

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

A comparison of the genetic basis of wing size divergence in three parallel body size clines of Drosophila melanogaster.

PubMed Central

Gilchrist, A S; Partridge, L

1999-01-01

Body size clines in Drosophila melanogaster have been documented in both Australia and South America, and may exist in Southern Africa. We crossed flies from the northern and southern ends of each of these clines to produce F(1), F(2), and first backcross generations. Our analysis of generation means for wing area and wing length produced estimates of the additive, dominance, epistatic, and maternal effects underlying divergence within each cline. For both females and males of all three clines, the generation means were adequately described by these parameters, indicating that linkage and higher order interactions did not contribute significantly to wing size divergence. Marked differences were apparent between the clines in the occurrence and magnitude of the significant genetic parameters. No cline was adequately described by a simple additive-dominance model, and significant epistatic and maternal effects occurred in most, but not all, of the clines. Generation variances were also analyzed. Only one cline was described sufficiently by a simple additive variance model, indicating significant epistatic, maternal, or linkage effects in the remaining two clines. The diversity in genetic architecture of the clines suggests that natural selection has produced similar phenotypic divergence by different combinations of gene action and interaction. PMID:10581284

The magnetized sheath of a dusty plasma with grains size distribution

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

Ou, Jing, E-mail: ouj@ipp.ac.cn; Gan, Chunyun; Lin, Binbin

2015-05-15

The structure of a plasma sheath in the presence of dust grains size distribution (DGSD) is investigated in the multi-fluid framework. It is shown that effect of the dust grains with different sizes on the sheath structure is a collective behavior. The spatial distributions of electric potential, the electron and ion densities and velocities, and the dust grains surface potential are strongly affected by DGSD. The dynamics of dust grains with different sizes in the sheath depend on not only DGSD but also their radius. By comparison of the sheath structure, it is found that under the same expected valuemore » of DGSD condition, the sheath length is longer in the case of lognormal distribution than that in the case of uniform distribution. In two cases of normal and lognormal distributions, the sheath length is almost equal for the small variance of DGSD, and then the difference of sheath length increases gradually with increase in the variance.« less

Measurement invariance versus selection invariance: is fair selection possible?

PubMed

Borsboom, Denny; Romeijn, Jan-Willem; Wicherts, Jelte M

2008-06-01

This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement instrument is used and group differences are present in the location but not in the variance of the latent distribution, sensitivity and positive predictive value will be higher in the group at the higher end of the latent dimension, whereas specificity and negative predictive value will be higher in the group at the lower end of the latent dimension. When latent variances are unequal, the differences in these quantities depend on the size of group differences in variances relative to the size of group differences in means. The effect originates as a special case of Simpson's paradox, which arises because the observed score distribution is collapsed into an accept-reject dichotomy. Simulations show the effect can be substantial in realistic situations. It is suggested that the effect may be partly responsible for overprediction in minority groups as typically found in empirical studies on differential academic performance. A methodological solution to the problem is suggested, and social policy implications are discussed. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

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

1980-01-01

The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

Analysis of categorical moderators in mixed-effects meta-analysis: Consequences of using pooled versus separate estimates of the residual between-studies variances.

PubMed

Rubio-Aparicio, María; Sánchez-Meca, Julio; López-López, José Antonio; Botella, Juan; Marín-Martínez, Fulgencio

2017-11-01

Subgroup analyses allow us to examine the influence of a categorical moderator on the effect size in meta-analysis. We conducted a simulation study using a dichotomous moderator, and compared the impact of pooled versus separate estimates of the residual between-studies variance on the statistical performance of the Q B (P) and Q B (S) tests for subgroup analyses assuming a mixed-effects model. Our results suggested that similar performance can be expected as long as there are at least 20 studies and these are approximately balanced across categories. Conversely, when subgroups were unbalanced, the practical consequences of having heterogeneous residual between-studies variances were more evident, with both tests leading to the wrong statistical conclusion more often than in the conditions with balanced subgroups. A pooled estimate should be preferred for most scenarios, unless the residual between-studies variances are clearly different and there are enough studies in each category to obtain precise separate estimates. © 2017 The British Psychological Society.

Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

PubMed

Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

2015-03-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

PubMed Central

Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

2015-01-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

Variance in response of pole-size trees and seedlings of Douglas-fir and western hemlock to nitrogen and phosphorus fertilizers.

Treesearch

M.A. Radwan; J.S. Shumway; D.S. Debell; J.M. Kraft

1991-01-01

Three experiments were conducted to determine effects of N and P fertilizers on growth and levels of plant-tissue nutrients of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and western hemlock (Tsuga heterophylla (Raf.) Sarg.). Both pole-size trees in closed-canopy stands and potted seedlings were use d . Soil series were...

Image variance and spatial structure in remotely sensed scenes. [South Dakota, California, Missouri, Kentucky, Louisiana, Tennessee, District of Columbia, and Oregon

NASA Technical Reports Server (NTRS)

Woodcock, C. E.; Strahler, A. H.

1984-01-01

Digital images derived by scanning air photos and through acquiring aircraft and spcecraft scanner data were studied. Results show that spatial structure in scenes can be measured and logically related to texture and image variance. Imagery data were used of a South Dakota forest; a housing development in Canoga Park, California; an agricltural area in Mississppi, Louisiana, Kentucky, and Tennessee; the city of Washington, D.C.; and the Klamath National Forest. Local variance, measured as the average standard deviation of brightness values within a three-by-three moving window, reaches a peak at a resolution cell size about two-thirds to three-fourths the size of the objects within the scene. If objects are smaller than the resolution cell size of the image, this peak does not occur and local variance simply decreases with increasing resolution as spatial averaging occurs. Variograms can also reveal the size, shape, and density of objects in the scene.

Approximate Sample Size Formulas for Testing Group Mean Differences when Variances Are Unequal in One-Way ANOVA

ERIC Educational Resources Information Center

Guo, Jiin-Huarng; Luh, Wei-Ming

2008-01-01

This study proposes an approach for determining appropriate sample size for Welch's F test when unequal variances are expected. Given a certain maximum deviation in population means and using the quantile of F and t distributions, there is no need to specify a noncentrality parameter and it is easy to estimate the approximate sample size needed…

Uncertainty in Population Estimates for Endangered Animals and Improving the Recovery Process

PubMed Central

Haines, Aaron M.; Zak, Matthew; Hammond, Katie; Scott, J. Michael; Goble, Dale D.; Rachlow, Janet L.

2013-01-01

Simple Summary The objective of our study was to evaluate the mention of uncertainty (i.e., variance) associated with population size estimates within U.S. recovery plans for endangered animals. To do this we reviewed all finalized recovery plans for listed terrestrial vertebrate species. We found that more recent recovery plans reported more estimates of population size and uncertainty. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty. We recommend that updated recovery plans combine uncertainty of population size estimates with a minimum detectable difference to aid in successful recovery. Abstract United States recovery plans contain biological information for a species listed under the Endangered Species Act and specify recovery criteria to provide basis for species recovery. The objective of our study was to evaluate whether recovery plans provide uncertainty (e.g., variance) with estimates of population size. We reviewed all finalized recovery plans for listed terrestrial vertebrate species to record the following data: (1) if a current population size was given, (2) if a measure of uncertainty or variance was associated with current estimates of population size and (3) if population size was stipulated for recovery. We found that 59% of completed recovery plans specified a current population size, 14.5% specified a variance for the current population size estimate and 43% specified population size as a recovery criterion. More recent recovery plans reported more estimates of current population size, uncertainty and population size as a recovery criterion. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty compared to reptiles and amphibians. We suggest the use of calculating minimum detectable differences to improve confidence when delisting endangered animals and we identified incentives for individuals to get involved in recovery planning to improve access to quantitative data. PMID:26479531

Effect size for the main cognitive function determinants in a large cross-sectional study.

PubMed

Mura, T; Amieva, H; Goldberg, M; Dartigues, J-F; Ankri, J; Zins, M; Berr, C

2016-11-01

The aim of our study was to examine the effect sizes of different cognitive function determinants in middle and early old age. Cognitive functions were assessed in 11 711 volunteers (45 to 75 years old), included in the French CONSTANCES cohort between January 2012 and May 2014, using the free and cued selective reminding test (FCSRT), verbal fluency tasks, digit-symbol substitution test (DSST) and trail making test (TMT), parts A and B. The effect sizes of socio-demographic (age, sex, education), lifestyle (alcohol, tobacco, physical activity), cardiovascular (diabetes, blood pressure) and psychological (depressive symptomatology) variables were computed as omega-squared coefficients (ω 2 ; part of the variation of a neuropsychological score that is independently explained by a given variable). These sets of variables explained from R 2 = 10% (semantic fluency) to R 2 = 26% (DSST) of the total variance. In all tests, socio-demographic variables accounted for the greatest part of the explained variance. Age explained from ω 2 = 0.5% (semantic fluency) to ω 2 = 7.5% (DSST) of the total score variance, gender from ω 2 = 5.2% (FCSRT) to a negligible part (semantic fluency or TMT) and education from ω 2 = 7.2% (DSST) to ω 2 = 1.4% (TMT-A). Behavioral, cardiovascular and psychological variables only slightly influenced the cognitive test results (all ω 2 < 0.8%, most ω 2 < 0.1%). Socio-demographic variables (age, gender and education) are the main variables associated with cognitive performance variations between 45 and 75 years of age in the general population. © 2016 EAN.

Finite-size analysis of continuous-variable measurement-device-independent quantum key distribution

NASA Astrophysics Data System (ADS)

Zhang, Xueying; Zhang, Yichen; Zhao, Yijia; Wang, Xiangyu; Yu, Song; Guo, Hong

2017-10-01

We study the impact of the finite-size effect on the continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) protocol, mainly considering the finite-size effect on the parameter estimation procedure. The central-limit theorem and maximum likelihood estimation theorem are used to estimate the parameters. We also analyze the relationship between the number of exchanged signals and the optimal modulation variance in the protocol. It is proved that when Charlie's position is close to Bob, the CV-MDI QKD protocol has the farthest transmission distance in the finite-size scenario. Finally, we discuss the impact of finite-size effects related to the practical detection in the CV-MDI QKD protocol. The overall results indicate that the finite-size effect has a great influence on the secret-key rate of the CV-MDI QKD protocol and should not be ignored.

Standard Deviation for Small Samples

ERIC Educational Resources Information Center

Joarder, Anwar H.; Latif, Raja M.

2006-01-01

Neater representations for variance are given for small sample sizes, especially for 3 and 4. With these representations, variance can be calculated without a calculator if sample sizes are small and observations are integers, and an upper bound for the standard deviation is immediate. Accessible proofs of lower and upper bounds are presented for…

Larger Mammalian Body Size Leads to Lower Retroviral Activity

PubMed Central

Katzourakis, Aris; Magiorkinis, Gkikas; Lim, Aaron G.; Gupta, Sunetra; Belshaw, Robert; Gifford, Robert

2014-01-01

Retroviruses have been infecting mammals for at least 100 million years, leaving descendants in host genomes known as endogenous retroviruses (ERVs). The abundance of ERVs is partly determined by their mode of replication, but it has also been suggested that host life history traits could enhance or suppress their activity. We show that larger bodied species have lower levels of ERV activity by reconstructing the rate of ERV integration across 38 mammalian species. Body size explains 37% of the variance in ERV integration rate over the last 10 million years, controlling for the effect of confounding due to other life history traits. Furthermore, 68% of the variance in the mean age of ERVs per genome can also be explained by body size. These results indicate that body size limits the number of recently replicating ERVs due to their detrimental effects on their host. To comprehend the possible mechanistic links between body size and ERV integration we built a mathematical model, which shows that ERV abundance is favored by lower body size and higher horizontal transmission rates. We argue that because retroviral integration is tumorigenic, the negative correlation between body size and ERV numbers results from the necessity to reduce the risk of cancer, under the assumption that this risk scales positively with body size. Our model also fits the empirical observation that the lifetime risk of cancer is relatively invariant among mammals regardless of their body size, known as Peto's paradox, and indicates that larger bodied mammals may have evolved mechanisms to limit ERV activity. PMID:25033295

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events

PubMed Central

Vincenzi, Simone

2014-01-01

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an ‘extinction window’ of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the ‘extinction window’, although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. PMID:24920116

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.

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

PubMed

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

2017-09-14

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

Uncertainty in Population Estimates for Endangered Animals and Improving the Recovery Process.

PubMed

Haines, Aaron M; Zak, Matthew; Hammond, Katie; Scott, J Michael; Goble, Dale D; Rachlow, Janet L

2013-08-13

United States recovery plans contain biological information for a species listed under the Endangered Species Act and specify recovery criteria to provide basis for species recovery. The objective of our study was to evaluate whether recovery plans provide uncertainty (e.g., variance) with estimates of population size. We reviewed all finalized recovery plans for listed terrestrial vertebrate species to record the following data: (1) if a current population size was given, (2) if a measure of uncertainty or variance was associated with current estimates of population size and (3) if population size was stipulated for recovery. We found that 59% of completed recovery plans specified a current population size, 14.5% specified a variance for the current population size estimate and 43% specified population size as a recovery criterion. More recent recovery plans reported more estimates of current population size, uncertainty and population size as a recovery criterion. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty compared to reptiles and amphibians. We suggest the use of calculating minimum detectable differences to improve confidence when delisting endangered animals and we identified incentives for individuals to get involved in recovery planning to improve access to quantitative data.

Evidence for Gender-Dependent Genotype by Environment Interaction in Adult Depression.

PubMed

Molenaar, Dylan; Middeldorp, Christel M; Willemsen, Gonneke; Ligthart, Lannie; Nivard, Michel G; Boomsma, Dorret I

2015-10-14

Depression in adults is heritable with about 40 % of the phenotypic variance due to additive genetic effects and the remaining phenotypic variance due to unique (unshared) environmental effects. Common environmental effects shared by family members are rarely found in adults. One possible explanation for this finding is that there is an interaction between genes and the environment which may mask effects of the common environment. To test this hypothesis, we investigated genotype by environment interaction in a large sample of female and male adult twins aged 18-70 years. The anxious depression subscale of the Adult Self Report from the Achenbach System of Empirically Based Assessment (Achenbach and Rescorla in Manual for the ASEBA adult: forms and profiles, 2003) was completed by 13,022 twins who participate in longitudinal studies of the Netherlands Twin Register. In a single group analysis, we found genotype by unique environment interaction, but no genotype by common environment interaction. However, when conditioning on gender, we observed genotype by common environment interaction in men, with larger common environmental variance in men who are genetically less at risk to develop depression. Although the effect size of the interaction is characterized by large uncertainty, the results show that there is at least some variance due to the common environment in adult depression in men.

The Effect of the Multivariate Box-Cox Transformation on the Power of MANOVA.

ERIC Educational Resources Information Center

Kirisci, Levent; Hsu, Tse-Chi

Most of the multivariate statistical techniques rely on the assumption of multivariate normality. The effects of non-normality on multivariate tests are assumed to be negligible when variance-covariance matrices and sample sizes are equal. Therefore, in practice, investigators do not usually attempt to remove non-normality. In this simulation…

Determinants of male floating behaviour and floater reproduction in a threatened population of the hihi (Notiomystis cincta)

PubMed Central

Brekke, Patricia; Ewen, John G; Clucas, Gemma; Santure, Anna W

2015-01-01

Floating males are usually thought of as nonbreeders. However, some floating individuals are able to reproduce through extra-pair copulations. Floater reproductive success can impact breeders’ sex ratio, reproductive variance, multiple paternity and inbreeding, particularly in small populations. Changes in reproductive variance alter the rate of genetic drift and loss of genetic diversity. Therefore, genetic management of threatened species requires an understanding of floater reproduction and determinants of floating behaviour to effectively conserve species. Here, we used a pedigreed, free-living population of the endangered New Zealand hihi (Notiomystis cincta) to assess variance in male reproductive success and test the genetic (inbreeding and heritability) and conditional (age and size) factors that influence floater behaviour and reproduction. Floater reproduction is common in this species. However, floater individuals have lower reproductive success and variance in reproductive success than territorial males (total and extra-pair fledglings), so their relative impact on the population's reproductive performance is low. Whether an individual becomes a floater, and if so then how successful they are, is determined mainly by individual age (young and old) and to lesser extents male size (small) and inbreeding level (inbred). Floating males have a small, but important role in population reproduction and persistence of threatened populations. PMID:26366197

Assessing differential gene expression with small sample sizes in oligonucleotide arrays using a mean-variance model.

PubMed

Hu, Jianhua; Wright, Fred A

2007-03-01

The identification of the genes that are differentially expressed in two-sample microarray experiments remains a difficult problem when the number of arrays is very small. We discuss the implications of using ordinary t-statistics and examine other commonly used variants. For oligonucleotide arrays with multiple probes per gene, we introduce a simple model relating the mean and variance of expression, possibly with gene-specific random effects. Parameter estimates from the model have natural shrinkage properties that guard against inappropriately small variance estimates, and the model is used to obtain a differential expression statistic. A limiting value to the positive false discovery rate (pFDR) for ordinary t-tests provides motivation for our use of the data structure to improve variance estimates. Our approach performs well compared to other proposed approaches in terms of the false discovery rate.

Sample size calculation for studies with grouped survival data.

PubMed

Li, Zhiguo; Wang, Xiaofei; Wu, Yuan; Owzar, Kouros

2018-06-10

Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples. Copyright © 2018 John Wiley & Sons, Ltd.

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

PubMed

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

1998-04-01

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

Effects of different crumb rubber sizes on the flowability and compressive strength of hybrid fibre reinforced ECC

NASA Astrophysics Data System (ADS)

Khed, Veerendrakumar C.; Mohammed, Bashar S.; Fadhil Nuruddin, Muhd

2018-04-01

The different sizes of crumb rubber have been used to investigate the effects on flowability and the compressive strength of the hybrid fibre reinforced engineered cementitious composite. Two sizes of crumb rubber 30 mesh and 1 to 3mm were used in partial replacement with the fine aggregate up to 60%. The experimental study was carried out through mathematical and statistical analysis by response surface methodology (RSM) using the Design Expert software. The response models have been developed and the results were validated by analysis of variance (ANOVA). It was found that finer sized crumb rubber inclusion had produced better workability and higher compressive strength when compared to the larger size and it was concluded that crumb rubber has negative effect on compressive strength and positive effect on workability. The optimization results are found to an approximately good agreement with the experimental results.

The ties that bind what is known to the recall of what is new.

PubMed

Nelson, D L; Zhang, N

2000-12-01

Cued recall success varies with what people know and with what they do during an episode. This paper focuses on prior knowledge and disentangles the relative effects of 10 features of words and their relationships on cued recall. Results are reported for correlational and multiple regression analyses of data obtained from free association norms and from 29 experiments. The 10 features were only weakly correlated with each other in the norms and, with notable exceptions, in the experiments. The regression analysis indicated that forward cue-to-target strength explained the most variance, followed by backward target-to-cue strength. Target connectivity and set size explained the next most variance, along with mediated cue-to-target strength. Finally, frequency, concreteness, shared associate strength, and cue set size also contributed significantly to recall. Taken together, indices of prior word knowledge explain 49% of the recall variance. Theoretically driven equations that use free association to predict cued recall were also evaluated. Each equation was designed to condense multiple indices of word interconnectivity into a single predictor.

The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

ERIC Educational Resources Information Center

Miller, Geoffrey F.; Penke, Lars

2007-01-01

Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

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. 

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.

IN-STREAM AND WATERSHED PREDICTORS OF GENETIC DIVERSITY, EFFECTIVE POPULATION SIZE AND IMMIGRATION ACROSS RIVER-STREAM NETWORKS

EPA Science Inventory

The influence of spatial processes on population dynamics within river-stream networks is poorly understood. Utilizing spatially explicit analyses of temporal genetic variance, we examined whether persistence of Central Stonerollers (Campostoma anomalum) reflects differences in h...

Eta Squared and Partial Eta Squared as Measures of Effect Size in Educational Research

ERIC Educational Resources Information Center

Richardson, John T. E.

2011-01-01

Eta squared measures the proportion of the total variance in a dependent variable that is associated with the membership of different groups defined by an independent variable. Partial eta squared is a similar measure in which the effects of other independent variables and interactions are partialled out. The development of these measures is…

A Preliminary Study of the Effects of Within-Group Covariance Structure on Recovery in Cluster Analysis. Research Report RR-94-46.

ERIC Educational Resources Information Center

Donoghue, John R.

Monte Carlo studies investigated effects of within-group covariance structure on subgroup recovery by several widely used hierarchical clustering methods. In Study 1, subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. All clustering methods were strongly affected by…

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events.

PubMed

Vincenzi, Simone

2014-08-06

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an 'extinction window' of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the 'extinction window', although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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.

Testlet-Based Multidimensional Adaptive Testing.

PubMed

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

On the origin of size-dependent and size-independent crystal growth: Influence of advection and diffusion

USGS Publications Warehouse

Kile, D.E.; Eberl, D.D.

2003-01-01

Crystal growth experiments were conducted using potassium alum and calcite crystals in aqueous solution under both non-stirred and stirred conditions to elucidate the mechanism for size-dependent (proportionate) and size-independent (constant) crystal growth. Growth by these two laws can be distinguished from each other because the relative size difference among crystals is maintained during proportionate growth, leading to a constant crystal size variance (??2) for a crystal size distribution (CSD) as the mean size increases. The absolute size difference among crystals is maintained during constant growth, resulting in a decrease in size variance. Results of these experiments show that for centimeter-sized alum crystals, proportionate growth occurs in stirred systems, whereas constant growth occurs in non-stirred systems. Accordingly, the mechanism for proportionate growth is hypothesized to be related to the supply of reactants to the crystal surface by advection, whereas constant growth is related to supply by diffusion. Paradoxically, micrometer-sized calcite crystals showed proportionate growth both in stirred and in non-stirred systems. Such growth presumably results from the effects of convection and Brownian motion, which promote an advective environment and hence proportionate growth for minute crystals in non-stirred systems, thereby indicating the importance of solution velocity relative to crystal size. Calcite crystals grown in gels, where fluid motion was minimized, showed evidence for constant, diffusion-controlled growth. Additional investigations of CSDs of naturally occurring crystals indicate that proportionate growth is by far the most common growth law, thereby suggesting that advection, rather than diffusion, is the dominant process for supplying reactants to crystal surfaces.

Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

PubMed

Vitezica, Zulma G; Varona, Luis; Elsen, Jean-Michel; Misztal, Ignacy; Herring, William; Legarra, Andrès

2016-01-29

Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations. We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population. We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.

Variation in Seed Germination of 134 Common Species on the Eastern Tibetan Plateau: Phylogenetic, Life History and Environmental Correlates

PubMed Central

Xu, Jing; Li, Wenlong; Zhang, Chunhui; Liu, Wei; Du, Guozhen

2014-01-01

Seed germination is a crucial stage in the life history of a species because it represents the pathway from adult to offspring, and it can affect the distribution and abundance of species in communities. In this study, we examined the effects of phylogenetic, life history and environmental factors on seed germination of 134 common species from an alpine/subalpine meadow on the eastern Tibetan Plateau. In one-way ANOVAs, phylogenetic groups (at or above order) explained 13.0% and 25.9% of the variance in germination percentage and mean germination time, respectively; life history attributes, such as seed size, dispersal mode, explained 3.7%, 2.1% of the variance in germination percentage and 6.3%, 8.7% of the variance in mean germination time, respectively; the environmental factors temperature and habitat explained 4.7%, 1.0% of the variance in germination percentage and 13.5%, 1.7% of the variance in mean germination time, respectively. Our results demonstrated that elevated temperature would lead to a significant increase in germination percentage and an accelerated germination. Multi-factorial ANOVAs showed that the three major factors contributing to differences in germination percentage and mean germination time in this alpine/subalpine meadow were phylogenetic attributes, temperature and seed size (explained 10.5%, 4.7% and 1.4% of the variance in germination percentage independently, respectively; and explained 14.9%, 13.5% and 2.7% of the variance in mean germination time independently, respectively). In addition, there were strong associations between phylogenetic group and life history attributes, and between life history attributes and environmental factors. Therefore, germination variation are constrained mainly by phylogenetic inertia in a community, and seed germination variation correlated with phylogeny is also associated with life history attributes, suggesting a role of niche adaptation in the conservation of germination variation within lineages. Meanwhile, selection can maintain the association between germination behavior and the environmental conditions within a lineage. PMID:24893308

CAPN1, CAST, and DGAT1 genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in a beef cattle population selected for haplotype and allele equalization

USDA-ARS?s Scientific Manuscript database

Genetic marker effects and type of inheritance are estimated with poor precision when minor marker allele frequencies are low. A stable composite population (MARC III) was subjected to marker assisted selection for multiple years to equalize specific marker frequencies to 1) estimate effect size an...

µ-Calpain, calpastatin, and growth hormone receptor genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in Angus cattle selected to increase minor haplotype ... frequencies

USDA-ARS?s Scientific Manuscript database

Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size an...

Effects of decreasing resolution on spectral and spatial information content in an agricultural area. [Pottawatmie study site, Iowa and Nebraska

NASA Technical Reports Server (NTRS)

1983-01-01

The effects of decreasing spatial resolution from 6 1/4 miles square to 50 miles square are described. The effects of increases in cell size is studied on; the mean and variance of spectral data; spatial trends; and vegetative index numbers. Information content changes on cadastral, vegetal, soil, water and physiographic information are summarized.

Time-dependent solutions for a stochastic model of gene expression with molecule production in the form of a compound Poisson process.

PubMed

Jędrak, Jakub; Ochab-Marcinek, Anna

2016-09-01

We study a stochastic model of gene expression, in which protein production has a form of random bursts whose size distribution is arbitrary, whereas protein decay is a first-order reaction. We find exact analytical expressions for the time evolution of the cumulant-generating function for the most general case when both the burst size probability distribution and the model parameters depend on time in an arbitrary (e.g., oscillatory) manner, and for arbitrary initial conditions. We show that in the case of periodic external activation and constant protein degradation rate, the response of the gene is analogous to the resistor-capacitor low-pass filter, where slow oscillations of the external driving have a greater effect on gene expression than the fast ones. We also demonstrate that the nth cumulant of the protein number distribution depends on the nth moment of the burst size distribution. We use these results to show that different measures of noise (coefficient of variation, Fano factor, fractional change of variance) may vary in time in a different manner. Therefore, any biological hypothesis of evolutionary optimization based on the nonmonotonic dependence of a chosen measure of noise on time must justify why it assumes that biological evolution quantifies noise in that particular way. Finally, we show that not only for exponentially distributed burst sizes but also for a wider class of burst size distributions (e.g., Dirac delta and gamma) the control of gene expression level by burst frequency modulation gives rise to proportional scaling of variance of the protein number distribution to its mean, whereas the control by amplitude modulation implies proportionality of protein number variance to the mean squared.

Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data.

PubMed

Vasan, Ramachandran S; Glazer, Nicole L; Felix, Janine F; Lieb, Wolfgang; Wild, Philipp S; Felix, Stephan B; Watzinger, Norbert; Larson, Martin G; Smith, Nicholas L; Dehghan, Abbas; Grosshennig, Anika; Schillert, Arne; Teumer, Alexander; Schmidt, Reinhold; Kathiresan, Sekar; Lumley, Thomas; Aulchenko, Yurii S; König, Inke R; Zeller, Tanja; Homuth, Georg; Struchalin, Maksim; Aragam, Jayashri; Bis, Joshua C; Rivadeneira, Fernando; Erdmann, Jeanette; Schnabel, Renate B; Dörr, Marcus; Zweiker, Robert; Lind, Lars; Rodeheffer, Richard J; Greiser, Karin Halina; Levy, Daniel; Haritunians, Talin; Deckers, Jaap W; Stritzke, Jan; Lackner, Karl J; Völker, Uwe; Ingelsson, Erik; Kullo, Iftikhar; Haerting, Johannes; O'Donnell, Christopher J; Heckbert, Susan R; Stricker, Bruno H; Ziegler, Andreas; Reffelmann, Thorsten; Redfield, Margaret M; Werdan, Karl; Mitchell, Gary F; Rice, Kenneth; Arnett, Donna K; Hofman, Albert; Gottdiener, John S; Uitterlinden, Andre G; Meitinger, Thomas; Blettner, Maria; Friedrich, Nele; Wang, Thomas J; Psaty, Bruce M; van Duijn, Cornelia M; Wichmann, H-Erich; Munzel, Thomas F; Kroemer, Heyo K; Benjamin, Emelia J; Rotter, Jerome I; Witteman, Jacqueline C; Schunkert, Heribert; Schmidt, Helena; Völzke, Henry; Blankenberg, Stefan

2009-07-08

Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

The Effects of Teacher Efficacy, Teacher Certification Route, Content Hours in the Sciences, Field-Based Experiences and Class Size on Middle School Student Achievement

NASA Astrophysics Data System (ADS)

Salgado, Robina

No Child Left Behind Act (NCLB) was signed into law in 2002 with the idea that all students, no matter the circumstances can learn and that highly qualified teachers should be present in every classrooms (United Stated Department of Education, 2011). The mandates of NCLB also forced states to begin measuring the progress of science proficiency beginning in 2007. The study determined the effects of teacher efficacy, the type of certification route taken by individuals, the number of content hours taken in the sciences, field-based experience and class size on middle school student achievement as measured by the 8th grade STAAR in a region located in South Texas. This data provides knowledge into the effect different teacher training methods have on secondary school science teacher efficacy in Texas and how it impacts student achievement. Additionally, the results of the study determined if traditional and alternative certification programs are equally effective in properly preparing science teachers for the classroom. The study described was a survey design comparing nonequivalent groups. The study utilized the Science Teaching Efficacy Belief Instrument (STEBI). A 25-item efficacy scale made up of two subscales, Personal Science Teaching Efficacy Belief (PSTE) and Science Teaching Outcome Expectancy (STOE) (Bayraktar, 2011). Once the survey was completed a 3-Way ANOVA, MANOVA, and Multiple Linear Regression were performed in SPSS to calculate the results. The results from the study indicated no significant difference between route of certification on student achievement, but a large effect size was reported, 17% of the variances in student achievement can be accounted for by route of certification. A MANOVA was conducted to assess the differences between number of science content hours on a linear combination of personal science teacher efficacy, science teaching outcome expectancy and total science teacher efficacy as measured by the STEBI. No significant difference was found, but a large effect size was reported, 14% of variances in efficacy can be accounted for by number of science content hours. A Multiple Linear Regression analysis was conducted to evaluate how total personal efficacy, total outcome expectancy and total teacher efficacy predict student achievement. A significant regression equation was found, with an R2 of .39. The R 2 reflected a high effect size, where 39% of variances in student achievement can be explained by efficacy. Total efficacy of the teacher was a significant predictor of student achievement.

An alternative approach to confidence interval estimation for the win ratio statistic.

PubMed

Luo, Xiaodong; Tian, Hong; Mohanty, Surya; Tsai, Wei Yann

2015-03-01

Pocock et al. (2012, European Heart Journal 33, 176-182) proposed a win ratio approach to analyzing composite endpoints comprised of outcomes with different clinical priorities. In this article, we establish a statistical framework for this approach. We derive the null hypothesis and propose a closed-form variance estimator for the win ratio statistic in all pairwise matching situation. Our simulation study shows that the proposed variance estimator performs well regardless of the magnitude of treatment effect size and the type of the joint distribution of the outcomes. © 2014, The International Biometric Society.

Tests of Mediation: Paradoxical Decline in Statistical Power as a Function of Mediator Collinearity

ERIC Educational Resources Information Center

Beasley, T. Mark

2014-01-01

Increasing the correlation between the independent variable and the mediator ("a" coefficient) increases the effect size ("ab") for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation caused by…

[Practical aspects regarding sample size in clinical research].

PubMed

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

1996-01-01

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

The Genealogical Consequences of Fecundity Variance Polymorphism

PubMed Central

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

On the error in crop acreage estimation using satellite (LANDSAT) data

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator)

1983-01-01

The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

Effects of after-school programs with at-risk youth on attendance and externalizing behaviors: a systematic review and meta-analysis.

PubMed

Kremer, Kristen P; Maynard, Brandy R; Polanin, Joshua R; Vaughn, Michael G; Sarteschi, Christine M

2015-03-01

The popularity, demand, and increased federal and private funding for after-school programs have resulted in a marked increase in after-school programs over the past two decades. After-school programs are used to prevent adverse outcomes, decrease risks, or improve functioning with at-risk youth in several areas, including academic achievement, crime and behavioral problems, socio-emotional functioning, and school engagement and attendance; however, the evidence of effects of after-school programs remains equivocal. This systematic review and meta-analysis, following Campbell Collaboration guidelines, examined the effects of after-school programs on externalizing behaviors and school attendance with at-risk students. A systematic search for published and unpublished literature resulted in the inclusion of 24 studies. A total of 64 effect sizes (16 for attendance outcomes; 49 for externalizing behavior outcomes) extracted from 31 reports were included in the meta-analysis using robust variance estimation to handle dependencies among effect sizes. Mean effects were small and non-significant for attendance and externalizing behaviors. A moderate to large amount of heterogeneity was present; however, no moderator variable tested explained the variance between studies. Significant methodological shortcomings were identified across the corpus of studies included in this review. Implications for practice, policy and research are discussed.

Effects of After-School Programs with At-Risk Youth on Attendance and Externalizing Behaviors: A Systematic Review and Meta-Analysis

PubMed Central

Maynard, Brandy R.; Polanin, Joshua R.; Vaughn, Michael G.; Sarteschi, Christine M.

2015-01-01

The popularity, demand, and increased federal and private funding for after-school programs have resulted in a marked increase in after-school programs over the past two decades. After-school programs are used to prevent adverse outcomes, decrease risks, or improve functioning with at-risk youth in several areas, including academic achievement, crime and behavioral problems, socio-emotional functioning, and school engagement and attendance; however, the evidence of effects of after-school programs remains equivocal. This systematic review and meta-analysis, following Campbell Collaboration guidelines, examined the effects of after-school programs on externalizing behaviors and school attendance with at-risk students. A systematic search for published and unpublished literature resulted in the inclusion of 24 studies. A total of 64 effect sizes (16 for attendance outcomes; 49 for externalizing behavior outcomes) extracted from 31 reports were included in the meta-analysis using robust variance estimation to handle dependencies among effect sizes. Mean effects were small and non-significant for attendance and externalizing behaviors. A moderate to large amount of heterogeneity was present; however, no moderator variable tested explained the variance between studies. Significant methodological shortcomings were identified across the corpus of studies included in this review. Implications for practice, policy and research are discussed. PMID:25416228

Remote sensing of environmental particulate pollutants - Optical methods for determinations of size distribution and complex refractive index

NASA Technical Reports Server (NTRS)

Fymat, A. L.

1978-01-01

A unifying approach, based on a generalization of Pearson's differential equation of statistical theory, is proposed for both the representation of particulate size distribution and the interpretation of radiometric measurements in terms of this parameter. A single-parameter gamma-type distribution is introduced, and it is shown that inversion can only provide the dimensionless parameter, r/ab (where r = particle radius, a = effective radius, b = effective variance), at least when the distribution vanishes at both ends. The basic inversion problem in reconstructing the particle size distribution is analyzed, and the existing methods are reviewed (with emphasis on their capabilities) and classified. A two-step strategy is proposed for simultaneously determining the complex refractive index and reconstructing the size distribution of atmospheric particulates.

[Effective size of subpopulation of the early run sockeye salmon Oncorhynchus nerka from Azabach's Lake (Kamchatka): effect of density on variance of reproductive success].

PubMed

Efremov, V V; Parenskiĭ, V A

2004-04-01

Using Parensky's approach for estimating the number of breeding pairs, we determined effective subpopulation size Ne in early-run sockeye salmon Oncorhynchus nerka from Azabach'e Lake (Kamchatka) in 1977 through 1981. On average (over years and populations), biased sex ratio decreased Ne by 7% as compared to the number of fish on the spawning sites (Ni). High density reduced the Ne/Ni ratio by 62-66% because some fish were excluded from spawning. Dominance polygyny as compared to monogamy and random union of gametes could reduce Ne by about 17%.

EVOLUTION, PHYLOGENY, SEXUAL DIMORPHISM AND MATING SYSTEM IN THE GRACKLES (QUISCALUS SPP.: ICTERINAE).

PubMed

Björklund, Mats

1991-05-01

According to theory, two consequences of sexual selection are sexual dimorphism in size and secondary sexual characteristics, due to either intra- or intersexual selection. In this paper I suggest three criteria for the test of an evolutionary hypothesis involving quantitative morphological characters. First, the postulated change must be shown to have occurred in evolutionary time. Second, this change must be positively correlated with a change in the proposed selective agent. Third, given two taxa with different degrees of sexual size dimorphism and different mating system, the possible influence of drift must be rejected. If the hypothesis is not rejected by these three criteria, then we still have no proof of causality, but we can at least be more confident about its plausibility. This is applied to the particular hypothesis that sexual dimorphism in the Boat-tailed and Great-tailed grackles (Quiscalus spp; Icterinae; Aves) is caused by the highly polygynous mating system in these species. In relation to an outgroup, both species have increased disproportionately in male tarsus and tail size, creating an increased sexual dimorphism. This has cooccurred with the evolution of their particular mating system. However, the variance among species in male tarsus size can be accounted for by drift, and need not be a result of selection for increased size. In contrast, the variance among species in male tail size was much larger than expected under a null model of drift, indicating directional selection for long tails. The variance in female tail size was not larger than expected by drift, whereas the variance in female tarsus size was in fact lower than expected by drift, indicating stabilizing selection. The data are consistent with the hypothesis with regard to tail size, but not with regard to body size. © 1991 The Society for the Study of Evolution.

Genetic Variance in the F2 Generation of Divergently Selected Parents

Treesearch

M.P. Koshy; G. Namkoong; J.H. Roberds

1998-01-01

Either by selective breeding for population divergence or by using natural population differences, F2 and advanced generation hybrids can be developed with high variances. We relate the size of the genetic variance to the population divergence based on a forward and backward mutation model at a locus with two alleles with additive gene action....

Local extinction and recolonization, species effective population size, and modern human origins.

PubMed

Eller, Elise; Hawks, John; Relethford, John H

2004-10-01

A primary objection from a population genetics perspective to a multiregional model of modern human origins is that the model posits a large census size, whereas genetic data suggest a small effective population size. The relationship between census size and effective size is complex, but arguments based on an island model of migration show that if the effective population size reflects the number of breeding individuals and the effects of population subdivision, then an effective population size of 10,000 is inconsistent with the census size of 500,000 to 1,000,000 that has been suggested by archeological evidence. However, these models have ignored the effects of population extinction and recolonization, which increase the expected variance among demes and reduce the inbreeding effective population size. Using models developed for population extinction and recolonization, we show that a large census size consistent with the multiregional model can be reconciled with an effective population size of 10,000, but genetic variation among demes must be high, reflecting low interdeme migration rates and a colonization process that involves a small number of colonists or kin-structured colonization. Ethnographic and archeological evidence is insufficient to determine whether such demographic conditions existed among Pleistocene human populations, and further work needs to be done. More realistic models that incorporate isolation by distance and heterogeneity in extinction rates and effective deme sizes also need to be developed. However, if true, a process of population extinction and recolonization has interesting implications for human demographic history.

