Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation.

PubMed

Xia, Charley; Amador, Carmen; Huffman, Jennifer; Trochet, Holly; Campbell, Archie; Porteous, David; Hastie, Nicholas D; Hayward, Caroline; Vitart, Veronique; Navarro, Pau; Haley, Chris S

2016-02-01

Genome-wide association studies have successfully identified thousands of loci for a range of human complex traits and diseases. The proportion of phenotypic variance explained by significant associations is, however, limited. Given the same dense SNP panels, mixed model analyses capture a greater proportion of phenotypic variance than single SNP analyses but the total is generally still less than the genetic variance estimated from pedigree studies. Combining information from pedigree relationships and SNPs, we examined 16 complex anthropometric and cardiometabolic traits in a Scottish family-based cohort comprising up to 20,000 individuals genotyped for ~520,000 common autosomal SNPs. The inclusion of related individuals provides the opportunity to also estimate the genetic variance associated with pedigree as well as the effects of common family environment. Trait variation was partitioned into SNP-associated and pedigree-associated genetic variation, shared nuclear family environment, shared couple (partner) environment and shared full-sibling environment. Results demonstrate that trait heritabilities vary widely but, on average across traits, SNP-associated and pedigree-associated genetic effects each explain around half the genetic variance. For most traits the recently-shared environment of couples is also significant, accounting for ~11% of the phenotypic variance on average. On the other hand, the environment shared largely in the past by members of a nuclear family or by full-siblings, has a more limited impact. Our findings point to appropriate models to use in future studies as pedigree-associated genetic effects and couple environmental effects have seldom been taken into account in genotype-based analyses. Appropriate description of the trait variation could help understand causes of intra-individual variation and in the detection of contributing loci and environmental factors.

Shared versus distinct genetic contributions of mental wellbeing with depression and anxiety symptoms in healthy twins.

PubMed

Routledge, Kylie M; Burton, Karen L O; Williams, Leanne M; Harris, Anthony; Schofield, Peter R; Clark, C Richard; Gatt, Justine M

2016-10-30

Mental wellbeing and mental illness symptoms are typically conceptualized as opposite ends of a continuum, despite only sharing about a quarter in common variance. We investigated the normative variation in measures of wellbeing and of depression and anxiety in 1486 twins who did not meet clinical criteria for an overt diagnosis. We quantified the shared versus distinct genetic and environmental variance between wellbeing and depression and anxiety symptoms. The majority of participants (93%) reported levels of depression and anxiety symptoms within the healthy range, yet only 23% reported a wellbeing score within the "flourishing" range: the remainder were within the ranges of "moderate" (67%) or "languishing" (10%). In twin models, measures of wellbeing and of depression and anxiety shared 50.09% of variance due to genetic factors and 18.27% due to environmental factors; the rest of the variance was due to unique variation impacting wellbeing or depression and anxiety symptoms. These findings suggest that an absence of clinically-significant symptoms of depression and anxiety does not necessarily indicate that an individual is flourishing. Both unique and shared genetic and environmental factors may determine why some individuals flourish in the absence of symptoms while others do not. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Shared genetic variance between obesity and white matter integrity in Mexican Americans

PubMed Central

Spieker, Elena A.; Kochunov, Peter; Rowland, Laura M.; Sprooten, Emma; Winkler, Anderson M.; Olvera, Rene L.; Almasy, Laura; Duggirala, Ravi; Fox, Peter T.; Blangero, John; Glahn, David C.; Curran, Joanne E.

2015-01-01

Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m2) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h2 = 0.58), WC (h2 = 0.57), and FA (h2 = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors. PMID:25763009

Measuring the Relationship between Two Questionnaires: Appropriate Definitions of Intuitive Understandings

ERIC Educational Resources Information Center

Burt, Gordon

2005-01-01

A number of recent articles have claimed strong relationships--i.e., very high "proportions of shared variance"--between pairs of teaching and learning questionnaires. These claims have been the subject of debate and it has emerged that the proportion of shared variance is defined as the complement of Wilks' lambda. The present article argues that…

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins

PubMed Central

Silberg, Judy L.; Gillespie, Nathan; Moore, Ashlee A.; Eaves, Lindon J.; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-01-01

Objective Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. Method We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Results Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. Conclusions There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children. PMID:25728588

Education Modifies Genetic and Environmental Influences on BMI

PubMed Central

Johnson, Wendy; Kyvik, Kirsten Ohm; Skytthe, Axel; Deary, Ian J.; Sørensen, Thorkild I. A.

2011-01-01

Obesity is more common among the less educated, suggesting education-related environmental triggers. Such triggers may act differently dependent on genetic and environmental predisposition to obesity. In a Danish Twin Registry survey, 21,522 twins of same-sex pairs provided zygosity, height, weight, and education data. Body mass index (BMI = kg weight/ m height2) was used to measure degree of obesity. We used quantitative genetic modeling to examine how genetic and shared and nonshared environmental variance in BMI differed by level of education and to estimate how genetic and shared and nonshared environmental correlations between education and BMI differed by level of education, analyzing women and men separately. Correlations between education and BMI were −.13 in women, −.15 in men. High BMI's were less frequent among well-educated participants, generating less variance. In women, this was due to restriction of all forms of variance, overall by a factor of about 2. In men, genetic variance did not vary with education, but results for shared and nonshared environmental variance were similar to those for women. The contributions of the shared environment to the correlations between education and BMI were substantial among the well-educated, suggesting importance of familial environmental influences common to high education and lower BMI. Family influence was particularly important in linking high education and lower levels of obesity. PMID:21283825

Multivariable confounding adjustment in distributed data networks without sharing of patient-level data.

PubMed

Toh, Sengwee; Reichman, Marsha E; Houstoun, Monika; Ding, Xiao; Fireman, Bruce H; Gravel, Eric; Levenson, Mark; Li, Lingling; Moyneur, Erick; Shoaibi, Azadeh; Zornberg, Gwen; Hennessy, Sean

2013-11-01

It is increasingly necessary to analyze data from multiple sources when conducting public health safety surveillance or comparative effectiveness research. However, security, privacy, proprietary, and legal concerns often reduce data holders' willingness to share highly granular information. We describe and compare two approaches that do not require sharing of patient-level information to adjust for confounding in multi-site studies. We estimated the risks of angioedema associated with angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), and aliskiren in comparison with beta-blockers within Mini-Sentinel, which has created a distributed data system of 18 health plans. To obtain the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs), we performed (i) a propensity score-stratified case-centered logistic regression analysis, a method identical to a stratified Cox regression analysis but needing only aggregated risk set data, and (ii) an inverse variance-weighted meta-analysis, which requires only the site-specific HR and variance. We also performed simulations to further compare the two methods. Compared with beta-blockers, the adjusted HR was 3.04 (95% CI: 2.81, 3.27) for ACEIs, 1.16 (1.00, 1.34) for ARBs, and 2.85 (1.34, 6.04) for aliskiren in the case-centered analysis. The corresponding HRs were 2.98 (2.76, 3.21), 1.15 (1.00, 1.33), and 2.86 (1.35, 6.04) in the meta-analysis. Simulations suggested that the two methods may produce different results under certain analytic scenarios. The case-centered analysis and the meta-analysis produced similar results without the need to share patient-level data across sites in our empirical study, but may provide different results in other study settings. Copyright © 2013 John Wiley & Sons, Ltd.

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

PubMed

Renaud, Sabrina; Dufour, Anne-Béatrice; Hardouin, Emilie A; Ledevin, Ronan; Auffray, Jean-Christophe

2015-01-01

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

Neural Mechanisms of Interference Control Underlie the Relationship between Fluid Intelligence and Working Memory Span

ERIC Educational Resources Information Center

Burgess, Gregory C.; Gray, Jeremy R.; Conway, Andrew R. A.; Braver, Todd S.

2011-01-01

Fluid intelligence (gF) and working memory (WM) span predict success in demanding cognitive situations. Recent studies show that much of the variance in gF and WM span is shared, suggesting common neural mechanisms. This study provides a direct investigation of the degree to which shared variance in gF and WM span can be explained by neural…

Gene Variants Associated with Antisocial Behaviour: A Latent Variable Approach

ERIC Educational Resources Information Center

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

2013-01-01

Objective: The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods: Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a…

Blood pressure and cerebral white matter share common genetic factors in Mexican Americans.

PubMed

Kochunov, Peter; Glahn, David C; Lancaster, Jack; Winkler, Anderson; Karlsgodt, Kathrin; Olvera, Rene L; Curran, Joanna E; Carless, Melanie A; Dyer, Thomas D; Almasy, Laura; Duggirala, Ravi; Fox, Peter T; Blangero, John

2011-02-01

Elevated arterial pulse pressure and blood pressure (BP) can lead to atrophy of cerebral white matter (WM), potentially attributable to shared genetic factors. We calculated the magnitude of shared genetic variance between BP and fractional anisotropy of water diffusion, a sensitive measurement of WM integrity in a well-characterized population of Mexican Americans. The patterns of whole-brain and regional genetic overlap between BP and fractional anisotropy were interpreted in the context the pulse-wave encephalopathy theory. We also tested whether regional pattern in genetic pleiotropy is modulated by the phylogeny of WM development. BP and high-resolution (1.7 × 1.7 × 3 mm; 55 directions) diffusion tensor imaging data were analyzed for 332 (202 females; mean age 47.9 ± 13.3 years) members of the San Antonio Family Heart Study. Bivariate genetic correlation analysis was used to calculate the genetic overlap between several BP measurements (pulse pressure, systolic BP, and diastolic BP) and fractional anisotropy (whole-brain and regional values). Intersubject variance in pulse pressure and systolic BP exhibited a significant genetic overlap with variance in whole-brain fractional anisotropy values, sharing 36% and 22% of genetic variance, respectively. Regionally, shared genetic variance was significantly influenced by rates of WM development (r=-0.75; P=0.01). The pattern of genetic overlap between BP and WM integrity was generally in agreement with the pulse-wave encephalopathy theory. Our study provides evidence that a set of pleiotropically acting genetic factors jointly influence phenotypic variation in BP and WM integrity. The magnitude of this overlap appears to be influenced by phylogeny of WM development, suggesting a possible role for genotype-by-age interactions.

Blood Pressure and Cerebral White Matter Share Common Genetic Factors in Mexican-Americans

PubMed Central

Kochunov, Peter; Glahn, David C; Lancaster, Jack; Winkler, Anderson; Karlsgodt, Kathrin; Olvera, Rene L; Curran, Joanna E; Carless, Melanie A; Dyer, Thomas D; Almasy, Laura; Duggirala, Ravi; Fox, Peter T; Blangero, John

2010-01-01

Elevated arterial pulse pressure (PP) and blood pressure (BP) can lead to atrophy of cerebral white matter (WM), potentially due to shared genetic factors. We calculated the magnitude of shared genetic variance between BP and fractional anisotropy (FA) of water diffusion, a sensitive measurement of WM integrity in a well-characterized population of Mexican-Americans. The patterns of whole-brain and regional genetic overlap between BP and FA were interpreted in the context the pulse-wave encephalopathy (PWE) theory. We also tested whether regional pattern in genetic pleiotropy is modulated by the phylogeny of WM development. BP and high-resolution (1.7×1.7×3mm, 55 directions) diffusion tensor imaging (DTI) data were analyzed for 332 (202 females; mean age=47.9±13.3years) members of the San Antonio Family Heart Study. Bivariate genetic correlation analysis was used to calculate the genetic overlap between several BP measurements [PP, systolic (SBP) and diastolic (DBP)] and FA (whole-brain and regional values). Intersubject variance in PP and SBP exhibited a significant genetic overlap with variance in whole-brain FA values, sharing 36% and 22% of genetic variance, respectively. Regionally, shared genetic variance was significantly influenced by rates of WM development (r=−.75, p=0.01). The pattern of genetic overlap between BP and WM integrity was generally in-agreement with the PWE theory. Our study provides evidence that a set of pleiotropically acting genetic factors jointly influence phenotypic variation in BP and WM integrity. The magnitude of this overlap appears to be influenced by phylogeny of WM development suggesting a possible role for genotype-by-age interactions. PMID:21135356

Decomposing the relation between Rapid Automatized Naming (RAN) and reading ability.

PubMed

Arnell, Karen M; Joanisse, Marc F; Klein, Raymond M; Busseri, Michael A; Tannock, Rosemary

2009-09-01

The Rapid Automatized Naming (RAN) test involves rapidly naming sequences of items presented in a visual array. RAN has generated considerable interest because RAN performance predicts reading achievement. This study sought to determine what elements of RAN are responsible for the shared variance between RAN and reading performance using a series of cognitive tasks and a latent variable modelling approach. Participants performed RAN measures, a test of reading speed and comprehension, and six tasks, which tapped various hypothesised components of the RAN. RAN shared 10% of the variance with reading comprehension and 17% with reading rate. Together, the decomposition tasks explained 52% and 39% of the variance shared between RAN and reading comprehension and between RAN and reading rate, respectively. Significant predictors suggested that working memory encoding underlies part of the relationship between RAN and reading ability.

A Common-Fate Analysis of Pornography Acceptance, Use, and Sexual Satisfaction Among Heterosexual Married Couples.

PubMed

Brown, Cameron C; Carroll, Jason S; Yorgason, Jeremy B; Busby, Dean M; Willoughby, Brian J; Larson, Jeffry H

2017-02-01

Using matched, heterosexual couple data from the Relationship Evaluation Questionnaire (RELATE; n = 326 couples), an adapted common-fate approach was used to examine both common and unique attributes of husbands' and wives' acceptance of pornography and sexual satisfaction as well as husbands' and wives' pornography use. It was expected that spouses' unique as well as shared variance of pornography acceptance would be significantly associated with husbands' and wives' levels of personal pornography use and that these use patterns would be significantly associated with husbands' and wives' unique as well as shared variance of sexual satisfaction. It was also expected that pornography use would significantly mediate the relationship between pornography acceptance and sexual satisfaction. Results indicated that the shared variance of pornography acceptance was positively associated with both spouses' pornography use and that spouses' pornography use was negatively associated with their own sexual satisfaction. Wives' pornography use was found to be positively associated with the couple's shared variance of sexual satisfaction, but pornography use did not significantly mediate the relationship between pornography acceptance and sexual satisfaction. These findings emphasize the complexity of pornography use in couple relationships and the importance of studying pornography acceptance and use as a coupling dynamic within marriages rather than just an individual behavior.

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning

ERIC Educational Resources Information Center

Adlof, Suzanne M.; Patten, Hannah

2017-01-01

Purpose: This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method: Fifty children, with a mean age of 8 years (range 5-12…

Teaching Effectiveness and the Conditions that Matter Most in High-Needs Schools: A Policy Brief

ERIC Educational Resources Information Center

Berry, Barnett; Daughtrey, Alesha; Wieder, Alan

2009-01-01

Over the last decade, policy and business leaders have come to know what parents have always known: teachers make the greatest difference to student achievement. With new statistical and analytical methods used by a wide range of researchers, evidence has been mounting that teacher quality can account for a large share of variance in student test…

Bullying and Victimization in Elementary Schools: A Comparison of Bullies, Victims, Bully/Victims, and Uninvolved Preadolescents

ERIC Educational Resources Information Center

Veenstra, Rene; Lindenberg, Siegwart; Oldehinkel, Albertine J.; De Winter, Andrea F.; Verhulst, Frank C.; Ormel, Johan

2005-01-01

Research on bullying and victimization largely rests on univariate analyses and on reports from a single informant. Researchers may thus know too little about the simultaneous effects of various independent and dependent variables, and their research may be biased by shared method variance. The database for this Dutch study was large (N=1,065) and…

An Examination of Shared Variance in Self-Report and Objective Measures of Attention in the Incarcerated Adult Population

ERIC Educational Resources Information Center

Asbjornsen, Arve E.; Jones, Lise O.; Munkvold, Linda H.; Obrzut, John E.; Manger, Terje

2010-01-01

Objective: The present study was designed to test some assumptions about screening procedures for ADHD in adults. Method: Twenty-eight incarcerated male adults completed a self report scale of attention deficits as a part of an examination of attention and reading skills. Further assessment of attention included a battery of tests that assessed…

Teacher Effectiveness: The Conditions that Matter Most and a Look to the Future

ERIC Educational Resources Information Center

Berry, Barnett

2010-01-01

Over the last decade, policy and business leaders have come to know what parents have always known: teachers make the greatest difference to student achievement. With new statistical and analytical methods used by a wide range of researchers, evidence has been mounting that teacher quality can account for a large share of variance in student test…

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.

Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

PubMed

Böing-Messing, Florian; Mulder, Joris

2018-05-03

In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

Estimation of variance in Cox's regression model with shared gamma frailties.

PubMed

Andersen, P K; Klein, J P; Knudsen, K M; Tabanera y Palacios, R

1997-12-01

The Cox regression model with a shared frailty factor allows for unobserved heterogeneity or for statistical dependence between the observed survival times. Estimation in this model when the frailties are assumed to follow a gamma distribution is reviewed, and we address the problem of obtaining variance estimates for regression coefficients, frailty parameter, and cumulative baseline hazards using the observed nonparametric information matrix. A number of examples are given comparing this approach with fully parametric inference in models with piecewise constant baseline hazards.

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

The Relationship between Parent-Infant Bed Sharing and Marital Satisfaction for Mothers of Infants

ERIC Educational Resources Information Center

Messmer, Rosemary; Miller, Lynn D.; Yu, Christine M.

2012-01-01

This study investigated the relationship between marital satisfaction and time spent bed sharing with infants in a community sample of 81 bed sharing mothers. Time spent bed sharing did not significantly predict variance in marital satisfaction when considering bed sharers as a whole. Moderation analysis, however, showed the interaction between…

A Genetic Epidemiological Mega Analysis of Smoking Initiation in Adolescents

PubMed Central

Prom-Wormley, Elizabeth; Eaves, Lindon J.; Rhee, Soo Hyun; Hewitt, John K.; Young, Susan; Corley, Robin; McGue, Matt; Iacono, William G.; Legrand, Lisa; Samek, Diana R.; Murrelle, E. Lenn; Silberg, Judy L.; Miles, Donna R.; Schieken, Richard M.; Beunen, Gaston P.; Thomis, Martine; Rose, Richard J.; Dick, Danielle M.; Boomsma, Dorret I.; Bartels, Meike; Vink, Jacqueline M.; Lichtenstein, Paul; White, Victoria; Kaprio, Jaakko; Neale, Michael C.

2017-01-01

Abstract Introduction: Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation (SI) across adolescence. Methods: Mega-analysis of pooled genetically informative data on SI was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N = 19 313 pairs) between ages 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the United States, Europe, and Australia. Results: Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of SI across developed countries. The estimate of additive genetic contributions to liability of SI increased from approximately 15% to 45% from ages 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to SI at age 13 (70%) and gradually less by age 19 (40%). Conclusions: Both additive genetic and shared environmental factors significantly contribute to variance in SI throughout adolescence. The present study, the largest genetic epidemiological study on SI to date, found consistent results across 11 studies for the etiology of SI. Environmental factors, especially those shared by siblings in a family, primarily influence SI variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies. Implications: This is the first study to find evidence of genetic factors in liability to SI at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across studies reflecting similar etiology of liability to initiate smoking across different cultures and time periods. Thus familial factors strongly contribute to individual differences in who starts to smoke with a gradual increase in the impact of genetic factors and a corresponding decrease in that of the shared environment. PMID:27807125

A random variance model for detection of differential gene expression in small microarray experiments.

PubMed

Wright, George W; Simon, Richard M

2003-12-12

Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true. We propose a model by which the within gene variances are drawn from an inverse gamma distribution, whose parameters are estimated across all genes. This results in a test statistic that is a minor variation of those used in standard linear models. We demonstrate that the model assumptions are valid on experimental data, and that the model has more power than standard tests to pick up large changes in expression, while not increasing the rate of false positives. This method is incorporated into BRB-ArrayTools version 3.0 (http://linus.nci.nih.gov/BRB-ArrayTools.html). ftp://linus.nci.nih.gov/pub/techreport/RVM_supplement.pdf

Cross-Sectional Analysis of Time-Dependent Data: Mean-Induced Association in Age-Heterogeneous Samples and an Alternative Method Based on Sequential Narrow Age-Cohort Samples

ERIC Educational Resources Information Center

Hofer, Scott M.; Flaherty, Brian P.; Hoffman, Lesa

2006-01-01

The effect of time-related mean differences on estimates of association in cross-sectional studies has not been widely recognized in developmental and aging research. Cross-sectional studies of samples varying in age have found moderate to high levels of shared age-related variance among diverse age-related measures. These findings may be…

Environmental influences on the longitudinal covariance of expressive vocabulary: measuring the home literacy environment in a genetically sensitive design

PubMed Central

Hart, Sara A.; Petrill, Stephen A.; DeThorne, Laura S.; Deater-Deckard, Kirby; Thompson, Lee A.; Schatschneider, Chris; Cutting, Laurie E.

2010-01-01

Background Despite the well-replicated relationship between the home literacy environment and expressive vocabulary, few studies have examined the extent to which the home literacy environment is associated with the development of early vocabulary ability in the context of genetic influences. This study examined the influence of the home literacy environment on the longitudinal covariance of expressive vocabulary within a genetically sensitive design. Methods Participants were drawn from the Western Reserve Reading Project, a longitudinal twin project of 314 twin pairs based in Ohio. Twins were assessed via three annual home visits during early elementary school; expressive vocabulary was measured via the Boston Naming Test (BNT), and the Home Literacy Environment (HLE) was assessed using mothers’ report. Results The heritability of the BNT was moderate and significant at each measurement occasion, h2 = .29–.49, as were the estimates of the shared environment, c2 = .27–.39. HLE accounted for between 6–10% of the total variance in each year of vocabulary assessment. Furthermore, 7–9% of the total variance of the stability over time in BNT was accounted for by covariance in the home literacy environment. Conclusions These results indicate that aspects of the home literacy environment, as reported by mothers, account for some of the shared environmental variance associated with expressive vocabulary in school aged children. PMID:19298476

Psychopathic personality traits in 5 year old twins: the importance of genetic and shared environmental influences.

PubMed

Tuvblad, Catherine; Fanti, Kostas A; Andershed, Henrik; Colins, Olivier F; Larsson, Henrik

2017-04-01

There is limited research on the genetic and environmental bases of psychopathic personality traits in children. In this study, psychopathic personality traits were assessed in a total of 1189 5-year-old boys and girls drawn from the Preschool Twin Study in Sweden. Psychopathic personality traits were assessed with the Child Problematic Traits Inventory, a teacher-report measure of psychopathic personality traits in children ranging from 3 to 12 years old. Univariate results showed that genetic influences accounted for 57, 25, and 74 % of the variance in the grandiose-deceitful, callous-unemotional, and impulsive-need for stimulation dimensions, while the shared environment accounted for 17, 48 and 9 % (n.s.) in grandiose-deceitful and callous-unemotional, impulsive-need for stimulation dimensions, respectively. No sex differences were found in the genetic and environmental variance components. The non-shared environment accounted for the remaining 26, 27 and 17 % of the variance, respectively. The three dimensions of psychopathic personality were moderately correlated (0.54-0.66) and these correlations were primarily mediated by genetic and shared environmental factors. In contrast to research conducted with adolescent and adult twins, we found that both genetic and shared environmental factors influenced psychopathic personality traits in early childhood. These findings indicate that etiological models of psychopathic personality traits would benefit by taking developmental stages and processes into consideration.

Synthetic ALSPAC longitudinal datasets for the Big Data VR project.

PubMed

Avraam, Demetris; Wilson, Rebecca C; Burton, Paul

2017-01-01

Three synthetic datasets - of observation size 15,000, 155,000 and 1,555,000 participants, respectively - were created by simulating eleven cardiac and anthropometric variables from nine collection ages of the ALSAPC birth cohort study. The synthetic datasets retain similar data properties to the ALSPAC study data they are simulated from (co-variance matrices, as well as the mean and variance values of the variables) without including the original data itself or disclosing participant information.  In this instance, the three synthetic datasets have been utilised in an academia-industry collaboration to build a prototype virtual reality data analysis software, but they could have a broader use in method and software development projects where sensitive data cannot be freely shared.

Aging Trajectories in Different Body Systems Share Common Environmental Etiology: The Healthy Aging Twin Study (HATS).

PubMed

Moayyeri, Alireza; Hart, Deborah J; Snieder, Harold; Hammond, Christopher J; Spector, Timothy D; Steves, Claire J

2016-02-01

Little is known about the extent to which aging trajectories of different body systems share common sources of variance. We here present a large twin study investigating the trajectories of change in five systems: cardiovascular, respiratory, skeletal, morphometric, and metabolic. Longitudinal clinical data were collected on 3,508 female twins in the TwinsUK registry (complete pairs:740 monozygotic (MZ), 986 dizygotic (DZ), mean age at entry 48.9 ± 10.4, range 18-75 years; mean follow-up 10.2 ± 2.8 years, range 4-17.8 years). Panel data on multiple age-related variables were used to estimate biological ages for each individual at each time point, in linear mixed effects models. A weighted average approach was used to combine variables within predefined body system groups. Aging trajectories for each system in each individual were then constructed using linear modeling. Multivariate structural equation modeling of these aging trajectories showed low genetic effects (heritability), ranging from 2% in metabolic aging to 22% in cardiovascular aging. However, we found a significant effect of shared environmental factors on the variations in aging trajectories in cardiovascular (54%), skeletal (34%), morphometric (53%), and metabolic systems (53%). The remainder was due to environmental factors unique to each individual plus error. Multivariate Cholesky decomposition showed that among aging trajectories for various body systems there were significant and substantial correlations between the unique environmental latent factors as well as shared environmental factors. However, there was no evidence for a single common factor for aging. This study, the first of its kind in aging, suggests that diverse organ systems share non-genetic sources of variance for aging trajectories. Confirmatory studies are needed using population-based twin cohorts and alternative methods of handling missing data.

Shared environmental influences on personality: A combined twin and adoption approach

PubMed Central

Matteson, Lindsay K.; McGue, Matt; Iacono, William G.

2013-01-01

In the past, shared environmental influences on personality traits have been found to be negligible in behavior genetic studies (e.g., Bouchard & McGue, 2003). However, most studies have been based on biometrical modeling of twins only. Failure to meet key assumptions of the classical twin design could lead to biased estimates of shared environmental effects. Alternative approaches to the etiology of personality are needed. In the current study we estimated the impact of shared environmental factors on adolescent personality by simultaneously modeling both twin and adoption data. We found evidence for significant shared environmental influences on Multidimensional Personality Questionnaire (MPQ) Absorption (15% variance explained), Alienation (10%), Harm Avoidance (14%), and Traditionalism (26%) scales. Additionally, we found that in most cases biometrical models constraining parameter estimates to be equal across study type (twins versus adoptees) fit no worse than models allowing these parameters to vary; this suggests that results converge across study design despite the potential (sometimes opposite) biases of twin and adoption studies. Thus, we can be more confident that our findings represent the true contribution of shared environmental variance to personality development. PMID:24065564

Risk and the evolution of human exchange.

PubMed

Kaplan, Hillard S; Schniter, Eric; Smith, Vernon L; Wilson, Bart J

2012-08-07

Compared with other species, exchange among non-kin is a hallmark of human sociality in both the breadth of individuals and total resources involved. One hypothesis is that extensive exchange evolved to buffer the risks associated with hominid dietary specialization on calorie dense, large packages, especially from hunting. 'Lucky' individuals share food with 'unlucky' individuals with the expectation of reciprocity when roles are reversed. Cross-cultural data provide prima facie evidence of pair-wise reciprocity and an almost universal association of high-variance (HV) resources with greater exchange. However, such evidence is not definitive; an alternative hypothesis is that food sharing is really 'tolerated theft', in which individuals possessing more food allow others to steal from them, owing to the threat of violence from hungry individuals. Pair-wise correlations may reflect proximity providing greater opportunities for mutual theft of food. We report a laboratory experiment of foraging and food consumption in a virtual world, designed to test the risk-reduction hypothesis by determining whether people form reciprocal relationships in response to variance of resource acquisition, even when there is no external enforcement of any transfer agreements that might emerge. Individuals can forage in a high-mean, HV patch or a low-mean, low-variance (LV) patch. The key feature of the experimental design is that individuals can transfer resources to others. We find that sharing hardly occurs after LV foraging, but among HV foragers sharing increases dramatically over time. The results provide strong support for the hypothesis that people are pre-disposed to evaluate gains from exchange and respond to unsynchronized variance in resource availability through endogenous reciprocal trading relationships.

Two dynamic regimes in the human gut microbiome

PubMed Central

Smillie, Chris S.; Alm, Eric J.

2017-01-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. PMID:28222117

Two dynamic regimes in the human gut microbiome.

PubMed

Gibbons, Sean M; Kearney, Sean M; Smillie, Chris S; Alm, Eric J

2017-02-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

PubMed

Evans, Luke M; Tahmasbi, Rasool; Jones, Matt; Vrieze, Scott I; Abecasis, Gonçalo R; Das, Sayantan; Bjelland, Douglas W; de Candia, Teresa R; Yang, Jian; Goddard, Michael E; Visscher, Peter M; Keller, Matthew C

2018-03-28

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.

Differential heritability of adult and juvenile antisocial traits.

PubMed

Lyons, M J; True, W R; Eisen, S A; Goldberg, J; Meyer, J M; Faraone, S V; Eaves, L J; Tsuang, M T

1995-11-01

Studies of adult antisocial behavior or criminality usually find genetic factors to be more important than the family environment, whereas studies of delinquency find the family environment to be more important. We compared DSM-III-R antisocial personality disorder symptoms before vs after the age of 15 years within a sample of twins, rather than comparing across studies. We administered the Diagnostic Interview Schedule Version III-revised by telephone to 3226 pairs of male twins from the Vietnam Era Twin Registry. Biometrical modeling was applied to each symptom of antisocial personality disorder and summary measures of juvenile and adult symptoms. Five juvenile symptoms were significantly heritable, and five were significantly influenced by the shared environment. Eight adult symptoms were significantly heritable, and one was significantly influenced by the shared environment. The shared environment explained about six times more variance in juvenile anti-social traits than in adult traits. Shared environmental influences on adult antisocial traits overlapped entirely with those on juvenile traits. Additive genetic factors explained about six times more variance in adult vs juvenile traits. The juvenile genetic determinants overlapped completely with genetic influences on adult traits. The unique environment (plus measurement error) explained the largest proportion of variance in both juvenile and adult antisocial traits. Characteristics of the shared or family environment that promote antisocial behavior during childhood and early adolescence also promote later antisocial behavior, but to a much lesser extent. Genetic causal factors are much more prominent for adult than for juvenile antisocial traits.

Taylor’s Law of Temporal Fluctuation Scaling in Stock Illiquidity

NASA Astrophysics Data System (ADS)

Cai, Qing; Xu, Hai-Chuan; Zhou, Wei-Xing

2016-08-01

Taylor’s law of temporal fluctuation scaling, variance ˜ a(mean)b, is ubiquitous in natural and social sciences. We report for the first time convincing evidence of a solid temporal fluctuation scaling law in stock illiquidity by investigating the mean-variance relationship of the high-frequency illiquidity of almost all stocks traded on the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange (SZSE) during the period from 1999 to 2011. Taylor’s law holds for A-share markets (SZSE Main Board, SZSE Small & Mediate Enterprise Board, SZSE Second Board, and SHSE Main Board) and B-share markets (SZSE B-share and SHSE B-share). We find that the scaling exponent b is greater than 2 for the A-share markets and less than 2 for the B-share markets. We further unveil that Taylor’s law holds for stocks in 17 industry categories, in 28 industrial sectors and in 31 provinces and direct-controlled municipalities with the majority of scaling exponents b ∈ (2, 3). We also investigate the Δt-min illiquidity and find that the scaling exponent b(Δt) increases logarithmically for small Δt values and decreases fast to a stable level.

Risk and the evolution of human exchange

PubMed Central

Kaplan, Hillard S.; Schniter, Eric; Smith, Vernon L.; Wilson, Bart J.

2012-01-01

Compared with other species, exchange among non-kin is a hallmark of human sociality in both the breadth of individuals and total resources involved. One hypothesis is that extensive exchange evolved to buffer the risks associated with hominid dietary specialization on calorie dense, large packages, especially from hunting. ‘Lucky’ individuals share food with ‘unlucky’ individuals with the expectation of reciprocity when roles are reversed. Cross-cultural data provide prima facie evidence of pair-wise reciprocity and an almost universal association of high-variance (HV) resources with greater exchange. However, such evidence is not definitive; an alternative hypothesis is that food sharing is really ‘tolerated theft’, in which individuals possessing more food allow others to steal from them, owing to the threat of violence from hungry individuals. Pair-wise correlations may reflect proximity providing greater opportunities for mutual theft of food. We report a laboratory experiment of foraging and food consumption in a virtual world, designed to test the risk-reduction hypothesis by determining whether people form reciprocal relationships in response to variance of resource acquisition, even when there is no external enforcement of any transfer agreements that might emerge. Individuals can forage in a high-mean, HV patch or a low-mean, low-variance (LV) patch. The key feature of the experimental design is that individuals can transfer resources to others. We find that sharing hardly occurs after LV foraging, but among HV foragers sharing increases dramatically over time. The results provide strong support for the hypothesis that people are pre-disposed to evaluate gains from exchange and respond to unsynchronized variance in resource availability through endogenous reciprocal trading relationships. PMID:22513855

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

Genes, Culture and Conservatism-A Psychometric-Genetic Approach.

PubMed

Schwabe, Inga; Jonker, Wilfried; van den Berg, Stéphanie M

2016-07-01

The Wilson-Patterson conservatism scale was psychometrically evaluated using homogeneity analysis and item response theory models. Results showed that this scale actually measures two different aspects in people: on the one hand people vary in their agreement with either conservative or liberal catch-phrases and on the other hand people vary in their use of the "?" response category of the scale. A 9-item subscale was constructed, consisting of items that seemed to measure liberalism, and this subscale was subsequently used in a biometric analysis including genotype-environment interaction, correcting for non-homogeneous measurement error. Biometric results showed significant genetic and shared environmental influences, and significant genotype-environment interaction effects, suggesting that individuals with a genetic predisposition for conservatism show more non-shared variance but less shared variance than individuals with a genetic predisposition for liberalism.

Understanding the covariation of tics, attention-deficit/hyperactivity, and obsessive-compulsive symptoms: A population-based adult twin study.

PubMed

Pinto, Rebecca; Monzani, Benedetta; Leckman, James F; Rück, Christian; Serlachius, Eva; Lichtenstein, Paul; Mataix-Cols, David

2016-10-01

Chronic tic disorders (TD), attention-deficit/hyperactivity-disorder (ADHD), and obsessive-compulsive disorder (OCD) frequently co-occur in clinical and epidemiological samples. Family studies have found evidence of shared familial transmission between TD and OCD, whereas the familial association between these disorders and ADHD is less clear. This study aimed to investigate to what extent liability of tics, attention-deficit/hyperactivity, and obsessive-compulsive symptoms is caused by shared or distinct genetic or environmental influences, in a large population-representative sample of Swedish adult twins (n = 21,911). Tics, attention-deficit/hyperactivity, and obsessive-compulsive symptoms showed modest, but significant covariation. Model fitting suggested a latent liability factor underlying the three phenotypes. This common factor was relatively heritable, and explained significantly less of the variance of attention-deficit/hyperactivity symptom liability. The majority of genetic variance was specific rather than shared. The greatest proportion of total variance in liability of tics, attention-deficit/hyperactivity, and obsessive-compulsive symptoms was attributed to specific non-shared environmental influences. Our findings suggest that the co-occurrence of tics and obsessive-compulsive symptoms, and to a lesser extent attention-deficit/hyperactivity symptoms, can be partly explained by shared etiological influences. However, these phenotypes do not appear to be alternative expressions of the same underlying genetic liability. Further research examining sub-dimensions of these phenotypes may serve to further clarify the association between these disorders and identify more genetically homogenous symptom subtypes. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Use of Discordant MZ Twins to Generate Hypotheses regarding Non-Shared Environmental Influence on Anxiety in Middle Childhood

ERIC Educational Resources Information Center

Asbury, Kathryn; Dunn, Judy; Plomin, Robert

2006-01-01

Non-shared environmental influence (NSE) has been found to account for around 50 percent of anxiety variance, but specific NSE factors have not been identified. Discordant monozygotic (MZ) twins can be used to generate relevant hypotheses because MZ discordance can be caused by NSE, but not by genes or shared environment. Of 1590 MZ pairs teacher…

Environmental rather than genetic factors determine the variation in the age of the infancy to childhood transition: a twins study.

PubMed

German, Alina; Livshits, Gregory; Peter, Inga; Malkin, Ida; Dubnov, Jonathan; Akons, Hannah; Shmoish, Michael; Hochberg, Ze'ev

2015-03-01

Using a twins study, we sought to assess the contribution of genetic against environmental factor as they affect the age at transition from infancy to childhood (ICT). The subjects were 56 pairs of monozygotic twins, 106 pairs of dizygotic twins, and 106 pairs of regular siblings (SBs), for a total of 536 children. Their ICT was determined, and a variance component analysis was implemented to estimate components of the familial variance, with simultaneous adjustment for potential covariates. We found substantial contribution of the common environment shared by all types of SBs that explained 27.7% of the total variance in ICT, whereas the common twin environment explained 9.2% of the variance, gestational age 3.5%, and birth weight 1.8%. In addition, 8.7% was attributable to sex difference, but we found no detectable contribution of genetic factors to inter-individual variation in ICT age. Developmental plasticity impacts much of human growth. Here we show that of the ∼50% of the variance provided to adult height by the ICT, 42.2% is attributable to adaptive cues represented by shared twin and SB environment, with no detectable genetic involvement. Copyright © 2015 Elsevier Inc. All rights reserved.

Markowitz portfolio optimization model employing fuzzy measure

NASA Astrophysics Data System (ADS)

Ramli, Suhailywati; Jaaman, Saiful Hafizah

2017-04-01

Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

Experiences of college-age youths in families with a recessive genetic condition.

PubMed

Hern, Marcia J; Beery, Theresa A; Barry, Detrice G

2006-05-01

Growing up in a family with a recessive genetic condition can trigger questions about progeny effect. This study explored perceptions of family hardiness and information sharing by 18- to 21-year-olds about genetic risk. Semistructured interviews, the Family Hardiness Index (FHI), and a Family Information Sharing Analog Scale (FISAS) were used. Participants included 11 youths who had relatives with hemophilia and 4 with sickle cell anemia. Findings revealed seven themes: assimilating premature knowledge; caring for others, denying self; cautioning during development; experiencing continual sickness; feeling less than; magnifying transition experiences; and sustaining by faith. There was no significant correlation between total FHI and FISAS. However, there was a statistically significant difference in FISAS between genetic condition variance. Specifically, higher hardiness was found and information sharing correlated among college youths in families with hemophilia. Additional research can lead to nursing interventions to provide genetic information to youths in families for illness variance.

Category representations in the brain are both discretely localized and widely distributed.

PubMed

Shehzad, Zarrar; McCarthy, Gregory

2018-06-01

Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Initial functional MRI studies supported the localizationist perspective that category information is represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately. However, localized representations are revealed by using analytical methods that separate unique from shared information among brain regions. The distributed nature of shared information and the localized nature of unique information suggest that brain connectivity may encourage spreading of information but category-specific computations are carried out in distinct domain-specific regions. NEW & NOTEWORTHY Whether visual category information is localized in unique domain-specific brain regions or distributed in many domain-general brain regions is hotly contested. We resolve this debate by using multivariate analyses to parse functional MRI signals from different brain regions into unique and shared variance. Our findings support elements of both models and show information is initially localized and then shared among other regions leading to distributed representations being observed.

Neural Mechanisms of Interference Control Underlie the Relationship Between Fluid Intelligence and Working Memory Span

PubMed Central

Burgess, Gregory C.; Gray, Jeremy R.; Conway, Andrew R. A.; Braver, Todd S.

2014-01-01

Fluid intelligence (gF) and working memory (WM) span predict success in demanding cognitive situations. Recent studies show that much of the variance in gF and WM span is shared, suggesting common neural mechanisms. This study provides a direct investigation of the degree to which shared variance in gF and WM span can be explained by neural mechanisms of interference control. We measured performance and fMRI activity in 102 participants during the n-back WM task, focusing on the selective activation effects associated with high-interference lure trials. Brain activity on these trials was correlated with gF, WM span, and task performance in core brain regions linked to WM and executive control, including bilateral dorsolateral PFC (middle frontal gyrus, BA9) and parietal cortex (inferior parietal cortex; BA 40/7). Interference-related performance and interference-related activity accounted for a significant proportion of the shared variance in gF and WM span. Path analyses indicate that interference control activity may affect gF through a common set of processes that also influence WM span. These results suggest that individual differences in interference control mechanisms are important for understanding the relationship between gF and WM span. PMID:21787103

Psychometric Properties of the Death Anxiety Scale-Extended among Patients with End-Stage Renal Disease.

PubMed

Sharif Nia, Hamid; Pahlevan Sharif, Saeed; Koocher, Gerald P; Yaghoobzadeh, Ameneh; Haghdoost, Ali Akbar; Mar Win, Ma Thin; Soleimani, Mohammad Ali

2017-01-01

This study aimed to evaluate the validity and reliability of the Persian version of Death Anxiety Scale-Extended (DAS-E). A total of 507 patients with end-stage renal disease completed the DAS-E. The factor structure of the scale was evaluated using exploratory factor analysis with an oblique rotation and confirmatory factor analysis. The content and construct validity of the DAS-E were assessed. Average variance extracted, maximum shared squared variance, and average shared squared variance were estimated to assess discriminant and convergent validity. Reliability was assessed using Cronbach's alpha coefficient (α = .839 and .831), composite reliability (CR = .845 and .832), Theta (θ = .893 and .867), and McDonald Omega (Ω = .796 and .743). The analysis indicated a two-factor solution. Reliability and discriminant validity of the factors was established. Findings revealed that the present scale was a valid and reliable instrument that can be used in assessment of death anxiety in Iranian patients with end-stage renal disease.

Mindfulness and emotion regulation difficulties in generalized anxiety disorder: Preliminary evidence for independent and overlapping contributions

PubMed Central

Roemer, Lizabeth; Lee, Jonathan K.; Salters-Pedneault, Kristalyn; Erisman, Shannon M.; Orsillo, Susan M.; Mennin, Douglas S.

2013-01-01

Diminished levels of mindfulness (awareness and acceptance/nonjudgment) and difficulties in emotion regulation have both been proposed to play a role in symptoms of generalized anxiety disorder (GAD); the current studies investigated these relationships in a nonclinical and a clinical sample. In the first study, among a sample of 395 individuals at an urban commuter campus, we found that self reports of both emotion regulation difficulties and aspects of mindfulness accounted for unique variance in GAD symptom severity, above and beyond shared variance with depressive and anxious symptoms, as well as shared variance with one another. In the second study, we found that individuals diagnosed with clinically significant GAD (n = 16) reported significantly lower levels of mindfulness and significantly higher levels of difficulties in emotion regulation than individuals in a non-anxious control group (n = 16). Results are discussed in terms of directions for future research and potential implications for treatment development. PMID:19433145

A Primer on the Genetics of Comorbid Eating Disorders and Substance Use Disorders.

PubMed

Munn-Chernoff, Melissa A; Baker, Jessica H

2016-03-01

Eating disorders (EDs) and substance use disorders (SUDs) frequently co-occur; however, the reasons for this are unclear. We review the current literature on genetic risk for EDs and SUDs, as well as preliminary findings exploring whether these classes of disorders have overlapping genetic risk. Overall, genetic factors contribute to individual differences in liability to multiple EDs and SUDs. Although initial family studies concluded that no shared familial (which includes genetic) risk between EDs and SUDs exists, twin studies suggest a moderate proportion of shared variance is attributable to overlapping genetic factors, particularly for those EDs characterized by binge eating and/or inappropriate compensatory behaviours. No adoption or molecular genetic studies have examined shared genetic risk between these classes of disorders. Research investigating binge eating and inappropriate compensatory behaviours using emerging statistical genetic methods, as well as examining gene-environment interplay, will provide important clues into the aetiology of comorbid EDs and SUDs. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Maternal Psychological Control and Its Association with Mother and Child Perceptions of Adolescent Adjustment: More Evidence on the Strength of Shared Perspectives.

PubMed

Valdes, Olivia M; Laursen, Brett; Guimond, Fanny A; Hartl, Amy C; Denner, Jill

2016-10-01

Mothers and adolescents hold distinct albeit correlated views of their relationship and of one another. The present study focuses on disentangling these independent views. Concurrent associations between maternal psychological control and children's adjustment are examined at two time points in order to identify the degree to which associations reflect (a) views that are shared by mothers and adolescents, and (b) views that are unique to mothers and adolescents. A total of 123 (56 % female) U.S. Latino/a adolescents (M = 10.4 years old at the outset) and their mothers reported on maternal psychological control, children's conduct problems, and children's anxiety, twice within a 5-month period. Data were collected at the close of primary school when the adolescents were in grade 5 and again at the beginning of middle school, when they were in grade 6. Results from conventional correlations indicated that mother- and adolescent-reports yielded similar associations between maternal psychological control and adolescent adjustment. Common fate model analyses partitioned results into variance shared across mother and adolescent reports and variance unique to mother and adolescent reports. Results differed for anxiety and conduct problems. Shared views indicated that greater maternal psychological control was associated with heightened child conduct problems; there were no associations unique to either reporter. In contrast, unique reporter views indicated that greater maternal psychological control was associated with child anxiety; there were no associations involving shared views. Although mother- and adolescent-reports agree that maternal psychological control is correlated with children's adjustment, there is considerable divergence in results when associations are partitioned according to shared and unique reporter views. Associations between maternal psychological control and children's anxiety are more apt to be inflated by same-reporter variance bias than are associations between maternal psychological control and children's conduct problems.

Contributions of Risk and Protective Factors to Prediction of Psychological Symptoms after Traumatic Experiences

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Field, Nigel P.; Dalenberg, Constance J.; Macia, Kathryn S.; Spain, David A.

2016-01-01

Objective Traumatic experiences cause considerable suffering and place a burden on society due to lost productivity, increases in suicidality, violence, criminal behavior, and psychological disorder. The impact of traumatic experiences is complicated because many factors affect individuals’ responses. By employing several methodological improvements, we sought to identify risk factors that would account for a greater proportion of variance in later disorder than prior studies. Method In a sample of 129 traumatically injured hospital patients and family members of injured patients, we studied pre-trauma, time of trauma, and post-trauma psychosocial risk and protective factors hypothesized to influence responses to traumatic experiences and posttraumatic (PT) symptoms (including symptoms of PTSD, depression, negative thinking, and dissociation) two months after trauma. Results The risk factors were all significantly correlated with later PT symptoms, with post-trauma life stress, post-trauma social support, and acute stress symptoms showing the strongest relationships. A hierarchical regression, in which the risk factors were entered in 6 steps based on their occurrence in time, showed the risks accounted for 72% of the variance in later symptoms. Most of the variance in PT symptoms was shared among many risk factors, and pre-trauma and post-trauma risk factors accounted for the most variance. Conclusions Collectively, the risk factors accounted for more variance in later PT symptoms than in previous studies. These risk factors may identify individuals at risk for PT psychological disorders and targets for treatment. PMID:27423351

Rethinking Shared Environment as a Source of Variance Underlying Attention-Deficit/Hyperactivity Disorder Symptoms: Comment on Burt (2009)

ERIC Educational Resources Information Center

Wood, Alexis C.; Buitelaar, Jan; Rijsdijk, Fruhling; Asherson, Philip; Kuntsi, Jonna

2010-01-01

Burt (2009) recently published a meta-analysis of twin studies on behaviors associated with childhood psychopathologies, concluding that the finding that traits associated with attention-deficit/hyperactivity disorder (ADHD) were the only behaviors that did not show a significant influence of shared environment (C) was surprising. We agree,…

Predictors of father-son communication about sexuality.

PubMed

Lehr, Sally T; Demi, Alice S; Dilorio, Colleen; Facteau, Jeffrey

2005-05-01

Examining the factors that influence adolescents' sexual behaviors is crucial for understanding why they often engage in risky sexual behaviors. Using social cognitive theory, we examined predictors of father-son communication about sexuality. Fathers (N=155) of adolescent sons completed a survey measuring 12 variables, including self-efficacy and outcome expectations. We found that (a) son's pubertal development, father's sex-based values, father's education; father's communication with his father, outcome expectations, and general communication accounted for 36% of the variance in information sharing communication and (b) son's pubertal development, outcome expectations, general communication, and father-son contact accounted for 20% of the variance in values sharing communication. Study findings can aid professionals in designing guidelines for programs to promote father-son general communication and sex-based communication.

Pauci ex tanto numero: reduce redundancy in multi-model ensembles

NASA Astrophysics Data System (ADS)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-08-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.

Pauci ex tanto numero: reducing redundancy in multi-model ensembles

NASA Astrophysics Data System (ADS)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-02-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.

Does education confer a culture of healthy behavior? Smoking and drinking patterns in Danish twins.