4D MRI of polycystic kidneys from rapamycin-treated Glis3-deficient mice

PubMed Central

Xie, Luke; Qi, Yi; Subashi, Ergys; Liao, Grace; Miller DeGraff, Laura; Jetten, Anton M.; Johnson, G. Allan

2015-01-01

Polycystic kidney disease (PKD) is a life-threatening disease that leads to a grotesque enlargement of the kidney and significant lose of function. Several imaging studies with MRI have demonstrated that cyst size in polycystic kidneys can determine disease severity and progression. In the present study, we found that while kidney volume and cyst volume decreased with drug treatment, renal function did not improve with treatment. Here, we applied dynamic contrast-enhanced MRI to study PKD in a Glis3-deficient mouse model. Cysts from this model have a wide range of sizes and develop at an early age. To capture this crucial stage and assess cysts in detail, we imaged during early development (3 to 17 weeks) and applied high spatiotemporal resolution MRI (125×125×125 cubic microns every 7.7 seconds). A drug treatment with rapamycin (also known as sirolimus) was applied to determine whether disease progression could be halted. The effect and synergy (interaction) of aging and treatment were evaluated using an analysis of variance (ANOVA). Structural measurements including kidney volume, cyst volume, and cyst-kidney volume ratio changed significantly with age. Drug treatment significantly decreased these metrics. Functional measurements of time-to-peak (TTP) mean and TTP variance were determined. TTP mean did not change with age, while TTP variance increased with age. The treatment of rapamycin generally did not affect these functional metrics. Synergistic effects of treatment and age were not found for any measurements. Together, the size and volume ratio of cysts decreased with drug treatment, while renal function remained the same. Quantifying renal structure and function with MRI can comprehensively assess the pathophysiology of PKD and response to treatment. PMID:25810360

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

PubMed

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Technical and biological variance structure in mRNA-Seq data: life in the real world

PubMed Central

2012-01-01

Background mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. Results In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. Conclusions These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems. PMID:22769017

The impact of hypnotic suggestibility in clinical care settings.

PubMed

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

2011-07-01

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

The impact of hypnotic suggestibility in clinical care settings

PubMed Central

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

2013-01-01

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

Unexpected finite size effects in interfacial systems: Why bigger is not always better—Increase in uncertainty of surface tension with bulk phase width

NASA Astrophysics Data System (ADS)

Longford, Francis G. J.; Essex, Jonathan W.; Skylaris, Chris-Kriton; Frey, Jeremy G.

2018-06-01

We present an unexpected finite size effect affecting interfacial molecular simulations that is proportional to the width-to-surface-area ratio of the bulk phase Ll/A. This finite size effect has a significant impact on the variance of surface tension values calculated using the virial summation method. A theoretical derivation of the origin of the effect is proposed, giving a new insight into the importance of optimising system dimensions in interfacial simulations. We demonstrate the consequences of this finite size effect via a new way to estimate the surface energetic and entropic properties of simulated air-liquid interfaces. Our method is based on macroscopic thermodynamic theory and involves comparing the internal energies of systems with varying dimensions. We present the testing of these methods using simulations of the TIP4P/2005 water forcefield and a Lennard-Jones fluid model of argon. Finally, we provide suggestions of additional situations, in which this finite size effect is expected to be significant, as well as possible ways to avoid its impact.

A standardized mean difference effect size for multiple baseline designs across individuals.

PubMed

Hedges, Larry V; Pustejovsky, James E; Shadish, William R

2013-12-01

Single-case designs are a class of research methods for evaluating treatment effects by measuring outcomes repeatedly over time while systematically introducing different condition (e.g., treatment and control) to the same individual. The designs are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single-case designs have focused attention on methods for summarizing and meta-analyzing findings and on the need for effect sizes indices that are comparable to those used in between-subjects designs. In the previous work, we discussed how to define and estimate an effect size that is directly comparable to the standardized mean difference often used in between-subjects research based on the data from a particular type of single-case design, the treatment reversal or (AB)(k) design. This paper extends the effect size measure to another type of single-case study, the multiple baseline design. We propose estimation methods for the effect size and its variance, study the estimators using simulation, and demonstrate the approach in two applications. Copyright © 2013 John Wiley & Sons, Ltd.

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

PubMed

Li, Johnson Ching-Hong

2016-12-01

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

Use of "t"-Test and ANOVA in Career-Technical Education Research

ERIC Educational Resources Information Center

Rojewski, Jay W.; Lee, In Heok; Gemici, Sinan

2012-01-01

Use of t-tests and analysis of variance (ANOVA) procedures in published research from three scholarly journals in career and technical education (CTE) during a recent 5-year period was examined. Information on post hoc analyses, reporting of effect size, alpha adjustments to account for multiple tests, power, and examination of assumptions…

Quadratic elongation: A quantitative measure of distortion in coordination polyhedra

USGS Publications Warehouse

Robinson, Kelly F.; Gibbs, G.V.; Ribbe, P.H.

1971-01-01

Quadratic elongation and the variance of bond angles are linearly correlated for distorted octahedral and tetrahedral coordination complexes, both of which show variations in bond length and bond angle. The quadratic elonga tion is dimensionless, giving a quantitative measure of polyhedral distortion which is independent of the effective size of the polyhedron.

Incorporating Quality Scores in Meta-Analysis

ERIC Educational Resources Information Center

Ahn, Soyeon; Becker, Betsy Jane

2011-01-01

This paper examines the impact of quality-score weights in meta-analysis. A simulation examines the roles of study characteristics such as population effect size (ES) and its variance on the bias and mean square errors (MSEs) of the estimators for several patterns of relationship between quality and ES, and for specific patterns of systematic…

Power analysis to detect treatment effect in longitudinal studies with heterogeneous errors and incomplete data.

PubMed

Vallejo, Guillermo; Ato, Manuel; Fernández García, Paula; Livacic Rojas, Pablo E; Tuero Herrero, Ellián

2016-08-01

 S. Usami (2014) describes a method to realistically determine sample size in longitudinal research using a multilevel model. The present research extends the aforementioned work to situations where it is likely that the assumption of homogeneity of the errors across groups is not met and the error term does not follow a scaled identity covariance structure.   For this purpose, we followed a procedure based on transforming the variance components of the linear growth model and the parameter related to the treatment effect into specific and easily understandable indices. At the same time, we provide the appropriate statistical machinery for researchers to use when data loss is unavoidable, and changes in the expected value of the observed responses are not linear.   The empirical powers based on unknown variance components were virtually the same as the theoretical powers derived from the use of statistically processed indexes.   The main conclusion of the study is the accuracy of the proposed method to calculate sample size in the described situations with the stipulated power criteria.

Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

PubMed

Lebigre, Christophe; Arcese, Peter; Reid, Jane M

2013-07-01

Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased the variance in age-specific reproductive success relative to the social mating system to a degree that increased across successive age classes. This comprehensive decomposition of the total variances in age-specific reproductive success and LRS into age-specific (co)variances attributable to two reproductive routes showed that within-age and among-age covariances contributed substantially to the total variance and that extra-pair reproduction can alter the (co)variance structure of age-specific reproductive success. Such covariances and impacts should consequently be integrated into theoretical assessments of demographic and evolutionary processes in age-structured populations. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

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).

Socioeconomic Status (SES) and Children's Intelligence (IQ): In a UK-Representative Sample SES Moderates the Environmental, Not Genetic, Effect on IQ

PubMed Central

Hanscombe, Ken B.; Trzaskowski, Maciej; Haworth, Claire M. A.; Davis, Oliver S. P.; Dale, Philip S.; Plomin, Robert

2012-01-01

Background The environment can moderate the effect of genes - a phenomenon called gene-environment (GxE) interaction. Several studies have found that socioeconomic status (SES) modifies the heritability of children's intelligence. Among low-SES families, genetic factors have been reported to explain less of the variance in intelligence; the reverse is found for high-SES families. The evidence however is inconsistent. Other studies have reported an effect in the opposite direction (higher heritability in lower SES), or no moderation of the genetic effect on intelligence. Methods Using 8716 twin pairs from the Twins Early Development Study (TEDS), we attempted to replicate the reported moderating effect of SES on children's intelligence at ages 2, 3, 4, 7, 9, 10, 12 and 14: i.e., lower heritability in lower-SES families. We used a twin model that allowed for a main effect of SES on intelligence, as well as a moderating effect of SES on the genetic and environmental components of intelligence. Results We found greater variance in intelligence in low-SES families, but minimal evidence of GxE interaction across the eight ages. A power calculation indicated that a sample size of about 5000 twin pairs is required to detect moderation of the genetic component of intelligence as small as 0.25, with about 80% power - a difference of 11% to 53% in heritability, in low- (−2 standard deviations, SD) and high-SES (+2 SD) families. With samples at each age of about this size, the present study found no moderation of the genetic effect on intelligence. However, we found the greater variance in low-SES families is due to moderation of the environmental effect – an environment-environment interaction. Conclusions In a UK-representative sample, the genetic effect on intelligence is similar in low- and high-SES families. Children's shared experiences appear to explain the greater variation in intelligence in lower SES. PMID:22312423

Effective number of breeding adults in Bufo bufo estimated from age-specific variation at minisatellite loci

USGS Publications Warehouse

Scribner, K.T.; Arntzen, J.W.; Burke, T.

1997-01-01

Estimates of the effective number of breeding adults were derived for three semi-isolated populations of the common toad Bufo bufo based on temporal (i.e. adult-progeny) variance in allele frequency for three highly polymorphic minisatellite loci. Estimates of spatial variance in allele frequency among populations and of age-specific measures of genetic variability are also described. Each population was characterized by a low effective adult breeding number (N(b)) based on a large age-specific variance in minisatellite allele frequency. Estimates of N(b) (range 21-46 for population means across three loci) were ??? 55-230-fold lower than estimates of total adult census size. The implications of low effective breeding numbers for long-term maintenance of genetic variability and population viability are discussed relative to the species' reproductive ecology, current land-use practices, and present and historical habitat modification and loss. The utility of indirect measures of population parameters such as N(b) and N(e) based on time-series data of minisatellite allele frequencies is discussed relative to similar measures estimated from commonly used genetic markers such as protein allozymes.

Testlet-Based Multidimensional Adaptive Testing

PubMed Central

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range. PMID:27917132

Plastic strain is a mixture of avalanches and quasireversible deformations: Study of various sizes

NASA Astrophysics Data System (ADS)

Szabó, Péter; Ispánovity, Péter Dusán; Groma, István

2015-02-01

The size dependence of plastic flow is studied by discrete dislocation dynamical simulations of systems with various amounts of interacting dislocations while the stress is slowly increased. The regions between avalanches in the individual stress curves as functions of the plastic strain were found to be nearly linear and reversible where the plastic deformation obeys an effective equation of motion with a nearly linear force. For small plastic deformation, the mean values of the stress-strain curves obey a power law over two decades. Here and for somewhat larger plastic deformations, the mean stress-strain curves converge for larger sizes, while their variances shrink, both indicating the existence of a thermodynamical limit. The converging averages decrease with increasing size, in accordance with size effects from experiments. For large plastic deformations, where steady flow sets in, the thermodynamical limit was not realized in this model system.

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

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

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

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.

Insights into the genetic architecture of morphological traits in two passerine bird species.

PubMed

Silva, C N S; McFarlane, S E; Hagen, I J; Rönnegård, L; Billing, A M; Kvalnes, T; Kemppainen, P; Rønning, B; Ringsby, T H; Sæther, B-E; Qvarnström, A; Ellegren, H; Jensen, H; Husby, A

2017-09-01

Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (V P ), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of V P ). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.

Estimating individual glomerular volume in the human kidney: clinical perspectives.

PubMed

Puelles, Victor G; Zimanyi, Monika A; Samuel, Terence; Hughson, Michael D; Douglas-Denton, Rebecca N; Bertram, John F; Armitage, James A

2012-05-01

Measurement of individual glomerular volumes (IGV) has allowed the identification of drivers of glomerular hypertrophy in subjects without overt renal pathology. This study aims to highlight the relevance of IGV measurements with possible clinical implications and determine how many profiles must be measured in order to achieve stable size distribution estimates. We re-analysed 2250 IGV estimates obtained using the disector/Cavalieri method in 41 African and 34 Caucasian Americans. Pooled IGV analysis of mean and variance was conducted. Monte-Carlo (Jackknife) simulations determined the effect of the number of sampled glomeruli on mean IGV. Lin's concordance coefficient (R(C)), coefficient of variation (CV) and coefficient of error (CE) measured reliability. IGV mean and variance increased with overweight and hypertensive status. Superficial glomeruli were significantly smaller than juxtamedullary glomeruli in all subjects (P < 0.01), by race (P < 0.05) and in obese individuals (P < 0.01). Subjects with multiple chronic kidney disease (CKD) comorbidities showed significant increases in IGV mean and variability. Overall, mean IGV was particularly reliable with nine or more sampled glomeruli (R(C) > 0.95, <5% difference in CV and CE). These observations were not affected by a reduced sample size and did not disrupt the inverse linear correlation between mean IGV and estimated total glomerular number. Multiple comorbidities for CKD are associated with increased IGV mean and variance within subjects, including overweight, obesity and hypertension. Zonal selection and the number of sampled glomeruli do not represent drawbacks for future longitudinal biopsy-based studies of glomerular size and distribution.

Identification of major and minor QTL for ecologically important morphological traits in three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Liu, Jun; Shikano, Takahito; Leinonen, Tuomas; Cano, José Manuel; Li, Meng-Hua; Merilä, Juha

2014-04-16

Quantitative trait locus (QTL) mapping studies of Pacific three-spined sticklebacks (Gasterosteus aculeatus) have uncovered several genomic regions controlling variability in different morphological traits, but QTL studies of Atlantic sticklebacks are lacking. We mapped QTL for 40 morphological traits, including body size, body shape, and body armor, in a F2 full-sib cross between northern European marine and freshwater three-spined sticklebacks. A total of 52 significant QTL were identified at the 5% genome-wide level. One major QTL explaining 74.4% of the total variance in lateral plate number was detected on LG4, whereas several major QTL for centroid size (a proxy for body size), and the lengths of two dorsal spines, pelvic spine, and pelvic girdle were mapped on LG21 with the explained variance ranging from 27.9% to 57.6%. Major QTL for landmark coordinates defining body shape variation also were identified on LG21, with each explaining ≥15% of variance in body shape. Multiple QTL for different traits mapped on LG21 overlapped each other, implying pleiotropy and/or tight linkage. Thus, apart from providing confirmatory data to support conclusions born out of earlier QTL studies of Pacific sticklebacks, this study also describes several novel QTL of both major and smaller effect for ecologically important traits. The finding that many major QTL mapped on LG21 suggests that this linkage group might be a hotspot for genetic determinants of ecologically important morphological traits in three-spined sticklebacks.

Detecting and describing preventive intervention effects in a universal school-based randomized trial targeting delinquent and violent behavior.

PubMed

Stoolmiller, M; Eddy, J M; Reid, J B

2000-04-01

This study examined theoretical, methodological, and statistical problems involved in evaluating the outcome of aggression on the playground for a universal preventive intervention for conduct disorder. Moderately aggressive children were hypothesized most likely to benefit. Aggression was measured on the playground using observers blind to the group status of the children. Behavior was micro-coded in real time to minimize potential expectancy biases. The effectiveness of the intervention was strongly related to initial levels of aggressiveness. The most aggressive children improved the most. Models that incorporated corrections for low reliability (the ratio of variance due to true time-stable individual differences to total variance) and censoring (a floor effect in the rate data due to short periods of observation) obtained effect sizes 5 times larger than models without such corrections with respect to children who were initially 2 SDs above the mean on aggressiveness.

A Phase Field Study of the Effect of Microstructure Grain Size Heterogeneity on Grain Growth

NASA Astrophysics Data System (ADS)

Crist, David J. D.

Recent studies conducted with sharp-interface models suggest a link between the spatial distribution of grain size variance and average grain growth rate. This relationship and its effect on grain growth rate was examined using the diffuse-interface Phase Field Method on a series of microstructures with different degrees of grain size gradation. Results from this work indicate that the average grain growth rate has a positive correlation with the average grain size dispersion for phase field simulations, confirming previous observations. It is also shown that the grain growth rate in microstructures with skewed grain size distributions is better measured through the change in the volume-weighted average grain size than statistical mean grain size. This material is based upon work supported by the National Science Foundation under Grant No. 1334283. The NSF project title is "DMREF: Real Time Control of Grain Growth in Metals" and was awarded by the Civil, Mechanical and Manufacturing Innovation division under the Designing Materials to Revolutionize and Engineer our Future (DMREF) program.

Feasibility of speckle variance OCT for imaging cutaneous microvasculature regeneration during healing of wounds in diabetic mice

NASA Astrophysics Data System (ADS)

Sharma, P.; Kumawat, J.; Kumar, S.; Sahu, K.; Verma, Y.; Gupta, P. K.; Rao, K. D.

2018-02-01

We report on a study to assess the feasibility of a swept source-based speckle variance optical coherence tomography setup for monitoring cutaneous microvasculature. Punch wounds created in the ear pinnae of diabetic mice were monitored at different times post wounding to assess the structural and vascular changes. It was observed that the epithelium thickness increases post wounding and continues to be thick even after healing. Also, the wound size assessed by vascular images is larger than the physical wound size. The results show that the developed speckle variance optical coherence tomography system can be used to monitor vascular regeneration during wound healing in diabetic mice.

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Statistical review. Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. The median power to detect small, medium, and large effect sizes was .40 (interquartile range [IQR]=.24-.71), .98 (IQR=.85-1.00), and 1.00 (IQR=1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR=.26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

PubMed

Gebreyesus, Grum; Lund, Mogens S; Buitenhuis, Bart; Bovenhuis, Henk; Poulsen, Nina A; Janss, Luc G

2017-12-05

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

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.

Study books on ADHD genetics: balanced or biased?

PubMed Central

te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-01-01

ABSTRACT Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master’s programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics’ outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them. PMID:28532325

Study books on ADHD genetics: balanced or biased?

PubMed

Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-06-01

Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.

Discerning some Tylenol brands using attenuated total reflection Fourier transform infrared data and multivariate analysis techniques.

PubMed

Msimanga, Huggins Z; Ollis, Robert J

2010-06-01

Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to classify acetaminophen-containing medicines using their attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectra. Four formulations of Tylenol (Arthritis Pain Relief, Extra Strength Pain Relief, 8 Hour Pain Relief, and Extra Strength Pain Relief Rapid Release) along with 98% pure acetaminophen were selected for this study because of the similarity of their spectral features, with correlation coefficients ranging from 0.9857 to 0.9988. Before acquiring spectra for the predictor matrix, the effects on spectral precision with respect to sample particle size (determined by sieve size opening), force gauge of the ATR accessory, sample reloading, and between-tablet variation were examined. Spectra were baseline corrected and normalized to unity before multivariate analysis. Analysis of variance (ANOVA) was used to study spectral precision. The large particles (35 mesh) showed large variance between spectra, while fine particles (120 mesh) indicated good spectral precision based on the F-test. Force gauge setting did not significantly affect precision. Sample reloading using the fine particle size and a constant force gauge setting of 50 units also did not compromise precision. Based on these observations, data acquisition for the predictor matrix was carried out with the fine particles (sieve size opening of 120 mesh) at a constant force gauge setting of 50 units. After removing outliers, PCA successfully classified the five samples in the first and second components, accounting for 45.0% and 24.5% of the variances, respectively. The four-component PLS-DA model (R(2)=0.925 and Q(2)=0.906) gave good test spectra predictions with an overall average of 0.961 +/- 7.1% RSD versus the expected 1.0 prediction for the 20 test spectra used.

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

PubMed

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

2010-06-30

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

Modeling organizational determinants of hospital mortality.

PubMed Central

al-Haider, A S; Wan, T T

1991-01-01

This study examines hospital characteristics that affect the differential in hospital mortality. Death rates for 1984 Medicare inpatients in acute care hospitals, released by the Health Care Financing Administration in 1986, were analyzed. A confirmatory statistical approach to organizational determinants of hospital mortality was formulated and validated through an empirical examination of 239 hospitals. The findings suggest that the effect of hospital size and specialization on mortality was a spurious one when the effects of other variables were simultaneously controlled. A positive association existed between service intensity and hospital mortality: the more hospital services consumed, the higher the mortality rate. Community attributes accounted for more variance in hospital mortality rates than did organizational attributes. The organizational and community factors studied explained 27 percent of the total variance in hospital mortality. PMID:1869442

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population. PMID:23874733

Variable variance Preisach model for multilayers with perpendicular magnetic anisotropy

NASA Astrophysics Data System (ADS)

Franco, A. F.; Gonzalez-Fuentes, C.; Morales, R.; Ross, C. A.; Dumas, R.; Åkerman, J.; Garcia, C.

2016-08-01

We present a variable variance Preisach model that fully accounts for the different magnetization processes of a multilayer structure with perpendicular magnetic anisotropy by adjusting the evolution of the interaction variance as the magnetization changes. We successfully compare in a quantitative manner the results obtained with this model to experimental hysteresis loops of several [CoFeB/Pd ] n multilayers. The effect of the number of repetitions and the thicknesses of the CoFeB and Pd layers on the magnetization reversal of the multilayer structure is studied, and it is found that many of the observed phenomena can be attributed to an increase of the magnetostatic interactions and subsequent decrease of the size of the magnetic domains. Increasing the CoFeB thickness leads to the disappearance of the perpendicular anisotropy, and such a minimum thickness of the Pd layer is necessary to achieve an out-of-plane magnetization.

Toward privacy-preserving JPEG image retrieval

NASA Astrophysics Data System (ADS)

Cheng, Hang; Wang, Jingyue; Wang, Meiqing; Zhong, Shangping

2017-07-01

This paper proposes a privacy-preserving retrieval scheme for JPEG images based on local variance. Three parties are involved in the scheme: the content owner, the server, and the authorized user. The content owner encrypts JPEG images for privacy protection by jointly using permutation cipher and stream cipher, and then, the encrypted versions are uploaded to the server. With an encrypted query image provided by an authorized user, the server may extract blockwise local variances in different directions without knowing the plaintext content. After that, it can calculate the similarity between the encrypted query image and each encrypted database image by a local variance-based feature comparison mechanism. The authorized user with the encryption key can decrypt the returned encrypted images with plaintext content similar to the query image. The experimental results show that the proposed scheme not only provides effective privacy-preserving retrieval service but also ensures both format compliance and file size preservation for encrypted JPEG images.

New trends in gender and mathematics performance: a meta-analysis.

PubMed

Lindberg, Sara M; Hyde, Janet Shibley; Petersen, Jennifer L; Linn, Marcia C

2010-11-01

In this article, we use meta-analysis to analyze gender differences in recent studies of mathematics performance. First, we meta-analyzed data from 242 studies published between 1990 and 2007, representing the testing of 1,286,350 people. Overall, d = 0.05, indicating no gender difference, and variance ratio = 1.08, indicating nearly equal male and female variances. Second, we analyzed data from large data sets based on probability sampling of U.S. adolescents over the past 20 years: the National Longitudinal Surveys of Youth, the National Education Longitudinal Study of 1988, the Longitudinal Study of American Youth, and the National Assessment of Educational Progress. Effect sizes for the gender difference ranged between -0.15 and +0.22. Variance ratios ranged from 0.88 to 1.34. Taken together, these findings support the view that males and females perform similarly in mathematics.

Power and Sample Size Calculations for Testing Linear Combinations of Group Means under Variance Heterogeneity with Applications to Meta and Moderation Analyses

ERIC Educational Resources Information Center

Shieh, Gwowen; Jan, Show-Li

2015-01-01

The general formulation of a linear combination of population means permits a wide range of research questions to be tested within the context of ANOVA. However, it has been stressed in many research areas that the homogeneous variances assumption is frequently violated. To accommodate the heterogeneity of variance structure, the…

Whole-animal metabolic rate is a repeatable trait: a meta-analysis.

PubMed

Nespolo, Roberto F; Franco, Marcela

2007-06-01

Repeatability studies are gaining considerable interest among physiological ecologists, particularly in traits affected by high environmental/residual variance, such as whole-animal metabolic rate (MR). The original definition of repeatability, known as the intraclass correlation coefficient, is computed from the components of variance obtained in a one-way ANOVA on several individuals from which two or more measurements are performed. An alternative estimation of repeatability, popular among physiological ecologists, is the Pearson product-moment correlation between two consecutive measurements. However, despite the more than 30 studies reporting repeatability of MR, so far there is not a definite synthesis indicating: (1) whether repeatability changes in different types of animals; (2) whether some kinds of metabolism are more repeatable than others; and most important, (3) whether metabolic rate is significantly repeatable. We performed a meta-analysis to address these questions, as well as to explore the historical trend in repeatability studies. Our results show that metabolic rate is significantly repeatable and its effect size is not statistically affected by any of the mentioned factors (i.e. repeatability of MR does not change in different species, type of metabolism, time between measurements, and number of individuals). The cumulative meta-analysis revealed that repeatability studies in MR have already reached an asymptotical effect size with no further change either in its magnitude and/or variance (i.e. additional studies will not contribute significantly to the estimator). There was no evidence of strong publication bias.

Effect of plasma arc welding variables on fusion zone grain size and hardness of AISI 321 austenitic stainless steel

NASA Astrophysics Data System (ADS)

Kondapalli, S. P.

2017-12-01

In the present work, pulsed current microplasma arc welding is carried out on AISI 321 austenitic stainless steel of 0.3 mm thickness. Peak current, Base current, Pulse rate and Pulse width are chosen as the input variables, whereas grain size and hardness are considered as output responses. Response surface method is adopted by using Box-Behnken Design, and in total 27 experiments are performed. Empirical relation between input and output response is developed using statistical software and analysis of variance (ANOVA) at 95% confidence level to check the adequacy. The main effect and interaction effect of input variables on output response are also studied.

Effect of Cutting Velocity / Stem Size on the Efficiency of NRCRI Cassave Stem Cutting Machine

NASA Astrophysics Data System (ADS)

Ikejiofor, M. C.

2012-11-01

The developed NRCRI (National Root Crops Research Institute) cassava stem cutting machine was evaluated. The cassava stems from the variety TME 419 were used. The sizes of the stem used were 1.8, 2.0, 2.3 and 2.6cm. Also, different cutting velocities of 1.20, 1.23 and 1.32m/s were used. The stakes produced has length of 2.5cm. Analysis of variance in RCBD was used to evaluate the effect of the cutting velocity and the stem size on the efficiency of the cutting machine. The result of the analysis showed that the cutting velocity had very highly significant effect, while the stem size had no significant effect at 5% level on the efficiency of the cutting machine. The data obtained also showed that the highest and least cutting efficiencies of 99.42 and 94.71% were obtained with the machine cutting velocities of 1.2 and 1.32m/s respectively.

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

PubMed

Petruzzellis, Francesco; Palandrani, Chiara; Savi, Tadeja; Alberti, Roberto; Nardini, Andrea; Bacaro, Giovanni

2017-12-01

The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV BI ) and among populations (ITV POP ), relatively few studies have analyzed intraspecific variability within individuals (ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.

Repeatability and reproducibility of ribotyping and its computer interpretation.

PubMed

Lefresne, Gwénola; Latrille, Eric; Irlinger, Françoise; Grimont, Patrick A D

2004-04-01

Many molecular typing methods are difficult to interpret because their repeatability (within-laboratory variance) and reproducibility (between-laboratory variance) have not been thoroughly studied. In the present work, ribotyping of coryneform bacteria was the basis of a study involving within-gel and between-gel repeatability and between-laboratory reproducibility (two laboratories involved). The effect of different technical protocols, different algorithms, and different software for fragment size determination was studied. Analysis of variance (ANOVA) showed, within a laboratory, that there was no significant added variance between gels. However, between-laboratory variance was significantly higher than within-laboratory variance. This may be due to the use of different protocols. An experimental function was calculated to transform the data and make them compatible (i.e., erase the between-laboratory variance). The use of different interpolation algorithms (spline, Schaffer and Sederoff) was a significant source of variation in one laboratory only. The use of either Taxotron (Institut Pasteur) or GelCompar (Applied Maths) was not a significant source of added variation when the same algorithm (spline) was used. However, the use of Bio-Gene (Vilber Lourmat) dramatically increased the error (within laboratory, within gel) in one laboratory, while decreasing the error in the other laboratory; this might be due to automatic normalization attempts. These results were taken into account for building a database and performing automatic pattern identification using Taxotron. Conversion of the data considerably improved the identification of patterns irrespective of the laboratory in which the data were obtained.

First among Others? Cohen's "d" vs. Alternative Standardized Mean Group Difference Measures

ERIC Educational Resources Information Center

Cahan, Sorel; Gamliel, Eyal

2011-01-01

Standardized effect size measures typically employed in behavioral and social sciences research in the multi-group case (e.g., [eta][superscript 2], f[superscript 2]) evaluate between-group variability in terms of either total or within-group variability, such as variance or standard deviation--that is, measures of dispersion about the mean. In…

Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research.

ERIC Educational Resources Information Center

Levine, Timothy R.; Hullett, Craig R.

2002-01-01

Alerts communication researchers to potential errors stemming from the use of SPSS (Statistical Package for the Social Sciences) to obtain estimates of eta squared in analysis of variance (ANOVA). Strives to clarify issues concerning the development and appropriate use of eta squared and partial eta squared in ANOVA. Discusses the reporting of…

A Generally Robust Approach for Testing Hypotheses and Setting Confidence Intervals for Effect Sizes

ERIC Educational Resources Information Center

Keselman, H. J.; Algina, James; Lix, Lisa M.; Wilcox, Rand R.; Deering, Kathleen N.

2008-01-01

Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. This article describes a framework for robust estimation and testing that uses trimmed means with an approximate degrees of…

A Preliminary Comparison of the Effectiveness of Cluster Analysis Weighting Procedures for Within-Group Covariance Structure.

ERIC Educational Resources Information Center

Donoghue, John R.

A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…

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.

Improvements for retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Husi, L.; Bréon, F. M.; Ma, R.; Chen, L.; Wang, Z.

2017-12-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR ( 1.5µm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (>15 µm) and to reduce the uncertainties caused by cloud heterogeneity. A premium resoltion of 0.8° is determined by considering successful retrievals and cloud horizontal homogeneity. The improved algorithm is applied to measurements of POLDER in 2008, and we further compared our retrievals with cloud effective radii estimations of Moderate Resolution Imaging Spectroradiometer (MODIS). The results indicate that in global scale, the cloud effective radii and effective variance is larger in the central ocean than inland and coast areas. Over heavy polluted regions, the cloud droplets has small effective radii and narraw distribution due to the influence of aerosol particles.

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.

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

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

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

Incremental validity of the episode size criterion in binge-eating definitions: An examination in women with purging syndromes.

PubMed

Forney, K Jean; Bodell, Lindsay P; Haedt-Matt, Alissa A; Keel, Pamela K

2016-07-01

Of the two primary features of binge eating, loss of control (LOC) eating is well validated while the role of eating episode size is less clear. Given the ICD-11 proposal to eliminate episode size from the binge-eating definition, the present study examined the incremental validity of the size criterion, controlling for LOC. Interview and questionnaire data come from four studies of 243 women with bulimia nervosa (n = 141) or purging disorder (n = 102). Hierarchical linear regression tested if the largest reported episode size, coded in kilocalories, explained additional variance in eating disorder features, psychopathology, personality traits, and impairment, holding constant LOC eating frequency, age, and body mass index (BMI). Analyses also tested if episode size moderated the association between LOC eating and these variables. Holding LOC constant, episode size explained significant variance in disinhibition, trait anxiety, and eating disorder-related impairment. Episode size moderated the association of LOC eating with purging frequency and depressive symptoms, such that in the presence of larger eating episodes, LOC eating was more closely associated with these features. Neither episode size nor its interaction with LOC explained additional variance in BMI, hunger, restraint, shape concerns, state anxiety, negative urgency, or global functioning. Taken together, results support the incremental validity of the size criterion, in addition to and in combination with LOC eating, for defining binge-eating episodes in purging syndromes. Future research should examine the predictive validity of episode size in both purging and nonpurging eating disorders (e.g., binge eating disorder) to inform nosological schemes. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:651-662). © 2016 Wiley Periodicals, Inc.

An Empirical Study of Design Parameters for Assessing Differential Impacts for Students in Group Randomized Trials.

PubMed

Jaciw, Andrew P; Lin, Li; Ma, Boya

2016-10-18

Prior research has investigated design parameters for assessing average program impacts on achievement outcomes with cluster randomized trials (CRTs). Less is known about parameters important for assessing differential impacts. This article develops a statistical framework for designing CRTs to assess differences in impact among student subgroups and presents initial estimates of critical parameters. Effect sizes and minimum detectable effect sizes for average and differential impacts are calculated before and after conditioning on effects of covariates using results from several CRTs. Relative sensitivities to detect average and differential impacts are also examined. Student outcomes from six CRTs are analyzed. Achievement in math, science, reading, and writing. The ratio of between-cluster variation in the slope of the moderator divided by total variance-the "moderator gap variance ratio"-is important for designing studies to detect differences in impact between student subgroups. This quantity is the analogue of the intraclass correlation coefficient. Typical values were .02 for gender and .04 for socioeconomic status. For studies considered, in many cases estimates of differential impact were larger than of average impact, and after conditioning on effects of covariates, similar power was achieved for detecting average and differential impacts of the same size. Measuring differential impacts is important for addressing questions of equity, generalizability, and guiding interpretation of subgroup impact findings. Adequate power for doing this is in some cases reachable with CRTs designed to measure average impacts. Continuing collection of parameters for assessing differential impacts is the next step. © The Author(s) 2016.

Environmentally transmitted parasites: Host-jumping in a heterogeneous environment.

PubMed

Caraco, Thomas; Cizauskas, Carrie A; Wang, Ing-Nang

2016-05-21

Groups of chronically infected reservoir-hosts contaminate resource patches by shedding a parasite׳s free-living stage. Novel-host groups visit the same patches, where they are exposed to infection. We treat arrival at patches, levels of parasite deposition, and infection of the novel host as stochastic processes, and derive the expected time elapsing until a host-jump (initial infection of a novel host) occurs. At stationarity, mean parasite densities are independent of reservoir-host group size. But within-patch parasite-density variances increase with reservoir group size. The probability of infecting a novel host declines with parasite-density variance; consequently larger reservoir groups extend the mean waiting time for host-jumping. Larger novel-host groups increase the probability of a host-jump during any single patch visit, but also reduce the total number of visits per unit time. Interaction of these effects implies that the waiting time for the first infection increases with the novel-host group size. If the reservoir-host uses resource patches in any non-uniform manner, reduced spatial overlap between host species increases the waiting time for host-jumping. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stresses in Implant-Supported Fixed Complete Dentures with Different Screw-Tightening Sequences and Torque Application Modes.

PubMed

Barcellos, Leonardo H; Palmeiro, Marina Lobato; Naconecy, Marcos M; Geremia, Tomás; Cervieri, André; Shinkai, Rosemary S

2018-05-17

To compare the effects of different screw-tightening sequences and torque applications on stresses in implant-supported fixed complete dentures supported by five abutments. Strain gauges fixed to the abutments were used to test the sequences 2-4-3-1-5; 1-2-3-4-5; 3-2-4-1-5; and 2-5-4-1-3 with direct 10-Ncm torque or progressive torque (5 + 10 Ncm). Data were analyzed using analysis of variance and standardized effect size. No effects of tightening sequence or torque application were found except for the sequence 3-2-4-1-5 and some small to moderate effect sizes. Screw-tightening sequences and torque application modes have only a marginal effect on residual stresses.

Evidence for Break-Up of Clumps in Dynamically Stirred Regions of Saturn's Rings

NASA Astrophysics Data System (ADS)

Colwell, J. E.; Sega, D. N.; Jerousek, R. G.; Cooney, J. H.; Esposito, L. W.

2017-12-01

Stellar occultations of Saturn's rings observed by the Cassini Ultraviolet Imaging Spectrograph (UVIS) High Speed Photometer (HSP) record stellar brightness seen through the rings as photon counts that are described by Poisson counting statistics in the absence of intervening ring material. The variance in the data increases above counting statistics due to the discrete sizes of the ring particles, with larger particles leading to a larger variance at a given optical depth. We take advantage of the high spatial resolution and multiple viewing geometries of the UVIS occultations to study variations in particle size near and within strongly perturbed regions of Saturn's A ring, in particular the strong first order Lindblad resonances with Janus and the Mimas 5:3 Lindblad resonance and inner vertical resonance. The variance shows changes in the area-weighted particle size between peaks and troughs in the density waves as well as an overall decrease in particle size in the broad "halo" regions that bracket the strong Janus Lindblad resonances in the A ring. In addition we see a decrease in particle size at the location of the Mimas 5:3 bending wave wavetrain itself, and an increase in optical depth at the location of the wave when viewed from high elevation angles out of the ring plane. Taken together, these observations suggest that clumps of particles, perhaps the ubiquitous A ring self-gravity wakes, are disaggregated in the bending wave, even though standard bending wave theory does not predict enhanced collision velocities. We also examine the skewness, a higher order moment of the occultation data, that is diagnostic of asymmetries in the particle size distribution. We use Monte Carlo simulations of occultations to match the first three moments of the data (the signal mean, or equivalently the optical depth, the variance, and the skewness) to illustrate differences in ring particle size in these perturbed regions.

OCT Amplitude and Speckle Statistics of Discrete Random Media.

PubMed

Almasian, Mitra; van Leeuwen, Ton G; Faber, Dirk J

2017-11-01

Speckle, amplitude fluctuations in optical coherence tomography (OCT) images, contains information on sub-resolution structural properties of the imaged sample. Speckle statistics could therefore be utilized in the characterization of biological tissues. However, a rigorous theoretical framework relating OCT speckle statistics to structural tissue properties has yet to be developed. As a first step, we present a theoretical description of OCT speckle, relating the OCT amplitude variance to size and organization for samples of discrete random media (DRM). Starting the calculations from the size and organization of the scattering particles, we analytically find expressions for the OCT amplitude mean, amplitude variance, the backscattering coefficient and the scattering coefficient. We assume fully developed speckle and verify the validity of this assumption by experiments on controlled samples of silica microspheres suspended in water. We show that the OCT amplitude variance is sensitive to sub-resolution changes in size and organization of the scattering particles. Experimentally determined and theoretically calculated optical properties are compared and in good agreement.

Estimating individual glomerular volume in the human kidney: clinical perspectives

PubMed Central

Puelles, Victor G.; Zimanyi, Monika A.; Samuel, Terence; Hughson, Michael D.; Douglas-Denton, Rebecca N.; Bertram, John F.

2012-01-01

Background. Measurement of individual glomerular volumes (IGV) has allowed the identification of drivers of glomerular hypertrophy in subjects without overt renal pathology. This study aims to highlight the relevance of IGV measurements with possible clinical implications and determine how many profiles must be measured in order to achieve stable size distribution estimates. Methods. We re-analysed 2250 IGV estimates obtained using the disector/Cavalieri method in 41 African and 34 Caucasian Americans. Pooled IGV analysis of mean and variance was conducted. Monte-Carlo (Jackknife) simulations determined the effect of the number of sampled glomeruli on mean IGV. Lin’s concordance coefficient (RC), coefficient of variation (CV) and coefficient of error (CE) measured reliability. Results. IGV mean and variance increased with overweight and hypertensive status. Superficial glomeruli were significantly smaller than juxtamedullary glomeruli in all subjects (P < 0.01), by race (P < 0.05) and in obese individuals (P < 0.01). Subjects with multiple chronic kidney disease (CKD) comorbidities showed significant increases in IGV mean and variability. Overall, mean IGV was particularly reliable with nine or more sampled glomeruli (RC > 0.95, <5% difference in CV and CE). These observations were not affected by a reduced sample size and did not disrupt the inverse linear correlation between mean IGV and estimated total glomerular number. Conclusions. Multiple comorbidities for CKD are associated with increased IGV mean and variance within subjects, including overweight, obesity and hypertension. Zonal selection and the number of sampled glomeruli do not represent drawbacks for future longitudinal biopsy-based studies of glomerular size and distribution. PMID:21984554

The Use of Growth Mixture Modeling for Studying Resilience to Major Life Stressors in Adulthood and Old Age: Lessons for Class Size and Identification and Model Selection.

PubMed

Infurna, Frank J; Grimm, Kevin J

2017-12-15

Growth mixture modeling (GMM) combines latent growth curve and mixture modeling approaches and is typically used to identify discrete trajectories following major life stressors (MLS). However, GMM is often applied to data that does not meet the statistical assumptions of the model (e.g., within-class normality) and researchers often do not test additional model constraints (e.g., homogeneity of variance across classes), which can lead to incorrect conclusions regarding the number and nature of the trajectories. We evaluate how these methodological assumptions influence trajectory size and identification in the study of resilience to MLS. We use data on changes in subjective well-being and depressive symptoms following spousal loss from the HILDA and HRS. Findings drastically differ when constraining the variances to be homogenous versus heterogeneous across trajectories, with overextraction being more common when constraining the variances to be homogeneous across trajectories. In instances, when the data are non-normally distributed, assuming normally distributed data increases the extraction of latent classes. Our findings showcase that the assumptions typically underlying GMM are not tenable, influencing trajectory size and identification and most importantly, misinforming conceptual models of resilience. The discussion focuses on how GMM can be leveraged to effectively examine trajectories of adaptation following MLS and avenues for future research. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identification of Major and Minor QTL for Ecologically Important Morphological Traits in Three-Spined Sticklebacks (Gasterosteus aculeatus)

PubMed Central

Liu, Jun; Shikano, Takahito; Leinonen, Tuomas; Cano, José Manuel; Li, Meng-Hua; Merilä, Juha

2014-01-01

Quantitative trait locus (QTL) mapping studies of Pacific three-spined sticklebacks (Gasterosteus aculeatus) have uncovered several genomic regions controlling variability in different morphological traits, but QTL studies of Atlantic sticklebacks are lacking. We mapped QTL for 40 morphological traits, including body size, body shape, and body armor, in a F2 full-sib cross between northern European marine and freshwater three-spined sticklebacks. A total of 52 significant QTL were identified at the 5% genome-wide level. One major QTL explaining 74.4% of the total variance in lateral plate number was detected on LG4, whereas several major QTL for centroid size (a proxy for body size), and the lengths of two dorsal spines, pelvic spine, and pelvic girdle were mapped on LG21 with the explained variance ranging from 27.9% to 57.6%. Major QTL for landmark coordinates defining body shape variation also were identified on LG21, with each explaining ≥15% of variance in body shape. Multiple QTL for different traits mapped on LG21 overlapped each other, implying pleiotropy and/or tight linkage. Thus, apart from providing confirmatory data to support conclusions born out of earlier QTL studies of Pacific sticklebacks, this study also describes several novel QTL of both major and smaller effect for ecologically important traits. The finding that many major QTL mapped on LG21 suggests that this linkage group might be a hotspot for genetic determinants of ecologically important morphological traits in three-spined sticklebacks. PMID:24531726

A Visual Model for the Variance and Standard Deviation

ERIC Educational Resources Information Center

Orris, J. B.

2011-01-01

This paper shows how the variance and standard deviation can be represented graphically by looking at each squared deviation as a graphical object--in particular, as a square. A series of displays show how the standard deviation is the size of the average square.

Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: a primer and applications.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E

2014-04-01

This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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

PubMed

Carneiro, Clarissa F D; Moulin, Thiago C; Macleod, Malcolm R; Amaral, Olavo B

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.

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

PubMed Central

Macleod, Malcolm R.

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science. PMID:29698451

Sample size calculation in economic evaluations.

PubMed

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

1998-06-01

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

Eta- and Partial Eta-Squared in L2 Research: A Cautionary Review and Guide to More Appropriate Usage

ERIC Educational Resources Information Center

Norouzian, Reza; Plonsky, Luke

2018-01-01

Eta-squared (?[superscript 2]) and partial eta-squared (?[subscript p][superscript 2]) are effect sizes that express the amount of variance accounted for by one or more independent variables. These indices are generally used in conjunction with ANOVA, the most commonly used statistical test in second language (L2) research (Plonsky, 2013).…

Optimal Design in Three-Level Block Randomized Designs with Two Levels of Nesting: An ANOVA Framework with Random Effects

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2013-01-01

Large-scale experiments that involve nested structures may assign treatment conditions either to subgroups such as classrooms or to individuals such as students within subgroups. Key aspects of the design of such experiments include knowledge of the variance structure in higher levels and the sample sizes necessary to reach sufficient power to…

Genetic Difference in Height Growth and Survival of Cottonwood Full-Sib Families

Treesearch

D. T. Cooper; W. K. Randall

1973-01-01

Sixteen full-sib families from crosses between four fast-growing female and four fast-growing male clones of cottonwood (Populus deltoides Bartr.) were clonally evaluated for 1 year in a replicated field test. Seedling size had no effect on clonal performance. Approximately 70 percent of the genetic variance for height and 20 percent of that for...

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.

Size of Self-Gravity Wakes from Cassini UVIS Tracking Occultations and Ring Transparency Statistics

NASA Astrophysics Data System (ADS)

Esposito, Larry W.; Rehnberg, Morgan; Colwell, Joshua E.; Sremcevic, Miodrag

2017-10-01

We compare two methods for determining the size of self-gravity wakes in Saturn’s rings. Analysis of gaps seen in UVIS occultations gives a power law distribution from 10-100m (Rehnberg etal 2017). Excess variance from UVIS occultations can be related to characteristic clump widths, a method which extends the work of Showalter and Nicholson (1990) to more arbitrary shadow distributions. In the middle A ring, we use results from Colwell etal (2017) for the variance and results from Jerousek etal (2016) for the relative size of gaps and wakes to estimate the wake width consistent with the excess variance observed there. Our method gives:W= sqrt (A) * E/T2 * (1+ S/W)Where A is the area observed by UVIS in an integration period, E is the measured excess variance above Poisson statistics, T is the mean transparency, and S and W are the separation and width of self-gravity wakes in the granola bar model of Colwell etal (2006). We find:W ~ 10m and infer the wavelength of the fastest growing instabilityLambda(TOOMRE) = S + W ~ 30m.This is consistent with the calculation of the Toomre wavelength from the surface mass density of the A ring, and with the highest resolution UVIS star occultations.

Size of Self-Gravity Wakes from Cassini UVIS Tracking Occultations and Ring Transparency Statistics

NASA Astrophysics Data System (ADS)

Esposito, L. W.; Rehnberg, M.; Colwell, J. E.; Sremcevic, M.

2017-12-01

We compare two methods for determining the size of self-gravity wakes in Saturn's rings. Analysis of gaps seen in UVIS occultations gives a power law distribution from 10-100m (Rehnberg etal 2017). Excess variance from UVIS occultations can be related to characteristic clump widths, a method which extends the work of Showalter and Nicholson (1990) to more arbitrary shadow distributions. In the middle A ring, we use results from Colwell etal (2017) for the variance and results from Jerousek etal (2016) for the relative size of gaps and wakes to estimate the wake width consistent with the excess variance observed there. Our method gives: W= sqrt (A) * E/T2 * (1+ S/W)Where A is the area observed by UVIS in an integration period, E is the measured excess variance above Poisson statistics, T is the mean transparency, and S and W are the separation and width of self-gravity wakes in the granola bar model of Colwell etal (2006). We find: W 10m and infer the wavelength of the fastest growing instability lamdaT = S + W 30m. This is consistent with the calculation of the Toomre wavelength from the surface mass density of the A ring, and with the highest resolution UVIS star occultations.

Positive density-dependent reproduction regulated by local kinship and size in an understorey tropical tree

PubMed Central

Castilla, Antonio R.; Pope, Nathaniel; Jha, Shalene

2016-01-01

Background and Aims Global pollinator declines and continued habitat fragmentation highlight the critical need to understand reproduction and gene flow across plant populations. Plant size, conspecific density and local kinship (i.e. neighbourhood genetic relatedness) have been proposed as important mechanisms influencing the reproductive success of flowering plants, but have rarely been simultaneously investigated. Methods We conducted this study on a continuous population of the understorey tree Miconia affinis in the Forest Dynamics Plot on Barro Colorado Island in central Panama. We used spatial, reproductive and population genetic data to investigate the effects of tree size, conspecific neighbourhood density and local kinship on maternal and paternal reproductive success. We used a Bayesian framework to simultaneously model the effects of our explanatory variables on the mean and variance of maternal viable seed set and siring success. Key Results Our results reveal that large trees had lower proportions of viable seeds in their fruits but sired more seeds. We documented differential effects of neighbourhood density and local kinship on both maternal and paternal reproductive components. Trees in more dense neighbourhoods produced on average more viable seeds, although this positive density effect was influenced by variance-inflation with increasing local kinship. Neighbourhood density did not have significant effects on siring success. Conclusions This study is one of the first to reveal an interaction among tree size, conspecific density and local kinship as critical factors differentially influencing maternal and paternal reproductive success. We show that both maternal and paternal reproductive success should be evaluated to determine the population-level and individual traits most essential for plant reproduction. In addition to conserving large trees, we suggest the inclusion of small trees and the conservation of dense patches with low kinship as potential strategies for strengthening the reproductive status of tropical trees. PMID:26602288

Positive density-dependent reproduction regulated by local kinship and size in an understorey tropical tree.

PubMed

Castilla, Antonio R; Pope, Nathaniel; Jha, Shalene

2016-02-01

Global pollinator declines and continued habitat fragmentation highlight the critical need to understand reproduction and gene flow across plant populations. Plant size, conspecific density and local kinship (i.e. neighbourhood genetic relatedness) have been proposed as important mechanisms influencing the reproductive success of flowering plants, but have rarely been simultaneously investigated. We conducted this study on a continuous population of the understorey tree Miconia affinis in the Forest Dynamics Plot on Barro Colorado Island in central Panama. We used spatial, reproductive and population genetic data to investigate the effects of tree size, conspecific neighbourhood density and local kinship on maternal and paternal reproductive success. We used a Bayesian framework to simultaneously model the effects of our explanatory variables on the mean and variance of maternal viable seed set and siring success. Our results reveal that large trees had lower proportions of viable seeds in their fruits but sired more seeds. We documented differential effects of neighbourhood density and local kinship on both maternal and paternal reproductive components. Trees in more dense neighbourhoods produced on average more viable seeds, although this positive density effect was influenced by variance-inflation with increasing local kinship. Neighbourhood density did not have significant effects on siring success. This study is one of the first to reveal an interaction among tree size, conspecific density and local kinship as critical factors differentially influencing maternal and paternal reproductive success. We show that both maternal and paternal reproductive success should be evaluated to determine the population-level and individual traits most essential for plant reproduction. In addition to conserving large trees, we suggest the inclusion of small trees and the conservation of dense patches with low kinship as potential strategies for strengthening the reproductive status of tropical trees. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown.

PubMed

Konietschke, Frank; Libiger, Ondrej; Hothorn, Ludwig A

2012-01-01

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

Skeletal maturation, fundamental motor skills and motor performance in preschool children.

PubMed

Freitas, D L; Lausen, B; Maia, J A; Gouveia, É R; Antunes, A M; Thomis, M; Lefevre, J; Malina, R M

2018-06-01

Relationships among skeletal age (SA), body size and fundamental motor skills (FMS) and motor performance were considered in 155 boys and 159 girls 3-6 years of age. Stature and body mass were measured. SA of the hand-wrist was assessed with the Tanner-Whitehouse II 20 bone method. The Test of Gross Motor Development, 2 nd edition (TGMD-2) and the Preschool Test Battery were used, respectively, to assess FMS and motor performance. Based on hierarchical regression analyses, the standardized residuals of SA on chronological age (SAsr) explained a maximum of 6.1% of the variance in FMS and motor performance in boys (ΔR 2 3 , range 0.0% to 6.1%) and a maximum of 20.4% of the variance in girls (ΔR 2 3 , range 0.0% to 20.4%) over that explained by body size and interactions of SAsr with body size (step 3). The interactions of the SAsr and stature and body mass (step 2) explained a maximum of 28.3% of the variance in boys (ΔR 2 2 , range 0.5% to 28.3%) and 16.7% of the variance in girls (ΔR 2 2 , range 0.7% to 16.7%) over that explained by body size alone. With the exception of balance, relationships among SAsr and FMS or motor performance differed between boys and girls. Overall, SA per se or interacting with body size had a relatively small influence in FMS and motor performance in children 3-6 years of age. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle.

PubMed

Cernicchiaro, N; Renter, D G; Xiang, S; White, B J; Bello, N M

2013-06-01

Variability in ADG of feedlot cattle can affect profits, thus making overall returns more unstable. Hence, knowledge of the factors that contribute to heterogeneity of variances in animal performance can help feedlot managers evaluate risks and minimize profit volatility when making managerial and economic decisions in commercial feedlots. The objectives of the present study were to evaluate heteroskedasticity, defined as heterogeneity of variances, in ADG of cohorts of commercial feedlot cattle, and to identify cattle demographic factors at feedlot arrival as potential sources of variance heterogeneity, accounting for cohort- and feedlot-level information in the data structure. An operational dataset compiled from 24,050 cohorts from 25 U. S. commercial feedlots in 2005 and 2006 was used for this study. Inference was based on a hierarchical Bayesian model implemented with Markov chain Monte Carlo, whereby cohorts were modeled at the residual level and feedlot-year clusters were modeled as random effects. Forward model selection based on deviance information criteria was used to screen potentially important explanatory variables for heteroskedasticity at cohort- and feedlot-year levels. The Bayesian modeling framework was preferred as it naturally accommodates the inherently hierarchical structure of feedlot data whereby cohorts are nested within feedlot-year clusters. Evidence for heterogeneity of variance components of ADG was substantial and primarily concentrated at the cohort level. Feedlot-year specific effects were, by far, the greatest contributors to ADG heteroskedasticity among cohorts, with an estimated ∼12-fold change in dispersion between most and least extreme feedlot-year clusters. In addition, identifiable demographic factors associated with greater heterogeneity of cohort-level variance included smaller cohort sizes, fewer days on feed, and greater arrival BW, as well as feedlot arrival during summer months. These results support that heterogeneity of variances in ADG is prevalent in feedlot performance and indicate potential sources of heteroskedasticity. Further investigation of factors associated with heteroskedasticity in feedlot performance is warranted to increase consistency and uniformity in commercial beef cattle production and subsequent profitability.

Influence of outliers on accuracy estimation in genomic prediction in plant breeding.

PubMed

Estaghvirou, Sidi Boubacar Ould; Ogutu, Joseph O; Piepho, Hans-Peter

2014-10-01

Outliers often pose problems in analyses of data in plant breeding, but their influence on the performance of methods for estimating predictive accuracy in genomic prediction studies has not yet been evaluated. Here, we evaluate the influence of outliers on the performance of methods for accuracy estimation in genomic prediction studies using simulation. We simulated 1000 datasets for each of 10 scenarios to evaluate the influence of outliers on the performance of seven methods for estimating accuracy. These scenarios are defined by the number of genotypes, marker effect variance, and magnitude of outliers. To mimic outliers, we added to one observation in each simulated dataset, in turn, 5-, 8-, and 10-times the error SD used to simulate small and large phenotypic datasets. The effect of outliers on accuracy estimation was evaluated by comparing deviations in the estimated and true accuracies for datasets with and without outliers. Outliers adversely influenced accuracy estimation, more so at small values of genetic variance or number of genotypes. A method for estimating heritability and predictive accuracy in plant breeding and another used to estimate accuracy in animal breeding were the most accurate and resistant to outliers across all scenarios and are therefore preferable for accuracy estimation in genomic prediction studies. The performances of the other five methods that use cross-validation were less consistent and varied widely across scenarios. The computing time for the methods increased as the size of outliers and sample size increased and the genetic variance decreased. Copyright © 2014 Ould Estaghvirou et al.

Strong effects of ionizing radiation from Chernobyl on mutation rates

NASA Astrophysics Data System (ADS)

Møller, Anders Pape; Mousseau, Timothy A.

2015-02-01

In this paper we use a meta-analysis to examine the relationship between radiation and mutation rates in Chernobyl across 45 published studies, covering 30 species. Overall effect size of radiation on mutation rates estimated as Pearson's product-moment correlation coefficient was very large (E = 0.67; 95% confidence intervals (CI) 0.59 to 0.73), accounting for 44.3% of the total variance in an unstructured random-effects model. Fail-safe calculations reflecting the number of unpublished null results needed to eliminate this average effect size showed the extreme robustness of this finding (Rosenberg's method: 4135 at p = 0.05). Indirect tests did not provide any evidence of publication bias. The effect of radiation on mutations varied among taxa, with plants showing a larger effect than animals. Humans were shown to have intermediate sensitivity of mutations to radiation compared to other species. Effect size did not decrease over time, providing no evidence for an improvement in environmental conditions. The surprisingly high mean effect size suggests a strong impact of radioactive contamination on individual fitness in current and future generations, with potentially significant population-level consequences, even beyond the area contaminated with radioactive material.

Strong effects of ionizing radiation from Chernobyl on mutation rates.

PubMed

Møller, Anders Pape; Mousseau, Timothy A

2015-02-10

In this paper we use a meta-analysis to examine the relationship between radiation and mutation rates in Chernobyl across 45 published studies, covering 30 species. Overall effect size of radiation on mutation rates estimated as Pearson's product-moment correlation coefficient was very large (E = 0.67; 95% confidence intervals (CI) 0.59 to 0.73), accounting for 44.3% of the total variance in an unstructured random-effects model. Fail-safe calculations reflecting the number of unpublished null results needed to eliminate this average effect size showed the extreme robustness of this finding (Rosenberg's method: 4135 at p = 0.05). Indirect tests did not provide any evidence of publication bias. The effect of radiation on mutations varied among taxa, with plants showing a larger effect than animals. Humans were shown to have intermediate sensitivity of mutations to radiation compared to other species. Effect size did not decrease over time, providing no evidence for an improvement in environmental conditions. The surprisingly high mean effect size suggests a strong impact of radioactive contamination on individual fitness in current and future generations, with potentially significant population-level consequences, even beyond the area contaminated with radioactive material.

Birth order, family configuration, and verbal achievement.

PubMed

Breland, H M

1974-12-01

Two samples of National Merit Scholarship participants test in 1962 and the entire population of almost 800,000 participants tested in 1965 were examined. Consistent effects in all 3 groups were observed with respect to both birth order and family size (1st born and those of smaller families scored higher). Control of both socioeconomic variables and maternal age, by analysis of variance as well as by analysis of covariance, failed to alter the relationships. Stepdown analyses suggested that the effects were due to a verbal component and that no differences were attributable to nonverbal factors. Mean test scores were computed for detailed sibship configurations based on birth order, family size, sibling spacing, and sibling sex.

The effects of delay duration on visual working memory for orientation.

PubMed

Shin, Hongsup; Zou, Qijia; Ma, Wei Ji

2017-12-01

We used a delayed-estimation paradigm to characterize the joint effects of set size (one, two, four, or six) and delay duration (1, 2, 3, or 6 s) on visual working memory for orientation. We conducted two experiments: one with delay durations blocked, another with delay durations interleaved. As dependent variables, we examined four model-free metrics of dispersion as well as precision estimates in four simple models. We tested for effects of delay time using analyses of variance, linear regressions, and nested model comparisons. We found significant effects of set size and delay duration on both model-free and model-based measures of dispersion. However, the effect of delay duration was much weaker than that of set size, dependent on the analysis method, and apparent in only a minority of subjects. The highest forgetting slope found in either experiment at any set size was a modest 1.14°/s. As secondary results, we found a low rate of nontarget reports, and significant estimation biases towards oblique orientations (but no dependence of their magnitude on either set size or delay duration). Relative stability of working memory even at higher set sizes is consistent with earlier results for motion direction and spatial frequency. We compare with a recent study that performed a very similar experiment.

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

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

Determinants of genetic structure in a nonequilibrium metapopulation of the plant Silene latifolia.

PubMed

Fields, Peter D; Taylor, Douglas R

2014-01-01

Population genetic differentiation will be influenced by the demographic history of populations, opportunities for migration among neighboring demes and founder effects associated with repeated extinction and recolonization. In natural populations, these factors are expected to interact with each other and their magnitudes will vary depending on the spatial distribution and age structure of local demes. Although each of these effects has been individually identified as important in structuring genetic variance, their relative magnitude is seldom estimated in nature. We conducted a population genetic analysis in a metapopulation of the angiosperm, Silene latifolia, from which we had more than 20 years of data on the spatial distribution, demographic history, and extinction and colonization of demes. We used hierarchical Bayesian methods to disentangle which features of the populations contributed to among population variation in allele frequencies, including the magnitude and direction of their effects. We show that population age, long-term size and degree of connectivity all combine to affect the distribution of genetic variance; small, recently-founded, isolated populations contributed most to increase FST in the metapopulation. However, the effects of population size and population age are best understood as being modulated through the effects of connectivity to other extant populations, i.e. FST diminishes as populations age, but at a rate that depends how isolated the population is. These spatial and temporal correlates of population structure give insight into how migration, founder effect and within-deme genetic drift have combined to enhance and restrict genetic divergence in a natural metapopulation.

Response to selection while maximizing genetic variance in small populations.

PubMed

Cervantes, Isabel; Gutiérrez, Juan Pablo; Meuwissen, Theo H E

2016-09-20

Rare breeds represent a valuable resource for future market demands. These populations are usually well-adapted, but their low census compromises the genetic diversity and future of these breeds. Since improvement of a breed for commercial traits may also confer higher probabilities of survival for the breed, it is important to achieve good responses to artificial selection. Therefore, efficient genetic management of these populations is essential to ensure that they respond adequately to genetic selection in possible future artificial selection scenarios. Scenarios that maximize the maximum genetic variance in a unique population could be a valuable option. The aim of this work was to study the effect of the maximization of genetic variance to increase selection response and improve the capacity of a population to adapt to a new environment/production system. We simulated a random scenario (A), a full-sib scenario (B), a scenario applying the maximum variance total (MVT) method (C), a MVT scenario with a restriction on increases in average inbreeding (D), a MVT scenario with a restriction on average individual increases in inbreeding (E), and a minimum coancestry scenario (F). Twenty replicates of each scenario were simulated for 100 generations, followed by 10 generations of selection. Effective population size was used to monitor the outcomes of these scenarios. Although the best response to selection was achieved in scenarios B and C, they were discarded because they are unpractical. Scenario A was also discarded because of its low response to selection. Scenario D yielded less response to selection and a smaller effective population size than scenario E, for which response to selection was higher during early generations because of the moderately structured population. In scenario F, response to selection was slightly higher than in Scenario E in the last generations. Application of MVT with a restriction on individual increases in inbreeding resulted in the largest response to selection during early generations, but if inbreeding depression is a concern, a minimum coancestry scenario is then a valuable alternative, in particular for a long-term response to selection.

The effects of surfactant and electrolyte concentrations on the size of nanochitosan during storage

NASA Astrophysics Data System (ADS)

Primaningtyas, Annisa; Budhijanto, Wiratni; Fahrurrozi, Mohammad; Kusumastuti, Yuni

2017-05-01

The nano-sized particle of chitosan (nanochitosan) is a potential natural preservative agent for fresh fish and fish product preservation. Theoretically, nano-sized particles exert strong van der Waals force to each other so that the problem associated with nanochitosan is agglomeration that leads to size instability during storage. Size stability is of importance in the application of nanochitosan as an antimicrobial agent because it considerably affects the antimicrobial activity of chitosan. In this study, the formulation of nanochitosan was optimized with respect to the two major factors in colloid dispersion theory, which were the presence of surfactant and electrolyte. Polysorbate-80 was chosen as the representative of food grade surfactant while NaCl was used as the electrolyte. The purposes of this study were to evaluate the effect of polysorbate-80 concentration and to determine the effect of NaCl ions on the particle size of nanochitosan for at least one month storage period. Data were analyzed using Analysis of Variance (ANOVA) to identify the factors significantly affect the size stability. The dynamics of particle size distribution during storage was measured by Particle Size Analyzer (PSA). The result showed that surfactant did not significantly affect the particle size stability. On the other hand, the addition of electrolyte into the colloidal dispersion of nanochitosan consistently stabilized and also narrowed the particle size distribution during storage in the range of 175-391 nm.

Stroop Color-Word Interference Test: Normative data for the Latin American Spanish speaking adult population.

PubMed

Rivera, D; Perrin, P B; Stevens, L F; Garza, M T; Weil, C; Saracho, C P; Rodríguez, W; Rodríguez-Agudelo, Y; Rábago, B; Weiler, G; García de la Cadena, C; Longoni, M; Martínez, C; Ocampo-Barba, N; Aliaga, A; Galarza-Del-Angel, J; Guerra, A; Esenarro, L; Arango-Lasprilla, J C

2015-01-01

To generate normative data on the Stroop Test across 11 countries in Latin America, with country-specific adjustments for gender, age, and education, where appropriate. The sample consisted of 3,977 healthy adults who were recruited from Argentina, Bolivia, Chile, Cuba, El Salvador, Guatemala, Honduras, Mexico, Paraguay, Peru, and, Puerto Rico. Each subject was administered the Stroop Test, as part of a larger neuropsychological battery. A standardized five-step statistical procedure was used to generate the norms. The final multiple linear regression models explained 14-36% of the variance in Stroop Word scores, 12-41% of the variance in the Stoop Color, 14-36% of the variance in the Stroop Word-Color scores, and 4-15% of variance in Stroop Interference scores. Although t-tests showed significant differences between men and women on the Stroop test, none of the countries had an effect size larger than 0.3. As a result, gender-adjusted norms were not generated. This is the first normative multicenter study conducted in Latin America to create norms for the Stoop Test in a Spanish-Speaking sample. This study will therefore have important implications for the future of neuropsychology research and practice throughout the region.

Income reliably predicts daily sadness, but not happiness: A replication and extension of Kushlev, Dunn, & Lucas (2015)

PubMed Central

Hudson, Nathan W.; Lucas, Richard E.; Donnellan, M. Brent; Kushlev, Kostadin

2017-01-01

Kushlev, Dunn, and Lucas (2015) found that income predicts less daily sadness—but not greater happiness—among Americans. The present study used longitudinal data from an approximately representative German sample to replicate and extend these findings. Our results largely replicated Kushlev and colleagues’: income predicted less daily sadness (albeit with a smaller effect size), but was unrelated to happiness. Moreover, the association between income and sadness could not be explained by demographics, stress, or daily time-use. Extending Kushlev and colleagues’ findings, new analyses indicated that only between-persons variance in income (but not within-persons variance) predicted daily sadness—perhaps because there was relatively little within-persons variance in income. Finally, income predicted less daily sadness and worry, but not less anger or frustration—potentially suggesting that income predicts less “internalizing” but not less “externalizing” negative emotions. Together, our study and Kushlev and colleagues’ provide evidence that income robustly predicts select daily negative emotions—but not positive ones. PMID:29250303

New Trends in Gender and Mathematics Performance: A Meta-Analysis

PubMed Central

Lindberg, Sara M.; Hyde, Janet Shibley; Petersen, Jennifer L.; Linn, Marcia C.

2010-01-01

In this paper, we use meta-analysis to analyze gender differences in recent studies of mathematics performance. First, we meta-analyzed data from 242 studies published between 1990 and 2007, representing the testing of 1,286,350 people. Overall, d = .05, indicating no gender difference, and VR = 1.08, indicating nearly equal male and female variances. Second, we analyzed data from large data sets based on probability sampling of U.S. adolescents over the past 20 years: the NLSY, NELS88, LSAY, and NAEP. Effect sizes for the gender difference ranged between −0.15 and +0.22. Variance ratios ranged from 0.88 to 1.34. Taken together these findings support the view that males and females perform similarly in mathematics. PMID:21038941

Differences between the sexes in technical mastery of rhythmic gymnastics.

PubMed

Bozanic, Ana; Miletic, Durdica

2011-02-01

The aims of this study were to determine possible differences between the sexes in specific rhythmic gymnastics techniques, and to examine the influence of various aspects of technique on rhythmic composition performance. Seventy-five students aged 21 ± 2 years (45 males, 30 female) undertook four test sessions to determine: coefficients of asymmetry, stability, versatility, and the two rhythmic compositions (without apparatus and with rope). An independent-sample t-test revealed sex-based differences in technique acquisition: stability for ball (P < 0.05; effect size = 0.65) and club (P < 0.05; effect size = 0.79) performance and rhythmic composition without apparatus (P < 0.05; effect size = 0.66). Multiple regression analysis revealed that the variables for assessing stability (beta = 0.44; P < 0.05) and versatility (beta = 0.61; P < 0.05) explained 61% of the variance in the rhythmic composition performance of females, and the variables for assessing asymmetry (beta = -0.38; P < 0.05), versatility (beta = 0.32; P < 0.05), and stability (beta = 0.29; P < 0.05) explained 52% of the variance in the rhythmic composition performance of males. The results suggest that female students dominate in body skill technique, while male students have the advantage with apparatus. There was a lack of an expressive aesthetic component in performance for males. The need for ambidexterity should be considered in the planning of training programmes.

Number of pins in two-stage stratified sampling for estimating herbage yield

Treesearch

William G. O' Regan; C. Eugene Conrad

1975-01-01

In a two-stage stratified procedure for sampling herbage yield, plots are stratified by a pin frame in stage one, and clipped. In stage two, clippings from selected plots are sorted, dried, and weighed. Sample size and distribution of plots between the two stages are determined by equations. A way to compute the effect of number of pins on the variance of estimated...

How the variance of some extraction variables may affect the quality of espresso coffees served in coffee shops.

PubMed

Severini, Carla; Derossi, Antonio; Fiore, Anna G; De Pilli, Teresa; Alessandrino, Ofelia; Del Mastro, Arcangela

2016-07-01

To improve the quality of espresso coffee, the variables under the control of the barista, such as grinding grade, coffee quantity and pressure applied to the coffee cake, as well as their variance, are of great importance. A nonlinear mixed effect modeling was used to obtain information on the changes in chemical attributes of espresso coffee (EC) as a function of the variability of extraction conditions. During extraction, the changes in volume were well described by a logistic model, whereas the chemical attributes were better fit by a first-order kinetic. The major source of information was contained in the grinding grade, which accounted for 87-96% of the variance of the experimental data. The variability of the grinding produced changes in caffeine content in the range of 80.03 mg and 130.36 mg when using a constant grinding grade of 6.5. The variability in volume and chemical attributes of EC is large. Grinding had the most important effect as the variability in particle size distribution observed for each grinding level had a profound effect on the quality of EC. Standardization of grinding would be of crucial importance for obtaining all espresso coffees with a high quality. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

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

PubMed

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

2015-10-13

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

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

PubMed

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

2018-07-01

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

Individual and population-level responses to ocean acidification.

PubMed

Harvey, Ben P; McKeown, Niall J; Rastrick, Samuel P S; Bertolini, Camilla; Foggo, Andy; Graham, Helen; Hall-Spencer, Jason M; Milazzo, Marco; Shaw, Paul W; Small, Daniel P; Moore, Pippa J

2016-01-29

Ocean acidification is predicted to have detrimental effects on many marine organisms and ecological processes. Despite growing evidence for direct impacts on specific species, few studies have simultaneously considered the effects of ocean acidification on individuals (e.g. consequences for energy budgets and resource partitioning) and population level demographic processes. Here we show that ocean acidification increases energetic demands on gastropods resulting in altered energy allocation, i.e. reduced shell size but increased body mass. When scaled up to the population level, long-term exposure to ocean acidification altered population demography, with evidence of a reduction in the proportion of females in the population and genetic signatures of increased variance in reproductive success among individuals. Such increased variance enhances levels of short-term genetic drift which is predicted to inhibit adaptation. Our study indicates that even against a background of high gene flow, ocean acidification is driving individual- and population-level changes that will impact eco-evolutionary trajectories.

The Cohesive Population Genetics of Molecular Drive

PubMed Central

Ohta, Tomoko; Dover, Gabriel A.

1984-01-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive. PMID:6500260

The cohesive population genetics of molecular drive.

PubMed

Ohta, T; Dover, G A

1984-10-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

PubMed

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Accounting for Sampling Error When Inferring Population Synchrony from Time-Series Data: A Bayesian State-Space Modelling Approach with Applications

PubMed Central

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Background Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. Methodology/Principal findings The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. Conclusion/Significance The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates. PMID:24489839

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID:29547617

tscvh R Package: Computational of the two samples test on microarray-sequencing data

NASA Astrophysics Data System (ADS)

Fajriyah, Rohmatul; Rosadi, Dedi

2017-12-01

We present a new R package, a tscvh (two samples cross-variance homogeneity), as we called it. This package is a software of the cross-variance statistical test which has been proposed and introduced by Fajriyah ([3] and [4]), based on the cross-variance concept. The test can be used as an alternative test for the significance difference between two means when sample size is small, the situation which is usually appeared in the bioinformatics research. Based on its statistical distribution, the p-value can be also provided. The package is built under a homogeneity of variance between samples.

Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review.

PubMed

Jeran, S; Steinbrecher, A; Pischon, T

2016-08-01

Activity-related energy expenditure (AEE) might be an important factor in the etiology of chronic diseases. However, measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity. Recently, accelerometry has been proposed for objective assessment of physical activity, but it is unclear to what extent this methods explains the variance in AEE. We conducted a systematic review searching MEDLINE database (until 2014) on studies that estimated AEE based on accelerometry-assessed physical activity in adults under free-living conditions (using doubly labeled water method). Extracted study characteristics were sample size, accelerometer (type (uniaxial, triaxial), metrics (for example, activity counts, steps, acceleration), recording period, body position, wear time), explained variance of AEE (R(2)) and number of additional predictors. The relation of univariate and multivariate R(2) with study characteristics was analyzed using nonparametric tests. Nineteen articles were identified. Examination of various accelerometers or subpopulations in one article was treated separately, resulting in 28 studies. Sample sizes ranged from 10 to 149. In most studies the accelerometer was triaxial, worn at the trunk, during waking hours and reported activity counts as output metric. Recording periods ranged from 5 to 15 days. The variance of AEE explained by accelerometer-assessed physical activity ranged from 4 to 80% (median crude R(2)=26%). Sample size was inversely related to the explained variance. Inclusion of 1 to 3 other predictors in addition to accelerometer output significantly increased the explained variance to a range of 12.5-86% (median total R(2)=41%). The increase did not depend on the number of added predictors. We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry. Thus, data on predicted AEE based on accelerometry-assessed physical activity need to be interpreted cautiously.

Improved variance estimation of classification performance via reduction of bias caused by small sample size.

PubMed

Wickenberg-Bolin, Ulrika; Göransson, Hanna; Fryknäs, Mårten; Gustafsson, Mats G; Isaksson, Anders

2006-03-13

Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm that the classifier is robust with good generalization performance to new examples, or at least that it performs better than random guessing. A suggested alternative is to obtain a confidence interval of the error rate using repeated design and test sets selected from available examples. However, it is known that even in the ideal situation of repeated designs and tests with completely novel samples in each cycle, a small test set size leads to a large bias in the estimate of the true variance between design sets. Therefore different methods for small sample performance estimation such as a recently proposed procedure called Repeated Random Sampling (RSS) is also expected to result in heavily biased estimates, which in turn translates into biased confidence intervals. Here we explore such biases and develop a refined algorithm called Repeated Independent Design and Test (RIDT). Our simulations reveal that repeated designs and tests based on resampling in a fixed bag of samples yield a biased variance estimate. We also demonstrate that it is possible to obtain an improved variance estimate by means of a procedure that explicitly models how this bias depends on the number of samples used for testing. For the special case of repeated designs and tests using new samples for each design and test, we present an exact analytical expression for how the expected value of the bias decreases with the size of the test set. We show that via modeling and subsequent reduction of the small sample bias, it is possible to obtain an improved estimate of the variance of classifier performance between design sets. However, the uncertainty of the variance estimate is large in the simulations performed indicating that the method in its present form cannot be directly applied to small data sets.

Design and analysis of three-arm trials with negative binomially distributed endpoints.

PubMed

Mütze, Tobias; Munk, Axel; Friede, Tim

2016-02-20

A three-arm clinical trial design with an experimental treatment, an active control, and a placebo control, commonly referred to as the gold standard design, enables testing of non-inferiority or superiority of the experimental treatment compared with the active control. In this paper, we propose methods for designing and analyzing three-arm trials with negative binomially distributed endpoints. In particular, we develop a Wald-type test with a restricted maximum-likelihood variance estimator for testing non-inferiority or superiority. For this test, sample size and power formulas as well as optimal sample size allocations will be derived. The performance of the proposed test will be assessed in an extensive simulation study with regard to type I error rate, power, sample size, and sample size allocation. For the purpose of comparison, Wald-type statistics with a sample variance estimator and an unrestricted maximum-likelihood estimator are included in the simulation study. We found that the proposed Wald-type test with a restricted variance estimator performed well across the considered scenarios and is therefore recommended for application in clinical trials. The methods proposed are motivated and illustrated by a recent clinical trial in multiple sclerosis. The R package ThreeArmedTrials, which implements the methods discussed in this paper, is available on CRAN. Copyright © 2015 John Wiley & Sons, Ltd.

3D Photonic Crystals Build Up By Self-Organization Of Nanospheres

DTIC Science & Technology

2006-05-23

variance for simple tetragonal Vst , of which general form is defined in Equation (5), could be an important parameter affecting band structure, and it is...plotted along with gap size both as a function of lattice parameter ratio c/a in Figure 2. Apparently, the inverse of variance, i.e. 1/ Vst , shows a...possible. 0.8 1.0 1.2 1.4 1.6 1.8 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 gap size (%) 1/ Vst c/a of simple tetragonal g ap s iz e (% ) 0.85 0.86

Sexual network drivers of HIV and herpes simplex virus type 2 transmission

PubMed Central

Omori, Ryosuke; Abu-Raddad, Laith J.

2017-01-01

Objectives: HIV and herpes simplex virus type 2 (HSV-2) infections are sexually transmitted and propagate in sexual networks. Using mathematical modeling, we aimed to quantify effects of key network statistics on infection transmission, and extent to which HSV-2 prevalence can be a proxy of HIV prevalence. Design/methods: An individual-based simulation model was constructed to describe sex partnering and infection transmission, and was parameterized with representative natural history, transmission, and sexual behavior data. Correlations were assessed on model outcomes (HIV/HSV-2 prevalences) and multiple linear regressions were conducted to estimate adjusted associations and effect sizes. Results: HIV prevalence was one-third or less of HSV-2 prevalence. HIV and HSV-2 prevalences were associated with a Spearman's rank correlation coefficient of 0.64 (95% confidence interval: 0.58–0.69). Collinearities among network statistics were detected, most notably between concurrency versus mean and variance of number of partners. Controlling for confounding, unmarried mean/variance of number of partners (or alternatively concurrency) were the strongest predictors of HIV prevalence. Meanwhile, unmarried/married mean/variance of number of partners (or alternatively concurrency), and clustering coefficient were the strongest predictors of HSV-2 prevalence. HSV-2 prevalence was a strong predictor of HIV prevalence by proxying effects of network statistics. Conclusion: Network statistics produced similar and differential effects on HIV/HSV-2 transmission, and explained most of the variation in HIV and HSV-2 prevalences. HIV prevalence reflected primarily mean and variance of number of partners, but HSV-2 prevalence was affected by a range of network statistics. HSV-2 prevalence (as a proxy) can forecast a population's HIV epidemic potential, thereby informing interventions. PMID:28514276

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

PubMed

Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam

2016-08-17

There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.

Mesoscale spatiotemporal variability in a complex host-parasite system influenced by intermediate host body size

PubMed Central

2017-01-01

Background Parasites are essential components of natural communities, but the factors that generate skewed distributions of parasite occurrences and abundances across host populations are not well understood. Methods Here, we analyse at a seascape scale the spatiotemporal relationships of parasite exposure and host body-size with the proportion of infected hosts (i.e., prevalence) and aggregation of parasite burden across ca. 150 km of the coast and over 22 months. We predicted that the effects of parasite exposure on prevalence and aggregation are dependent on host body-sizes. We used an indirect host-parasite interaction in which migratory seagulls, sandy-shore molecrabs, and an acanthocephalan worm constitute the definitive hosts, intermediate hosts, and endoparasite, respectively. In such complex systems, increments in the abundance of definitive hosts imply increments in intermediate hosts’ exposure to the parasite’s dispersive stages. Results Linear mixed-effects models showed a significant, albeit highly variable, positive relationship between seagull density and prevalence. This relationship was stronger for small (cephalothorax length >15 mm) than large molecrabs (<15 mm). Independently of seagull density, large molecrabs carried significantly more parasites than small molecrabs. The analysis of the variance-to-mean ratio of per capita parasite burden showed no relationship between seagull density and mean parasite aggregation across host populations. However, the amount of unexplained variability in aggregation was strikingly higher in larger than smaller intermediate hosts. This unexplained variability was driven by a decrease in the mean-variance scaling in heavily infected large molecrabs. Conclusions These results show complex interdependencies between extrinsic and intrinsic population attributes on the structure of host-parasite interactions. We suggest that parasite accumulation—a characteristic of indirect host-parasite interactions—and subsequent increasing mortality rates over ontogeny underpin size-dependent host-parasite dynamics. PMID:28828270

Mesoscale spatiotemporal variability in a complex host-parasite system influenced by intermediate host body size.