PubMed

Johnson, Wendy; Kyvik, Kirsten Ohm; Mortensen, Erik L; Skytthe, Axel; Batty, G David; Deary, Ian J

2011-01-01

More education is associated with healthier smoking and drinking behaviors. Most analyses of effects of education focus on mean levels. Few studies have compared variance in health-related behaviors at different levels of education or analyzed how education impacts underlying genetic and environmental sources of health-related behaviors. This study explored these influences. In a 2002 postal questionnaire, 21,522 members of the Danish Twin Registry, born during 1931-1982, reported smoking and drinking habits. The authors used quantitative genetic models to examine how these behaviors' genetic and environmental variances differed with level of education, adjusting for birth-year effects. As expected, more education was associated with less smoking, and average drinking levels were highest among the most educated. At 2 standard deviations above the mean educational level, variance in smoking and drinking was about one-third that among those at 2 standard deviations below, because fewer highly educated people reported high levels of smoking or drinking. Because shared environmental variance was particularly restricted, one explanation is that education created a culture that discouraged smoking and heavy drinking. Correlations between shared environmental influences on education and the health behaviors were substantial among the well-educated for smoking in both sexes and drinking in males, reinforcing this notion.

Does academic performance or personal growth share a stronger association with learning environment perception?

PubMed

Colbert-Getz, Jorie M; Tackett, Sean; Wright, Scott M; Shochet, Robert S

2016-08-28

This study was conducted to characterize the relative strength of associations of learning environment perception with academic performance and with personal growth. In 2012-2014 second and third year students at Johns Hopkins University School of Medicine completed a learning environment survey and personal growth scale. Hierarchical linear regression analysis was employed to determine if the proportion of variance in learning environment scores accounted for by personal growth was significantly larger than the proportion accounted for by academic performance (course/clerkship grades). The proportion of variance in learning environment scores accounted for by personal growth was larger than the proportion accounted for by academic performance in year 2 [R(2)Δ of 0.09, F(1,175) = 14.99,  p < .001] and year 3 [R(2)Δ of 0.28, F(1,169) = 76.80, p < .001]. Learning environment scores shared a small amount of variance with academic performance in years 2 and 3.  The amount of variance between learning environment scores and personal growth was small in year 2 and large in year 3. Since supportive learning environments are essential for medical education, future work must determine if enhancing personal growth prior to and during the clerkship year will increase learning environment perception.

The Genetic and Environmental Etiologies of the Relations between Cognitive Skills and Components of Reading Ability

PubMed Central

Christopher, Micaela E.; Keenan, Janice M.; Hulslander, Jacqueline; DeFries, John C.; Miyake, Akira; Wadsworth, Sally J.; Willcutt, Erik; Pennington, Bruce; Olson, Richard K.

2016-01-01

While previous research has shown cognitive skills to be important predictors of reading ability in children, the respective roles for genetic and environmental influences on these relations is an open question. The present study explored the genetic and environmental etiologies underlying the relations between selected executive functions and cognitive abilities (working memory, inhibition, processing speed, and naming speed) with three components of reading ability (word reading, reading comprehension, and listening comprehension). Twin pairs drawn from the Colorado Front Range (n = 676; 224 monozygotic pairs; 452 dizygotic pairs) between the ages of eight and 16 (M = 11.11) were assessed on multiple measures of each cognitive and reading-related skill. Each cognitive and reading-related skill was modeled as a latent variable, and behavioral genetic analyses estimated the portions of phenotypic variance on each latent variable due to genetic, shared environmental, and nonshared environmental influences. The covariance between the cognitive skills and reading-related skills was driven primarily by genetic influences. The cognitive skills also shared large amounts of genetic variance, as did the reading-related skills. The common cognitive genetic variance was highly correlated with the common reading genetic variance, suggesting that genetic influences involved in general cognitive processing are also important for reading ability. Skill-specific genetic variance in working memory and processing speed also predicted components of reading ability. Taken together, the present study supports a genetic association between children’s cognitive ability and reading ability. PMID:26974208

Fetal Environment Is a Major Determinant of the Neonatal Blood Thyroxine Level: Results of a Large Dutch Twin Study.

PubMed

Zwaveling-Soonawala, Nitash; van Beijsterveldt, Catharina E M; Mesfum, Ertirea T; Wiedijk, Brenda; Oomen, Petra; Finken, Martijn J J; Boomsma, Dorret I; van Trotsenburg, A S Paul

2015-06-01

The interindividual variability in thyroid hormone function parameters is much larger than the intraindividual variability, suggesting an individual set point for these parameters. There is evidence to suggest that environmental factors are more important than genetic factors in the determination of this individual set point. This study aimed to quantify the effect of genetic factors and (fetal) environment on the early postnatal blood T4 concentration. This was a classical twin study comparing the resemblance of neonatal screening blood T4 concentrations in 1264 mono- and 2566 dizygotic twin pairs retrieved from the population-based Netherlands Twin Register. Maximum-likelihood estimates of variance explained by genetic and environmental influences were obtained by structural equation modeling in data from full-term and preterm twin pairs. In full-term infants, genetic factors explained 40%/31% of the variance in standardized T4 scores in boys/girls, and shared environment, 27%/22%. The remaining variance of 33%/47% was due to environmental factors not shared by twins. For preterm infants, genetic factors explained 34%/0% of the variance in boys/girls, shared environment 31%/57%, and unique environment 35%/43%. In very preterm twins, no significant contribution of genetic factors was observed. Environment explains a large proportion of the resemblance of the postnatal blood T4 concentration in twin pairs. Because we analyzed neonatal screening results, the fetal environment is the most likely candidate for these environmental influences. Genetic influences on the T4 set point diminished with declining gestational age, especially in girls. This may be due to major environmental influences such as immaturity and nonthyroidal illness in very preterm infants.

Situational Influences on the Morale of Older Rural Adults in Child-Shared Housing: A Comparative Analysis.

ERIC Educational Resources Information Center

Kivett, Vira R.; Learner, R. Max

1982-01-01

Results showed no significant difference in the morale scores of older rural adults living with children (N=97) and those in other arrangements (N=243) when health was controlled. However, more than twice as much variance in morale scores could be explained for parents in child-shared housing as for other parents. (Author)

Hindcast of extreme sea states in North Atlantic extratropical storms

NASA Astrophysics Data System (ADS)

Ponce de León, Sonia; Guedes Soares, Carlos

2015-02-01

This study examines the variability of freak wave parameters around the eye of northern hemisphere extratropical cyclones. The data was obtained from a hindcast performed with the WAve Model (WAM) model forced by the wind fields of the Climate Forecast System Reanalysis (CFSR). The hindcast results were validated against the wave buoys and satellite altimetry data showing a good correlation. The variability of different wave parameters was assessed by applying the empirical orthogonal functions (EOF) technique on the hindcast data. From the EOF analysis, it can be concluded that the first empirical orthogonal function (V1) accounts for greater share of variability of significant wave height (Hs), peak period (Tp), directional spreading (SPR) and Benjamin-Feir index (BFI). The share of variance in V1 varies for cyclone and variable: for the 2nd storm and Hs V1 contains 96 % of variance while for the 3rd storm and BFI V1 accounts only for 26 % of variance. The spatial patterns of V1 show that the variables are distributed around the cyclones centres mainly in a lobular fashion.

Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure

PubMed Central

Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J.; Barrada, Juan R.

2017-01-01

Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content. PMID:29085313

Observational Measures of Implementer Fidelity for a School-based Preventive Intervention: Development, Reliability and Validity

PubMed Central

Cross, Wendi; West, Jennifer; Wyman, Peter A.; Schmeelk-Cone, Karen; Xia, Yinglin; Tu, Xin; Teisl, Michael; Brown, C. Hendricks; Forgatch, Marion

2014-01-01

Current measures of implementer fidelity often fail to adequately measure core constructs of adherence and competence, and their relationship to outcomes can be mixed. To address these limitations, we used observational methods to assess these constructs and their relationships to proximal outcomes in a randomized trial of a school-based preventive intervention (Rochester Resilience Project) designed to strengthen emotion self-regulation skills in 1st–3rd graders with elevated aggressive-disruptive behaviors. Within the intervention group (n = 203), a subsample (n = 76) of students was selected to reflect the overall sample. Implementers were 10 paraprofessionals. Videotaped observations of three lessons from Year 1 of the intervention (14 lessons) were coded for each implementer-child dyad on Adherence (content) and Competence (quality). Using multi-level modeling we examined how much of the variance in the fidelity measures was attributed to implementer and to the child within implementer. Both measures had large and significant variance accounted for by implementer (Competence, 68%; Adherence, 41%); child within implementer did not account for significant variance indicating that ratings reflected stable qualities of the implementer rather than the child. Raw Adherence and Competence scores shared 46% of variance (r = .68). Controlling for baseline differences and age, the amount (Adherence) and quality (Competence) of program delivered predicted children’s enhanced response to the intervention on both child and parent reports after six months, but not on teacher report of externalizing behavior. Our findings support the use of multiple observations for measuring fidelity and that adherence and competence are important components of fidelity which could be assessed by many programs using these methods. PMID:24736951

The role of conduct disorder in the relationship between alcohol, nicotine and cannabis use disorders.

PubMed

Grant, J D; Lynskey, M T; Madden, P A F; Nelson, E C; Few, L R; Bucholz, K K; Statham, D J; Martin, N G; Heath, A C; Agrawal, A

2015-12-01

Genetic influences contribute significantly to co-morbidity between conduct disorder and substance use disorders. Estimating the extent of overlap can assist in the development of phenotypes for genomic analyses. Multivariate quantitative genetic analyses were conducted using data from 9577 individuals, including 3982 complete twin pairs and 1613 individuals whose co-twin was not interviewed (aged 24-37 years) from two Australian twin samples. Analyses examined the genetic correlation between alcohol dependence, nicotine dependence and cannabis abuse/dependence and the extent to which the correlations were attributable to genetic influences shared with conduct disorder. Additive genetic (a(2) = 0.48-0.65) and non-shared environmental factors explained variance in substance use disorders. Familial effects on conduct disorder were due to additive genetic (a(2) = 0.39) and shared environmental (c(2) = 0.15) factors. All substance use disorders were influenced by shared genetic factors (rg = 0.38-0.56), with all genetic overlap between substances attributable to genetic influences shared with conduct disorder. Genes influencing individual substance use disorders were also significant, explaining 40-73% of the genetic variance per substance. Among substance users in this sample, the well-documented clinical co-morbidity between conduct disorder and substance use disorders is primarily attributable to shared genetic liability. Interventions targeted at generally reducing deviant behaviors may address the risk posed by this shared genetic liability. However, there is also evidence for genetic and environmental influences specific to each substance. The identification of these substance-specific risk factors (as well as potential protective factors) is critical to the future development of targeted treatment protocols.

Accounting for female space sharing in St. Kilda Soay sheep (Ovis aries) results in little change in heritability estimates.

PubMed

Regan, C E; Pilkington, J G; Bérénos, C; Pemberton, J M; Smiseth, P T; Wilson, A J

2017-01-01

When estimating heritability in free-living populations, it is common practice to account for common environment effects, because of their potential to generate phenotypic covariance among relatives thereby biasing heritability estimates. In quantitative genetic studies of natural populations, however, philopatry, which results in relatives being clustered in space, is rarely accounted for. The two studies that have been carried out so far suggest absolute declines in heritability estimates of up to 43% when accounting for space sharing by relatives. However, due to methodological limitations these estimates may not be representative. We used data from the St. Kilda Soay sheep population to estimate heritabilities with and without accounting for space sharing for five traits for which there is evidence for additive genetic variance (birthweight, birth date, lamb August weight, and female post-mortem jaw and metacarpal length). We accounted for space sharing by related females by separately incorporating spatial autocorrelation, and a home range similarity matrix. Although these terms accounted for up to 18% of the variance in these traits, heritability estimates were only reduced by up to 7%. Our results suggest that the bias caused by not accounting for space sharing may be lower than previously thought. This suggests that philopatry does not inevitably lead to a large bias if space sharing by relatives is not accounted for. We hope our work stimulates researchers to model shared space when relatives in their study population share space, as doing so will enable us to better understand when bias may be of particular concern. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

The effect of the Statewide Sharing variance on geographic disparity in kidney transplantation in the United States.

PubMed

Davis, Ashley E; Mehrotra, Sanjay; Kilambi, Vikram; Kang, Joseph; McElroy, Lisa; Lapin, Brittany; Holl, Jane; Abecassis, Michael; Friedewald, John J; Ladner, Daniela P

2014-08-07

The Statewide Sharing variance to the national kidney allocation policy allocates kidneys not used within the procuring donor service area (DSA), first within the state, before the kidneys are offered regionally and nationally. Tennessee and Florida implemented this variance. Known geographic differences exist between the 58 DSAs, in direct violation of the Final Rule stipulated by the US Department of Health and Human Services. This study examined the effect of Statewide Sharing on geographic allocation disparity over time between DSAs within Tennessee and Florida and compared them with geographic disparity between the DSAs within a state for all states with more than one DSA (California, New York, North Carolina, Ohio, Pennsylvania, Texas, and Wisconsin). A retrospective analysis from 1987 to 2009 was conducted using Organ Procurement and Transplant Network data. Five previously used indicators for geographic allocation disparity were applied: deceased-donor kidney transplant rates, waiting time to transplantation, cumulative dialysis time at transplantation, 5-year graft survival, and cold ischemic time. Transplant rates, waiting time, dialysis time, and graft survival varied greatly between deceased-donor kidney recipients in DSAs in all states in 1987. After implementation of Statewide Sharing in 1992, disparity indicators decreased by 41%, 36%, 31%, and 9%, respectively, in Tennessee and by 28%, 62%, 34%, and 19%, respectively in Florida, such that the geographic allocation disparity in Tennessee and Florida almost completely disappeared. Statewide kidney allocations incurred 7.5 and 5 fewer hours of cold ischemic time in Tennessee and Florida, respectively. Geographic disparity between DSAs in all the other states worsened or improved to a lesser degree. As sweeping changes to the kidney allocation system are being discussed to alleviate geographic disparity--changes that are untested run the risk of unintended consequences--more limited changes, such as Statewide Sharing, should be further studied and considered. Copyright © 2014 by the American Society of Nephrology.

Combat Exposure Severity as a Moderator of Genetic and Environmental Liability to Posttraumatic Stress Disorder

PubMed Central

Wolf, Erika J.; Mitchell, Karen S.; Koenen, Karestan C.; Miller, Mark W.

2014-01-01

Background Twin studies of veterans and adults suggest that approximately 30–46% of the variance in posttraumatic stress disorder (PTSD) is attributable to genetic factors. The remaining variance is attributable to the non-shared environment, which, by definition, includes combat exposure. This study used a gene by measured environment twin design to examine if the effect of genetic and environmental factors that contribute to the etiology PTSD were dependent on level of combat exposure. Methods The sample was drawn from the Vietnam Era Twin Registry and included 620 male-male twin pairs who served in the U.S. Military in South East Asia during the Vietnam War era. Analyses were based on data from a clinical diagnostic interview of lifetime PTSD symptoms and a self-report measure of combat exposure. Results Biometric modeling revealed that the effect of genetic and non-shared environment factors on PTSD varied as a function of level of combat exposure such that the association between these factors and PTSD was stronger at higher levels of combat exposure. Conclusions Combat exposure may act as a catalyst that augments the impact of hereditary and environmental contributions to PTSD. Individuals with the greatest exposure to combat trauma were at increased risk for PTSD as a function of both genetic and other environmental factors. Additional work is needed to determine the biological and environmental mechanisms driving these associations. PMID:24001428

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.

Are There Common Familial Influences for Major Depressive Disorder and an Overeating-Binge Eating Dimension in both European-American and African-American Female Twins?

PubMed Central

Munn-Chernoff, Melissa A.; Grant, Julia D.; Agrawal, Arpana; Koren, Rachel; Glowinski, Anne L.; Bucholz, Kathleen K.; Madden, Pamela A. F.; Heath, Andrew C.; Duncan, Alexis E.

2014-01-01

Objective Although prior studies have demonstrated that depression is associated with an overeating-binge eating dimension (OE-BE), phenotypically, little research has investigated whether familial factors contribute to the co-occurrence of these phenotypes, especially in community samples with multiple racial/ethnic groups. We examined the extent to which familial (i.e., genetic and shared environmental) influences overlapped between Major Depressive Disorder (MDD) and OE-BE in a population-based sample and whether these influences were similar across racial/ethnic groups Method Participants included 3226 European-American (EA) and 550 African-American (AA) young adult women from the Missouri Adolescent Female Twin Study. An adaptation of the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was administered to assess lifetime DSM-IV MDD and OE-BE. Quantitative genetic modeling was used to estimate familial influences between both phenotypes; all models controlled for age. Results The best-fitting model, which combined racial/ethnic groups, found that additive genetic influences accounted for 44% (95% CI: 34%, 53%) of the MDD variance and 40% (25%, 54%) for OE-BE, with the remaining variances due to non-shared environmental influences. Genetic overlap was substantial (rg = .61 [.39, .85]); non-shared environmental influences on MDD and OE-BE overlapped weakly (re = .26 [.09, .42]) Discussion Results suggest that common familial influences underlie MDD and OE-BE, and the magnitude of familial influences contributing to the comorbidity between MDD and OE-BE is similar between EA and AA women. If racial/ethnic differences truly exist, then larger sample sizes may be needed to fully elucidate familial risk for comorbid MDD and OE-BE across these groups. PMID:24659561

Investment strategy due to the minimization of portfolio noise level by observations of coarse-grained entropy

NASA Astrophysics Data System (ADS)

Urbanowicz, Krzysztof; Hołyst, Janusz A.

2004-12-01

Using a recently developed method of noise level estimation that makes use of properties of the coarse-grained entropy, we have analyzed the noise level for the Dow Jones index and a few stocks from the New York Stock Exchange. We have found that the noise level ranges from 40% to 80% of the signal variance. The condition of a minimal noise level has been applied to construct optimal portfolios from selected shares. We show that the implementation of a corresponding threshold investment strategy leads to positive returns for historical data.

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins.

PubMed

Silberg, Judy L; Gillespie, Nathan; Moore, Ashlee A; Eaves, Lindon J; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-04-01

Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children.

Separating Common from Unique Variance Within Emotional Distress: An Examination of Reliability and Relations to Worry.

PubMed

Marshall, Andrew J; Evanovich, Emma K; David, Sarah Jo; Mumma, Gregory H

2018-01-17

High comorbidity rates among emotional disorders have led researchers to examine transdiagnostic factors that may contribute to shared psychopathology. Bifactor models provide a unique method for examining transdiagnostic variables by modelling the common and unique factors within measures. Previous findings suggest that the bifactor model of the Depression Anxiety and Stress Scale (DASS) may provide a method for examining transdiagnostic factors within emotional disorders. This study aimed to replicate the bifactor model of the DASS, a multidimensional measure of psychological distress, within a US adult sample and provide initial estimates of the reliability of the general and domain-specific factors. Furthermore, this study hypothesized that Worry, a theorized transdiagnostic variable, would show stronger relations to general emotional distress than domain-specific subscales. Confirmatory factor analysis was used to evaluate the bifactor model structure of the DASS in 456 US adult participants (279 females and 177 males, mean age 35.9 years) recruited online. The DASS bifactor model fitted well (CFI = 0.98; RMSEA = 0.05). The General Emotional Distress factor accounted for most of the reliable variance in item scores. Domain-specific subscales accounted for modest portions of reliable variance in items after accounting for the general scale. Finally, structural equation modelling indicated that Worry was strongly predicted by the General Emotional Distress factor. The DASS bifactor model is generalizable to a US community sample and General Emotional Distress, but not domain-specific factors, strongly predict the transdiagnostic variable Worry.

Analysis of mitochondrial genetic diversity of Ustilago maydis in Mexico.

PubMed

Jiménez-Becerril, María F; Hernández-Delgado, Sanjuana; Solís-Oba, Myrna; González Prieto, Juan M

2018-01-01

The current understanding of the genetic diversity of the phytopathogenic fungus Ustilago maydis is limited. To determine the genetic diversity and structure of U. maydis, 48 fungal isolates were analyzed using mitochondrial simple sequence repeats (SSRs). Tumours (corn smut or 'huitlacoche') were collected from different Mexican states with diverse environmental conditions. Using bioinformatic tools, five microsatellites were identified within intergenic regions of the U. maydis mitochondrial genome. SSRMUM4 was the most polymorphic marker. The most common repeats were hexanucleotides. A total of 12 allelic variants were identified, with a mean of 2.4 alleles per locus. An estimate of the genetic diversity using analysis of molecular variance (AMOVA) revealed that the highest variance component is within states (84%), with moderate genetic differentiation between states (16%) (F ST  = 0.158). A dendrogram generated using the unweighted paired-grouping method with arithmetic averages (UPGMA) and the Bayesian analysis of population structure grouped the U. maydis isolates into two subgroups (K = 2) based on their shared SSRs.

Genetic and environmental contributions to body mass index: comparative analysis of monozygotic twins, dizygotic twins and same-age unrelated siblings.

PubMed

Segal, N L; Feng, R; McGuire, S A; Allison, D B; Miller, S

2009-01-01

Earlier studies have established that a substantial percentage of variance in obesity-related phenotypes is explained by genetic components. However, only one study has used both virtual twins (VTs) and biological twins and was able to simultaneously estimate additive genetic, non-additive genetic, shared environmental and unshared environmental components in body mass index (BMI). Our current goal was to re-estimate four components of variance in BMI, applying a more rigorous model to biological and virtual multiples with additional data. Virtual multiples share the same family environment, offering unique opportunities to estimate common environmental influence on phenotypes that cannot be separated from the non-additive genetic component using only biological multiples. Data included 929 individuals from 164 monozygotic twin pairs, 156 dizygotic twin pairs, five triplet sets, one quadruplet set, 128 VT pairs, two virtual triplet sets and two virtual quadruplet sets. Virtual multiples consist of one biological child (or twins or triplets) plus one same-aged adoptee who are all raised together since infancy. We estimated the additive genetic, non-additive genetic, shared environmental and unshared random components in BMI using a linear mixed model. The analysis was adjusted for age, age(2), age(3), height, height(2), height(3), gender and race. Both non-additive genetic and common environmental contributions were significant in our model (P-values<0.0001). No significant additive genetic contribution was found. In all, 63.6% (95% confidence interval (CI) 51.8-75.3%) of the total variance of BMI was explained by a non-additive genetic component, 25.7% (95% CI 13.8-37.5%) by a common environmental component and the remaining 10.7% by an unshared component. Our results suggest that genetic components play an essential role in BMI and that common environmental factors such as diet or exercise also affect BMI. This conclusion is consistent with our earlier study using a smaller sample and shows the utility of virtual multiples for separating non-additive genetic variance from common environmental variance.

Facts about Noroviruses on Cruise Ships

MedlinePlus

... Cruise Tips for Healthy Cruising Related Resources Cruise Ship Inspection Scores & Information Inspection Scores Cruise Line Directory ... Variances About Inspections Facts About Noroviruses on Cruise Ships Recommend on Facebook Tweet Share Compartir Noroviruses People ...

The effect of Think Pair Share (TPS) using scientific approach on students’ self-confidence and mathematical problem-solving

NASA Astrophysics Data System (ADS)

Rifa’i, A.; Lestari, H. P.

2018-03-01

This study was designed to know the effects of Think Pair Share using Scientific Approach on students' self-confidence and mathematical problem-solving. Quasi-experimental with pre-test post-test non-equivalent group method was used as a basis for design this study. Self-confidence questionnaire and problem-solving test have been used for measurement of the two variables. Two classes of the first grade in religious senior high school (MAN) in Indonesia were randomly selected for this study. Teaching sequence and series from mathematics book at control group in the traditional way and at experiment group has been in TPS using scientific approach learning method. For data analysis regarding students’ problem-solving skill and self-confidence, One-Sample t-Test, Independent Sample t-Test, and Multivariate of Variance (MANOVA) were used. The results showed that (1) TPS using a scientific approach and traditional learning had positive effects (2) TPS using scientific approach learning in comparative with traditional learning had a more significant effect on students’ self-confidence and problem-solving skill.

Value at Risk on Composite Price Share Index Stock Data

NASA Astrophysics Data System (ADS)

Oktaviarina, A.

2018-01-01

The financial servicest authority was declared Let’s Save Campaign on n commemoration of the World Savings Day that falls on this day, October 31, 2016. The activity was greeted enthusiastically by Indonesia Stock Exchange by taking out the slogan Let’s Save The Stocks. Stock is a form of investment that is expected to benefit in the future despite has risks. Value at Risk (VaR) is a method that can measure how much the risk of a financial investment. Composite Stock Price Indeks is the stock price index used by Indonesia Stock Exchange as stock volatility benchmarks in Indonesia. This study aimed to estimate Value at Risk (VaR) on closing price Composite Price Share Index Stock data on the period 20 September 2016 until 20 September 2017. Box-Pierce test results p value=0.9528 which is greater than a, that shows homoskedasticity. Value at Risk (VaR) with Variance Covariance Method is Rp.3.054.916,07 which means with 99% confindence interval someone who invests Rp.100.000.000,00 will get Rp.3.054.916,07 as a maximum loss.

Nonsymbolic number and cumulative area representations contribute shared and unique variance to symbolic math competence

PubMed Central

Lourenco, Stella F.; Bonny, Justin W.; Fernandez, Edmund P.; Rao, Sonia

2012-01-01

Humans and nonhuman animals share the capacity to estimate, without counting, the number of objects in a set by relying on an approximate number system (ANS). Only humans, however, learn the concepts and operations of symbolic mathematics. Despite vast differences between these two systems of quantification, neural and behavioral findings suggest functional connections. Another line of research suggests that the ANS is part of a larger, more general system of magnitude representation. Reports of cognitive interactions and common neural coding for number and other magnitudes such as spatial extent led us to ask whether, and how, nonnumerical magnitude interfaces with mathematical competence. On two magnitude comparison tasks, college students estimated (without counting or explicit calculation) which of two arrays was greater in number or cumulative area. They also completed a battery of standardized math tests. Individual differences in both number and cumulative area precision (measured by accuracy on the magnitude comparison tasks) correlated with interindividual variability in math competence, particularly advanced arithmetic and geometry, even after accounting for general aspects of intelligence. Moreover, analyses revealed that whereas number precision contributed unique variance to advanced arithmetic, cumulative area precision contributed unique variance to geometry. Taken together, these results provide evidence for shared and unique contributions of nonsymbolic number and cumulative area representations to formally taught mathematics. More broadly, they suggest that uniquely human branches of mathematics interface with an evolutionarily primitive general magnitude system, which includes partially overlapping representations of numerical and nonnumerical magnitude. PMID:23091023

Equality in Educational Policy and the Heritability of Educational Attainment

PubMed Central

Colodro-Conde, Lucía; Rijsdijk, Frühling; Tornero-Gómez, María J.; Sánchez-Romera, Juan F.; Ordoñana, Juan R.

2015-01-01

Secular variation in the heritability of educational attainment are proposed to be due to the implementation of more egalitarian educational policies leading to increased equality in educational opportunities in the second part of the 20th century. The action of effect is hypothesized to be a decrease of shared environmental (e.g., family socioeconomic status or parents’ education) influences on educational attainment, giving more room for genetic differences between individuals to impact on the variation of the trait. However, this hypothesis has not yet found consistent evidence. Support for this effect relies mainly on comparisons between countries adopting different educational systems or between different time periods within a country reflecting changes in general policy. Using a population-based sample of 1271 pairs of adult twins, we analyzed the effect of the introduction of a specific educational policy in Spain in 1970. The shared-environmental variance decreased, leading to an increase in heritability in the post-reform cohort (44 vs. 67%) for males. Unstandardized estimates of genetic variance were of a similar magnitude (.56 vs. .57) between cohorts, while shared environmental variance decreased from .56 to .04. Heritability remained in the same range for women (40 vs. 34%). Our results support the role of educational policy in affecting the relative weight of genetic and environmental factors on educational attainment, such that increasing equality in educational opportunities increases heritability estimates by reducing variation of non-genetic familial origin. PMID:26618539

Shared effects of organic microcontaminants and environmental stressors on biofilms and invertebrates in impaired rivers.

PubMed

Sabater, S; Barceló, D; De Castro-Català, N; Ginebreda, A; Kuzmanovic, M; Petrovic, M; Picó, Y; Ponsatí, L; Tornés, E; Muñoz, I

2016-03-01

Land use type, physical and chemical stressors, and organic microcontaminants were investigated for their effects on the biological communities (biofilms and invertebrates) in several Mediterranean rivers. The diversity of invertebrates, and the scores of the first principal component of a PCA performed with the diatom communities were the best descriptors of the distribution patterns of the biological communities against the river stressors. These two metrics decreased according to the progressive site impairment (associated to higher area of agricultural and urban-industrial, high water conductivity, higher dissolved organic carbon and dissolved inorganic nitrogen concentrations, and higher concentration of organic microcontaminants, particularly pharmaceutical and industrial compounds). The variance partition analyses (RDAs) attributed the major share (10%) of the biological communities' response to the environmental stressors (nutrients, altered discharge, dissolved organic matter), followed by the land use occupation (6%) and of the organic microcontaminants (2%). However, the variance shared by the three groups of descriptors was very high (41%), indicating that their simultaneous occurrence determined most of the variation in the biological communities. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Causes of individual differences in adolescent optimism: a study in Dutch twins and their siblings.

PubMed

Mavioğlu, Rezan Nehir; Boomsma, Dorret I; Bartels, Meike

2015-11-01

The aim of this study was to investigate the degree to which genetic and environmental influences affect variation in adolescent optimism. Optimism (3 items and 6 items approach) and pessimism were assessed by the Life Orientation Test-Revised (LOT-R) in 5,187 adolescent twins and 999 of their non-twin siblings from the Netherlands Twin Register (NTR). Males reported significantly higher optimism scores than females, while females score higher on pessimism. Genetic structural equation modeling revealed that about one-third of the variance in optimism and pessimism was due to additive genetic effects, with the remaining variance being explained by non-shared environmental effects. A bivariate correlated factor model revealed two dimensions with a genetic correlation of -.57 (CI -.67, -.47), while the non-shared environmental correlation was estimated to be -.21 (CI -.25, -.16). Neither an effect of shared environment, non-additive genetic influences, nor quantitative sex differences was found for both dimensions. This result indicates that individual differences in adolescent optimism are mainly accounted for by non-shared environmental factors. These environmental factors do not contribute to the similarity of family members, but to differences between them. Familial resemblance in optimism and pessimism assessed in adolescents is fully accounted for by genetic overlap between family members.

Effect of Physics Problem Solving on Structures Schemes and Knowledge Associations

NASA Astrophysics Data System (ADS)

Setyowidodo, I.; Jatmiko, B.; Susantini, E.; Widodo, S.; Shofwan, A.

2017-09-01

This study aims to develop learners’ thinking structures through associations, case based, and schematic method so that different knowledge structures have a role in influencing the structure of creative thinking. The learners have low mastery of physics materials since they are not given sufficient opportunity to build their own knowledge. They should be directed to approach each new problem or task with their prior knowledge, assimilate new information, and construct their own understanding. The design of this research was a quasi-experiment using purposive sampling. Data were analyzed using variance analysis. The design of this research was a quasi-experiment using purposive sampling. Data were analyzed using variance analysis. The learning process of problemsolving consists of: 1) identifying problems, 2) planning projects, 3) creating projects, 4) presenting projects, and 5) evaluating projects. From the results of this research, it can be concluded that problem-solving method can provide strong supports in developing the learners’ creative thinking skills as they can share their knowledge and interact with their friends and the environment. This learning activity also constitutes an appropriate technique to help the learners to develop problem solving knowledge and skills.

Band selection method based on spectrum difference in targets of interest in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xiaohan; Yang, Guang; Yang, Yongbo; Huang, Junhua

2016-10-01

While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.

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.

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning

PubMed Central

Patten, Hannah

2017-01-01

Purpose This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method Fifty children, with a mean age of 8 years (range 5–12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Results Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. Conclusions These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed. PMID:28241284

The Fukushima-137Cs deposition case study: properties of the multi-model ensemble.

PubMed

Solazzo, E; Galmarini, S

2015-01-01

In this paper we analyse the properties of an eighteen-member ensemble generated by the combination of five atmospheric dispersion modelling systems and six meteorological data sets. The models have been applied to the total deposition of (137)Cs, following the nuclear accident of the Fukushima power plant in March 2011. Analysis is carried out with the scope of determining whether the ensemble is reliable, sufficiently diverse and if its accuracy and precision can be improved. Although ensemble practice is becoming more and more popular in many geophysical applications, good practice guidelines are missing as to how models should be combined for the ensembles to offer an improvement over single model realisations. We show that the ensemble of models share large portions of bias and variance and make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble mean with the advantage of being poorly correlated, allowing to save computational resources and reduce noise (and thus improving accuracy). We further propose and discuss two methods for selecting subsets of skilful and diverse members, and prove that, in the contingency of the present analysis, their mean outscores the full ensemble mean in terms of both accuracy (error) and precision (variance). Copyright © 2014. Published by Elsevier Ltd.

Impact of “Sick” and “Recovery” Roles on Brain Injury Rehabilitation Outcomes

PubMed Central

Barclay, David A.

2012-01-01

This study utilizes a multivariate, correlational, expost facto research design to examine Parsons' “sick role” as a dynamic, time-sensitive process of “sick role” and “recovery role” and the impact of this process on goal attainment (H1) and psychosocial distress (H2) of adult survivors of acquired brain injury. Measures used include the Brief Symptom Inventory-18, a Goal Attainment Scale, and an original instrument to measure sick role process. 60 survivors of ABI enrolled in community reentry rehabilitation participated. Stepwise regression analyses did not fully support the multivariate hypotheses. Two models emerged from the stepwise analyses. Goal attainment, gender, and postrehab responsibilities accounted for 40% of the shared variance of psychosocial distress. Anxiety and depression accounted for 22% of the shared variance of goal attainment with anxiety contributing to the majority of the explained variance. Bivariate analysis found sick role variables, anxiety, somatization, depression, gender, and goal attainment as significant. The study has implications for ABI rehabilitation in placing greater emphasis on sick role processes, anxiety, gender, and goal attainment in guiding program planning and future research with survivors of ABI. PMID:23119164

Interlaboratory comparison of red-cell ATP, 2,3-diphosphoglycerate and haemolysis measurements.

PubMed

Hess, J R; Kagen, L R; van der Meer, P F; Simon, T; Cardigan, R; Greenwalt, T J; AuBuchon, J P; Brand, A; Lockwood, W; Zanella, A; Adamson, J; Snyder, E; Taylor, H L; Moroff, G; Hogman, C

2005-07-01

Red blood cell (RBC) storage systems are licensed based on their ability to prevent haemolysis and maintain RBC 24-h in vivo recovery. Preclinical testing includes measurement of RBC ATP as a surrogate for recovery, 2,3-diphosphoglycerate (DPG) as a surrogate for oxygen affinity, and free haemoglobin, which is indicative of red cell lysis. The reproducibility of RBC ATP, DPG and haemolysis measurements between centres was investigated. Five, 4-day-old leucoreduced AS-1 RBC units were pooled, aliquotted and shipped on ice to 14 laboratories in the USA and European Union (EU). Each laboratory was to sample the bag twice on day 7 and measure RBC ATP, DPG, haemoglobin and haemolysis levels in triplicate on each sample. The variability of results was assessed by using coefficients of variation (CV) and analysis of variance. Measurements were highly reproducible at the individual sites. Between sites, the CV was 16% for ATP, 35% for DPG, 2% for total haemoglobin and 54% for haemolysis. For ATP and total haemoglobin, 94 and 80% of the variance in measurements was contributed by differences between sites, and more than 80% of the variance for DPG and haemolysis measurements came from markedly discordant results from three sites and one site, respectively. In descending order, mathematical errors, unvalidated analytical methods, a lack of shared standards and fluid handling errors contributed to the variability in measurements from different sites. While the methods used by laboratories engaged in RBC storage system clinical trials demonstrated good precision, differences in results between laboratories may hinder comparative analysis. Efforts to improve performance should focus on developing robust methods, especially for measuring RBC ATP.

Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

PubMed

Pereira, Ana Santos; Dâmaso-Rodrigues, Maria Luísa; Amorim, Ana; Daam, Michiel A; Cerejeira, Maria José

2018-06-16

Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.

Cortisol Secretion and Change in Sleep Problems in Early Childhood: Moderation by Maternal Overcontrol

PubMed Central

Kiel, Elizabeth J.; Hummel, Alexandra C.; Luebbe, Aaron M.

2015-01-01

Childhood sleep problems are prevalent and relate to a wide range of negative psychological outcomes. However, it remains unclear how biological processes, such as HPA activity, may predict sleep problems over time in childhood in the context of certain parenting environments. Fifty-one mothers and their 18–20 month-old toddlers participated in a short-term longitudinal study assessing how shared variance among morning levels, diurnal change, and nocturnal change in toddlers’ cortisol secretion predicted change in sleep problems in the context of maternal overprotection and critical control. A composite characterized by low variability in, and, to a lesser extent, high morning values of cortisol, predicted increasing sleep problems from age 2 to age 3 when mothers reported high critical control. Results suggest value in assessing shared variance among different indices of cortisol secretion patterns and the interaction between cortisol and the environment in predicting sleep problems in early childhood. PMID:25766262

Familial Resemblance in Dietary Intakes of Children, Adolescents, and Parents: Does Dietary Quality Play a Role?

PubMed Central

Bogl, Leonie H.; Silventoinen, Karri; Intemann, Timm; Michels, Nathalie; Molnár, Dénes; Page, Angie S.; Papoutsou, Stalo; Pigeot, Iris; Russo, Paola; Veidebaum, Toomas; Moreno, Luis A.; Lissner, Lauren

2017-01-01

Information on familial resemblance is important for the design of effective family-based interventions. We aimed to quantify familial correlations and estimate the proportion of variation attributable to genetic and shared environmental effects (i.e., familiality) for dietary intake variables and determine whether they vary by generation, sex, dietary quality, or by the age of the children. The study sample consisted of 1435 families (1007 mothers, 438 fathers, 1035 daughters, and 1080 sons) from the multi-center I.Family study. Dietary intake was assessed in parents and their 2–19 years old children using repeated 24-h dietary recalls, from which the usual energy and food intakes were estimated with the U.S. National Cancer Institute Method. Food items were categorized as healthy or unhealthy based on their sugar, fat, and fiber content. Interclass and intraclass correlations were calculated for relative pairs. Familiality was estimated using variance component methods. Parent–offspring (r = 0.11–0.33), sibling (r = 0.21–0.43), and spouse (r = 0.15–0.33) correlations were modest. Parent–offspring correlations were stronger for the intake of healthy (r = 0.33) than unhealthy (r = 0.10) foods. Familiality estimates were 61% (95% CI: 54–68%) for the intake of fruit and vegetables and the sum of healthy foods and only 30% (95% CI: 23–38%) for the sum of unhealthy foods. Familial factors explained a larger proportion of the variance in healthy food intake (71%; 95% CI: 62–81%) in younger children below the age of 11 than in older children equal or above the age of 11 (48%; 95% CI: 38–58%). Factors shared by family members such as genetics and/or the shared home environment play a stronger role in shaping children’s intake of healthy foods than unhealthy foods. This suggests that family-based interventions are likely to have greater effects when targeting healthy food choices and families with younger children, and that other sorts of intervention are needed to address the intake of unhealthy foods by children. PMID:28817074

Familial Resemblance in Dietary Intakes of Children, Adolescents, and Parents: Does Dietary Quality Play a Role?

PubMed

Bogl, Leonie H; Silventoinen, Karri; Hebestreit, Antje; Intemann, Timm; Williams, Garrath; Michels, Nathalie; Molnár, Dénes; Page, Angie S; Pala, Valeria; Papoutsou, Stalo; Pigeot, Iris; Reisch, Lucia A; Russo, Paola; Veidebaum, Toomas; Moreno, Luis A; Lissner, Lauren; Kaprio, Jaakko

2017-08-17

Information on familial resemblance is important for the design of effective family-based interventions. We aimed to quantify familial correlations and estimate the proportion of variation attributable to genetic and shared environmental effects (i.e., familiality) for dietary intake variables and determine whether they vary by generation, sex, dietary quality, or by the age of the children. The study sample consisted of 1435 families (1007 mothers, 438 fathers, 1035 daughters, and 1080 sons) from the multi-center I.Family study. Dietary intake was assessed in parents and their 2-19 years old children using repeated 24-h dietary recalls, from which the usual energy and food intakes were estimated with the U.S. National Cancer Institute Method. Food items were categorized as healthy or unhealthy based on their sugar, fat, and fiber content. Interclass and intraclass correlations were calculated for relative pairs. Familiality was estimated using variance component methods. Parent-offspring ( r = 0.11-0.33), sibling ( r = 0.21-0.43), and spouse ( r = 0.15-0.33) correlations were modest. Parent-offspring correlations were stronger for the intake of healthy ( r = 0.33) than unhealthy ( r = 0.10) foods. Familiality estimates were 61% (95% CI: 54-68%) for the intake of fruit and vegetables and the sum of healthy foods and only 30% (95% CI: 23-38%) for the sum of unhealthy foods. Familial factors explained a larger proportion of the variance in healthy food intake (71%; 95% CI: 62-81%) in younger children below the age of 11 than in older children equal or above the age of 11 (48%; 95% CI: 38-58%). Factors shared by family members such as genetics and/or the shared home environment play a stronger role in shaping children's intake of healthy foods than unhealthy foods. This suggests that family-based interventions are likely to have greater effects when targeting healthy food choices and families with younger children, and that other sorts of intervention are needed to address the intake of unhealthy foods by children.

Predictors of Weapon Carrying in Youth Attending Drop-in Centers

PubMed Central

Blumberg, Elaine J.; Liles, Sandy; Kelley, Norma J.; Hovell, Melbourne F.; Bousman, Chad A.; Shillington, Audrey M.; Ji, Ming; Clapp, John

2012-01-01

Objective To test and compare 2 predictive models of weapon carrying in youth (n=308) recruited from 4 drop-in centers in San Diego and Imperial counties. Methods Both models were based on the Behavioral Ecological Model (BEM). Results The first and second models significantly explained 39% and 53% of the variance in weapon carrying, respectively, and both full models shared the significant predictors of being black(−), being Hispanic (−), peer modeling of weapon carrying/jail time(+), and school suspensions(+). Conclusions Results suggest that the BEM offers a generalizable conceptual model that may inform prevention strategies for youth at greatest risk of weapon carrying. PMID:19320622

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.

Gender Differences in Marital Status Moderation of Genetic and Environmental Influences on Subjective Health.

PubMed

Finkel, Deborah; Franz, Carol E; Horwitz, Briana; Christensen, Kaare; Gatz, Margaret; Johnson, Wendy; Kaprio, Jaako; Korhonen, Tellervo; Niederheiser, Jenae; Petersen, Inge; Rose, Richard J; Silventoinen, Karri

2015-10-14

From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health.

Genetic and environmental variance in content dimensions of the MMPI.

PubMed

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

PubMed

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

PubMed Central

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181

Ex Post Facto Monte Carlo Variance Reduction

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

Booth, Thomas E.

The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance inmore » a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.« less

The genetic relationship between cannabis and tobacco cigarette use in European- and African-American female twins and siblings.

PubMed

Agrawal, Arpana; Grant, Julia D; Lynskey, Michael T; Madden, Pamela A F; Heath, Andrew C; Bucholz, Kathleen K; Sartor, Carolyn E

2016-06-01

Use of cigarettes and cannabis frequently co-occurs. We examine the role of genetic and environmental influences on variation in and covariation between tobacco cigarette and cannabis use across European-American (EA) and African-American (AA) women. Data on lifetime cannabis and cigarette use were drawn from interviews of 956 AA and 3557 EA young adult female twins and non-twin same sex female full siblings. Twin modeling was used to decompose variance in and covariance between cigarette and cannabis use into additive genetic, shared, special twin and non-shared environmental sources. Cigarette use was more common in EAs (75.3%, 95% C.I. 73.8-76.7%) than AAs (64.2%, 95% C.I. 61.2-67.2%) while cannabis use was marginally more commonly reported by AAs (55.5%, 95% C.I. 52.5-58.8%) than EAs (52.4%, 95% C.I. 50.7-54.0%). Additive genetic factors were responsible for 43-66% of the variance in cigarette and cannabis use. Broad shared environmental factors (shared+special twin) played a more significant role in EA (23-29%) than AA (2-15%) women. In AA women, the influence of non-shared environment was more pronounced (42-45% vs. 11-19% in EA women). There was strong evidence for the same familial influences underlying use of both substances (rA=0.82-0.89; rC+T=0.70-0.75). Non-shared environmental factors were also correlated but less so (rE=0.48-0.66). No racial/ethnic differences were apparent in these sources of covariation. Heritability of cigarette and cannabis use is comparable across racial/ethnic groups. Differences in the contribution of shared and non-shared environmental influences indicate that different factors may shape substance use in EA and AA women. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Intolerance for discomfort among smokers: comparison of smoking-specific and non-specific measures to smoking history and patterns.

PubMed

Sirota, Alan D; Rohsenow, Damaris J; Dolan, Sara L; Martin, Rosemarie A; Kahler, Christopher W

2013-03-01

Intolerance of discomfort associated with recent smoking cessation has been studied with only one smoking-specific questionnaire. The present study investigates the extent to which the previously validated Intolerance for Smoking Abstinence Discomfort Questionnaire (IDQ-S) scales share variance with (a) laboratory measures of distress tolerance (Paced Serial Addition Task and a breath-holding task) that have themselves been validated against smoking history, (b) the cold pressor task (not previously validated for smoking), and (c) an anxiety sensitivity questionnaire previously used for a similar purpose. The study then tests the hypothesis that the IDQ-S scales will have a higher correlation with smoking rate and dependence and with number and length of past smoking cessation attempts than with anxiety sensitivity or behavioral distress tolerance tasks do, since those measures are not smoking-specific. Sixty daily smokers recruited from the community completed the measures. The behavioral tasks and anxiety sensitivity shared little common variance. Anxiety sensitivity correlated more highly with IDQ-S than did the behavioral tasks but only 27% of variance was shared with the IDQ-S Withdrawal Intolerance; no distress tolerance measure correlated significantly with the IDQ-S Lack of Cognitive Coping scale. Only the IDQ-S scales correlated significantly with nicotine dependence, rate and past cessation: Withdrawal Intolerance with nicotine dependence and rate, and Lack of Cognitive Coping with fewer quit attempts. The smoking-specific measure of intolerance for discomfort may be more useful in smoking research than the less specific measures of distress tolerance. Published by Elsevier Ltd.

Statistical study of EBR-II fuel elements manufactured by the cold line at Argonne-West and by Atomics International

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

Harkness, A. L.

1977-09-01

Nine elements from each batch of fuel elements manufactured for the EBR-II reactor have been analyzed for /sup 235/U content by NDA methods. These values, together with those of the manufacturer, are used to estimate the product variance and the variances of the two measuring methods. These variances are compared with the variances computed from the stipulations of the contract. A method is derived for resolving the several variances into their within-batch and between-batch components. Some of these variance components have also been estimated by independent and more familiar conventional methods for comparison.

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

Assessing the uncertainty in a normal tissue complication probability difference (∆NTCP): radiation-induced liver disease (RILD) in liver tumour patients treated with proton vs X-ray therapy.

PubMed

Kobashi, Keiji; Prayongrat, Anussara; Kimoto, Takuya; Toramatsu, Chie; Dekura, Yasuhiro; Katoh, Norio; Shimizu, Shinichi; Ito, Yoichi M; Shirato, Hiroki

2018-03-01

Modern radiotherapy technologies such as proton beam therapy (PBT) permit dose escalation to the tumour and minimize unnecessary doses to normal tissues. To achieve appropriate patient selection for PBT, a normal tissue complication probability (NTCP) model can be applied to estimate the risk of treatment-related toxicity relative to X-ray therapy (XRT). A methodology for estimating the difference in NTCP (∆NTCP), including its uncertainty as a function of dose to normal tissue, is described in this study using the Delta method, a statistical method for evaluating the variance of functions, considering the variance-covariance matrix. We used a virtual individual patient dataset of radiation-induced liver disease (RILD) in liver tumour patients who were treated with XRT as a study model. As an alternative option for individual patient data, dose-bin data, which consists of the number of patients who developed toxicity in each dose level/bin and the total number of patients in that dose level/bin, are useful for multi-institutional data sharing. It provides comparable accuracy with individual patient data when using the Delta method. With reliable NTCP models, the ∆NTCP with uncertainty might potentially guide the use of PBT; however, clinical validation and a cost-effectiveness study are needed to determine the appropriate ∆NTCP threshold.

Family structure and posttraumatic stress reactions: a longitudinal study using multilevel analyses

PubMed Central

2011-01-01

Background There is limited research on the relevance of family structures to the development and maintenance of posttraumatic stress following disasters. We longitudinally studied the effects of marital and parental statuses on posttraumatic stress reactions after the 2004 Southeast Asian tsunami and whether persons in the same households had more shared stress reactions than others. Method The study included a tourist population of 641 Norwegian adult citizens, many of them from families with children. We measured posttraumatic stress symptoms with the Impact of Event Scale-Revised at 6 months and 2 years post-disaster. Analyses included multilevel methods with mixed effects models. Results Results showed that neither marital nor parental status was significantly related to posttraumatic stress. At both assessments, adults living in the same household reported levels of posttraumatic stress that were more similar to one another than adults who were not living together. Between households, disaster experiences were closely related to the variance in posttraumatic stress symptom levels at both assessments. Within households, however, disaster experiences were less related to the variance in symptom level at 2 years than at 6 months. Conclusions These results indicate that adult household members may influence one another's posttraumatic stress reactions as well as their interpretations of the disaster experiences over time. Our findings suggest that multilevel methods may provide important information about family processes after disasters. PMID:22171549

Monozygotic twin differences in school performance are stable and systematic.