PubMed

Rodríguez, Sara M; Valdivia, Nelson

2017-01-01

Parasites are essential components of natural communities, but the factors that generate skewed distributions of parasite occurrences and abundances across host populations are not well understood. Here, we analyse at a seascape scale the spatiotemporal relationships of parasite exposure and host body-size with the proportion of infected hosts (i.e., prevalence) and aggregation of parasite burden across ca. 150 km of the coast and over 22 months. We predicted that the effects of parasite exposure on prevalence and aggregation are dependent on host body-sizes. We used an indirect host-parasite interaction in which migratory seagulls, sandy-shore molecrabs, and an acanthocephalan worm constitute the definitive hosts, intermediate hosts, and endoparasite, respectively. In such complex systems, increments in the abundance of definitive hosts imply increments in intermediate hosts' exposure to the parasite's dispersive stages. Linear mixed-effects models showed a significant, albeit highly variable, positive relationship between seagull density and prevalence. This relationship was stronger for small (cephalothorax length >15 mm) than large molecrabs (<15 mm). Independently of seagull density, large molecrabs carried significantly more parasites than small molecrabs. The analysis of the variance-to-mean ratio of per capita parasite burden showed no relationship between seagull density and mean parasite aggregation across host populations. However, the amount of unexplained variability in aggregation was strikingly higher in larger than smaller intermediate hosts. This unexplained variability was driven by a decrease in the mean-variance scaling in heavily infected large molecrabs. These results show complex interdependencies between extrinsic and intrinsic population attributes on the structure of host-parasite interactions. We suggest that parasite accumulation-a characteristic of indirect host-parasite interactions-and subsequent increasing mortality rates over ontogeny underpin size-dependent host-parasite dynamics.

The history of effective population size and genetic diversity in the Yellowstone grizzly (Ursus arctos): implications for conservation.

PubMed

Miller, Craig R; Waits, Lisette P

2003-04-01

Protein, mtDNA, and nuclear microsatellite DNA analyses have demonstrated that the Yellowstone grizzly bear has low levels of genetic variability compared with other Ursus arctos populations. Researchers have attributed this difference to inbreeding during a century of anthropogenic isolation and population size reduction. We test this hypothesis and assess the seriousness of genetic threats by generating microsatellite data for 110 museum specimens collected between 1912 and 1981. A loss of variability is detected, but it is much less severe than hypothesized. Variance in allele frequencies over time is used to estimate an effective population size of approximately 80 across the 20th century and >100 currently. The viability of the population is unlikely to be substantially reduced by genetic factors in the next several generations. However, gene flow from outside populations will be beneficial in avoiding inbreeding and the erosion of genetic diversity in the future.

Automated sampling assessment for molecular simulations using the effective sample size

PubMed Central

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

2010-01-01

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

Genetic parameters for uniformity of harvest weight and body size traits in the GIFT strain of Nile tilapia.

PubMed

Marjanovic, Jovana; Mulder, Han A; Khaw, Hooi L; Bijma, Piter

2016-06-10

Animal breeding programs have been very successful in improving the mean levels of traits through selection. However, in recent decades, reducing the variability of trait levels between individuals has become a highly desirable objective. Reaching this objective through genetic selection requires that there is genetic variation in the variability of trait levels, a phenomenon known as genetic heterogeneity of environmental (residual) variance. The aim of our study was to investigate the potential for genetic improvement of uniformity of harvest weight and body size traits (length, depth, and width) in the genetically improved farmed tilapia (GIFT) strain. In order to quantify the genetic variation in uniformity of traits and estimate the genetic correlations between level and variance of the traits, double hierarchical generalized linear models were applied to individual trait values. Our results showed substantial genetic variation in uniformity of all analyzed traits, with genetic coefficients of variation for residual variance ranging from 39 to 58 %. Genetic correlation between trait level and variance was strongly positive for harvest weight (0.60 ± 0.09), moderate and positive for body depth (0.37 ± 0.13), but not significantly different from 0 for body length and width. Our results on the genetic variation in uniformity of harvest weight and body size traits show good prospects for the genetic improvement of uniformity in the GIFT strain. A high and positive genetic correlation was estimated between level and variance of harvest weight, which suggests that selection for heavier fish will also result in more variation in harvest weight. Simultaneous improvement of harvest weight and its uniformity will thus require index selection.

Determining size and dispersion of minimum viable populations for land management planning and species conservation

NASA Astrophysics Data System (ADS)

Lehmkuhl, John F.

1984-03-01

The concept of minimum populations of wildlife and plants has only recently been discussed in the literature. Population genetics has emerged as a basic underlying criterion for determining minimum population size. This paper presents a genetic framework and procedure for determining minimum viable population size and dispersion strategies in the context of multiple-use land management planning. A procedure is presented for determining minimum population size based on maintenance of genetic heterozygosity and reduction of inbreeding. A minimum effective population size ( N e ) of 50 breeding animals is taken from the literature as the minimum shortterm size to keep inbreeding below 1% per generation. Steps in the procedure adjust N e to account for variance in progeny number, unequal sex ratios, overlapping generations, population fluctuations, and period of habitat/population constraint. The result is an approximate census number that falls within a range of effective population size of 50 500 individuals. This population range defines the time range of short- to long-term population fitness and evolutionary potential. The length of the term is a relative function of the species generation time. Two population dispersion strategies are proposed: core population and dispersed population.

Optimizing occupational exposure measurement strategies when estimating the log-scale arithmetic mean value--an example from the reinforced plastics industry.

PubMed

Lampa, Erik G; Nilsson, Leif; Liljelind, Ingrid E; Bergdahl, Ingvar A

2006-06-01

When assessing occupational exposures, repeated measurements are in most cases required. Repeated measurements are more resource intensive than a single measurement, so careful planning of the measurement strategy is necessary to assure that resources are spent wisely. The optimal strategy depends on the objectives of the measurements. Here, two different models of random effects analysis of variance (ANOVA) are proposed for the optimization of measurement strategies by the minimization of the variance of the estimated log-transformed arithmetic mean value of a worker group, i.e. the strategies are optimized for precise estimation of that value. The first model is a one-way random effects ANOVA model. For that model it is shown that the best precision in the estimated mean value is always obtained by including as many workers as possible in the sample while restricting the number of replicates to two or at most three regardless of the size of the variance components. The second model introduces the 'shared temporal variation' which accounts for those random temporal fluctuations of the exposure that the workers have in common. It is shown for that model that the optimal sample allocation depends on the relative sizes of the between-worker component and the shared temporal component, so that if the between-worker component is larger than the shared temporal component more workers should be included in the sample and vice versa. The results are illustrated graphically with an example from the reinforced plastics industry. If there exists a shared temporal variation at a workplace, that variability needs to be accounted for in the sampling design and the more complex model is recommended.

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics

PubMed Central

Dowding, Irene; Haufe, Stefan

2018-01-01

Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This “naive” approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment. PMID:29615885

Spatially tuned normalization explains attention modulation variance within neurons.

PubMed

Ni, Amy M; Maunsell, John H R

2017-09-01

Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism. NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical area can be largely explained by between-neuron differences in normalization strength. Here we demonstrate that attention modulation size varies within neurons as well and that this variance is largely explained by within-neuron differences in normalization strength. We provide a new spatially tuned normalization model that explains this broad range of observed normalization and attention effects. Copyright © 2017 the American Physiological Society.

An Investigation of the Raudenbush (1988) Test for Studying Variance Heterogeneity.

ERIC Educational Resources Information Center

Harwell, Michael

1997-01-01

The meta-analytic method proposed by S. W. Raudenbush (1988) for studying variance heterogeneity was studied. Results of a Monte Carlo study indicate that the Type I error rate of the test is sensitive to even modestly platykurtic score distributions and to the ratio of study sample size to the number of studies. (SLD)

Effects of composition of grains of debris flow on its impact force

NASA Astrophysics Data System (ADS)

Tang, jinbo; Hu, Kaiheng; Cui, Peng

2017-04-01

Debris flows compose of solid material with broad size distribution from fine sand to boulders. Impact force imposed by debris flows is a very important issue for protection engineering design and strongly influenced by their grain composition. However, this issue has not been studied in depth and the effects of grain composition not been considered in the calculation of the impact force. In this present study, the small-scale flume experiments with five kinds of compositions of grains for debris flow were carried out to study the effect of the composition of grains of debris flow on its impact force. The results show that the impact force of debris flow increases with the grain size, the hydrodynamic pressure of debris flow is calibrated based on the normalization parameter dmax/d50, in which dmax is the maximum size and d50 is the median size. Furthermore, a log-logistic statistic distribution could be used to describe the distribution of magnitude of impact force of debris flow, where the mean and the variance of the present distribution increase with grain size. This distribution proposed in the present study could be used to the reliability analysis of structures impacted by debris flow.

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat.

PubMed

Jighly, Abdulqader; Joukhadar, Reem; Singh, Sukhwinder; Ogbonnaya, Francis C

2018-01-01

Whole genome duplication (WGD) is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW) to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents ( Triticum turgidum; 2n = 4x = 28, AABB subgenomes) with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii ; 2n = 2x = 14, DD subgenome). The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy, which will facilitate the effective utilization of wheat wild relatives in breeding.

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat

PubMed Central

Jighly, Abdulqader; Joukhadar, Reem; Singh, Sukhwinder; Ogbonnaya, Francis C.

2018-01-01

Whole genome duplication (WGD) is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW) to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes) with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome). The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy, which will facilitate the effective utilization of wheat wild relatives in breeding. PMID:29467793

Robustness of the far-field response of nonlocal plasmonic ensembles.

PubMed

Tserkezis, Christos; Maack, Johan R; Liu, Zhaowei; Wubs, Martijn; Mortensen, N Asger

2016-06-22

Contrary to classical predictions, the optical response of few-nm plasmonic particles depends on particle size due to effects such as nonlocality and electron spill-out. Ensembles of such nanoparticles are therefore expected to exhibit a nonclassical inhomogeneous spectral broadening due to size distribution. For a normal distribution of free-electron nanoparticles, and within the simple nonlocal hydrodynamic Drude model, both the nonlocal blueshift and the plasmon linewidth are shown to be considerably affected by ensemble averaging. Size-variance effects tend however to conceal nonlocality to a lesser extent when the homogeneous size-dependent broadening of individual nanoparticles is taken into account, either through a local size-dependent damping model or through the Generalized Nonlocal Optical Response theory. The role of ensemble averaging is further explored in realistic distributions of isolated or weakly-interacting noble-metal nanoparticles, as encountered in experiments, while an analytical expression to evaluate the importance of inhomogeneous broadening through measurable quantities is developed. Our findings are independent of the specific nonclassical theory used, thus providing important insight into a large range of experiments on nanoscale and quantum plasmonics.

Analysis of aperture averaging measurements. [laser scintillation data on the effect of atmospheric turbulence on signal fluctuations

NASA Technical Reports Server (NTRS)

Fried, D. L.

1975-01-01

Laser scintillation data obtained by the NASA Goddard Space Flight Center balloon flight no. 5 from White Sands Missile Range on 19 October 1973 are analyzed. The measurement data, taken with various size receiver apertures, were related to predictions of aperture averaging theory, and it is concluded that the data are in reasonable agreement with theory. The following parameters are assigned to the vertical distribution of the strength of turbulence during the period of the measurements (daytime), for lambda = 0.633 microns, and the source at the zenith; the aperture averaging length is d sub o = 0.125 m, and the log-amplitude variance is (beta sub l)2 = 0.084 square nepers. This corresponds to a normalized point intensity variance of 0.40.

Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT.

PubMed

McCollough, Cynthia H; Ulzheimer, Stefan; Halliburton, Sandra S; Shanneik, Kaiss; White, Richard D; Kalender, Willi A

2007-05-01

To develop a consensus standard for quantification of coronary artery calcium (CAC). A standard for CAC quantification was developed by a multi-institutional, multimanufacturer international consortium of cardiac radiologists, medical physicists, and industry representatives. This report specifically describes the standardization of scan acquisition and reconstruction parameters, the use of patient size-specific tube current values to achieve a prescribed image noise, and the use of the calcium mass score to eliminate scanner- and patient size-based variations. An anthropomorphic phantom containing calibration inserts and additional phantom rings were used to simulate small, medium-size, and large patients. The three phantoms were scanned by using the recommended protocols for various computed tomography (CT) systems to determine the calibration factors that relate measured CT numbers to calcium hydroxyapatite density and to determine the tube current values that yield comparable noise values. Calculation of the calcium mass score was standardized, and the variance in Agatston, volume, and mass scores was compared among CT systems. Use of the recommended scanning parameters resulted in similar noise for small, medium-size, and large phantoms with all multi-detector row CT scanners. Volume scores had greater interscanner variance than did Agatston and calcium mass scores. Use of a fixed calcium hydroxyapatite density threshold (100 mg/cm(3)), as compared with use of a fixed CT number threshold (130 HU), reduced interscanner variability in Agatston and calcium mass scores. With use of a density segmentation threshold, the calcium mass score had the smallest variance as a function of patient size. Standardized quantification of CAC yielded comparable image noise, spatial resolution, and mass scores among different patient sizes and different CT systems and facilitated reduced radiation dose for small and medium-size patients.

Effective size of two feral domestic cat populations (Felis catus L): effect of the mating system.

PubMed

Kaeuffer, R; Pontier, D; Devillard, S; Perrin, N

2004-02-01

A variety of behavioural traits have substantial effects on the gene dynamics and genetic structure of local populations. The mating system is a plastic trait that varies with environmental conditions in the domestic cat (Felis catus) allowing an intraspecific comparison of the impact of this feature on genetic characteristics of the population. To assess the potential effect of the heterogenity of males' contribution to the next generation on variance effective size, we applied the ecological approach of Nunney & Elam (1994) based upon a demographic and behavioural study, and the genetic 'temporal methods' of Waples (1989) and Berthier et al. (2002) using microsatellite markers. The two cat populations studied were nearly closed, similar in size and survival parameters, but differed in their mating system. Immigration appeared extremely restricted in both cases due to environmental and social constraints. As expected, the ratio of effective size to census number (Ne/N) was higher in the promiscuous cat population (harmonic mean = 42%) than in the polygynous one (33%), when Ne was calculated from the ecological method. Only the genetic results based on Waples' estimator were consistent with the ecological results, but failed to evidence an effect of the mating system. Results based on the estimation of Berthier et al. (2002) were extremely variable, with Ne sometimes exceeding census size. Such low reliability in the genetic results should retain attention for conservation purposes.

Emotional Freedom Techniques for Anxiety: A Systematic Review With Meta-analysis.

PubMed

Clond, Morgan

2016-05-01

Emotional Freedom Technique (EFT) combines elements of exposure and cognitive therapies with acupressure for the treatment of psychological distress. Randomized controlled trials retrieved by literature search were assessed for quality using the criteria developed by the American Psychological Association's Division 12 Task Force on Empirically Validated Treatments. As of December 2015, 14 studies (n = 658) met inclusion criteria. Results were analyzed using an inverse variance weighted meta-analysis. The pre-post effect size for the EFT treatment group was 1.23 (95% confidence interval, 0.82-1.64; p < 0.001), whereas the effect size for combined controls was 0.41 (95% confidence interval, 0.17-0.67; p = 0.001). Emotional freedom technique treatment demonstrated a significant decrease in anxiety scores, even when accounting for the effect size of control treatment. However, there were too few data available comparing EFT to standard-of-care treatments such as cognitive behavioral therapy, and further research is needed to establish the relative efficacy of EFT to established protocols.

Population ecology of breeding Pacific common eiders on the Yukon-Kuskokwim Delta, Alaska

USGS Publications Warehouse

Wilson, Heather M.; Flint, Paul L.; Powell, Abby N.; Grand, J. Barry; Moral, Christine L.

2012-01-01

Populations of Pacific common eiders (Somateria mollissima v-nigrum) on the Yukon-Kuskokwim Delta (YKD) in western Alaska declined by 50–90% from 1957 to 1992 and then stabilized at reduced numbers from the early 1990s to the present. We investigated the underlying processes affecting their population dynamics by collection and analysis of demographic data from Pacific common eiders at 3 sites on the YKD (1991–2004) for 29 site-years. We examined variation in components of reproduction, tested hypotheses about the influence of specific ecological factors on life-history variables, and investigated their relative contributions to local population dynamics. Reproductive output was low and variable, both within and among individuals, whereas apparent survival of adult females was high and relatively invariant (0.89 ± 0.005). All reproductive parameters varied across study sites and years. Clutch initiation dates ranged from 4 May to 28 June, with peak (modal) initiation occurring on 26 May. Females at an island study site consistently initiated clutches 3–5 days earlier in each year than those on 2 mainland sites. Population variance in nest initiation date was negatively related to the peak, suggesting increased synchrony in years of delayed initiation. On average, total clutch size (laid) ranged from 4.8 to 6.6 eggs, and declined with date of nest initiation. After accounting for partial predation and non-viability of eggs, average clutch size at hatch ranged from 2.0 to 5.8 eggs. Within seasons, daily survival probability (DSP) of nests was lowest during egg-laying and late-initiation dates. Estimated nest survival varied considerably across sites and years (mean = 0.55, range: 0.06–0.92), but process variance in nest survival was relatively low (0.02, CI: 0.01–0.05), indicating that most variance was likely attributed to sampling error. We found evidence that observer effects may have reduced overall nest survival by 0.0–0.36 across site-years. Study sites with lower sample sizes and more frequent visitations appeared to experience greater observer effects. In general, Pacific common eiders exhibited high spatio-temporal variance in reproductive components. Larger clutch sizes and high nest survival at early initiation dates suggested directional selection favoring early nesting. However, stochastic environmental effects may have precluded response to this apparent selection pressure. Our results suggest that females breeding early in the season have the greatest reproductive value, as these birds lay the largest clutches and have the highest probability of successfully hatching. We developed stochastic, stage-based, matrix population models that incorporated observed spatio-temporal (process) variance and co-variation in vital rates, and projected the stable stage distribution () and population growth rate (λ). We used perturbation analyses to examine the relative influence of changes in vital rates on λ and variance decomposition to assess the proportion of variation in λ explained by process variation in each vital rate. In addition to matrix-based λ, we estimated λ using capture–recapture approaches, and log-linear regression. We found the stable age distribution for Pacific common eiders was weighted heavily towards experienced adult females (≥4 yr of age), and all calculations of λ indicated that the YKD population was stable to slightly increasing (λmatrix = 1.02, CI: 1.00–1.04); λreverse-capture–recapture = 1.05, CI: 0.99–1.11; λlog-linear = 1.04, CI: 0.98–1.10). Perturbation analyses suggested the population would respond most dramatically to changes in adult female survival (relative influence of adult survival was 1.5 times that of fecundity), whereas retrospective variation in λ was primarily explained by fecundity parameters (60%), particularly duckling survival (42%). Among components of fecundity, sensitivities were highest for duckling survival, suggesti

Mapped Plot Patch Size Estimates

Treesearch

Paul C. Van Deusen

2005-01-01

This paper demonstrates that the mapped plot design is relatively easy to analyze and describes existing formulas for mean and variance estimators. New methods are developed for using mapped plots to estimate average patch size of condition classes. The patch size estimators require assumptions about the shape of the condition class, limiting their utility. They may...

School-based prevention program associated with increased short- and long-term retention of safety knowledge.

PubMed

Klas, Karla S; Vlahos, Peter G; McCully, Michael J; Piche, David R; Wang, Stewart C

2015-01-01

Validation of program effectiveness is essential in justifying school-based injury prevention education. Although Risk Watch (RW) targets burn, fire, and life safety, its effectiveness has not been previously evaluated in the medical literature. Between 2007 and 2012, a trained fire service public educator (FSPE) taught RW to all second grade students in one public school district. The curriculum was delivered in 30-minute segments for 9 consecutive weeks via presentations, a safety smoke house trailer, a model-sized hazard house, a student workbook, and parent letters. A written pre-test (PT) was given before RW started, a post-test (PT#1) was given immediately after RW, and a second post-test (PT#2) was administered to the same students the following school year (ranging from 12 to 13 months after PT). Students who did not complete the PT or at least one post-test were excluded. Comparisons were made by paired t-test, analysis of variance, and regression analysis. After 183 (8.7%) were excluded for missing tests, 1,926 remaining students scored significantly higher (P = .0001) on PT#1 (mean 14.8) and PT#2 (mean 14.7) than the PT (mean 12.1). There was 1 FSPE and 36 school teachers with class size ranging from 10 to 27 (mean 21.4). Class size was not predictive of test score improvement (R = 0%), while analysis of variance showed that individual teachers trended toward some influence. This 6-year prospective study demonstrated that the RW program delivered by an FSPE effectively increased short-term knowledge and long-term retention of fire/life safety in early elementary students. Collaborative partnerships are critical to preserving community injury prevention education programs.

Deflation as a method of variance reduction for estimating the trace of a matrix inverse

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

Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

Deflation as a method of variance reduction for estimating the trace of a matrix inverse

DOE PAGES

Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

2017-04-06

Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

Will smaller plates lead to smaller waists? A systematic review and meta-analysis of the effect that experimental manipulation of dishware size has on energy consumption.

PubMed

Robinson, E; Nolan, S; Tudur-Smith, C; Boyland, E J; Harrold, J A; Hardman, C A; Halford, J C G

2014-10-01

It has been suggested that providing consumers with smaller dishware may prove an effective way of helping people eat less and preventing weight gain, but experimental evidence supporting this has been mixed. The objective of the present work was to examine the current evidence base for whether experimentally manipulated differences in dishware size influence food consumption. We systematically reviewed studies that experimentally manipulated the dishware size participants served themselves at a meal with and measured subsequent food intake. We used inverse variance meta-analysis, calculating the standardized mean difference (SMD) in food intake between smaller and larger dishware size conditions. Nine experiments from eight publications were eligible for inclusion. The majority of experiments found no significance difference in food intake when participants ate from smaller vs. larger dishware. With all available data included, analysis indicated a marginal effect of dishware size on food intake, with larger dishware size associated with greater intake. However, this effect was small and there was a large amount of heterogeneity across studies (SMD: -0.18, 95% confidence interval: -0.35, 0.00, I(2) = 77%). Evidence to date does not show that dishware size has a consistent effect on food intake, so recommendations surrounding the use of smaller plates/dishware to improve public health may be premature. © 2014 The Authors. obesity reviews © 2014 World Obesity.

Low genetic diversity and minimal population substructure in the endangered Florida manatee: implications for conservation

USGS Publications Warehouse

Tucker, Kimberly Pause; Hunter, Margaret E.; Bonde, Robert K.; Austin, James D.; Clark, Ann Marie; Beck, Cathy A.; McGuire, Peter M.; Oli, Madan K.

2012-01-01

Species of management concern that have been affected by human activities typically are characterized by low genetic diversity, which can adversely affect their ability to adapt to environmental changes. We used 18 microsatellite markers to genotype 362 Florida manatees (Trichechus manatus latirostris), and investigated genetic diversity, population structure, and estimated genetically effective population size (Ne). The observed and expected heterozygosity and average number of alleles were 0.455 ± 0.04, 0.479 ± 0.04, and 4.77 ± 0.51, respectively. All measures of Florida manatee genetic diversity were less than averages reported for placental mammals, including fragmented or nonideal populations. Overall estimates of differentiation were low, though significantly greater than zero, and analysis of molecular variance revealed that over 95% of the total variance was among individuals within predefined management units or among individuals along the coastal subpopulations, with only minor portions of variance explained by between group variance. Although genetic issues, as inferred by neutral genetic markers, appear not to be critical at present, the Florida manatee continues to face demographic challenges due to anthropogenic activities and stochastic factors such as red tides, oil spills, and disease outbreaks; these can further reduce genetic diversity of the manatee population.

On the competition among aerosol number, size and composition in predicting CCN variability: a multi-annual field study in an urbanized desert.

PubMed

Crosbie, E; Youn, J-S; Balch, B; Wonaschütz, A; Shingler, T; Wang, Z; Conant, W C; Betterton, E A; Sorooshian, A

2015-02-10

A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012-2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm -3 ), highest in winter (430 cm -3 ) and have a secondary peak during the North American monsoon season (July to September; 372 cm -3 ). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm -3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41% (pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.

Bias correction for estimated QTL effects using the penalized maximum likelihood method.

PubMed

Zhang, J; Yue, C; Zhang, Y-M

2012-04-01

A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.

Partitioning degrees of freedom in hierarchical and other richly-parameterized models.

PubMed

Cui, Yue; Hodges, James S; Kong, Xiaoxiao; Carlin, Bradley P

2010-02-01

Hodges & Sargent (2001) developed a measure of a hierarchical model's complexity, degrees of freedom (DF), that is consistent with definitions for scatterplot smoothers, interpretable in terms of simple models, and that enables control of a fit's complexity by means of a prior distribution on complexity. DF describes complexity of the whole fitted model but in general it is unclear how to allocate DF to individual effects. We give a new definition of DF for arbitrary normal-error linear hierarchical models, consistent with Hodges & Sargent's, that naturally partitions the n observations into DF for individual effects and for error. The new conception of an effect's DF is the ratio of the effect's modeled variance matrix to the total variance matrix. This gives a way to describe the sizes of different parts of a model (e.g., spatial clustering vs. heterogeneity), to place DF-based priors on smoothing parameters, and to describe how a smoothed effect competes with other effects. It also avoids difficulties with the most common definition of DF for residuals. We conclude by comparing DF to the effective number of parameters p(D) of Spiegelhalter et al (2002). Technical appendices and a dataset are available online as supplemental materials.

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

PubMed

Lu, Kaifeng

2016-05-01

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

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

PubMed

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

2010-01-15

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

Predicting research use in nursing organizations: a multilevel analysis.

PubMed

Estabrooks, Carole A; Midodzi, William K; Cummings, Greta G; Wallin, Lars

2007-01-01

No empirical literature was found that explained how organizational context (operationalized as a composite of leadership, culture, and evaluation) influences research utilization. Similarly, no work was found on the interaction of individuals and contextual factors, or the relative importance or contribution of forces at different organizational levels to either such proposed interactions or, ultimately, to research utilization. To determine independent factors that predict research utilization among nurses, taking into account influences at individual nurse, specialty, and hospital levels. Cross-sectional survey data for 4,421 registered nurses in Alberta, Canada were used in a series of multilevel (three levels) modeling analyses to predict research utilization. A multilevel model was developed in MLwiN version 2.0 and used to: (a) estimate simultaneous effects of several predictors and (b) quantify the amount of explained variance in research utilization that could be apportioned to individual, specialty, and hospital levels. There was significant variation in research utilization (p <.05). Factors (remaining in the final model at statistically significant levels) found to predict more research utilization at the three levels of analysis were as follows. At the individual nurse level (Level 1): time spent on the Internet and lower levels of emotional exhaustion. At the specialty level (Level 2): facilitation, nurse-to-nurse collaboration, a higher context (i.e., of nursing culture, leadership, and evaluation), and perceived ability to control policy. At the hospital level (Level 3): only hospital size was significant in the final model. The total variance in research utilization was 1.04, and the intraclass correlations (the percent contribution by contextual factors) were 4% (variance = 0.04, p <.01) at the hospital level and 8% (variance = 0.09, p <.05) at the specialty level. The contribution attributable to individual factors alone was 87% (variance = 0.91, p <.01). Variation in research utilization was explained mainly by differences in individual characteristics, with specialty- and organizational-level factors contributing relatively little by comparison. Among hospital-level factors, hospital size was the only significant determinant of research utilization. Although organizational determinants explained less variance in the model, they were still statistically significant when analyzed alone. These findings suggest that investigations into mechanisms that influence research utilization must address influences at multiple levels of the organization. Such investigations will require careful attention to both methodological and interpretative challenges present when dealing with multiple units of analysis.

Determining the size of a complete disturbance landscape: multi-scale, continental analysis of forest change.

PubMed

Buma, Brian; Costanza, Jennifer K; Riitters, Kurt

2017-11-21

The scale of investigation for disturbance-influenced processes plays a critical role in theoretical assumptions about stability, variance, and equilibrium, as well as conservation reserve and long-term monitoring program design. Critical consideration of scale is required for robust planning designs, especially when anticipating future disturbances whose exact locations are unknown. This research quantified disturbance proportion and pattern (as contagion) at multiple scales across North America. This pattern of scale-associated variability can guide selection of study and management extents, for example, to minimize variance (measured as standard deviation) between any landscapes within an ecoregion. We identified the proportion and pattern of forest disturbance (30 m grain size) across multiple landscape extents up to 180 km 2 . We explored the variance in proportion of disturbed area and the pattern of that disturbance between landscapes (within an ecoregion) as a function of the landscape extent. In many ecoregions, variance between landscapes within an ecoregion was minimal at broad landscape extents (low standard deviation). Gap-dominated regions showed the least variance, while fire-dominated showed the largest. Intensively managed ecoregions displayed unique patterns. A majority of the ecoregions showed low variance between landscapes at some scale, indicating an appropriate extent for incorporating natural regimes and unknown future disturbances was identified. The quantification of the scales of disturbance at the ecoregion level provides guidance for individuals interested in anticipating future disturbances which will occur in unknown spatial locations. Information on the extents required to incorporate disturbance patterns into planning is crucial for that process.

The Comstar D/3 gain degradation experiment

NASA Technical Reports Server (NTRS)

Lee, T. C.; Hodge, D. B.

1981-01-01

The results of gain degradation measurements using the Comstar D/3 19.04 GHz beacon are reported. This experiment utilized 0.6 and 5 m aperture antennas aligned along the same propagation path to examine propagation effects which are related to the antenna aperture size. Sample data for clear air, scintillation in clear air, and precipitation fading are presented. Distributions of the received signal levels and variances for both antennas are also presented.

Size matters for lice on birds: Coevolutionary allometry of host and parasite body size.

PubMed

Harnos, Andrea; Lang, Zsolt; Petrás, Dóra; Bush, Sarah E; Szabó, Krisztián; Rózsa, Lajos

2017-02-01

Body size is one of the most fundamental characteristics of all organisms. It influences physiology, morphology, behavior, and even interspecific interactions such as those between parasites and their hosts. Host body size influences the magnitude and variability of parasite size according to Harrison's rule (HR: positive relationship between host and parasite body sizes) and Poulin's Increasing Variance Hypothesis (PIVH: positive relationship between host body size and the variability of parasite body size). We analyzed parasite-host body size allometry for 581 species of avian lice (∼15% of known diversity) and their hosts. We applied phylogenetic generalized least squares (PGLS) methods to account for phylogenetic nonindependence controlling for host and parasite phylogenies separately and variance heterogeneity. We tested HR and PIVH for the major families of avian lice (Ricinidae, Menoponidae, Philopteridae), and for distinct ecological guilds within Philopteridae. Our data indicate that most families and guilds of avian lice follow both HR and PIVH; however, ricinids did not follow PIVH and the "body lice" guild of philopterid lice did not follow HR or PIVH. We discuss mathematical and ecological factors that may be responsible for these patterns, and we discuss the potential pervasiveness of these relationships among all parasites on Earth. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Instructional designing the STEM education model for fostering creative thinking abilities in physics laboratory environment classes

NASA Astrophysics Data System (ADS)

Chanthala, Chumpon; Santiboon, Toansakul; Ponkham, Kamon

2018-01-01

To investigate the effects of students' activity-based on learning approaching management through the STEM Education Instructional Model for fostering their creative thinking abilities of their learning achievements in physics laboratory classroom environments with the sample size consisted of 48 students at the 10th grade level in two classes in Mahasarakham University Demonstration School(Secondary Division) in Thailand. Students' creative thinking abilities were assessed with the with the 24-item GuilfordCreative Thinking Questionnaire (GCTQ). Students' perceptions of their physics classroom learning environments were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Associations between students' learning achievements of their post-test assessment indicated that 26% of the coefficient predictive value (R2) of the variance in students' creative thinking abilities was attributable to their perceptions for the GCTQ. Students' learning outcomes of their post-test assessment, the R2value indicated that 35% of the variances for the PLEI, the R2value indicated that 63% of the variances for their creative thinking abilities were attributable to theiraffecting the activity-based on learning for fostering their creative thinking are provided.

Factors impacting sense of community among adults with brain injury.

PubMed

Ditchman, Nicole; Chan, Fong; Haak, Christopher; Easton, Amanda B

2017-05-01

Despite increasing interest in examining community outcomes following disability, sense of community (SOC) has received relatively no attention in the rehabilitation literature. SOC refers to feelings of belonging and attachment one has for a community and is of particular relevance for people with brain injury who are at increased risk of social isolation. The aim of this study was to investigate factors contributing to SOC for individuals with brain injury. Members from 2 brain injury associations (n = 98) participated in this survey-based study. Hierarchical regression analysis was used to explore demographic, disability-related, community and social participation variables' impact on SOC with regard to one's town or city. Follow-up mediation analyses were conducted to explore relationships among social self-efficacy, support network, neighboring behavior, and SOC. Findings indicated that disability-related and community variables accounted for over 40% of the variance in SOC. Size of social support network was the only significant independent contributor to SOC variance. Follow-up analyses provided support for (a) the partial mediating effect of social support network size on the relationship between social self-efficacy and SOC, and (b) the mediating effect of neighboring behavior on the relationship between social self-efficacy and social support network size. Findings from this study highlight the particular importance of self-efficacy, social support, and neighboring behaviors in promoting SOC for people with brain injury. Recommendations are provided to advance research efforts and inform intervention approaches to improve the felt experience of community among people with brain injury. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Decadal climate prediction in the large ensemble limit

NASA Astrophysics Data System (ADS)

Yeager, S. G.; Rosenbloom, N. A.; Strand, G.; Lindsay, K. T.; Danabasoglu, G.; Karspeck, A. R.; Bates, S. C.; Meehl, G. A.

2017-12-01

In order to quantify the benefits of initialization for climate prediction on decadal timescales, two parallel sets of historical simulations are required: one "initialized" ensemble that incorporates observations of past climate states and one "uninitialized" ensemble whose internal climate variations evolve freely and without synchronicity. In the large ensemble limit, ensemble averaging isolates potentially predictable forced and internal variance components in the "initialized" set, but only the forced variance remains after averaging the "uninitialized" set. The ensemble size needed to achieve this variance decomposition, and to robustly distinguish initialized from uninitialized decadal predictions, remains poorly constrained. We examine a large ensemble (LE) of initialized decadal prediction (DP) experiments carried out using the Community Earth System Model (CESM). This 40-member CESM-DP-LE set of experiments represents the "initialized" complement to the CESM large ensemble of 20th century runs (CESM-LE) documented in Kay et al. (2015). Both simulation sets share the same model configuration, historical radiative forcings, and large ensemble sizes. The twin experiments afford an unprecedented opportunity to explore the sensitivity of DP skill assessment, and in particular the skill enhancement associated with initialization, to ensemble size. This talk will highlight the benefits of a large ensemble size for initialized predictions of seasonal climate over land in the Atlantic sector as well as predictions of shifts in the likelihood of climate extremes that have large societal impact.

Synthetic aperture radar operator tactical target acquisition research

NASA Technical Reports Server (NTRS)

Hershberger, M. L.; Craig, D. W.

1978-01-01

A radar target acquisition research study was conducted to access the effects of two levels of 13 radar sensor, display, and mission parameters on operator tactical target acquisition. A saturated fractional-factorial screening design was employed to examine these parameters. Data analysis computed ETA squared values for main and second-order effects for the variables tested. Ranking of the research parameters in terms of importance to system design revealed four variables (radar coverage, radar resolution/multiple looks, display resolution, and display size) accounted for 50 percent of the target acquisition probability variance.

Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle.

PubMed

Uemoto, Yoshinobu; Sasaki, Shinji; Kojima, Takatoshi; Sugimoto, Yoshikazu; Watanabe, Toshio

2015-11-19

Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data. In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design. The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV. The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured using denser SNPs and the prediction model accounted for MAF, but a large sample size is needed to increase the accuracy of GEBV under all QTL MAF categories.

Post-stratified estimation: with-in strata and total sample size recommendations

Treesearch

James A. Westfall; Paul L. Patterson; John W. Coulston

2011-01-01

Post-stratification is used to reduce the variance of estimates of the mean. Because the stratification is not fixed in advance, within-strata sample sizes can be quite small. The survey statistics literature provides some guidance on minimum within-strata sample sizes; however, the recommendations and justifications are inconsistent and apply broadly for many...

A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models

ERIC Educational Resources Information Center

Jackson, Dennis L.; Voth, Jennifer; Frey, Marc P.

2013-01-01

Determining an appropriate sample size for use in latent variable modeling techniques has presented ongoing challenges to researchers. In particular, small sample sizes are known to present concerns over sampling error for the variances and covariances on which model estimation is based, as well as for fit indexes and convergence failures. The…

A distribution model for the aerial application of granular agricultural particles

NASA Technical Reports Server (NTRS)

Fernandes, S. T.; Ormsbee, A. I.

1978-01-01

A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

A Note on Maximized Posttest Contrasts.

ERIC Educational Resources Information Center

Williams, John D.

1979-01-01

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

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.

Embryogenesis in the anthers of different ornamental pepper (Capsicum annuum L.) genotypes.

PubMed

Barroso, P A; Rêgo, M M; Rêgo, E R; Soares, W S

2015-10-27

The aim of this study was to relate flower bud size with microspore developmental stages and the induction of embryos in the anthers of different ornamental pepper (Capsicum annuum L.) genotypes. Flower buds were randomly collected and visually divided into three classes based on both petal and sepal size. The length and diameter of the bud as well as the length of the petal, sepal, and anther were then measured. The microspore stage was also determined for each anther of the bud where it was found. The data were subjected to analysis of variance (P ≤ 0.01), and the means were separated by Tukey's test (P ≤ 0.01). The broad sense heritability, the CVg/CVe relation, and the Pearson correlation between characters were also determined. Anthers from 10 C. annuum genotypes were cultivated in four culture media types for the induction of embryos. The data were transformed by Arcsin (x) and subjected to analysis of variance (P ≤ 0.01), and the means were separated by Tukey's test (P ≤ 0.01). The majority of anthers in the second class had uninucleate microspores. No correlation was observed between bud size and the number of uninucleate microspores. Genotype 9 specimens grown in M2 medium induced the highest number of embryos (16) compared to the other treatments, which indicates a significant interaction effect between culture media and genotypes.

Structure analysis of simulated molecular clouds with the Δ-variance

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

Bertram, Erik; Klessen, Ralf S.; Glover, Simon C. O.

Here, we employ the Δ-variance analysis and study the turbulent gas dynamics of simulated molecular clouds (MCs). Our models account for a simplified treatment of time-dependent chemistry and the non-isothermal nature of the gas. We investigate simulations using three different initial mean number densities of n 0 = 30, 100 and 300 cm -3 that span the range of values typical for MCs in the solar neighbourhood. Furthermore, we model the CO line emission in a post-processing step using a radiative transfer code. We evaluate Δ-variance spectra for centroid velocity (CV) maps as well as for integrated intensity and columnmore » density maps for various chemical components: the total, H 2 and 12CO number density and the integrated intensity of both the 12CO and 13CO (J = 1 → 0) lines. The spectral slopes of the Δ-variance computed on the CV maps for the total and H 2 number density are significantly steeper compared to the different CO tracers. We find slopes for the linewidth–size relation ranging from 0.4 to 0.7 for the total and H 2 density models, while the slopes for the various CO tracers range from 0.2 to 0.4 and underestimate the values for the total and H 2 density by a factor of 1.5–3.0. We demonstrate that optical depth effects can significantly alter the Δ-variance spectra. Furthermore, we report a critical density threshold of 100 cm -3 at which the Δ-variance slopes of the various CO tracers change sign. We thus conclude that carbon monoxide traces the total cloud structure well only if the average cloud density lies above this limit.« less

Structure analysis of simulated molecular clouds with the Δ-variance

DOE PAGES

Bertram, Erik; Klessen, Ralf S.; Glover, Simon C. O.