PubMed

von Stumm, Sophie; Plomin, Robert

2018-06-19

School performance is one of the most stable and heritable psychological characteristics. Notwithstanding, monozygotic twins (MZ), who have identical genotypes, differ in school performance. These MZ differences result from non-shared environments that do not contribute to the similarity within twin pairs. Because to date few non-shared environmental factors have been reliably associated with MZ differences in school performance, they are thought to be idiosyncratic and due to chance, suggesting that the effect of non-shared environments on MZ differences are age- and trait-specific. In a sample of 2768 MZ twin pairs, we found first that MZ differences in school performance were moderately stable from age 12 through 16, with differences at the ages 12 and 14 accounting for 20% of the variance in MZ differences at age 16. Second, MZ differences in school performance correlated positively with MZ differences across 16 learning-related variables, including measures of intelligence, personality and school attitudes, with the twin who scored higher on one also scoring higher on the other measures. Finally, MZ differences in the 16 learning-related variables accounted for 22% of the variance in MZ differences in school performance at age 16. These findings suggest that, unlike for other psychological domains, non-shared environmental factors affect school performance in systematic ways that have long-term and generalist influence. Our findings should motivate the search for non-shared environmental factors responsible for the stable and systematic effects on children's differences in school performance. A video abstract of this article can be viewed at: https://youtu.be/0bw2Fl_HGq0. © 2018 John Wiley & Sons Ltd.

Shared genetic influences on negative emotionality and major depression/conduct disorder comorbidity.

PubMed

Tackett, Jennifer L; Waldman, Irwin D; Van Hulle, Carol A; Lahey, Benjamin B

2011-08-01

To investigate whether genetic contributions to major depressive disorder and conduct disorder comorbidity are shared with genetic influences on negative emotionality. Primary caregivers of 2,022 same- and opposite-sex twin pairs 6 to 18 years of age comprised a population-based sample. Participants were randomly selected across five regions in Tennessee, with stratification by age and geographic location. Face-to-face structured interviews were conducted with the primary caregiver of a representative sample of twins. After accounting for genetic influences on negative emotionality, genetic influences on major depressive disorder/conduct disorder comorbidity were nonsignficant, but only in male twins. Specifically, 19% of the variance in the two disorders was accounted for by genetic factors shared with negative emotionality in male twins. Although the full hypothesis could not be tested in female twins, 10% to 11% of the variance in the two disorders was also accounted for by genetic factors shared with negative emotionality. Common shared environmental and nonshared environmental influences were found for major depressive disorder/conduct disorder comorbidity in male and female twins. Negative emotionality represents an important dispositional trait that may explain genetic influences on major depressive disorder/conduct disorder comorbidity, at least for boys. Models of major depressive disorder/conduct disorder comorbidity must simultaneously measure common and specific genetic and environmental factors for a full understanding of this phenomenon. Gender differences require specific research attention in dispositional factors and developmental progression. Copyright © 2011 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters.

PubMed

Chung, SungWon; Lu, Ying; Henry, Roland G

2006-11-01

Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. In this paper, two new approaches are introduced called residual bootstrap and repetition bootknife. We show that repetition bootknife corrects for the large bias present in the repetition bootstrap method and, therefore, better estimates the standard errors. Like wild bootstrap, residual bootstrap is applicable to single acquisition scheme, and both are based on regression residuals (called model-based resampling). Residual bootstrap is based on the assumption that non-constant variance of measured diffusion-attenuated signals can be modeled, which is actually the assumption behind the widely used weighted least squares solution of diffusion tensor. The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.

A Multisource Approach to Assessing Child Maltreatment From Records, Caregivers, and Children.

PubMed

Sierau, Susan; Brand, Tilman; Manly, Jody Todd; Schlesier-Michel, Andrea; Klein, Annette M; Andreas, Anna; Garzón, Leonhard Quintero; Keil, Jan; Binser, Martin J; von Klitzing, Kai; White, Lars O

2017-02-01

Practitioners and researchers alike face the challenge that different sources report inconsistent information regarding child maltreatment. The present study capitalizes on concordance and discordance between different sources and probes applicability of a multisource approach to data from three perspectives on maltreatment-Child Protection Services (CPS) records, caregivers, and children. The sample comprised 686 participants in early childhood (3- to 8-year-olds; n = 275) or late childhood/adolescence (9- to 16-year-olds; n = 411), 161 from two CPS sites and 525 from the community oversampled for psychosocial risk. We established three components within a factor-analytic approach: the shared variance between sources on presence of maltreatment (convergence), nonshared variance resulting from the child's own perspective, and the caregiver versus CPS perspective. The shared variance between sources was the strongest predictor of caregiver- and self-reported child symptoms. Child perspective and caregiver versus CPS perspective mainly added predictive strength of symptoms in late childhood/adolescence over and above convergence in the case of emotional maltreatment, lack of supervision, and physical abuse. By contrast, convergence almost fully accounted for child symptoms for failure to provide. Our results suggest consistent information from different sources reporting on maltreatment is, on average, the best indicator of child risk.

Multiple Brain Markers are Linked to Age-Related Variation in Cognition

PubMed Central

Hedden, Trey; Schultz, Aaron P.; Rieckmann, Anna; Mormino, Elizabeth C.; Johnson, Keith A.; Sperling, Reisa A.; Buckner, Randy L.

2016-01-01

Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition. Clinically normal older humans aged 65–90 from the Harvard Aging Brain Study (N = 186) were characterized on a priori magnetic resonance imaging markers of gray matter thickness and volume, white matter hyperintensities, fractional anisotropy (FA), resting-state functional connectivity, positron emission tomography markers of glucose metabolism and amyloid burden, and cognitive factors of processing speed, executive function, and episodic memory. Partial correlation and mediation analyses estimated age-related variance in cognition shared with individual brain markers and unique to each marker. The largest relationships linked FA and striatum volume to processing speed and executive function, and hippocampal volume to episodic memory. Of the age-related variance in cognition, 70–80% was accounted for by combining all brain markers (but only ∼20% of total variance). Age had significant indirect effects on cognition via brain markers, with significant markers varying across cognitive domains. These results suggest that most age-related variation in cognition is shared among multiple brain markers, but potential specificity between some brain markers and cognitive domains motivates additional study of age-related markers of neural health. PMID:25316342

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.

Acceptance alone is a better predictor of psychopathology and well-being than emotional competence, emotion regulation and mindfulness.

PubMed

Kotsou, Ilios; Leys, Christophe; Fossion, Pierre

2018-01-15

Emotional competence, emotion regulation, mindfulness and acceptance have all been strongly associated to emotional disorders and psychological well-being in multiple studies. However little research has compared the unique predictive ability of these different constructs. We hypothesised that they will all share a large proportion of common variance and that when compared to the broader constructs emotional competence, emotion regulation and mindfulness, acceptance alone would predict a larger proportion of unique variance METHODS: 228 participants from a community sample completed anonymously measures of anxiety, depression, happiness, acceptance, mindfulness, emotional competence and emotion regulation. We then ran multiple regressions to assess and compare the predictive ability of these different constructs. For measures of psychological distress, the acceptance measure uniquely accounted for between 4 and 30 times the variance that the emotional competence, emotion regulation and mindfulness measures did. These results are based on cross-sectional designs and non-clinical samples, longitudinal and experimental studies as clinical samples may be useful in order to assess the potential protective power of acceptance over time. Another limitation is the use of self-report questionnaires. Results confirmed our hypothesis, supporting the research on the importance of acceptance as a central factor in the understanding of the onset and maintenance of emotional disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Why are children in the same family so different from one another?*

PubMed Central

Plomin, Robert; Daniels, Denise

2011-01-01

Summary One of the most important findings that has emerged from human behavioral genetics involves the environment rather than heredity, providing the best available evidence for the importance of environmental influences on personality, psychopathology, and cognition. The research also converges on the remarkable conclusion that these environmental influences make two children in the same family as different from one another as are pairs of children selected randomly from the population. The theme of the target article is that environmental differences between children in the same family (called “nonshared environment”) represent the major source of environmental variance for personality, psychopathology, and cognitive abilities. One example of the evidence that supports this conclusion involves correlations for pairs of adopted children reared in the same family from early in life. Because these children share family environment but not heredity, their correlation directly estimates the importance of shared family environment. For most psychological characteristics, correlations for adoptive “siblings” hover near zero, which implies that the relevant environmental influences are not shared by children in the same family. Although it has been thought that cognitive abilities represent an exception to this rule, recent data suggest that environmental variance that affects IQ is also of the nonshared variety after adolescence. The article has three goals: (1) To describe quantitative genetic methods and research that lead to the conclusion that nonshared environment is responsible for most environmental variation relevant to psychological development, (2) to discuss specific nonshared environmental influences that have been studied to date, and (3) to consider relationships between nonshared environmental influences and behavioral differences between children in the same family. The reason for presenting this article in BBS is to draw attention to the far-reaching implications of finding that psychologically relevant environmental influences make children in a family different from, not similar to, one another. PMID:21807642

Why are children in the same family so different from one another?

PubMed

Plomin, Robert; Daniels, Denise

2011-06-01

One of the most important findings that has emerged from human behavioral genetics involves the environment rather than heredity, providing the best available evidence for the importance of environmental influences on personality, psychopathology, and cognition. The research also converges on the remarkable conclusion that these environmental influences make two children in the same family as different from one another as are pairs of children selected randomly from the population. The theme of the target article is that environmental differences between children in the same family (called "nonshared environment") represent the major source of environmental variance for personality, psychopathology, and cognitive abilities. One example of the evidence that supports this conclusion involves correlations for pairs of adopted children reared in the same family from early in life. Because these children share family environment but not heredity, their correlation directly estimates the importance of shared family environment. For most psychological characteristics, correlations for adoptive "siblings" hover near zero, which implies that the relevant environmental influences are not shared by children in the same family. Although it has been thought that cognitive abilities represent an exception to this rule, recent data suggest that environmental variance that affects IQ is also of the nonshared variety after adolescence. The article has three goals: (1) To describe quantitative genetic methods and research that lead to the conclusion that nonshared environment is responsible for most environmental variation relevant to psychological development, (2) to discuss specific nonshared environmental influences that have been studied to date, and (3) to consider relationships between nonshared environmental influences and behavioral differences between children in the same family. The reason for presenting this article in BBS is to draw attention to the far-reaching implications of finding that psychologically relevant environmental influences make children in a family different from, not similar to, one another.

How strongly do word reading times and lexical decision times correlate? Combining data from eye movement corpora and megastudies.

PubMed

Kuperman, Victor; Drieghe, Denis; Keuleers, Emmanuel; Brysbaert, Marc

2013-01-01

We assess the amount of shared variance between three measures of visual word recognition latencies: eye movement latencies, lexical decision times, and naming times. After partialling out the effects of word frequency and word length, two well-documented predictors of word recognition latencies, we see that 7-44% of the variance is uniquely shared between lexical decision times and naming times, depending on the frequency range of the words used. A similar analysis of eye movement latencies shows that the percentage of variance they uniquely share either with lexical decision times or with naming times is much lower. It is 5-17% for gaze durations and lexical decision times in studies with target words presented in neutral sentences, but drops to 0.2% for corpus studies in which eye movements to all words are analysed. Correlations between gaze durations and naming latencies are lower still. These findings suggest that processing times in isolated word processing and continuous text reading are affected by specific task demands and presentation format, and that lexical decision times and naming times are not very informative in predicting eye movement latencies in text reading once the effect of word frequency and word length are taken into account. The difference between controlled experiments and natural reading suggests that reading strategies and stimulus materials may determine the degree to which the immediacy-of-processing assumption and the eye-mind assumption apply. Fixation times are more likely to exclusively reflect the lexical processing of the currently fixated word in controlled studies with unpredictable target words rather than in natural reading of sentences or texts.

Counting OCR errors in typeset text

NASA Astrophysics Data System (ADS)

Sandberg, Jonathan S.

1995-03-01

Frequently object recognition accuracy is a key component in the performance analysis of pattern matching systems. In the past three years, the results of numerous excellent and rigorous studies of OCR system typeset-character accuracy (henceforth OCR accuracy) have been published, encouraging performance comparisons between a variety of OCR products and technologies. These published figures are important; OCR vendor advertisements in the popular trade magazines lead readers to believe that published OCR accuracy figures effect market share in the lucrative OCR market. Curiously, a detailed review of many of these OCR error occurrence counting results reveals that they are not reproducible as published and they are not strictly comparable due to larger variances in the counts than would be expected by the sampling variance. Naturally, since OCR accuracy is based on a ratio of the number of OCR errors over the size of the text searched for errors, imprecise OCR error accounting leads to similar imprecision in OCR accuracy. Some published papers use informal, non-automatic, or intuitively correct OCR error accounting. Still other published results present OCR error accounting methods based on string matching algorithms such as dynamic programming using Levenshtein (edit) distance but omit critical implementation details (such as the existence of suspect markers in the OCR generated output or the weights used in the dynamic programming minimization procedure). The problem with not specifically revealing the accounting method is that the number of errors found by different methods are significantly different. This paper identifies the basic accounting methods used to measure OCR errors in typeset text and offers an evaluation and comparison of the various accounting methods.

Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

PubMed Central

Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

2012-01-01

Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

Competing risks regression for clustered data

PubMed Central

Zhou, Bingqing; Fine, Jason; Latouche, Aurelien; Labopin, Myriam

2012-01-01

A population average regression model is proposed to assess the marginal effects of covariates on the cumulative incidence function when there is dependence across individuals within a cluster in the competing risks setting. This method extends the Fine–Gray proportional hazards model for the subdistribution to situations, where individuals within a cluster may be correlated due to unobserved shared factors. Estimators of the regression parameters in the marginal model are developed under an independence working assumption where the correlation across individuals within a cluster is completely unspecified. The estimators are consistent and asymptotically normal, and variance estimation may be achieved without specifying the form of the dependence across individuals. A simulation study evidences that the inferential procedures perform well with realistic sample sizes. The practical utility of the methods is illustrated with data from the European Bone Marrow Transplant Registry. PMID:22045910

A Canonical Analysis of Career Choice Crystallization and Vocational Maturity.

ERIC Educational Resources Information Center

Blustein, David L.

1988-01-01

Administered measures of vocational maturity and career choice crystallization to 158 community college students. Used canonical analysis to identify relationships between age, gender, career choice crystallization, and vocational maturity. Analysis yielded one significant canonical root, indicating most shared variance between variables was…

Sharing Health Information and Influencing Behavioral Intentions: The Role of Health Literacy, Information Overload, and the Internet in the Diffusion of Healthy Heart Information.

PubMed

Crook, Brittani; Stephens, Keri K; Pastorek, Angie E; Mackert, Michael; Donovan, Erin E

2016-01-01

Low health literacy remains an extremely common and problematic issue, given that individuals with lower health literacy are more likely to experience health challenges and negative health outcomes. In this study, we use the first three stages of the innovation-decision process found in the theory of diffusion of innovations (Rogers, 2003). We incorporate health literacy into a model explaining how perceived health knowledge, information sharing, attitudes, and behavior are related. Results show that health information sharing explains 33% of the variance in behavioral intentions, indicating that the communicative practice of sharing information can positively impact health outcomes. Further, individuals with high health literacy tend to share less information about heart health than those with lower health literacy. Findings also reveal that perceived heart-health knowledge operates differently than health literacy to predict health outcomes.

Genetic and Environmental Influences on Frontal EEG Asymmetry and Alpha Power in 9–10 Year Old Twins

PubMed Central

Gao, Yu; Tuvblad, Catherine; Raine, Adrian; Lozano, Dora I.; Baker, Laura A.

2008-01-01

Modest genetic influences on frontal EEG asymmetry have been found in adults, but little is known about its genetic origins in children. Resting frontal asymmetry and alpha power were examined in 951 9–10-year-old twins. Results showed that in both males and females: (1) a modest but significant amount of variance in frontal asymmetry was accounted for by genetic factors (11–27%) with the remainder accounted for by non-shared environmental influences, and (2) alpha power were highly heritable, with 70–85% of the variance accounted for by genetic factors. Results suggest that the genetic architecture of frontal asymmetry and alpha power in late childhood are similar to that in adulthood and that the high non-shared environmental influences on frontal asymmetry may reflect environmentally-influenced individual differences in the maturation of frontal cortex as well as state-dependent influences on specific measurements. PMID:19386046

Dichotic listening and otoacoustic emissions: shared variance between cochlear function and dichotic listening performance in adults with normal hearing.

PubMed

Markevych, Vladlena; Asbjørnsen, Arve E; Lind, Ola; Plante, Elena; Cone, Barbara

2011-07-01

The present study investigated a possible connection between speech processing and cochlear function. Twenty-two subjects with age range from 18 to 39, balanced for gender with normal hearing and without any known neurological condition, were tested with the dichotic listening (DL) test, in which listeners were asked to identify CV-syllables in a nonforced, and also attention-right, and attention-left condition. Transient evoked otoacoustic emissions (TEOAEs) were recorded for both ears, with and without the presentation of contralateral broadband noise. The main finding was a strong negative correlation between language laterality as measured with the dichotic listening task and of the TEOAE responses. The findings support a hypothesis of shared variance between central and peripheral auditory lateralities, and contribute to the attentional theory of auditory lateralization. The results have implications for the understanding of the cortico-fugal efferent control of cochlear activity. 2011 Elsevier Inc. All rights reserved.

The Developmental Influence of Primary Memory Capacity on Working Memory and Academic Achievement

PubMed Central

2015-01-01

In this study, we investigate the development of primary memory capacity among children. Children between the ages of 5 and 8 completed 3 novel tasks (split span, interleaved lists, and a modified free-recall task) that measured primary memory by estimating the number of items in the focus of attention that could be spontaneously recalled in serial order. These tasks were calibrated against traditional measures of simple and complex span. Clear age-related changes in these primary memory estimates were observed. There were marked individual differences in primary memory capacity, but each novel measure was predictive of simple span performance. Among older children, each measure shared variance with reading and mathematics performance, whereas for younger children, the interleaved lists task was the strongest single predictor of academic ability. We argue that these novel tasks have considerable potential for the measurement of primary memory capacity and provide new, complementary ways of measuring the transient memory processes that predict academic performance. The interleaved lists task also shared features with interference control tasks, and our findings suggest that young children have a particular difficulty in resisting distraction and that variance in the ability to resist distraction is also shared with measures of educational attainment. PMID:26075630

The developmental influence of primary memory capacity on working memory and academic achievement.

PubMed

Hall, Debbora; Jarrold, Christopher; Towse, John N; Zarandi, Amy L

2015-08-01

In this study, we investigate the development of primary memory capacity among children. Children between the ages of 5 and 8 completed 3 novel tasks (split span, interleaved lists, and a modified free-recall task) that measured primary memory by estimating the number of items in the focus of attention that could be spontaneously recalled in serial order. These tasks were calibrated against traditional measures of simple and complex span. Clear age-related changes in these primary memory estimates were observed. There were marked individual differences in primary memory capacity, but each novel measure was predictive of simple span performance. Among older children, each measure shared variance with reading and mathematics performance, whereas for younger children, the interleaved lists task was the strongest single predictor of academic ability. We argue that these novel tasks have considerable potential for the measurement of primary memory capacity and provide new, complementary ways of measuring the transient memory processes that predict academic performance. The interleaved lists task also shared features with interference control tasks, and our findings suggest that young children have a particular difficulty in resisting distraction and that variance in the ability to resist distraction is also shared with measures of educational attainment. (c) 2015 APA, all rights reserved).

The Relationship between Social Capital in Hospitals and Physician Job Satisfaction

PubMed Central

Ommen, Oliver; Driller, Elke; Köhler, Thorsten; Kowalski, Christoph; Ernstmann, Nicole; Neumann, Melanie; Steffen, Petra; Pfaff, Holger

2009-01-01

Background Job satisfaction in the hospital is an important predictor for many significant management ratios. Acceptance in professional life or high workload are known as important predictors for job satisfaction. The influence of social capital in hospitals on job satisfaction within the health care system, however, remains to be determined. Thus, this article aimed at analysing the relationship between overall job satisfaction of physicians and social capital in hospitals. Methods The results of this study are based upon questionnaires sent by mail to 454 physicians working in the field of patient care in 4 different German hospitals in 2002. 277 clinicians responded to the poll, for a response rate of 61%. Analysis was performed using three linear regression models with physician overall job satisfaction as the dependent variable and age, gender, professional experience, workload, and social capital as independent variables. Results The first regression model explained nearly 9% of the variance of job satisfaction. Whereas job satisfaction increased slightly with age, gender and professional experience were not identified as significant factors to explain the variance. Setting up a second model with the addition of subjectively-perceived workload to the analysis, the explained variance increased to 18% and job satisfaction decreased significantly with increasing workload. The third model including social capital in hospital explained 36% of the variance with social capital, professional experience and workload as significant factors. Conclusion This analysis demonstrated that the social capital of an organisation, in addition to professional experience and workload, represents a significant predictor of overall job satisfaction of physicians working in the field of patient care. Trust, mutual understanding, shared aims, and ethical values are qualities of social capital that unify members of social networks and communities and enable them to act cooperatively. PMID:19445692

A Genetic Epidemiological Mega Analysis of Smoking Initiation in Adolescents.

PubMed

Maes, Hermine H; Prom-Wormley, Elizabeth; Eaves, Lindon J; Rhee, Soo Hyun; Hewitt, John K; Young, Susan; Corley, Robin; McGue, Matt; Iacono, William G; Legrand, Lisa; Samek, Diana R; Murrelle, E Lenn; Silberg, Judy L; Miles, Donna R; Schieken, Richard M; Beunen, Gaston P; Thomis, Martine; Rose, Richard J; Dick, Danielle M; Boomsma, Dorret I; Bartels, Meike; Vink, Jacqueline M; Lichtenstein, Paul; White, Victoria; Kaprio, Jaakko; Neale, Michael C

2017-04-01

Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation (SI) across adolescence. Mega-analysis of pooled genetically informative data on SI was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N = 19 313 pairs) between ages 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the United States, Europe, and Australia. Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of SI across developed countries. The estimate of additive genetic contributions to liability of SI increased from approximately 15% to 45% from ages 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to SI at age 13 (70%) and gradually less by age 19 (40%). Both additive genetic and shared environmental factors significantly contribute to variance in SI throughout adolescence. The present study, the largest genetic epidemiological study on SI to date, found consistent results across 11 studies for the etiology of SI. Environmental factors, especially those shared by siblings in a family, primarily influence SI variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies. This is the first study to find evidence of genetic factors in liability to SI at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across studies reflecting similar etiology of liability to initiate smoking across different cultures and time periods. Thus familial factors strongly contribute to individual differences in who starts to smoke with a gradual increase in the impact of genetic factors and a corresponding decrease in that of the shared environment. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Enduring consequences from the War on Drugs: How policing practices impact HIV risk among people who inject drugs in Baltimore City

PubMed Central

Flath, Natalie; Tobin, Karin; King, Kelly; Lee, Alexandra; Latkin, Carl

2017-01-01

Background Neighborhood-level characteristics, including police activity, are associated with HIV and Hepatitis C injection risk-behaviors among people who inject drugs (PWID). However, the pathways through which these neighborhood perceptions shape individual-level HIV risk behaviors are unclear. This study helps to explain perceived behaviors between perceived neighborhood police activity and HIV injection risk behavior (i.e., injection syringe/tool sharing in the previous six months). Methods A sample of (n=366) PWIDs who self-reported recent use were recruited using community-based outreach methods in Baltimore, Maryland. Neighborhood police perceptions were assessed by asking participants whether they would (1) be more likely to ask others to share injection tools in the context of heightened police activity; and (2) be less likely to carry syringes with them due to fear of arrest. Poisson regression with robust variance was used to identify statistical relationships. Recent police encounters, frequency of heroin injection, and socio-demographic characteristics were controlled for in the model. Results Neighborhood police perceptions shaped injection-risk behavior. Half of the sample (49%) reported an aversion of carrying personal syringes, due to fear of arrest. Those who agreed they would be more likely to ask others to share injection equipment in the context of heightened police activity were more likely to share syringes (21% versus 3%, p<0.01). Adjusted models showed that syringe sharing was independently associated with asking to borrow equipment in neighborhoods with perceived heightened police activity (aPR 2.22 95% CI 1.7, 3.0). Conclusion This study sheds light on how police perceptions may influence injection risk behavior. While these relationships require further elucidation, this study suggests that public health interventions aiming to reduce HIV risk would benefit from improving community- police relationships. PMID:28318343

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.

PubMed

Lee, S Hong; Ripke, Stephan; Neale, Benjamin M; Faraone, Stephen V; Purcell, Shaun M; Perlis, Roy H; Mowry, Bryan J; Thapar, Anita; Goddard, Michael E; Witte, John S; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E; Asherson, Philip; Azevedo, Maria H; Backlund, Lena; Badner, Judith A; Bailey, Anthony J; Banaschewski, Tobias; Barchas, Jack D; Barnes, Michael R; Barrett, Thomas B; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayés, Mònica; Bellivier, Frank; Bergen, Sarah E; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B; Black, Donald W; Blackwood, Douglas H R; Bloss, Cinnamon S; Boehnke, Michael; Boomsma, Dorret I; Breen, Gerome; Breuer, René; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G; Buitelaar, Jan K; Bunney, William E; Buxbaum, Joseph D; Byerley, William F; Byrne, Enda M; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Cloninger, C Robert; Collier, David A; Cook, Edwin H; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H; Craig, David W; Craig, Ian W; Crosbie, Jennifer; Cuccaro, Michael L; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J; Doyle, Alysa E; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P; Edenberg, Howard J; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E; Ferrier, I Nicol; Flickinger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B; Freitag, Christine M; Friedl, Marion; Frisén, Louise; Gallagher, Louise; Gejman, Pablo V; Georgieva, Lyudmila; Gershon, Elliot S; Geschwind, Daniel H; Giegling, Ina; Gill, Michael; Gordon, Scott D; Gordon-Smith, Katherine; Green, Elaine K; Greenwood, Tiffany A; Grice, Dorothy E; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P; Hamshere, Marian L; Hansen, Thomas F; Hartmann, Annette M; Hautzinger, Martin; Heath, Andrew C; Henders, Anjali K; Herms, Stefan; Hickie, Ian B; Hipolito, Maria; Hoefels, Susanne; Holmans, Peter A; Holsboer, Florian; Hoogendijk, Witte J; Hottenga, Jouke-Jan; Hultman, Christina M; Hus, Vanessa; Ingason, Andrés; Ising, Marcus; Jamain, Stéphane; Jones, Edward G; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kähler, Anna K; Kahn, René S; Kandaswamy, Radhika; Keller, Matthew C; Kennedy, James L; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K; Klauck, Sabine M; Klei, Lambertus; Knowles, James A; Kohli, Martin A; Koller, Daniel L; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landén, Mikael; Långström, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B; Leboyer, Marion; Ledbetter, David H; Lee, Phil H; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F; Lewis, Cathryn M; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A; Lin, Dan-Yu; Linszen, Don H; Liu, Chunyu; Lohoff, Falk W; Loo, Sandra K; Lord, Catherine; Lowe, Jennifer K; Lucae, Susanne; MacIntyre, Donald J; Madden, Pamela A F; Maestrini, Elena; Magnusson, Patrik K E; Mahon, Pamela B; Maier, Wolfgang; Malhotra, Anil K; Mane, Shrikant M; Martin, Christa L; Martin, Nicholas G; Mattheisen, Manuel; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A; McGhee, Kevin A; McGough, James J; McGrath, Patrick J; McGuffin, Peter; McInnis, Melvin G; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W; McMahon, Francis J; McMahon, William M; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P; Montgomery, Grant W; Moran, Jennifer L; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W; Morrow, Eric M; Moskvina, Valentina; Muglia, Pierandrea; Mühleisen, Thomas W; Muir, Walter J; Müller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M; Myin-Germeys, Inez; Neale, Michael C; Nelson, Stan F; Nievergelt, Caroline M; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A; Nöthen, Markus M; Nurnberger, John I; Nwulia, Evaristus A; Nyholt, Dale R; O'Dushlaine, Colm; Oades, Robert D; Olincy, Ann; Oliveira, Guiomar; Olsen, Line; Ophoff, Roel A; Osby, Urban; Owen, Michael J; Palotie, Aarno; Parr, Jeremy R; Paterson, Andrew D; Pato, Carlos N; Pato, Michele T; Penninx, Brenda W; Pergadia, Michele L; Pericak-Vance, Margaret A; Pickard, Benjamin S; Pimm, Jonathan; Piven, Joseph; Posthuma, Danielle; Potash, James B; Poustka, Fritz; Propping, Peter; Puri, Vinay; Quested, Digby J; Quinn, Emma M; Ramos-Quiroga, Josep Antoni; Rasmussen, Henrik B; Raychaudhuri, Soumya; Rehnström, Karola; Reif, Andreas; Ribasés, Marta; Rice, John P; Rietschel, Marcella; Roeder, Kathryn; Roeyers, Herbert; Rossin, Lizzy; Rothenberger, Aribert; Rouleau, Guy; Ruderfer, Douglas; Rujescu, Dan; Sanders, Alan R; Sanders, Stephan J; Santangelo, Susan L; Sergeant, Joseph A; Schachar, Russell; Schalling, Martin; Schatzberg, Alan F; Scheftner, William A; Schellenberg, Gerard D; Scherer, Stephen W; Schork, Nicholas J; Schulze, Thomas G; Schumacher, Johannes; Schwarz, Markus; Scolnick, Edward; Scott, Laura J; Shi, Jianxin; Shilling, Paul D; Shyn, Stanley I; Silverman, Jeremy M; Slager, Susan L; Smalley, Susan L; Smit, Johannes H; Smith, Erin N; Sonuga-Barke, Edmund J S; St Clair, David; State, Matthew; Steffens, Michael; Steinhausen, Hans-Christoph; Strauss, John S; Strohmaier, Jana; Stroup, T Scott; Sutcliffe, James S; Szatmari, Peter; Szelinger, Szabocls; Thirumalai, Srinivasa; Thompson, Robert C; Todorov, Alexandre A; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; van den Oord, Edwin J C G; Van Grootheest, Gerard; Van Os, Jim; Vicente, Astrid M; Vieland, Veronica J; Vincent, John B; Visscher, Peter M; Walsh, Christopher A; Wassink, Thomas H; Watson, Stanley J; Weissman, Myrna M; Werge, Thomas; Wienker, Thomas F; Wijsman, Ellen M; Willemsen, Gonneke; Williams, Nigel; Willsey, A Jeremy; Witt, Stephanie H; Xu, Wei; Young, Allan H; Yu, Timothy W; Zammit, Stanley; Zandi, Peter P; Zhang, Peng; Zitman, Frans G; Zöllner, Sebastian; Devlin, Bernie; Kelsoe, John R; Sklar, Pamela; Daly, Mark J; O'Donovan, Michael C; Craddock, Nicholas; Sullivan, Patrick F; Smoller, Jordan W; Kendler, Kenneth S; Wray, Naomi R

2013-09-01

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Online Information Sharing About Risks: The Case of Organic Food.

PubMed

Hilverda, Femke; Kuttschreuter, Margôt

2018-03-23

Individuals have to make sense of an abundance of information to decide whether or not to purchase certain food products. One of the means to sense-making is information sharing. This article reports on a quantitative study examining online information sharing behavior regarding the risks of organic food products. An online survey among 535 respondents was conducted in the Netherlands to examine the determinants of information sharing behavior, and their relationships. Structural equation modeling was applied to test both the measurement model and the structural model. Results showed that the intention to share information online about the risks of organic food was low. Conversations and email were the preferred channels to share information; of the social media Facebook stood out. The developed model was found to provide an adequate description of the data. It explained 41% of the variance in information sharing. Injunctive norms and outcome expectancies were most important in predicting online information sharing, followed by information-related determinants. Risk-perception-related determinants showed a significant, but weak, positive relationship with online information sharing. Implications for authorities communicating on risks associated with food are addressed. © 2018 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Vicarious resilience in sexual assault and domestic violence advocates.

PubMed

Frey, Lisa L; Beesley, Denise; Abbott, Deah; Kendrick, Elizabeth

2017-01-01

There is little research related to sexual assault and domestic violence advocates' experiences, with the bulk of the literature focused on stressors and systemic barriers that negatively impact efforts to assist survivors. However, advocates participating in these studies have also emphasized the positive impact they experience consequent to their work. This study explores the positive impact. Vicarious resilience, personal trauma experiences, peer relational quality, and perceived organizational support in advocates (n = 222) are examined. Also, overlap among the conceptual components of vicarious resilience is explored. The first set of multiple regressions showed that personal trauma experiences and peer relational health predicted compassion satisfaction and vicarious posttraumatic growth, with organizational support predicting only compassion satisfaction. The second set of multiple regressions showed that (a) there was significant shared variance between vicarious posttraumatic growth and compassion satisfaction; (b) after accounting for vicarious posttraumatic growth, organizational support accounted for significant variance in compassion satisfaction; and (c) after accounting for compassion satisfaction, peer relational health accounted for significant variance in vicarious posttraumatic growth. Results suggest that it may be more meaningful to conceptualize advocates' personal growth related to their work through the lens of a multidimensional construct such as vicarious resilience. Organizational strategies promoting vicarious resilience (e.g., shared organizational power, training components) are offered, and the value to trauma-informed care of fostering advocates' vicarious resilience is discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comorbidity of depression with levels of smoking: an exploration of the shared familial risk hypothesis.

PubMed

Johnson, Eric O; Rhee, Soo Hyun; Chase, Gary A; Breslau, Naomi

2004-12-01

Comorbidity of depression and smoking is well recognized, but results from studies that have assessed alternative explanations have varied by the level of smoking and the study method. We examined all 13 etiology models of comorbidity described by Neale and Kendler (American Journal of Genetics, 57, 935-953, 1995) for depression and each of four levels of smoking to shed light on the role that differing definitions might have played in generating the conflicting findings. Data came from 979 young adults aged 26-35 years who participated in an epidemiological cohort study in southeastern Michigan. Respondent and family history data on parental smoking and depression were analyzed using the biometric modeling method for family data, which Rhee and colleagues (Journal of Child Psychology and Psychiatry and Allied Disciplines, 44, 612-636, 2003; Behavior Genetics, 34, 251-265, 2004) have shown to be valid more frequently than traditional prevalence analyses. Results of the biometric model fitting suggested that for ever smoking, the comorbidity with depression may be related to chance or a high liability threshold for smoking only. In contrast, a correlated liabilities model fit the data best for the comorbidity of depression with daily, heavy, and nicotine-dependent smoking. The familial correlations accounted for 73%-95% of the total variance shared between depression and these levels of smoking. These results differ from analyses of these data using a traditional prevalence approach, which found no evidence of shared familial liability. The conflicting findings of the studies that have examined the relationship between smoking and depression may be attributable to differences in definition of the disorders and the methods used to analyze them.

Genes for Reading and Spelling

ERIC Educational Resources Information Center

Bates, Timothy C.

2006-01-01

This article reviews research on the behavioral and molecular genetics of reading and, where available, spelling. Recent research is summarized, suggesting that reading and spelling appear to share a common genetic basis, and that dyslexia lies on a genetic continuum with normal variance in reading skill. Research also suggests that while many of…

Exploring Statistics Anxiety: Contrasting Mathematical, Academic Performance and Trait Psychological Predictors

ERIC Educational Resources Information Center

Bourne, Victoria J.

2018-01-01

Statistics anxiety is experienced by a large number of psychology students, and previous research has examined a range of potential correlates, including academic performance, mathematical ability and psychological predictors. These varying predictors are often considered separately, although there may be shared variance between them. In the…

Evaluation of three lidar scanning strategies for turbulence measurements

NASA Astrophysics Data System (ADS)

Newman, J. F.; Klein, P. M.; Wharton, S.; Sathe, A.; Bonin, T. A.; Chilson, P. B.; Muschinski, A.

2015-11-01

Several errors occur when a traditional Doppler-beam swinging (DBS) or velocity-azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers. Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

Evaluation of three lidar scanning strategies for turbulence measurements

NASA Astrophysics Data System (ADS)

Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia; Sathe, Ameya; Bonin, Timothy A.; Chilson, Phillip B.; Muschinski, Andreas

2016-05-01

Several errors occur when a traditional Doppler beam swinging (DBS) or velocity-azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

Methods to Estimate the Variance of Some Indices of the Signal Detection Theory: A Simulation Study

ERIC Educational Resources Information Center

Suero, Manuel; Privado, Jesús; Botella, Juan

2017-01-01

A simulation study is presented to evaluate and compare three methods to estimate the variance of the estimates of the parameters d and "C" of the signal detection theory (SDT). Several methods have been proposed to calculate the variance of their estimators, "d'" and "c." Those methods have been mostly assessed by…

Turbulence Variance Characteristics in the Unstable Atmospheric Boundary Layer above Flat Pine Forest

NASA Astrophysics Data System (ADS)

Asanuma, Jun

Variances of the velocity components and scalars are important as indicators of the turbulence intensity. They also can be utilized to estimate surface fluxes in several types of "variance methods", and the estimated fluxes can be regional values if the variances from which they are calculated are regionally representative measurements. On these motivations, variances measured by an aircraft in the unstable ABL over a flat pine forest during HAPEX-Mobilhy were analyzed within the context of the similarity scaling arguments. The variances of temperature and vertical velocity within the atmospheric surface layer were found to follow closely the Monin-Obukhov similarity theory, and to yield reasonable estimates of the surface sensible heat fluxes when they are used in variance methods. This gives a validation to the variance methods with aircraft measurements. On the other hand, the specific humidity variances were influenced by the surface heterogeneity and clearly fail to obey MOS. A simple analysis based on the similarity law for free convection produced a comprehensible and quantitative picture regarding the effect of the surface flux heterogeneity on the statistical moments, and revealed that variances of the active and passive scalars become dissimilar because of their different roles in turbulence. The analysis also indicated that the mean quantities are also affected by the heterogeneity but to a less extent than the variances. The temperature variances in the mixed layer (ML) were examined by using a generalized top-down bottom-up diffusion model with some combinations of velocity scales and inversion flux models. The results showed that the surface shear stress exerts considerable influence on the lower ML. Also with the temperature and vertical velocity variances ML variance methods were tested, and their feasibility was investigated. Finally, the variances in the ML were analyzed in terms of the local similarity concept; the results confirmed the original hypothesis by Panofsky and McCormick that the local scaling in terms of the local buoyancy flux defines the lower bound of the moments.

Sequential causal inference: Application to randomized trials of adaptive treatment strategies

PubMed Central

Dawson, Ree; Lavori, Philip W.

2009-01-01

SUMMARY Clinical trials that randomize subjects to decision algorithms, which adapt treatments over time according to individual response, have gained considerable interest as investigators seek designs that directly inform clinical decision making. We consider designs in which subjects are randomized sequentially at decision points, among adaptive treatment options under evaluation. We present a sequential method to estimate the comparative effects of the randomized adaptive treatments, which are formalized as adaptive treatment strategies. Our causal estimators are derived using Bayesian predictive inference. We use analytical and empirical calculations to compare the predictive estimators to (i) the ‘standard’ approach that allocates the sequentially obtained data to separate strategy-specific groups as would arise from randomizing subjects at baseline; (ii) the semi-parametric approach of marginal mean models that, under appropriate experimental conditions, provides the same sequential estimator of causal differences as the proposed approach. Simulation studies demonstrate that sequential causal inference offers substantial efficiency gains over the standard approach to comparing treatments, because the predictive estimators can take advantage of the monotone structure of shared data among adaptive strategies. We further demonstrate that the semi-parametric asymptotic variances, which are marginal ‘one-step’ estimators, may exhibit significant bias, in contrast to the predictive variances. We show that the conditions under which the sequential method is attractive relative to the other two approaches are those most likely to occur in real studies. PMID:17914714

Lean Six Sigma implementation and organizational culture.

PubMed

Knapp, Susan

2015-01-01

The purpose of this paper is to examine the relationship between four organizational cultural types defined by the Competing Values Framework and three Lean Six Sigma implementation components - management involvement, use of Lean Six Sigma methods and Lean Six Sigma infrastructure. The study involved surveying 446 human resource and quality managers from 223 hospitals located in Maine, New Hampshire, Vermont, Massachusetts and Rhode Island using the Organizational Culture Assessment Instrument. Findings - In total, 104 completed responses were received and analyzed using multivariate analysis of variance. Follow-up analysis of variances showed management support was significant, F(3, 100)=4.89, p < 0.01, η2=1.28; infrastructure was not significant, F(3, 100)=1.55, p=0.21, η2=0.05; and using Lean Six Sigma methods was also not significant, F(3, 100)=1.34, p=0.26, η2=0.04. Post hoc analysis identified group and development cultures having significant interactions with management support. The relationship between organizational culture and Lean Six Sigma in hospitals provides information on how specific cultural characteristics impact the Lean Six Sigma initiative key components. This information assists hospital staff who are considering implementing quality initiatives by providing an understanding of what cultural values correspond to effective Lean Six Sigma implementation. Managers understanding the quality initiative cultural underpinnings, are attentive to the culture-shared values and norm's influence can utilize strategies to better implement Lean Six Sigma.

A rapid generalized least squares model for a genome-wide quantitative trait association analysis in families.

PubMed

Li, Xiang; Basu, Saonli; Miller, Michael B; Iacono, William G; McGue, Matt

2011-01-01

Genome-wide association studies (GWAS) using family data involve association analyses between hundreds of thousands of markers and a trait for a large number of related individuals. The correlations among relatives bring statistical and computational challenges when performing these large-scale association analyses. Recently, several rapid methods accounting for both within- and between-family variation have been proposed. However, these techniques mostly model the phenotypic similarities in terms of genetic relatedness. The familial resemblances in many family-based studies such as twin studies are not only due to the genetic relatedness, but also derive from shared environmental effects and assortative mating. In this paper, we propose 2 generalized least squares (GLS) models for rapid association analysis of family-based GWAS, which accommodate both genetic and environmental contributions to familial resemblance. In our first model, we estimated the joint genetic and environmental variations. In our second model, we estimated the genetic and environmental components separately. Through simulation studies, we demonstrated that our proposed approaches are more powerful and computationally efficient than a number of existing methods are. We show that estimating the residual variance-covariance matrix in the GLS models without SNP effects does not lead to an appreciable bias in the p values as long as the SNP effect is small (i.e. accounting for no more than 1% of trait variance). Copyright © 2011 S. Karger AG, Basel.

Low self-esteem during adolescence predicts poor health, criminal behavior, and limited economic prospects during adulthood.

PubMed

Trzesniewski, Kali H; Donnellan, M Brent; Moffitt, Terrie E; Robins, Richard W; Poulton, Richie; Caspi, Avshalom

2006-03-01

Using prospective data from the Dunedin Multidisciplinary Health and Development Study birth cohort, the authors found that adolescents with low self-esteem had poorer mental and physical health, worse economic prospects, and higher levels of criminal behavior during adulthood, compared with adolescents with high self-esteem. The long-term consequences of self-esteem could not be explained by adolescent depression, gender, or socioeconomic status. Moreover, the findings held when the outcome variables were assessed using objective measures and informant reports; therefore, the findings cannot be explained by shared method variance in self-report data. The findings suggest that low self-esteem during adolescence predicts negative real-world consequences during adulthood. Copyright (c) 2006 APA, all rights reserved.

Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Estimating integrated variance in the presence of microstructure noise using linear regression

NASA Astrophysics Data System (ADS)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

The Petersen-Lincoln estimator and its extension to estimate the size of a shared population.

PubMed

Chao, Anne; Pan, H-Y; Chiang, Shu-Chuan

2008-12-01

The Petersen-Lincoln estimator has been used to estimate the size of a population in a single mark release experiment. However, the estimator is not valid when the capture sample and recapture sample are not independent. We provide an intuitive interpretation for "independence" between samples based on 2 x 2 categorical data formed by capture/non-capture in each of the two samples. From the interpretation, we review a general measure of "dependence" and quantify the correlation bias of the Petersen-Lincoln estimator when two types of dependences (local list dependence and heterogeneity of capture probability) exist. An important implication in the census undercount problem is that instead of using a post enumeration sample to assess the undercount of a census, one should conduct a prior enumeration sample to avoid correlation bias. We extend the Petersen-Lincoln method to the case of two populations. This new estimator of the size of the shared population is proposed and its variance is derived. We discuss a special case where the correlation bias of the proposed estimator due to dependence between samples vanishes. The proposed method is applied to a study of the relapse rate of illicit drug use in Taiwan. ((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Haplotype-Based Association Analysis via Variance-Components Score Test

PubMed Central

Tzeng, Jung-Ying ; Zhang, Daowen 

2007-01-01

Haplotypes provide a more informative format of polymorphisms for genetic association analysis than do individual single-nucleotide polymorphisms. However, the practical efficacy of haplotype-based association analysis is challenged by a trade-off between the benefits of modeling abundant variation and the cost of the extra degrees of freedom. To reduce the degrees of freedom, several strategies have been considered in the literature. They include (1) clustering evolutionarily close haplotypes, (2) modeling the level of haplotype sharing, and (3) smoothing haplotype effects by introducing a correlation structure for haplotype effects and studying the variance components (VC) for association. Although the first two strategies enjoy a fair extent of power gain, empirical evidence showed that VC methods may exhibit only similar or less power than the standard haplotype regression method, even in cases of many haplotypes. In this study, we report possible reasons that cause the underpowered phenomenon and show how the power of the VC strategy can be improved. We construct a score test based on the restricted maximum likelihood or the marginal likelihood function of the VC and identify its nontypical limiting distribution. Through simulation, we demonstrate the validity of the test and investigate the power performance of the VC approach and that of the standard haplotype regression approach. With suitable choices for the correlation structure, the proposed method can be directly applied to unphased genotypic data. Our method is applicable to a wide-ranging class of models and is computationally efficient and easy to implement. The broad coverage and the fast and easy implementation of this method make the VC strategy an effective tool for haplotype analysis, even in modern genomewide association studies. PMID:17924336

Variance Difference between Maximum Likelihood Estimation Method and Expected A Posteriori Estimation Method Viewed from Number of Test Items

ERIC Educational Resources Information Center

Mahmud, Jumailiyah; Sutikno, Muzayanah; Naga, Dali S.

2016-01-01

The aim of this study is to determine variance difference between maximum likelihood and expected A posteriori estimation methods viewed from number of test items of aptitude test. The variance presents an accuracy generated by both maximum likelihood and Bayes estimation methods. The test consists of three subtests, each with 40 multiple-choice…

Two-step sensitivity testing of parametrized and regionalized life cycle assessments: methodology and case study.

PubMed

Mutel, Christopher L; de Baan, Laura; Hellweg, Stefanie

2013-06-04

Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.

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

When Assessing Intra-Familial Relationships, Are Sociologists, Psychoanalysts and Psychiatrists Really Considering Different Constructs? An Empirical Study.

PubMed

Falissard, Bruno; Barry, Caroline; Hassler, Christine; Letrait, Muriel; Macher, Guillaume; Marty, François; Ramos, Elsa; Revah-Lévy, Anne; Robert, Philippe; de Singly, François

2015-01-01

This paper aimed to look for the existence of a common core when envisaging intra-familial interactions as perceived by adolescents, which could be shared by sociology, psychoanalysis and child and adolescent psychiatry. An empirical study based on a mixed-method design collected the responses of 194 adolescents to the instruction "In the next half hour, would you please write as freely as you wish about your relationships in your family, explaining how things are". All answers were then analyzed and 18 dimensions related to 3 different theoretical frameworks were rated blind using numerical scores by two independent raters from each discipline. Inter-rater reliability was good. A parallel analysis evidenced a strong underlying factor explaining a large amount of variance (>50%). This factor is bipolar, it reflects the level of positivity/negativity in the adolescent's point of view concerning his/her intra-familial relationships. A second factor can marginally be considered (10% of the variance). The 2-factor analysis found one factor related to positive feelings and the other to negative feelings. This finding of unidimensionality supports family study as an intervention science.

Heritability, family, school and academic achievement in adolescence.

PubMed

Pokropek, Artur; Sikora, Joanna

2015-09-01

We demonstrate how genetically informed designs can be applied to administrative exam data to study academic achievement. ACE mixture latent class models have been used with Year 6 and 9 exam data for seven cohorts of Polish students which include 24,285 pairs of twins. Depending on a learning domain and classroom environment history, from 58% to 88% of variance in exam results is attributable to heritability, up to 34% to shared environment and from 8% to 15% depends on unique events in students' lives. Moreover, between 54% and 66% of variance in students' learning gains made between Years 6 and 9 is explained by heritability. The unique environment accounts for between 34% and 46% of that variance. However, we find no classroom effects on student progress made between Years 6 and 9. We situate this finding against the view that classroom peer groups and teachers matter for adolescent learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Working Memory and Parent-Rated Components of Attention in Middle Childhood: A Behavioral Genetic Study

PubMed Central

Deater-Deckard, Kirby; Cutting, Laurie; Thompson, Lee A.; Petrill, Stephen A.

2012-01-01

The purpose of the current study was to investigate potential genetic and environmental correlations between working memory and three behavioral aspects of the attention network (i.e., executive, alerting, and orienting) using a twin design. Data were from 90 monozygotic (39% male) and 112 same-sex dizygotic (41% male) twins. Individual differences in working memory performance (digit span) and parent-rated measures of executive, alerting, and orienting attention included modest to moderate genetic variance, modest shared environmental variance, and modest to moderate nonshared environmental variance. As hypothesized, working memory performance was correlated with executive and alerting attention, but not orienting attention. The correlation between working memory, executive attention, and alerting attention was completely accounted for by overlapping genetic covariance, suggesting a common genetic mechanism or mechanisms underlying the links between working memory and certain parent-rated indicators of attentive behavior. PMID:21948215

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

PubMed Central

Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

2015-01-01

Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

Evaluation of three lidar scanning strategies for turbulence measurements

DOE PAGES

Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia; ...

2016-05-03

Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused bymore » VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.« less

Evaluation of three lidar scanning strategies for turbulence measurements

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

Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia

Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused bymore » VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.« less

Familial resemblance and shared latent familial variance in recurrent fall risk in older women

PubMed Central

Cauley, Jane A.; Roth, Stephen M.; Kammerer, Candace; Stone, Katie; Hillier, Teresa A.; Ensrud, Kristine E.; Hochberg, Marc; Nevitt, Michael C.; Zmuda, Joseph M.

2010-01-01

Background: A possible familial component to fracture risk may be mediated through a genetic liability to fall recurrently. Methods: Our analysis sample included 186 female sibling-ships (n = 401) of mean age 71.9 yr (SD = 5.0). Using variance component models, we estimated residual upper-limit heritabilities in fall-risk mobility phenotypes (e.g., chair-stand time, rapid step-ups, and usual-paced walking speed) and in recurrent falls. We also estimated familial and environmental (unmeasured) correlations between pairs of fall-risk mobility phenotypes. All models were adjusted for age, height, body mass index, and medical and environmental factors. Results: Residual upper-limit heritabilities were all moderate (P < 0.05), ranging from 0.27 for usual-paced walking speed to 0.58 for recurrent falls. A strong familial correlation between usual-paced walking speed and rapid step-ups of 0.65 (P < 0.01) was identified. Familial correlations between usual-paced walking speed and chair-stand time (−0.02) and between chair-stand time and rapid step-ups (−0.27) were both nonsignificant (P > 0.05). Environmental correlations ranged from 0.35 to 0.58 (absolute values), P < 0.05 for all. Conclusions: There exists moderate familial resemblance in fall-risk mobility phenotypes and recurrent falls among older female siblings, which we expect is primarily genetic given that adult siblings live separate lives. All fall-risk mobility phenotypes may be coinfluenced at least to a small degree by shared latent familial or environmental factors; however, up to approximately one-half of the covariation between usual-paced walking speed and rapid step-ups may be due to a common set of genes. PMID:20167680

Job sharing: a retention strategy for nurses.

PubMed

Kane, D

1999-01-01

Job sharing is a part-time employment alternative which offers advantages for employers interested in retaining experienced staff and nurses who are seeking a more equitable balance between work life and home life responsibilities. This quasi experimental, ex post facto research study was designed to determine if there are differences in job satisfaction, burnout, and desire to leave their position, in nurses who are employed in full-time, part-time, or job sharing positions. The sample (N = 269) was drawn from a large Canadian teaching and referral hospital. Three sample groups were developed, consisting of job sharing, full-time, and part-time nurses, respectively. Descriptive statistics were used to identify characteristics of the selected population. Analysis of variance was used to examine differences between the three employment groups on the outcome measures of job satisfaction, burnout, and desire to leave their position. The results of this study significantly support the belief that job sharing has a positive impact on job satisfaction and job retention. Implications for nursing administrators as well as individual nurses will be discussed.

Socio-Historical Factors Mediating Collaborative Teaching and Learning: A Design-Based Investigation and Intervention

ERIC Educational Resources Information Center

Hackett, Jacob

2016-01-01

Collaborative (Co-)teaching is a complex instructional delivery model used to improve teaching practice in inclusive settings. The model involves multiple certified teachers--representing both special and general education--sharing the same space and presenting material to classrooms with a wide variance in learning needs. Co-teaching has become…

The Contribution of Working Memory to Fluid Reasoning: Capacity, Control, or Both?

ERIC Educational Resources Information Center

Chuderski, Adam; Necka, Edward

2012-01-01

Fluid reasoning shares a large part of its variance with working memory capacity (WMC). The literature on working memory (WM) suggests that the capacity of the focus of attention responsible for simultaneous maintenance and integration of information within WM, as well as the effectiveness of executive control exerted over WM, determines…

Measuring the Relationship between Scores on Two Questionnaires

ERIC Educational Resources Information Center

Richardson, John T. E.

2007-01-01

Characterising the relationship between participants' scores on two different questionnaires is a common problem in educational research. The complement of the statistic known as Wilks' lambda measures the amount of variance shared between the scores obtained by the same group of participants on two sets of variables. (1 - lambda) is symmetric, in…

The Influence of Hemispheric Dominance on Scores of the Myers-Briggs Type Indicator.

ERIC Educational Resources Information Center

Hartman, Steve E.; And Others

1997-01-01

Results for 75 medical students and 248 undergraduates suggest that the Myers-Briggs Type Indicator appears to sample only 3 bipolar personality dimensions rather than the 4 that the use of "type tables" implies. One of these dimensions shares substantial variance with the cognitive model of hemispheric dominance. (SLD)

Inferring a Child's Level of Self-esteem from a Knowledge of Other Personality Factors.

ERIC Educational Resources Information Center

Kawash, George F.; Clewes, Janet L.

1986-01-01

Correlation and regression analysis confirmed that there is a high degree of shared variance between Coopersmith's Self-Esteem Inventory (SEI) and the Children's Personality Questionnaire (CPQ), suggesting that self-esteem may be more integrated within an individual's total personality functioning than has been discussed in the literature.…

Infant Emotion Regulation Strategy Moderates Relations between Self-Reported Maternal Depressive Symptoms and Infant HPA Activity

ERIC Educational Resources Information Center

Khoury, Jennifer E.; Gonzalez, Andrea; Levitan, Robert; Masellis, Mario; Basile, Vincenzo; Atkinson, Leslie

2016-01-01

Children of mothers with depressive symptoms often have high cortisol levels. Research shows that various child characteristics (e.g., attachment pattern, internalizing behaviours, and temperament) moderate this association. We suggest that these characteristics share common variance with emotion regulation strategy. Therefore, we examine infant…

Third Grade Written Narratives: A Cross-Linguistic Study.

ERIC Educational Resources Information Center

Gregory, George Ann

A study examined what a third grader might understand about composing a common genre like the narrative, given the degree of variance among approaches and experience. Data were collected from different school sites over a period of several years. These sites shared common geographical areas: three schools were located in the Sonoran desert shared…

Synaptic noise is an information bottleneck in the inner retina during dynamic visual stimulation

PubMed Central

Freed, Michael A; Liang, Zhiyin

2014-01-01

In daylight, noise generated by cones determines the fidelity with which visual signals are initially encoded. Subsequent stages of visual processing require synapses from bipolar cells to ganglion cells, but whether these synapses generate a significant amount of noise was unknown. To characterize noise generated by these synapses, we recorded excitatory postsynaptic currents from mammalian retinal ganglion cells and subjected them to a computational noise analysis. The release of transmitter quanta at bipolar cell synapses contributed substantially to the noise variance found in the ganglion cell, causing a significant loss of fidelity from bipolar cell array to postsynaptic ganglion cell. Virtually all the remaining noise variance originated in the presynaptic circuit. Circuit noise had a frequency content similar to noise shared by ganglion cells but a very different frequency content from noise from bipolar cell synapses, indicating that these synapses constitute a source of independent noise not shared by ganglion cells. These findings contribute a picture of daylight retinal circuits where noise from cones and noise generated by synaptic transmission of cone signals significantly limit visual fidelity. PMID:24297850

Deterministic theory of Monte Carlo variance

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

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

Enduring Consequences From the War on Drugs: How Policing Practices Impact HIV Risk Among People Who Inject Drugs in Baltimore City.

PubMed

Flath, Natalie; Tobin, Karin; King, Kelly; Lee, Alexandra; Latkin, Carl

2017-07-03

Neighborhood-level characteristics, including police activity, are associated with HIV and Hepatitis C injection risk-behaviors among people who inject drugs (PWID). However, the pathways through which these neighborhood perceptions shape individual-level HIV risk behaviors are unclear. This study helps to explain perceived behaviors between perceived neighborhood police activity and HIV injection risk behavior (i.e., injection syringe/tool sharing in the previous 6 months). A sample of (n = 366) PWIDs who self-reported recent use were recruited using community-based outreach methods in Baltimore, Maryland. Neighborhood police perceptions were assessed by asking participants whether they would (1) be more likely to ask others to share injection tools in the context of heightened police activity and (2) be less likely to carry syringes with them due to fear of arrest. Poisson regression with robust variance was used to identify statistical relationships. Recent police encounters, frequency of heroin injection, and sociodemographic characteristics were controlled for in the model. Neighborhood police perceptions shaped injection-risk behavior. Half of the sample (49%) reported an aversion of carrying personal syringes, due to fear of arrest. Those who agreed they would be more likely to ask others to share injection equipment in the context of heightened police activity were more likely to share syringes (21% vs. 3%, p <.01). Adjusted models showed that syringe sharing was independently associated with asking to borrow equipment in neighborhoods with perceived heightened police activity (aPR: 2.22, 95% confidence interval (CI): 1.7, 3.0). This study sheds light on how police perceptions may influence injection risk behavior. While these relationships require further elucidation, this study suggests that public health interventions aiming to reduce HIV risk would benefit from improving community-police relationships.

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.

WE-FG-207B-04: Noise Suppression for Energy-Resolved CT Via Variance Weighted Non-Local Filtration

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

Harms, J; Zhu, L

Purpose: The photon starvation problem is exacerbated in energy-resolved CT, since the detected photons are shared by multiple energy channels. Using pixel similarity-based non-local filtration, we aim to produce accurate and high-resolution energy-resolved CT images with significantly reduced noise. Methods: Averaging CT images reconstructed from different energy channels reduces noise at the price of losing spectral information, while conventional denoising techniques inevitably degrade image resolution. Inspired by the fact that CT images of the same object at different energies share the same structures, we aim to reduce noise of energy-resolved CT by averaging only pixels of similar materials - amore » non-local filtration technique. For each CT image, an empirical exponential model is used to calculate the material similarity between two pixels based on their CT values and the similarity values are organized in a matrix form. A final similarity matrix is generated by averaging these similarity matrices, with weights inversely proportional to the estimated total noise variance in the sinogram of different energy channels. Noise suppression is achieved for each energy channel via multiplying the image vector by the similarity matrix. Results: Multiple scans on a tabletop CT system are used to simulate 6-channel energy-resolved CT, with energies ranging from 75 to 125 kVp. On a low-dose acquisition at 15 mA of the Catphan©600 phantom, our method achieves the same image spatial resolution as a high-dose scan at 80 mA with a noise standard deviation (STD) lower by a factor of >2. Compared with another non-local noise suppression algorithm (ndiNLM), the proposed algorithms obtains images with substantially improved resolution at the same level of noise reduction. Conclusion: We propose a noise-suppression method for energy-resolved CT. Our method takes full advantage of the additional structural information provided by energy-resolved CT and preserves image values at each energy level. Research reported in this publication was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics.

PubMed

Pare, Guillaume; Mao, Shihong; Deng, Wei Q

2016-06-08

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

PubMed Central

Pare, Guillaume; Mao, Shihong; Deng, Wei Q.

2016-01-01

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519

Comparing transformation methods for DNA microarray data

PubMed Central

Thygesen, Helene H; Zwinderman, Aeilko H

2004-01-01

Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method. PMID:15202953

Comparing transformation methods for DNA microarray data.

PubMed

Thygesen, Helene H; Zwinderman, Aeilko H

2004-06-17

When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

A model of prediction and cross-validation of fat-free mass in men with motor complete spinal cord injury.

PubMed

Gorgey, Ashraf S; Dolbow, David R; Gater, David R

2012-07-01

To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Cross-sectional design. Research setting in a large medical center. Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Not applicable. Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R(2)=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R(2)=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R(2)=.53, SEE=5.3kg, P<.0001). The whole-body FFM(predicted) (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM(measured) (FFM measured using dual-energy x-ray absorptiometry scan) (R(2)=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM(measured), and 66% of legs FFM(measured). The trunk FFM(predicted) shared 69% of the variance in trunk FFM(measured) (R(2)=.69, SEE=2.7kg, P<.0001), and legs FFM(predicted) shared 67% of the variance in legs FFM(measured) (R(2)=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Psychopathology in 7-year-old children: Differences in maternal and paternal ratings and the genetic epidemiology.

PubMed

Wesseldijk, Laura W; Fedko, Iryna O; Bartels, Meike; Nivard, Michel G; van Beijsterveldt, Catharina E M; Boomsma, Dorret I; Middeldorp, Christel M

2017-04-01

The assessment of children's psychopathology is often based on parental report. Earlier studies have suggested that rater bias can affect the estimates of genetic, shared environmental and unique environmental influences on differences between children. The availability of a large dataset of maternal as well as paternal ratings of psychopathology in 7-year old children enabled (i) the analysis of informant effects on these assessments, and (ii) to obtain more reliable estimates of the genetic and non-genetic effects. DSM-oriented measures of affective, anxiety, somatic, attention-deficit/hyperactivity, oppositional-defiant, conduct, and obsessive-compulsive problems were rated for 12,310 twin pairs from the Netherlands Twin Register by mothers (N = 12,085) and fathers (N = 8,516). The effects of genetic and non-genetic effects were estimated on the common and rater-specific variance. For all scales, mean scores on maternal ratings exceeded paternal ratings. Parents largely agreed on the ranking of their child's problems (r 0.60-0.75). The heritability was estimated over 55% for maternal and paternal ratings for all scales, except for conduct problems (44-46%). Unbiased shared environmental influences, i.e., on the common variance, were significant for affective (13%), oppositional (13%), and conduct problems (37%). In clinical settings, different cutoffs for (sub)clinical scores could be applied to paternal and maternal ratings of their child's psychopathology. Only for conduct problems, shared environmental and genetic influences explain an equal amount in differences between children. For the other scales, genetic factors explain the majority of the variance, especially for the common part that is free of rater bias. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Are there shared environmental influences on adolescent behavior? Evidence from a study of adoptive siblings.

PubMed

Buchanan, Jacob P; McGue, Matt; Keyes, Margaret; Iacono, William G

2009-09-01

The failure to identify specific non-shared environmental influences on behavior coupled with the belief that shared environmental factors contribute minimally to individual differences in behavior has led to the concern that major environmental determinants of behavior may be idiosyncratic, and therefore undetectable. We used data on adoptive (N = 246) and biologically related (N = 130) same-sex sibling pairs (mean ages = 16.1 years older sibling; 13.8 years younger sibling) from the Sibling Interaction and Behavior Study (SIBS) to determine whether non-idiosyncratic environmental factors shared by siblings contributed to individual differences in a diverse set of behavioral outcomes. Evidence for shared environmental influence was sought for eight composite measures covering a wide array of adolescent functioning: Academic Achievement, Total IQ, Substance Use Disorders, Externalizing Disorders, Internalizing Disorders, Peer Groups, Disinhibited Personality, and Negative Emotionality. For six of eight composites, significant shared environmental effects, accounting for 14-22% of the variance, were observed for these same-sex sibling pairs. These findings support the use of adoptive sibling designs to directly estimate shared environmental effects and implicate the existence of systematic environmental influences on behavior that are potentially detectable.

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

Applications of non-parametric statistics and analysis of variance on sample variances

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

PubMed

Li, Shi; Mukherjee, Bhramar; Taylor, Jeremy M G; Rice, Kenneth M; Wen, Xiaoquan; Rice, John D; Stringham, Heather M; Boehnke, Michael

2014-07-01

With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes. © 2014 WILEY PERIODICALS, INC.

Shared Decision Making and Other Variables as Correlates of Satisfaction with Health Care Decisions in a United States National Survey

PubMed Central

Wills, Celia E.; Holloman, Christopher; Olson, Jacklyn; Hechmer, Catherine; Miller, Carla K.; Duchemin, Anne-Marie

2012-01-01

Objective The purpose of this study was to examine the relationship between shared decision-making (SDM) and satisfaction with decision (SWD) within a larger survey of patient decision-making in health care consultations. Methods A randomly selected age-proportionate national sample of adults (aged 21–70 years) stratified on race, ethnicity, and gender (N = 488) was recruited from a health research volunteer registry and completed an online survey with reference to a recent health consultation. Measures included the Shared Decision Making-9 questionnaire (SDM-Q-9), Satisfaction With Decision (SWD) scale, sociodemographic, health, and other standardized decision-making measures. Forward selection weighted multiple regression analysis was used to model correlates of SWD. Results After controlling for sociodemographic variables, SDM-Q-9 total score was associated with SWD, adjusted R2 = .368, p < .001. Three of nine SDM-Q-9 items accounted for significant proportions of variance in SWD. Conclusion SDM was positively associated with SWD and was strongest for three areas of SDM: patients being helped in a health care consultation with understanding information, with treatment preference elicitation, and with weighing options thoroughly. Practice Implications By identifying variables such as SDM that are associated with SWD, health care interventions can better target modifiable factors to enhance satisfaction and other outcomes. PMID:22410642

Genetic Factors Influence Serological Measures of Common Infections

PubMed Central

Rubicz, Rohina; Leach, Charles T.; Kraig, Ellen; Dhurandhar, Nikhil V.; Duggirala, Ravindranath; Blangero, John; Yolken, Robert; Göring, Harald H.H.

2011-01-01

Background/Aims Antibodies against infectious pathogens provide information on past or present exposure to infectious agents. While host genetic factors are known to affect the immune response, the influence of genetic factors on antibody levels to common infectious agents is largely unknown. Here we test whether antibody levels for 13 common infections are significantly heritable. Methods IgG antibodies to Chlamydophila pneumoniae, Helicobacter pylori, Toxoplasma gondii, adenovirus 36 (Ad36), hepatitis A virus, influenza A and B, cytomegalovirus, Epstein-Barr virus, herpes simplex virus (HSV)-1 and −2, human herpesvirus-6, and varicella zoster virus were determined for 1,227 Mexican Americans. Both quantitative and dichotomous (seropositive/seronegative) traits were analyzed. Influences of genetic and shared environmental factors were estimated using variance components pedigree analysis, and sharing of underlying genetic factors among traits was investigated using bivariate analyses. Results Serological phenotypes were significantly heritable for most pathogens (h2 = 0.17–0.39), except for Ad36 and HSV-2. Shared environment was significant for several pathogens (c2 = 0.10–0.32). The underlying genetic etiology appears to be largely different for most pathogens. Conclusions Our results demonstrate, for the first time for many of these pathogens, that individual genetic differences of the human host contribute substantially to antibody levels to many common infectious agents, providing impetus for the identification of underlying genetic variants, which may be of clinical importance. PMID:21996708

Relationship between Sleep Habits and Nighttime Sleep among Healthy Preschool Children in Taiwan.

PubMed

Lo, Ming Jae

2016-12-01

Introduction : We examined the nighttime sleep habits associated with insufficient sleep quantity and poor sleep quality among healthy preschool-aged Taiwanese children. Materials and Methods : The study population of this cross-sectional survey was a stratified random sample of 3 to 6-year-old preschool children from 19 cities and counties in Taiwan. A caregiver-administered questionnaire was used to collect information on preschooler sleep quantity (sleep duration and sleep latency) and sleep quality (sleep disturbances and disruption) and potentially related sleep habits. Results : Of the 1253 children for whom analysable survey data were collected (children's mean age: 5.03 ± 1.27 years), more than half (53.07%) engaged in bedtime television (TV)-viewing, 88.95% required a sleep reminder, 43.85% exhibited bedtime resistance, 93.6% engaged in co-sleeping (bed-sharing or room-sharing), and only 33.72% slept in a well darkened bedroom. Bedtime TV-viewing, co-sleeping, bedroom light exposure, and bedtime resistance were the primary predictors, without a bedtime TV-viewing habit was the strongest predictor analysed; it explained 15.2% and 19.9% of the variance in adequate sleep quantity and improved sleep quality in preschool children. Conclusion : Sleep loss and poor sleep quality in preschool children could be alleviated, at least partly, by curtailing bedtime TV-viewing, limiting light exposure during sleeping, and reducing bed-sharing habit.

Genetic contributions to antisocial personality and behavior: a meta-analytic review from an evolutionary perspective.

PubMed

Ferguson, Christopher J

2010-01-01

Evidence from behavioral genetics supports the conclusion that a significant amount of the variance in antisocial personality and behavior (APB) is due to genetic contributions. Many scientific fields such as psychology, medicine, and criminal justice struggle to incorporate this information with preexisting paradigms that focused exclusively on external or learned etiology of antisocial behavior. The current paper presents a meta-analytic review of behavioral genetic etiological studies of APB. Results indicated that 56% of the variance in APB can be explained through genetic influences, with 11% due to shared non-genetic influences, and 31% due to unique non-genetic influences. This data is discussed in relation to evolutionary psychological theory.

Force-stabilizing synergies in motor tasks involving two actors

PubMed Central

Solnik, Stanislaw; Reschechtko, Sasha; Wu, Yen-Hsun; Zatsiorsky, Vladimir M.; Latash, Mark L.

2015-01-01

We investigated the ability of two persons to produce force-stabilizing synergies in accurate multi-finger force production tasks under visual feedback on the total force only. The subjects produced a time profile of total force (the sum of two hand forces in one-person tasks and the sum of two subject forces in two-person tasks) consisting of a ramp-up, steady-state, and ramp-down segments; the steady-state segment was interrupted in the middle by a quick force pulse. Analyses of the structure of inter-trial finger force variance, motor equivalence, anticipatory synergy adjustments (ASAs), and the unintentional drift of the sharing pattern were performed. The two-person performance was characterized by a dramatically higher amount of inter-trial variance that did not affect total force, higher finger force deviations that did not affect total force (motor equivalent deviations), shorter ASAs, and larger drift of the sharing pattern. The rate of sharing pattern drift correlated with the initial disparity between the forces produced by the two persons (or two hands). The drift accelerated following the quick force pulse. Our observations show that sensory information on the task-specific performance variable is sufficient for the organization of performance-stabilizing synergies. They suggest, however, that two actors are less likely to follow a single optimization criterion as compared to a single performer. The presence of ASAs in the two-person condition might reflect fidgeting by one or both of the subjects. We discuss the characteristics of the drift in the sharing pattern as reflections of different characteristic times of motion within the sub-spaces that affect and do not affect salient performance variables. PMID:26105756

Force-stabilizing synergies in motor tasks involving two actors.

PubMed

Solnik, Stanislaw; Reschechtko, Sasha; Wu, Yen-Hsun; Zatsiorsky, Vladimir M; Latash, Mark L

2015-10-01

We investigated the ability of two persons to produce force-stabilizing synergies in accurate multi-finger force production tasks under visual feedback on the total force only. The subjects produced a time profile of total force (the sum of two hand forces in one-person tasks and the sum of two subject forces in two-person tasks) consisting of a ramp-up, steady-state, and ramp-down segments; the steady-state segment was interrupted in the middle by a quick force pulse. Analyses of the structure of inter-trial finger force variance, motor equivalence, anticipatory synergy adjustments (ASAs), and the unintentional drift of the sharing pattern were performed. The two-person performance was characterized by a dramatically higher amount of inter-trial variance that did not affect total force, higher finger force deviations that did not affect total force (motor equivalent deviations), shorter ASAs, and larger drift of the sharing pattern. The rate of sharing pattern drift correlated with the initial disparity between the forces produced by the two persons (or two hands). The drift accelerated following the quick force pulse. Our observations show that sensory information on the task-specific performance variable is sufficient for the organization of performance-stabilizing synergies. They suggest, however, that two actors are less likely to follow a single optimization criterion as compared to a single performer. The presence of ASAs in the two-person condition might reflect fidgeting by one or both of the subjects. We discuss the characteristics of the drift in the sharing pattern as reflections of different characteristic times of motion within the subspaces that affect and do not affect salient performance variables.

A sibling based design to quantify genetic and shared environmental effects of venous thromboembolism in Sweden.

PubMed

Zöller, Bengt; Ohlsson, Henrik; Sundquist, Jan; Sundquist, Kristina

2017-01-01

Few large studies have examined the heritability of venous thromboembolism (VTE). Moreover, twin studies have been suggested to overestimate heritability. The aim of the present study was to determine the heritability nationwide in the general Swedish population using full siblings and half-siblings. VTE was defined using the Swedish patient register. Full sibling (FS) and half-sibling (HS) pairs born 1950-1990 were obtained from the Swedish Multi-generation Register. A maximum of 5years age difference was allowed. We also required that the individuals within the pair should reside in the same household for at least 8years or not at all (0years) before the youngest turned 16. Information about sibling pair residence within the same household, small residential area, and municipality was obtained from Statistics Sweden. We assumed three potential sources of liability to VTE: additive genetic (A), shared (or common/familial) environment (C), and unique environment (E) components. Totally 881,206 FS pairs and 95,198 HS pairs were included. The full model predicted heritability for VTE with 47% for males and 40% for females. Environmental factors shared by siblings contributed to 0% of the variance in liability for both sexes, and unique environment (E) components accounted for 53% in males and 60% in females. The high heritability of VTE risk indicates that genetic susceptibility plays a substantial role for VTE in the Swedish general population. Overestimation of heritability from twin studies is not likely. The proportion of the variance attributable to shared familial environment factors is small. Subject codes: Genetics, epidemiology, thrombosis, cardiovascular disease, embolism. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social Information Processing in Children: Specific Relations to Anxiety, Depression, and Affect

ERIC Educational Resources Information Center

Luebbe, Aaron M.; Bell, Debora J.; Allwood, Maureen A.; Swenson, Lance P.; Early, Martha C.

2010-01-01

Two studies examined shared and unique relations of social information processing (SIP) to youth's anxious and depressive symptoms. Whether SIP added unique variance over and above trait affect in predicting internalizing symptoms was also examined. In Study 1, 215 youth (ages 8-13) completed symptom measures of anxiety and depression and a…

The Therapeutic Relationship in the Brief Treatment of Depression: Contributions to Clinical Improvement and Enhanced Adaptive Capacities

ERIC Educational Resources Information Center

Zuroff, David C.; Blatt, Sidney J.

2006-01-01

Using data from the National Institute of Mental Health Treatment for Depression Collaborative Research Program, the authors examined the impact on treatment outcome of the patient's perception of the quality of the therapeutic relationship and contribution to the therapeutic alliance. Shared variance with early clinical improvement was removed…

Psychometric Evaluation of the Demographic Index of Cultural Exposure (DICE) in Two Mexican-Origin Community Samples

ERIC Educational Resources Information Center

Cruz, Rick A.; Wilkinson, Anna V.; Bondy, Melissa L.; Koehly, Laura M.

2012-01-01

Reliability and validity evidence is provided for the Demographic Index of Cultural Exposure (DICE), consisting of six demographic proxy indicators of acculturation, within two community samples of Mexican-origin adults (N= 497 for each sample). Factor analytic procedures were used to examine the common variance shared between the six demographic…

How "Community" Matters for How People Interact With Information: Mixed Methods Study of Young Men Who Have Sex With Other Men

PubMed Central

Meadowbrooke, Chrysta Cathleen; Loveluck, Jimena; Hickok, Andrew; Bauermeister, Jose Artruro

2013-01-01

Background We lack a systematic portrait of the relationship between community involvement and how people interact with information. Young men who have sex with men (YMSM) are a population for which these relationships are especially salient: their gay community involvement varies and their information technology use is high. YMSM under age 24 are also one of the US populations with the highest risk of HIV/AIDS. Objective To develop, test, and refine a model of gay community involvement (GCI) factors in human-information interaction (HII) as applied to HIV/AIDS information among YMSM, specifically examining the role of Internet use in GCI and HII. Methods Mixed methods included: 1) online questionnaire with 194 YMSM; and 2) qualitative interviews with 19 YMSM with high GCI levels. Recruitment utilized social media, dating websites, health clinics, bars/clubs, and public postings. The survey included questions regarding HIV/AIDS–related information acquisition and use patterns, gay community involvement, risk behaviors, and technology use. For survey data, we tested multiple linear regression models using a series of community- and information-related variables as dependent variables. Independent variables included community- and information-related variables and demographic covariates. We then conducted a recursive path analysis in order to estimate a final model, which we refined through a grounded theory analysis of qualitative interview data. Results Four community-related variables significantly predicted how people interact with information (HII variables): 1) gay community involvement (GCI), 2) social costs of information seeking, 3) network expertise accessibility, and 4) community relevance. GCI was associated with significantly lower perceived social costs of HIV/AIDS information seeking (R 2=0.07). GCI and social costs significantly predicted network expertise accessibility (R 2=0.14). GCI predicted 14% of the variance in community relevance and 9% of the variance in information seeking frequency. Incidental HIV/AIDS information acquisition (IIA) was also significantly predicted by GCI (R 2=0.16). 28% of the variance in HIV/AIDS information use was explained by community relevance, network expertise access, and both IIA and information seeking. The final path model showed good fit: the RSMEA was 0.054 (90% CI: .000-.101); the Chi-square was non-significant (χ2(11)=17.105; P=.105); and the CFI was 0.967. Qualitative findings suggest that the model may be enhanced by including information sharing: organizing events, disseminating messages, encouraging safety, and referring and recommending. Information sharing emerged under conditions of pro-social community value enactment and may have consequences for further HII. YMSM with greater GCI generally used the Internet more, although they chatted online less. Conclusions HIV/AIDS–related HII and associated technology uses are community-embedded processes. The model provides theoretical mediators that may serve as a focus for intervention: 1) valuing HIV/AIDS information, through believing it is relevant to one’s group, and 2) supportive and knowledgeable network members with whom to talk about HIV/AIDS. Pro-social community value endorsement and information sharing may also be important theoretical mediators. Our model could open possibilities for considering how informatics interventions can also be designed as community-level interventions and vice versa. PMID:23428825

Estimation of genetic parameters and their sampling variances of quantitative traits in the type 2 modified augmented design

USDA-ARS?s Scientific Manuscript database

We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

Shared genetic effects between hepatic steatosis and fibrosis: A prospective twin study

PubMed Central

Cui, Jeffrey; Chen, Chi-Hua; Lo, Min-Tzu; Schork, Nicholas; Bettencourt, Ricki; Gonzalez, Monica P; Bhatt, Archana; Hooker, Jonathan; Shaffer, Katherine; Nelson, Karen E; Long, Michelle T; Brenner, David A; Sirlin, Claude B; Loomba, Rohit

2016-01-01

Introduction Nonalcoholic fatty liver disease (NAFLD) is associated with metabolic risk factors including hypertension and dyslipidemia, and may progress to liver fibrosis. Previous studies have shown that hepatic steatosis and fibrosis are heritable but whether they have a significant shared gene effect is unknown. This study aimed to examine the shared gene effects between hepatic steatosis, fibrosis, and their associations with metabolic risk factors. Methods This is a cross-sectional analysis of a prospective cohort of well-characterized, community-dwelling twins (45 monozygotic, 20 dizygotic twin pairs, 130 total subjects) from Southern California. Hepatic steatosis was assessed with MRI-proton density fat fraction (MRI-PDFF) and hepatic fibrosis was assessed with magnetic resonance elastography (MRE). A standard bivariate twin AE model was used to estimate the proportion of phenotypic variance between two phenotypes accounted for by additive genetic effects (A) and individual-specific environmental effects (E). Genetic correlations (rG) estimated from this model represent the degree to which the genetic determinants of two phenotypes overlap. Results The mean (±SD) age and BMI were 47.1 (±21.9) years and 26.9 (±6.5) kg/m2, respectively. 20% (26/130) of the cohort had hepatic steatosis (MRI-PDFF ≥5%) and 8.2% (10/122) had hepatic fibrosis (MRE ≥3Kpa). Blood pressure (systolic and diastolic), triglycerides, glucose, homeostatic model assessment of insulin resistance (HOMA-IR), insulin, hemoglobin A1c (HbA1c), and low high-density lipoprotein (HDL) had significant shared gene effects with hepatic steatosis. Triglycerides, glucose, HOMA-IR, insulin, HbA1c, and low HDL had significant shared gene effects with hepatic fibrosis. Hepatic steatosis and fibrosis had a highly significant shared gene effect of 0.756 (95% CI: 0.716–1, p<0.0001). Conclusions Genes involved with steatosis pathogenesis may also be involved with fibrosis pathogenesis. PMID:27315352

New Variance-Reducing Methods for the PSD Analysis of Large Optical Surfaces

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2010-01-01

Edge data of a measured surface map of a circular optic result in large variance or "spectral leakage" behavior in the corresponding Power Spectral Density (PSD) data. In this paper we present two new, alternative methods for reducing such variance in the PSD data by replacing the zeros outside the circular area of a surface map by non-zero values either obtained from a PSD fit (method 1) or taken from the inside of the circular area (method 2).

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Maternal pre-pregnancy weight and externalising behaviour problems in preschool children: a UK-based twin study.

PubMed

Antoniou, Evangelia E; Fowler, Tom; Reed, Keith; Southwood, Taunton R; McCleery, Joseph P; Zeegers, Maurice P

2014-10-14

To estimate the heritability of child behaviour problems and investigate the association between maternal pre-pregnancy overweight and child behaviour problems in a genetically sensitive design. Observational cross-sectional study. The Twins and Multiple Births Association Heritability Study (TAMBAHS) is an online UK-wide volunteer-based study investigating the development of twins from birth until 5 years of age. A total of 443 (16% of the initial registered members) mothers answered questions on pre-pregnancy weight and their twins' internalising and externalising problems using the Child Behavior Checklist and correcting for important covariates including gestational age, twins' birth weight, age and sex, mother's educational level and smoking (before, during and after pregnancy). The heritability of behaviour problems and their association with maternal pre-pregnancy weight. The genetic analysis suggested that genetic and common environmental factors account for most of the variation in externalising disorders (an ACE model was the most parsimonious with genetic factors (A) explaining 46% (95% CI 33% to 60%) of the variance, common environment (C) explaining 42% (95% CI 27% to 54%) and non-shared environmental factors (E) explaining 13% (95% CI 10% to 16%) of the variance. For internalising problems, a CE model was the most parsimonious model with the common environment explaining 51% (95% CI 44% to 58%) of the variance and non-shared environment explaining 49% (95% CI 42% to 56%) of the variance. Moreover, the regression analysis results suggested that children of overweight mothers showed a trend (OR=1.10, 95% CI 0.58% to 2.06) towards being more aggressive and exhibit externalising behaviours compared to children of normal weight mothers. Maternal pre-pregnancy weight may play a role in children's aggressive behaviour. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas

PubMed Central

Lescroart, Mark D.; Stansbury, Dustin E.; Gallant, Jack L.

2015-01-01

Perception of natural visual scenes activates several functional areas in the human brain, including the Parahippocampal Place Area (PPA), Retrosplenial Complex (RSC), and the Occipital Place Area (OPA). It is currently unclear what specific scene-related features are represented in these areas. Previous studies have suggested that PPA, RSC, and/or OPA might represent at least three qualitatively different classes of features: (1) 2D features related to Fourier power; (2) 3D spatial features such as the distance to objects in a scene; or (3) abstract features such as the categories of objects in a scene. To determine which of these hypotheses best describes the visual representation in scene-selective areas, we applied voxel-wise modeling (VM) to BOLD fMRI responses elicited by a set of 1386 images of natural scenes. VM provides an efficient method for testing competing hypotheses by comparing predictions of brain activity based on encoding models that instantiate each hypothesis. Here we evaluated three different encoding models that instantiate each of the three hypotheses listed above. We used linear regression to fit each encoding model to the fMRI data recorded from each voxel, and we evaluated each fit model by estimating the amount of variance it predicted in a withheld portion of the data set. We found that voxel-wise models based on Fourier power or the subjective distance to objects in each scene predicted much of the variance predicted by a model based on object categories. Furthermore, the response variance explained by these three models is largely shared, and the individual models explain little unique variance in responses. Based on an evaluation of previous studies and the data we present here, we conclude that there is currently no good basis to favor any one of the three alternative hypotheses about visual representation in scene-selective areas. We offer suggestions for further studies that may help resolve this issue. PMID:26594164

Heritability estimates of the Big Five personality traits based on common genetic variants.

PubMed

Power, R A; Pluess, M

2015-07-14

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P < 0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG = 1.00, P < 0.001), despite low phenotypic correlation (r = - 0.09, P < 0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.

Psychometric evaluation of the Shared Decision-Making Instrument--Revised.

PubMed

Bartlett, Jacqueline A; Peterson, Jane A

2013-02-01

The purpose of this study was to evaluate the psychometric properties of the Shared Decision-Making Inventory-Revised (SDMI-R) to measure four constructs (knowledge, attitudes, self-efficacy, and intent) theoretically defined as vital in discussing the human papillomavirus (HPV) disease and vaccine with clients. The SDMI-R was distributed to a sample (N = 1,525) of school nurses. Correlational matrixes denoted moderate to strong correlations, indicating adequate internal reliability. Reliability for the total instrument was satisfactory (α = .874) along with Attitude, Self-Efficacy and Intent subscales .828, .917, .891, respectively. Exploratory factor analysis revealed five components that explained 75.96% of the variance.

Examining regional variability in work ethic within Mexico: Individual difference or shared value.

PubMed

Arciniega, Luis M; Woehr, David J; Del Rincón, Germán A

2018-02-19

Despite the acceptance of work ethic as an important individual difference, little research has examined the extent to which work ethic may reflect shared environmental or socio-economic factors. This research addresses this concern by examining the influence of geographic proximity on the work ethic experienced by 254 employees from Mexico, working in 11 different cities in the Northern, Central and Southern regions of the country. Using a sequence of complementary analyses to assess the main source of variance on seven dimensions of work ethic, our results indicate that work ethic is most appropriately considered at the individual level. © 2018 International Union of Psychological Science.

How "community" matters for how people interact with information: mixed methods study of young men who have sex with other men.

PubMed

Veinot, Tiffany Christine; Meadowbrooke, Chrysta Cathleen; Loveluck, Jimena; Hickok, Andrew; Bauermeister, Jose Artruro

2013-02-21

We lack a systematic portrait of the relationship between community involvement and how people interact with information. Young men who have sex with men (YMSM) are a population for which these relationships are especially salient: their gay community involvement varies and their information technology use is high. YMSM under age 24 are also one of the US populations with the highest risk of HIV/AIDS. To develop, test, and refine a model of gay community involvement (GCI) factors in human-information interaction (HII) as applied to HIV/AIDS information among YMSM, specifically examining the role of Internet use in GCI and HII. Mixed methods included: 1) online questionnaire with 194 YMSM; and 2) qualitative interviews with 19 YMSM with high GCI levels. Recruitment utilized social media, dating websites, health clinics, bars/clubs, and public postings. The survey included questions regarding HIV/AIDS-related information acquisition and use patterns, gay community involvement, risk behaviors, and technology use. For survey data, we tested multiple linear regression models using a series of community- and information-related variables as dependent variables. Independent variables included community- and information-related variables and demographic covariates. We then conducted a recursive path analysis in order to estimate a final model, which we refined through a grounded theory analysis of qualitative interview data. Four community-related variables significantly predicted how people interact with information (HII variables): 1) gay community involvement (GCI), 2) social costs of information seeking, 3) network expertise accessibility, and 4) community relevance. GCI was associated with significantly lower perceived social costs of HIV/AIDS information seeking (R(2)=0.07). GCI and social costs significantly predicted network expertise accessibility (R(2)=0.14). GCI predicted 14% of the variance in community relevance and 9% of the variance in information seeking frequency. Incidental HIV/AIDS information acquisition (IIA) was also significantly predicted by GCI (R(2)=0.16). 28% of the variance in HIV/AIDS information use was explained by community relevance, network expertise access, and both IIA and information seeking. The final path model showed good fit: the RSMEA was 0.054 (90% CI: .000-.101); the Chi-square was non-significant (χ(2)(11)=17.105; P=.105); and the CFI was 0.967. Qualitative findings suggest that the model may be enhanced by including information sharing: organizing events, disseminating messages, encouraging safety, and referring and recommending. Information sharing emerged under conditions of pro-social community value enactment and may have consequences for further HII. YMSM with greater GCI generally used the Internet more, although they chatted online less. HIV/AIDS-related HII and associated technology uses are community-embedded processes. The model provides theoretical mediators that may serve as a focus for intervention: 1) valuing HIV/AIDS information, through believing it is relevant to one's group, and 2) supportive and knowledgeable network members with whom to talk about HIV/AIDS. Pro-social community value endorsement and information sharing may also be important theoretical mediators. Our model could open possibilities for considering how informatics interventions can also be designed as community-level interventions and vice versa.

Methods to Estimate the Between-Study Variance and Its Uncertainty in Meta-Analysis

ERIC Educational Resources Information Center

Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia

2016-01-01

Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

Familial influences on the full range of variability in attention and activity levels during adolescence: A longitudinal twin study.

PubMed

Peng, Chun-Zi; Grant, Julia D; Heath, Andrew C; Reiersen, Angela M; Mulligan, Richard C; Anokhin, Andrey P

2016-05-01

To investigate familial influences on the full range of variability in attention and activity across adolescence, we collected maternal ratings of 339 twin pairs at ages 12, 14, and 16, and estimated the transmitted and new familial influences on attention and activity as measured by the Strengths and Weaknesses of Attention-Deficit/Hyperactivity Disorder Symptoms and Normal Behavior Scale. Familial influences were substantial for both traits across adolescence: genetic influences accounted for 54%-73% (attention) and 31%-73% (activity) of the total variance, and shared environmental influences accounted for 0%-22% of the attention variance and 13%-57% of the activity variance. The longitudinal stability of individual differences in attention and activity was largely accounted for by familial influences transmitted from previous ages. Innovations over adolescence were also partially attributable to familial influences. Studying the full range of variability in attention and activity may facilitate our understanding of attention-deficit/hyperactivity disorder's etiology and intervention.

Relationship of word- and sentence-level working memory to reading and writing in second, fourth, and sixth grade.

PubMed

Berninger, Virginia W; Abbott, Robert D; Swanson, H Lee; Lovitt, Dan; Trivedi, Pam; Lin, Shin-Ju Cindy; Gould, Laura; Youngstrom, Marci; Shimada, Shirley; Amtmann, Dagmar

2010-04-01

The purpose of this study was to evaluate the contribution of working memory at the word and sentence levels of language to reading and writing outcomes. Measures of working memory at the word and sentence levels, reading and writing, were administered to 2nd (N = 122), 4th (N = 222), and 6th (N = 105) graders. Structural equation modeling was used to evaluate whether the 2 predictor working memory factors contributed unique variance beyond their shared covariance to each of 5 outcome factors: handwriting, spelling, composing, word reading, and reading comprehension. At each grade level, except for handwriting and composing in 6th grade, the word-level working memory factor contributed unique variance to each reading and writing outcome. The text-level working memory factor contributed unique variance to reading comprehension in 4th and 6th grade. The clinical significance of these findings for assessment and intervention is discussed.

Genetic and nonshared environmental factors affect the likelihood of being charged with driving under the influence (DUI) and driving while intoxicated (DWI).

PubMed

Beaver, Kevin M; Barnes, J C

2012-12-01

Driving under the influence (DUI) and driving while intoxicated (DWI) are related to a range of serious health, legal, and financial costs. Given the costs to society of DUIs and DWIs, there has been interest in identifying the causes of DUIs and DWIs. The current study added to this existing knowledge base by estimating genetic and environmental effects on DUIs and DWIs in a sample of twins drawn from the National Longitudinal Study of Adolescent Health (Add Health). The results of the analyses revealed that genetic factors explained 53% of the variance in DUIs/DWIs and the nonshared environment explained 47% of the variance. Shared environmental factors explained none of the variance in DUIs/DWIs. We conclude with a discussion of the results, the limitations of the study, and how the findings might be compatible with policies designed to reduce DUIs and DWIs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Strong Genetic Overlap Between Executive Functions and Intelligence

PubMed Central

Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.

2016-01-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7-15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically-mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. PMID:27359131

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.

Noise and drift analysis of non-equally spaced timing data

NASA Technical Reports Server (NTRS)

Vernotte, F.; Zalamansky, G.; Lantz, E.

1994-01-01

Generally, it is possible to obtain equally spaced timing data from oscillators. The measurement of the drifts and noises affecting oscillators is then performed by using a variance (Allan variance, modified Allan variance, or time variance) or a system of several variances (multivariance method). However, in some cases, several samples, or even several sets of samples, are missing. In the case of millisecond pulsar timing data, for instance, observations are quite irregularly spaced in time. Nevertheless, since some observations are very close together (one minute) and since the timing data sequence is very long (more than ten years), information on both short-term and long-term stability is available. Unfortunately, a direct variance analysis is not possible without interpolating missing data. Different interpolation algorithms (linear interpolation, cubic spline) are used to calculate variances in order to verify that they neither lose information nor add erroneous information. A comparison of the results of the different algorithms is given. Finally, the multivariance method was adapted to the measurement sequence of the millisecond pulsar timing data: the responses of each variance of the system are calculated for each type of noise and drift, with the same missing samples as in the pulsar timing sequence. An estimation of precision, dynamics, and separability of this method is given.

Anxiety as a context for understanding associations between hypochondriasis, obsessive-compulsive, and panic attack symptoms.

PubMed

Longley, Susan L; Calamari, John E; Wu, Kevin; Wade, Michael

2010-12-01

In the context of the integrative model of anxiety and depression, we examined whether the essential problem of hypochondriasis is one of anxiety. When analyzed, data from a large nonclinical sample corresponded to the integrative model's characterization of anxiety as composed of both broad, shared and specific, unique symptom factors. The unique hypochondriasis, obsessive-compulsive, and panic attack symptom factors all had correlational patterns expected of anxiety with the shared, broad factors of negative emotionality and positive emotionality. A confirmatory factor analysis showed a higher-order, bifactor model was the best fit to our data; the shared and the unique hypochondriasis and anxiety symptom factors both contributed substantial variance. This study provides refinements to an empirically based taxonomy and clarifies what hypochondriasis is and, importantly, what it is not. Copyright © 2010. Published by Elsevier Ltd.

Why do identical twins differ in personality: shared environment reconsidered.

PubMed

Torgersen, Anne Mari; Janson, Harald

2002-02-01

While heritability studies show that most of the variance in adult personality can be attributed to genetic or so-called nonshared environmental influence, this does not mean that shared events lack importance for the development of later personality differences. We studied the relationship between Big Five personality differences in monozygotic (MZ) twins at age 29, and life stressors at age 6 to 15, using prospective data from 26 MZ pairs studied from birth onwards. A positive significant correlation was found between stressors in childhood and early adolescence, and intrapair personality differences in Agreeableness, Openness, Conscientiousness, and five-factor profiles. We note that the effects of shared events are labeled "nonshared" environment when the effect is to make siblings more different. Case examples illustrate the relationship between stress and personality differences, and provide hypotheses for further studies in larger samples.

A mobile asset sharing policy for hospitals with real time locating systems.

PubMed

Demircan-Yıldız, Ece Arzu; Fescioglu-Unver, Nilgun

2016-01-01

Each year, hospitals lose a considerable amount of time and money due to misplaced mobile assets. In addition the assets which remain in departments that frequently use them depreciate early, while other assets of the same type in different departments are rarely used. A real time locating system can prevent these losses when used with appropriate asset sharing policies. This research quantifies the amount of time a medium size hospital saves by using real time locating system and proposes an asset selection rule to eliminate the asset usage imbalance problem. The asset selection rule proposed is based on multi objective optimization techniques. The effectiveness of this rule on asset to patient time and asset utilization rate variance performance measures were tested using discrete event simulation method. Results show that the proposed asset selection rule improved the usage balance significantly. Sensitivity analysis showed that the proposed rule is robust to changes in demand rates and user preferences. Real time locating systems enable saving considerable amount of time in hospitals, and they can still be improved by integrating decision support mechanisms. Combining tracking technology and asset selection rules helps improve healthcare services.

Validity Evidence and Scoring Guidelines for Standardized Patient Encounters and Patient Notes From a Multisite Study of Clinical Performance Examinations in Seven Medical Schools.

PubMed

Park, Yoon Soo; Hyderi, Abbas; Heine, Nancy; May, Win; Nevins, Andrew; Lee, Ming; Bordage, Georges; Yudkowsky, Rachel

2017-11-01

To examine validity evidence of local graduation competency examination scores from seven medical schools using shared cases and to provide rater training protocols and guidelines for scoring patient notes (PNs). Between May and August 2016, clinical cases were developed, shared, and administered across seven medical schools (990 students participated). Raters were calibrated using training protocols, and guidelines were developed collaboratively across sites to standardize scoring. Data included scores from standardized patient encounters for history taking, physical examination, and PNs. Descriptive statistics were used to examine scores from the different assessment components. Generalizability studies (G-studies) using variance components were conducted to estimate reliability for composite scores. Validity evidence was collected for response process (rater perception), internal structure (variance components, reliability), relations to other variables (interassessment correlations), and consequences (composite score). Student performance varied by case and task. In the PNs, justification of differential diagnosis was the most discriminating task. G-studies showed that schools accounted for less than 1% of total variance; however, for the PNs, there were differences in scores for varying cases and tasks across schools, indicating a school effect. Composite score reliability was maximized when the PN was weighted between 30% and 40%. Raters preferred using case-specific scoring guidelines with clear point-scoring systems. This multisite study presents validity evidence for PN scores based on scoring rubric and case-specific scoring guidelines that offer rigor and feedback for learners. Variability in PN scores across participating sites may signal different approaches to teaching clinical reasoning among medical schools.

Effects of social contact and zygosity on 21-y weight change in male twins.