2015-05-27

Here, we employ the Δ-variance analysis and study the turbulent gas dynamics of simulated molecular clouds (MCs). Our models account for a simplified treatment of time-dependent chemistry and the non-isothermal nature of the gas. We investigate simulations using three different initial mean number densities of n 0 = 30, 100 and 300 cm -3 that span the range of values typical for MCs in the solar neighbourhood. Furthermore, we model the CO line emission in a post-processing step using a radiative transfer code. We evaluate Δ-variance spectra for centroid velocity (CV) maps as well as for integrated intensity and columnmore » density maps for various chemical components: the total, H 2 and 12CO number density and the integrated intensity of both the 12CO and 13CO (J = 1 → 0) lines. The spectral slopes of the Δ-variance computed on the CV maps for the total and H 2 number density are significantly steeper compared to the different CO tracers. We find slopes for the linewidth–size relation ranging from 0.4 to 0.7 for the total and H 2 density models, while the slopes for the various CO tracers range from 0.2 to 0.4 and underestimate the values for the total and H 2 density by a factor of 1.5–3.0. We demonstrate that optical depth effects can significantly alter the Δ-variance spectra. Furthermore, we report a critical density threshold of 100 cm -3 at which the Δ-variance slopes of the various CO tracers change sign. We thus conclude that carbon monoxide traces the total cloud structure well only if the average cloud density lies above this limit.« less

A Monte Carlo Study of Levene's Test of Homogeneity of Variance: Empirical Frequencies of Type I Error in Normal Distributions.

ERIC Educational Resources Information Center

Neel, John H.; Stallings, William M.

An influential statistics test recommends a Levene text for homogeneity of variance. A recent note suggests that Levene's test is upwardly biased for small samples. Another report shows inflated Alpha estimates and low power. Neither study utilized more than two sample sizes. This Monte Carlo study involved sampling from a normal population for…

Life-history traits and effective population size in species with overlapping generations revisited: the importance of adult mortality.

PubMed

Waples, R S

2016-10-01

The relationship between life-history traits and the key eco-evolutionary parameters effective population size (Ne) and Ne/N is revisited for iteroparous species with overlapping generations, with a focus on the annual rate of adult mortality (d). Analytical methods based on populations with arbitrarily long adult lifespans are used to evaluate the influence of d on Ne, Ne/N and the factors that determine these parameters: adult abundance (N), generation length (T), age at maturity (α), the ratio of variance to mean reproductive success in one season by individuals of the same age (φ) and lifetime variance in reproductive success of individuals in a cohort (Vk•). Although the resulting estimators of N, T and Vk• are upwardly biased for species with short adult lifespans, the estimate of Ne/N is largely unbiased because biases in T are compensated for by biases in Vk• and N. For the first time, the contrasting effects of T and Vk• on Ne and Ne/N are jointly considered with respect to d and φ. A simple function of d and α based on the assumption of constant vital rates is shown to be a robust predictor (R(2)=0.78) of Ne/N in an empirical data set of life tables for 63 animal and plant species with diverse life histories. Results presented here should provide important context for interpreting the surge of genetically based estimates of Ne that has been fueled by the genomics revolution.

Effects of intravenous, sternal, and humerus intraosseous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

PubMed

Blouin, Dawn; Gegel, Brian T; Johnson, Don; Garcia-Blanco, Jose C

2016-01-01

To determine if there were significant differences among humerus intraosseous (HIO), sternal intraosseous (SIO), and intravenous (IV) administration of 500 mL Hextend in hemodynamics or administration time in a hypovolemic swine model. Vivarium. Yorkshire swine; sample size was based on a large effect size of 0.5, an α of 0.05, and a power of 80 percent Swine were randomly assigned to one of four groups: HIO (n = 9), SIO (n = 9), IV (n = 9), and control (n = 9). Swine were exsanguinated 30 percent of their blood volume. Hextend (500 mL) was administered by either the HIO, SIO, or IV route; the control group received none. Time of administration of Hextend; systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), heart rate (HR), cardiac output (CO), and stroke volume (SV) data were collected every 2 minutes and compared by group over 8 minutes. A repeated analysis of variance found that there were no significant differences in SBP, DBP, MAP, HR, CO, and SV among HIO, SIO, and IV groups over 8 minutes (p > 0.05). An analyses of variance determined that there was no significant difference between groups relative to time of administration (p = 0.521). When IV access is difficult, both HIO and SIO are effective techniques for rapid vascular access and the administration of Hextend for patients in hypovolemic shock.

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

PubMed

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

2013-03-01

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

Combining ability analysis for within-boll yield components in upland cotton (Gossypium hirsutum L.).

PubMed

Imran, M; Shakeel, A; Azhar, F M; Farooq, J; Saleem, M F; Saeed, A; Nazeer, W; Riaz, M; Naeem, M; Javaid, A

2012-08-24

Cotton is an important cash crop worldwide, accounting for a large percentage of world agricultural exports; however, yield per acre is still poor in many countries, including Pakistan. Diallel mating system was used to identify parents for improving within-boll yield and fiber quality parameters. Combining ability analysis was employed to obtain suitable parents for this purpose. The parental genotypes CP-15/2, NIAB Krishma, CIM-482, MS-39, and S-12 were crossed in complete diallel mating under green house conditions during 2009. The F₀ seed of 20 hybrids and five parents were planted in the field in randomized complete block design with three replications during 2010. There were highly significant differences among all F₁ hybrids and their parents. Specific combining ability (SCA) variance was greater than general combining ability (GCA) variance for bolls per plant (9.987), seeds per boll (0.635), seed density (5.672), lint per seed (4.174), boll size (3.69), seed cotton yield (0.315), and lint percentage (0.470), showing predominance of non-additive genes; while seed volume (3.84) was controlled by additive gene action based on maximum GCA variance. Cultivar MS-39 was found to be the best general combiner for seed volume (0.102), seeds per boll (0.448), and lint per seed (0.038) and its utilization produced valuable hybrids, including MS-39 x NIAB Krishma and MS-39 x S-12. The parental line CIM-482 had high GCA effects for boll size (0.33) and seeds per boll (0.90). It also showed good SCA with S-12 and NIAB Krishma for bolls per plant, with CP- 15/2 for boll size, and with MS-39 for seeds per boll. The hybrids, namely, CP-15/2 x NIAB Krishma, NIAB Krishma x S-12, NIAB Krishma x CIM-482, MS-39 x NIAB Krishma, MS-39 x CP-15/2, and S-12 x MS-39 showed promising results. Correlation analysis revealed that seed cotton yield showed significant positive correlation with bolls per plant, boll size and seeds per boll while it showed negative correlation with lint percentage and lint per seed. Seed volume showed significant negative correlation with seed density. Seeds per boll were positively correlated with boll size and negatively correlated with bolls per plant lint percentage and lint per seed. Similarly, lint per seed exhibited positive correlation with lint percentage and boll size showed significantly negative correlation with bolls per plant. Presence of non-additive genetic effects in traits like bolls per plant, seeds per boll, lint per seed, seed cotton yield, and lint percentage is indicative of later generation selection or heterosis breeding may be adopted. For boll size, seed volume and seed density early generation selection may be followed because of the presence of additive gene action. The parental material used in this study and cross combinations obtained from these parents may be exploited in future breeding endeavors.

Association of total mixed ration particle fractions retained on the Penn State Particle Separator with milk, fat, and protein yield lactation curves at the cow level.

PubMed

Caccamo, M; Ferguson, J D; Veerkamp, R F; Schadt, I; Petriglieri, R; Azzaro, G; Pozzebon, A; Licitra, G

2014-01-01

As part of a larger project aiming to develop management evaluation tools based on results from test-day (TD) models, the objective of this study was to examine the effect of physical composition of total mixed rations (TMR) tested quarterly from March 2006 through December 2008 on milk, fat, and protein yield curves for 25 herds in Ragusa, Sicily. A random regression sire-maternal grandsire model was used to estimate variance components for milk, fat, and protein yields fitted on a full data set, including 241,153 TD records from 9,809 animals in 42 herds recorded from 1995 through 2008. The model included parity, age at calving, year at calving, and stage of pregnancy as fixed effects. Random effects were herd × test date, sire and maternal grandsire additive genetic effect, and permanent environmental effect modeled using third-order Legendre polynomials. Model fitting was carried out using ASREML. Afterward, for the 25 herds involved in the study, 9 particle size classes were defined based on the proportions of TMR particles on the top (19-mm) and middle (8-mm) screen of the Penn State Particle Separator. Subsequently, the model with estimated variance components was used to examine the influence of TMR particle size class on milk, fat, and protein yield curves. An interaction was included with the particle size class and days in milk. The effect of the TMR particle size class was modeled using a ninth-order Legendre polynomial. Lactation curves were predicted from the model while controlling for TMR chemical composition (crude protein content of 15.5%, neutral detergent fiber of 40.7%, and starch of 19.7% for all classes), to have pure estimates of particle distribution not confounded by nutrient content of TMR. We found little effect of class of particle proportions on milk yield and fat yield curves. Protein yield was greater for sieve classes with 10.4 to 17.4% of TMR particles retained on the top (19-mm) sieve. Optimal distributions different from those recommended may reflect regional differences based on climate and types and quality of forages fed. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genomic analysis of cow mortality and milk production using a threshold-linear model.

PubMed

Tsuruta, S; Lourenco, D A L; Misztal, I; Lawlor, T J

2017-09-01

The objective of this study was to investigate the feasibility of genomic evaluation for cow mortality and milk production using a single-step methodology. Genomic relationships between cow mortality and milk production were also analyzed. Data included 883,887 (866,700) first-parity, 733,904 (711,211) second-parity, and 516,256 (492,026) third-parity records on cow mortality (305-d milk yields) of Holsteins from Northeast states in the United States. The pedigree consisted of up to 1,690,481 animals including 34,481 bulls genotyped with 36,951 SNP markers. Analyses were conducted with a bivariate threshold-linear model for each parity separately. Genomic information was incorporated as a genomic relationship matrix in the single-step BLUP. Traditional and genomic estimated breeding values (GEBV) were obtained with Gibbs sampling using fixed variances, whereas reliabilities were calculated from variances of GEBV samples. Genomic EBV were then converted into single nucleotide polymorphism (SNP) marker effects. Those SNP effects were categorized according to values corresponding to 1 to 4 standard deviations. Moving averages and variances of SNP effects were calculated for windows of 30 adjacent SNP, and Manhattan plots were created for SNP variances with the same window size. Using Gibbs sampling, the reliability for genotyped bulls for cow mortality was 28 to 30% in EBV and 70 to 72% in GEBV. The reliability for genotyped bulls for 305-d milk yields was 53 to 65% to 81 to 85% in GEBV. Correlations of SNP effects between mortality and 305-d milk yields within categories were the highest with the largest SNP effects and reached >0.7 at 4 standard deviations. All SNP regions explained less than 0.6% of the genetic variance for both traits, except regions close to the DGAT1 gene, which explained up to 2.5% for cow mortality and 4% for 305-d milk yields. Reliability for GEBV with a moderate number of genotyped animals can be calculated by Gibbs samples. Genomic information can greatly increase the reliability of predictions not only for milk but also for mortality. The existence of a common region on Bos taurus autosome 14 affecting both traits may indicate a major gene with a pleiotropic effect on milk and mortality. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A resource for the assessment of lung nodule size estimation methods: database of thoracic CT scans of an anthropomorphic phantom◊

PubMed Central

Gavrielides, Marios A.; Kinnard, Lisa M.; Myers, Kyle J.; Peregoy, Jennifer; Pritchard, William F.; Zeng, Rongping; Esparza, Juan; Karanian, John; Petrick, Nicholas

2010-01-01

A number of interrelated factors can affect the precision and accuracy of lung nodule size estimation. To quantify the effect of these factors, we have been conducting phantom CT studies using an anthropomorphic thoracic phantom containing a vasculature insert to which synthetic nodules were inserted or attached. Ten repeat scans were acquired on different multi-detector scanners, using several sets of acquisition and reconstruction protocols and various nodule characteristics (size, shape, density, location). This study design enables both bias and variance analysis for the nodule size estimation task. The resulting database is in the process of becoming publicly available as a resource to facilitate the assessment of lung nodule size estimation methodologies and to enable comparisons between different methods regarding measurement error. This resource complements public databases of clinical data and will contribute towards the development of procedures that will maximize the utility of CT imaging for lung cancer screening and tumor therapy evaluation. PMID:20640011

Separating parental environment from seed size effects on next generation growth and development in Arabidopsis.

PubMed

Elwell, Angela L; Gronwall, David S; Miller, Nathan D; Spalding, Edgar P; Brooks, Tessa L Durham

2011-02-01

Plant growth and development is profoundly influenced by environmental conditions that laboratory experimentation typically attempts to control. However, growth conditions are not uniform between or even within laboratories and the extent to which these differences influence plant growth and development is unknown. Experiments with wild-type Arabidopsis thaliana were designed to quantify the influences of parental environment and seed size on growth and development in the next generation. A single lot of seed was planted in six environmental chambers and grown to maturity. The seed produced was mechanically sieved into small and large size classes then grown in a common environment and subjected to a set of assays spanning the life cycle. Analysis of variance demonstrated that seed size effects were particularly significant early in development, affecting primary root growth and gravitropism, but also flowering time. Parental environment affected progeny germination time, flowering and weight of seed the progeny produced. In some cases, the parental environment affected the magnitude of (interacted with) the observed seed size effects. These data indicate that life history circumstances of the parental generation can affect growth and development throughout the life cycle of the next generation to an extent that should be considered when performing genetic studies. © 2010 Blackwell Publishing Ltd.

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.

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

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

Öztürk, Hande; Noyan, I. Cevdet

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

DOE PAGES

Öztürk, Hande; Noyan, I. Cevdet

2017-08-24

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

Population growth enhances the mean fixation time of neutral mutations and the persistence of neutral variation.

PubMed

Waxman, D

2012-06-01

A fundamental result of population genetics states that a new mutation, at an unlinked neutral locus in a randomly mating diploid population, has a mean time of fixation of ∼4N(e) generations, where N(e) is the effective population size. This result is based on an assumption of fixed population size, which does not universally hold in natural populations. Here, we analyze such neutral fixations in populations of changing size within the framework of the diffusion approximation. General expressions are derived for the mean and variance of the fixation time in changing populations. Some explicit results are given for two cases: (i) the effective population size undergoes a sudden change, representing a sudden population expansion or a sudden bottleneck; (ii) the effective population changes linearly for a limited period of time and then remains constant. Additionally, a lower bound for the mean time of fixation is obtained for an effective population size that increases with time, and this is applied to exponentially growing populations. The results obtained in this work show, among other things, that for populations that increase in size, the mean time of fixation can be enhanced, sometimes substantially so, over 4N(e,0) generations, where N(e,0) is the effective population size at the time the mutation arises. Such an enhancement is associated with (i) an increased probability of neutral polymorphism in a population and (ii) an enhanced persistence of high-frequency neutral variation, which is the variation most likely to be observed.

Interval estimation and optimal design for the within-subject coefficient of variation for continuous and binary variables

PubMed Central

Shoukri, Mohamed M; Elkum, Nasser; Walter, Stephen D

2006-01-01

Background In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements for the within-subject coefficient of variation for continuous and binary variables. Methods We investigate the validity of the approximate normal confidence interval by Monte Carlo simulations. In designing a reliability study, a crucial issue is the balance between the number of subjects to be recruited and the number of repeated measurements per subject. We discuss efficiency of estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated by an example on Magnetic Resonance Imaging (MRI). We also discuss the issue of sample size estimation for dichotomous responses with two examples. Results For the continuous variable we found that the variance stabilizing transformation improves the asymptotic coverage probabilities on the within-subject coefficient of variation for the continuous variable. The maximum like estimation and sample size estimation based on pre-specified width of confidence interval are novel contribution to the literature for the binary variable. Conclusion Using the sample size formulas, we hope to help clinical epidemiologists and practicing statisticians to efficiently design reliability studies using the within-subject coefficient of variation, whether the variable of interest is continuous or binary. PMID:16686943

Effects of process variables on the properties of YBa2Cu3O(7-x) ceramics formed by investment casting

NASA Technical Reports Server (NTRS)

Hooker, M. W.; Taylor, T. D.; Leigh, H. D.; Wise, S. A.; Buckley, J. D.; Vasquez, P.; Buck, G. M.; Hicks, L. P.

1993-01-01

An investment casting process has been developed to produce net-shape, superconducting ceramics. In this work, a factorial experiment was performed to determine the critical process parameters for producing cast YBa2Cu3O7 ceramics with optimum properties. An analysis of variance procedure indicated that the key variables in casting superconductive ceramics are the particle size distribution and sintering temperature. Additionally, the interactions between the sintering temperature and the other process parameters (e.g., particle size distribution and the use of silver dopants) were also found to influence the density, porosity, and critical current density of the fired ceramics.

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

NASA Technical Reports Server (NTRS)

Menard, Richard; Chang, Lang-Ping

1998-01-01

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

Sensitivity metric approach for retrieval of aerosol properties from multiangular and multispectral polarized radiances

NASA Astrophysics Data System (ADS)

Miecznik, Grzegorz; Illing, Rainer; Petroy, Shelley; Sokolik, Irina N.

2005-07-01

Linearly polarized radiation is sensitive to the microphysical properties of aerosols, namely, to the particle- size distribution and refractive index. The discriminating power of polarized radiation increases strongly with the increasing range of scattering angles and the addition of multiple wavelengths. The polarization and directionality of the Earth's reflectances (POLDER) missions demonstrate that some aerosol properties can be successfully derived from spaceborne polarimetric, multiangular measurements at two visible wavelengths. We extend the concept to analyze the retrieval capabilities of a spaceborne instrument with six polarimetric channels at 412, 445, 555, 865, 1250, and 2250 nm, measuring approximately 100 scattering angles covering a range between 50 and 150 deg. Our focus is development of an analysis methodology that can help quantify the benefits of such multiangular and multispectral polarimetric measurements. To that goal we employ a sensitivity metric approach in a framework of the principal-component analysis. The radiances and noise used to construct the sensitivity metric are calculated with the realistic solar flux for representative orbital viewing geometries, accounting for surface reflection from the ground, and statistical and calibration errors of a notional instrument. Spherical aerosol particles covering a range of representative microphysical properties (effective radius, effective variance, real and imaginary parts of the refractive index, single-scattering albedo) are considered in the calculations. We find that there is a limiting threshold for the effective size (approximately 0.7 μm), below which the weak scattering intensity results in a decreased signal-to-noise ratio and minimal polarization sensitivity, precluding reliable aerosol retrievals. For such small particles, close to the Rayleigh scattering limit, the total intensity provides a much stronger aerosol signature than the linear polarization, inspiring retrieval when the combined signals of intensities and the polarization fraction are used. We also find a strong correlation between aerosol parameters, in particular between the effective size and the variance, which forces one to simultaneously retrieve at least these two parameters.

Tropical forest fragmentation affects floral visitors but not the structure of individual-based palm-pollinator networks.

PubMed

Dáttilo, Wesley; Aguirre, Armando; Quesada, Mauricio; Dirzo, Rodolfo

2015-01-01

Despite increasing knowledge about the effects of habitat loss on pollinators in natural landscapes, information is very limited regarding the underlying mechanisms of forest fragmentation affecting plant-pollinator interactions in such landscapes. Here, we used a network approach to describe the effects of forest fragmentation on the patterns of interactions involving the understory dominant palm Astrocaryum mexicanum (Arecaceae) and its floral visitors (including both effective and non-effective pollinators) at the individual level in a Mexican tropical rainforest landscape. Specifically, we asked: (i) Does fragment size affect the structure of individual-based plant-pollinator networks? (ii) Does the core of highly interacting visitor species change along the fragmentation size gradient? (iii) Does forest fragment size influence the abundance of effective pollinators of A. mexicanum? We found that fragment size did not affect the topological structure of the individual-based palm-pollinator network. Furthermore, while the composition of peripheral non-effective pollinators changed depending on fragment size, effective core generalist species of pollinators remained stable. We also observed that both abundance and variance of effective pollinators of male and female flowers of A. mexicanum increased with forest fragment size. These findings indicate that the presence of effective pollinators in the core of all forest fragments could keep the network structure stable along the gradient of forest fragmentation. In addition, pollination of A. mexicanum could be more effective in larger fragments, since the greater abundance of pollinators in these fragments may increase the amount of pollen and diversity of pollen donors between flowers of individual plants. Given the prevalence of fragmentation in tropical ecosystems, our results indicate that the current patterns of land use will have consequences on the underlying mechanisms of pollination in remnant forests.

Food cue reactivity and craving predict eating and weight gain: a meta-analytic review.

PubMed

Boswell, Rebecca G; Kober, Hedy

2016-02-01

According to learning-based models of behavior, food cue reactivity and craving are conditioned responses that lead to increased eating and subsequent weight gain. However, evidence supporting this relationship has been mixed. We conducted a quantitative meta-analysis to assess the predictive effects of food cue reactivity and craving on eating and weight-related outcomes. Across 69 reported statistics from 45 published reports representing 3,292 participants, we found an overall medium effect of food cue reactivity and craving on outcomes (r = 0.33, p < 0.001; approximately 11% of variance), suggesting that cue exposure and the experience of craving significantly influence and contribute to eating behavior and weight gain. Follow-up tests revealed a medium effect size for the effect of both tonic and cue-induced craving on eating behavior (r = 0.33). We did not find significant differences in effect sizes based on body mass index, age, or dietary restraint. However, we did find that visual food cues (e.g. pictures and videos) were associated with a similar effect size to real food exposure and a stronger effect size than olfactory cues. Overall, the present findings suggest that food cue reactivity, cue-induced craving and tonic craving systematically and prospectively predict food-related outcomes. These results have theoretical, methodological, public health and clinical implications. © 2015 World Obesity.

Improved Event Location Uncertainty Estimates

DTIC Science & Technology

2008-06-30

throughout this study . The data set consists of GT0-2 nuclear explosions from the SAIC Nuclear Explosion Database (www.rdss.info, Bahavar et al...errors: Bias and variance In this study SNR dependence of both delay and variance of reading errors of first arriving P waves are analyzed and...ground truth and range of event size. For other datasets we turn to estimates based on double- differences between arrival times of station pairs

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

Input-variable sensitivity assessment for sediment transport relations

NASA Astrophysics Data System (ADS)

Fernández, Roberto; Garcia, Marcelo H.

2017-09-01

A methodology to assess input-variable sensitivity for sediment transport relations is presented. The Mean Value First Order Second Moment Method (MVFOSM) is applied to two bed load transport equations showing that it may be used to rank all input variables in terms of how their specific variance affects the overall variance of the sediment transport estimation. In sites where data are scarce or nonexistent, the results obtained may be used to (i) determine what variables would have the largest impact when estimating sediment loads in the absence of field observations and (ii) design field campaigns to specifically measure those variables for which a given transport equation is most sensitive; in sites where data are readily available, the results would allow quantifying the effect that the variance associated with each input variable has on the variance of the sediment transport estimates. An application of the method to two transport relations using data from a tropical mountain river in Costa Rica is implemented to exemplify the potential of the method in places where input data are limited. Results are compared against Monte Carlo simulations to assess the reliability of the method and validate its results. For both of the sediment transport relations used in the sensitivity analysis, accurate knowledge of sediment size was found to have more impact on sediment transport predictions than precise knowledge of other input variables such as channel slope and flow discharge.

Meta-analysis with missing study-level sample variance data.

PubMed

Chowdhry, Amit K; Dworkin, Robert H; McDermott, Michael P

2016-07-30

We consider a study-level meta-analysis with a normally distributed outcome variable and possibly unequal study-level variances, where the object of inference is the difference in means between a treatment and control group. A common complication in such an analysis is missing sample variances for some studies. A frequently used approach is to impute the weighted (by sample size) mean of the observed variances (mean imputation). Another approach is to include only those studies with variances reported (complete case analysis). Both mean imputation and complete case analysis are only valid under the missing-completely-at-random assumption, and even then the inverse variance weights produced are not necessarily optimal. We propose a multiple imputation method employing gamma meta-regression to impute the missing sample variances. Our method takes advantage of study-level covariates that may be used to provide information about the missing data. Through simulation studies, we show that multiple imputation, when the imputation model is correctly specified, is superior to competing methods in terms of confidence interval coverage probability and type I error probability when testing a specified group difference. Finally, we describe a similar approach to handling missing variances in cross-over studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Family members' unique perspectives of the family: examining their scope, size, and relations to individual adjustment.

PubMed

Jager, Justin; Bornstein, Marc H; Putnick, Diane L; Hendricks, Charlene

2012-06-01

Using the McMaster Family Assessment Device (Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's "unique perspective" or nonshared, idiosyncratic view of the family. We used a modified multitrait-multimethod confirmatory factor analysis that (a) isolated for each family member's 6 reports of family dysfunction the nonshared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by 1 or more family members and (b) extracted common variance across each family member's set of nonshared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. In addition, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these "unique perspectives" reflect about the family are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Family Members' Unique Perspectives of the Family: Examining their Scope, Size, and Relations to Individual Adjustment

PubMed Central

Jager, Justin; Bornstein, Marc H.; Diane, L. Putnick; Hendricks, Charlene

2012-01-01

Using the Family Assessment Device (FAD; Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's “unique perspective” or non-shared, idiosyncratic view of the family. To do so we used a modified multitrait-multimethod confirmatory factor analysis that (1) isolated for each family member's six reports of family dysfunction the non-shared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by one or more family members and (2) extracted common variance across each family member's set of non-shared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. Additionally, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these “unique perspectives” reflect about the family are discussed. PMID:22545933

Finite-size scaling of survival probability in branching processes

NASA Astrophysics Data System (ADS)

Garcia-Millan, Rosalba; Font-Clos, Francesc; Corral, Álvaro

2015-04-01

Branching processes pervade many models in statistical physics. We investigate the survival probability of a Galton-Watson branching process after a finite number of generations. We derive analytically the existence of finite-size scaling for the survival probability as a function of the control parameter and the maximum number of generations, obtaining the critical exponents as well as the exact scaling function, which is G (y ) =2 y ey /(ey-1 ) , with y the rescaled distance to the critical point. Our findings are valid for any branching process of the Galton-Watson type, independently of the distribution of the number of offspring, provided its variance is finite. This proves the universal behavior of the finite-size effects in branching processes, including the universality of the metric factors. The direct relation to mean-field percolation is also discussed.

Wake-Driven Dynamics of Finite-Sized Buoyant Spheres in Turbulence

NASA Astrophysics Data System (ADS)

Mathai, Varghese; Prakash, Vivek N.; Brons, Jon; Sun, Chao; Lohse, Detlef

2015-09-01

Particles suspended in turbulent flows are affected by the turbulence and at the same time act back on the flow. The resulting coupling can give rise to rich variability in their dynamics. Here we report experimental results from an investigation of finite-sized buoyant spheres in turbulence. We find that even a marginal reduction in the particle's density from that of the fluid can result in strong modification of its dynamics. In contrast to classical spatial filtering arguments and predictions of particle models, we find that the particle acceleration variance increases with size. We trace this reversed trend back to the growing contribution from wake-induced forces, unaccounted for in current particle models in turbulence. Our findings highlight the need for improved multiphysics based models that account for particle wake effects for a faithful representation of buoyant-sphere dynamics in turbulence.

Preparation of Pickering emulsions stabilized by metal organic frameworks using oscillatory woven metal micro-screen.

PubMed

Sabouni, R; Gomaa, H G

2015-06-14

Uniform Pickering emulsions stabilized by metal organic frameworks (MOFs) MIL-101 and ZIF-8 nanoparticles (NPs) were successfully prepared using an oscillatory woven metal microscreen (WMMS) emulsification system in the presence and the absence of surfactants. The effects of operating and system parameters including the frequency and amplitude of oscillation, the type of nano-particle and/or surfactant on the droplet size and coefficient of variance of the prepared emulsions are investigated. The results showed that both the hydrodynamics of the system and the hydrophobic/hydrophilic nature of the NP influenced the interfacial properties of the oil-water interface during droplet formation and after detachment, which in turn affected the final droplet size and distribution. Comparison between the measured and predicted droplet size using a simple torque balance (TB) model is discussed.

The infinitesimal model: Definition, derivation, and implications.

PubMed

Barton, N H; Etheridge, A M; Véber, A

2017-12-01

Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Finite-size effects on bacterial population expansion under controlled flow conditions

NASA Astrophysics Data System (ADS)

Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc; Toschi, Federico

2017-03-01

The expansion of biological species in natural environments is usually described as the combined effect of individual spatial dispersal and growth. In the case of aquatic ecosystems flow transport can also be extremely relevant as an extra, advection induced, dispersal factor. We designed and assembled a dedicated microfluidic device to control and quantify the expansion of populations of E. coli bacteria under both co-flowing and counter-flowing conditions, measuring the front speed at varying intensity of the imposed flow. At variance with respect to the case of classic advective-reactive-diffusive chemical fronts, we measure that almost irrespective of the counter-flow velocity, the front speed remains finite at a constant positive value. A simple model incorporating growth, dispersion and drift on finite-size hard beads allows to explain this finding as due to a finite volume effect of the bacteria. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) that ignore the finite size of organisms may be inaccurate to describe the physics of spatial growth dynamics of bacteria.

Phylogenetic signal, feeding behaviour and brain volume in Neotropical bats.

PubMed

Rojas, D; Mancina, C A; Flores-Martínez, J J; Navarro, L

2013-09-01

Comparative correlational studies of brain size and ecological traits (e.g. feeding habits and habitat complexity) have increased our knowledge about the selective pressures on brain evolution. Studies conducted in bats as a model system assume that shared evolutionary history has a maximum effect on the traits. However, this effect has not been quantified. In addition, the effect of levels of diet specialization on brain size remains unclear. We examined the role of diet on the evolution of brain size in Mormoopidae and Phyllostomidae using two comparative methods. Body mass explained 89% of the variance in brain volume. The effect of feeding behaviour (either characterized as feeding habits, as levels of specialization on a type of item or as handling behaviour) on brain volume was also significant albeit not consistent after controlling for body mass and the strength of the phylogenetic signal (λ). Although the strength of the phylogenetic signal of brain volume and body mass was high when tested individually, λ values in phylogenetic generalized least squares models were significantly different from 1. This suggests that phylogenetic independent contrasts models are not always the best approach for the study of ecological correlates of brain size in New World bats. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Leadership and Organizational Learning: Accounting for Variances in Small-Size Business Enterprises

ERIC Educational Resources Information Center

Graham, Carroll M.; Nafukho, Fredrick M.

2007-01-01

This study's primary purpose was to determine the relationship between leadership and the dependent variable organizational learning readiness at three locations of a small-size business enterprise in the Mid-Western United States. Surveys were acquired within an exploratory correlational research design and the results indicated leadership…

Differences in Middle School Science Achievement by School District Size

ERIC Educational Resources Information Center

Mann, Matthew James; Maxwell, Gerri M.; Holland, Glenda

2013-01-01

This study examined differences in Texas middle school student achievement in science by school district enrollment size. Quantitative research utilized analysis of variance to determine whether significant differences existed between student achievement on the 2010 Texas Assessment of Knowledge and Skills 8th grade science results and four school…

Investigating Reliabilities of Intraindividual Variability Indicators

ERIC Educational Resources Information Center

Wang, Lijuan; Grimm, Kevin J.

2012-01-01

Reliabilities of the two most widely used intraindividual variability indicators, "ISD[superscript 2]" and "ISD", are derived analytically. Both are functions of the sizes of the first and second moments of true intraindividual variability, the size of the measurement error variance, and the number of assessments within a burst. For comparison,…

GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment

PubMed Central

Rietveld, Cornelius A.; Medland, Sarah E.; Derringer, Jaime; Yang, Jian; Esko, Tõnu; Martin, Nicolas W.; Westra, Harm-Jan; Shakhbazov, Konstantin; Abdellaoui, Abdel; Agrawal, Arpana; Albrecht, Eva; Alizadeh, Behrooz Z.; Amin, Najaf; Barnard, John; Baumeister, Sebastian E.; Benke, Kelly S.; Bielak, Lawrence F.; Boatman, Jeffrey A.; Boyle, Patricia A.; Davies, Gail; de Leeuw, Christiaan; Eklund, Niina; Evans, Daniel S.; Ferhmann, Rudolf; Fischer, Krista; Gieger, Christian; Gjessing, Håkon K.; Hägg, Sara; Harris, Jennifer R.; Hayward, Caroline; Holzapfel, Christina; Ibrahim-Verbaas, Carla A.; Ingelsson, Erik; Jacobsson, Bo; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika; Kanoni, Stavroula; Karjalainen, Juha; Kolcic, Ivana; Kristiansson, Kati; Kutalik, Zoltán; Lahti, Jari; Lee, Sang H.; Lin, Peng; Lind, Penelope A.; Liu, Yongmei; Lohman, Kurt; Loitfelder, Marisa; McMahon, George; Vidal, Pedro Marques; Meirelles, Osorio; Milani, Lili; Myhre, Ronny; Nuotio, Marja-Liisa; Oldmeadow, Christopher J.; Petrovic, Katja E.; Peyrot, Wouter J.; Polašek, Ozren; Quaye, Lydia; Reinmaa, Eva; Rice, John P.; Rizzi, Thais S.; Schmidt, Helena; Schmidt, Reinhold; Smith, Albert V.; Smith, Jennifer A.; Tanaka, Toshiko; Terracciano, Antonio; van der Loos, Matthijs J.H.M.; Vitart, Veronique; Völzke, Henry; Wellmann, Jürgen; Yu, Lei; Zhao, Wei; Allik, Jüri; Attia, John R.; Bandinelli, Stefania; Bastardot, François; Beauchamp, Jonathan; Bennett, David A.; Berger, Klaus; Bierut, Laura J.; Boomsma, Dorret I.; Bültmann, Ute; Campbell, Harry; Chabris, Christopher F.; Cherkas, Lynn; Chung, Mina K.; Cucca, Francesco; de Andrade, Mariza; De Jager, Philip L.; De Neve, Jan-Emmanuel; Deary, Ian J.; Dedoussis, George V.; Deloukas, Panos; Dimitriou, Maria; Eiriksdottir, Gudny; Elderson, Martin F.; Eriksson, Johan G.; Evans, David M.; Faul, Jessica D.; Ferrucci, Luigi; Garcia, Melissa E.; Grönberg, Henrik; Gudnason, Vilmundur; Hall, Per; Harris, Juliette M.; Harris, Tamara B.; Hastie, Nicholas D.; Heath, Andrew C.; Hernandez, Dena G.; Hoffmann, Wolfgang; Hofman, Adriaan; Holle, Rolf; Holliday, Elizabeth G.; Hottenga, Jouke-Jan; Iacono, William G.; Illig, Thomas; Järvelin, Marjo-Riitta; Kähönen, Mika; Kaprio, Jaakko; Kirkpatrick, Robert M.; Kowgier, Matthew; Latvala, Antti; Launer, Lenore J.; Lawlor, Debbie A.; Lehtimäki, Terho; Li, Jingmei; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.; Madden, Pamela A.; Magnusson, Patrik K. E.; Mäkinen, Tomi E.; Masala, Marco; McGue, Matt; Metspalu, Andres; Mielck, Andreas; Miller, Michael B.; Montgomery, Grant W.; Mukherjee, Sutapa; Nyholt, Dale R.; Oostra, Ben A.; Palmer, Lyle J.; Palotie, Aarno; Penninx, Brenda; Perola, Markus; Peyser, Patricia A.; Preisig, Martin; Räikkönen, Katri; Raitakari, Olli T.; Realo, Anu; Ring, Susan M.; Ripatti, Samuli; Rivadeneira, Fernando; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sarin, Antti-Pekka; Schlessinger, David; Scott, Rodney J.; Snieder, Harold; Pourcain, Beate St; Starr, John M.; Sul, Jae Hoon; Surakka, Ida; Svento, Rauli; Teumer, Alexander; Tiemeier, Henning; Rooij, Frank JAan; Van Wagoner, David R.; Vartiainen, Erkki; Viikari, Jorma; Vollenweider, Peter; Vonk, Judith M.; Waeber, Gérard; Weir, David R.; Wichmann, H.-Erich; Widen, Elisabeth; Willemsen, Gonneke; Wilson, James F.; Wright, Alan F.; Conley, Dalton; Davey-Smith, George; Franke, Lude; Groenen, Patrick J. F.; Hofman, Albert; Johannesson, Magnus; Kardia, Sharon L.R.; Krueger, Robert F.; Laibson, David; Martin, Nicholas G.; Meyer, Michelle N.; Posthuma, Danielle; Thurik, A. Roy; Timpson, Nicholas J.; Uitterlinden, André G.; van Duijn, Cornelia M.; Visscher, Peter M.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.

2013-01-01

A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics. PMID:23722424

The impact of the Sarbanes Oxley Act on auditing fees: An empirical study of the oil and gas industry

NASA Astrophysics Data System (ADS)

Ezelle, Ralph Wayne, Jr.

2011-12-01

This study examines auditing of energy firms prior and post Sarbanes Oxley Act of 2002. The research explores factors impacting the asset adjusted audit fee of oil and gas companies and specifically examines the effect of the Sarbanes Oxley Act. This research analyzes multiple year audit fees of the firms engaged in the oil and gas industry. Pooled samples were created to improve statistical power with sample sizes sufficient to test for medium and large effect size. The Sarbanes Oxley Act significantly increases a firm's asset adjusted audit fees. Additional findings are that part of the variance in audit fees was attributable to the market value of the enterprise, the number of subsidiaries, the receivables and inventory, debt ratio, non-profitability, and receipt of a going concern report.

The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis.

PubMed

Af Wåhlberg, A E; Barraclough, P; Freeman, J

2015-12-01

The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include unpublished results. The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, using the mean of accidents as proxy for effect indicated that studies where effects for violations are not reported have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which tendencies are controlled for. Methodological factors and dissemination bias have inflated the published effect sizes of the DBQ. Strong evidence of various artefactual effects is apparent. A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

It Depends on the Partner: Person-Related Sources of Efficacy Beliefs and Performance for Athlete Pairs.

PubMed

Habeeb, Christine M; Eklund, Robert C; Coffee, Pete

2017-06-01

This study explored person-related sources of variance in athletes' efficacy beliefs and performances when performing in pairs with distinguishable roles differing in partner dependence. College cheerleaders (n = 102) performed their role in repeated performance trials of two low- and two high-difficulty paired-stunt tasks with three different partners. Data were obtained on self-, other-, and collective efficacy beliefs and subjective performances, and objective performance assessments were obtained from digital recordings. Using the social relations model framework, total variance in each belief/assessment was partitioned, for each role, into numerical components of person-related variance relative to the self, the other, and the collective. Variance component by performance role by task-difficulty repeated-measures analysis of variances revealed that the largest person-related variance component differed by athlete role and increased in size in high-difficulty tasks. Results suggest that the extent the athlete's performance depends on a partner relates to the extent the partner is a source of self-, other-, and collective efficacy beliefs.

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

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

ERIC Educational Resources Information Center

Shieh, Gwowen

2013-01-01

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

Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

PubMed

Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

2017-01-01

Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

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.

On sample size and different interpretations of snow stability datasets

NASA Astrophysics Data System (ADS)

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

2009-04-01

Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar aspect distributions to the large dataset. We used 100 different subsets for each sample size. Statistical variations obtained in the complete dataset were also tested on the smaller subsets using the Mann-Whitney or the Kruskal-Wallis test. For each subset size, the number of subsets were counted in which the significance level was reached. For these tests no nominal data scale was assumed. (iii) For the same subsets described above, the distribution of the aspect median was determined. A count of how often this distribution was substantially different from the distribution obtained with the complete dataset was made. Since two valid stability interpretations were available (an objective and a subjective interpretation as described above), the effect of the arbitrary choice of the interpretation on spatial variability results was tested. In over one third of the cases the two interpretations came to different results. The effect of these differences were studied in a similar method as described in (iii): the distribution of the aspect median was determined for subsets of the complete dataset using both interpretations, compared against each other as well as to the results of the complete dataset. For the complete dataset the two interpretations showed mainly identical results. Therefore the subset size was determined from the point at which the results of the two interpretations converged. A universal result for the optimal subset size cannot be presented since results differed between different situations contained in the dataset. The optimal subset size is thus dependent on stability variation in a given situation, which is unknown initially. There are indications that for some situations even the complete dataset might be not large enough. At a subset size of approximately 25, the significant differences between aspect groups (as determined using the whole dataset) were only obtained in one out of five situations. In some situations, up to 20% of the subsets showed a substantially different distribution of the aspect median. Thus, in most cases, 25 measurements (which can be achieved by six two-person teams in one day) did not allow to draw reliable conclusions.

Family Caregivers of Liver Transplant Recipients: Coping Strategies Associated With Different Levels of Post-traumatic Growth.

PubMed

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

2018-03-01

Analyze the influence of 2 variables (post-traumatic growth and time since liver transplantation) on coping strategies used by the transplant recipient's family members. In all, 218 family members who were their main caregivers of liver transplant recipients were selected. They were evaluated using the Posttraumatic Growth Inventory and the Brief COPE. A 3 × 3 factorial analysis of variance was used to analyze the influence that post-traumatic growth level (low, medium, and high) and time since transplantation (≤3.5 years, >3.5 to ≤9 years, and >9 years) exerted on caregiver coping strategies. No interactive effects between the two factors in the study were found. The only significant main effect was the influence of the post-traumatic growth factor on the following variables: instrumental support (P = .007), emotional support (P = .005), self-distraction (P = .006), positive reframing (P = .000), acceptance (P = .013), and religion (P = <.001). According to the most relevant effect sizes, low post-traumatic growth compared with medium growth was associated with less use of self-distraction (P = .006, d = -0.52, medium effect size), positive reframing (P = .001, d = -0.62, medium effect size), and religion (P = .000, d = -0.66, medium effect size), and in comparison with high growth, it was associated with less use of positive reframing (P = .002, d = -0.56, medium effect size) and religion (P = .000, d = 0.87, large effect size). Regardless of the time elapsed since the stressful life event (liver transplantation), family members with low post-traumatic growth usually use fewer coping strategies involving a positive, transcendent vision to deal with transplantation. Copyright © 2017 Elsevier Inc. All rights reserved.

Social competence: evaluation of assertiveness in Spanish adolescents.

PubMed

Castedo, Antonio López; Juste, Margarita Pino; Alonso, José Domínguez

2015-02-01

Relations between assertiveness in adolescents' social behavior and demographic variables were assessed in 4,943 Spanish adolescents, ages 12 to 17 years, enrolled in 32 schools for Compulsory Secondary Education. Province of residence, school size, age, grade, and academic focus were statistically significant sources of variance in assertiveness scores. All effects were small. Patterns in responses indicate the items should be reviewed to improve the measure for adolescents, and as a tool for addressing teens' social competence in real life situations.

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

NASA Astrophysics Data System (ADS)

Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

2009-11-01

Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

Fokker-Planck equation for particle growth by monomer attachment.

PubMed

Matsoukas, Themis; Lin, Yulan

2006-09-01

The population balance equation (PBE) for growth by attachment of a monomeric unit is described in the discrete domain by an infinite set of differential equations. Transforming the discrete problem into the continuous domain produces a series expansion which is usually truncated past the first term. We study the effect of this truncation and we show that by including the second-order term one obtains a Fokker-Planck approximation of the continuous PBE whose first and second moments are exact. We use this truncation to study the asymptotic behavior of the variance of the size distribution with growth rate that is a power-law function of the particle mass with exponent a . We obtain analytic expressions for the variance and show that its asymptotic behavior is different in the regimes a<1/2 and a>1/2. These conclusions are corroborated by Monte Carlo simulations.

Fixation of slightly beneficial mutations: effects of life history.

PubMed

Vindenes, Yngvild; Lee, Aline Magdalena; Engen, Steinar; Saether, Bernt-Erik

2010-04-01

Recent studies of rates of evolution have revealed large systematic differences among organisms with different life histories, both within and among taxa. Here, we consider how life history may affect the rate of evolution via its influence on the fixation probability of slightly beneficial mutations. Our approach is based on diffusion modeling for a finite, stage-structured population with stochastic population dynamics. The results, which are verified by computer simulations, demonstrate that even with complex population structure just two demographic parameters are sufficient to give an accurate approximation of the fixation probability of a slightly beneficial mutation. These are the reproductive value of the stage in which the mutation first occurs and the demographic variance of the population. The demographic variance also determines what influence population size has on the fixation probability. This model represents a substantial generalization of earlier models, covering a large range of life histories.

Evolution of sociality by natural selection on variances in reproductive fitness: evidence from a social bee.

PubMed

Stevens, Mark I; Hogendoorn, Katja; Schwarz, Michael P

2007-08-29

The Central Limit Theorem (CLT) is a statistical principle that states that as the number of repeated samples from any population increase, the variance among sample means will decrease and means will become more normally distributed. It has been conjectured that the CLT has the potential to provide benefits for group living in some animals via greater predictability in food acquisition, if the number of foraging bouts increases with group size. The potential existence of benefits for group living derived from a purely statistical principle is highly intriguing and it has implications for the origins of sociality. Here we show that in a social allodapine bee the relationship between cumulative food acquisition (measured as total brood weight) and colony size accords with the CLT. We show that deviations from expected food income decrease with group size, and that brood weights become more normally distributed both over time and with increasing colony size, as predicted by the CLT. Larger colonies are better able to match egg production to expected food intake, and better able to avoid costs associated with producing more brood than can be reared while reducing the risk of under-exploiting the food resources that may be available. These benefits to group living derive from a purely statistical principle, rather than from ecological, ergonomic or genetic factors, and could apply to a wide variety of species. This in turn suggests that the CLT may provide benefits at the early evolutionary stages of sociality and that evolution of group size could result from selection on variances in reproductive fitness. In addition, they may help explain why sociality has evolved in some groups and not others.

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction norm model

PubMed Central

Calus, Mario PL; Bijma, Piter; Veerkamp, Roel F

2004-01-01

Covariance functions have been proposed to predict breeding values and genetic (co)variances as a function of phenotypic within herd-year averages (environmental parameters) to include genotype by environment interaction. The objective of this paper was to investigate the influence of definition of environmental parameters and non-random use of sires on expected breeding values and estimated genetic variances across environments. Breeding values were simulated as a linear function of simulated herd effects. The definition of environmental parameters hardly influenced the results. In situations with random use of sires, estimated genetic correlations between the trait expressed in different environments were 0.93, 0.93 and 0.97 while simulated at 0.89 and estimated genetic variances deviated up to 30% from the simulated values. Non random use of sires, poor genetic connectedness and small herd size had a large impact on the estimated covariance functions, expected breeding values and calculated environmental parameters. Estimated genetic correlations between a trait expressed in different environments were biased upwards and breeding values were more biased when genetic connectedness became poorer and herd composition more diverse. The best possible solution at this stage is to use environmental parameters combining large numbers of animals per herd, while losing some information on genotype by environment interaction in the data. PMID:15339629

LPA gene: interaction between the apolipoprotein(a) size ('kringle IV' repeat) polymorphism and a pentanucleotide repeat polymorphism influences Lp(a) lipoprotein level.

PubMed

Røsby, O; Berg, K

2000-01-01

In order to search for factors influencing the Lp(a) lipoprotein level, we have examined the apolipoprotein(a) (apo(a)) size polymorphism as well as a pentanucleotide (TTTTA) repeat polymorphism in the 5' control region of the LPA gene. Lp(a) lipoprotein levels were compared between individuals with different genotypes as defined by pulsed field gel electrophoresis of DNA plugs, and PCR of DNA samples followed by polyacrylamide gel electrophoresis. DNA plugs and DNA were prepared from blood samples collected from blood donors. Twenty-seven different K IV repeat alleles were observed in the 71 women and 92 men from which apo(a) size polymorphism results were obtained. Alleles encoding 26-32 Kringle IV repeats were the most frequent. Alleles encoding seven to 11 TTTTA repeats were detected in the 84 women and 122 men included in the pentanucleotide polymorphism study, and homozygosity for eight TTTTA repeats was the most common genotype. The eight TTTTA repeat allele occurred with almost any apo(a) allele. An inverse relationship between number of K IV repeats and Lp(a) concentration was confirmed. The contributions of the apo(a) size polymorphism and the pentanucleotide repeat polymorphism to the interindividual variance of Lp(a) lipoprotein concentrations were 9.7 and 3.5%, respectively (type IV sum of squares). Nineteen per cent of the variance in Lp(a) lipoprotein level appeared to be the result of the multiplication product (interaction) between the apo(a) size polymorphism and the pentanucleotide repeat polymorphism. The contribution of the apo(a) size polymorphism alone to the variation in Lp(a) lipoprotein level was lower than previously reported. However, the multiplicative interaction effect between the K IV repeat polymorphism and the pentanucleotide repeat polymorphism may be an important factor explaining the variation in Lp(a) lipoprotein levels among the populations.

Genomic Microsatellites as Evolutionary Chronometers: A Test in Wild Cats

PubMed Central

Driscoll, Carlos A.; Menotti-Raymond, Marilyn; Nelson, George; Goldstein, David; O'Brien, Stephen J.

2002-01-01

Nuclear microsatellite loci (2- to 5-bp tandem repeats) would seem to be ideal markers for population genetic monitoring because of their abundant polymorphism, wide dispersal in vertebrate genomes, near selective neutrality, and ease of assessment; however, questions about their mode of generation, mutation rates and ascertainment bias have limited interpretation considerably. We have assessed the patterns of genomic diversity for ninety feline microsatellite loci among previously characterized populations of cheetahs, lions and pumas in recapitulating demographic history. The results imply that the microsatellite diversity measures (heterozygosity, allele reconstitution and microsatellite allele variance) offer proportionate indicators, albeit with large variance, of historic population bottlenecks and founder effects. The observed rate of reconstruction of new alleles plus the growth in the breadth of microsatellite allele size (variance) was used here to develop genomic estimates of time intervals following historic founder events in cheetahs (12,000 yr ago), in North American pumas (10,000–17,000 yr ago), and in Asiatic lions of the Gir Forest (1000–4000 yr ago). [Supplemental material available online at http://rex.nci.nih.gov/lgd/front_page.htm and at http://www.genome.org.] PMID:11875029

Genetical Analysis of Chromosomal Interaction Effects on the Activities of the Glucose 6-Phosphate and 6-Phosphogluconate Dehydrogenases in DROSOPHILA MELANOGASTER

PubMed Central

Miyashita, Naohiko; Laurie-Ahlberg, C. C.

1984-01-01

By combining ten second and ten third chromosomes, we investigated chromosomal interaction with respect to the action of the modifier factors on G6PD and 6PGD activities in Drosophila melanogaster. Analysis of variance revealed that highly significant chromosomal interaction exists for both enzyme activities. From the estimated variance components, it was concluded that the variation in enzyme activity attributed to the interaction is as great as the variation attributed to the second chromosome but less than attributed to the third chromosome. The interaction is not explained by the variation of body size (live weight). The interaction is generated from both the lack of correlation of second chromosomes for third chromosome backgrounds and the heterogeneous variance of second chromosomes for different third chromosome backgrounds. Large and constant correlation between G6PD and 6PGD activities were found for third chromosomes with any second chromosome background, whereas the correlations for second chromosomes were much smaller and varied considerably with the third chromosome background. This result suggests that the activity modifiers on the second chromosome are under the influence of third chromosome factors. PMID:6425115

Factors controlling degree of correlation between ISEE 1 and ISEE 3 interplanetary magnetic field measurements

NASA Technical Reports Server (NTRS)

Crooker, N. U.; Siscoe, G. L.; Russell, C. T.; Smith, E. J.

1982-01-01

Correlation variability between ISEE 1 and 3 IMF measurements is investigated, and factors governing the variability are discussed. About 200 two-hour periods when correlation was good, and 200 when correlation was poor, are examined, and both IMF variance and spacecraft separation distance in the plane perpendicular to the earth-sun line exert substantial control. The scale size of magnetic features is larger when variance is high, and abrupt changes in the correlation coefficient from poor to good or good to poor in adjacent two-hour intervals appear to be governed by the sense of change of IMF variance and vice versa. During periods of low variance, good correlations are most likely to occur when the distance between ISEE 1 and 3 perpendicular to the IMF is less than 20 earth radii.

Use of morphological characteristics to define functional groups of predatory fishes in the Celtic Sea.

PubMed

Reecht, Y; Rochet, M-J; Trenkel, V M; Jennings, S; Pinnegar, J K

2013-08-01

An ecomorphological method was developed, with a focus on predation functions, to define functional groups in the Celtic Sea fish community. Eleven functional traits, measured for 930 individuals from 33 species, led to 11 functional groups. Membership of functional groups was linked to body size and taxonomy. For seven species, there were ontogenetic changes in group membership. When diet composition, expressed as the proportions of different prey types recorded in stomachs, was compared among functional groups, morphology-based predictions accounted for 28-56% of the interindividual variance in prey type. This was larger than the 12-24% of variance that could be explained solely on the basis of body size. © 2013 The Fisheries Society of the British Isles.

Accounting for heterogeneity in meta-analysis using a multiplicative model-an empirical study.

PubMed

Mawdsley, David; Higgins, Julian P T; Sutton, Alex J; Abrams, Keith R

2017-03-01

In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In this paper, we compare the two models using a random sample of 448 meta-analyses drawn from the Cochrane Database of Systematic Reviews. In general, differences in goodness of fit are modest. The multiplicative model tends to give results that are closer to the null, with a narrower confidence interval. Both approaches make different assumptions about the outcome of the meta-analysis. In our opinion, the selection of the more appropriate model will often be guided by whether the multiplicative model's assumption of a single effect size is plausible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Signatures of negative selection in the genetic architecture of human complex traits.

PubMed

Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian

2018-05-01

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

PATERNAL GENOTYPE INFLUENCES INCUBATION PERIOD, OFFSPRING SIZE, AND OFFSPRING SHAPE IN AN OVIPAROUS REPTILE.

PubMed

Olsson, Mats; Gullberg, Annica; Shine, Richard; Madsen, Thomas; Tegelström, Håkan

1996-06-01

Theoretical models for the evolution of life-history traits assume a genetic basis for a significant proportion of the phenotypic variance observed in characteristics such as hatching date and offspring size. However, recent experimental work has shown that much of the phenotypic variance in hatchling reptiles is induced by nongenetic factors, such as maternal nutrition and thermoregulation, and the physical conditions experienced during embryogenesis. Thus, there is no unambiguous evidence for strictly genetic (intraspecific) influences on the phenotypes of hatchling reptiles. We report results from a technique that uses a genetic marker trait and DNA fingerprinting to determine paternity of offspring from multiply sired clutches of European sand lizards, Lacerta agilis. By focusing on paternal rather than maternal effects, we show that hatchling genotypes exert a direct influence on the duration of incubation, the size (mass, snout-vent length) and shape (relative tail length) of the hatchling, and subsequent growth rates of the lizard during the first 3 mo of life. Embryos with genes that code for a few days' delay in hatching are thereby larger when they hatch, having undergone further differentiation (and hence, have changed in bodily proportions), and are able to grow faster after hatching. Our data thus provide empirical support for a crucial but rarely tested assumption of life-history theory, and illuminate some of the proximate mechanisms that produce intraspecific variation in offspring phenotypes. © 1996 The Society for the Study of Evolution.

Normative morphometric data for cerebral cortical areas over the lifetime of the adult human brain.

PubMed

Potvin, Olivier; Dieumegarde, Louis; Duchesne, Simon

2017-08-01

Proper normative data of anatomical measurements of cortical regions, allowing to quantify brain abnormalities, are lacking. We developed norms for regional cortical surface areas, thicknesses, and volumes based on cross-sectional MRI scans from 2713 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The explained variance for the left/right cortex was 76%/76% for surface area, 43%/42% for thickness, and 80%/80% for volume. The mean explained variance for all regions was 41% for surface areas, 27% for thicknesses, and 46% for volumes. Age, sex and eTIV predicted most of the explained variance for surface areas and volumes while age was the main predictors for thicknesses. Scanner characteristics generally predicted a limited amount of variance, but this effect was stronger for thicknesses than surface areas and volumes. For new individuals, estimates of their expected surface area, thickness and volume based on their characteristics and the scanner characteristics can be obtained using the derived formulas, as well as Z score effect sizes denoting the extent of the deviation from the normative sample. Models predicting normative values were validated in independent samples of healthy adults, showing satisfactory validation R 2 . Deviations from the normative sample were measured in individuals with mild Alzheimer's disease and schizophrenia and expected patterns of deviations were observed. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Assessing the relationship between computational speed and precision: a case study comparing an interpreted versus compiled programming language using a stochastic simulation model in diabetes care.

PubMed

McEwan, Phil; Bergenheim, Klas; Yuan, Yong; Tetlow, Anthony P; Gordon, Jason P

2010-01-01

Simulation techniques are well suited to modelling diseases yet can be computationally intensive. This study explores the relationship between modelled effect size, statistical precision, and efficiency gains achieved using variance reduction and an executable programming language. A published simulation model designed to model a population with type 2 diabetes mellitus based on the UKPDS 68 outcomes equations was coded in both Visual Basic for Applications (VBA) and C++. Efficiency gains due to the programming language were evaluated, as was the impact of antithetic variates to reduce variance, using predicted QALYs over a 40-year time horizon. The use of C++ provided a 75- and 90-fold reduction in simulation run time when using mean and sampled input values, respectively. For a series of 50 one-way sensitivity analyses, this would yield a total run time of 2 minutes when using C++, compared with 155 minutes for VBA when using mean input values. The use of antithetic variates typically resulted in a 53% reduction in the number of simulation replications and run time required. When drawing all input values to the model from distributions, the use of C++ and variance reduction resulted in a 246-fold improvement in computation time compared with VBA - for which the evaluation of 50 scenarios would correspondingly require 3.8 hours (C++) and approximately 14.5 days (VBA). The choice of programming language used in an economic model, as well as the methods for improving precision of model output can have profound effects on computation time. When constructing complex models, more computationally efficient approaches such as C++ and variance reduction should be considered; concerns regarding model transparency using compiled languages are best addressed via thorough documentation and model validation.

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

PubMed

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Brain Size and Cerebral Glucose Metabolic Rate in Nonspecific Retardation and Down Syndrome.

ERIC Educational Resources Information Center

Haier, Richard J.; And Others

1995-01-01

Brain size and cerebral glucose metabolic rate were determined for 10 individuals with mild mental retardation (MR), 7 individuals with Down syndrome (DS), and 10 matched controls. MR and DS groups both had brain volumes of about 80% compared to controls, with variance greatest within the MR group. (SLD)

Growth models and the expected distribution of fluctuating asymmetry

USGS Publications Warehouse

Graham, John H.; Shimizu, Kunio; Emlen, John M.; Freeman, D. Carl; Merkel, John

2003-01-01

Multiplicative error accounts for much of the size-scaling and leptokurtosis in fluctuating asymmetry. It arises when growth involves the addition of tissue to that which is already present. Such errors are lognormally distributed. The distribution of the difference between two lognormal variates is leptokurtic. If those two variates are correlated, then the asymmetry variance will scale with size. Inert tissues typically exhibit additive error and have a gamma distribution. Although their asymmetry variance does not exhibit size-scaling, the distribution of the difference between two gamma variates is nevertheless leptokurtic. Measurement error is also additive, but has a normal distribution. Thus, the measurement of fluctuating asymmetry may involve the mixing of additive and multiplicative error. When errors are multiplicative, we recommend computing log E(l) − log E(r), the difference between the logarithms of the expected values of left and right sides, even when size-scaling is not obvious. If l and r are lognormally distributed, and measurement error is nil, the resulting distribution will be normal, and multiplicative error will not confound size-related changes in asymmetry. When errors are additive, such a transformation to remove size-scaling is unnecessary. Nevertheless, the distribution of l − r may still be leptokurtic.

Technical note: A method for assigning animals to treatment groups with unequal count per group that equalizes mean animal weight among groups.

PubMed

Epplin, F M; Haankuku, C; Horn, G W

2015-09-01

Pastures available for grazing studies may be of unequal size and may have heterogeneous carrying capacity necessitating the assignment of unequal numbers of animals per pasture. To reduce experimental error, it is often desirable that the initial mean BW be similar among experimental units. The objective of this note is to present and illustrate the use of a method for assignment of animals to experimental units of different sizes such that the initial mean weight of animals in each unit is approximately the same as the overall mean. Two alternative models were developed and solved to assign each of 231 weaned steers () to 1 of 12 pastures with carrying capacity ranging from 5 to 26 animals per pasture. A solution to Model 1 was obtained in which the mean weights among pastures were approximately the same but the variances among pastures were heteroskedastic, meaning that weight variances across pens were different (-value < 0.05). An alternative model was developed (Model 2) and used to derive assignments with nearly equal mean weights and homoskedastic variances among pastures.

Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

USGS Publications Warehouse

Dzul, Maria C.; Dixon, Philip M.; Quist, Michael C.; Dinsomore, Stephen J.; Bower, Michael R.; Wilson, Kevin P.; Gaines, D. Bailey

2013-01-01

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review.

PubMed

Yang, Qinghua

2017-03-01

The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen's d ranging from -1.17 to 1.28. To provide a better understanding of SNS-based interventions' effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.

Bony pelvic canal size and shape in relation to body proportionality in humans.

PubMed

Kurki, Helen K

2013-05-01

Obstetric selection acts on the female pelvic canal to accommodate the human neonate and contributes to pelvic sexual dimorphism. There is a complex relationship between selection for obstetric sufficiency and for overall body size in humans. The relationship between selective pressures may differ among populations of different body sizes and proportions, as pelvic canal dimensions vary among populations. Size and shape of the pelvic canal in relation to body size and shape were examined using nine skeletal samples (total female n = 57; male n = 84) from diverse geographical regions. Pelvic, vertebral, and lower limb bone measurements were collected. Principal component analyses demonstrate pelvic canal size and shape differences among the samples. Male multivariate variance in pelvic shape is greater than female variance for North and South Africans. High-latitude samples have larger and broader bodies, and pelvic canals of larger size and, among females, relatively broader medio-lateral dimensions relative to low-latitude samples, which tend to display relatively expanded inlet antero-posterior (A-P) and posterior canal dimensions. Differences in canal shape exist among samples that are not associated with latitude or body size, suggesting independence of some canal shape characteristics from body size and shape. The South Africans are distinctive with very narrow bodies and small pelvic inlets relative to an elongated lower canal in A-P and posterior lengths. Variation in pelvic canal geometry among populations is consistent with a high degree of evolvability in the human pelvis. Copyright © 2013 Wiley Periodicals, Inc.

Finite mixture model: A maximum likelihood estimation approach on time series data

NASA Astrophysics Data System (ADS)

Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-09-01

Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.

A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Albers, Janice; Green, Nicholas; Moran, Edward H.

2017-01-01

We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.

Tactile sensitivity of gloved hands in the cold operation.

PubMed

Geng, Q; Kuklane, K; Holmér, I

1997-11-01

In this study, tactile sensitivity of gloved hand in the cold operation has been investigated. The relations among physical properties of protective gloves and hand tactile sensitivity and cold protection were also analysed both objectively and subjectively. Subjects with various gloves participated in the experimental study during cold exposure at different ambient temperatures of -12 degrees C and -25 degrees C. Tactual performance was measured using an identification task with various sizes of objects over the percentage of misjudgment. Forearm, hand and finger skin temperatures were also recorded throughout. The experimental data were analysed using analysis of variance (ANOVA) model and the Tukey's multiple range test. The results obtained indicated that the tactual performance was affected both by gloves and by hands/fingers cooling. Effect of object size on the tactile discrimination was significant and the misjudgment increased when similar sizes of objects were identified, especially at -25 degrees C.

Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

PubMed

Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

2015-11-30

We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

A Comparison of Detection and Tracking Methods as Applied to OPIR Optics

DTIC Science & Technology

2014-12-01

foreground % images. The function requires you to input the scenes in vector format % as well as the window size, w. You can also set the variable...2,ii)) hold on end %% Build Scene A_org = A; % Format track data add variance, variance not included here...Kopp, “High energy laser directed energy weapons,” APA , Tech. Rep. APA - TR-2008–0501, Air Power Australia, Apr. 2012. [5] High-energy laser. (n.d

Adaptive Optics for Turbulent Shear Layers

DTIC Science & Technology

2006-12-20

which is related to the phase variance through the wave number). Once obtained 5 by whatever means, the phase variance was used to compute an...new inlet for a wider test section and included a downstream throat to chock the flow and prevent pressure disturbances from the vacuum pumps from...wavefronts in Figure 15 are for an aperture size that captures only about half a cycle; the streamnwise length of the half cycle being -- 10 cm ( 4 in

Preliminary evidence for good psychometric properties of the Norwegian version of the Brief Problems Monitor (BPM).

PubMed

Richter, Jörg

2015-04-01

Methods to assess intervention progress and outcome for frequent use are needed. To provide preliminary information about psychometric properties for the Norwegian version of the Brief Problems Monitor. Cronbach's alpha scores and intra-class correlation coefficients as indicators for internal consistency (reliability) and Pearson correlation coefficients between corresponding subscales of the long and short ASEBA form versions as well as multiple regression coefficients to explore the predictive power of the reduced item-set related to the corresponding scale-scores of the long version were calculated in large, representative data sets of Norwegian children and adolescents. Cronbach's alpha scores of the Norwegian version of the BPM subscales varied between 0.67 (attention BPM-youth) and 0.88 (attention BPM-teacher) and between 0.90 (BPM-youth) and 0.96 (BPM-teacher) for its total problem score. Corresponding subscales from the long versions and the BPM as well as the total problems scores were closely correlated with coefficients of high effect size (all r > 0.80). The variance of the items of the BPM explained about three-quarters or more of the variance in the corresponding subscales of the long version. The Norwegian BPM has good psychometric properties in terms of 1) being acceptable to good internal consistency and in terms of 2) regression coefficients of high effect size from the BPM items to the problem-scale scores of the long versions as validity indicators. Its use in clinical practice and research can be recommended.

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

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

Romano, Paul K.; Lund, Amanda L.; Siegel, Andrew R.

2017-06-19

The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulationmore » that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.« less

Hierarchical nuclear and cytoplasmic genetic architectures for plant growth and defense within Arabidopsis.

PubMed

Joseph, Bindu; Corwin, Jason A; Züst, Tobias; Li, Baohua; Iravani, Majid; Schaepman-Strub, Gabriela; Turnbull, Lindsay A; Kliebenstein, Daniel J

2013-06-01

To understand how genetic architecture translates between phenotypic levels, we mapped the genetic architecture of growth and defense within the Arabidopsis thaliana Kas × Tsu recombinant inbred line population. We measured plant growth using traditional size measurements and size-corrected growth rates. This population contains genetic variation in both the nuclear and cytoplasmic genomes, allowing us to separate their contributions. The cytoplasmic genome regulated a significant variance in growth but not defense, which was due to cytonuclear epistasis. Furthermore, growth adhered to an infinitesimal model of genetic architecture, while defense metabolism was more of a moderate-effect model. We found a lack of concordance between quantitative trait loci (QTL) regulating defense and those regulating growth. Given the published evidence proving the link between glucosinolates and growth, this is likely a false negative result caused by the limited population size. This size limitation creates an inability to test the entire potential genetic landscape possible between these two parents. We uncovered a significant effect of glucosinolates on growth once we accounted for allelic differences in growth QTLs. Therefore, other growth QTLs can mask the effects of defense upon growth. Investigating direct links across phenotypic hierarchies is fraught with difficulty; we identify issues complicating this analysis.

Hierarchical Nuclear and Cytoplasmic Genetic Architectures for Plant Growth and Defense within Arabidopsis[C][W

PubMed Central

Joseph, Bindu; Corwin, Jason A.; Züst, Tobias; Li, Baohua; Iravani, Majid; Schaepman-Strub, Gabriela; Turnbull, Lindsay A.; Kliebenstein, Daniel J.

2013-01-01

To understand how genetic architecture translates between phenotypic levels, we mapped the genetic architecture of growth and defense within the Arabidopsis thaliana Kas × Tsu recombinant inbred line population. We measured plant growth using traditional size measurements and size-corrected growth rates. This population contains genetic variation in both the nuclear and cytoplasmic genomes, allowing us to separate their contributions. The cytoplasmic genome regulated a significant variance in growth but not defense, which was due to cytonuclear epistasis. Furthermore, growth adhered to an infinitesimal model of genetic architecture, while defense metabolism was more of a moderate-effect model. We found a lack of concordance between quantitative trait loci (QTL) regulating defense and those regulating growth. Given the published evidence proving the link between glucosinolates and growth, this is likely a false negative result caused by the limited population size. This size limitation creates an inability to test the entire potential genetic landscape possible between these two parents. We uncovered a significant effect of glucosinolates on growth once we accounted for allelic differences in growth QTLs. Therefore, other growth QTLs can mask the effects of defense upon growth. Investigating direct links across phenotypic hierarchies is fraught with difficulty; we identify issues complicating this analysis. PMID:23749847

Effects of Droplet Size on Intrusion of Sub-Surface Oil Spills

NASA Astrophysics Data System (ADS)

Adams, Eric; Chan, Godine; Wang, Dayang

2014-11-01

We explore effects of droplet size on droplet intrusion and transport in sub-surface oil spills. Negatively buoyant glass beads released continuously to a stratified ambient simulate oil droplets in a rising multiphase plume, and distributions of settled beads are used to infer signatures of surfacing oil. Initial tests used quiescent conditions, while ongoing tests simulate currents by towing the source and a bottom sled. Without current, deposited beads have a Gaussian distribution, with variance increasing with decreasing particle size. Distributions agree with a model assuming first order particle loss from an intrusion layer of constant thickness, and empirically determined flow rate. With current, deposited beads display a parabolic distribution similar to that expected from a source in uniform flow; we are currently comparing observed distributions with similar analytical models. Because chemical dispersants have been used to reduce oil droplet size, our study provides one measure of their effectiveness. Results are applied to conditions from the `Deep Spill' field experiment, and the recent Deepwater Horizon oil spill, and are being used to provide ``inner boundary conditions'' for subsequent far field modeling of these events. This research was made possible by grants from Chevron Energy Technology Co., through the Chevron-MITEI University Partnership Program, and BP/The Gulf of Mexico Research Initiative, GISR.

Modeling turbidity type and intensity effects on the growth and starvation mortality of age-0 yellow perch

USGS Publications Warehouse

Manning, Nathan M; Bossenbroek, Jonathan M.; Mayer, Christine M.; Bunnell, David B.; Tyson, Jeff T.; Rudstam, Lars G.; Jackson, James R.

2014-01-01

We sought to quantify the possible population-level influence of sediment plumes and algal blooms on yellow perch (Perca flavescens), a visual predator found in systems with dynamic water clarity. We used an individual-based model (IBM), which allowed us to include variance in water clarity and the distribution of individual sizes. Our IBM was built with laboratory data showing that larval yellow perch feeding rates increased slightly as sediment turbidity level increased, but that both larval and juvenile yellow perch feeding rates decreased as phytoplankton level increased. Our IBM explained a majority of the variance in yellow perch length in data from the western and central basins of Lake Erie and Oneida Lake, with R2 values ranging from 0.611 to 0.742. Starvation mortality was size dependent, as the greatest daily mortality rates in each simulation occurred within days of each other. Our model showed that turbidity-dependent consumption rates and temperature are key components in determining growth and starvation mortality of age-0 yellow perch, linking fish production to land-based processes that influence water clarity. These results suggest the timing and persistence of sediment plumes and algal blooms can drastically alter the growth potential and starvation mortality of a yellow perch cohort.

Nine, seven, five, or three: how many figures do we need for assessing body image?

PubMed

Ambrosi-Randić, Neala; Pokrajac-Bulian, Alessandra; Taksić, Vladimir

2005-04-01

320 Croatian female students (M=20.4 yr.) were recruited to examine the validity and reliability of figural scales using different numbers of stimuli (3, 5, 7, and 9) and different serial presentation (serial and nonserial order). A two-way analysis of variance (4 numbers x 2 orders of stimuli) was performed on ratings of current self-size and ideal size as dependent variables. Analysis indicated a significant main effect of number of stimuli. This, together with post hoc tests indicated that ratings were significantly different for a scale of three figures from scales of more figures, which in turn did not differ among themselves. Main effects of order of stimuli, as well as the interaction, were not significant. The results support the hypothesis that the optimal number of figures on a scale is seven plus (or minus) two.

Now you see it, now you don't: on emotion, context, and the algorithmic prediction of human imageability judgments

PubMed Central

Westbury, Chris F.; Shaoul, Cyrus; Hollis, Geoff; Smithson, Lisa; Briesemeister, Benny B.; Hofmann, Markus J.; Jacobs, Arthur M.

2013-01-01

Many studies have shown that behavioral measures are affected by manipulating the imageability of words. Though imageability is usually measured by human judgment, little is known about what factors underlie those judgments. We demonstrate that imageability judgments can be largely or entirely accounted for by two computable measures that have previously been associated with imageability, the size and density of a word's context and the emotional associations of the word. We outline an algorithmic method for predicting imageability judgments using co-occurrence distances in a large corpus. Our computed judgments account for 58% of the variance in a set of nearly two thousand imageability judgments, for words that span the entire range of imageability. The two factors account for 43% of the variance in lexical decision reaction times (LDRTs) that is attributable to imageability in a large database of 3697 LDRTs spanning the range of imageability. We document variances in the distribution of our measures across the range of imageability that suggest that they will account for more variance at the extremes, from which most imageability-manipulating stimulus sets are drawn. The two predictors account for 100% of the variance that is attributable to imageability in newly-collected LDRTs using a previously-published stimulus set of 100 items. We argue that our model of imageability is neurobiologically plausible by showing it is consistent with brain imaging data. The evidence we present suggests that behavioral effects in the lexical decision task that are usually attributed to the abstract/concrete distinction between words can be wholly explained by objective characteristics of the word that are not directly related to the semantic distinction. We provide computed imageability estimates for over 29,000 words. PMID:24421777

Statistical power and effect sizes of depression research in Japan.

PubMed

Okumura, Yasuyuki; Sakamoto, Shinji

2011-06-01

Few studies have been conducted on the rationales for using interpretive guidelines for effect size, and most of the previous statistical power surveys have covered broad research domains. The present study aimed to estimate the statistical power and to obtain realistic target effect sizes of depression research in Japan. We systematically reviewed 18 leading journals of psychiatry and psychology in Japan and identified 974 depression studies that were mentioned in 935 articles published between 1990 and 2006. In 392 studies, logistic regression analyses revealed that using clinical populations was independently associated with being a statistical power of <0.80 (odds ratio 5.9, 95% confidence interval 2.9-12.0) and of <0.50 (odds ratio 4.9, 95% confidence interval 2.3-10.5). Of the studies using clinical populations, 80% did not achieve a power of 0.80 or more, and 44% did not achieve a power of 0.50 or more to detect the medium population effect sizes. A predictive model for the proportion of variance explained was developed using a linear mixed-effects model. The model was then used to obtain realistic target effect sizes in defined study characteristics. In the face of a real difference or correlation in population, many depression researchers are less likely to give a valid result than simply tossing a coin. It is important to educate depression researchers in order to enable them to conduct an a priori power analysis. © 2011 The Authors. Psychiatry and Clinical Neurosciences © 2011 Japanese Society of Psychiatry and Neurology.

On the additive and dominant variance and covariance of individuals within the genomic selection scope.

PubMed

Vitezica, Zulma G; Varona, Luis; Legarra, Andres

2013-12-01

Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or "breeding" values of individuals are generated by substitution effects, which involve both "biological" additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the "genotypic" value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.

Does population size affect genetic diversity? A test with sympatric lizard species.

PubMed

Hague, M T J; Routman, E J

2016-01-01

Genetic diversity is a fundamental requirement for evolution and adaptation. Nonetheless, the forces that maintain patterns of genetic variation in wild populations are not completely understood. Neutral theory posits that genetic diversity will increase with a larger effective population size and the decreasing effects of drift. However, the lack of compelling evidence for a relationship between genetic diversity and population size in comparative studies has generated some skepticism over the degree that neutral sequence evolution drives overall patterns of diversity. The goal of this study was to measure genetic diversity among sympatric populations of related lizard species that differ in population size and other ecological factors. By sampling related species from a single geographic location, we aimed to reduce nuisance variance in genetic diversity owing to species differences, for example, in mutation rates or historical biogeography. We compared populations of zebra-tailed lizards and western banded geckos, which are abundant and short-lived, to chuckwallas and desert iguanas, which are less common and long-lived. We assessed population genetic diversity at three protein-coding loci for each species. Our results were consistent with the predictions of neutral theory, as the abundant species almost always had higher levels of haplotype diversity than the less common species. Higher population genetic diversity in the abundant species is likely due to a combination of demographic factors, including larger local population sizes (and presumably effective population sizes), faster generation times and high rates of gene flow with other populations.

A pilot cluster randomized controlled trial of structured goal-setting following stroke.

PubMed

Taylor, William J; Brown, Melanie; William, Levack; McPherson, Kathryn M; Reed, Kirk; Dean, Sarah G; Weatherall, Mark

2012-04-01

To determine the feasibility, the cluster design effect and the variance and minimal clinical importance difference in the primary outcome in a pilot study of a structured approach to goal-setting. A cluster randomized controlled trial. Inpatient rehabilitation facilities. People who were admitted to inpatient rehabilitation following stroke who had sufficient cognition to engage in structured goal-setting and complete the primary outcome measure. Structured goal elicitation using the Canadian Occupational Performance Measure. Quality of life at 12 weeks using the Schedule for Individualised Quality of Life (SEIQOL-DW), Functional Independence Measure, Short Form 36 and Patient Perception of Rehabilitation (measuring satisfaction with rehabilitation). Assessors were blinded to the intervention. Four rehabilitation services and 41 patients were randomized. We found high values of the intraclass correlation for the outcome measures (ranging from 0.03 to 0.40) and high variance of the SEIQOL-DW (SD 19.6) in relation to the minimally importance difference of 2.1, leading to impractically large sample size requirements for a cluster randomized design. A cluster randomized design is not a practical means of avoiding contamination effects in studies of inpatient rehabilitation goal-setting. Other techniques for coping with contamination effects are necessary.

Impact of Damping Uncertainty on SEA Model Response Variance

NASA Technical Reports Server (NTRS)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Modelling and optimising of physicochemical features of walnut-oil beverage emulsions by implementation of response surface methodology: effect of preparation conditions on emulsion stability.

PubMed

Homayoonfal, Mina; Khodaiyan, Faramarz; Mousavi, Mohammad

2015-05-01

The major purpose of this study is to apply response surface methodology to model and optimise processing conditions for the preparation of beverage emulsions with maximum emulsion stability and viscosity, minimum particle size, turbidity loss rate, size index and peroxide value changes. A three-factor, five-level central composite design was conducted to estimate the effects of three independent variables: ultrasonic time (UT, 5-15 min), walnut-oil content (WO, 4-10% (w/w)) and Span 80 content (S80, 0.55-0.8). The results demonstrated the empirical models were satisfactorily (p < 0.0001) fitted to the experimental data. Evaluation of responses by analysis of variance indicated high coefficient determination values. The overall optimisation of preparation conditions was an UT of 14.630 min, WO content of 8.238% (w/w), and S80 content of 0.782% (w/w). Under this optimum region, responses were found to be 219.198, 99.184, 0.008, 0.008, 2.43 and 16.65 for particle size, emulsion stability, turbidity loss rate, size index, viscosity and peroxide value changes, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

Self-narrowing of size distributions of nanostructures by nucleation antibunching

NASA Astrophysics Data System (ADS)

Glas, Frank; Dubrovskii, Vladimir G.

2017-08-01

We study theoretically the size distributions of ensembles of nanostructures fed from a nanosize mother phase or a nanocatalyst that contains a limited number of the growth species that form each nanostructure. In such systems, the nucleation probability decreases exponentially after each nucleation event, leading to the so-called nucleation antibunching. Specifically, this effect has been observed in individual nanowires grown in the vapor-liquid-solid mode and greatly affects their properties. By performing numerical simulations over large ensembles of nanostructures as well as developing two different analytical schemes (a discrete and a continuum approach), we show that nucleation antibunching completely suppresses fluctuation-induced broadening of the size distribution. As a result, the variance of the distribution saturates to a time-independent value instead of growing infinitely with time. The size distribution widths and shapes primarily depend on the two parameters describing the degree of antibunching and the nucleation delay required to initiate the growth. The resulting sub-Poissonian distributions are highly desirable for improving size homogeneity of nanowires. On a more general level, this unique self-narrowing effect is expected whenever the growth rate is regulated by a nanophase which is able to nucleate an island much faster than it is refilled from a surrounding macroscopic phase.