PubMed

McCaffery, Jeanne M; Franz, Carol E; Jacobson, Kristen; Leahey, Tricia M; Xian, Hong; Wing, Rena R; Lyons, Michael J; Kremen, William S

2011-08-01

Recent evidence indicates that social contact is related to similarities in weight gain over time. However, no studies have examined this effect in a twin design, in which genetic and other environmental effects can also be estimated. We determined whether the frequency of social contact is associated with similarity in weight change from young adulthood (mean age: 20 y) to middle age (mean age: 41 y) in twins and quantified the percentage of variance in weight change attributable to social contact, genetic factors, and other environmental influences. Participants were 1966 monozygotic and 1529 dizygotic male twin pairs from the Vietnam-Era Twin Registry. Regression models tested whether frequency of social contact and zygosity predicted twin pair similarity in body mass index (BMI) change and weight change. Twin modeling was used to partition the percentage variance attributable to social contact, genetic, and other environmental effects. Twins gained an average of 3.99 BMI units, or 13.23 kg (29.11 lb), over 21 y. In regression models, both zygosity (P < 0.001) and degree of social contact (P < 0.02) significantly predicted twin pair similarity in BMI change. In twin modeling, social contact between twins contributed 16% of the variance in BMI change (P < 0.001), whereas genetic factors contributed 42%, with no effect of additional shared environmental factors (1%). Similar results were obtained for weight change. Frequency of social contact significantly predicted twin pair similarity in BMI and weight change over 21 y, independent of zygosity and other shared environmental influences.

Aesthetic judgement of orientation in modern art.

PubMed

Mather, George

2012-01-01

When creating an artwork, the artist makes a decision regarding the orientation at which the work is to be hung based on their aesthetic judgement and the message conveyed by the piece. Is the impact or aesthetic appeal of a work diminished when it is hung at an incorrect orientation? To investigate this question, Experiment 1 asked whether naïve observers can appreciate the correct orientation (as defined by the artist) of 40 modern artworks, some of which are entirely abstract. Eighteen participants were shown 40 paintings in a series of trials. Each trial presented all four cardinal orientations on a computer screen, and the participant was asked to select the orientation that was most attractive or meaningful. Results showed that the correct orientation was selected in 48% of trials on average, significantly above the 25% chance level, but well below perfect performance. A second experiment investigated the extent to which the 40 paintings contained recognisable content, which may have mediated orientation judgements. Recognition rates varied from 0% for seven of the paintings to 100% for five paintings. Orientation judgements in Experiment 1 correlated significantly with "meaningful" content judgements in Experiment 2: 42% of the variance in orientation judgements in Experiment 1 was shared with recognition of meaningful content in Experiment 2. For the seven paintings in which no meaningful content at all was detected, 41% of the variance in orientation judgements was shared with variance in a physical measure of image content, Fourier amplitude spectrum slope. For some paintings, orientation judgements were quite consistent, despite a lack of meaningful content. The origin of these orientation judgements remains to be identified.

Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.

PubMed

Austin, Peter C

2016-12-30

Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Comparative Studies on the Roles of Linguistic Knowledge and Sentence Processing Speed in L2 Listening and Reading Comprehension in an EFL Tertiary Setting

ERIC Educational Resources Information Center

Oh, Eunjou

2016-01-01

The present study investigated the relative contributions of vocabulary knowledge, grammar knowledge, and processing speed to second language listening and reading comprehension. Seventy-five Korean university students participated in the study. Results showed the three tested components had a significant portion of shared variance in explaining…

Decomposing the relationship between cognitive functioning and self-referent memory beliefs in older adulthood: What’s memory got to do with it?

PubMed Central

Payne, Brennan R.; Gross, Alden L.; Hill, Patrick L.; Parisi, Jeanine M.; Rebok, George W.; Stine-Morrow, Elizabeth A. L.

2018-01-01

With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2,802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability. PMID:27685541

Decomposing the relationship between cognitive functioning and self-referent memory beliefs in older adulthood: what's memory got to do with it?

PubMed

Payne, Brennan R; Gross, Alden L; Hill, Patrick L; Parisi, Jeanine M; Rebok, George W; Stine-Morrow, Elizabeth A L

2017-07-01

With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability.

Neutral Evolution of Multiple Quantitative Characters: A Genealogical Approach

PubMed Central

Griswold, Cortland K.; Logsdon, Benjamin; Gomulkiewicz, Richard

2007-01-01

The G matrix measures the components of phenotypic variation that are genetically heritable. The structure of G, that is, its principal components and their associated variances, determines, in part, the direction and speed of multivariate trait evolution. In this article we present a framework and results that give the structure of G under the assumption of neutrality. We suggest that a neutral expectation of the structure of G is important because it gives a null expectation for the structure of G from which the unique consequences of selection can be determined. We demonstrate how the processes of mutation, recombination, and drift shape the structure of G. Furthermore, we demonstrate how shared common ancestry between segregating alleles shapes the structure of G. Our results show that shared common ancestry, which manifests itself in the form of a gene genealogy, causes the structure of G to be nonuniform in that the variances associated with the principal components of G decline at an approximately exponential rate. Furthermore we show that the extent of the nonuniformity in the structure of G is enhanced with declines in mutation rates, recombination rates, and numbers of loci and is dependent on the pattern and modality of mutation. PMID:17339224

Genetic and environmental effects on same-sex sexual behavior: a population study of twins in Sweden.

PubMed

Långström, Niklas; Rahman, Qazi; Carlström, Eva; Lichtenstein, Paul

2010-02-01

There is still uncertainty about the relative importance of genes and environments on human sexual orientation. One reason is that previous studies employed self-selected, opportunistic, or small population-based samples. We used data from a truly population-based 2005-2006 survey of all adult twins (20-47 years) in Sweden to conduct the largest twin study of same-sex sexual behavior attempted so far. We performed biometric modeling with data on any and total number of lifetime same-sex sexual partners, respectively. The analyses were conducted separately by sex. Twin resemblance was moderate for the 3,826 studied monozygotic and dizygotic same-sex twin pairs. Biometric modeling revealed that, in men, genetic effects explained .34-.39 of the variance, the shared environment .00, and the individual-specific environment .61-.66 of the variance. Corresponding estimates among women were .18-.19 for genetic factors, .16-.17 for shared environmental, and 64-.66 for unique environmental factors. Although wide confidence intervals suggest cautious interpretation, the results are consistent with moderate, primarily genetic, familial effects, and moderate to large effects of the nonshared environment (social and biological) on same-sex sexual behavior.

Multivariate Cholesky models of human female fertility patterns in the NLSY.

PubMed

Rodgers, Joseph Lee; Bard, David E; Miller, Warren B

2007-03-01

Substantial evidence now exists that variables measuring or correlated with human fertility outcomes have a heritable component. In this study, we define a series of age-sequenced fertility variables, and fit multivariate models to account for underlying shared genetic and environmental sources of variance. We make predictions based on a theory developed by Udry [(1996) Biosocial models of low-fertility societies. In: Casterline, JB, Lee RD, Foote KA (eds) Fertility in the United States: new patterns, new theories. The Population Council, New York] suggesting that biological/genetic motivations can be more easily realized and measured in settings in which fertility choices are available. Udry's theory, along with principles from molecular genetics and certain tenets of life history theory, allow us to make specific predictions about biometrical patterns across age. Consistent with predictions, our results suggest that there are different sources of genetic influence on fertility variance at early compared to later ages, but that there is only one source of shared environmental influence that occurs at early ages. These patterns are suggestive of the types of gene-gene and gene-environment interactions for which we must account to better understand individual differences in fertility outcomes.

Hair Cortisol in Twins: Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes.

PubMed

Rietschel, Liz; Streit, Fabian; Zhu, Gu; McAloney, Kerrie; Frank, Josef; Couvy-Duchesne, Baptiste; Witt, Stephanie H; Binz, Tina M; McGrath, John; Hickie, Ian B; Hansell, Narelle K; Wright, Margaret J; Gillespie, Nathan A; Forstner, Andreas J; Schulze, Thomas G; Wüst, Stefan; Nöthen, Markus M; Baumgartner, Markus R; Walker, Brian R; Crawford, Andrew A; Colodro-Conde, Lucía; Medland, Sarah E; Martin, Nicholas G; Rietschel, Marcella

2017-11-10

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.

Basal salivary oxytocin level predicts extra- but not intra-personal dimensions of emotional intelligence.

PubMed

Koven, Nancy S; Max, Laura K

2014-06-01

A wealth of literature suggests that oxytocin is an important mediator of social cognition, but much of the research to date has relied on pharmaceutical administration methods that can raise oxytocin to artificially high levels. The present study builds upon previous work by examining whether basal oxytocin level predicts intra- and extra-personal (i.e., self- and other-focused) elements of emotional intelligence (EI), independent of shared variance with current mood. The sample included 71 healthy young adults (46 women). Assessment measures included the Mayer-Salovey-Caruso Emotional Intelligence Test Version 2.0 (MSCEIT), the Trait Meta-Mood Scale, and the Profile of Mood States. Peripheral oxytocin levels were examined with enzyme-linked immunosorbent assay from saliva after solid phase extraction. Oxytocin level was unrelated to TMMS scores but was positively associated with performance in the Experiential EI domain of the MSCEIT. However, total mood disturbance was positively related to MSCEIT scores. Hierarchical regression analysis indicated that oxytocin level added unique variance to the prediction of MSCEIT performance beyond that of current mood. These results confirm an association between endogenous levels of oxytocin in healthy adults and a subset of EI abilities, including extra-personal emotion recognition and the channeling of emotions to enhance social proficiency. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tinnitus and Hearing Survey: A Screening Tool to Differentiate Bothersome Tinnitus From Hearing Difficulties

PubMed Central

Griest, Susan; Zaugg, Tara L.; Thielman, Emily; Kaelin, Christine; Galvez, Gino; Carlson, Kathleen F.

2015-01-01

Purpose Individuals complaining of tinnitus often attribute hearing problems to the tinnitus. In such cases some (or all) of their reported “tinnitus distress” may in fact be caused by trouble communicating due to hearing problems. We developed the Tinnitus and Hearing Survey (THS) as a tool to rapidly differentiate hearing problems from tinnitus problems. Method For 2 of our research studies, we administered the THS twice (mean of 16.5 days between tests) to 67 participants who did not receive intervention. These data allow for measures of statistical validation of the THS. Results Reliability of the THS was good to excellent regarding internal consistency (α = .86–.94), test–retest reliability (r = .76–.83), and convergent validity between the Tinnitus Handicap Inventory (Newman, Jacobson, & Spitzer, 1996; Newman, Sandridge, & Jacobson, 1998) and the A (Tinnitus) subscale of the THS (r = .78). Factor analysis confirmed that the 2 subscales, A (Tinnitus) and B (Hearing), have strong internal structure, explaining 71.7% of the total variance, and low correlation with each other (r = .46), resulting in a small amount of shared variance (21%). Conclusion These results provide evidence that the THS is statistically validated and reliable for use in assisting patients and clinicians in quickly (and collaboratively) determining whether intervention for tinnitus is appropriate. PMID:25551458

Automatic variance reduction for Monte Carlo simulations via the local importance function transform

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

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditionalmore » Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.« less

The association between negative self-descriptions and depressive symptomology: does culture make a difference?

PubMed

Saint Arnault, Denise; Sakamoto, Shinji; Moriwaki, Aiko

2005-04-01

Research findings that depressed Americans endorse more negative self-related adjectives than controls may be related to a shared self-enhancement cultural frame. This study examines the relationship between negative core self-descriptors and depressive symptoms in 79 Japanese and 50 American women. Americans had more positive self-descriptions and core self-descriptors; however, there were no cultural group differences in number of negative self-descriptors or core self-descriptors. There was a significant correlation between negative core self-descriptor and Beck Depression Inventory (BDI) for Americans only, explaining 10.6% of the BDI variance. Analysis of variance revealed that there was significant BDI group differences for American negative core self-descriptor only. Theoretical possibilities are discussed.

The Association Between Negative Self-Descriptions and Depressive Symptomology: Does Culture Make a Difference?

PubMed Central

Sakamoto, Shinji; Moriwaki, Aiko

2007-01-01

Research findings that depressed Americans endorse more negative self-related adjectives than controls may be related to a shared self-enhancement cultural frame. This study examines the relationship between negative core self-descriptors and depressive symptoms in 79 Japanese and 50 American women. Americans had more positive self-descriptions and core self-descriptors; however, there were no cultural group differences in number of negative self-descriptors or core self-descriptors. There was a significant correlation between negative core self-descriptor and Beck Depression Inventory (BDI) for Americans only, explaining 10.6% of the BDI variance. Analysis of variance revealed that there was significant BDI group differences for American negative core self-descriptor only. Theoretical possibilities are discussed. PMID:15902678

Genetic and Environmental Influences on Global Family Conflict

PubMed Central

Horwitz, Briana N.; Neiderhiser, Jenae M.; Ganiban, Jody M.; Spotts, Erica L.; Lichtenstein, Paul; Reiss, David

2010-01-01

This study examined genetic and environmental influences on global family conflict. The sample comprised 872 same-sex pairs of twin parents, their spouses/partners and one adolescent child per twin from the Twin and Offspring Study in Sweden (TOSS). The twins, spouses and child each reported on the degree of family conflict, and there was significant agreement among the family members’ ratings. These shared perspectives were explained by one common factor, indexing global family conflict. Genetic influences explained 36% of the variance in this common factor, suggesting that twins’ heritable characteristics contribute to family conflict, via genotype-environment correlation. Nonshared environmental effects explained the remaining 64% of this variance, indicating that twins’ unique childhood and/or current family experiences also play an important role. PMID:20438198

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

PubMed Central

Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

2015-01-01

Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

A New Nonparametric Levene Test for Equal Variances

ERIC Educational Resources Information Center

Nordstokke, David W.; Zumbo, Bruno D.

2010-01-01

Tests of the equality of variances are sometimes used on their own to compare variability across groups of experimental or non-experimental conditions but they are most often used alongside other methods to support assumptions made about variances. A new nonparametric test of equality of variances is described and compared to current "gold…

Dichotic Listening and Otoacoustic Emissions: Shared Variance between Cochlear Function and Dichotic Listening Performance in Adults with Normal Hearing

ERIC Educational Resources Information Center

Markevych, Vladlena; Asbjornsen, Arve E.; Lind, Ola; Plante, Elena; Cone, Barbara

2011-01-01

The present study investigated a possible connection between speech processing and cochlear function. Twenty-two subjects with age range from 18 to 39, balanced for gender with normal hearing and without any known neurological condition, were tested with the dichotic listening (DL) test, in which listeners were asked to identify CV-syllables in a…

Individual Differences in Exercise Behavior: Stability and Change in Genetic and Environmental Determinants From Age 7 to 18.

PubMed

Huppertz, Charlotte; Bartels, Meike; de Zeeuw, Eveline L; van Beijsterveldt, Catharina E M; Hudziak, James J; Willemsen, Gonneke; Boomsma, Dorret I; de Geus, Eco J C

2016-09-01

Exercise behavior during leisure time is a major source of health-promoting physical activity and moderately tracks across childhood and adolescence. This study aims to investigate the absolute and relative contribution of genes and the environment to variance in exercise behavior from age 7 to 18, and to elucidate the stability and change of genetic and shared environmental factors that underlie this behavior. The Netherlands Twin Register collected data on exercise behavior in twins aged approximately 7, 10, 12, 14, 16 and 18 years (N = 27,332 twins; 48 % males; 47 % with longitudinal assessments). Three exercise categories (low, middle, high) were analyzed by means of liability threshold models. First, a univariate model was fitted using the largest available cross-sectional dataset with linear and quadratic effects of age as modifiers on the means and variance components. Second, a simplex model was fitted on the longitudinal dataset. Heritability was low in 7-year-olds (14 % in males and 12 % in females), but gradually increased up to age 18 (79 % in males and 49 % in females), whereas the initially substantial relative influence of the shared environment decreased with age (from 80 to 4 % in males and from 80 to 19 % in females). This decrease was due to a large increase in the genetic variance. The longitudinal model showed the genetic effects in males to be largely stable and to accumulate from childhood to late adolescence, whereas in females, they were marked by both transmission and innovation at all ages. The shared environmental effects tended to be less stable in both males and females. In sum, the clear age-moderation of exercise behavior implies that family-based interventions might be useful to increase this behavior in children, whereas individual-based interventions might be better suited for adolescents. We showed that some determinants of individual differences in exercise behavior are stable across childhood and youth, whereas others come into play at specific ages. In view of the many benefits of regular exercise, identifying these determinants at specific ages should be a public health priority.

How do we use language? Shared patterns in the frequency of word use across 17 world languages

PubMed Central

Calude, Andreea S.; Pagel, Mark

2011-01-01

We present data from 17 languages on the frequency with which a common set of words is used in everyday language. The languages are drawn from six language families representing 65 per cent of the world's 7000 languages. Our data were collected from linguistic corpora that record frequencies of use for the 200 meanings in the widely used Swadesh fundamental vocabulary. Our interest is to assess evidence for shared patterns of language use around the world, and for the relationship of language use to rates of lexical replacement, defined as the replacement of a word by a new unrelated or non-cognate word. Frequencies of use for words in the Swadesh list range from just a few per million words of speech to 191 000 or more. The average inter-correlation among languages in the frequency of use across the 200 words is 0.73 (p < 0.0001). The first principal component of these data accounts for 70 per cent of the variance in frequency of use. Elsewhere, we have shown that frequently used words in the Indo-European languages tend to be more conserved, and that this relationship holds separately for different parts of speech. A regression model combining the principal factor loadings derived from the worldwide sample along with their part of speech predicts 46 per cent of the variance in the rates of lexical replacement in the Indo-European languages. This suggests that Indo-European lexical replacement rates might be broadly representative of worldwide rates of change. Evidence for this speculation comes from using the same factor loadings and part-of-speech categories to predict a word's position in a list of 110 words ranked from slowest to most rapidly evolving among 14 of the world's language families. This regression model accounts for 30 per cent of the variance. Our results point to a remarkable regularity in the way that human speakers use language, and hint that the words for a shared set of meanings have been slowly evolving and others more rapidly evolving throughout human history. PMID:21357232

Moderation of genetic and environmental influences on diurnal preference by age in adult twins.

PubMed

Barclay, Nicola L; Watson, Nathaniel F; Buchwald, Dedra; Goldberg, Jack

2014-03-01

Diurnal preference changes across the lifespan. However, the mechanisms underlying this age-related shift are poorly understood. The aim of this twin study was to determine the extent to which genetic and environmental influences on diurnal preference are moderated by age. Seven hundred and sixty-eight monozygotic and 674 dizygotic adult twin pairs participating in the University of Washington Twin Registry completed the reduced Morningness-Eveningness Questionnaire as a measure of diurnal preference. Participants ranged in age from 19 to 93 years (mean = 36.23, SD = 15.54) and were categorized on the basis of age into three groups: younger adulthood (19-35 years, n = 1715 individuals), middle adulthood (36-64 years, n = 1003 individuals) and older adulthood (65+ years, n = 168 individuals). Increasing age was associated with an increasing tendency towards morningness (r = 0.42, p < 0.001). Structural equation modeling techniques parsed the variance in diurnal preference into genetic and environmental influences for the total sample as well as for each age group separately. Additive genetic influences accounted for 52%[46-57%], and non-shared environmental influences 48%[43-54%], of the total variance in diurnal preference. In comparing univariate genetic models between age groups, the best-fitting model was one in which the parameter estimates for younger adults and older adults were equated, in comparison with middle adulthood. For younger and older adulthood, additive genetic influences accounted for 44%[31-49%] and non-shared environmental influences 56%[49-64%] of variance in diurnal preference, whereas for middle adulthood these estimates were 34%[21-45%] and 66%[55-79%], respectively. Therefore, genetic influences on diurnal preference are attenuated in middle adulthood. Attenuation is likely driven by the increased importance of work and family responsibilities during this life stage, in comparison with younger and older adulthood when these factors may be less influential in determining sleep-wake timing. These findings have implications for studies aimed at identifying specific non-shared environmental influences, as well as molecular genetic studies aimed at identifying specific polymorphisms associated with diurnal preference.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

Genetic and environmental influences on the comorbidity between depression, panic disorder, agoraphobia and social phobia: A twin study

PubMed Central

Mosing, Miriam A.; Gordon, Scott D.; Medland, Sarah E.; Statham, Dixie J.; Nelson, Elliot C.; Heath, Andrew C.; Martin, Nicholas G.; Wray, Naomi R.

2011-01-01

Background Major depression (MD) and anxiety disorders such as panic disorder (PD), agoraphobia (AG) and social phobia (SP) are heritable and highly comorbid. However, the relative importance of genetic and environmental aetiology of the covariation between these disorders, particularly the relationship between PD and AG is less clear. Methods The present study measured MD, PD and AG in a population sample of 5440 twin pairs and 1245 single twins, about 45% of whom were also scored for SP. Prevalences, within individual comorbidity and twin odds ratios for comorbidity are reported. A behavioural genetic analysis of the four disorders using the classical twin design was conducted. Results Odds ratios for MD, PD, AG, and SP in twins of individuals diagnosed with one of the four disorders were increased. Heritability estimates under a threshold-liability model for MD, PD, AG, and SP respectively were 0.33 (CI:0.30–0.42), 0.38 (CI:0.24–0.55), 0.48 (CI:0.37–0.65) of, and 0.39 (CI:0.16–0.65), with no evidence for any variance explained by the common environment shared by twins. We find that a common genetic factor explains a moderate proportion of variance in these four disorders. The genetic correlation between PD and AG was 0.83. Conclusion MD, PD, AG, and SP strongly co-aggregate within families and common genetic factors explain a moderate proportion of variance in these four disorders. The high genetic correlation between PD and AG and the increased odds ratio for PD and AG in siblings of those with AG without PD suggests a common genetic aetiology for PD and AG. PMID:19750555

Genetic Architecture of the Delis-Kaplan Executive Function System Trail Making Test: Evidence for Distinct Genetic Influences on Executive Function

PubMed Central

Vasilopoulos, Terrie; Franz, Carol E.; Panizzon, Matthew S.; Xian, Hong; Grant, Michael D.; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C.; Kremen, William S.

2012-01-01

Objective To examine how genes and environments contribute to relationships among Trail Making test conditions and the extent to which these conditions have unique genetic and environmental influences. Method Participants included 1237 middle-aged male twins from the Vietnam-Era Twin Study of Aging (VESTA). The Delis-Kaplan Executive Function System Trail Making test included visual searching, number and letter sequencing, and set-shifting components. Results Phenotypic correlations among Trails conditions ranged from 0.29 – 0.60, and genes accounted for the majority (58–84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set-shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. Conclusions A common genetic factor, most likely representing a combination of speed and sequencing accounted for most of the correlation among Trails 1–4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set-shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in non-patient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes. PMID:22201299

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed Central

Haanstra, Tsjitske M.; Tilbury, Claire; Kamper, Steven J.; Tordoir, Rutger L.; Vliet Vlieland, Thea P. M.; Nelissen, Rob G. H. H.; Cuijpers, Pim; de Vet, Henrica C. W.; Dekker, Joost; Knol, Dirk L.; Ostelo, Raymond W.

2015-01-01

Objectives The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Methods Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. Results The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Conclusion Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance. PMID:26214176

Dynamical Resilience Indicators in Time Series of Self-Rated Health Correspond to Frailty Levels in Older Adults.

PubMed

Gijzel, Sanne M W; van de Leemput, Ingrid A; Scheffer, Marten; Roppolo, Mattia; Olde Rikkert, Marcel G M; Melis, René J F

2017-07-01

We currently still lack valid methods to dynamically measure resilience for stressors before the appearance of adverse health outcomes that hamper well-being. Quantifying an older adult's resilience in an early stage would aid complex decision-making in health care. Translating complex dynamical systems theory to humans, we hypothesized that three dynamical indicators of resilience (variance, temporal autocorrelation, and cross-correlation) in time series of self-rated physical, mental, and social health were associated with frailty levels in older adults. We monitored self-rated physical, mental, and social health during 100 days using daily visual analogue scale questions in 22 institutionalized older adults (mean age 84.0, SD: 5.9 years). Frailty was determined by the Survey of Health, Ageing and Retirement in Europe (SHARE) frailty index. The resilience indicators (variance, temporal autocorrelation, and cross-correlation) were calculated using multilevel models. The self-rated health time series of frail elderly exhibited significantly elevated variance in the physical, mental, and social domain, as well as significantly stronger cross-correlations between all three domains, as compared to the nonfrail group (all P < 0.001). Temporal autocorrelation was not significantly associated with frailty. We found supporting evidence for two out of three hypothesized resilience indicators to be related to frailty levels in older adults. By mirroring the dynamical resilience indicators to a frailty index, we delivered a first empirical base to validate and quantify the construct of systemic resilience in older adults in a dynamic way. © 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.

Exploring Predictors of Information Use to Self-Manage Blood Pressure in Midwestern African American Women with Hypertension.

PubMed

Jones, Lenette M; Veinot, Tiffany; Pressler, Susan J; Coleman-Burns, Patricia; McCall, Alecia

2018-06-01

Self-management of hypertension requires patients to find, understand, and use information to lower their blood pressure. Little is known about information use among African American women with hypertension, therefore the purpose of this study was to examine predictors of self-reported information use to self-manage blood pressure. Ninety-four Midwestern African American women (mean age = 59) completed questionnaires about information behaviors (seeking, sharing, use) and personal beliefs (attitude, social norms) related to self-management of blood pressure. Linear regression was used to identify significant predictors of information use. The total variance explained by the model was 36%, F(7, 79) = 6.29, p < .001. Information sharing was the only significant predictor (beta = .46, p < .001). These results provide evidence that information sharing is a potential health behavior to support intervention strategies for African American women with hypertension.

Characterizing output bottlenecks in a supercomputer

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

Xie, Bing; Chase, Jeffrey; Dillow, David A

2012-01-01

Supercomputer I/O loads are often dominated by writes. HPC (High Performance Computing) file systems are designed to absorb these bursty outputs at high bandwidth through massive parallelism. However, the delivered write bandwidth often falls well below the peak. This paper characterizes the data absorption behavior of a center-wide shared Lustre parallel file system on the Jaguar supercomputer. We use a statistical methodology to address the challenges of accurately measuring a shared machine under production load and to obtain the distribution of bandwidth across samples of compute nodes, storage targets, and time intervals. We observe and quantify limitations from competing traffic,more » contention on storage servers and I/O routers, concurrency limitations in the client compute node operating systems, and the impact of variance (stragglers) on coupled output such as striping. We then examine the implications of our results for application performance and the design of I/O middleware systems on shared supercomputers.« less

Choice of Reading Comprehension Test Influences the Outcomes of Genetic Analyses

PubMed Central

Betjemann, Rebecca S.; Keenan, Janice M.; Olson, Richard K.; DeFries, John C.

2010-01-01

Does the choice of test for assessing reading comprehension influence the outcome of genetic analyses? A twin design compared two types of reading comprehension tests classified as primarily associated with word decoding (RC-D) or listening comprehension (RC-LC). For both types of tests, the overall genetic influence is high and nearly identical. However, the tests differed significantly in how they covary with the genes associated with decoding and listening comprehension. Although Cholesky decomposition showed that both types of comprehension tests shared significant genetic influence with both decoding and listening comprehension, RC-D tests shared most genetic variance with decoding, and RC-LC tests shared most with listening comprehension. Thus, different tests used to measure the same construct may manifest very different patterns of genetic covariation. These results suggest that the apparent discrepancies among the findings of previous twin studies of reading comprehension could be due at least in part to test differences. PMID:21804757

A de-noising method using the improved wavelet threshold function based on noise variance estimation

NASA Astrophysics Data System (ADS)

Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

2018-01-01

The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda, L.; Pilewskie, P.; Kindel, B. C.; Feldman, D. R.; Collins, W. D.

2013-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

Genetic and environmental influences on conduct and antisocial personality problems in childhood, adolescence, and adulthood.

PubMed

Wesseldijk, Laura W; Bartels, Meike; Vink, Jacqueline M; van Beijsterveldt, Catharina E M; Ligthart, Lannie; Boomsma, Dorret I; Middeldorp, Christel M

2017-06-21

Conduct problems in children and adolescents can predict antisocial personality disorder and related problems, such as crime and conviction. We sought an explanation for such predictions by performing a genetic longitudinal analysis. We estimated the effects of genetic, shared environmental, and unique environmental factors on variation in conduct problems measured at childhood and adolescence and antisocial personality problems measured at adulthood and on the covariation across ages. We also tested whether these estimates differed by sex. Longitudinal data were collected in the Netherlands Twin Register over a period of 27 years. Age appropriate and comparable measures of conduct and antisocial personality problems, assessed with the Achenbach System of Empirically Based Assessment, were available for 9783 9-10-year-old, 6839 13-18-year-old, and 7909 19-65-year-old twin pairs, respectively; 5114 twins have two or more assessments. At all ages, men scored higher than women. There were no sex differences in the estimates of the genetic and environmental influences. During childhood, genetic and environmental factors shared by children in families explained 43 and 44% of the variance of conduct problems, with the remaining variance due to unique environment. During adolescence and adulthood, genetic and unique environmental factors equally explained the variation. Longitudinal correlations across age varied between 0.20 and 0.38 and were mainly due to stable genetic factors. We conclude that shared environment is mainly of importance during childhood, while genetic factors contribute to variation in conduct and antisocial personality problems at all ages, and also underlie its stability over age.

Undue influence of weight and shape: is it distinct from body dissatisfaction and concern about weight and shape?

PubMed

Wade, T D; Zhu, G; Martin, N G

2011-04-01

Three cognitive constructs are risk factors for eating disorders: undue influence of weight and shape, concern about weight and shape, and body dissatisfaction (BD). Undue influence, a diagnostic criterion for eating disorders, is postulated to be closely associated with self-esteem whereas BD is postulated to be closely associated with body mass index (BMI). We understand less about the relationships with concern about weight and shape. The aim of the current investigation was examine the degree of overlap across these five phenotypes in terms of latent genetic and environmental risk factors in order to draw some conclusions about the similarities and differences across the three cognitive variables. A sample of female Australian twins (n=1056, including 348 complete pairs), mean age 35 years (S.D.=2.11, range 28-40), completed a semi-structured interview about eating pathology and self-report questionnaires. An independent pathways model was used to investigate the overlap of genetic and environmental risk factors for the five phenotypes. In terms of variance that was not shared with other phenotypes, self-esteem emerged as being separate, with 100% of its variance unshared with the other phenotypes, followed by undue influence (51%) and then concern (34%), BD (28%) and BMI (32%). In terms of shared genetic risk, undue influence and concern were more closely related than BD, whereas BMI and BD were found to share common sources of risk. With respect to environmental risk factors, concern, BMI and BD were more closely related to each other than to undue influence.

Rasch Analysis of the 9-Item Shared Decision Making Questionnaire in Women With Breast Cancer.

PubMed

Wu, Tzu-Yi; Chen, Cheng-Te; Huang, Yi-Jing; Hou, Wen-Hsuan; Wang, Jung-Der; Hsieh, Ching-Lin

2018-04-19

Shared decision making (SDM) is a best practice to help patients make optimal decisions by a process of healthcare, especially for women diagnosed with breast cancer and having heavy burden in long-term treatments. To promote successful SDM, it is crucial to assess the level of perceived involvement in SDM in women with breast cancer. The aims of this study were to apply Rasch analysis to examine the construct validity and person reliability of the 9-item Shared Decision Making Questionnaire (SDM-Q-9) in women with breast cancer. The construct validity of SDM-Q-9 was confirmed when the items fit the Rasch model's assumptions of unidimensionality: (1) infit and outfit mean square ranged from 0.6 to 1.4; (2) the unexplained variance of the first dimension of the principal component analysis was less than 20%. Person reliability was calculated. A total of 212 participants were recruited in this study. Item 1 did not fit the model's assumptions and was deleted. The unidimensionality of the remaining 8 items (SDM-Q-8) was supported with good item fit (infit and outfit mean square ranging from 0.6 to 1.3) and very low unexplained variance of the first dimension (5.3%) of the principal component analysis. The person reliability of the SDM-Q-8 was 0.90. The SDM-Q-8 was unidimensional and had good person reliability in women with breast cancer. The SDM-Q-8 has shown its potential for assessing the level of perceived involvement in SDM in women with breast cancer for both research and clinical purposes.

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.

Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

PubMed

Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

2012-02-01

An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p < .05 for both), and when regression was used to partial out shared variance between the two tests, the remaining variance predicted by the OSPAN was minimal (sr ( 2 ) = .029). When measures of spatial memory were included in the regression, the unique variance predicted by the OSPAN became negligible (sr ( 2 ) = .000004). This suggests that the executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

Strong genetic overlap between executive functions and intelligence.

PubMed

Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M

2016-09-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Genetic pleiotropy explains associations between musical auditory discrimination and intelligence.

PubMed

Mosing, Miriam A; Pedersen, Nancy L; Madison, Guy; Ullén, Fredrik

2014-01-01

Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions.

Genetic Pleiotropy Explains Associations between Musical Auditory Discrimination and Intelligence

PubMed Central

Mosing, Miriam A.; Pedersen, Nancy L.; Madison, Guy; Ullén, Fredrik

2014-01-01

Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions. PMID:25419664

A twin study of early-childhood asthma in Puerto Ricans.

PubMed

Bunyavanich, Supinda; Silberg, Judy L; Lasky-Su, Jessica; Gillespie, Nathan A; Lange, Nancy E; Canino, Glorisa; Celedón, Juan C

2013-01-01

The relative contributions of genetics and environment to asthma in Hispanics or to asthma in children younger than 3 years are not well understood. To examine the relative contributions of genetics and environment to early-childhood asthma by performing a longitudinal twin study of asthma in Puerto Rican children ≤ 3 years old. 678 twin infants from the Puerto Rico Neo-Natal Twin Registry were assessed for asthma at age 1 year, with follow-up data obtained for 624 twins at age 3 years. Zygosity was determined by DNA microsatellite profiling. Structural equation modeling was performed for three phenotypes at ages 1 and 3 years: physician-diagnosed asthma, asthma medication use in the past year, and ≥ 1 hospitalization for asthma in the past year. Models were additionally adjusted for early-life environmental tobacco smoke exposure, sex, and age. The prevalences of physician-diagnosed asthma, asthma medication use, and hospitalization for asthma were 11.6%, 10.8%, 4.9% at age 1 year, and 34.1%, 40.1%, and 8.5% at 3 years, respectively. Shared environmental effects contributed to the majority of variance in susceptibility to physician-diagnosed asthma and asthma medication use in the first year of life (84%-86%), while genetic effects drove variance in all phenotypes (45%-65%) at age 3 years. Early-life environmental tobacco smoke, sex, and age contributed to variance in susceptibility. Our longitudinal study in Puerto Rican twins demonstrates a changing contribution of shared environmental effects to liability for physician-diagnosed asthma and asthma medication use between ages 1 and 3 years. Early-life environmental tobacco smoke reduction could markedly reduce asthma morbidity in young Puerto Rican children.

Sexually antagonistic selection on genetic variation underlying both male and female same-sex sexual behavior.

PubMed

Berger, David; You, Tao; Minano, Maravillas R; Grieshop, Karl; Lind, Martin I; Arnqvist, Göran; Maklakov, Alexei A

2016-05-13

Intralocus sexual conflict, arising from selection for different alleles at the same locus in males and females, imposes a constraint on sex-specific adaptation. Intralocus sexual conflict can be alleviated by the evolution of sex-limited genetic architectures and phenotypic expression, but pleiotropic constraints may hinder this process. Here, we explored putative intralocus sexual conflict and genetic (co)variance in a poorly understood behavior with near male-limited expression. Same-sex sexual behaviors (SSBs) generally do not conform to classic evolutionary models of adaptation but are common in male animals and have been hypothesized to result from perception errors and selection for high male mating rates. However, perspectives incorporating sex-specific selection on genes shared by males and females to explain the expression and evolution of SSBs have largely been neglected. We performed two parallel sex-limited artificial selection experiments on SSB in male and female seed beetles, followed by sex-specific assays of locomotor activity and male sex recognition (two traits hypothesized to be functionally related to SSB) and adult reproductive success (allowing us to assess fitness consequences of genetic variance in SSB and its correlated components). Our experiments reveal both shared and sex-limited genetic variance for SSB. Strikingly, genetically correlated responses in locomotor activity and male sex-recognition were associated with sexually antagonistic fitness effects, but these effects differed qualitatively between male and female selection lines, implicating intralocus sexual conflict at both male- and female-specific genetic components underlying SSB. Our study provides experimental support for the hypothesis that widespread pleiotropy generates pervasive intralocus sexual conflict governing the expression of SSBs, suggesting that SSB in one sex can occur due to the expression of genes that carry benefits in the other sex.

Positive and Negative Affect as Links Between Social Anxiety and Depression: Predicting Concurrent and Prospective Mood Symptoms in Unipolar and Bipolar Mood Disorders.

PubMed

Cohen, Jonah N; Taylor Dryman, M; Morrison, Amanda S; Gilbert, Kirsten E; Heimberg, Richard G; Gruber, June

2017-11-01

The co-occurrence of social anxiety and depression is associated with increased functional impairment and a more severe course of illness. Social anxiety disorder is unique among the anxiety disorders in sharing an affective profile with depression, characterized by low levels of positive affect (PA) and high levels of negative affect (NA). Yet it remains unclear how this shared affective profile contributes to the covariation of social anxiety and depressive symptoms. We examined whether self-reported PA and NA accounted for unique variance in the association between social anxiety and depressive symptoms across three groups (individuals with remitted bipolar disorder, type I [BD; n = 32], individuals with remitted major depressive disorder [MDD; n = 31], and nonpsychiatric controls [n = 30]) at baseline and follow-ups of 6 and 12 months. Low levels of PA, but not NA, accounted for unique variance in both concurrent and prospective associations between social anxiety and depression in the BD group; in contrast, high levels of NA, but not PA, accounted for unique variance in concurrent and prospective associations between social anxiety and depression in the MDD group. Limitations include that social anxiety and PA/NA were assessed concurrently and all measurement was self-report. Few individuals with MDD/BD met current diagnostic criteria for social anxiety disorder. There was some attrition at follow-up assessments. Results suggest that affective mechanisms may contribute to the high rates of co-occurrence of social anxiety and depression in both MDD and BD. Implications of the differential role of PA and NA in the relationship between social anxiety and depression in MDD and BD and considerations for treatment are discussed. Copyright © 2017. Published by Elsevier Ltd.

A study of changes in genetic and environmental influences on weight and shape concern across adolescence.

PubMed

Wade, Tracey D; Hansell, Narelle K; Crosby, Ross D; Bryant-Waugh, Rachel; Treasure, Janet; Nixon, Reginald; Byrne, Susan; Martin, Nicholas G

2013-02-01

The goal of the current study was to examine whether genetic and environmental influences on an important risk factor for disordered eating, weight and shape concern, remained stable over adolescence. This stability was assessed in 2 ways: whether new sources of latent variance were introduced over development and whether the magnitude of variance contributing to the risk factor changed. We examined an 8-item WSC subscale derived from the Eating Disorder Examination (EDE) using telephone interviews with female adolescents. From 3 waves of data collected from female-female same-sex twin pairs from the Australian Twin Registry, a subset of the data (which included 351 pairs at Wave 1) was used to examine 3 age cohorts: 12 to 13, 13 to 15, and 14 to 16 years. The best-fitting model contained genetic and environmental influences, both shared and nonshared. Biometric model fitting indicated that nonshared environmental influences were largely specific to each age cohort, and results suggested that latent shared environmental and genetic influences that were influential at 12 to 13 years continued to contribute to subsequent age cohorts, with independent sources of both emerging at ages 13 to 15. The magnitude of all 3 latent influences could be constrained to be the same across adolescence. Ages 13 to 15 were indicated as a time of risk for the development of high levels of WSC, given that most specific environmental risk factors were significant at this time (e.g., peer teasing about weight, adverse life events), and indications of the emergence of new sources of latent genetic and environmental variance over this period. 2013 APA, all rights reserved

A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

2016-10-01

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

Genetic and environmental contributions to pro-social attitudes: a twin study of social responsibility.

PubMed

Rushton, J Philippe

2004-12-22

Although 51 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, only four previous studies have examined a genetic contribution to pro-social behaviour. Earlier work by the author with the University of London Institute of Psychiatry Adult Twin Register found that genes contributed approximately half of the variance to measures of self-report altruism, empathy, nurturance and aggression, including acts of violence. The present study extends those results by using a 22-item Social Responsibility Questionnaire with 174 pairs of monozygotic twins and 148 pairs of dizygotic twins. Forty-two per cent of the reliable variance was due to the twins' genes, 23% to the twins' common environment and the remainder to the twins' non-shared environment.

Only complementary voices tell the truth: a reevaluation of validity in multi-informant approaches of child and adolescent clinical assessments.

PubMed

Kaurin, Aleksandra; Egloff, Boris; Stringaris, Argyris; Wessa, Michèle

2016-08-01

Multi-informant approaches are thought to be key to clinical assessment. Classical theories of psychological measurements assume that only convergence among different informants' reports allows for an estimate of the true nature and causes of clinical presentations. However, the integration of multiple accounts is fraught with problems because findings in child and adolescent psychiatry do not conform to the fundamental expectation of convergence. Indeed, reports provided by different sources (self, parents, teachers, peers) share little variance. Moreover, in some cases informant divergence may be meaningful and not error variance. In this review, we give an overview of conceptual and theoretical foundations of valid multi-informant assessment and discuss why our common concepts of validity need revaluation.

Genetic and environmental contributions to pro-social attitudes: a twin study of social responsibility.

PubMed Central

Rushton, J. Philippe

2004-01-01

Although 51 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, only four previous studies have examined a genetic contribution to pro-social behaviour. Earlier work by the author with the University of London Institute of Psychiatry Adult Twin Register found that genes contributed approximately half of the variance to measures of self-report altruism, empathy, nurturance and aggression, including acts of violence. The present study extends those results by using a 22-item Social Responsibility Questionnaire with 174 pairs of monozygotic twins and 148 pairs of dizygotic twins. Forty-two per cent of the reliable variance was due to the twins' genes, 23% to the twins' common environment and the remainder to the twins' non-shared environment. PMID:15615684

Genetic and environmental influences on global family conflict.

PubMed

Horwitz, Briana N; Neiderhiser, Jenae M; Ganiban, Jody M; Spotts, Erica L; Lichtenstein, Paul; Reiss, David

2010-04-01

This study examined genetic and environmental influences on global family conflict. The sample comprised 872 same-sex pairs of twin parents, their spouses/partners, and one adolescent child per twin from the Twin and Offspring Study in Sweden. The twins, spouses, and child each reported on the degree of family conflict, and there was significant agreement among the family members' ratings. These shared perspectives were explained by one common factor, indexing global family conflict. Genetic influences explained 36% of the variance in this common factor, suggesting that twins' heritable characteristics contribute to family conflict, via genotype-environment correlation. Nonshared environmental effects explained the remaining 64% of this variance, indicating that twins' unique childhood and/or current family experiences also play an important role. 2010 APA, all rights reserved

Genetic and environmental transmission of body mass index fluctuation.

PubMed

Bergin, Jocilyn E; Neale, Michael C; Eaves, Lindon J; Martin, Nicholas G; Heath, Andrew C; Maes, Hermine H

2012-11-01

This study sought to determine the relationship between body mass index (BMI) fluctuation and cardiovascular disease phenotypes, diabetes, and depression and the role of genetic and environmental factors in individual differences in BMI fluctuation using the extended twin-family model (ETFM). This study included 14,763 twins and their relatives. Health and Lifestyle Questionnaires were obtained from 28,492 individuals from the Virginia 30,000 dataset including twins, parents, siblings, spouses, and children of twins. Self-report cardiovascular disease, diabetes, and depression data were available. From self-reported height and weight, BMI fluctuation was calculated as the difference between highest and lowest BMI after age 18, for individuals 18-80 years. Logistic regression analyses were used to determine the relationship between BMI fluctuation and disease status. The ETFM was used to estimate the significance and contribution of genetic and environmental factors, cultural transmission, and assortative mating components to BMI fluctuation, while controlling for age. We tested sex differences in additive and dominant genetic effects, parental, non-parental, twin, and unique environmental effects. BMI fluctuation was highly associated with disease status, independent of BMI. Genetic effects accounted for ~34 % of variance in BMI fluctuation in males and ~43 % of variance in females. The majority of the variance was accounted for by environmental factors, about a third of which were shared among twins. Assortative mating, and cultural transmission accounted for only a small proportion of variance in this phenotype. Since there are substantial health risks associated with BMI fluctuation and environmental components of BMI fluctuation account for over 60 % of variance in males and over 50 % of variance in females, environmental risk factors may be appropriate targets to reduce BMI fluctuation.

Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

NASA Astrophysics Data System (ADS)

Indarsih, Indrati, Ch. Rini

2016-02-01

In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

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

An application of the LC-LSTM framework to the self-esteem instability case.

PubMed

Alessandri, Guido; Vecchione, Michele; Donnellan, Brent M; Tisak, John

2013-10-01

The present research evaluates the stability of self-esteem as assessed by a daily version of the Rosenberg (Society and the adolescent self-image, Princeton University Press, Princeton, 1965) general self-esteem scale (RGSE). The scale was administered to 391 undergraduates for five consecutive days. The longitudinal data were analyzed using the integrated LC-LSTM framework that allowed us to evaluate: (1) the measurement invariance of the RGSE, (2) its stability and change across the 5-day assessment period, (3) the amount of variance attributable to stable and transitory latent factors, and (4) the criterion-related validity of these factors. Results provided evidence for measurement invariance, mean-level stability, and rank-order stability of daily self-esteem. Latent state-trait analyses revealed that variances in scores of the RGSE can be decomposed into six components: stable self-esteem (40 %), ephemeral (or temporal-state) variance (36 %), stable negative method variance (9 %), stable positive method variance (4 %), specific variance (1 %) and random error variance (10 %). Moreover, latent factors associated with daily self-esteem were associated with measures of depression, implicit self-esteem, and grade point average.

Recovering Wood and McCarthy's ERP-prototypes by means of ERP-specific procrustes-rotation.

PubMed

Beauducel, André

2018-02-01

The misallocation of treatment-variance on the wrong component has been discussed in the context of temporal principal component analysis of event-related potentials. There is, until now, no rotation-method that can perfectly recover Wood and McCarthy's prototypes without making use of additional information on treatment-effects. In order to close this gap, two new methods: for component rotation were proposed. After Varimax-prerotation, the first method identifies very small slopes of successive loadings. The corresponding loadings are set to zero in a target-matrix for event-related orthogonal partial Procrustes- (EPP-) rotation. The second method generates Gaussian normal distributions around the peaks of the Varimax-loadings and performs orthogonal Procrustes-rotation towards these Gaussian distributions. Oblique versions of this Gaussian event-related Procrustes- (GEP) rotation and of EPP-rotation are based on Promax-rotation. A simulation study revealed that the new orthogonal rotations recover Wood and McCarthy's prototypes and eliminate misallocation of treatment-variance. In an additional simulation study with a more pronounced overlap of the prototypes GEP Promax-rotation reduced the variance misallocation slightly more than EPP Promax-rotation. Comparison with Existing Method(s): Varimax- and conventional Promax-rotations resulted in substantial misallocations of variance in simulation studies when components had temporal overlap. A substantially reduced misallocation of variance occurred with the EPP-, EPP Promax-, GEP-, and GEP Promax-rotations. Misallocation of variance can be minimized by means of the new rotation methods: Making use of information on the temporal order of the loadings may allow for improvements of the rotation of temporal PCA components. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

PubMed

Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

2018-07-01

Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

Achievement Goals, Reasons for Goal Pursuit, and Achievement Goal Complexes as Predictors of Beneficial Outcomes: Is the Influence of Goals Reducible to Reasons?

ERIC Educational Resources Information Center

Sommet, Nicolas; Elliot, Andrew J.

2017-01-01

In the present research, we proposed a systematic approach to disentangling the shared and unique variance explained by achievement goals, reasons for goal pursuit, and specific goal-reason combinations (i.e., achievement goal complexes). Four studies using this approach (involving nearly 1,800 participants) led to 3 basic sets of findings. First,…

[Theory, method and application of method R on estimation of (co)variance components].

PubMed

Liu, Wen-Zhong

2004-07-01

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

Common heritable effects underpin concerns over norm maintenance and in-group favoritism: evidence from genetic analyses of right-wing authoritarianism and traditionalism.

PubMed

Lewis, Gary J; Bates, Timothy C

2014-08-01

Research has shown that in-group favoritism is associated with concerns over the maintenance of social norms. Here we present two studies examining whether genetic factors underpin this association. A classical twin design was used to decompose phenotypic variance into genetic and environmental components in two studies. Study 1 used 812 pairs of adult U.S. twins from the nationally representative MIDUS II sample. Study 2 used 707 pairs of middle-age twins from the Minnesota Twin Registry. In-group favoritism was measured with scales tapping preferences for in-group (vs. out-group) individuals; norm concerns were measured with the Multidimensional Personality Questionnaire-Traditionalism (Study 1) and Right-Wing Authoritarianism (RWA; Study 2) scales. In Study 1, heritable effects underlying traditionalism were moderately (c. 35%) overlapping with the genetic variance underpinning in-group favoritism. In Study 2, heritable influences on RWA were entirely shared with the heritable effects on in-group favoritism. Moreover, we observed that Big Five Openness shared common genetic links to both RWA and in-group favoritism. These results suggest that, at the genetic level, in-group favoritism is linked with a system related to concern over normative social practices, which is, in turn, partially associated with trait Openness. © 2013 Wiley Periodicals, Inc.

Exploring Oral Cancer Patients' Preference in Medical Decision Making and Quality of Life.

PubMed

Cheng, Sun-Long; Liao, Hsien-Hua; Shueng, Pei-Wei; Lee, Hsi-Chieh; Cheewakriangkrai, Chalong; Chang, Chi-Chang

2017-01-01

Little is known about the clinical effects of shared medical decision making (SMDM) associated with quality of life about oral cancer? To understand patients who occurred potential cause of SMDM and extended to explore the interrelated components of quality of life for providing patients with potential adaptation of early assessment. All consenting patients completed the SMDM questionnaire and 36-Item Short Form (SF-36). Regression analyses were conducted to find predictors of quality of life among oral cancer patients. The proposed model predicted 57.4% of the variance in patients' SF-36 Mental Component scores. Patient mental component summary scores were associated with smoking habit (β=-0.3449, p=0.022), autonomy (β=-0.226, p=0.018) and Control preference (β=-0.388, p=0.007). The proposed model predicted 42.6% of the variance in patients' SF-36 Physical component scores. Patient physical component summary scores were associated with higher education (β=0.288, p=0.007), employment status (β=-0.225, p=0.033), involvement perceived (β=-0.606, p=0.011) and Risk communication (β=-0.558, p=0.019). Future research is necessary to determine whether oral cancer patients would benefit from early screening and intervention to address shared medical decision making.

An Empirical Assessment of Defense Contractor Risk 1976-1984.

DTIC Science & Technology

1986-06-01

Model to evaluate the. Department of Defense contract pricing , financing, and profit policies . ’ D*’ ’ *NTV D? 7A’:: TA E *A l ..... -:- A-i SN 0102...defense con- tractor risk-return relationship is performed utilizing four methods: mean-variance analysis of rate of return, the Capital Asset Pricing Model ...relationship is performed utilizing four methods: mean- variance analysis of rate of return, the Capital Asset Pricing Model , mean-variance analysis of total

Reductions in HIV/STI Incidence and Sharing of Injection Equipment among Female Sex Workers Who Inject Drugs: Results from a Randomized Controlled Trial

PubMed Central

Strathdee, Steffanie A.; Abramovitz, Daniela; Lozada, Remedios; Martinez, Gustavo; Rangel, Maria Gudelia; Vera, Alicia; Staines, Hugo; Magis-Rodriguez, Carlos; Patterson, Thomas L.

2013-01-01

Background We evaluated brief combination interventions to simultaneously reduce sexual and injection risks among female sex workers who inject drugs (FSW-IDUs) in Tijuana and Ciudad Juarez, Mexico during 2008–2010, when harm reduction coverage was expanding rapidly in Tijuana, but less so in Juarez. Methods FSW-IDUs ≥18 years reporting sharing injection equipment and unprotected sex with clients within the last month participated in a randomized factorial trial comparing four brief, single-session conditions combining either an interactive or didactic version of a sexual risk intervention to promote safer sex in the context of drug use, and an injection risk intervention to reduce sharing of needles/injection paraphernalia. Women underwent quarterly interviews and testing for HIV, syphilis, gonorrhea, Chlamydia and Trichomonas, blinding interviewers and assessors to assignment. Poisson regression with robust variance estimation and repeated measures ordinal logistic regression examined effects on combined HIV/STI incidence and receptive needle sharing frequency. Findings Of 584 initially HIV-negative FSW-IDUs, retention was ≥90%. After 12 months, HIV/STI incidence decreased >50% in the interactive vs. didactic sex intervention (Tijuana:AdjRR:0.38,95% CI:0.16–0.89; Juarez: AdjRR:0.44,95% CI:0.19–0.99). In Juarez, women receiving interactive vs. didactic injection risk interventions decreased receptive needle-sharing by 85% vs. 71%, respectively (p = 0.04); in Tijuana, receptive needle sharing declined by 95%, but was similar in active versus didactic groups. Tijuana women reported significant increases in access to syringes and condoms, but Juarez women did not. Interpretation After 12 months in both cities, the interactive sexual risk intervention significantly reduced HIV/STI incidence. Expanding free access to sterile syringes coupled with brief, didactic education on safer injection was necessary and sufficient for achieving robust, sustained injection risk reductions in Tijuana. In the absence of expanding syringe access in Juarez, the injection risk intervention achieved significant, albeit more modest reductions, suggesting that community-level interventions incorporating harm reduction are more powerful than individual-level interventions. Trial Registration clinicaltrials.gov NCT00840658 PMID:23785451

Analysis of Behavioral and Emotional Problems in Children Highlights the Role of Genotype × Environment Interaction.

PubMed

Molenaar, Dylan; Middeldorp, Christel; van Beijsterveldt, Toos; Boomsma, Dorret I

2015-01-01

This study tested for Genotype × Environment (G × E) interaction on behavioral and emotional problems in children using new methods that do not require identification of candidate genes or environments, can distinguish between interaction with shared and unique environment, and are insensitive to scale effects. Parental ratings of problem behavior from 14,755 twin pairs (5.3 years, SD = 0.22) indicated G × E interaction on emotional liability, social isolation, aggression, attention problems, dependency, anxiety, and physical coordination. Environmental influences increased in children who were genetically more predisposed to problem behavior, with ~20% of the variance due to G × E interaction (8% for anxiety to 37% for attention problems). Ignoring G × E interaction does not greatly bias heritability estimates, but it does offer a comprehensive model of the etiology for childhood problems. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.

Emotions as Proximal Causes of Word of Mouth: A Nonlinear Approach.

PubMed

Lopes, Rita Rueff; Navarro, José; Silva, Ana Junca

2018-01-01

Service research tends to operationalize word of mouth (WOM) behavior as one of the many responses to service satisfaction. In this sense, little is known about its antecedents or moderators. The objective of this study was to investigate the role of customers' emotions during service experiences on WOM, applying nonlinear techniques and exploring the moderating role of customers' propensity for emotional contagion. Using the critical incidents technique, 122 customers recalled significant service experiences and the emotions they aroused, and reported if they shared said experiences with other individuals. We found that, whereas linear methods presented non-significant results in the emotions-WOM relationship, nonlinear ones (artificial neural networks) explained 46% of variance. Negative emotions were stronger predictors of WOM and the importance of emotions for WOM was significantly higher for individuals with high propensity for emotional contagion (R^2 = .79) than for those with lower levels (R^2 = .48). Theoretical and practical implications are discussed.

MVL spatiotemporal analysis for model intercomparison in EPS: application to the DEMETER multi-model ensemble

NASA Astrophysics Data System (ADS)

Fernández, J.; Primo, C.; Cofiño, A. S.; Gutiérrez, J. M.; Rodríguez, M. A.

2009-08-01

In a recent paper, Gutiérrez et al. (Nonlinear Process Geophys 15(1):109-114, 2008) introduced a new characterization of spatiotemporal error growth—the so called mean-variance logarithmic (MVL) diagram—and applied it to study ensemble prediction systems (EPS); in particular, they analyzed single-model ensembles obtained by perturbing the initial conditions. In the present work, the MVL diagram is applied to multi-model ensembles analyzing also the effect of model formulation differences. To this aim, the MVL diagram is systematically applied to the multi-model ensemble produced in the EU-funded DEMETER project. It is shown that the shared building blocks (atmospheric and ocean components) impose similar dynamics among different models and, thus, contribute to poorly sampling the model formulation uncertainty. This dynamical similarity should be taken into account, at least as a pre-screening process, before applying any objective weighting method.

Cultural Consensus Theory: Aggregating Continuous Responses in a Finite Interval

NASA Astrophysics Data System (ADS)

Batchelder, William H.; Strashny, Alex; Romney, A. Kimball

Cultural consensus theory (CCT) consists of cognitive models for aggregating responses of "informants" to test items about some domain of their shared cultural knowledge. This paper develops a CCT model for items requiring bounded numerical responses, e.g. probability estimates, confidence judgments, or similarity judgments. The model assumes that each item generates a latent random representation in each informant, with mean equal to the consensus answer and variance depending jointly on the informant and the location of the consensus answer. The manifest responses may reflect biases of the informants. Markov Chain Monte Carlo (MCMC) methods were used to estimate the model, and simulation studies validated the approach. The model was applied to an existing cross-cultural dataset involving native Japanese and English speakers judging the similarity of emotion terms. The results sharpened earlier studies that showed that both cultures appear to have very similar cognitive representations of emotion terms.

Parametric Cooling of Ultracold Atoms

NASA Astrophysics Data System (ADS)

Boguslawski, Matthew; Bharath, H. M.; Barrios, Maryrose; Chapman, Michael

2017-04-01

An oscillator is characterized by a restoring force which determines the natural frequency at which oscillations occur. The amplitude and phase-noise of these oscillations can be amplified or squeezed by modulating the magnitude of this force (e.g. the stiffness of the spring) at twice the natural frequency. This is parametric excitation; a long-studied phenomena in both the classical and quantum regimes. Parametric cooling, or the parametric squeezing of thermo-mechanical noise in oscillators has been studied in micro-mechanical oscillators and trapped ions. We study parametric cooling in ultracold atoms. This method shows a modest reduction of the variance of atomic momenta, and can be easily employed with pre-existing controls in many experiments. Parametric cooling is comparable to delta-kicked cooling, sharing similar limitations. We expect this cooling to find utility in microgravity experiments where the experiment duration is limited by atomic free expansion.

Soft-tissue facial characteristics of attractive Chinese men compared to normal men

PubMed Central

Wu, Feng; Li, Junfang; He, Hong; Huang, Na; Tang, Youchao; Wang, Yuanqing

2015-01-01

Objective: To compare the facial characteristics of attractive Chinese men with those of reference men. Materials and Methods: The three-dimensional coordinates of 50 facial landmarks were collected in 40 healthy reference men and in 40 “attractive” men, soft tissue facial angles, distances, areas, and volumes were computed and compared using analysis of variance. Results: When compared with reference men, attractive men shared several similar facial characteristics: relatively large forehead, reduced mandible, and rounded face. They had a more acute soft tissue profile, an increased upper facial width and middle facial depth, larger mouth, and more voluminous lips than reference men. Conclusions: Attractive men had several facial characteristics suggesting babyness. Nonetheless, each group of men was characterized by a different development of these features. Esthetic reference values can be a useful tool for clinicians, but should always consider the characteristics of individual faces. PMID:26221357

A simple approximation of moments of the quasi-equilibrium distribution of an extended stochastic theta-logistic model with non-integer powers.

PubMed

Bhowmick, Amiya Ranjan; Bandyopadhyay, Subhadip; Rana, Sourav; Bhattacharya, Sabyasachi

2016-01-01

The stochastic versions of the logistic and extended logistic growth models are applied successfully to explain many real-life population dynamics and share a central body of literature in stochastic modeling of ecological systems. To understand the randomness in the population dynamics of the underlying processes completely, it is important to have a clear idea about the quasi-equilibrium distribution and its moments. Bartlett et al. (1960) took a pioneering attempt for estimating the moments of the quasi-equilibrium distribution of the stochastic logistic model. Matis and Kiffe (1996) obtain a set of more accurate and elegant approximations for the mean, variance and skewness of the quasi-equilibrium distribution of the same model using cumulant truncation method. The method is extended for stochastic power law logistic family by the same and several other authors (Nasell, 2003; Singh and Hespanha, 2007). Cumulant truncation and some alternative methods e.g. saddle point approximation, derivative matching approach can be applied if the powers involved in the extended logistic set up are integers, although plenty of evidence is available for non-integer powers in many practical situations (Sibly et al., 2005). In this paper, we develop a set of new approximations for mean, variance and skewness of the quasi-equilibrium distribution under more general family of growth curves, which is applicable for both integer and non-integer powers. The deterministic counterpart of this family of models captures both monotonic and non-monotonic behavior of the per capita growth rate, of which theta-logistic is a special case. The approximations accurately estimate the first three order moments of the quasi-equilibrium distribution. The proposed method is illustrated with simulated data and real data from global population dynamics database. Copyright © 2015 Elsevier Inc. All rights reserved.

Human Aggression Across the Lifespan: Genetic Propensities and Environmental Moderators

PubMed Central

Tuvblad, Catherine; Baker, Laura A.

2013-01-01

This chapter reviews the recent evidence of genetic and environmental influences on human aggression. Findings from a large selection of the twin and adoption studies that have investigated the genetic and environmental architecture of aggressive behavior are summarized. These studies together show that about half (50%) of the variance in aggressive behavior is explained by genetic influences in both males and females, with the remaining 50% of the variance being explained by environmental factors not shared by family members. Form of aggression (reactive, proactive, direct/physical, indirect/relational), method of assessment (laboratory observation, self-report, ratings by parents and teachers), and age of the subjects—all seem to be significant moderators of the magnitude of genetic and environmental influences on aggressive behavior. Neither study design (twin vs. sibling adoption design) nor sex (male vs. female) seems to impact the magnitude of the genetic and environmental influences on aggression. There is also some evidence of gene-environment interaction (G × E) from both twin/adoption studies and molecular genetic studies. Various measures of family adversity and social disadvantage have been found to moderate genetic influences on aggressive behavior. Findings from these G × E studies suggest that not all individuals will be affected to the same degree by experiences and exposures, and that genetic predispositions may have different effects depending on the environment. PMID:22078481

An apparent contradiction: increasing variability to achieve greater precision?

PubMed

Rosenblatt, Noah J; Hurt, Christopher P; Latash, Mark L; Grabiner, Mark D

2014-02-01

To understand the relationship between variability of foot placement in the frontal plane and stability of gait patterns, we explored how constraining mediolateral foot placement during walking affects the structure of kinematic variance in the lower-limb configuration space during the swing phase of gait. Ten young subjects walked under three conditions: (1) unconstrained (normal walking), (2) constrained (walking overground with visual guides for foot placement to achieve the measured unconstrained step width) and, (3) beam (walking on elevated beams spaced to achieve the measured unconstrained step width). The uncontrolled manifold analysis of the joint configuration variance was used to quantify two variance components, one that did not affect the mediolateral trajectory of the foot in the frontal plane ("good variance") and one that affected this trajectory ("bad variance"). Based on recent studies, we hypothesized that across conditions (1) the index of the synergy stabilizing the mediolateral trajectory of the foot (the normalized difference between the "good variance" and "bad variance") would systematically increase and (2) the changes in the synergy index would be associated with a disproportionate increase in the "good variance." Both hypotheses were confirmed. We conclude that an increase in the "good variance" component of the joint configuration variance may be an effective method of ensuring high stability of gait patterns during conditions requiring increased control of foot placement, particularly if a postural threat is present. Ultimately, designing interventions that encourage a larger amount of "good variance" may be a promising method of improving stability of gait patterns in populations such as older adults and neurological patients.

Discrete velocity computations with stochastic variance reduction of the Boltzmann equation for gas mixtures

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

Clarke, Peter; Varghese, Philip; Goldstein, David

We extend a variance reduced discrete velocity method developed at UT Austin [1, 2] to gas mixtures with large mass ratios and flows with trace species. The mixture is stored as a collection of independent velocity distribution functions, each with a unique grid in velocity space. Different collision types (A-A, A-B, B-B, etc.) are treated independently, and the variance reduction scheme is formulated with different equilibrium functions for each separate collision type. The individual treatment of species enables increased focus on species important to the physics of the flow, even if the important species are present in trace amounts. Themore » method is verified through comparisons to Direct Simulation Monte Carlo computations and the computational workload per time step is investigated for the variance reduced method.« less

Characterization of turbulence stability through the identification of multifractional Brownian motions

NASA Astrophysics Data System (ADS)

Lee, K. C.

2013-02-01

Multifractional Brownian motions have become popular as flexible models in describing real-life signals of high-frequency features in geoscience, microeconomics, and turbulence, to name a few. The time-changing Hurst exponent, which describes regularity levels depending on time measurements, and variance, which relates to an energy level, are two parameters that characterize multifractional Brownian motions. This research suggests a combined method of estimating the time-changing Hurst exponent and variance using the local variation of sampled paths of signals. The method consists of two phases: initially estimating global variance and then accurately estimating the time-changing Hurst exponent. A simulation study shows its performance in estimation of the parameters. The proposed method is applied to characterization of atmospheric stability in which descriptive statistics from the estimated time-changing Hurst exponent and variance classify stable atmosphere flows from unstable ones.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

PubMed

Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

2015-10-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

PubMed Central

Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

2016-01-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

Statistical aspects of quantitative real-time PCR experiment design.

PubMed

Kitchen, Robert R; Kubista, Mikael; Tichopad, Ales

2010-04-01

Experiments using quantitative real-time PCR to test hypotheses are limited by technical and biological variability; we seek to minimise sources of confounding variability through optimum use of biological and technical replicates. The quality of an experiment design is commonly assessed by calculating its prospective power. Such calculations rely on knowledge of the expected variances of the measurements of each group of samples and the magnitude of the treatment effect; the estimation of which is often uninformed and unreliable. Here we introduce a method that exploits a small pilot study to estimate the biological and technical variances in order to improve the design of a subsequent large experiment. We measure the variance contributions at several 'levels' of the experiment design and provide a means of using this information to predict both the total variance and the prospective power of the assay. A validation of the method is provided through a variance analysis of representative genes in several bovine tissue-types. We also discuss the effect of normalisation to a reference gene in terms of the measured variance components of the gene of interest. Finally, we describe a software implementation of these methods, powerNest, that gives the user the opportunity to input data from a pilot study and interactively modify the design of the assay. The software automatically calculates expected variances, statistical power, and optimal design of the larger experiment. powerNest enables the researcher to minimise the total confounding variance and maximise prospective power for a specified maximum cost for the large study. Copyright 2010 Elsevier Inc. All rights reserved.

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.

A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data

PubMed Central

Feng, Hao; Conneely, Karen N.; Wu, Hao

2014-01-01

DNA methylation is an important epigenetic modification that has essential roles in cellular processes including gene regulation, development and disease and is widely dysregulated in most types of cancer. Recent advances in sequencing technology have enabled the measurement of DNA methylation at single nucleotide resolution through methods such as whole-genome bisulfite sequencing and reduced representation bisulfite sequencing. In DNA methylation studies, a key task is to identify differences under distinct biological contexts, for example, between tumor and normal tissue. A challenge in sequencing studies is that the number of biological replicates is often limited by the costs of sequencing. The small number of replicates leads to unstable variance estimation, which can reduce accuracy to detect differentially methylated loci (DML). Here we propose a novel statistical method to detect DML when comparing two treatment groups. The sequencing counts are described by a lognormal-beta-binomial hierarchical model, which provides a basis for information sharing across different CpG sites. A Wald test is developed for hypothesis testing at each CpG site. Simulation results show that the proposed method yields improved DML detection compared to existing methods, particularly when the number of replicates is low. The proposed method is implemented in the Bioconductor package DSS. PMID:24561809

Cross-bispectrum computation and variance estimation

NASA Technical Reports Server (NTRS)

Lii, K. S.; Helland, K. N.

1981-01-01

A method for the estimation of cross-bispectra of discrete real time series is developed. The asymptotic variance properties of the bispectrum are reviewed, and a method for the direct estimation of bispectral variance is given. The symmetry properties are described which minimize the computations necessary to obtain a complete estimate of the cross-bispectrum in the right-half-plane. A procedure is given for computing the cross-bispectrum by subdividing the domain into rectangular averaging regions which help reduce the variance of the estimates and allow easy application of the symmetry relationships to minimize the computational effort. As an example of the procedure, the cross-bispectrum of a numerically generated, exponentially distributed time series is computed and compared with theory.

The Threat of Common Method Variance Bias to Theory Building

ERIC Educational Resources Information Center

Reio, Thomas G., Jr.

2010-01-01

The need for more theory building scholarship remains one of the pressing issues in the field of HRD. Researchers can employ quantitative, qualitative, and/or mixed methods to support vital theory-building efforts, understanding however that each approach has its limitations. The purpose of this article is to explore common method variance bias as…

ADHD and Method Variance: A Latent Variable Approach Applied to a Nationally Representative Sample of College Freshmen

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

This study employed a correlated trait-correlated method application of confirmatory factor analysis to disentangle trait and method variance from measures of attention-deficit/hyperactivity disorder obtained at the college level. The two trait factors were "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" ("DSM-IV")…

Understanding the Relation between Anorexia Nervosa and Bulimia Nervosa in a Swedish National Twin Sample

PubMed Central

Bulik, Cynthia M; Thornton, Laura; Root, Tammy L.; Pisetsky, Emily M.; Lichtenstein, Paul; Pedersen, Nancy L.

2010-01-01

Background We present a bivariate twin analysis of anorexia nervosa (AN) and bulimia nervosa (BN) to determine the extent to which shared genetic and environmental factors contribute to liability to these disorders. Method Focusing on females from the Swedish Twin study of Adults: Genes and Environment (STAGE) (N=7000), we calculated heritability estimates for narrow and broad AN and BN and estimated their genetic correlation. Results In the full model, the heritability estimate for narrow AN was (a2 = .57; 95% CI: .00, .81) and for narrow BN (a2 = .62; 95% CI: .08, .70) with the remaining variance accounted for by unique environmental factors. Shared environmental factors estimates were (c2 = .00; 95% CI: .00, .67) for AN and (c2 = .00; 95% CI: .00, .40) for BN. Moderate additive genetic (.46) and unique environmental (.42) correlations between AN and BN were observed. Heritability estimates for broad AN were lower (a2 = .29; 95% CI: .04, .43) than for narrow AN, but estimates for broad BN were similar to narrow BN. The genetic correlation for broad AN and BN was .79 and the unique environmental correlation was .44. Conclusions We highlight the contribution of additive genetic factors to both narrow and broad AN and BN and demonstrate a moderate overlap of both genetic and unique environmental factors that influence the two conditions. Common concurrent and sequential comorbidity of AN and BN can in part be accounted for by shared genetic and environmental influences on liability although independent factors also operative. PMID:19828139

Heuristic and analytic processing: age trends and associations with cognitive ability and cognitive styles.

PubMed

Kokis, Judite V; Macpherson, Robyn; Toplak, Maggie E; West, Richard F; Stanovich, Keith E

2002-09-01

Developmental and individual differences in the tendency to favor analytic responses over heuristic responses were examined in children of two different ages (10- and 11-year-olds versus 13-year-olds), and of widely varying cognitive ability. Three tasks were examined that all required analytic processing to override heuristic processing: inductive reasoning, deductive reasoning under conditions of belief bias, and probabilistic reasoning. Significant increases in analytic responding with development were observed on the first two tasks. Cognitive ability was associated with analytic responding on all three tasks. Cognitive style measures such as actively open-minded thinking and need for cognition explained variance in analytic responding on the tasks after variance shared with cognitive ability had been controlled. The implications for dual-process theories of cognition and cognitive development are discussed.

How strong is the impact of the Indo-ocean dipole on the surface air temperature/sea level pressure anomalies in the Mediterranean region?

NASA Astrophysics Data System (ADS)

Polonsky, Alexander B.; Basharin, Dmitry V.

2017-04-01

The aim of this paper is to study the interannual climate variability over the Mediterranean region related to the Indo-ocean dipole (IOD) using the data of re-analyses, archival data and specialized numerical experiments. It is shown that the IOD does not impact essentially the anomalies of surface air temperature (SAT) and sea level pressure (SLP) in the Mediterranean region. On average, the IOD-induced share of the SAT/SLP variance in the total variance of these fields in the Mediterranean region is smaller than 10% even in summer when it is at a maximum. However, the statistically significant IOD-induced SAT/SLP anomalies in the Mediterranean region are detectable. For definite IOD events the associated Mediterranean SAT anomalies can reach about 1 °C.

An evaluation of evaluative personality terms: a comparison of the big seven and five-factor model in predicting psychopathology.

PubMed

Durrett, Christine; Trull, Timothy J

2005-09-01

Two personality models are compared regarding their relationship with personality disorder (PD) symptom counts and with lifetime Axis I diagnoses. These models share 5 similar domains, and the Big 7 model also includes 2 domains assessing self-evaluation: positive and negative valence. The Big 7 model accounted for more variance in PDs than the 5-factor model, primarily because of the association of negative valence with most PDs. Although low-positive valence was associated with most Axis I diagnoses, the 5-factor model generally accounted for more variance in Axis I diagnoses than the Big 7 model. Some predicted associations between self-evaluation and psychopathology were not found, and unanticipated associations emerged. These findings are discussed regarding the utility of evaluative terms in clinical assessment.

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M.J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. Although no individual single nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels, i.e. expression quantitative loci (eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10−4), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, TS had a smaller, non-significant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and TS/CT were included in the analysis (p=0.01). Previous work has shown that TS and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Are there common familial influences for major depressive disorder and an overeating-binge eating dimension in both European American and African American female twins?

PubMed

Munn-Chernoff, Melissa A; Grant, Julia D; Agrawal, Arpana; Koren, Rachel; Glowinski, Anne L; Bucholz, Kathleen K; Madden, Pamela A F; Heath, Andrew C; Duncan, Alexis E

2015-05-01

Although prior studies have demonstrated that depression is associated with an overeating-binge eating dimension (OE-BE) phenotypically, little research has investigated whether familial factors contribute to the co-occurrence of these phenotypes, especially in community samples with multiple racial/ethnic groups. We examined the extent to which familial (i.e., genetic and shared environmental) influences overlapped between Major Depressive Disorder (MDD) and OE-BE in a population-based sample and whether these influences were similar across racial/ethnic groups. Participants included 3,226 European American (EA) and 550 African American (AA) young adult women from the Missouri Adolescent Female Twin Study. An adaptation of the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was administered to assess lifetime DSM-IV MDD and OE-BE. Quantitative genetic modeling was used to estimate familial influences between both phenotypes; all models controlled for age. The best-fitting model, which combined racial/ethnic groups, found that additive genetic influences accounted for 44% (95% CI: 34%, 53%) of the MDD variance and 40% (25%, 54%) for OE-BE, with the remaining variances due to non-shared environmental influences. Genetic overlap was substantial (rg  = .61 [.39, .85]); non-shared environmental influences on MDD and OE-BE overlapped weakly (re  = .26 [.09, .42]). Results suggest that common familial influences underlie MDD and OE-BE, and the magnitude of familial influences contributing to the comorbidity between MDD and OE-BE is similar between EA and AA women. If racial/ethnic differences truly exist, then larger sample sizes may be needed to fully elucidate familial risk for comorbid MDD and OE-BE across these groups. © 2014 Wiley Periodicals, Inc.

Examining the role of common genetic variants on alcohol, tobacco, cannabis, and illicit drug dependence

PubMed Central

Palmer, RHC; Brick, L; Nugent, NR; Bidwell, LC; McGeary, JE; Knopik, VS; Keller, MC

2014-01-01

Background and Aims Twin and family studies suggest that genetic influences are shared across substances of abuse. However, despite evidence of heritability, genome-wide association and candidate gene studies have indicated numerous markers of limited effects, suggesting that much of the heritability remains missing. We estimated (1) the aggregate effect of common single nucleotide polymorphisms (SNPs) on multiple indicators of comorbid drug problems that are typically employed across community and population-based samples, and (2) the genetic covariance across these measures. Participants 2596 unrelated subjects from the “Study of Addiction: Genetics and Environment” provided information on alcohol, tobacco, cocaine, cannabis, and other illicit substance dependence. Phenotypic measures included: (1) a factor score based on DSM-IV drug dependence diagnoses (DD), (2) a factor score based on problem use (PU; i.e., 1+ DSM-IV symptoms), and (3) dependence vulnerability (DV; a ratio of DSM-IV symptoms to the number of substances used). Findings Univariate and bivariate Genome-wide complex trait analyses of this selected sample indicated that common SNPs explained 25-36% of the variance across measures, with DD and DV having the largest effects [h2SNP (CI)=0.36 (0.11-0.62) and 0.33(0.07-0.58), respectively; PU = 0.25 (-0.01-0.51)]. Genetic effects were shared across the three phenotypic measures of comorbid drug problems (rSNP; rDD-PU = 0.92 (0.76-1.00), rDD-DV = 0.97 (0.87-1.00), and rPU-DV = 0.96 (0.82-1.00)). Conclusion At least 20% of the variance in the generalized vulnerability to substance dependence is attributable to common single nucleotide polymorphisms. The additive effect of common single nucleotide polymorphisms is shared across important indicators of comorbid drug problems. PMID:25424661

Identification and analysis of pig chimeric mRNAs using RNA sequencing data

PubMed Central

2012-01-01

Background Gene fusion is ubiquitous over the course of evolution. It is expected to increase the diversity and complexity of transcriptomes and proteomes through chimeric sequence segments or altered regulation. However, chimeric mRNAs in pigs remain unclear. Here we identified some chimeric mRNAs in pigs and analyzed the expression of them across individuals and breeds using RNA-sequencing data. Results The present study identified 669 putative chimeric mRNAs in pigs, of which 251 chimeric candidates were detected in a set of RNA-sequencing data. The 618 candidates had clear trans-splicing sites, 537 of which obeyed the canonical GU-AG splice rule. Only two putative pig chimera variants whose fusion junction was overlapped with that of a known human chimeric mRNA were found. A set of unique chimeric events were considered middle variances in the expression across individuals and breeds, and revealed non-significant variance between sexes. Furthermore, the genomic region of the 5′ partner gene shares a similar DNA sequence with that of the 3′ partner gene for 458 putative chimeric mRNAs. The 81 of those shared DNA sequences significantly matched the known DNA-binding motifs in the JASPAR CORE database. Four DNA motifs shared in parental genomic regions had significant similarity with known human CTCF binding sites. Conclusions The present study provided detailed information on some pig chimeric mRNAs. We proposed a model that trans-acting factors, such as CTCF, induced the spatial organisation of parental genes to the same transcriptional factory so that parental genes were coordinatively transcribed to give birth to chimeric mRNAs. PMID:22925561

The peer effect on pain tolerance.

PubMed

Engebretsen, Solveig; Frigessi, Arnoldo; Engø-Monsen, Kenth; Furberg, Anne-Sofie; Stubhaug, Audun; de Blasio, Birgitte Freiesleben; Nielsen, Christopher Sivert

2018-05-19

Twin studies have found that approximately half of the variance in pain tolerance can be explained by genetic factors, while shared family environment has a negligible effect. Hence, a large proportion of the variance in pain tolerance is explained by the (non-shared) unique environment. The social environment beyond the family is a potential candidate for explaining some of the variance in pain tolerance. Numerous individual traits have previously shown to be associated with friendship ties. In this study, we investigate whether pain tolerance is associated with friendship ties. We study the friendship effect on pain tolerance by considering data from the Tromsø Study: Fit Futures I, which contains pain tolerance measurements and social network information for adolescents attending first year of upper secondary school in the Tromsø area in Northern Norway. Pain tolerance was measured with the cold-pressor test (primary outcome), contact heat and pressure algometry. We analyse the data by using statistical methods from social network analysis. Specifically, we compute pairwise correlations in pain tolerance among friends. We also fit network autocorrelation models to the data, where the pain tolerance of an individual is explained by (among other factors) the average pain tolerance of the individual's friends. We find a significant and positive relationship between the pain tolerance of an individual and the pain tolerance of their friends. The estimated effect is that for every 1 s increase in friends' average cold-pressor tolerance time, the expected cold-pressor pain tolerance of the individual increases by 0.21 s (p-value: 0.0049, sample size n=997). This estimated effect is controlled for sex. The friendship effect remains significant when controlling for potential confounders such as lifestyle factors and test sequence among the students. Further investigating the role of sex on this friendship effect, we only find a significant peer effect of male friends on males, while there is no significant effect of friends' average pain tolerance on females in stratified analyses. Similar, but somewhat lower estimates were obtained for the other pain modalities. We find a positive and significant peer effect in pain tolerance. Hence, there is a significant tendency for students to be friends with others with similar pain tolerance. Sex-stratified analyses show that the only significant effect is the effect of male friends on males. Two different processes can explain the friendship effect in pain tolerance, selection and social transmission. Individuals might select friends directly due to similarity in pain tolerance, or indirectly through similarity in other confounding variables that affect pain tolerance. Alternatively, there is an influence effect among friends either directly in pain tolerance, or indirectly through other variables that affect pain tolerance. If there is indeed a social influence effect in pain tolerance, then the social environment can account for some of the unique environmental variance in pain tolerance. If so, it is possible to therapeutically affect pain tolerance through alteration of the social environment.

Joint multi-population analysis for genetic linkage of bipolar disorder or "wellness" to chromosome 4p.

PubMed

Visscher, P M; Haley, C S; Ewald, H; Mors, O; Egeland, J; Thiel, B; Ginns, E; Muir, W; Blackwood, D H

2005-02-05

To test the hypothesis that the same genetic loci confer susceptibility to, or protection from, disease in different populations, and that a combined analysis would improve the map resolution of a common susceptibility locus, we analyzed data from three studies that had reported linkage to bipolar disorder in a small region on chromosome 4p. Data sets comprised phenotypic information and genetic marker data on Scottish, Danish, and USA extended pedigrees. Across the three data sets, 913 individuals appeared in the pedigrees, 462 were classified, either as unaffected (323) or affected (139) with unipolar or bipolar disorder. A consensus linkage map was created from 14 microsatellite markers in a 33 cM region. Phenotypic and genetic data were analyzed using a variance component (VC) and allele sharing method. All previously reported elevated test statistics in the region were confirmed with one or both analysis methods, indicating the presence of one or more susceptibility genes to bipolar disorder in the three populations in the studied chromosome segment. When the results from both the VC and allele sharing method were considered, there was strong evidence for a susceptibility locus in the data from Scotland, some evidence in the data from Denmark and relatively less evidence in the data from the USA. The test statistics from the Scottish data set dominated the test statistics from the other studies, and no improved map resolution for a putative genetic locus underlying susceptibility in all three studies was obtained. Studies reporting linkage to the same region require careful scrutiny and preferably joint or meta analysis on the same basis in order to ensure that the results are truly comparable. (c) 2004 Wiley-Liss, Inc.

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.

The mean and variance of phylogenetic diversity under rarefaction

PubMed Central

Matsen, Frederick A.

2013-01-01

Summary Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required. PMID:23833701

The mean and variance of phylogenetic diversity under rarefaction.

PubMed

Nipperess, David A; Matsen, Frederick A

2013-06-01

Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

Borderline personality features in depressed or anxious patients.

PubMed

Distel, Marijn A; Smit, Johannes H; Spinhoven, Philip; Penninx, Brenda W J H

2016-07-30

Anxiety and depression frequently co-occur with borderline personality disorder. Relatively little research examined the presence of borderline personality features and its main domains (affective instability, identity problems, negative relationships and self-harm) in individuals with remitted and current anxiety and depression. Participants with current (n=597) or remitted (n=1115) anxiety and/or depression and healthy controls (n=431) were selected from the Netherlands Study of Depression and Anxiety. Assessments included the Personality Assessment Inventory - Borderline Features Scale and several clinical characteristics of anxiety and depression. Borderline personality features were more common in depression than in anxiety. Current comorbid anxiety and depression was associated with most borderline personality features. Anxiety and depression status explained 29.7% of the variance in borderline personality features and 3.8% (self-harm) to 31% (identity problems) of the variance in the four domains. A large part of the variance was shared between anxiety and depression but both disorders also explained a significant amount of unique variance. The severity of anxiety and depression and the level of daily dysfunctioning was positively associated with borderline personality features. Individuals with a longer duration of anxiety and depression showed more affective instability and identity problems. These findings suggest that patients with anxiety and depression may benefit from an assessment of personality pathology as it may have implications for psychological and pharmacological treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Job sharing: impact on the general well-being of female nurses.

PubMed

Kane, D; Kartha, A

1992-01-01

Women today have more life choices than ever before: career, marriage, motherhood, or any combination of the three. Unfortunately little has been done to make up for the competing demands of these roles. Job sharing may be the alternative choice which allows working women to cope with the multiple stressors of having it all--career and family without having to sacrifice their sense of well-being. Nursing administrators stand to benefit from a work schedule alternative which promotes a healthy balance between work and family. Job sharing may offer a solution to the loss of valued staff nurses who require less than full-time employment. In order to compare the general well-being of female nurses who are employed in full-time, casual part-time, and job sharing positions a descriptive correlation study was conducted. One hundred female nurses between the ages of 22 and 40 who have their children living at home with them completed the 18-Item General Well-Being Questionnaire. Additional questions regarding job satisfaction, physical health status, and demographic data were also included. The results of the analyses of variances revealed there were no statistical differences between the general well-being scores of women working full-time, casual part-time, or job sharing. However, crosstabulations showed the job sharing nurses had the highest ratings for job satisfaction and physical health status.

Comparison of two methods for composite score generation in dry eye syndrome.

PubMed

See, Craig; Bilonick, Richard A; Feuer, William; Galor, Anat

2013-09-19

To compare two methods of composite score generation in dry eye syndrome (DES). Male patients seen in the Miami Veterans Affairs eye clinic with normal eyelid, corneal, and conjunctival anatomy were recruited to participate in the study. Patients filled out the Dry Eye Questionnaire 5 (DEQ5) and underwent measurement of tear film parameters. DES severity scores were generated by independent component analysis (ICA) and latent class analysis (LCA). A total of 247 men were included in the study. Mean age was 69 years (SD 9). Using ICA analysis, osmolarity was found to carry the largest weight, followed by eyelid vascularity and meibomian orifice plugging. Conjunctival injection and tear breakup time (TBUT) carried the lowest weights. Using LCA analysis, TBUT was found to be best at discriminating healthy from diseased eyes, followed closely by Schirmer's test. DEQ5, eyelid vascularity, and conjunctival injection were the poorest at discrimination. The adjusted correlation coefficient between the two generated composite scores was 0.63, indicating that the shared variance was less than 40%. Both ICA and LCA produced composite scores for dry eye severity, with weak to moderate agreement; however, agreement for the relative importance of single diagnostic tests was poor between the two methods.

Optimal distribution of integration time for intensity measurements in degree of linear polarization polarimetry.

PubMed

Li, Xiaobo; Hu, Haofeng; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie

2016-04-04

We consider the degree of linear polarization (DOLP) polarimetry system, which performs two intensity measurements at orthogonal polarization states to estimate DOLP. We show that if the total integration time of intensity measurements is fixed, the variance of the DOLP estimator depends on the distribution of integration time for two intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the DOLP estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time in an approximate way by employing Delta method and Lagrange multiplier method. According to the theoretical analyses and real-world experiments, it is shown that the variance of the DOLP estimator can be decreased for any value of DOLP. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improve the measurement accuracy of the polarimetry system.

A neural model of valuation and information virality

PubMed Central

Baek, Elisa C.; O’Donnell, Matthew Brook; Kim, Hyun Suk; Cappella, Joseph N.

2017-01-01

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. PMID:28242678

A critique of the official report on the evacuation of the World Trade Center: continued doubts.

PubMed

Hotchkiss, H Lawrence; Aguirre, B E; Best, Eric

2013-10-01

This paper criticises the conclusions and the unanswered questions in the National Institute of Standards and Technology (NIST)'s official report on the evacuation of the World Trade Center in New York City, United States, on 11 September 2001. It reviews the extent to which the report disregards several conventional statistical methods and comments on the NIST's refusal to share the machine-readable data file with the scientific community for replication and further analysis. Problems lie in the sampling methods employed, the treatment of missing data, the use of ordinary least squares (OLS) with binary dependent variables, the failure to document the scalability of the scales used, the lack of tests to check for constant error variance, and the absence of overall fit tests of the model. There are also conceptual and theoretical issues, such as the absence in the report of considerations of the influence of group-level processes and their impact on the collective behaviour of evacuating collectivities. © 2013 The Author(s). Disasters © Overseas Development Institute, 2013.

A novel hybrid scattering order-dependent variance reduction method for Monte Carlo simulations of radiative transfer in cloudy atmosphere

NASA Astrophysics Data System (ADS)

Wang, Zhen; Cui, Shengcheng; Yang, Jun; Gao, Haiyang; Liu, Chao; Zhang, Zhibo

2017-03-01

We present a novel hybrid scattering order-dependent variance reduction method to accelerate the convergence rate in both forward and backward Monte Carlo radiative transfer simulations involving highly forward-peaked scattering phase function. This method is built upon a newly developed theoretical framework that not only unifies both forward and backward radiative transfer in scattering-order-dependent integral equation, but also generalizes the variance reduction formalism in a wide range of simulation scenarios. In previous studies, variance reduction is achieved either by using the scattering phase function forward truncation technique or the target directional importance sampling technique. Our method combines both of them. A novel feature of our method is that all the tuning parameters used for phase function truncation and importance sampling techniques at each order of scattering are automatically optimized by the scattering order-dependent numerical evaluation experiments. To make such experiments feasible, we present a new scattering order sampling algorithm by remodeling integral radiative transfer kernel for the phase function truncation method. The presented method has been implemented in our Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model for validation and evaluation. The main advantage of the method is that it greatly improves the trade-off between numerical efficiency and accuracy order by order.

Some refinements on the comparison of areal sampling methods via simulation

Treesearch

Jeffrey Gove

2017-01-01

The design of forest inventories and development of new sampling methods useful in such inventories normally have a two-fold target of design unbiasedness and minimum variance in mind. Many considerations such as costs go into the choices of sampling method for operational and other levels of inventory. However, the variance in terms of meeting a specified level of...

Efficiently estimating salmon escapement uncertainty using systematically sampled data

USGS Publications Warehouse

Reynolds, Joel H.; Woody, Carol Ann; Gove, Nancy E.; Fair, Lowell F.

2007-01-01

Fish escapement is generally monitored using nonreplicated systematic sampling designs (e.g., via visual counts from towers or hydroacoustic counts). These sampling designs support a variety of methods for estimating the variance of the total escapement. Unfortunately, all the methods give biased results, with the magnitude of the bias being determined by the underlying process patterns. Fish escapement commonly exhibits positive autocorrelation and nonlinear patterns, such as diurnal and seasonal patterns. For these patterns, poor choice of variance estimator can needlessly increase the uncertainty managers have to deal with in sustaining fish populations. We illustrate the effect of sampling design and variance estimator choice on variance estimates of total escapement for anadromous salmonids from systematic samples of fish passage. Using simulated tower counts of sockeye salmon Oncorhynchus nerka escapement on the Kvichak River, Alaska, five variance estimators for nonreplicated systematic samples were compared to determine the least biased. Using the least biased variance estimator, four confidence interval estimators were compared for expected coverage and mean interval width. Finally, five systematic sampling designs were compared to determine the design giving the smallest average variance estimate for total annual escapement. For nonreplicated systematic samples of fish escapement, all variance estimators were positively biased. Compared to the other estimators, the least biased estimator reduced bias by, on average, from 12% to 98%. All confidence intervals gave effectively identical results. Replicated systematic sampling designs consistently provided the smallest average estimated variance among those compared.

Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

PubMed

Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

2013-07-01

Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

Attention stabilizes the shared gain of V4 populations

PubMed Central

Rabinowitz, Neil C; Goris, Robbe L; Cohen, Marlene; Simoncelli, Eero P

2015-01-01

Responses of sensory neurons represent stimulus information, but are also influenced by internal state. For example, when monkeys direct their attention to a visual stimulus, the response gain of specific subsets of neurons in visual cortex changes. Here, we develop a functional model of population activity to investigate the structure of this effect. We fit the model to the spiking activity of bilateral neural populations in area V4, recorded while the animal performed a stimulus discrimination task under spatial attention. The model reveals four separate time-varying shared modulatory signals, the dominant two of which each target task-relevant neurons in one hemisphere. In attention-directed conditions, the associated shared modulatory signal decreases in variance. This finding provides an interpretable and parsimonious explanation for previous observations that attention reduces variability and noise correlations of sensory neurons. Finally, the recovered modulatory signals reflect previous reward, and are predictive of subsequent choice behavior. DOI: http://dx.doi.org/10.7554/eLife.08998.001 PMID:26523390

Additive Partial Least Squares for efficient modelling of independent variance sources demonstrated on practical case studies.

PubMed

Luoma, Pekka; Natschläger, Thomas; Malli, Birgit; Pawliczek, Marcin; Brandstetter, Markus

2018-05-12

A model recalibration method based on additive Partial Least Squares (PLS) regression is generalized for multi-adjustment scenarios of independent variance sources (referred to as additive PLS - aPLS). aPLS allows for effortless model readjustment under changing measurement conditions and the combination of independent variance sources with the initial model by means of additive modelling. We demonstrate these distinguishing features on two NIR spectroscopic case-studies. In case study 1 aPLS was used as a readjustment method for an emerging offset. The achieved RMS error of prediction (1.91 a.u.) was of similar level as before the offset occurred (2.11 a.u.). In case-study 2 a calibration combining different variance sources was conducted. The achieved performance was of sufficient level with an absolute error being better than 0.8% of the mean concentration, therefore being able to compensate negative effects of two independent variance sources. The presented results show the applicability of the aPLS approach. The main advantages of the method are that the original model stays unadjusted and that the modelling is conducted on concrete changes in the spectra thus supporting efficient (in most cases straightforward) modelling. Additionally, the method is put into context of existing machine learning algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.

flowVS: channel-specific variance stabilization in flow cytometry.

PubMed

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett's likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett's likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

A Multilevel AR(1) Model: Allowing for Inter-Individual Differences in Trait-Scores, Inertia, and Innovation Variance.

PubMed

Jongerling, Joran; Laurenceau, Jean-Philippe; Hamaker, Ellen L

2015-01-01

In this article we consider a multilevel first-order autoregressive [AR(1)] model with random intercepts, random autoregression, and random innovation variance (i.e., the level 1 residual variance). Including random innovation variance is an important extension of the multilevel AR(1) model for two reasons. First, between-person differences in innovation variance are important from a substantive point of view, in that they capture differences in sensitivity and/or exposure to unmeasured internal and external factors that influence the process. Second, using simulation methods we show that modeling the innovation variance as fixed across individuals, when it should be modeled as a random effect, leads to biased parameter estimates. Additionally, we use simulation methods to compare maximum likelihood estimation to Bayesian estimation of the multilevel AR(1) model and investigate the trade-off between the number of individuals and the number of time points. We provide an empirical illustration by applying the extended multilevel AR(1) model to daily positive affect ratings from 89 married women over the course of 42 consecutive days.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa

PubMed Central

Petegrosso, Raphael; Tolar, Jakub

2018-01-01

Single-cell RNA sequencing (scRNA-seq) has been widely applied to discover new cell types by detecting sub-populations in a heterogeneous group of cells. Since scRNA-seq experiments have lower read coverage/tag counts and introduce more technical biases compared to bulk RNA-seq experiments, the limited number of sampled cells combined with the experimental biases and other dataset specific variations presents a challenge to cross-dataset analysis and discovery of relevant biological variations across multiple cell populations. In this paper, we introduce a method of variance-driven multitask clustering of single-cell RNA-seq data (scVDMC) that utilizes multiple single-cell populations from biological replicates or different samples. scVDMC clusters single cells in multiple scRNA-seq experiments of similar cell types and markers but varying expression patterns such that the scRNA-seq data are better integrated than typical pooled analyses which only increase the sample size. By controlling the variance among the cell clusters within each dataset and across all the datasets, scVDMC detects cell sub-populations in each individual experiment with shared cell-type markers but varying cluster centers among all the experiments. Applied to two real scRNA-seq datasets with several replicates and one large-scale droplet-based dataset on three patient samples, scVDMC more accurately detected cell populations and known cell markers than pooled clustering and other recently proposed scRNA-seq clustering methods. In the case study applied to in-house Recessive Dystrophic Epidermolysis Bullosa (RDEB) scRNA-seq data, scVDMC revealed several new cell types and unknown markers validated by flow cytometry. MATLAB/Octave code available at https://github.com/kuanglab/scVDMC. PMID:29630593

flowVS: channel-specific variance stabilization in flow cytometry

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

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

flowVS: channel-specific variance stabilization in flow cytometry

DOE PAGES

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

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

Vidal-Codina, F., E-mail: fvidal@mit.edu; Nguyen, N.C., E-mail: cuongng@mit.edu; Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basismore » approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.« less

Turbulence feature modifications from high to low wind conditions: results from the CCT observations at Ny-Ålesund, Svalbard.

NASA Astrophysics Data System (ADS)

Schiavon, Mario; Mazzola, Mauro; Tampieri, Francesco; Pietro Viola, Angelo; Choi, Taejin

2017-04-01

The turbulence features in the quasi neutral surface layer are investigated as the intensity of the wind decreases, i.e. as the forcing due to the shear decreases. In this aim, a 5-year (2012-2016) set of observations of meteorological and micro-meteorological parameters acquired on the Climate Change Tower (CCT) in Ny-Ålesund, Svalbard Islands, is used. The 34-m high tower, operated by the Italian National Council of Research (CNR) is equipped with four slow response wind and temperature probes and three fast response sonic anemometers and is located on heterogeneous terrain. One of the fast sensors was installed by KOPRI since 2012. The observations are averaged over 10 and 30 minutes intervals. The analysis addresses the share of the mean turbulent kinetic energy (TKE) among the along-wind, cross-wind and vertical velocity variances (respectively < u2 >, < v2 >, < w2 >), with attention to the parameterizations of the boundary layer commonly used in NWP models: the classical Mellor-Yamada (1982) scheme with the return-to-isotropy term by Rotta(1951) and its modifications, and the recent approach by Zilitinkevich and coworkers (2013). The results show that the share of TKE among the vertical < w2 > and the total horizontal variance < u2 > + < v2 > is weakly dependent on the wind velocity while the share of the total horizontal variance between the along-wind and cross-wind components depends on wind speed. At high velocity (and large wind shear) a clear anisotropy , with < u2 >≈ 2 < v2 >, is observed, quite consistent with literature (Tampieri, 2017, pag. 69). As the velocity decreases, the ratio < u2 > /(< u2 > + < v2 >) displays a wide flat distribution between 0.2 and 0.8 with median values corresponding approximately to horizontal isotropy: < u2 >≈< v2 >. These features can be parameterized using suitable coefficients, function of the wind intensity in the equations for the TKE share, capturing the average behaviour of the flow. A further investigation based on estimates of the relative importance of the high frequency and low frequency spectral distribution of TKE suggests that the presence of slow motions (like meandering) affects the tendency to isotropy; in absence of such effects, the horizontal turbulence is anisotropic both in high and in relatively low wind conditions. Some comparison with the results from other data sets is outlined, to give a preliminary answer to the possible generalization of such features. Mellor, Yamada. Rev. G. Space Phys. 20, 851 (1982) Rotta. Z. Phys. 129, 547 (1951) Tampieri. Turbulence and Dispersion in the PBL. Springer (2017) Zilitinkevich et al. Bound.-Layer Meteorol. 146, 341 (2013)

The development of generosity and moral cognition across five cultures.