Variance in predicted cup size by 2-dimensional vs 3-dimensional computerized tomography-based templating in primary total hip arthroplasty.

PubMed

Osmani, Feroz A; Thakkar, Savyasachi; Ramme, Austin; Elbuluk, Ameer; Wojack, Paul; Vigdorchik, Jonathan M

2017-12-01

Preoperative total hip arthroplasty templating can be performed with radiographs using acetate prints, digital viewing software, or with computed tomography (CT) images. Our hypothesis is that 3D templating is more precise and accurate with cup size prediction as compared to 2D templating with acetate prints and digital templating software. Data collected from 45 patients undergoing robotic-assisted total hip arthroplasty compared cup sizes templated on acetate prints and OrthoView software to MAKOplasty software that uses CT scan. Kappa analysis determined strength of agreement between each templating modality and the final size used. t tests compared mean cup-size variance from the final size for each templating technique. Interclass correlation coefficient (ICC) determined reliability of digital and acetate planning by comparing predictions of the operating surgeon and a blinded adult reconstructive fellow. The Kappa values for CT-guided, digital, and acetate templating with the final size was 0.974, 0.233, and 0.262, respectively. Both digital and acetate templating significantly overpredicted cup size, compared to CT-guided methods ( P < .001). There was no significant difference between digital and acetate templating ( P  = .117). Interclass correlation coefficient value for digital and acetate templating was 0.928 and 0.931, respectively. CT-guided planning more accurately predicts hip implant cup size when compared to the significant overpredictions of digital and acetate templating. CT-guided templating may also lead to better outcomes due to bone stock preservation from a smaller and more accurate cup size predicted than that of digital and acetate predictions.

A Model Based Approach to Sample Size Estimation in Recent Onset Type 1 Diabetes

PubMed Central

Bundy, Brian; Krischer, Jeffrey P.

2016-01-01

The area under the curve C-peptide following a 2-hour mixed meal tolerance test from 481 individuals enrolled on 5 prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrollment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in Observed vs. Expected calculations to estimate the presumption of benefit in ongoing trials. PMID:26991448

The efficiency of close inbreeding to reduce genetic adaptation to captivity

PubMed Central

Theodorou, K; Couvet, D

2015-01-01

Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs. PMID:25052417

The influence of genetic and environmental factors in estimations of current body size, desired body size, and body dissatisfaction.

PubMed

Wade, T D; Bulik, C M; Heath, A C; Martin, N G; Eaves, L J

2001-08-01

The objective was to investigate the genetic epidemiology of figural stimuli. Standard figural stimuli were available from 5,325 complete twin pairs: 1,751 (32.9%) were monozygotic females, 1,068 (20.1%) were dizygotic females, 752 (14.1%) were monozygotic males, 495 (9.3%) were dizygotic males, and 1,259 (23.6%) were dizygotic male-female pairs. Univariate twin analyses were used to examine the influences on the individual variation in current body size and ideal body size. These data were analysed separately for men and women in each of five age groups. A factorial analysis of variance, with polychoric correlations between twin pairs as the dependent variable, and age, sex, zygosity, and the three interaction terms (age x sex, age x zygosity, sex x zygosity) as independent variables, was used to examine trends across the whole data set. Results showed genetic influences had the largest impact on the individual variation in current body size measures, whereas non-shared environmental influences were associated with the majority of individual variation in ideal body size. There was a significant main effect of zygosity (heritability) in predicting polychoric correlations for current body size and body dissatisfaction. There was a significant main effect of gender and zygosity in predicting ideal body size, with a gender x zygosity interaction. In common with BMI, heritability is important in influencing the estimation of current body size. Selection of desired body size for both men and women is more strongly influenced by environmental factors.

Genetic and maternal effect influences on viability of common frog tadpoles under different environmental conditions.

PubMed

Pakkasmaa, S; Merilä, J; O'Hara, R B

2003-08-01

The influence of environmental stress on the expression of genetic and maternal effects on the viability traits has seldom been assessed in wild vertebrates. We have estimated genetic and maternal effects on the viability (viz probability of survival, probability of being deformed, and body size and shape) of common frog, Rana temporaria, tadpoles under stressful (low pH) and nonstressful (neutral pH) environmental conditions. A Bayesian analysis using generalized linear mixed models was applied to data from a factorial laboratory experiment. The expression of additive genetic variance was independent of pH treatments, and all traits were significantly heritable (survival: h2 approximately 0.08; deformities: h2 approximately 0.26; body size: h2 approximately 0.12; body shape: h2 approximately 0.14). Likewise, nonadditive genetic contributions to variation in all traits were significant, independent of pH treatments and typically of magnitude similar to the additive genetic effects. Maternal effects were large for all traits, especially for viability itself, and their expression was partly dependent on the environment. In the case of body size, the maternal effects were mediated largely through egg size. In general, the results give little evidence for the conjecture that environmental stress created by low pH would impact strongly on the genetic architecture of fitness-related traits in frogs, and hamper adaptation to stress caused by acidification. The low heritabilities and high dominance contributions conform to the pattern typical for traits subject to relatively strong directional selection.

Laser beam propagation in atmospheric turbulence

NASA Technical Reports Server (NTRS)

Murty, S. S. R.

1979-01-01

The optical effects of atmospheric turbulence on the propagation of low power laser beams are reviewed in this paper. The optical effects are produced by the temperature fluctuations which result in fluctuations of the refractive index of air. The commonly-used models of index-of-refraction fluctuations are presented. Laser beams experience fluctuations of beam size, beam position, and intensity distribution within the beam due to refractive turbulence. Some of the observed effects are qualitatively explained by treating the turbulent atmosphere as a collection of moving gaseous lenses of various sizes. Analytical results and experimental verifications of the variance, covariance and probability distribution of intensity fluctuations in weak turbulence are presented. For stronger turbulence, a saturation of the optical scintillations is observed. The saturation of scintillations involves a progressive break-up of the beam into multiple patches; the beam loses some of its lateral coherence. Heterodyne systems operating in a turbulent atmosphere experience a loss of heterodyne signal due to the destruction of coherence.

A new model for Mars atmospheric dust based upon analysis of ultraviolet through infrared observations from Mariner 9, Viking, and Phobos

NASA Technical Reports Server (NTRS)

Clancy, R. T.; Lee, S. W.; Gladstone, G. R.; McMillan, W. W.; Rousch, T.

1995-01-01

We propose key modifications to the Toon et al. (1977) model of the particle size distribution and composition of Mars atmospheric dust, based on a variety of spacecraft and wavelength observations of the dust. A much broader (r(sub eff)variance-0.8 micron), smaller particle size (r(sub mode)-0.02 microns) distribution coupled with a "palagonite-like" composition is argued to fit the complete ultraviolet-to-30-micron absorption properties of the dust better than the montmorillonite-basalt r(sub eff)variance= 0.4 micron, r(sub mode)= 0.40 micron dust model of Toon et al. Mariner 9 (infrared interferometer spectrometer) IRIS spectra of high atmospheric dust opacities during the 1971 - 1972 Mars global dust storm are analyzed in terms of the Toon et al. dust model, and a Hawaiian palagonite sample with two different size distribution models incorporating smaller dust particle sizes. Viking Infrared Thermal Mapper (IRTM) emission-phase-function (EPF) observations at 9 microns are analyzed to retrieve 9-micron dust opacities coincident with solar band dust opacities obtained from the same EPF sequences. These EPF dust opacities provide an independent measurement of the visible/9-microns extinction opacity ratio (> or equal to 2) for Mars atmospheric dust, which is consistent with a previous measurement by Martin (1986). Model values for the visible/9-microns opacity ratio and the ultraviolet and visible single-scattering albedos are calculated for the palagonite model with the smaller particle size distributions and compared to the same properties for the Toon et al. model of dust. The montmorillonite model of the dust is found to fit the detailed shape of the dust 9-micron absorption well. However, it predicts structured, deep absorptions at 20 microns which are not observed and requires a separate ultraviolet-visible absorbing component to match the observed behavior of the dust in this wavelength region. The modeled palagonite does not match the 8- to 9-micron absorption presented by the dust in the IRIS spectra, probably due to its low SiO2 content (31%). However, it does provide consistent levels of ultraviolet/visible absorption, 9- to 12-micron absorption, and a lack of structured absorption at 20 microns. The ratios of dust extinction opacities at visible, 9 microns, and 30 microns are strongly affected by the dust particle size distribution. The Toon et al. dust size distribution (r(sub mode)= 0.40, r(sub eff)variance= 0.4 microns, r(sub cw mu)= 2.7 microns) predicts the correct ratio of the 9- to 30-micron opacity, but underpredicts the visible/9-micron opacity ratio considerably (1 versus > or equal to 2). A similar particle distribution width with smaller particle sizes (r(sub mode)= 0.17, r(sub eff)variance= 0.4 microns, r(sub cw mu)=1.2 microns) will fit the observed visible/9-micron opacity ratio, but overpredicts the observed 9-micron/30-micron opacity ratio. A smaller and much broader particle size distribution (r(sub mode)= 0.02, r(sub eff)variance= 0.8 microns, r(sub cw mu)= 1.8 microns) can fit both dust opacity ratios. Overall, the nanocrystalline structure of palagonite coupled with a smaller, broader distribution of dust particle sizes provides a more consistent fit than the Toon et al. model of the dust to the IRIS spectra, the observed visible/9-micron dust opacity ratio, the Phobos occultation measurements of dust particle sizes, and the weakness of surface near IR absorptions expected for clay minerals.

A new model for Mars atmospheric dust based upon analysis of ultraviolet through infrared observations from Mariner 9, Viking, and Phobos

NASA Technical Reports Server (NTRS)

Clancy, R. T.; Lee, S. W.; Gladstone, G. R.; Mcmillan, W. W.; Rousch, T.

1995-01-01

We propose key modifications to the Toon et al. (1977) model of the particle size distribution and composition of Mars atmospheric dust, based on a variety of spacecraft and wavelength observations of the dust. A much broader (r(sub eff) variance approximately 0.8 micrometers), smaller particle size (r(sub mode) approximately 0.02 micrometers) distribution coupled with a 'palagonite-like' composition is argued to fit the complete ultraviolet-to-30-micrometer absorption properties of the dust better than the montmorillonite-basalt, r(sub eff) variance = 0.4 micrometers, r(sub mode) = 0.40 dust model of Toon et al. Mariner 9 (infrared interferometer spectrometer) IRIS spectra of high atmospheric dust opacities during the 1971-1972 Mars global dust storm are analyzed in terms of the Toon et al. dust model, and a Hawaiian palagonite sample (Rousch et al., 1991) with two different size distribution models incorporating smaller dust particle sizes. Viking Infrared Thermal Mapper (IRTM) emmission-phase-function (EPF) observations at 9 micrometers are analyzed to retrieve 9-micrometer dust opacities coincident with solar band dust opacities obtained from the same EPF sequences (Clancy and Lee, 1991). These EPF dust opacities provide an independent measurement of the visible/9-micrometer extinction opacity ratio (greater than or = 2) for Mars atmospheric dust, which is consistent with a previous measurement by Martin (1986). Model values for the visible/9-micrometer opacity ratio and the ultraviolet and visible single-scattering albedos are calculated for the palagonite model with the smaller particle size distributions compared to the same properties for the Toon et al. model of dust. The montmorillonite model of the dust is found to fit the detailed shape of the dust 9-micrometer absorption well. However, it predicts structured, deep aborptions at 20 micrometers which are not observed and requires a separate ultraviolet-visible absorbing component to match the observed behavior of the dust in this wavelength region. The modeled palagonite does not match the 8-to 9-micrometer absorption presented by the dust in the IRIS spectra, probably due to its low SiO2 content (31%). However, it does provide consistent levels of ultraviolet/visible absorption, 9-to 12-micrometer absorption, and a lack of structured absorption at 20 micrometers. The ratios of dust extinction opacities at visible, 9 micrometers, and 30 micrometers are strongly affected by the dust particle size distribution. The Toon et al. dust size distribution (r(sub mode) = 0.40,r(sub eff) variance = 0.4 micrometers, r(sub cwmu) = 2.7 micrometers) predicts the correct ratio of the 9- to 30-micrometer opacity, but underpredicts the visible/9-micrometer opacity ratio considerably (1 versus greater than or = 2). A similar particle distribution width with smaller particle sizes (r(sub mode) = 0.17, r(sub eff) variance = 0.4 micrometers, r(sub cwmu) = 1.2 micrometers) will fit the observed visible/9-micrometer opacity ratio, but overpredicts the observed 9-micrometer/30-micrometer opacity ratio. A smaller and much broader particle size distribution (r(sub mode) = 0.002, r(sub eff) variance = 0.8 micrometers, r(sub cwmu) = 1.8 micrometers) can fit both dust opacity ratios. Overall, the nanocrystalline structure of palagonite coupled with a smaller, broader distribution of dust particle sizes provides a more consistent fit than the Toon et al. model of the dust to the IRIS spectra, the observed visible/9-micrometer dust opacity ratio, the Phobos occulation measurements of the dust particle sizes (Chassefiere et al., 1992), and the weakness of surface near IR absorptions expected for clay minerals (Clark, 1992; Bell and Crisp, 1993).

Bottleneck Effect on Evolutionary Rate in the Nearly Neutral Mutation Model

PubMed Central

Araki, H.; Tachida, H.

1997-01-01

Variances of evolutionary rates among lineages in some proteins are larger than those expected from simple Poisson processes. This phenomenon is called overdispersion of the molecular clock. If population size N is constant, the overdispersion is observed only in a limited range of 2Nσ under the nearly neutral mutation model, where σ represents the standard deviation of selection coefficients of new mutants. In this paper, we investigated effects of changing population size on the evolutionary rate by computer simulations assuming the nearly neutral mutation model. The size was changed cyclically between two numbers, N(1) and N(2) (N(1) > N(2)), in the simulations. The overdispersion is observed if 2N(2)σ is less than two and the state of reduced size (bottleneck state) continues for more than ~0.1/u generations, where u is the mutation rate. The overdispersion results mainly because the average fitnesses of only a portion of populations go down when the population size is reduced and only in these populations subsequent advantageous substitutions occur after the population size becomes large. Since the fitness reduction after the bottleneck is stochastic, acceleration of the evolutionary rate does not necessarily occur uniformly among loci. From these results, we argue that the nearly neutral mutation model is a candidate mechanism to explain the overdispersed molecular clock. PMID:9335622

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

PubMed

Graf, Alexandra C; Bauer, Peter

2011-06-30

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

Impact of aortic root size on left ventricular afterload and stroke volume.

PubMed

Sahlén, Anders; Hamid, Nadira; Amanullah, Mohammed Rizwan; Fam, Jiang Ming; Yeo, Khung Keong; Lau, Yee How; Lam, Carolyn S P; Ding, Zee Pin

2016-07-01

The left ventricle (LV) ejects blood into the proximal aorta. Age and hypertension are associated with stiffening and dilation of the aortic root, typically viewed as indicative of adverse remodeling. Based on analytical considerations, we hypothesized that a larger aortic root should be associated with lower global afterload (effective arterial elastance, EA) and larger stroke volume (SV). Moreover, as antihypertensive drugs differ in their effect on central blood pressure, we examined the role of antihypertensive drugs for the relation between aortic root size and afterload. We studied a large group of patients (n = 1250; 61 ± 12 years; 78 % males; 64 % hypertensives) from a single-center registry with known or suspected coronary artery disease. Aortic root size was measured by echocardiography as the diameter of the tubular portion of the ascending aorta. LV outflow tract Doppler was used to record SV. In the population as a whole, after adjusting for key covariates in separate regression models, aortic root size was an independent determinant of both SV and EA. This association was found to be heterogeneous and stronger in patients taking a calcium channel blocker (CCB; 10.6 % of entire population; aortic root size accounted for 8 % of the explained variance of EA). Larger aortic root size is an independent determinant of EA and SV. This association was heterogeneous and stronger in patients on CCB therapy.

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

Natural selection and inheritance of breeding time and clutch size in the collared flycatcher.

PubMed

Sheldon, B C; Kruuk, L E B; Merilä, J

2003-02-01

Many characteristics of organisms in free-living populations appear to be under directional selection, possess additive genetic variance, and yet show no evolutionary response to selection. Avian breeding time and clutch size are often-cited examples of such characters. We report analyses of inheritance of, and selection on, these traits in a long-term study of a wild population of the collared flycatcher Ficedula albicollis. We used mixed model analysis with REML estimation ("animal models") to make full use of the information in complex multigenerational pedigrees. Heritability of laying date, but not clutch size, was lower than that estimated previously using parent-offspring regressions, although for both traits there was evidence of substantial additive genetic variance (h2 = 0.19 and 0.29, respectively). Laying date and clutch size were negatively genetically correlated (rA = -0.41 +/- 0.09), implying that selection on one of the traits would cause a correlated response in the other, but there was little evidence to suggest that evolution of either trait would be constrained by correlations with other phenotypic characters. Analysis of selection on these traits in females revealed consistent strong directional fecundity selection for earlier breeding at the level of the phenotype (beta = -0.28 +/- 0.03), but little evidence for stabilising selection on breeding time. We found no evidence that clutch size was independently under selection. Analysis of fecundity selection on breeding values for laying date, estimated from an animal model, indicated that selection acts directly on additive genetic variance underlying breeding time (beta = -0.20 +/- 0.04), but not on clutch size (beta = 0.03 +/- 0.05). In contrast, selection on laying date via adult female survival fluctuated in sign between years, and was opposite in sign for selection on phenotypes (negative) and breeding values (positive). Our data thus suggest that any evolutionary response to selection on laying date is partially constrained by underlying life-history trade-offs, and illustrate the difficulties in using purely phenotypic measures and incomplete fitness estimates to assess evolution of life-history trade-offs. We discuss some of the difficulties associated with understanding the evolution of laying date and clutch size in natural populations.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

Analysis of the variation in OCT measurements of a structural bottle neck for eye-brain transfer of visual information from 3D-volumes of the optic nerve head, PIMD-Average [02π

NASA Astrophysics Data System (ADS)

Söderberg, Per G.; Malmberg, Filip; Sandberg-Melin, Camilla

2016-03-01

The present study aimed to analyze the clinical usefulness of the thinnest cross section of the nerve fibers in the optic nerve head averaged over the circumference of the optic nerve head. 3D volumes of the optic nerve head of the same eye was captured at two different visits spaced in time by 1-4 weeks, in 13 subjects diagnosed with early to moderate glaucoma. At each visit 3 volumes containing the optic nerve head were captured independently with a Topcon OCT- 2000 system. In each volume, the average shortest distance between the inner surface of the retina and the central limit of the pigment epithelium around the optic nerve head circumference, PIMD-Average [02π], was determined semiautomatically. The measurements were analyzed with an analysis of variance for estimation of the variance components for subjects, visits, volumes and semi-automatic measurements of PIMD-Average [0;2π]. It was found that the variance for subjects was on the order of five times the variance for visits, and the variance for visits was on the order of 5 times higher than the variance for volumes. The variance for semi-automatic measurements of PIMD-Average [02π] was 3 orders of magnitude lower than the variance for volumes. A 95 % confidence interval for mean PIMD-Average [02π] was estimated to 1.00 +/-0.13 mm (D.f. = 12). The variance estimates indicate that PIMD-Average [02π] is not suitable for comparison between a onetime estimate in a subject and a population reference interval. Cross-sectional independent group comparisons of PIMD-Average [02π] averaged over subjects will require inconveniently large sample sizes. However, cross-sectional independent group comparison of averages of within subject difference between baseline and follow-up can be made with reasonable sample sizes. Assuming a loss rate of 0.1 PIMD-Average [02π] per year and 4 visits per year it was found that approximately 18 months follow up is required before a significant change of PIMDAverage [02π] can be observed with a power of 0.8. This is shorter than what has been observed both for HRT measurements and automated perimetry measurements with a similar observation rate. It is concluded that PIMDAverage [02π] has the potential to detect deterioration of glaucoma quicker than currently available primary diagnostic instruments. To increase the efficiency of PIMD-Average [02π] further, the variation among visits within subject has to be reduced.

Noisy covariance matrices and portfolio optimization

NASA Astrophysics Data System (ADS)

Pafka, S.; Kondor, I.

2002-05-01

According to recent findings [#!bouchaud!#,#!stanley!#], empirical covariance matrices deduced from financial return series contain such a high amount of noise that, apart from a few large eigenvalues and the corresponding eigenvectors, their structure can essentially be regarded as random. In [#!bouchaud!#], e.g., it is reported that about 94% of the spectrum of these matrices can be fitted by that of a random matrix drawn from an appropriately chosen ensemble. In view of the fundamental role of covariance matrices in the theory of portfolio optimization as well as in industry-wide risk management practices, we analyze the possible implications of this effect. Simulation experiments with matrices having a structure such as described in [#!bouchaud!#,#!stanley!#] lead us to the conclusion that in the context of the classical portfolio problem (minimizing the portfolio variance under linear constraints) noise has relatively little effect. To leading order the solutions are determined by the stable, large eigenvalues, and the displacement of the solution (measured in variance) due to noise is rather small: depending on the size of the portfolio and on the length of the time series, it is of the order of 5 to 15%. The picture is completely different, however, if we attempt to minimize the variance under non-linear constraints, like those that arise e.g. in the problem of margin accounts or in international capital adequacy regulation. In these problems the presence of noise leads to a serious instability and a high degree of degeneracy of the solutions.

Biological maturity-associated variance in peak power output and momentum in academy rugby union players.

PubMed

Howard, Sean M A; Cumming, Sean P; Atkinson, Mark; Malina, Robert M

2016-11-01

The study aimed to evaluate the mediating effect of biological maturation on anthropometrical measurements, performance indicators and subsequent selection in a group of academy rugby union players. Fifty-one male players 14-17 years of age were assessed for height, weight and BMI, and percentage of predicted mature status attained at the time of observation was used as an indicator of maturity status. Following this, initial sprint velocity (ISV), Wattbike peak power output (PPO) and initial sprint momentum (ISM) were assessed. A bias towards on-time (n = 44) and early (n = 7) maturers was evident in the total sample and magnified with age cohort. Relative to UK reference values, weight and height were above the 90th and 75th centiles, respectively. Significant (p ≤ .01) correlations were observed between maturity status and BMI (r = .48), weight (r = .63) and height (r = .48). Regression analysis (controlling for age) revealed that maturity status and height explained 68% of ISM variance; however, including BMI in the model attenuated the influence of maturity status below statistical significance (p = .72). Height and BMI explained 51% of PPO variance, while no initial significant predictors were identified for ISV. The sample consisted of players who were on-time and early in maturation with no late maturers represented. This was attributable, in part, to the mediating effect of maturation on body size, which, in turn, predicted performance variables.

Characterizing fish community diversity across Virginia landscapes: Prerequisite for conservation

USGS Publications Warehouse

Angermeier, P.L.; Winston, M.R.

1999-01-01

The number of community types occurring within landscapes is an important, but often unprotected, component of biological diversity. Generally applicable protocols for characterizing community diversity need to be developed to facilitate conservation. We used several multivariate techniques to analyze geographic variation in the composition of fish communities in Virginia streams. We examined relationships between community composition and six landscape variables: drainage basin, physiography, stream order, elevation, channel slope, and map coordinates. We compared patterns at two scales (statewide and subdrainage-specific) to assess sensitivity of community classification to spatial scale. We also compared patterns based on characterizing communities by species composition vs. ecological composition. All landscape variables explained significant proportions of the variance in community composition. Statewide, they explained 32% of the variance in species composition and 48% of the variance in ecological composition. Typical communities in each drainage or physiography were statistically distinctive. Communities in different combinations of drainage, physiography, and stream size were even more distinctive, but composition was strongly spatially autocorrelated. Ecological similarity and species similarity of community pairs were strongly related, but replacement by ecologically similar species was common among drainage-physiography combinations. Landscape variables explained significant proportions of variance in community composition within selected subdrainages, but proportions were less than at the statewide scale, and the explanatory power of individual variables varied considerably among subdrainages. Community variation within subdrainages appeared to be much more closely related to environmental variation than to replacement among ecologically similar species. Our results suggest that taxonomic and ecological characterizations of community composition are complementary; both are useful in a conservation context. Landscape features such as drainage, physiography, and water body size generally may provide a basis for assessing aquatic community diversity, especially in regions where the biota is poorly known. Systematic conservation of community types would be a major advance relative to most current conservation programs, which typically focus narrowly on populations of imperiled species. More effective conservation of aquatic biodiversity will require new approaches that recognize the value of both species and assemblages, and that emphasize protection of key landscape-scale processes.

Skeletal maturation, fundamental motor skills and motor coordination in children 7-10 years.

PubMed

Freitas, Duarte L; Lausen, Berthold; Maia, José António; Lefevre, Johan; Gouveia, Élvio Rúbio; Thomis, Martine; Antunes, António Manuel; Claessens, Albrecht L; Beunen, Gaston; Malina, Robert M

2015-01-01

Relationships between skeletal maturation and fundamental motor skills and gross motor coordination were evaluated in 429 children (213 boys and 216 girls) 7-10 years. Skeletal age was assessed (Tanner-Whitehouse 2 method), and stature, body mass, motor coordination (Körperkoordinations Test für Kinder, KTK) and fundamental motor skills (Test of Gross Motor Development, TGMD-2) were measured. Relationships among chronological age, skeletal age (expressed as the standardised residual of skeletal age on chronological age) and body size and fundamental motor skills and motor coordination were analysed with hierarchical multiple regression. Standardised residual of skeletal age on chronological age interacting with stature and body mass explained a maximum of 7.0% of the variance in fundamental motor skills and motor coordination over that attributed to body size per se. Standardised residual of skeletal age on chronological age alone accounted for a maximum of 9.0% of variance in fundamental motor skills, and motor coordination over that attributed to body size per se and interactions between standardised residual of skeletal age on chronological age and body size. In conclusion, skeletal age alone or interacting with body size has a negligible influence on fundamental motor skills and motor coordination in children 7-10 years.

Finite Size Corrections to the Parisi Overlap Function in the GREM

NASA Astrophysics Data System (ADS)

Derrida, Bernard; Mottishaw, Peter

2018-01-01

We investigate the effects of finite size corrections on the overlap probabilities in the Generalized Random Energy Model in two situations where replica symmetry is broken in the thermodynamic limit. Our calculations do not use replicas, but shed some light on what the replica method should give for finite size corrections. In the gradual freezing situation, which is known to exhibit full replica symmetry breaking, we show that the finite size corrections lead to a modification of the simple relations between the sample averages of the overlaps Y_k between k configurations predicted by replica theory. This can be interpreted as fluctuations in the replica block size with a negative variance. The mechanism is similar to the one we found recently in the random energy model in Derrida and Mottishaw (J Stat Mech 2015(1): P01021, 2015). We also consider a simultaneous freezing situation, which is known to exhibit one step replica symmetry breaking. We show that finite size corrections lead to full replica symmetry breaking and give a more complete derivation of the results presented in Derrida and Mottishaw (Europhys Lett 115(4): 40005, 2016) for the directed polymer on a tree.

On geological interpretations of crystal size distributions: Constant vs. proportionate growth

USGS Publications Warehouse

Eberl, D.D.; Kile, D.E.; Drits, V.A.

2002-01-01

Geological interpretations of crystal size distributions (CSDs) depend on understanding the crystal growth laws that generated the distributions. Most descriptions of crystal growth, including a population-balance modeling equation that is widely used in petrology, assume that crystal growth rates at any particular time are identical for all crystals, and, therefore, independent of crystal size. This type of growth under constant conditions can be modeled by adding a constant length to the diameter of each crystal for each time step. This growth equation is unlikely to be correct for most mineral systems because it neither generates nor maintains the shapes of lognormal CSDs, which are among the most common types of CSDs observed in rocks. In an alternative approach, size-dependent (proportionate) growth is modeled approximately by multiplying the size of each crystal by a factor, an operation that maintains CSD shape and variance, and which is in accord with calcite growth experiments. The latter growth law can be obtained during supply controlled growth using a modified version of the Law of Proportionate Effect (LPE), an equation that simulates the reaction path followed by a CSD shape as mean size increases.

Detection of periimplant fenestration and dehiscence with the use of two scan modes and the smallest voxel sizes of a cone-beam computed tomography device.

PubMed

de-Azevedo-Vaz, Sergio Lins; Vasconcelos, Karla de Faria; Neves, Frederico Sampaio; Melo, Saulo Leonardo Sousa; Campos, Paulo Sérgio Flores; Haiter-Neto, Francisco

2013-01-01

To assess the accuracy of cone-beam computed tomography (CBCT) in periimplant fenestration and dehiscence detection, and to determine the effects of 2 voxel sizes and scan modes. One hundred titanium implants were placed in bovine ribs in which periimplant fenestration and dehiscence were simulated. CBCT images were acquired with the use of 3 protocols of the i-CAT NG unit: A) 0.2 mm voxel size half-scan (180°); B) 0.2 mm voxel size full-scan (360°); and C) 0.12 mm voxel size full scan (360°). Receiver operating characteristic curves and diagnostic values were obtained. The Az values were compared with the use of analysis of variance. The Az value for dehiscence in protocol A was significantly lower than those of B or C (P < .01). They did not statistically differ for fenestration (P > .05). Protocol B yielded the highest values. The voxel sizes did not affect fenestration and dehiscence detection, and for dehiscence full-scan performed better than half-scan. Copyright © 2013 Elsevier Inc. All rights reserved.

Remote sensing of floe size distribution and surface topography

NASA Technical Reports Server (NTRS)

Rothrock, D. A.; Thorndike, A. S.

1984-01-01

Floe size can be measured by several properties p- for instance, area or mean caliper diameter. Two definitions of floe size distribution seem particularly useful. F(p), the fraction of area covered by floes no smaller than p; and N(p), the number of floes per unit area no smaller than p. Several summertime distributions measured are a graph, their slopes range from -1.7 to -2.5. The variance of an estimate is also calculated.

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

PubMed

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

2016-11-20

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

Moments of catchment storm area

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Wang, Q.

1985-01-01

The portion of a catchment covered by a stationary rainstorm is modeled by the common area of two overlapping circles. Given that rain occurs within the catchment and conditioned by fixed storm and catchment sizes, the first two moments of the distribution of the common area are derived from purely geometrical considerations. The variance of the wetted fraction is shown to peak when the catchment size is equal to the size of the predominant storm. The conditioning on storm size is removed by assuming a probability distribution based upon the observed fractal behavior of cloud and rainstorm areas.

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Does Self-Control Training Improve Self-Control? A Meta-Analysis.

PubMed

Friese, Malte; Frankenbach, Julius; Job, Veronika; Loschelder, David D

2017-11-01

Self-control is positively associated with a host of beneficial outcomes. Therefore, psychological interventions that reliably improve self-control are of great societal value. A prominent idea suggests that training self-control by repeatedly overriding dominant responses should lead to broad improvements in self-control over time. Here, we conducted a random-effects meta-analysis based on robust variance estimation of the published and unpublished literature on self-control training effects. Results based on 33 studies and 158 effect sizes revealed a small-to-medium effect of g = 0.30, confidence interval (CI 95 ) [0.17, 0.42]. Moderator analyses found that training effects tended to be larger for (a) self-control stamina rather than strength, (b) studies with inactive compared to active control groups, (c) males than females, and (d) when proponents of the strength model of self-control were (co)authors of a study. Bias-correction techniques suggested the presence of small-study effects and/or publication bias and arrived at smaller effect size estimates (range: g corrected = .13 to .24). The mechanisms underlying the effect are poorly understood. There is not enough evidence to conclude that the repeated control of dominant responses is the critical element driving training effects.

The effect of caster wheel diameter and mass distribution on drag forces in manual wheelchairs.

PubMed

Zepeda, Rene; Chan, Franco; Sawatzky, Bonita

2016-01-01

This study proposes a way to reduce energy losses in the form of rolling resistance friction during manual wheelchair propulsion by increasing the size of the front caster wheels and adjusting the weight distribution. Drag tests were conducted using a treadmill and a force transducer. Three different casters diameter (4 in., 5 in., and 6 in.) and six different mass distribution combinations (based on percentage of total weight on the caster wheels) were studied. A two-way analysis of variance test was performed to compare caster size and weight distribution contribution with drag force of an ultralight wheelchair. The 4 in. caster contributed significantly more drag, but only when weight was 40% or greater over the casters. Weight distribution contributed more to drag regardless of the casters used.

Governing board structure, business strategy, and performance of acute care hospitals: a contingency perspective.

PubMed Central

Young, G; Beekun, R I; Ginn, G O

1992-01-01

Contingency theory suggests that for a hospital governing board to be effective in taking on a more active role in strategic management, the board needs to be structured to complement the overall strategy of the organization. A survey study was conducted to examine the strategies of acute care hospitals as related to the structural characteristics of their governing boards. After controlling for organizational size and system membership, results indicated a significant relationship between the governing board structure of 109 acute care hospitals and their overall business strategy. Strategy also accounted for more of the variance in board structure than either organization size or system membership. Finally, the greater the match between board structure and hospital strategy, the stronger the hospitals' financial performance. PMID:1399656

Free space optical communication using beam parameters with translational and transverse rotational invariance.

PubMed

Ivan, J Solomon; Goswami, Kaumudibikash

2015-06-01

Two natural requirements on a measurable quantity possessed by a paraxially propagating light-field to be suitable for free space optical communication are invariance under free space propagation and invariance under transverse plane rotation. While the former invariance ensures that the measurable quantity is robust while signalling through free space, the latter invariance ensures that a detector measuring the quantity can be oriented at any angle in the transverse plane, and a measurement by the detector yields the same value for the quantity irrespective of the transverse angle, thus avoiding alignment issues. The variance matrix of a paraxially propagating light-field is analyzed from the perspective of the aforementioned invariances. That the "charge" of a paraxial light-field, which is contained in the variance matrix, and which has been previously well studied for its suitability toward free space optical communication, possesses these two invariance properties, emerges naturally in the analysis. Seven functionally independent quantities other than charge, which are derived from the variance matrix, and which share these invariances, are presented and studied for their suitability toward signalling through turbulent atmosphere using the low-order Hermite-Gaussian modes. It is found that the spot size of a Gaussian light-field can be effectively used as a switch, to communicate through short distances in a turbulent atmosphere.

Amplitude Scintillation due to Atmospheric Turbulence for the Deep Space Network Ka-Band Downlink

NASA Technical Reports Server (NTRS)

Ho, C.; Wheelon, A.

2004-01-01

Fast amplitude variations due to atmospheric scintillation are the main concerns for the Deep Space Network (DSN) Ka-band downlink under clear weather conditions. A theoretical study of the amplitude scintillation variances for a finite aperture antenna is presented. Amplitude variances for weak scattering scenarios are examined using turbulence theory to describe atmospheric irregularities. We first apply the Kolmogorov turbulent spectrum to a point receiver for three different turbulent profile models, especially for an exponential model varying with altitude. These analytic solutions then are extended to a receiver with a finite aperture antenna for the three profile models. Smoothing effects of antenna aperture are expressed by gain factors. A group of scaling factor relations is derived to show the dependences of amplitude variances on signal wavelength, antenna size, and elevation angle. Finally, we use these analytic solutions to estimate the scintillation intensity for a DSN Goldstone 34-m receiving station. We find that the (rms) amplitude fluctuation is 0.13 dB at 20-deg elevation angle for an exponential model, while the fluctuation is 0.05 dB at 90 deg. These results will aid us in telecommunication system design and signal-fading prediction. They also provide a theoretical basis for further comparison with other measurements at Ka-band.

The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

PubMed Central

Lohmueller, Kirk E.

2014-01-01

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation's effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation's effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits. PMID:24875776

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Improvement in Self-reported Quality of Life with Cognitive Therapy for Recurrent Major Depressive Disorder

PubMed Central

Jha, Manish Kumar; Minhajuddin, Abu; Thase, Michael E.; Jarrett, Robin B.

2014-01-01

Background Major Depressive Disorder is common, often recurrent and/or chronic. Theoretically, assessing quality of life (QoL) in addition to the current practice of assessing depressive symptoms has the potential to offer a more comprehensive evaluation of the effects of treatment interventions and course of illness. Methods Before and after acute-phase cognitive therapy (CT), 492 patients from Continuation Phase Cognitive Therapy Relapse Prevention trial (Jarrett et al., 2013, Jarrett and Thase, 2010) completed the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), Inventory of Depressive Symptomatology Self-report (IDS-SR) & Beck Depression Inventory (BDI); clinicians completed Hamilton Rating Scale for Depression-17-items. Repeated measures analysis of variance evaluated the improvement in QoL before/after CT and measured the effect sizes. Change analyses to assess clinical significance (Hageman and Arrindell, 1999) were conducted. Results At the end of acute-phase CT, a repeated measure analysis of variance produced a statistically significant increase in Q-LES-Q scores with effect sizes of 0.48 - 1.3; 76.9 - 91.4% patients reported clinically significant improvement. Yet, only 11 - 38.2% QoL scores normalized. An analysis of covariance showed that change in depression severity (covariates=IDS-SR, BDI) completely accounted for the improvement in Q-LES-Q scores. Limitations There were only two time points of observation; clinically significant change analyses lacked matched normal controls; and generalizability is constrained by sampling characteristics. Conclusions: Quality of life improves significantly in patients with recurrent MDD after CT; however, this improvement is completely accounted for by change in depression severity. Normalization of QoL in all patients may require targeted, additional, and/or longer treatment. PMID:25082112

Improvement in self-reported quality of life with cognitive therapy for recurrent major depressive disorder.

PubMed

Jha, Manish Kumar; Minhajuddin, Abu; Thase, Michael E; Jarrett, Robin B

2014-01-01

Major depressive disorder (MDD) is common, often recurrent and/or chronic. Theoretically, assessing quality of life (QoL) in addition to the current practice of assessing depressive symptoms has the potential to offer a more comprehensive evaluation of the effects of treatment interventions and course of illness. Before and after acute-phase cognitive therapy (CT), 492 patients from Continuation Phase Cognitive Therapy Relapse Prevention trial (Jarrett et al., 2013; Jarrett and Thase, 2010) completed the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), Inventory of Depressive Symptomatology Self-report (IDS-SR) and Beck Depression Inventory (BDI); clinicians completed Hamilton Rating Scale for Depression-17-items. Repeated measures analysis of variance evaluated the improvement in QoL before/after CT and measured the effect sizes. Change analyses to assess clinical significance (Hageman and Arrindell, 1999) were conducted. At the end of acute-phase CT, a repeated measure analysis of variance produced a statistically significant increase in Q-LES-Q scores with effect sizes of 0.48-1.3%; 76.9-91.4% patients reported clinically significant improvement. Yet, only 11-38.2% QoL scores normalized. An analysis of covariance showed that change in depression severity (covariates=IDS-SR, BDI) completely accounted for the improvement in Q-LES-Q scores. There were only two time points of observation; clinically significant change analyses lacked matched normal controls; and generalizability is constrained by sampling characteristics. Quality of life improves significantly in patients with recurrent MDD after CT; however, this improvement is completely accounted for by change in depression severity. Normalization of QoL in all patients may require targeted, additional, and/or longer treatment. Copyright © 2014 Elsevier B.V. All rights reserved.

Exact results in the large system size limit for the dynamics of the chemical master equation, a one dimensional chain of equations.

PubMed

Martirosyan, A; Saakian, David B

2011-08-01

We apply the Hamilton-Jacobi equation (HJE) formalism to solve the dynamics of the chemical master equation (CME). We found exact analytical expressions (in large system-size limit) for the probability distribution, including explicit expression for the dynamics of variance of distribution. We also give the solution for some simple cases of the model with time-dependent rates. We derived the results of the Van Kampen method from the HJE approach using a special ansatz. Using the Van Kampen method, we give a system of ordinary differential equations (ODEs) to define the variance in a two-dimensional case. We performed numerics for the CME with stationary noise. We give analytical criteria for the disappearance of bistability in the case of stationary noise in one-dimensional CMEs.

A model-based approach to sample size estimation in recent onset type 1 diabetes.