PubMed

Cowell, Jason M; Lee, Kang; Malcolm-Smith, Susan; Selcuk, Bilge; Zhou, Xinyue; Decety, Jean

2017-07-01

Morality is an evolved aspect of human nature, yet is heavily influenced by cultural environment. This developmental study adopted an integrative approach by combining measures of socioeconomic status (SES), executive function, affective sharing, empathic concern, theory of mind, and moral judgment in predicting sharing behavior in children (N = 999) from the age of 5 to 12 in five large-scale societies: Canada, China, Turkey, South Africa, and the USA. Results demonstrate that age, gender, SES, culture, and social cognitive mechanisms explain over 20% of the variance worldwide in children's resource allocation. These findings are discussed in reference to standard cultural comparisons (individualist/collectivist), as well as the degree of market integration, and highlight continuities and discontinuities in children's generosity across urban contexts. © 2016 John Wiley & Sons Ltd.

Exploring links among imitation, mental development, and temperament

PubMed Central

Fenstermacher, Susan K.; Saudino, Kimberly J.

2016-01-01

Links among imitation, performance on a standardized test of intellectual development, and laboratory-assessed temperament were explored in 311 24-month old twin pairs. Moderate phenotypic associations were found between imitation, mental development, and temperament dimensions of Affect/Extraversion and Task Orientation. Covariance between imitation and mental development reflected genetic and shared environmental influences, whereas associations between imitation and temperament reflected genetic, shared, and nonshared environmental influences. Genetic factors linking imitation and temperament were the same as those linking temperament and mental development. Nonetheless, approximately 62% of total genetic variance on imitation was independent of genetic influences on mental development and temperament, suggesting that young children’s imitation is not simply an index of general cognitive ability or dispositional style but has many underlying genetic influences that are unique. PMID:27840593

Exploring links among imitation, mental development, and temperament.

PubMed

Fenstermacher, Susan K; Saudino, Kimberly J

2016-01-01

Links among imitation, performance on a standardized test of intellectual development, and laboratory-assessed temperament were explored in 311 24-month old twin pairs. Moderate phenotypic associations were found between imitation, mental development, and temperament dimensions of Affect/Extraversion and Task Orientation. Covariance between imitation and mental development reflected genetic and shared environmental influences, whereas associations between imitation and temperament reflected genetic, shared, and nonshared environmental influences. Genetic factors linking imitation and temperament were the same as those linking temperament and mental development. Nonetheless, approximately 62% of total genetic variance on imitation was independent of genetic influences on mental development and temperament, suggesting that young children's imitation is not simply an index of general cognitive ability or dispositional style but has many underlying genetic influences that are unique.

Combat exposure severity as a moderator of genetic and environmental liability to post-traumatic stress disorder.

PubMed

Wolf, E J; Mitchell, K S; Koenen, K C; Miller, M W

2014-05-01

Twin studies of veterans and adults suggest that approximately 30-46% of the variance in post-traumatic stress disorder (PTSD) is attributable to genetic factors. The remaining variance is attributable to the non-shared environment, which, by definition, includes combat exposure. This study used a gene by measured environment twin design to determine whether the effects of genetic and environmental factors that contribute to the etiology of PTSD are dependent on the level of combat exposure. The sample was drawn from the Vietnam Era Twin Registry (VETR) and included 620 male-male twin pairs who served in the US Military in South East Asia during the Vietnam War era. Analyses were based on data from a clinical diagnostic interview of lifetime PTSD symptoms and a self-report measure of combat exposure. Biometric modeling revealed that the effects of genetic and non-shared environment factors on PTSD varied as a function of level of combat exposure such that the association between these factors and PTSD was stronger at higher levels of combat exposure. Combat exposure may act as a catalyst that augments the impact of hereditary and environmental contributions to PTSD. Individuals with the greatest exposure to combat trauma were at increased risk for PTSD as a function of both genetic and environmental factors. Additional work is needed to determine the biological and environmental mechanisms driving these associations.

Comorbidity of Alcohol and Gambling Problems in Emerging Adults: A Bifactor Model Conceptualization.

PubMed

Tackett, Jennifer L; Krieger, Heather; Neighbors, Clayton; Rinker, Dipali; Rodriguez, Lindsey; Edward, Gottheil

2017-03-01

Addictive disorders, such as pathological gambling and alcohol use disorders, frequently co-occur at greater than chance levels. Substantive questions stem from this comorbidity regarding the extent to which shared variance between gambling and alcohol use reflects a psychological core of addictive tendencies, and whether this differs as a function of gender. The aims of this study were to differentiate both common and unique variance in alcohol and gambling problems in a bifactor model, examine measurement invariance of this model by gender, and identify substantive correlates of the final bifactor model. Undergraduates (N = 4475) from a large northwestern university completed an online screening questionnaire which included demographics, quantity of money lost and won when gambling, the South Oaks Gambling Screen, the AUDIT, gambling motives, drinking motives, personality, and the Brief Symptom Inventory. Results suggest that the bifactor model fit the data well in the full sample. Although the data suggest configural invariance across gender, factor loadings could not be constrained to be equal between men and women. As such, general and specific factors were examined separately by gender with a more intensive subsample of females and males (n = 264). Correlations with motivational tendencies, personality traits, and mental health symptoms indicated support for the validity of the bifactor model, as well as gender-specific patterns of association. Results suggest informative distinctions between shared and unique attributes related to problematic drinking and gambling.

Shared Genetics of Temporomandibular Disorder Pain and Neck Pain: Results of a Twin Study.

PubMed

Visscher, Corine M; Schouten, Maarten J; Ligthart, Lannie; van Houtem, Caroline Mhh; de Jongh, Ad; Boomsma, Dorret I

2018-03-06

(1) To examine the heritability of TMD pain and of neck pain; and (2) to estimate the potential overlap in genetic and environmental factors influencing TMD pain and neck pain. Data from 2,238 adult female twins who completed a survey on TMD pain and neck pain were analyzed. The total variance of TMD pain and neck pain was decomposed into variance attributable to additive genetic effects and nonshared environmental effects. Bivariate structural equation modeling was applied to estimate trait-specific and genetic effects shared between traits. The prevalence of TMD pain and neck pain was 8.6% and 46.8%, respectively, while 6.7% of the twins reported both TMD pain and neck pain. The phenotypic correlation between TMD pain and neck pain, based on a liability threshold model, was 0.43 (95% confidence interval [CI] 0.34 to 0.51). The heritability for TMD was 0.35 (0.17 to 0.51), and for neck pain was 0.33 (0.23 to 0.43). The genetic correlation between TMD pain and neck pain was 0.64 (0.35 to 1.00), and the environmental correlation was 0.32 (0.14 to 0.48). This study shows that variation in TMD pain and neck pain can in part be attributed to genes. The comorbidity between them is partly explained by genes that influence both traits and partly by the same environmental factors.

Comorbidity of Alcohol and Gambling Problems in Emerging Adults: A Bifactor Model Conceptualization

PubMed Central

Krieger, Heather; Neighbors, Clayton; Rinker, Dipali; Rodriguez, Lindsey; Edward, Gottheil

2017-01-01

Addictive disorders, such as pathological gambling and alcohol use disorders, frequently co-occur at greater than chance levels. Substantive questions stem from this comorbidity regarding the extent to which shared variance between gambling and alcohol use reflects a psychological core of addictive tendencies, and whether this differs as a function of gender. The aims of this study were to differentiate both common and unique variance in alcohol and gambling problems in a bifactor model, examine measurement invariance of this model by gender, and identify substantive correlates of the final bifactor model. Undergraduates (N = 4475) from a large northwestern university completed an online screening questionnaire which included demographics, quantity of money lost and won when gambling, the South Oaks Gambling Screen, the AUDIT, gambling motives, drinking motives, personality, and the Brief Symptom Inventory. Results suggest that the bifactor model fit the data well in the full sample. Although the data suggest configural invariance across gender, factor loadings could not be constrained to be equal between men and women. As such, general and specific factors were examined separately by gender with a more intensive subsample of females and males (n = 264). Correlations with motivational tendencies, personality traits, and mental health symptoms indicated support for the validity of the bifactor model, as well as gender-specific patterns of association. Results suggest informative distinctions between shared and unique attributes related to problematic drinking and gambling. PMID:27260007

Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

NASA Astrophysics Data System (ADS)

Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

2015-10-01

The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning.

PubMed

Adlof, Suzanne M; Patten, Hannah

2017-03-01

This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Fifty children, with a mean age of 8 years (range 5-12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed.

Global-scale modes of surface temperature variability on interannual to century timescales

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1994-01-01

Using 100 years of global temperature anomaly data, we have performed a singluar value decomposition of temperature variations in narrow frequency bands to isolate coherent spatio-temporal modes of global climate variability. Statistical significance is determined from confidence limits obtained by Monte Carlo simulations. Secular variance is dominated by a globally coherent trend; with nearly all grid points warming in phase at varying amplitude. A smaller, but significant, share of the secular variance corresponds to a pattern dominated by warming and subsequent cooling in the high latitude North Atlantic with a roughly centennial timescale. Spatial patterns associated with significant peaks in variance within a broad period range from 2.8 to 5.7 years exhibit characteristic El Nino-Southern Oscillation (ENSO) patterns. A recent transition to a regime of higher ENSO frequency is suggested by our analysis. An interdecadal mode in the 15-to-18 years period and a mode centered at 7-to-8 years period both exhibit predominantly a North Atlantic Oscillation (NAO) temperature pattern. A potentially significant decadal mode centered on 11-to-12 years period also exhibits an NAO temperature pattern and may be modulated by the century-scale North Atlantic variability.

Predictability Experiments With the Navy Operational Global Atmospheric Prediction System

NASA Astrophysics Data System (ADS)

Reynolds, C. A.; Gelaro, R.; Rosmond, T. E.

2003-12-01

There are several areas of research in numerical weather prediction and atmospheric predictability, such as targeted observations and ensemble perturbation generation, where it is desirable to combine information about the uncertainty of the initial state with information about potential rapid perturbation growth. Singular vectors (SVs) provide a framework to accomplish this task in a mathematically rigorous and computationally feasible manner. In this study, SVs are calculated using the tangent and adjoint models of the Navy Operational Global Atmospheric Prediction System (NOGAPS). The analysis error variance information produced by the NRL Atmospheric Variational Data Assimilation System is used as the initial-time SV norm. These VAR SVs are compared to SVs for which total energy is both the initial and final time norms (TE SVs). The incorporation of analysis error variance information has a significant impact on the structure and location of the SVs. This in turn has a significant impact on targeted observing applications. The utility and implications of such experiments in assessing the analysis error variance estimates will be explored. Computing support has been provided by the Department of Defense High Performance Computing Center at the Naval Oceanographic Office Major Shared Resource Center at Stennis, Mississippi.

Common Genetic Influences on Negative Emotionality and a General Psychopathology Factor in Childhood and Adolescence

PubMed Central

Tackett, Jennifer L.; Lahey, Benjamin B.; Hulle, Carol Van; Waldman, Irwin; Krueger, Robert F.; Rathouz, Paul J.

2014-01-01

Previous research using confirmatory factor analysis to model psychopathology comorbidity supported the hypothesis of a broad general factor (i.e., a “bifactor”; Holzinger & Swineford, 1937) of psychopathology in children, adolescents, and adults, with more specific higher-order internalizing and externalizing factors reflecting additional shared variance in symptoms (Lahey et al., 2012; Lahey, Van Hulle, Singh, Waldman, & Rathouz, 2011). The psychological nature of this general factor has not been explored, however. The current study tests a prediction derived from the spectrum hypothesis of personality and psychopathology, that variance in a general psychopathology bifactor overlaps substantially—at both phenotypic and genetic levels—with the dispositional trait of negative emotionality. Data on psychopathology symptoms and dispositional traits were collected from both parents and youth in a representative sample of 1,569 twin pairs (ages 9–17) from Tennessee. Predictions based on the spectrum hypothesis were supported, with variance in negative emotionality and the general factor overlapping substantially at both phenotypic and etiologic levels. Furthermore, stronger correlations were found between negative emotionality and the general psychopathology factor than among other dispositions and other psychopathology factors. PMID:24364617

Common genetic influences on negative emotionality and a general psychopathology factor in childhood and adolescence.

PubMed

Tackett, Jennifer L; Lahey, Benjamin B; van Hulle, Carol; Waldman, Irwin; Krueger, Robert F; Rathouz, Paul J

2013-11-01

Previous research using confirmatory factor analysis to model psychopathology comorbidity has supported the hypothesis of a broad general factor (i.e., a "bifactor"; Holzinger & Swineford, 1937) of psychopathology in children, adolescents, and adults, with more specific higher order internalizing and externalizing factors reflecting additional shared variance in symptoms (Lahey et al., 2012; Lahey, van Hulle, Singh, Waldman, & Rathouz, 2011). The psychological nature of this general factor has not been explored, however. The current study tested a prediction, derived from the spectrum hypothesis of personality and psychopathology, that variance in a general psychopathology bifactor overlaps substantially-at both phenotypic and genetic levels-with the dispositional trait of negative emotionality. Data on psychopathology symptoms and dispositional traits were collected from both parents and youth in a representative sample of 1,569 twin pairs (ages 9-17 years) from Tennessee. Predictions based on the spectrum hypothesis were supported, with variance in negative emotionality and the general factor overlapping substantially at both phenotypic and etiologic levels. Furthermore, stronger correlations were found between negative emotionality and the general psychopathology factor than among other dispositions and other psychopathology factors. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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.

[Analysis of variance of repeated data measured by water maze with SPSS].

PubMed

Qiu, Hong; Jin, Guo-qin; Jin, Ru-feng; Zhao, Wei-kang

2007-01-01

To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P

An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

ERIC Educational Resources Information Center

Attali, Yigal

2010-01-01

Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

Procedures for estimating confidence intervals for selected method performance parameters.

PubMed

McClure, F D; Lee, J K

2001-01-01

Procedures for estimating confidence intervals (CIs) for the repeatability variance (sigmar2), reproducibility variance (sigmaR2 = sigmaL2 + sigmar2), laboratory component (sigmaL2), and their corresponding standard deviations sigmar, sigmaR, and sigmaL, respectively, are presented. In addition, CIs for the ratio of the repeatability component to the reproducibility variance (sigmar2/sigmaR2) and the ratio of the laboratory component to the reproducibility variance (sigmaL2/sigmaR2) are also presented.

Social information processing in children: specific relations to anxiety, depression, and affect.

PubMed

Luebbe, Aaron M; Bell, Debora J; Allwood, Maureen A; Swenson, Lance P; Early, Martha C

2010-01-01

Two studies examined shared and unique relations of social information processing (SIP) to youth's anxious and depressive symptoms. Whether SIP added unique variance over and above trait affect in predicting internalizing symptoms was also examined. In Study 1, 215 youth (ages 8-13) completed symptom measures of anxiety and depression and a vignette-based interview measure of SIP. Anxiety and depression were each related to a more negative information-processing style. Only depression was uniquely related to a less positive information processing style. In Study 2, 127 youth (ages 10-13) completed measures of anxiety, depression, SIP, and trait affect. SIP's relations to internalizing symptoms were replicated. Over and above negative affect, negative SIP predicted both anxiety and depression. Low positive SIP added variance over and above positive affect in predicting only depression. Finally, SIP functioning partially mediated the relations of affect to internalizing symptoms.

Differences between multimedia and text-based assessments of emotion management: An exploration with the multimedia emotion management assessment (MEMA).

PubMed

MacCann, Carolyn; Lievens, Filip; Libbrecht, Nele; Roberts, Richard D

2016-11-01

People process emotional information using visual, vocal, and verbal cues. However, emotion management is typically assessed with text based rather than multimedia stimuli. This study (N = 427) presents the new multimedia emotion management assessment (MEMA) and compares it to the text-based assessment of emotion management used in the MSCEIT. The text-based and multimedia assessment showed similar levels of cognitive saturation and similar prediction of relevant criteria. Results demonstrate that the MEMA scores have equivalent evidence of validity to the text-based MSCEIT test scores, demonstrating that multimedia assessment of emotion management is viable. Furthermore, our results inform the debate as to whether cognitive saturation in emotional intelligence (EI) measures represents "noise" or "substance". We find that cognitive ability associations with EI represent substantive variance rather than construct-irrelevant shared variance due to reading comprehension ability required for text-based items.

Exploring individual differences in children's mathematical skills: a correlational and dimensional approach.

PubMed

Sigmundsson, H; Polman, R C J; Lorås, H

2013-08-01

Individual differences in mathematical skills are typically explained by an innate capability to solve mathematical tasks. At the behavioural level this implies a consistent level of mathematical achievement that can be captured by strong relationships between tasks, as well as by a single statistical dimension that underlies performance on all mathematical tasks. To investigate this general assumption, the present study explored interrelations and dimensions of mathematical skills. For this purpose, 68 ten-year-old children from two schools were tested using nine mathematics tasks from the Basic Knowledge in Mathematics Test. Relatively low-to-moderate correlations between the mathematics tasks indicated most tasks shared less than 25% of their variance. There were four principal components, accounting for 70% of the variance in mathematical skill across tasks and participants. The high specificity in mathematical skills was discussed in relation to the principle of task specificity of learning.

Sampling in freshwater environments: suspended particle traps and variability in the final data.

PubMed

Barbizzi, Sabrina; Pati, Alessandra

2008-11-01

This paper reports one practical method to estimate the measurement uncertainty including sampling, derived by the approach implemented by Ramsey for soil investigations. The methodology has been applied to estimate the measurements uncertainty (sampling and analyses) of (137)Cs activity concentration (Bq kg(-1)) and total carbon content (%) in suspended particle sampling in a freshwater ecosystem. Uncertainty estimates for between locations, sampling and analysis components have been evaluated. For the considered measurands, the relative expanded measurement uncertainties are 12.3% for (137)Cs and 4.5% for total carbon. For (137)Cs, the measurement (sampling+analysis) variance gives the major contribution to the total variance, while for total carbon the spatial variance is the dominant contributor to the total variance. The limitations and advantages of this basic method are discussed.

Comparison of amplitude-decorrelation, speckle-variance and phase-variance OCT angiography methods for imaging the human retina and choroid

PubMed Central

Gorczynska, Iwona; Migacz, Justin V.; Zawadzki, Robert J.; Capps, Arlie G.; Werner, John S.

2016-01-01

We compared the performance of three OCT angiography (OCTA) methods: speckle variance, amplitude decorrelation and phase variance for imaging of the human retina and choroid. Two averaging methods, split spectrum and volume averaging, were compared to assess the quality of the OCTA vascular images. All data were acquired using a swept-source OCT system at 1040 nm central wavelength, operating at 100,000 A-scans/s. We performed a quantitative comparison using a contrast-to-noise (CNR) metric to assess the capability of the three methods to visualize the choriocapillaris layer. For evaluation of the static tissue noise suppression in OCTA images we proposed to calculate CNR between the photoreceptor/RPE complex and the choriocapillaris layer. Finally, we demonstrated that implementation of intensity-based OCT imaging and OCT angiography methods allows for visualization of retinal and choroidal vascular layers known from anatomic studies in retinal preparations. OCT projection imaging of data flattened to selected retinal layers was implemented to visualize retinal and choroidal vasculature. User guided vessel tracing was applied to segment the retinal vasculature. The results were visualized in a form of a skeletonized 3D model. PMID:27231598

iTemplate: A template-based eye movement data analysis approach.

PubMed

Xiao, Naiqi G; Lee, Kang

2018-02-08

Current eye movement data analysis methods rely on defining areas of interest (AOIs). Due to the fact that AOIs are created and modified manually, variances in their size, shape, and location are unavoidable. These variances affect not only the consistency of the AOI definitions, but also the validity of the eye movement analyses based on the AOIs. To reduce the variances in AOI creation and modification and achieve a procedure to process eye movement data with high precision and efficiency, we propose a template-based eye movement data analysis method. Using a linear transformation algorithm, this method registers the eye movement data from each individual stimulus to a template. Thus, users only need to create one set of AOIs for the template in order to analyze eye movement data, rather than creating a unique set of AOIs for all individual stimuli. This change greatly reduces the error caused by the variance from manually created AOIs and boosts the efficiency of the data analysis. Furthermore, this method can help researchers prepare eye movement data for some advanced analysis approaches, such as iMap. We have developed software (iTemplate) with a graphic user interface to make this analysis method available to researchers.

Imaging and characterizing shear wave and shear modulus under orthogonal acoustic radiation force excitation using OCT Doppler variance method.

PubMed

Zhu, Jiang; Qu, Yueqiao; Ma, Teng; Li, Rui; Du, Yongzhao; Huang, Shenghai; Shung, K Kirk; Zhou, Qifa; Chen, Zhongping

2015-05-01

We report on a novel acoustic radiation force orthogonal excitation optical coherence elastography (ARFOE-OCE) technique for imaging shear wave and quantifying shear modulus under orthogonal acoustic radiation force (ARF) excitation using the optical coherence tomography (OCT) Doppler variance method. The ARF perpendicular to the OCT beam is produced by a remote ultrasonic transducer. A shear wave induced by ARF excitation propagates parallel to the OCT beam. The OCT Doppler variance method, which is sensitive to the transverse vibration, is used to measure the ARF-induced vibration. For analysis of the shear modulus, the Doppler variance method is utilized to visualize shear wave propagation instead of Doppler OCT method, and the propagation velocity of the shear wave is measured at different depths of one location with the M scan. In order to quantify shear modulus beyond the OCT imaging depth, we move ARF to a deeper layer at a known step and measure the time delay of the shear wave propagating to the same OCT imaging depth. We also quantitatively map the shear modulus of a cross-section in a tissue-equivalent phantom after employing the B scan.

Investigating the genetic and environmental bases of biases in threat recognition and avoidance in children with anxiety problems

PubMed Central

2012-01-01

Background Adults with anxiety show biased categorization and avoidance of threats. Such biases may emerge through complex interplay between genetics and environments, occurring early in life. Research on threat biases in children has focuses on a restricted range of biases, with insufficient focus on genetic and environmental origins. Here, we explore differences between children with and without anxiety problems in under-studied areas of threat bias. We focused both on associations with anxious phenotype and the underlying gene-environmental correlates for two specific processes: the categorisation of threat faces and avoidance learning. Method Two-hundred and fifty 10-year old MZ and DZ twin pairs (500 individuals) completed tasks assessing accuracy in the labelling of threatening facial expressions and in the acquisition of avoidant responses to a card associated with a masked threatening face. To assess whether participants met criteria for an anxiety disorder, parents of twins completed a self-guided computerized version of the Development and Well-being Assessment (DAWBA). Comparison of MZ and DZ twin correlations using model-fitting were used to compute estimates of genetic, shared and non-shared environmental effects. Results Of the 500 twins assessed, 25 (5%) met diagnostic criteria for a current anxiety disorder. Children with anxiety disorders were more accurate in their ability to recognize disgust faces than those without anxiety disorders, but were commensurate on identifying other threatening face emotions (angry, fearful, sad). Children with anxiety disorders but also more strongly avoided selecting a conditioned stimulus than non-anxious children. While recognition of socially threatening faces was moderately heritable, avoidant responses were heavily influenced by the non-shared environment. Conclusion These data add to other findings on threat biases in anxious children. Specifically, we found biases in the labelling of some negative-valence faces and in the acquisition of avoidant responses. While non-shared environmental effects explained all of the variance on threat avoidance, some of this may be due to measurement error. PMID:22788754

Means and Variances without Calculus

ERIC Educational Resources Information Center

Kinney, John J.

2005-01-01

This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

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.

Cross-frequency and band-averaged response variance prediction in the hybrid deterministic-statistical energy analysis method

NASA Astrophysics Data System (ADS)

Reynders, Edwin P. B.; Langley, Robin S.

2018-08-01

The hybrid deterministic-statistical energy analysis method has proven to be a versatile framework for modeling built-up vibro-acoustic systems. The stiff system components are modeled deterministically, e.g., using the finite element method, while the wave fields in the flexible components are modeled as diffuse. In the present paper, the hybrid method is extended such that not only the ensemble mean and variance of the harmonic system response can be computed, but also of the band-averaged system response. This variance represents the uncertainty that is due to the assumption of a diffuse field in the flexible components of the hybrid system. The developments start with a cross-frequency generalization of the reciprocity relationship between the total energy in a diffuse field and the cross spectrum of the blocked reverberant loading at the boundaries of that field. By making extensive use of this generalization in a first-order perturbation analysis, explicit expressions are derived for the cross-frequency and band-averaged variance of the vibrational energies in the diffuse components and for the cross-frequency and band-averaged variance of the cross spectrum of the vibro-acoustic field response of the deterministic components. These expressions are extensively validated against detailed Monte Carlo analyses of coupled plate systems in which diffuse fields are simulated by randomly distributing small point masses across the flexible components, and good agreement is found.

A simple and exploratory way to determine the mean-variance relationship in generalized linear models.

PubMed

Tsou, Tsung-Shan

2007-03-30

This paper introduces an exploratory way to determine how variance relates to the mean in generalized linear models. This novel method employs the robust likelihood technique introduced by Royall and Tsou.A urinary data set collected by Ginsberg et al. and the fabric data set analysed by Lee and Nelder are considered to demonstrate the applicability and simplicity of the proposed technique. Application of the proposed method could easily reveal a mean-variance relationship that would generally be left unnoticed, or that would require more complex modelling to detect. Copyright (c) 2006 John Wiley & Sons, Ltd.

The Choice Project: Peer Workers Promoting Shared Decision Making at a Youth Mental Health Service.

PubMed

Simmons, Magenta Bender; Batchelor, Samantha; Dimopoulos-Bick, Tara; Howe, Deb

2017-08-01

In youth mental health services, consumer participation is essential, but few implementation strategies exist to engage young consumers. This project evaluated an intervention implemented in an Australian youth mental health service that utilized peer workers to promote shared decision making via an online tool. All new clients ages 16-25 were invited to participate in this nonrandomized comparative study, which used a historical comparison group (N=80). Intervention participants (N=149) engaged with a peer worker and used the online tool before and during their intake assessment. Pre- and postintake data were collected for both groups; measures included decisional conflict, perceived shared decision making, and satisfaction. A series of paired t tests, analyses of variance, and multiple regressions were conducted to assess differences in scores across intervention and comparison groups and pre- and postintake assessments. Ratings of perceived shared decision making with intake workers were higher in the intervention group than in the comparison group (p=.015). In both groups, decisional conflict scores were significantly lower after the intake assessment (p<.001 for both groups). Both perceived shared decision making and lower decisional conflict were associated with satisfaction (p<.015). Young people who participated in an intervention that combined peer work and shared decision making reported feeling more involved in their assessment. Feeling involved and having lower decisional conflict after seeing an intake worker were important for client satisfaction. These findings demonstrate the importance of both peer work and shared decision making for promoting optimal outcomes in youth mental health services.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed.

El-Niño/Southern Oscillation (ENSO) influences on monthly NO 3 load and concentration, stream flow and precipitation in the Little River Watershed, Tifton, Georgia (GA)

NASA Astrophysics Data System (ADS)

Keener, V. W.; Feyereisen, G. W.; Lall, U.; Jones, J. W.; Bosch, D. D.; Lowrance, R.

2010-02-01

SummaryAs climate variability increases, it is becoming increasingly critical to find predictable patterns that can still be identified despite overall uncertainty. The El-Niño/Southern Oscillation is the best known pattern. Its global effects on weather, hydrology, ecology and human health have been well documented. Climate variability manifested through ENSO has strong effects in the southeast United States, seen in precipitation and stream flow data. However, climate variability may also affect water quality in nutrient concentrations and loads, and have impacts on ecosystems, health, and food availability in the southeast. In this research, we establish a teleconnection between ENSO and the Little River Watershed (LRW), GA., as seen in a shared 3-7 year mode of variability for precipitation, stream flow, and nutrient load time series. Univariate wavelet analysis of the NINO 3.4 index of sea surface temperature (SST) and of precipitation, stream flow, NO 3 concentration and load time series from the watershed was used to identify common signals. Shared 3-7 year modes of variability were seen in all variables, most strongly in precipitation, stream flow and nutrient load in strong El Niño years. The significance of shared 3-7 year periodicity over red noise with 95% confidence in SST and precipitation, stream flow, and NO 3 load time series was confirmed through cross-wavelet and wavelet-coherence transforms, in which common high power and co-variance were computed for each set of data. The strongest 3-7 year shared power was seen in SST and stream flow data, while the strongest co-variance was seen in SST and NO 3 load data. The strongest cross-correlation was seen as a positive value between the NINO 3.4 and NO 3 load with a three-month lag. The teleconnection seen in the LRW between the NINO 3.4 index and precipitation, stream flow, and NO 3 load can be utilized in a model to predict monthly nutrient loads based on short-term climate variability, facilitating management in high risk seasons.

Heritability of somatotype components: a multivariate analysis.

PubMed

Peeters, M W; Thomis, M A; Loos, R J F; Derom, C A; Fagard, R; Claessens, A L; Vlietinck, R F; Beunen, G P

2007-08-01

To study the genetic and environmental determination of variation in Heath-Carter somatotype (ST) components (endomorphy, mesomorphy and ectomorphy). Multivariate path analysis on twin data. Eight hundred and three members of 424 adult Flemish twin pairs (18-34 years of age). The results indicate the significance of sex differences and the significance of the covariation between the three ST components. After age-regression, variation of the population in ST components and their covariation is explained by additive genetic sources of variance (A), shared (familial) environment (C) and unique environment (E). In men, additive genetic sources of variance explain 28.0% (CI 8.7-50.8%), 86.3% (71.6-90.2%) and 66.5% (37.4-85.1%) for endomorphy, mesomorphy and ectomorphy, respectively. For women, corresponding values are 32.3% (8.9-55.6%), 82.0% (67.7-87.7%) and 70.1% (48.9-81.8%). For all components in men and women, more than 70% of the total variation was explained by sources of variance shared between the three components, emphasising the importance of analysing the ST in a multivariate way. The findings suggest that the high heritabilities for mesomorphy and ectomorphy reported in earlier twin studies in adolescence are maintained in adulthood. For endomorphy, which represents a relative measure of subcutaneous adipose tissue, however, the results suggest heritability may be considerably lower than most values reported in earlier studies on adolescent twins. The heritability is also lower than values reported for, for example, body mass index (BMI), which next to the weight of organs and adipose tissue also includes muscle and bone tissue. Considering the differences in heritability between musculoskeletal robustness (mesomorphy) and subcutaneous adipose tissue (endomorphy) it may be questioned whether studying the genetics of BMI will eventually lead to a better understanding of the genetics of fatness, obesity and overweight.

Faculty and resident evaluations of medical students on a surgery clerkship correlate poorly with standardized exam scores.

PubMed

Goldstein, Seth D; Lindeman, Brenessa; Colbert-Getz, Jorie; Arbella, Trisha; Dudas, Robert; Lidor, Anne; Sacks, Bethany

2014-02-01

The clinical knowledge of medical students on a surgery clerkship is routinely assessed via subjective evaluations from faculty members and residents. Interpretation of these ratings should ideally be valid and reliable. However, prior literature has questioned the correlation between subjective and objective components when assessing students' clinical knowledge. Retrospective cross-sectional data were collected from medical student records at The Johns Hopkins University School of Medicine from July 2009 through June 2011. Surgical faculty members and residents rated students' clinical knowledge on a 5-point, Likert-type scale. Interrater reliability was assessed using intraclass correlation coefficients for students with ≥4 attending surgeon evaluations (n = 216) and ≥4 resident evaluations (n = 207). Convergent validity was assessed by correlating average evaluation ratings with scores on the National Board of Medical Examiners (NBME) clinical subject examination for surgery. Average resident and attending surgeon ratings were also compared by NBME quartile using analysis of variance. There were high degrees of reliability for resident ratings (intraclass correlation coefficient, .81) and attending surgeon ratings (intraclass correlation coefficient, .76). Resident and attending surgeon ratings shared a moderate degree of variance (19%). However, average resident ratings and average attending surgeon ratings shared a small degree of variance with NBME surgery examination scores (ρ(2) ≤ .09). When ratings were compared among NBME quartile groups, the only significant difference was for residents' ratings of students with the lower 25th percentile of scores compared with the top 25th percentile of scores (P = .007). Although high interrater reliability suggests that attending surgeons and residents rate students with consistency, the lack of convergent validity suggests that these ratings may not be reflective of actual clinical knowledge. Both faculty members and residents may benefit from training in knowledge assessment, which will likely increase opportunities to recognize deficiencies and make student evaluation a more valuable tool. Copyright © 2014 Elsevier Inc. All rights reserved.

Familial Aggregation and Heritability of Schizophrenia and Co-aggregation of Psychiatric Illnesses in Affected Families.

PubMed

Chou, I-Jun; Kuo, Chang-Fu; Huang, Yu-Shu; Grainge, Matthew J; Valdes, Ana M; See, Lai-Chu; Yu, Kuang-Hui; Luo, Shue-Fen; Huang, Lu-Shuang; Tseng, Wen-Yi; Zhang, Weiya; Doherty, Michael

2017-09-01

Strong familial aggregation of schizophrenia has been reported but there is uncertainty concerning the degree of genetic contribution to the phenotypic variance of the disease. This study aimed to examine the familial aggregation and heritability of schizophrenia, and the relative risks (RRs) of other psychiatric diseases, in relatives of people with schizophrenia using the Taiwan National Health Insurance Database. The study population included individuals with affected first-degree or second-degree relatives identified from all beneficiaries (n = 23 422 955) registered in 2013. Diagnoses of schizophrenia made by psychiatrists were ascertained between January 1, 1996 and December 31, 2013. Having an affected co-twin, first-degree relative, second-degree relative, or spouse was associated with an adjusted RR (95% CI) of 37.86 (30.55-46.92), 6.30 (6.09-6.53), 2.44 (1.91-3.12), and 1.88 (1.64-2.15), respectively. Compared with the general population, individuals with one affected first-degree relative had a RR (95% CI) of 6.00 (5.79-6.22) and those with 2 or more had a RR (95% CI) of 14.66 (13.00-16.53) for schizophrenia. The accountability for the phenotypic variance of schizophrenia was 47.3% for genetic factors, 15.5% for shared environmental factors, and 37.2% for non-shared environmental factors. The RR (95% CI) in individuals with a first-degree relative with schizophrenia was 3.49 (3.34-3.64) for mood disorders and 3.91 (3.35-4.57) for delusional disorders. A family history of schizophrenia is therefore associated with a higher risk of developing schizophrenia, mood disorders, and delusional disorders. Heritability and environmental factors each account for half of the phenotypic variance of schizophrenia. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Gene variants associated with antisocial behaviour: A latent variable approach

PubMed Central

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

2013-01-01

Objective The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation program in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours, and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Results Eight single-nucleotide polymorphisms (SNPs) from 8 genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all 8 genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid, and cholinergic signaling as well as stress response pathways in mediating susceptibility to antisocial behaviour. Conclusions This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential “co-action” of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the etiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a ‘shared’ variance across genetic risk alleles associated with complex neuropsychiatric dimensional phenotypes using relatively small numbers of well-characterized research participants. PMID:23822756

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

Heuristics for Understanding the Concepts of Interaction, Polynomial Trend, and the General Linear Model.

ERIC Educational Resources Information Center

Thompson, Bruce

The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…

Benefits of Using Planned Comparisons Rather Than Post Hoc Tests: A Brief Review with Examples.

ERIC Educational Resources Information Center

DuRapau, Theresa M.

The rationale behind analysis of variance (including analysis of covariance and multiple analyses of variance and covariance) methods is reviewed, and unplanned and planned methods of evaluating differences between means are briefly described. Two advantages of using planned or a priori tests over unplanned or post hoc tests are presented. In…

Economic Pressure and Marital Quality: An Illustration of the Method Variance Problem in the Causal Modeling of Family Processes.

ERIC Educational Resources Information Center

Lorenz, Frederick O.; And Others

1991-01-01

Examined effects of method variance on models linking family economic pressure, marital quality, and expressions of hostility and warmth among 76 couples. Observer reports yielded results linking economic pressure to marital quality indirectly through interactional processes such as hostility. Self-reports or spouses' reports made it difficult to…

Research on the Characteristics of Alzheimer's Disease Using EEG

NASA Astrophysics Data System (ADS)

Ueda, Taishi; Musha, Toshimitsu; Yagi, Tohru

In this paper, we proposed a new method for diagnosing Alzheimer's disease (AD) on the basis of electroencephalograms (EEG). The method, which is termed Power Variance Function (PVF) method, indicates the variance of the power at each frequency. By using the proposed method, the power of EEG at each frequency was calculated using Wavelet transform, and the corresponding variances were defined as PVF. After the PVF histogram of 55 healthy people was approximated as a Generalized Extreme Value (GEV) distribution, we evaluated the PVF of 22 patients with AD and 25 patients with mild cognitive impairment (MCI). As a result, the values for all AD and MCI subjects were abnormal. In particular, the PVF in the θ band for MCI patients was abnormally high, and the PVF in the α band for AD patients was low.

Using simulation to assess the influence of race and insurer on shared decision making in periviable counseling.

PubMed

Tucker Edmonds, Brownsyne; McKenzie, Fatima; Fadel, William F; Matthias, Marianne S; Salyers, Michelle P; Barnato, Amber E; Frankel, Richard M

2014-12-01

Sociodemographic differences have been observed in the treatment of extremely premature (periviable) neonates, but the source of this variation is not well understood. We assessed the feasibility of using simulation to test the effect of maternal race and insurance status on shared decision making (SDM) in periviable counseling. We conducted a 2 × 2 factorial simulation experiment in which obstetricians and neonatologists counseled 2 consecutive standardized patients diagnosed with ruptured membranes at 23 weeks, counterbalancing race (black/white) and insurance status using random permutation. We assessed verisimilitude of the simulation in semistructured debriefing interviews. We coded physician communication related to resuscitation, mode of delivery, and steroid decisions using a 9-point SDM coding framework and then compared communication scores by standardized patient race and insurer using analysis of variance. Sixteen obstetricians and 15 neonatologists participated; 71% were women, 84% were married, and 75% were parents; 91% of the physicians rated the simulation as highly realistic. Overall, SDM scores were relatively high, with means ranging from 6.4 to 7.9 (of 9). There was a statistically significant interaction between race and insurer for SDM related to steroid use and mode of delivery (P < 0.01 and P = 0.01, respectively). Between-group comparison revealed nonsignificant differences (P = <0.10) between the SDM scores for privately insured black patients versus privately insured white patients, Medicaid-insured white patients versus Medicaid-insured black patients, and privately insured black patients versus Medicaid-insured black patients. This study confirms that simulation is a feasible method for studying sociodemographic effects on periviable counseling. Shared decision making may occur differentially based on patients' sociodemographic characteristics and deserves further study.

g in Middle Childhood: Moderate Genetic and Shared Environmental Influence Using Diverse Measures of General Cognitive Ability at 7, 9 and 10 Years in a Large Population Sample of Twins

ERIC Educational Resources Information Center

Davis, Oliver S. P.; Arden, Rosalind; Plomin, Robert

2008-01-01

A 2003 paper in this journal reported results from a large sample of twins assessed at 2, 3 and 4 years of age on parent-administered tests and reports of their verbal and nonverbal ability. We found clear evidence for phenotypic general cognitive ability (g) that accounted for about 50% of the variance, for modest genetic influence on g (about…

Development and psychometric testing of a scale assessing the sharing of medical information and interprofessional communication: the CSI scale

PubMed Central

2014-01-01

Background Interprofessional collaboration is essential in creating a safer patient environment. It includes the need to develop communication and coordination between professionals, implying a better sharing of medical information. Several questionnaires exist in the literature, but none of them have been developed in the French context. The objective was to develop and test the psychometric properties of the communication and sharing information (CSI) scale which assesses specifically interprofessional communication, especially the sharing of medical information and the effectiveness of communication between members of the team. Methods The questionnaire construction process used a literature review and involved a panel of voluntary professionals. A list of 32 items explored the quality of shared information delivered to patients and the effectiveness of interprofessional communication. The study was conducted in 16 voluntary units in a University Hospital (France), which included medical, surgical, obstetrics, intensive care, pediatrics, oncology and rehabilitation care. The scale-development process comprised an exploratory principal component analysis, Cronbach’s α-coefficients and structural equation modeling (SEM). Results From these 16 units, a total of 503 health professionals took part in the study. Among them, 23.9% were physicians (n = 120), 43.9% nurses (n = 221) and 32.2% nurse assistants (n = 162). The validated questionnaire comprised 13 items and 3 dimensions relative to “the sharing of medical information” (5 items), “communication between physicians” (4 items) and “communication between nurses and nurse assistants” (4 items). The 3 dimensions accounted for 63.7% of the variance of the final questionnaire. Their respective Cronbach’s alpha coefficients were 0.80, 0.87 and 0.81. SEM confirmed the existence of the 3 latent dimensions but the best characteristics were obtained with a hierarchical model including the three latent factors and a global “communication between healthcare professionals” latent factor, bringing the 8 items linked to communication together. All the structural coefficients were highly significant (P < 0.001). Conclusions This self-perception CSI scale assessing several facets of interprofessional communication is the first one developed in the French context. The development study exhibited excellent psychometric properties. Further psychometric analysis is needed to establish test-retest reliability, sensibility to change and concurrent validity. PMID:24625318

Importance Sampling Variance Reduction in GRESS ATMOSIM

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

Wakeford, Daniel Tyler

This document is intended to introduce the importance sampling method of variance reduction to a Geant4 user for application to neutral particle Monte Carlo transport through the atmosphere, as implemented in GRESS ATMOSIM.

The Genetic Liability to Disability Retirement: A 30-Year Follow-Up Study of 24,000 Finnish Twins

PubMed Central

Harkonmäki, Karoliina; Silventoinen, Karri; Levälahti, Esko; Pitkäniemi, Janne; Huunan-Seppälä, Antti; Klaukka, Timo; Koskenvuo, Markku; Kaprio, Jaakko

2008-01-01

Background No previous studies on the effect of genetic factors on the liability to disability retirement have been carried out. The main aim of this study was to investigate the contribution of genetic factors on disability retirement due to the most common medical causes, including depressive disorders. Methods The study sample consisted of 24 043 participants (49.7% women) consisting of 11 186 complete same-sex twin pairs including 3519 monozygotic (MZ) and 7667dizygotic (DZ) pairs. Information on retirement events during 1.1.1975–31.12.2004, including disability pensions (DPs) with diagnoses, was obtained from the Finnish nationwide official pension registers. Correlations in liability for MZ and DZ twins and discrete time correlated frailty model were used to investigate the genetic liability to age at disability retirement. Results The 30 year cumulative incidence of disability retirement was 20%. Under the best fitting genetic models, the heritability estimate for DPs due to any medical cause was 0.36 (95% CI 0.32–0.40), due to musculoskeletal disorders 0.37 (0.30–0.43), cardiovascular diseases 0.48 (0.39–0.57), mental disorders 0.42 (0.35–0.49) and all other reasons 0.24 (0.17–0.31). The effect of genetic factors decreased with increasing age of retirement. For DP due to depressive disorders, 28% of the variance was explained by environmental factors shared by family members (95% CI 21–36) and 58% of the variance by the age interval specific environmental factors (95% CI 44–71). Conclusions A moderate genetic contribution to the variation of disability retirement due to any medical cause was found. The genetic effects appeared to be stronger at younger ages of disability retirement suggesting the increasing influence of environmental factors not shared with family members with increasing age. Familial aggregation in DPs due to depressive disorders was best explained by the common environmental factors and genetic factors were not needed to account for the pattern of familial aggregation. PMID:18923678

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

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

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

Evidence of Convergent and Discriminant Validity of Child, Teacher, and Peer Reports of Teacher-Student Support

PubMed Central

Li, Yan; Hughes, Jan N.; Kwok, Oi-man; Hsu, Hsien-Yuan

2012-01-01

This study investigated the construct validity of measures of teacher-student support in a sample of 709 ethnically diverse second and third grade academically at-risk students. Confirmatory factor analysis investigated the convergent and discriminant validities of teacher, child, and peer reports of teacher-student support and child conduct problems. Results supported the convergent and discriminant validity of scores on the measures. Peer reports accounted for the largest proportion of trait variance and non-significant method variance. Child reports accounted for the smallest proportion of trait variance and the largest method variance. A model with two latent factors provided a better fit to the data than a model with one factor, providing further evidence of the discriminant validity of measures of teacher-student support. Implications for research, policy, and practice are discussed. PMID:21767024

Determining the bias and variance of a deterministic finger-tracking algorithm.

PubMed

Morash, Valerie S; van der Velden, Bas H M

2016-06-01

Finger tracking has the potential to expand haptic research and applications, as eye tracking has done in vision research. In research applications, it is desirable to know the bias and variance associated with a finger-tracking method. However, assessing the bias and variance of a deterministic method is not straightforward. Multiple measurements of the same finger position data will not produce different results, implying zero variance. Here, we present a method of assessing deterministic finger-tracking variance and bias through comparison to a non-deterministic measure. A proof-of-concept is presented using a video-based finger-tracking algorithm developed for the specific purpose of tracking participant fingers during a psychological research study. The algorithm uses ridge detection on videos of the participant's hand, and estimates the location of the right index fingertip. The algorithm was evaluated using data from four participants, who explored tactile maps using only their right index finger and all right-hand fingers. The algorithm identified the index fingertip in 99.78 % of one-finger video frames and 97.55 % of five-finger video frames. Although the algorithm produced slightly biased and more dispersed estimates relative to a human coder, these differences (x=0.08 cm, y=0.04 cm) and standard deviations (σ x =0.16 cm, σ y =0.21 cm) were small compared to the size of a fingertip (1.5-2.0 cm). Some example finger-tracking results are provided where corrections are made using the bias and variance estimates.

Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails?

PubMed

Jackson, Dan; Bowden, Jack

2016-09-07

Confidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. Whilst, under the random effects model, these new methods furnish confidence intervals with the correct coverage, the resulting intervals are usually very wide, making them uninformative. We discuss a simple strategy for obtaining 95 % confidence intervals for the between-study variance with a markedly reduced width, whilst retaining the nominal coverage probability. Specifically, we consider the possibility of using methods based on generalised heterogeneity statistics with unequal tail probabilities, where the tail probability used to compute the upper bound is greater than 2.5 %. This idea is assessed using four real examples and a variety of simulation studies. Supporting analytical results are also obtained. Our results provide evidence that using unequal tail probabilities can result in shorter 95 % confidence intervals for the between-study variance. We also show some further results for a real example that illustrates how shorter confidence intervals for the between-study variance can be useful when performing sensitivity analyses for the average effect, which is usually the parameter of primary interest. We conclude that using unequal tail probabilities when computing 95 % confidence intervals for the between-study variance, when using methods based on generalised heterogeneity statistics, can result in shorter confidence intervals. We suggest that those who find the case for using unequal tail probabilities convincing should use the '1-4 % split', where greater tail probability is allocated to the upper confidence bound. The 'width-optimal' interval that we present deserves further investigation.

Data assimilation method based on the constraints of confidence region

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

2018-03-01

The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

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…

Adult Second Language Reading in the USA: The Effects of Readers' Gender and Test Method

ERIC Educational Resources Information Center

Brantmeier, Cindy

2006-01-01

Bernhardt (2003) claims that half of the variance in second language (L2) reading is accounted for by first language literacy (20%) and second language knowledge (30%), and that one of the central goals of current L2 reading research should be to investigate the 50% of variance that remains unexplained. Part of this variance takes consists of…

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application.

PubMed

Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D

2016-06-15

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Origins of individual differences in imitation: links with language, pretend play, and socially insightful behavior in two-year-old twins.

PubMed

McEwen, Fiona; Happé, Francesca; Bolton, Patrick; Rijsdijk, Fruhling; Ronald, Angelica; Dworzynski, Katharina; Plomin, Robert

2007-01-01

Imitation, vocabulary, pretend play, and socially insightful behavior were investigated in 5,206 same- and opposite-sex 2-year-old twin pairs in the United Kingdom. Individual differences in imitative ability were due to modest heritability (30%), while environmental factors shared between twins (42%) and unique to each twin (28%) also made significant contributions to the variance. Imitation correlated significantly, although modestly, with vocabulary, pretend play, and socially insightful behavior, and the strongest relationship was with vocabulary. A model that represented the covariance between the variables as being due to correlated latent genetic and environmental factors fitted the data well, with shared environmental factors influencing most of the covariance. Parents who encourage imitation may also tend to foster the development of language, pretence, and socially insightful behavior.

A comparison of selection at list time and time-stratified sampling for estimating suspended sediment loads

Treesearch

Robert B. Thomas; Jack Lewis

1993-01-01

Time-stratified sampling of sediment for estimating suspended load is introduced and compared to selection at list time (SALT) sampling. Both methods provide unbiased estimates of load and variance. The magnitude of the variance of the two methods is compared using five storm populations of suspended sediment flux derived from turbidity data. Under like conditions,...

40 CFR 52.2020 - Identification of plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) Compliance and test methods 11/1/97 6/8/98, 63 FR 31116 (c)(131). Subchapter D—Motor Vehicle Emissions... 70893 (c)(229). Section 130.107 Variances 10/5/02 12/8/04, 69 FR 70893 (c)(229). Section 130.108 Test... 70895 (c)(230). Section 130.414 Modification of variance 10/11/08 10/18/10, 75 FR 63717. TEST METHODS...