PubMed

Bundy, Brian N; Krischer, Jeffrey P

2016-11-01

The area under the curve C-peptide following a 2-h mixed meal tolerance test from 498 individuals enrolled on five prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrolment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors, and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in observed versus expected calculations to estimate the presumption of benefit in ongoing trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Propagation of electromagnetic waves in a turbulent medium

NASA Technical Reports Server (NTRS)

Canuto, V. M.; Hartke, G. J.

1986-01-01

Theoretical modeling of the wealth of experimental data on propagation of electromagnetic radiation through turbulent media has centered on the use of the Heisenberg-Kolmogorov (HK) model, which is, however, valid only for medium to small sized eddies. Ad hoc modifications of the HK model to encompass the large-scale region of the eddy spectrum have been widely used, but a sound physical basis has been lacking. A model for large-scale turbulence that was recently proposed is applied to the above problem. The spectral density of the temperature field is derived and used to calculate the structure function of the index of refraction N. The result is compared with available data, yielding a reasonably good fit. The variance of N is also in accord with the data. The model is also applied to propagation effects. The phase structure function, covariance of the log amplitude, and variance of the log intensity are calculated. The calculated phase structure function is in excellent agreement with available data.

Genetic Engineering of Optical Properties of Biomaterials

NASA Astrophysics Data System (ADS)

Gourley, Paul; Naviaux, Robert; Yaffe, Michael

2008-03-01

Baker's yeast cells are easily cultured and can be manipulated genetically to produce large numbers of bioparticles (cells and mitochondria) with controllable size and optical properties. We have recently employed nanolaser spectroscopy to study the refractive index of individual cells and isolated mitochondria from two mutant strains. Results show that biomolecular changes induced by mutation can produce bioparticles with radical changes in refractive index. Wild-type mitochondria exhibit a distribution with a well-defined mean and small variance. In striking contrast, mitochondria from one mutant strain produced a histogram that is highly collapsed with a ten-fold decrease in the mean and standard deviation. In a second mutant strain we observed an opposite effect with the mean nearly unchanged but the variance increased nearly a thousand-fold. Both histograms could be self-consistently modeled with a single, log-normal distribution. The strains were further examined by 2-dimensional gel electrophoresis to measure changes in protein composition. All of these data show that genetic manipulation of cells represents a new approach to engineering optical properties of bioparticles.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

The effect of size and competition on tree growth rate in old-growth coniferous forests

USGS Publications Warehouse

Das, Adrian

2012-01-01

Tree growth and competition play central roles in forest dynamics. Yet models of competition often neglect important variation in species-specific responses. Furthermore, functions used to model changes in growth rate with size do not always allow for potential complexity. Using a large data set from old-growth forests in California, models were parameterized relating growth rate to tree size and competition for four common species. Several functions relating growth rate to size were tested. Competition models included parameters for tree size, competitor size, and competitor distance. Competitive strength was allowed to vary by species. The best ranked models (using Akaike’s information criterion) explained between 18% and 40% of the variance in growth rate, with each species showing a strong response to competition. Models indicated that relationships between competition and growth varied substantially among species. The results also suggested that the relationship between growth rate and tree size can be complex and that how we model it can affect not only our ability to detect that complexity but also whether we obtain misleading results. In this case, for three of four species, the best model captured an apparent and unexpected decline in potential growth rate for the smallest trees in the data set.

Variance in prey abundance influences time budgets of breeding seabirds: Evidence from pigeon guillemots Cepphus columba

USGS Publications Warehouse

Litzow, Michael A.; Piatt, John F.

2003-01-01

We use data on pigeon guillemots Cepphus columba to test the hypothesis that discretionary time in breeding seabirds is correlated with variance in prey abundance. We measured the amount of time that guillemots spent at the colony before delivering fish to chicks ("resting time") in relation to fish abundance as measured by beach seines and bottom trawls. Radio telemetry showed that resting time was inversely correlated with time spent diving for fish during foraging trips (r = -0.95). Pigeon guillemots fed their chicks either Pacific sand lance Ammodytes hexapterus, a schooling midwater fish, which exhibited high interannual variance in abundance (CV = 181%), or a variety of non-schooling demersal fishes, which were less variable in abundance (average CV = 111%). Average resting times were 46% higher at colonies where schooling prey dominated the diet. Individuals at these colonies reduced resting times 32% during years of low food abundance, but did not reduce meal delivery rates. In contrast, individuals feeding on non-schooling fishes did not reduce resting times during low food years, but did reduce meal delivery rates by 27%. Interannual variance in resting times was greater for the schooling group than for the non-schooling group. We conclude from these differences that time allocation in pigeon guillemots is more flexible when variable schooling prey dominate diets. Resting times were also 27% lower for individuals feeding two-chick rather than one-chick broods. The combined effects of diet and brood size on adult time budgets may help to explain higher rates of brood reduction for pigeon guillemot chicks fed non-schooling fishes.

Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.

PubMed

Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M

2016-11-01

Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

PubMed

Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

2014-09-01

Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Evaluating Effect of Albendazole on Trichuris trichiura Infection: A Systematic Review Article.

PubMed

Ahmadi Jouybari, Toraj; Najaf Ghobadi, Khadije; Lotfi, Bahare; Alavi Majd, Hamid; Ahmadi, Nayeb Ali; Rostami-Nejad, Mohammad; Aghaei, Abbas

2016-01-01

The aim of the study was assessment of defaults and conducted meta-analysis of the efficacy of single-dose oral albendazole against T. trichiura infection. We searched PubMed, ISI Web of Science, Science Direct, the Cochrane Central Register of Controlled Trials, and WHO library databases between 1983 and 2014. Data from 13 clinical trial articles were used. Each article was included the effect of single oral dose (400 mg) albendazole and placebo in treating two groups of patients with T. trichiura infection. For both groups in each article, sample size, the number of those with T. trichiura infection, and the number of those recovered following the intake of albendazole were identified and recorded. The relative risk and variance were computed. Funnel plot, Beggs and Eggers tests were used for assessment of publication bias. The random effect variance shift outlier model and likelihood ratio test were applied for detecting outliers. In order to detect influence, DFFITS values, Cook's distances and COVRATIO were used. Data were analyzed using STATA and R software. The article number 13 and 9 were outlier and influence, respectively. Outlier is diagnosed by variance shift of target study in inferential method and by RR value in graphical method. Funnel plot and Beggs test did not show the publication bias ( P =0.272). However, the Eggers test confirmed it ( P =0.034). Meta-analysis after removal of article 13 showed that relative risk was 1.99 (CI 95% 1.71 - 2.31). The estimated RR and our meta-analyses show that treatment of T. trichiura with single oral doses of albendazole is unsatisfactory. New anthelminthics are urgently needed.

PDF-based heterogeneous multiscale filtration model.

PubMed

Gong, Jian; Rutland, Christopher J

2015-04-21

Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.

On the relationship between ontogenetic and static allometry.

PubMed

Pélabon, Christophe; Bolstad, Geir H; Egset, Camilla K; Cheverud, James M; Pavlicev, Mihaela; Rosenqvist, Gunilla

2013-02-01

Ontogenetic and static allometries describe how a character changes in size when the size of the organism changes during ontogeny and among individuals measured at the same developmental stage, respectively. Understanding the relationship between these two types of allometry is crucial to understanding the evolution of allometry and, more generally, the evolution of shape. However, the effects of ontogenetic allometry on static allometry remain largely unexplored. Here, we first show analytically how individual variation in ontogenetic allometry and body size affect static allometry. Using two longitudinal data sets on ontogenetic and static allometry, we then estimate variances and covariances for the different parameters of the ontogenetic allometry defined in our model and assess their relative contribution to the static allometric slope. The mean ontogenetic allometry is the main parameter that determines the static allometric slope, while the covariance between the ontogenetic allometric slope and body size generates most of the discrepancies between ontogenetic and static allometry. These results suggest that the apparent evolutionary stasis of the static allometric slope is not generated by internal (developmental) constraints but more likely results from external constraints imposed by selection.

Does catch and release affect the mating system and individual reproductive success of wild Atlantic salmon (Salmo salar L.)?

PubMed

Richard, Antoine; Dionne, Mélanie; Wang, Jinliang; Bernatchez, Louis

2013-01-01

In this study, we documented the breeding system of a wild population of Atlantic salmon (Salmo salar L.) by genetically sampling every returning adult and assessed the determinants of individual fitness. We then quantified the impacts of catch and release (C&R) on mating and reproductive success. Both sexes showed high variance in individual reproductive success, and the estimated standardized variance was higher for males (2.86) than for females (0.73). We found a weak positive relationship between body size and fitness and observed that fitness was positively correlated with the number of mates, especially in males. Mature male parr sired 44% of the analysed offspring. The impact of C&R on the number of offspring was size dependent, as the reproductive success of larger fish was more impaired than smaller ones. Also, there was an interactive negative effect of water temperature and air exposure time on reproductive success of C&R salmon. This study improves our understanding of the complex reproductive biology of the Atlantic salmon and is the first to investigate the impact of C&R on reproductive success. Our study expands the management toolbox of appropriate C&R practices that promote conservation of salmon populations and limit negative impacts on mating and reproductive success. © 2012 Blackwell Publishing Ltd.

Technical Guidance for Conducting ASVAB Validation/Standards Studies in the U.S. Navy

DTIC Science & Technology

2015-02-01

the criterion), we can compute the variance of X in the unrestricted group, 2xS , and in the restricted (selected) group, 2 xs . 3 In contrast, we...well as the selected group, 2 xs . We also know the variance of Y in the selected group, 2ys , and the correlation of X and Y in the selected...and AS. Five levels of selection ratio (1.0, .8, .6, .4, and .2) and eight sample sizes (50, 75, 100, 150, 225, 350 , 500, and 800) were considered

A Generalized DIF Effect Variance Estimator for Measuring Unsigned Differential Test Functioning in Mixed Format Tests

ERIC Educational Resources Information Center

Penfield, Randall D.; Algina, James

2006-01-01

One approach to measuring unsigned differential test functioning is to estimate the variance of the differential item functioning (DIF) effect across the items of the test. This article proposes two estimators of the DIF effect variance for tests containing dichotomous and polytomous items. The proposed estimators are direct extensions of the…

Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects.

PubMed

Baird, Rachel; Maxwell, Scott E

2016-06-01

Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

29 CFR 1905.5 - Effect of variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Lifestyle factors and adolescent depressive symptomatology: Associations and effect sizes of diet, physical activity and sedentary behaviour.

PubMed

Hayward, Joshua; Jacka, Felice N; Skouteris, Helen; Millar, Lynne; Strugnell, Claudia; Swinburn, Boyd A; Allender, Steven

2016-11-01

Depression affects many Australian adolescents. Research points to the potential of lifestyle improvement for the population-level prevention of mental disorders. However, most studies examine single relationships without considering the combined contribution of lifestyle factors to variance in depression. This study examined associations between adolescent diet, physical activity and screen time behaviours and depressive symptomatology. A cross-sectional sample of year 8 and 10 students was recruited from 23 participating schools in 18 Victorian communities. Students were recruited using opt-out consent, resulting in 3295 participants from 4680 registered school enrolments (Participation Rate: 70.4%). Participants completed a supervised self-report questionnaire comprising Moods and Feelings Questionnaire-Short Form, an assessment of physical activity and sedentary behaviours during and outside school, and weekly food intake. Surveyed covariates included hours of sleep per night, age, socio-economic status and measured anthropometry. A hierarchical regression stratified by gender was conducted, with dichotomised Moods and Feelings Questionnaire-Short Form score as the outcome, and screen time, physical activity and dietary patterns as predictors. Nested regression analyses were then conducted to ascertain the variance in Moods and Feelings Questionnaire-Short Form score attributable to each significant predictor from the initial regression. Increased scores on an unhealthy dietary pattern (odds ratio = 1.18; 95% confidence interval = [1.07, 1.32]) and physical activity guideline attainment (0.91; [0.85, 0.97]) were associated with depressive symptomatology in males, while screen time guideline attainment (0.95; [0.91, 0.98]) was associated with depression in females. No association was observed between healthy diet pattern and Moods and Feelings Questionnaire-Short Form. Overall, effect sizes were generally small, and the regression model accounted for 5.22% of Moods and Feelings Questionnaire-Short Form variance. Gender-specific associations were observed between physical activity and both sedentary and dietary behaviours and depressive symptomatology among adolescents, although reverse causality cannot be refuted at this stage. Lifestyle behaviours may represent a modifiable target for the prevention of depressive symptomatology in adolescents. © The Royal Australian and New Zealand College of Psychiatrists 2016.

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

PubMed

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

2015-08-01

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

Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting

PubMed Central

Chan, Kwun Chuen Gary; Yam, Sheung Chi Phillip; Zhang, Zheng

2015-01-01

Summary The estimation of average treatment effects based on observational data is extremely important in practice and has been studied by generations of statisticians under different frameworks. Existing globally efficient estimators require non-parametric estimation of a propensity score function, an outcome regression function or both, but their performance can be poor in practical sample sizes. Without explicitly estimating either functions, we consider a wide class calibration weights constructed to attain an exact three-way balance of the moments of observed covariates among the treated, the control, and the combined group. The wide class includes exponential tilting, empirical likelihood and generalized regression as important special cases, and extends survey calibration estimators to different statistical problems and with important distinctions. Global semiparametric efficiency for the estimation of average treatment effects is established for this general class of calibration estimators. The results show that efficiency can be achieved by solely balancing the covariate distributions without resorting to direct estimation of propensity score or outcome regression function. We also propose a consistent estimator for the efficient asymptotic variance, which does not involve additional functional estimation of either the propensity score or the outcome regression functions. The proposed variance estimator outperforms existing estimators that require a direct approximation of the efficient influence function. PMID:27346982

Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting.

PubMed

Chan, Kwun Chuen Gary; Yam, Sheung Chi Phillip; Zhang, Zheng

2016-06-01

The estimation of average treatment effects based on observational data is extremely important in practice and has been studied by generations of statisticians under different frameworks. Existing globally efficient estimators require non-parametric estimation of a propensity score function, an outcome regression function or both, but their performance can be poor in practical sample sizes. Without explicitly estimating either functions, we consider a wide class calibration weights constructed to attain an exact three-way balance of the moments of observed covariates among the treated, the control, and the combined group. The wide class includes exponential tilting, empirical likelihood and generalized regression as important special cases, and extends survey calibration estimators to different statistical problems and with important distinctions. Global semiparametric efficiency for the estimation of average treatment effects is established for this general class of calibration estimators. The results show that efficiency can be achieved by solely balancing the covariate distributions without resorting to direct estimation of propensity score or outcome regression function. We also propose a consistent estimator for the efficient asymptotic variance, which does not involve additional functional estimation of either the propensity score or the outcome regression functions. The proposed variance estimator outperforms existing estimators that require a direct approximation of the efficient influence function.

Genetic drift and collective dispersal can result in chaotic genetic patchiness.

PubMed

Broquet, Thomas; Viard, Frédérique; Yearsley, Jonathan M

2013-06-01

Chaotic genetic patchiness denotes unexpected patterns of genetic differentiation that are observed at a fine scale and are not stable in time. These patterns have been described in marine species with free-living larvae, but are unexpected because they occur at a scale below the dispersal range of pelagic larvae. At the scale where most larvae are immigrants, theory predicts spatially homogeneous, temporally stable genetic variation. Empirical studies have suggested that genetic drift interacts with complex dispersal patterns to create chaotic genetic patchiness. Here we use a co-ancestry model and individual-based simulations to test this idea. We found that chaotic genetic patterns (qualified by global FST and spatio-temporal variation in FST's between pairs of samples) arise from the combined effects of (1) genetic drift created by the small local effective population sizes of the sessile phase and variance in contribution among breeding groups and (2) collective dispersal of related individuals in the larval phase. Simulations show that patchiness levels qualitatively comparable to empirical results can be produced by a combination of strong variance in reproductive success and mild collective dispersal. These results call for empirical studies of the effective number of breeders producing larval cohorts, and population genetics at the larval stage. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

High-resolution Monte Carlo simulation of flow and conservative transport in heterogeneous porous media: 1. Methodology and flow results

USGS Publications Warehouse

Naff, R.L.; Haley, D.F.; Sudicky, E.A.

1998-01-01

In this, the first of two papers concerned with the use of numerical simulation to examine flow and transport parameters in heterogeneous porous media via Monte Carlo methods, various aspects of the modelling effort are examined. In particular, the need to save on core memory causes one to use only specific realizations that have certain initial characteristics; in effect, these transport simulations are conditioned by these characteristics. Also, the need to independently estimate length scales for the generated fields is discussed. The statistical uniformity of the flow field is investigated by plotting the variance of the seepage velocity for vector components in the x, y, and z directions. Finally, specific features of the velocity field itself are illuminated in this first paper. In particular, these data give one the opportunity to investigate the effective hydraulic conductivity in a flow field which is approximately statistically uniform; comparisons are made with first- and second-order perturbation analyses. The mean cloud velocity is examined to ascertain whether it is identical to the mean seepage velocity of the model. Finally, the variance in the cloud centroid velocity is examined for the effect of source size and differing strengths of local transverse dispersion.

Comparison of random regression test-day models for Polish Black and White cattle.

PubMed

Strabel, T; Szyda, J; Ptak, E; Jamrozik, J

2005-10-01

Test-day milk yields of first-lactation Black and White cows were used to select the model for routine genetic evaluation of dairy cattle in Poland. The population of Polish Black and White cows is characterized by small herd size, low level of production, and relatively early peak of lactation. Several random regression models for first-lactation milk yield were initially compared using the "percentage of squared bias" criterion and the correlations between true and predicted breeding values. Models with random herd-test-date effects, fixed age-season and herd-year curves, and random additive genetic and permanent environmental curves (Legendre polynomials of different orders were used for all regressions) were chosen for further studies. Additional comparisons included analyses of the residuals and shapes of variance curves in days in milk. The low production level and early peak of lactation of the breed required the use of Legendre polynomials of order 5 to describe age-season lactation curves. For the other curves, Legendre polynomials of order 3 satisfactorily described daily milk yield variation. Fitting third-order polynomials for the permanent environmental effect made it possible to adequately account for heterogeneous residual variance at different stages of lactation.

Pluck or Luck: Does Trait Variation or Chance Drive Variation in Lifetime Reproductive Success?

PubMed

Snyder, Robin E; Ellner, Stephen P

2018-04-01

While there has been extensive interest in how intraspecific trait variation affects ecological processes, outcomes are highly variable even when individuals are identical: some are lucky, while others are not. Trait variation is therefore important only if it adds substantially to the variability produced by luck. We ask when trait variation has a substantial effect on variability in lifetime reproductive success (LRS), using two approaches: (1) we partition the variation in LRS into contributions from luck and trait variation and (2) we ask what can be inferred about an individual's traits and with what certainty, given their observed LRS. In theoretical stage- and size-structured models and two empirical case studies, we find that luck usually dominates the variance of LRS. Even when individuals differ substantially in ways that affect expected LRS, unless the effects of luck are substantially reduced (e.g., low variability in reproductive life span or annual fecundity), most variance in lifetime outcomes is due to luck, implying that departures from "null" models omitting trait variation will be hard to detect. Luck also obscures the relationship between realized LRS and individual traits. While trait variation may influence the fate of populations, luck often governs the lives of individuals.

Processing speed and visuospatial executive function predict visual working memory ability in older adults.

PubMed

Brown, Louise A; Brockmole, James R; Gow, Alan J; Deary, Ian J

2012-01-01

BACKGROUND/STUDY CONTEXT: Visual working memory (VWM) has been shown to be particularly age sensitive. Determining which measures share variance with this cognitive ability in older adults may help to elucidate the key factors underlying the effects of aging. Predictors of VWM (measured by a modified Visual Patterns Test) were investigated in a subsample (N = 44, mean age = 73) of older adults from the Lothian Birth Cohort 1936 (LBC1936; Deary et al., 2007 , BMC Geriatrics, 7, 28). Childhood intelligence (Moray House Test) and contemporaneous measures of processing speed (four-choice reaction time), executive function (verbal fluency; block design), and spatial working memory (backward spatial span), were assessed as potential predictors. All contemporaneous measures except verbal fluency were significantly associated with VWM, and processing speed had the largest effect size (r = -.53, p < .001). In linear regression analysis, even after adjusting for childhood intelligence, processing speed and the executive measure associated with visuospatial organization accounted for 35% of the variance in VWM. Processing speed may affect VWM performance in older adults via speed of encoding and/or rate of rehearsal, while executive resources specifically associated with visuospatial material are also important.

Point and interval estimation of pollinator importance: a study using pollination data of Silene caroliniana.

PubMed

Reynolds, Richard J; Fenster, Charles B

2008-05-01

Pollinator importance, the product of visitation rate and pollinator effectiveness, is a descriptive parameter of the ecology and evolution of plant-pollinator interactions. Naturally, sources of its variation should be investigated, but the SE of pollinator importance has never been properly reported. Here, a Monte Carlo simulation study and a result from mathematical statistics on the variance of the product of two random variables are used to estimate the mean and confidence limits of pollinator importance for three visitor species of the wildflower, Silene caroliniana. Both methods provided similar estimates of mean pollinator importance and its interval if the sample size of the visitation and effectiveness datasets were comparatively large. These approaches allowed us to determine that bumblebee importance was significantly greater than clearwing hawkmoth, which was significantly greater than beefly. The methods could be used to statistically quantify temporal and spatial variation in pollinator importance of particular visitor species. The approaches may be extended for estimating the variance of more than two random variables. However, unless the distribution function of the resulting statistic is known, the simulation approach is preferable for calculating the parameter's confidence limits.

Is there a general task switching ability?

PubMed

Yehene, Einat; Meiran, Nachshon

2007-11-01

Participants were tested on two analogous task switching paradigms involving Shape/Size tasks and Vertical/Horizontal tasks, respectively, and three measures of psychometric intelligence, tapping fluid, crystallized and perceptual speed abilities. The paradigms produced similar patterns of group mean reaction times (RTs) and the vast majority of the participants showed switching cost (switch RT minus repeat RT), mixing cost (repeat RT minus single-task RT) and congruency effects. The shared intra-individual variance across paradigms and with psychometric intelligence served as criteria for general ability. Structural equations modeling indicated that switching cost with ample preparation ("residual cost") and mixing cost met these criteria. However, switching cost with little preparation and congruency effects were predominantly paradigm specific.

Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis.

PubMed

Saviane, Chiara; Silver, R Angus

2006-06-15

Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.

Verbal Working Memory in Children With Cochlear Implants

PubMed Central

Caldwell-Tarr, Amanda; Low, Keri E.; Lowenstein, Joanna H.

2017-01-01

Purpose Verbal working memory in children with cochlear implants and children with normal hearing was examined. Participants Ninety-three fourth graders (47 with normal hearing, 46 with cochlear implants) participated, all of whom were in a longitudinal study and had working memory assessed 2 years earlier. Method A dual-component model of working memory was adopted, and a serial recall task measured storage and processing. Potential predictor variables were phonological awareness, vocabulary knowledge, nonverbal IQ, and several treatment variables. Potential dependent functions were literacy, expressive language, and speech-in-noise recognition. Results Children with cochlear implants showed deficits in storage and processing, similar in size to those at second grade. Predictors of verbal working memory differed across groups: Phonological awareness explained the most variance in children with normal hearing; vocabulary explained the most variance in children with cochlear implants. Treatment variables explained little of the variance. Where potentially dependent functions were concerned, verbal working memory accounted for little variance once the variance explained by other predictors was removed. Conclusions The verbal working memory deficits of children with cochlear implants arise due to signal degradation, which limits their abilities to acquire phonological awareness. That hinders their abilities to store items using a phonological code. PMID:29075747

Crystallite-size dependency of the pressure and temperature response in nanoparticles of magnesia

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

Rodenbough, Philip P.; Chan, Siu-Wai

We have carefully measured the hydrostatic compressibility and thermal expansion for a series of magnesia nanoparticles. We found a strong variance in these mechanical properties as crystallite size changed. For decreasing crystallite sizes, bulk modulus first increased, then reached a modest maximum of 165 GPa at an intermediate crystallite size of 14 nm, and then decreased thereafter to 77 GPa at 9 nm. Thermal expansion, meanwhile, decreased continuously to 70% of bulk value at 9 nm. These results are consistent to nano-ceria and together provide important insights into the thermal-mechanical structural properties of oxide nanoparticles.

Evolutionary model of the growth and size of firms

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2012-07-01

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size-variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.

The effect of a finite focal spot size on location dependent detectability in a fan beam CT system

NASA Astrophysics Data System (ADS)

Kim, Byeongjoon; Baek, Jongduk

2017-03-01

A finite focal spot size is one of the sources to degrade the resolution performance in a fan beam CT system. In this work, we investigated the effect of the finite focal spot size on signal detectability. For the evaluation, five spherical objects with diameters of 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm were used. The optical focal spot size viewed at the iso-center was a 1 mm (height) × 1 mm (width) with a target angle of 7 degrees, corresponding to an 8.21 mm (i.e., 1 mm / sin (7°)) focal spot length. Simulated projection data were acquired using 8 × 8 source lets, and reconstructed by Hanning weighted filtered backprojection. For each spherical object, the detectability was calculated at (0 mm, 0 mm) and (0 mm, 200 mm) using two image quality metrics: pixel signal to noise ratio (SNR) and detection SNR. For all signal sizes, the pixel SNR is higher at the iso-center since the noise variance at the off-center is much higher than that at the iso-center due to the backprojection weightings used in direct fan beam reconstruction. In contrast, detection SNR shows similar values for different spherical objects except 1 mm and 2 mm diameter spherical objects. Overall, the results indicate the resolution loss caused by the finite focal spot size degrades the detection performance, especially for small objects with less than 2 mm diameter.

Health Science students' evaluation of courses and Instructors: the effect of response rate and class size interaction.

PubMed

Kuwaiti, Ahmed Al

2015-01-01

This study aims at investigating the effect of response rate and class size interaction on students' evaluation of instructors and the courses offered at heath science colleges in Saudi Arabia. A retrospective study design was adapted to ascertain Course Evaluation Surveys (CES) conducted at the health science colleges of the University of Dammam [UOD] in the academic year 2013-2014. Accordingly, the CES data which was downloaded from an exclusive online application 'UDQUEST' which includes 337 different courses and 15,264 surveys were utilized in this study. Two-way analysis of variance was utilized to test whether there is any significant interaction between the class size and the response rate on the students' evaluation of courses and instructors. The study showed that high response rate is required for student evaluation of instructors at Health Science colleges when the class size is small whereas a medium response rate is required for students' evaluation of courses. On the other hand, when the class size is medium, a medium or high response rate is needed for students' evaluation of both instructors and courses. The results of this study recommend that the administrators of the health science colleges to be aware of the interpretation of students' evaluations of courses and instructors. The study also suggests that the interaction between response rate and class size is a very important factor that needs to be taken into consideration while interpreting the findings of the students' evaluation of instructors and courses.

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; vanDiedenhove, Bastiaan

2012-01-01

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

The effects of plasma inhomogeneity on the nanoparticle coating in a low pressure plasma reactor

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

Pourali, N.; Foroutan, G.

2015-10-15

A self-consistent model is used to study the surface coating of a collection of charged nanoparticles trapped in the sheath region of a low pressure plasma reactor. The model consists of multi-fluid plasma sheath module, including nanoparticle dynamics, as well as the surface deposition and particle heating modules. The simulation results show that the mean particle radius increases with time and the nanoparticle size distribution is broadened. The mean radius is a linear function of time, while the variance exhibits a quadratic dependence. The broadening in size distribution is attributed to the spatial inhomogeneity of the deposition rate which inmore » turn depends on the plasma inhomogeneity. The spatial inhomogeneity of the ions has strong impact on the broadening of the size distribution, as the ions contribute both in the nanoparticle charging and in direct film deposition. The distribution width also increases with increasing of the pressure, gas temperature, and the ambient temperature gradient.« less

Mindfulness-based interventions with youth: A comprehensive meta-analysis of group-design studies.

PubMed

Klingbeil, David A; Renshaw, Tyler L; Willenbrink, Jessica B; Copek, Rebecca A; Chan, Kai Tai; Haddock, Aaron; Yassine, Jordan; Clifton, Jesse

2017-08-01

The treatment effects of Mindfulness-Based Interventions (MBIs) with youth were synthesized from 76 studies involving 6121 participants. A total of 885 effect sizes were aggregated using meta-regression with robust variance estimation. Overall, MBIs were associated with small treatment effects in studies using pre-post (g=0.305, SE=0.039) and controlled designs (g=0.322, SE=0.040). Treatment effects were measured after a follow-up period in 24 studies (n=1963). Results demonstrated that treatment effects were larger at follow-up than post-treatment in pre-post (g=0.462, SE=0.118) and controlled designs (g=0.402, SE=0.081). Moderator analyses indicated that intervention setting and intervention dosage were not meaningfully related to outcomes after controlling for study design quality. With that said, the between-study heterogeneity in the intercept-only models was consistently small, thus limiting the amount of variance for the moderators to explain. A series of exploratory analyses were used to investigate the differential effectiveness of MBIs across four therapeutic process domains and seven therapeutic outcome domains. Small, positive results were generally observed across the process and outcome domains. Notably, MBIs were associated with moderate effects on the process variable of mindfulness in controlled studies (n=1108, g=0.510). Limitations and directions for future research and practice are discussed. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

A method for the microlensed flux variance of QSOs

NASA Astrophysics Data System (ADS)

Goodman, Jeremy; Sun, Ai-Lei

2014-06-01

A fast and practical method is described for calculating the microlensed flux variance of an arbitrary source by uncorrelated stars. The required inputs are the mean convergence and shear due to the smoothed potential of the lensing galaxy, the stellar mass function, and the absolute square of the Fourier transform of the surface brightness in the source plane. The mathematical approach follows previous authors but has been generalized, streamlined, and implemented in publicly available code. Examples of its application are given for Dexter and Agol's inhomogeneous-disc models as well as the usual Gaussian sources. Since the quantity calculated is a second moment of the magnification, it is only logarithmically sensitive to the sizes of very compact sources. However, for the inferred sizes of actual quasi-stellar objects (QSOs), it has some discriminatory power and may lend itself to simple statistical tests. At the very least, it should be useful for testing the convergence of microlensing simulations.

The role of early stages of cortical visual processing in size and distance judgment: a transcranial direct current stimulation study.

PubMed

Costa, Thiago L; Costa, Marcelo F; Magalhães, Adsson; Rêgo, Gabriel G; Nagy, Balázs V; Boggio, Paulo S; Ventura, Dora F

2015-02-19

Recent research suggests that V1 plays an active role in the judgment of size and distance. Nevertheless, no research has been performed using direct brain stimulation to address this issue. We used transcranial direct-current stimulation (tDCS) to directly modulate the early stages of cortical visual processing while measuring size and distance perception with a psychophysical scaling method of magnitude estimation in a repeated-measures design. The subjects randomly received anodal, cathodal, and sham tDCS in separate sessions starting with size or distance judgment tasks. Power functions were fit to the size judgment data, whereas logarithmic functions were fit to distance judgment data. Slopes and R(2) were compared with separate repeated-measures analyses of variance with two factors: task (size vs. distance) and tDCS (anodal vs. cathodal vs. sham). Anodal tDCS significantly decreased slopes, apparently interfering with size perception. No effects were found for distance perception. Consistent with previous studies, the results of the size task appeared to reflect a prothetic continuum, whereas the results of the distance task seemed to reflect a metathetic continuum. The differential effects of tDCS on these tasks may support the hypothesis that different physiological mechanisms underlie judgments on these two continua. The results further suggest the complex involvement of the early visual cortex in size judgment tasks that go beyond the simple representation of low-level stimulus properties. This supports predictive coding models and experimental findings that suggest that higher-order visual areas may inhibit incoming information from the early visual cortex through feedback connections when complex tasks are performed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

[Blood-sugar self control. A means for the diabetic of controlling his metabolic management. Quality control of a battery-run pocket size reflectometer (glucose-meter)].

PubMed

Leidinger, F; Jörgens, V; Chantelau, E; Berchtold, P; Berger, M

1980-07-26

Home blood glucose monitoring by diabetic patients has recently been advocated as an effective means to improve metabolic control. The Glucocheck apparatus, a pocket-size battery-driven reflectance-meter (in Germany commercially available under the name Glucose-meter), has been evaluated for accuracy and practicability. In 450 blood glucose measurements, the variance between the values obtained using the Glucocheck apparatus and routine clinical laboratory procedures was +/- 11.7%. Especially in the low range of blood glucose concentrations, the Glucocheck method was very reliable. The quantitative precision of the Glucocheck method depends, however, quite considerably on the ability of the patient to use the apparatus correctly. In order to profit from Glucocheck in clinical practice, particular efforts to educate the patients in its use are necessary.

A Cosmic Variance Cookbook

NASA Astrophysics Data System (ADS)

Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

2011-04-01

Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is less serious.

Optimization of biostimulant for bioremediation of contaminated coastal sediment by response surface methodology (RSM) and evaluation of microbial diversity by pyrosequencing.

PubMed

Subha, Bakthavachallam; Song, Young Chae; Woo, Jung Hui

2015-09-15

The present study aims to optimize the slow release biostimulant ball (BSB) for bioremediation of contaminated coastal sediment using response surface methodology (RSM). Different bacterial communities were evaluated using a pyrosequencing-based approach in contaminated coastal sediments. The effects of BSB size (1-5cm), distance (1-10cm) and time (1-4months) on changes in chemical oxygen demand (COD) and volatile solid (VS) reduction were determined. Maximum reductions of COD and VS, 89.7% and 78.8%, respectively, were observed at a 3cm ball size, 5.5cm distance and 4months; these values are the optimum conditions for effective treatment of contaminated coastal sediment. Most of the variance in COD and VS (0.9291 and 0.9369, respectively) was explained in our chosen models. BSB is a promising method for COD and VS reduction and enhancement of SRB diversity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sex differences in the ability to recognise non-verbal displays of emotion: a meta-analysis.

PubMed

Thompson, Ashley E; Voyer, Daniel

2014-01-01

The present study aimed to quantify the magnitude of sex differences in humans' ability to accurately recognise non-verbal emotional displays. Studies of relevance were those that required explicit labelling of discrete emotions presented in the visual and/or auditory modality. A final set of 551 effect sizes from 215 samples was included in a multilevel meta-analysis. The results showed a small overall advantage in favour of females on emotion recognition tasks (d=0.19). However, the magnitude of that sex difference was moderated by several factors, namely specific emotion, emotion type (negative, positive), sex of the actor, sensory modality (visual, audio, audio-visual) and age of the participants. Method of presentation (computer, slides, print, etc.), type of measurement (response time, accuracy) and year of publication did not significantly contribute to variance in effect sizes. These findings are discussed in the context of social and biological explanations of sex differences in emotion recognition.

[No relationship between blood type and personality: evidence from large-scale surveys in Japan and the US].

PubMed

Nawata, Kengo

2014-06-01

Despite the widespread popular belief in Japan about a relationship between personality and ABO blood type, this association has not been empirically substantiated. This study provides more robust evidence that there is no relationship between blood type and personality, through a secondary analysis of large-scale survey data. Recent data (after 2000) were collected using large-scale random sampling from over 10,000 people in total from both Japan and the US. Effect sizes were calculated. Japanese datasets from 2004 (N = 2,878-2,938), and 2,005 (N = 3,618-3,692) as well as one dataset from the US in 2004 (N = 3,037-3,092) were used. In all the datasets, 65 of 68 items yielded non-significant differences between blood groups. Effect sizes (eta2) were less than .003. This means that blood type explained less than 0.3% of the total variance in personality. These results show the non-relevance of blood type for personality.

Derived variants at six genes explain nearly half of size reduction in dog breeds.

PubMed

Rimbault, Maud; Beale, Holly C; Schoenebeck, Jeffrey J; Hoopes, Barbara C; Allen, Jeremy J; Kilroy-Glynn, Paul; Wayne, Robert K; Sutter, Nathan B; Ostrander, Elaine A

2013-12-01

Selective breeding of dogs by humans has generated extraordinary diversity in body size. A number of multibreed analyses have been undertaken to identify the genetic basis of this diversity. We analyzed four loci discovered in a previous genome-wide association study that used 60,968 SNPs to identify size-associated genomic intervals, which were too large to assign causative roles to genes. First, we performed fine-mapping to define critical intervals that included the candidate genes GHR, HMGA2, SMAD2, and STC2, identifying five highly associated markers at the four loci. We hypothesize that three of the variants are likely to be causative. We then genotyped each marker, together with previously reported size-associated variants in the IGF1 and IGF1R genes, on a panel of 500 domestic dogs from 93 breeds, and identified the ancestral allele by genotyping the same markers on 30 wild canids. We observed that the derived alleles at all markers correlated with reduced body size, and smaller dogs are more likely to carry derived alleles at multiple markers. However, breeds are not generally fixed at all markers; multiple combinations of genotypes are found within most breeds. Finally, we show that 46%-52.5% of the variance in body size of dog breeds can be explained by seven markers in proximity to exceptional candidate genes. Among breeds with standard weights <41 kg (90 lb), the genotypes accounted for 64.3% of variance in weight. This work advances our understanding of mammalian growth by describing genetic contributions to canine size determination in non-giant dog breeds.

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.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.

PubMed

Bignardi, A B; El Faro, L; Cardoso, V L; Machado, P F; Albuquerque, L G

2009-09-01

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Moral values of only and sibling children in mainland China.

PubMed

Shen, J; Yuan, B J

1999-01-01

Seventh graders (N = 346) in Beijing and Shanghai were administered the Chinese Values Survey (M. H. Bond & the Chinese Culture Connection, 1987) and the Rokeach Values Survey (modified version; R. A. Cole, 1972) in 1992. Results showed no statistically significant difference in scores between only and sibling children who rated Chinese values and Rokeach terminal values. The 2 groups appeared to be significantly different in rating Rokeach instrumental values, but the effect sizes accounted for less than 2% of the variance. The stereotype of only children as being "spoiled" was not supported by the data.

Genetic and environmental variances of bone microarchitecture and bone remodeling markers: a twin study.

PubMed

Bjørnerem, Åshild; Bui, Minh; Wang, Xiaofang; Ghasem-Zadeh, Ali; Hopper, John L; Zebaze, Roger; Seeman, Ego

2015-03-01

All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p < 0.001). For the corresponding distal radius traits, genetic factors accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ  = 0.49) than DZ (rDZ  = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling markers more because of differences in their genetic factors than differences in their environment. © 2014 American Society for Bone and Mineral Research.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Twig-leaf size relationships in woody plants vary intraspecifically along a soil moisture gradient

NASA Astrophysics Data System (ADS)

Yang, Xiao-Dong; Yan, En-Rong; Chang, Scott X.; Wang, Xi-Hua; Zhao, Yan-Tao; Shi, Qing-Ru

2014-10-01

Understanding scaling relationships between twig size and leaf size along environmental gradients is important for revealing strategies of plant biomass allocation with changing environmental constraints. However, it remains poorly understood how variations in the slope and y-intercept in the twig-leaf size relationship partition among individual, population and species levels across communities. Here, we determined the scaling relationships between twig cross-sectional area (twig size) and total leaf area per twig (leaf size) among individual, population and species levels along a soil moisture gradient in subtropical forests in eastern China. Twig and leaf tissues from 95 woody plant species were collected from three sites that form a soil moisture gradient: a wet site (W), a mesophytic site (M), and a dry site (D). The variance in scaling slope and y-intercept was partitioned among individual, population and species levels using a nested ANOVA. In addition, the change in the twig-leaf size relationship over the soil moisture gradient was determined for each of overlapping and turnover species. Twig size was positively related to leaf size across the three levels, with the variance partitioned at the individual level in scaling slope and y-intercept being 98 and 90%, respectively. Along the soil moisture gradient, the twig-leaf size relationship differed inter- and intraspecifically. At the species and population levels, there were homogeneous slopes but the y-intercept was W > M = D. In contrast, at the individual level, the regression slopes were heterogeneous among the three sites. More remarkably, the twig-leaf size relationships changed from negative allometry for overlapping species to isometry for turnover species. This study provides strong evidence for the twig-leaf size relationship to be intraspecific, particularly at the individual level. Our findings suggest that whether or not species have overlapping habitats is crucial for shaping the deployment pattern between twigs and leaves.