40 CFR 52.2020 - Identification of plan.

Code of Federal Regulations, 2014 CFR

2014-07-01

...)(131). Section 126.303(a) Compliance and test methods 11/1/97 6/8/98, 63 FR 31116 (c)(131). Subchapter...)(229). Section 130.107 Variances 10/5/02 12/8/04, 69 FR 70893 (c)(229). Section 130.108 Test procedures... 70895 (c)(230). Section 130.414 Modification of variance 10/11/08 10/18/10, 75 FR 63717. TEST METHODS...

Multimethod Assessment of Psychopathy in Relation to Factors of Internalizing and Externalizing from the Personality Assessment Inventory: The Impact of Method Variance and Suppressor Effects

ERIC Educational Resources Information Center

Blonigen, Daniel M.; Patrick, Christopher J.; Douglas, Kevin S.; Poythress, Norman G.; Skeem, Jennifer L.; Lilienfeld, Scott O.; Edens, John F.; Krueger, Robert F.

2010-01-01

Research to date has revealed divergent relations across factors of psychopathy measures with criteria of "internalizing" (INT; anxiety, depression) and "externalizing" (EXT; antisocial behavior, substance use). However, failure to account for method variance and suppressor effects has obscured the consistency of these findings…

Optimized doppler optical coherence tomography for choroidal capillary vasculature imaging

NASA Astrophysics Data System (ADS)

Liu, Gangjun; Qi, Wenjuan; Yu, Lingfeng; Chen, Zhongping

2011-03-01

In this paper, we analyzed the retinal and choroidal blood vasculature in the posterior segment of the human eye with optimized color Doppler and Doppler variance optical coherence tomography. Depth-resolved structure, color Doppler and Doppler variance images were compared. Blood vessels down to capillary level were able to be obtained with the optimized optical coherence color Doppler and Doppler variance method. For in-vivo imaging of human eyes, bulkmotion induced bulk phase must be identified and removed before using color Doppler method. It was found that the Doppler variance method is not sensitive to bulk motion and the method can be used without removing the bulk phase. A novel, simple and fast segmentation algorithm to indentify retinal pigment epithelium (RPE) was proposed and used to segment the retinal and choroidal layer. The algorithm was based on the detected OCT signal intensity difference between different layers. A spectrometer-based Fourier domain OCT system with a central wavelength of 890 nm and bandwidth of 150nm was used in this study. The 3-dimensional imaging volume contained 120 sequential two dimensional images with 2048 A-lines per image. The total imaging time was 12 seconds and the imaging area was 5x5 mm2.

A note on the kappa statistic for clustered dichotomous data.

PubMed

Zhou, Ming; Yang, Zhao

2014-06-30

The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

Negative Affectivity and Effortful Control in Mothers With Borderline Personality Disorder and in Their Young Children.

PubMed

Mena, Christina G; Macfie, Jenny; Strimpfel, Jennifer M

2017-06-01

Research has examined temperament in individuals with borderline personality disorder (BPD) but not in their offspring, despite offspring's risk of developing BPD and the importance of temperament in the etiology of BPD. We recruited a low-socioeconomic sample of 36 mothers with BPD and their children ages 4 through 7, and 34 normative comparisons. Replicating prior studies, mothers with BPD reported themselves as having more negative affectivity (frustration, fear) and less effortful control (inhibitory control, attentional control, activation control) than did comparisons. Mothers with BPD also reported that their offspring had more negative affectivity (anger/frustration, fear) and less effortful control (inhibitory control, attentional focusing) than did comparisons. We were concerned about potential bias and shared method variance. We therefore provided validity support for mothers' ratings of their children with teacher ratings of child behavior and child self-report via their story-stem completion narratives. We discuss children's temperamental vulnerability versus differential susceptibility to the environment.

Constructing inverse probability weights for continuous exposures: a comparison of methods.

PubMed

Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S

2014-03-01

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Spectral analysis of the Earth's topographic potential via 2D-DFT: a new data-based degree variance model to degree 90,000

NASA Astrophysics Data System (ADS)

Rexer, Moritz; Hirt, Christian

2015-09-01

Classical degree variance models (such as Kaula's rule or the Tscherning-Rapp model) often rely on low-resolution gravity data and so are subject to extrapolation when used to describe the decay of the gravity field at short spatial scales. This paper presents a new degree variance model based on the recently published GGMplus near-global land areas 220 m resolution gravity maps (Geophys Res Lett 40(16):4279-4283, 2013). We investigate and use a 2D-DFT (discrete Fourier transform) approach to transform GGMplus gravity grids into degree variances. The method is described in detail and its approximation errors are studied using closed-loop experiments. Focus is placed on tiling, azimuth averaging, and windowing effects in the 2D-DFT method and on analytical fitting of degree variances. Approximation errors of the 2D-DFT procedure on the (spherical harmonic) degree variance are found to be at the 10-20 % level. The importance of the reference surface (sphere, ellipsoid or topography) of the gravity data for correct interpretation of degree variance spectra is highlighted. The effect of the underlying mass arrangement (spherical or ellipsoidal approximation) on the degree variances is found to be crucial at short spatial scales. A rule-of-thumb for transformation of spectra between spherical and ellipsoidal approximation is derived. Application of the 2D-DFT on GGMplus gravity maps yields a new degree variance model to degree 90,000. The model is supported by GRACE, GOCE, EGM2008 and forward-modelled gravity at 3 billion land points over all land areas within the SRTM data coverage and provides gravity signal variances at the surface of the topography. The model yields omission errors of 9 mGal for gravity (1.5 cm for geoid effects) at scales of 10 km, 4 mGal (1 mm) at 2-km scales, and 2 mGal (0.2 mm) at 1-km scales.

Importance sampling variance reduction for the Fokker–Planck rarefied gas particle method

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

Collyer, B.S., E-mail: benjamin.collyer@gmail.com; London Mathematical Laboratory, 14 Buckingham Street, London WC2N 6DF; Connaughton, C.

The Fokker–Planck approximation to the Boltzmann equation, solved numerically by stochastic particle schemes, is used to provide estimates for rarefied gas flows. This paper presents a variance reduction technique for a stochastic particle method that is able to greatly reduce the uncertainty of the estimated flow fields when the characteristic speed of the flow is small in comparison to the thermal velocity of the gas. The method relies on importance sampling, requiring minimal changes to the basic stochastic particle scheme. We test the importance sampling scheme on a homogeneous relaxation, planar Couette flow and a lid-driven-cavity flow, and find thatmore » our method is able to greatly reduce the noise of estimated quantities. Significantly, we find that as the characteristic speed of the flow decreases, the variance of the noisy estimators becomes independent of the characteristic speed.« less

Automated variance reduction for MCNP using deterministic methods.

PubMed

Sweezy, J; Brown, F; Booth, T; Chiaramonte, J; Preeg, B

2005-01-01

In order to reduce the user's time and the computer time needed to solve deep penetration problems, an automated variance reduction capability has been developed for the MCNP Monte Carlo transport code. This new variance reduction capability developed for MCNP5 employs the PARTISN multigroup discrete ordinates code to generate mesh-based weight windows. The technique of using deterministic methods to generate importance maps has been widely used to increase the efficiency of deep penetration Monte Carlo calculations. The application of this method in MCNP uses the existing mesh-based weight window feature to translate the MCNP geometry into geometry suitable for PARTISN. The adjoint flux, which is calculated with PARTISN, is used to generate mesh-based weight windows for MCNP. Additionally, the MCNP source energy spectrum can be biased based on the adjoint energy spectrum at the source location. This method can also use angle-dependent weight windows.

Optimal distribution of integration time for intensity measurements in Stokes polarimetry.

PubMed

Li, Xiaobo; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie; Hu, Haofeng

2015-10-19

We consider the typical Stokes polarimetry system, which performs four intensity measurements to estimate a Stokes vector. We show that if the total integration time of intensity measurements is fixed, the variance of the Stokes vector estimator depends on the distribution of the integration time at four intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the Stokes vector estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time by employing Lagrange multiplier method. According to the theoretical analysis and real-world experiment, it is shown that the total variance of the Stokes vector estimator can be significantly decreased about 40% in the case discussed in this paper. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improves the measurement accuracy of the polarimetric system.

A consistent transported PDF model for treating differential molecular diffusion

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Zhang, Pei

2016-11-01

Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

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

Beer, M.

1980-12-01

The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

A close examination of double filtering with fold change and t test in microarray analysis

PubMed Central

2009-01-01

Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis

PubMed Central

Daye, Z. John; Chen, Jinbo; Li, Hongzhe

2011-01-01

Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833

Why do we differ in number sense? Evidence from a genetically sensitive investigation☆

PubMed Central

Tosto, M.G.; Petrill, S.A.; Halberda, J.; Trzaskowski, M.; Tikhomirova, T.N.; Bogdanova, O.Y.; Ly, R.; Wilmer, J.B.; Naiman, D.Q.; Germine, L.; Plomin, R.; Kovas, Y.

2014-01-01

Basic intellectual abilities of quantity and numerosity estimation have been detected across animal species. Such abilities are referred to as ‘number sense’. For human species, individual differences in number sense are detectable early in life, persist in later development, and relate to general intelligence. The origins of these individual differences are unknown. To address this question, we conducted the first large-scale genetically sensitive investigation of number sense, assessing numerosity discrimination abilities in 837 pairs of monozygotic and 1422 pairs of dizygotic 16-year-old twin pairs. Univariate genetic analysis of the twin data revealed that number sense is modestly heritable (32%), with individual differences being largely explained by non-shared environmental influences (68%) and no contribution from shared environmental factors. Sex-Limitation model fitting revealed no differences between males and females in the etiology of individual differences in number sense abilities. We also carried out Genome-wide Complex Trait Analysis (GCTA) that estimates the population variance explained by additive effects of DNA differences among unrelated individuals. For 1118 unrelated individuals in our sample with genotyping information on 1.7 million DNA markers, GCTA estimated zero heritability for number sense, unlike other cognitive abilities in the same twin study where the GCTA heritability estimates were about 25%. The low heritability of number sense, observed in this study, is consistent with the directional selection explanation whereby additive genetic variance for evolutionary important traits is reduced. PMID:24696527

Genetic architecture of lipid traits changes over time and differs by race: Princeton Lipid Follow-up Study.

PubMed

Woo, Jessica G; Morrison, John A; Stroop, Davis M; Aronson Friedman, Lisa; Martin, Lisa J

2014-07-01

Dyslipidemia is a major risk factor for CVD. Previous studies on lipid heritability have largely focused on white populations assessed after the obesity epidemic. Given secular trends and racial differences in lipid levels, this study explored whether lipid heritability is consistent across time and between races. African American and white nuclear families had fasting lipids measured in the 1970s and 22-30 years later. Heritability was estimated, and bivariate analyses between visits were conducted by race using variance components analysis. A total of 1,454 individuals (age 14.1/40.6 for offspring/parents at baseline; 39.6/66.5 at follow-up) in 373 families (286 white, 87 African American) were included. Lipid trait heritabilities were typically stronger during the 1970s than the 2000s. At baseline, additive genetic variation for LDL was significantly lower in African Americans than whites (P = 0.015). Shared genetic contribution to lipid variability over time was significant in both whites (all P < 0.0001) and African Americans (P ≤ 0.05 for total, LDL, and HDL cholesterol). African American families demonstrated shared environmental contributions to lipid variation over time (all P ≤ 0.05). Lower heritability, lower LDL genetic variance, and durable environmental effects across the obesity epidemic in African American families suggest race-specific approaches are needed to clarify the genetic etiology of lipids. Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

PubMed Central

Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

2015-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

Measurement of the viscoelastic compliance of the eustachian tube using a modified forced-response test.

PubMed

Ghadiali, Samir N; Federspiel, William J; Swarts, J Douglas; Doyle, William J

2002-01-01

Eustachian tube compliance (ETC) was suggested to be an important determinate of function. Previous attempts to quantify ETC used summary measures that are not clearly related to the physical properties of the system. Here, we present a new method for measuring ETC that conforms more closely to the engineering definition of compliance. The forced response test was modified to include oscillations in applied flow after the forced tubal opening. Pressure and flow were recorded during the standard and modified test in 12 anesthetized cynomolgus monkeys. The resulting pressure-flow, hysteresis loops were compared with those predicted by a simple fluid-structure model of the Eustachian tube with linear-elastic or viscoelastic properties. The tubal compliance index (TCI) and a viscoelastic compliance (C(v)) were calculated from these data for each monkey. The behavior of a viscoelastic, but not a linear elastic model accurately reproduced the experimental data for the monkey. The TCI and C(v) were linearly related, but the shared variance in these measures was only 63%. This new method for measuring ETC captures all information contained in the traditional TCI, but also provides information regarding the contribution of wall viscosity to Eustachian tube mechanics.

The Complex Dynamics of Sponsored Search Markets

NASA Astrophysics Data System (ADS)

Robu, Valentin; La Poutré, Han; Bohte, Sander

This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.

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.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

PubMed Central

Liu, Ruijie; Holik, Aliaksei Z.; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E.; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.; Ritchie, Matthew E.

2015-01-01

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package. PMID:25925576

Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

PubMed

Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

2008-07-01

Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

Sex-specific genetic variance and the evolution of sexual dimorphism: a systematic review of cross-sex genetic correlations.

PubMed

Poissant, Jocelyn; Wilson, Alastair J; Coltman, David W

2010-01-01

The independent evolution of the sexes may often be constrained if male and female homologous traits share a similar genetic architecture. Thus, cross-sex genetic covariance is assumed to play a key role in the evolution of sexual dimorphism (SD) with consequent impacts on sexual selection, population dynamics, and speciation processes. We compiled cross-sex genetic correlations (r(MF)) estimates from 114 sources to assess the extent to which the evolution of SD is typically constrained and test several specific hypotheses. First, we tested if r(MF) differed among trait types and especially between fitness components and other traits. We also tested the theoretical prediction of a negative relationship between r(MF) and SD based on the expectation that increases in SD should be facilitated by sex-specific genetic variance. We show that r(MF) is usually large and positive but that it is typically smaller for fitness components. This demonstrates that the evolution of SD is typically genetically constrained and that sex-specific selection coefficients may often be opposite in sign due to sub-optimal levels of SD. Most importantly, we confirm that sex-specific genetic variance is an important contributor to the evolution of SD by validating the prediction of a negative correlation between r(MF) and SD.

The genetic and environmental etiology of antisocial behavior from childhood to emerging adulthood.

PubMed

Tuvblad, Catherine; Narusyte, Jurgita; Grann, Martin; Sarnecki, Jerzy; Lichtenstein, Paul

2011-09-01

Previous research suggests that both genetic and environmental influences are important for antisocial behavior across the life span, even though the prevalence and incidence of antisocial behavior varies considerably across ages. However, little is known of how genetic and environmental effects influence the development of antisocial behavior. A total of 2,600 male and female twins from the population-based Swedish Twin Registry were included in the present study. Antisocial behavior was measured on four occasions, when twins were 8-9, 13-14, 16-17, and 19-20 years old. Longitudinal analyses of the data were conducted using structural equation modeling. The stability of antisocial behavior over time was explained by a common latent persistent antisocial behavior factor. A common genetic influence accounted for 67% of the total variance in this latent factor, the shared environment explained 26%, and the remaining 7% was due to the non-shared environment. Significant age-specific shared environmental factors were found at ages 13-14 years, suggesting that common experiences (e.g., peers) are important for antisocial behavior at this age. Results from this study show that genetic as well as shared environmental influences are important in antisocial behavior that persists from childhood to emerging adulthood.

Shared genetic contributions of fruit and vegetable consumption with BMI in families 20 y after sharing a household.

PubMed

Martin, Lisa J; Lee, Seung-Yeon; Couch, Sarah C; Morrison, John; Woo, Jessica G

2011-10-01

Obesity has a strong genetic basis, but the identification of genetic variants has not resulted in improved clinical care. However, phenotypes that influence weight, such as diet, may have shared underpinnings with obesity. Interestingly, diet also has a genetic basis. Thus, we hypothesized that the genetic underpinnings of diet may partially overlap with the genetics of obesity. Our objective was to determine whether dietary intake and BMI share heritable components in adulthood. We used a cross-sectional cohort of parents and adult offspring (n = 1410) from the Princeton Follow-up Study. Participants completed Block food-frequency questionnaires 15-27 y after sharing a household. Heritability of dietary intakes was estimated by using variance components analysis. Bivariate genetic analyses were used to estimate the shared effects between BMI and heritable dietary intakes. Fruit, vegetable, and protein consumption exhibited moderate heritability [(mean ± SE) 0.26 ± 0.06, 0.32 ± 0.06, and 0.21 ± 0.06, respectively; P < 0.001], but other dietary intakes were modest (h(2) < 0.2). Only fruit and vegetable consumption exhibited genetic correlations with BMI (ρ(g) = -0.28 ± 0.13 and -0.30 ± 0.13, respectively; P < 0.05). Phenotypic correlations with BMI were not significant. We showed that fruit, vegetable, and protein intakes are moderately heritable and that fruit and vegetable consumption shares underlying genetic effects with BMI in adulthood, which suggests that individuals genetically predisposed to low fruit and vegetable consumption may be predisposed to higher BMI. Thus, obese individuals who have low fruit and vegetable consumption may require targeted interventions that go beyond low-calorie, plant-based programs for weight management.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

Some variance reduction methods for numerical stochastic homogenization

PubMed Central

Blanc, X.; Le Bris, C.; Legoll, F.

2016-01-01

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. PMID:27002065

40 CFR 52.2020 - Identification of plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

...)(131). Section 126.303(a) Compliance and test methods 11/1/97 6/8/98, 63 FR 31116 (c)(131). Subchapter....107 Variances 10/5/02 12/8/04, 69 FR 70893 (c)(229). Section 130.108 Test procedures 10/5/02 12/8/04... 70895 (c)(230). Section 130.414 Modification of variance 10/11/08 10/18/10, 75 FR 63717. TEST METHODS...

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed Central

Patlak, J B

1993-01-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed. Images FIGURE 2 FIGURE 4 FIGURE 8 FIGURE 9 PMID:7690261

Community trees: Identifying codiversification in the Páramo dipteran community.

PubMed

Carstens, Bryan C; Gruenstaeudl, Michael; Reid, Noah M

2016-05-01

Groups of codistributed species that responded in a concerted manner to environmental events are expected to share patterns of evolutionary diversification. However, the identification of such groups has largely been based on qualitative, post hoc analyses. We develop here two methods (posterior predictive simulation [PPS], Kuhner-Felsenstein [K-F] analysis of variance [ANOVA]) for the analysis of codistributed species that, given a group of species with a shared pattern of diversification, allow empiricists to identify those taxa that do not codiversify (i.e., "outlier" species). The identification of outlier species makes it possible to jointly estimate the evolutionary history of co-diversifying taxa. To evaluate the approaches presented here, we collected data from Páramo dipterans, identified outlier species, and estimated a "community tree" from species that are identified as having codiversified. Our results demonstrate that dipteran communities from different Páramo habitats in the same mountain range are more closely related than communities in other ranges. We also conduct simulation testing to evaluate this approach. Results suggest that our approach provides a useful addition to comparative phylogeographic methods, while identifying aspects of the analysis that require careful interpretation. In particular, both the PPS and K-F ANOVA perform acceptably when there are one or two outlier species, but less so as the number of outliers increases. This is likely a function of the corresponding degradation of the signal of community divergence; without a strong signal from a codiversifying community, there is no dominant pattern from which to detect an outlier species. For this reason, both the magnitude of K-F distance distribution and outside knowledge about the phylogeographic history of each putative member of the community should be considered when interpreting the results. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits

PubMed Central

Zaitlen, Noah; Kraft, Peter; Patterson, Nick; Pasaniuc, Bogdan; Bhatia, Gaurav; Pollack, Samuela; Price, Alkes L.

2013-01-01

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays. PMID:23737753

Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits.

PubMed

Zaitlen, Noah; Kraft, Peter; Patterson, Nick; Pasaniuc, Bogdan; Bhatia, Gaurav; Pollack, Samuela; Price, Alkes L

2013-05-01

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays.

Quantitative genetic analysis of cellular adhesion molecules: the Fels Longitudinal Study.

PubMed

Lee, Miryoung; Czerwinski, Stefan A; Choh, Audrey C; Demerath, Ellen W; Sun, Shumei S; Chumlea, Wm C; Towne, Bradford; Siervogel, Roger M

2006-03-01

Circulating concentrations of inflammatory markers predict cardiovascular disease (CVD) risk and are closely associated with obesity. However, little is known concerning genetic influences on serum levels of inflammatory markers. In this study, we estimated the heritability (h2) of soluble cellular adhesion molecule (sCAM) concentrations and examined the correlational architecture between different sCAMs. The study population included 234 men and 270 women aged 18-76 years, belonging to 121 families participating in the Fels Longitudinal Study. Serum levels of soluble intercellular adhesion molecule-1 (sICAM-1), vascular cell adhesion molecule-1 (sVCAM-1), E-selectin (sESEL-1) and P-selectin (sPSEL-1) were assayed using commercially available kits. A variance components-based maximum likelihood method was used to estimate the h2 of the different serum inflammatory markers while simultaneously adjusting for the effects of known CVD risk factors, such as age and smoking. Additionally, we used bivariate extensions of these methods to estimate genetic and random environmental correlations among sCAMs. Levels of sCAMs were significantly heritable: h2=0.24+/-0.10 for sICAM-1, h2=0.22+/-0.10 for sVCAM-1, h2=0.50+/-0.11 for sESEL-1, and h2=0.46+/-0.10 for sPSEL-1. In addition, a significant genetic correlation (rho(G)=0.63) was found between sICAM-1 and sVCAM-1 indicating some degree of shared genetic control. In the Fels Longitudinal Study, the levels of four sCAMs are significantly influenced by genetic effects, and sICAM-1 shares a common genetic background with sVCAM-1.

Poisson denoising on the sphere

NASA Astrophysics Data System (ADS)

Schmitt, J.; Starck, J. L.; Fadili, J.; Grenier, I.; Casandjian, J. M.

2009-08-01

In the scope of the Fermi mission, Poisson noise removal should improve data quality and make source detection easier. This paper presents a method for Poisson data denoising on sphere, called Multi-Scale Variance Stabilizing Transform on Sphere (MS-VSTS). This method is based on a Variance Stabilizing Transform (VST), a transform which aims to stabilize a Poisson data set such that each stabilized sample has an (asymptotically) constant variance. In addition, for the VST used in the method, the transformed data are asymptotically Gaussian. Thus, MS-VSTS consists in decomposing the data into a sparse multi-scale dictionary (wavelets, curvelets, ridgelets...), and then applying a VST on the coefficients in order to get quasi-Gaussian stabilized coefficients. In this present article, the used multi-scale transform is the Isotropic Undecimated Wavelet Transform. Then, hypothesis tests are made to detect significant coefficients, and the denoised image is reconstructed with an iterative method based on Hybrid Steepest Descent (HST). The method is tested on simulated Fermi data.

Measurement System Characterization in the Presence of Measurement Errors

NASA Technical Reports Server (NTRS)

Commo, Sean A.

2012-01-01

In the calibration of a measurement system, data are collected in order to estimate a mathematical model between one or more factors of interest and a response. Ordinary least squares is a method employed to estimate the regression coefficients in the model. The method assumes that the factors are known without error; yet, it is implicitly known that the factors contain some uncertainty. In the literature, this uncertainty is known as measurement error. The measurement error affects both the estimates of the model coefficients and the prediction, or residual, errors. There are some methods, such as orthogonal least squares, that are employed in situations where measurement errors exist, but these methods do not directly incorporate the magnitude of the measurement errors. This research proposes a new method, known as modified least squares, that combines the principles of least squares with knowledge about the measurement errors. This knowledge is expressed in terms of the variance ratio - the ratio of response error variance to measurement error variance.

Weighted analysis of paired microarray experiments.

PubMed

Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle

2005-01-01

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Imaging shear wave propagation for elastic measurement using OCT Doppler variance method

NASA Astrophysics Data System (ADS)

Zhu, Jiang; Miao, Yusi; Qu, Yueqiao; Ma, Teng; Li, Rui; Du, Yongzhao; Huang, Shenghai; Shung, K. Kirk; Zhou, Qifa; Chen, Zhongping

2016-03-01

In this study, we have developed an acoustic radiation force orthogonal excitation optical coherence elastography (ARFOE-OCE) method for the visualization of the shear wave and the calculation of the shear modulus based on the OCT Doppler variance method. The vibration perpendicular to the OCT detection direction is induced by the remote acoustic radiation force (ARF) and the shear wave propagating along the OCT beam is visualized by the OCT M-scan. The homogeneous agar phantom and two-layer agar phantom are measured using the ARFOE-OCE system. The results show that the ARFOE-OCE system has the ability to measure the shear modulus beyond the OCT imaging depth. The OCT Doppler variance method, instead of the OCT Doppler phase method, is used for vibration detection without the need of high phase stability and phase wrapping correction. An M-scan instead of the B-scan for the visualization of the shear wave also simplifies the data processing.

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

PubMed

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

PubMed

Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L

2015-01-01

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

Non-Immunogenic Structurally and Biologically Intact Tissue Matrix Grafts for the Immediate Repair of Ballistic-Induced Vascular and Nerve Tissue Injury in Combat Casualty Care

DTIC Science & Technology

2005-07-01

as an access graft is addressed using statistical methods below. Graft consistency can be defined statistically as the variance associated with the...addressed using statistical methods below. Graft consistency can be defined statistically as the variance associated with the sample of grafts tested in...measured using a refractometer (Brix % method). The equilibration data are shown in Graph 1. The results suggest the following equilibration scheme: 40% v/v

Familial concordance for age at natural menopause: results from the Breakthrough Generations Study.

PubMed

Morris, Danielle H; Jones, Michael E; Schoemaker, Minouk J; Ashworth, Alan; Swerdlow, Anthony J

2011-09-01

Existing estimates of the heritability of menopause age have a wide range. Furthermore, few studies have analyzed to what extent familial similarities might reflect shared environment, rather than shared genes. We therefore analyzed familial concordance for age at natural menopause and the effects of shared genetic and environmental factors on this concordance. Participants were 2,060 individuals comprising first-degree relatives, aged 31 to 90 years, and participating in the UK Breakthrough Generations Study. Menopause data were collected using a self-administered questionnaire and analyzed using logistic regression and variance-components models. Women were at an increased risk of early menopause (≤45 y) if their mother (odds ratio, 6.2; P < 0.001) or non-twin sister (odds ratio, 5.5; P < 0.001) had had an early menopause. Likewise, women had an increased risk of late menopause (≥54 y) if their relative had had a late menopause (mother: odds ratio, 6.1; P < 0.01; non-twin sister: odds ratio, 2.3; P < 0.001). Estimated heritability was 41.6% (P < 0.01), with an additional 13.6% (P = 0.02) of the variation in menopause age attributed to environmental factors shared by sisters. We confirm that early menopause aggregates within families and show, for the first time, that there is also strong familial concordance for late menopause. Both genes and shared environment were the source of variation in menopause age. Past heritability estimates have not accounted for shared environment, and thus, the effect of genetic variants on menopause age may previously have been overestimated.

A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2016-12-01

Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Jackknife Estimation of Sampling Variance of Ratio Estimators in Complex Samples: Bias and the Coefficient of Variation. Research Report. ETS RR-06-19

ERIC Educational Resources Information Center

Oranje, Andreas

2006-01-01

A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…

Tinnitus complaint behaviour in long-standing Menière's disorder: its association with the other cardinal symptoms.

PubMed

Yoshida, T; Stephens, D; Kentala, E; Levo, H; Auramo, Y; Poe, D; Pyykkö, I

2011-10-01

To explore factors that determines tinnitus complaint behaviour in patients with chronic long-standing Menière's disorder. A questionnaire-based cross-sectional investigation. This included the Oto-neurological questionnaire, the Hearing Disability and Handicap Scale (HDHS), Hearing Measurement Scale (HMS) on sound localisation and the Dizziness Handicap Questionnaire (DHQ). Randomly selected 183 members of the Finnish Menière's Federation. Postal questionnaire. International Tinnitus Inventory and impact of tinnitus. The 183 patients,[36 men and 147 women; mean age, 63 years] had their Meniere's disorder-like symptoms, with a mean of 18 years [range, 1-43], 19% of patients ranked tinnitus as their most severe symptom, and 10% experienced tinnitus as causing a severe or very severe impact. Regression analysis indicated that 41% of International Tinnitus Inventory variance and 28% of tinnitus impact variance were explained by the cardinal symptoms of Menière's disorder. Furthermore, 40% of International Tinnitus Inventory and 25% of tinnitus impact variance were explained by symptom-related disabilities (HDHS, HMS and DHQ). Aural pressure, hearing loss and gait problems were the most important predictors of tinnitus complaint. Understanding what people say and limitation of activities because of vertigo were the most important related disabilities. Tinnitus shares a significant variance with the other cardinal symptoms in patients with long-standing Menière's disorder. As the impact is significantly related to activity limitations based on hearing disability and vertigo, the results suggest that therapeutic efforts to reduce tinnitus in Menière's disorder should include the alleviation of balance and hearing problems. © 2011 Blackwell Publishing Ltd.

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Modeling self-consistent multi-class dynamic traffic flow

NASA Astrophysics Data System (ADS)

Cho, Hsun-Jung; Lo, Shih-Ching

2002-09-01

In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

A Study of Impact Point Detecting Method Based on Seismic Signal

NASA Astrophysics Data System (ADS)

Huo, Pengju; Zhang, Yu; Xu, Lina; Huang, Yong

The projectile landing position has to be determined for its recovery and range in the targeting test. In this paper, a global search method based on the velocity variance is proposed. In order to verify the applicability of this method, simulation analysis within the scope of four million square meters has been conducted in the same array structure of the commonly used linear positioning method, and MATLAB was used to compare and analyze the two methods. The compared simulation results show that the global search method based on the speed of variance has high positioning accuracy and stability, which can meet the needs of impact point location.

Superresolution SAR Imaging Algorithm Based on Mvm and Weighted Norm Extrapolation

NASA Astrophysics Data System (ADS)

Zhang, P.; Chen, Q.; Li, Z.; Tang, Z.; Liu, J.; Zhao, L.

2013-08-01

In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.

Optimal design criteria - prediction vs. parameter estimation

NASA Astrophysics Data System (ADS)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Iterative raw measurements restoration method with penalized weighted least squares approach for low-dose CT

NASA Astrophysics Data System (ADS)

Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu

2014-03-01

Statistical iterative reconstruction and post-log data restoration algorithms for CT noise reduction have been widely studied and these techniques have enabled us to reduce irradiation doses while maintaining image qualities. In low dose scanning, electronic noise becomes obvious and it results in some non-positive signals in raw measurements. The nonpositive signal should be converted to positive signal so that it can be log-transformed. Since conventional conversion methods do not consider local variance on the sinogram, they have difficulty of controlling the strength of the filtering. Thus, in this work, we propose a method to convert the non-positive signal to the positive signal by mainly controlling the local variance. The method is implemented in two separate steps. First, an iterative restoration algorithm based on penalized weighted least squares is used to mitigate the effect of electronic noise. The algorithm preserves the local mean and reduces the local variance induced by the electronic noise. Second, smoothed raw measurements by the iterative algorithm are converted to the positive signal according to a function which replaces the non-positive signal with its local mean. In phantom studies, we confirm that the proposed method properly preserves the local mean and reduce the variance induced by the electronic noise. Our technique results in dramatically reduced shading artifacts and can also successfully cooperate with the post-log data filter to reduce streak artifacts.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations.

PubMed

Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng

2017-03-15

With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

Heat and solute tracers: how do they compare in heterogeneous aquifers?

PubMed

Irvine, Dylan J; Simmons, Craig T; Werner, Adrian D; Graf, Thomas

2015-04-01

A comparison of groundwater velocity in heterogeneous aquifers estimated from hydraulic methods, heat and solute tracers was made using numerical simulations. Aquifer heterogeneity was described by geostatistical properties of the Borden, Cape Cod, North Bay, and MADE aquifers. Both heat and solute tracers displayed little systematic under- or over-estimation in velocity relative to a hydraulic control. The worst cases were under-estimates of 6.63% for solute and 2.13% for the heat tracer. Both under- and over-estimation of velocity from the heat tracer relative to the solute tracer occurred. Differences between the estimates from the tracer methods increased as the mean velocity decreased, owing to differences in rates of molecular diffusion and thermal conduction. The variance in estimated velocity using all methods increased as the variance in log-hydraulic conductivity (K) and correlation length scales increased. The variance in velocity for each scenario was remarkably small when compared to σ2 ln(K) for all methods tested. The largest variability identified was for the solute tracer where 95% of velocity estimates ranged by a factor of 19 in simulations where 95% of the K values varied by almost four orders of magnitude. For the same K-fields, this range was a factor of 11 for the heat tracer. The variance in estimated velocity was always lowest when using heat as a tracer. The study results suggest that a solute tracer will provide more understanding about the variance in velocity caused by aquifer heterogeneity and a heat tracer provides a better approximation of the mean velocity. © 2013, National Ground Water Association.

Signal, noise, and variation in neural and sensory-motor latency

PubMed Central

Lee, Joonyeol; Joshua, Mati; Medina, Javier F.; Lisberger, Stephen G.

2016-01-01

Analysis of the neural code for sensory-motor latency in smooth pursuit eye movements reveals general principles of neural variation and the specific origin of motor latency. The trial-by-trial variation in neural latency in MT comprises: a shared component expressed as neuron-neuron latency correlations; and an independent component that is local to each neuron. The independent component arises heavily from fluctuations in the underlying probability of spiking with an unexpectedly small contribution from the stochastic nature of spiking itself. The shared component causes the latency of single neuron responses in MT to be weakly predictive of the behavioral latency of pursuit. Neural latency deeper in the motor system is more strongly predictive of behavioral latency. A model reproduces both the variance of behavioral latency and the neuron-behavior latency correlations in MT if it includes realistic neural latency variation, neuron-neuron latency correlations in MT, and noisy gain control downstream from MT. PMID:26971946

Intelligence, creativity, and cognitive control: The common and differential involvement of executive functions in intelligence and creativity

PubMed Central

Benedek, Mathias; Jauk, Emanuel; Sommer, Markus; Arendasy, Martin; Neubauer, Aljoscha C.

2014-01-01

Intelligence and creativity are known to be correlated constructs suggesting that they share a common cognitive basis. The present study assessed three specific executive abilities – updating, shifting, and inhibition – and examined their common and differential relations to fluid intelligence and creativity (i.e., divergent thinking ability) within a latent variable model approach. Additionally, it was tested whether the correlation of fluid intelligence and creativity can be explained by a common executive involvement. As expected, fluid intelligence was strongly predicted by updating, but not by shifting or inhibition. Creativity was predicted by updating and inhibition, but not by shifting. Moreover, updating (and the personality factor openness) was found to explain a relevant part of the shared variance between intelligence and creativity. The findings provide direct support for the executive involvement in creative thought and shed further light on the functional relationship between intelligence and creativity. PMID:25278640

Impact of marriage on HIV/AIDS risk behaviors among impoverished, at-risk couples: a multilevel latent variable approach.

PubMed

Stein, Judith A; Nyamathi, Adeline; Ullman, Jodie B; Bentler, Peter M

2007-01-01

Studies among normative samples generally demonstrate a positive impact of marriage on health behaviors and other related attitudes. In this study, we examine the impact of marriage on HIV/AIDS risk behaviors and attitudes among impoverished, highly stressed, homeless couples, many with severe substance abuse problems. A multilevel analysis of 368 high-risk sexually intimate married and unmarried heterosexual couples assessed individual and couple-level effects on social support, substance use problems, HIV/AIDS knowledge, perceived HIV/AIDS risk, needle-sharing, condom use, multiple sex partners, and HIV/AIDS testing. More variance was explained in the protective and risk variables by couple-level latent variable predictors than by individual latent variable predictors, although some gender effects were found (e.g., more alcohol problems among men). The couple-level variable of marriage predicted lower perceived risk, less deviant social support, and fewer sex partners but predicted more needle-sharing.

Genetic and Environmental Associations Between Procrastination and Internalizing/Externalizing Psychopathology.

PubMed

Gustavson, Daniel E; du Pont, Alta; Hatoum, Alexander S; Hyun Rhee, Soo; Kremen, William S; Hewitt, John K; Friedman, Naomi P

2017-09-01

Recent work on procrastination has begun to unravel the genetic and environmental correlates of this problematic behavior. However, little is known about how strongly procrastination is associated with internalizing and externalizing psychopathology, and the extent to which shared genetic/environmental factors or relevant personality constructs (e.g., fear of failure, impulsivity, and neuroticism) can inform the structure of these associations. The current study examined data from 764 young adult twins who completed questionnaires assessing procrastination and personality and structured interviews regarding psychopathology symptoms. Results indicated that procrastination was positively correlated with both internalizing and externalizing latent variables, and that these correlations were driven by shared genetic influences. Moreover, the association between procrastination and internalizing was accounted for by fear of failure and neuroticism, whereas the association between procrastination and externalizing was primarily explained by impulsivity. The role of procrastination in psychopathology is discussed using a framework that highlights common and broadband-specific variance.

Individual Differences in Motor Timing and Its Relation to Cognitive and Fine Motor Skills

PubMed Central

Lorås, Håvard; Stensdotter, Ann-Katrin; Öhberg, Fredrik; Sigmundsson, Hermundur

2013-01-01

The present study investigated the relationship between individual differences in timing movements at the level of milliseconds and performance on selected cognitive and fine motor skills. For this purpose, young adult participants (N = 100) performed a repetitive movement task paced by an auditory metronome at different rates. Psychometric measures included the digit-span and symbol search subtasks from the Wechsler battery as well as the Raven SPM. Fine motor skills were assessed with the Purdue Pegboard test. Motor timing performance was significantly related (mean r = .3) to cognitive measures, and explained both unique and shared variance with information-processing speed of Raven's scores. No significant relations were found between motor timing measures and fine motor skills. These results show that individual differences in cognitive and motor timing performance is to some extent dependent upon shared processing not associated with individual differences in manual dexterity. PMID:23874952

Individual differences in motor timing and its relation to cognitive and fine motor skills.

PubMed

Lorås, Håvard; Stensdotter, Ann-Katrin; Öhberg, Fredrik; Sigmundsson, Hermundur

2013-01-01

The present study investigated the relationship between individual differences in timing movements at the level of milliseconds and performance on selected cognitive and fine motor skills. For this purpose, young adult participants (N = 100) performed a repetitive movement task paced by an auditory metronome at different rates. Psychometric measures included the digit-span and symbol search subtasks from the Wechsler battery as well as the Raven SPM. Fine motor skills were assessed with the Purdue Pegboard test. Motor timing performance was significantly related (mean r = .3) to cognitive measures, and explained both unique and shared variance with information-processing speed of Raven's scores. No significant relations were found between motor timing measures and fine motor skills. These results show that individual differences in cognitive and motor timing performance is to some extent dependent upon shared processing not associated with individual differences in manual dexterity.

Reduction of bias and variance for evaluation of computer-aided diagnostic schemes.

PubMed

Li, Qiang; Doi, Kunio

2006-04-01

Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists in detecting various lesions in medical images. In addition to the development, an equally important problem is the reliable evaluation of the performance levels of various CAD schemes. It is good to see that more and more investigators are employing more reliable evaluation methods such as leave-one-out and cross validation, instead of less reliable methods such as resubstitution, for assessing their CAD schemes. However, the common applications of leave-one-out and cross-validation evaluation methods do not necessarily imply that the estimated performance levels are accurate and precise. Pitfalls often occur in the use of leave-one-out and cross-validation evaluation methods, and they lead to unreliable estimation of performance levels. In this study, we first identified a number of typical pitfalls for the evaluation of CAD schemes, and conducted a Monte Carlo simulation experiment for each of the pitfalls to demonstrate quantitatively the extent of bias and/or variance caused by the pitfall. Our experimental results indicate that considerable bias and variance may exist in the estimated performance levels of CAD schemes if one employs various flawed leave-one-out and cross-validation evaluation methods. In addition, for promoting and utilizing a high standard for reliable evaluation of CAD schemes, we attempt to make recommendations, whenever possible, for overcoming these pitfalls. We believe that, with the recommended evaluation methods, we can considerably reduce the bias and variance in the estimated performance levels of CAD schemes.

A twin study of spatial and non-spatial delayed response performance in middle age.

PubMed

Kremen, William S; Mai, Tuan; Panizzon, Matthew S; Franz, Carol E; Blankfeld, Howard M; Xian, Hong; Eisen, Seth A; Tsuang, Ming T; Lyons, Michael J

2011-06-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h(2)=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (r(g)=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high "failure" rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. Copyright © 2011 Elsevier Inc. All rights reserved.

Clusters of cultures: diversity in meaning of family value and gender role items across Europe.

PubMed

van Vlimmeren, Eva; Moors, Guy B D; Gelissen, John P T M

2017-01-01

Survey data are often used to map cultural diversity by aggregating scores of attitude and value items across countries. However, this procedure only makes sense if the same concept is measured in all countries. In this study we argue that when (co)variances among sets of items are similar across countries, these countries share a common way of assigning meaning to the items. Clusters of cultures can then be observed by doing a cluster analysis on the (co)variance matrices of sets of related items. This study focuses on family values and gender role attitudes. We find four clusters of cultures that assign a distinct meaning to these items, especially in the case of gender roles. Some of these differences reflect response style behavior in the form of acquiescence. Adjusting for this style effect impacts on country comparisons hence demonstrating the usefulness of investigating the patterns of meaning given to sets of items prior to aggregating scores into cultural characteristics.

Nonlinear Network Description for Many-Body Quantum Systems in Continuous Space

NASA Astrophysics Data System (ADS)

Ruggeri, Michele; Moroni, Saverio; Holzmann, Markus

2018-05-01

We show that the recently introduced iterative backflow wave function can be interpreted as a general neural network in continuum space with nonlinear functions in the hidden units. Using this wave function in variational Monte Carlo simulations of liquid 4He in two and three dimensions, we typically find a tenfold increase in accuracy over currently used wave functions. Furthermore, subsequent stages of the iteration procedure define a set of increasingly good wave functions, each with its own variational energy and variance of the local energy: extrapolation to zero variance gives energies in close agreement with the exact values. For two dimensional 4He, we also show that the iterative backflow wave function can describe both the liquid and the solid phase with the same functional form—a feature shared with the shadow wave function, but now joined by much higher accuracy. We also achieve significant progress for liquid 3He in three dimensions, improving previous variational and fixed-node energies.

A social relations model of observed family negativity and positivity using a genetically informative sample.

PubMed

Rasbash, Jon; Jenkins, Jennifer; O'Connor, Thomas G; Tackett, Jennifer; Reiss, David

2011-03-01

The goal of this study was to investigate individual and relationship influences on expressions of negativity and positivity in families. Parents and adolescents were observed in a round-robin design in a sample of 687 families. Data were analyzed using a multilevel social relations model. In addition, genetic contributions were estimated for actor effects. Children showed higher mean levels of negativity and lower mean levels of positivity as actors than did parents. Mothers were found to express and elicit higher mean levels of positivity and negativity than fathers. Actor effects were much stronger than partner effects, accounting for between 18%-39% of the variance depending on the actor and the outcome. Genetic (35%) and shared environmental (19%) influences explained a substantial proportion of the actor effect variance for negativity. Dyadic reciprocities were lowest in dyads with a high power differential (i.e., parent-child dyads) and highest for dyads with equal power (sibling and marital dyads). (c) 2011 APA, all rights reserved

A Twin Study of Spatial and Non-Spatial Delayed Response Performance in Middle Age

PubMed Central

Kremen, William S.; Mai, Tuan; Panizzon, Matthew S.; Franz, Carol E.; Blankfeld, Howard M.; Xian, Hong; Eisen, Seth A.; Tsuang, Ming T.; Lyons, Michael J.

2011-01-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h2=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (rg=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high “failure” rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. PMID:21477911

Scope of Attention, Control of Attention, and Intelligence in Children and Adults

PubMed Central

Cowan, Nelson; Fristoe, Nathanael M.; Elliott, Emily M.; Brunner, Ryan P.; Saults, J. Scott

2006-01-01

Recent experimentation has shown that cognitive aptitude measures are predicted by tests of the scope of an individual’s attention or capacity in simple working-memory tasks, and also by the ability to control attention. However, these experiments do not indicate how separate or related the scope and control of attention are. An experiment with 52 children 10 to 11 years old and 52 college students included measures of the scope and control of attention as well as verbal and nonverbal aptitude measures. The children showed little evidence of using sophisticated attentional control, but the scope of attention predicted intelligence in that group. In adults, the scope and control of attention both varied among individuals, and they accounted for considerable individual variance in intelligence. About 1/3 that variance was shared between scope and control, the rest being unique to one or the other. Scope and control of attention appear to be related but distinct contributors to intelligence. PMID:17489300

Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data

USGS Publications Warehouse

Cohn, Timothy A.

2005-01-01

This paper presents an adjusted maximum likelihood estimator (AMLE) that can be used to estimate fluvial transport of contaminants, like phosphorus, that are subject to censoring because of analytical detection limits. The AMLE is a generalization of the widely accepted minimum variance unbiased estimator (MVUE), and Monte Carlo experiments confirm that it shares essentially all of the MVUE's desirable properties, including high efficiency and negligible bias. In particular, the AMLE exhibits substantially less bias than alternative censored‐data estimators such as the MLE (Tobit) or the MLE followed by a jackknife. As with the MLE and the MVUE the AMLE comes close to achieving the theoretical Frechet‐Cramér‐Rao bounds on its variance. This paper also presents a statistical framework, applicable to both censored and complete data, for understanding and estimating the components of uncertainty associated with load estimates. This can serve to lower the cost and improve the efficiency of both traditional and real‐time water quality monitoring.

Partial Variance of Increments Method in Solar Wind Observations and Plasma Simulations

NASA Astrophysics Data System (ADS)

Greco, A.; Matthaeus, W. H.; Perri, S.; Osman, K. T.; Servidio, S.; Wan, M.; Dmitruk, P.

2018-02-01

The method called "PVI" (Partial Variance of Increments) has been increasingly used in analysis of spacecraft and numerical simulation data since its inception in 2008. The purpose of the method is to study the kinematics and formation of coherent structures in space plasmas, a topic that has gained considerable attention, leading the development of identification methods, observations, and associated theoretical research based on numerical simulations. This review paper will summarize key features of the method and provide a synopsis of the main results obtained by various groups using the method. This will enable new users or those considering methods of this type to find details and background collected in one place.

Global self-esteem and method effects: competing factor structures, longitudinal invariance, and response styles in adolescents.

PubMed

Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt

2014-06-01

The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for the RSES and to quantify and predict the method effects. This sample involves two waves (N =2,513 9th-grade and 2,370 10th-grade students) from five waves of a school-based longitudinal study. The RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained a large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style and found that being a girl and having a higher number of depressive symptoms were associated with both low self-esteem and negative response style, as measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents.

Global self-esteem and method effects: competing factor structures, longitudinal invariance and response styles in adolescents

PubMed Central

Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt

2013-01-01

The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for RSES; and to quantify and predict the method effects. This sample involves two waves (N=2513 ninth-grade and 2370 tenth-grade students) from five waves of a school-based longitudinal study. RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style, and found that being a girl and having higher number of depressive symptoms were associated with both low self-esteem and negative response style measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents. PMID:24061931

Stereotyped behavior of severely disabled children in classroom and free-play settings.

PubMed

Thompson, T J; Berkson, G

1985-05-01

The relationships between stereotyped behavior, object manipulation, self-manipulation, teacher attention, and various developmental measures were examined in 101 severely developmentally disabled children in their classrooms and a free-play setting. Stereotyped behavior without objects was positively correlated with self-manipulation and CA and was negatively correlated with complex object manipulation, developmental age, developmental quotient, and teacher attention. Stereotyped behavior with objects was negatively correlated with complex object manipulation. Partial correlations showed that age, self-manipulation, and developmental age shared unique variance with stereotyped behavior without objects.

Some variance reduction methods for numerical stochastic homogenization.

PubMed

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares

PubMed Central

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Mur, Marieke

2016-01-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as “human”, “mammal”, and “animal”). The feature-based model includes both object parts (such as “eye”, “tail”, and “handle”) and other descriptive features (such as “circular”, “green”, and “stubbly”). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation. Similarity judgments contain additional categorical variance that is not explained by visual features, reflecting a higher-level more purely semantic representation. PMID:26493748

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares.

PubMed

Jozwik, Kamila M; Kriegeskorte, Nikolaus; Mur, Marieke

2016-03-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as "human", "mammal", and "animal"). The feature-based model includes both object parts (such as "eye", "tail", and "handle") and other descriptive features (such as "circular", "green", and "stubbly"). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation. Similarity judgments contain additional categorical variance that is not explained by visual features, reflecting a higher-level more purely semantic representation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Psychometric properties of the positive and negative affect schedule (PANAS) in a heterogeneous sample of substance users

PubMed Central

Serafini, Kelly; Malin-Mayor, Bo; Nich, Charla; Hunkele, Karen; Carroll, Kathleen M.

2016-01-01

Background The Positive and Negative Affect Schedule (PANAS) is a widely used measure of affect, and a comprehensive psychometric evaluation has never been conducted among substance users. Objective To examine the psychometric properties of the PANAS in a sample of outpatient treatment substance users. Methods We used pooled data from four randomized clinical trials (N = 416; 34% female, 48% African American). Results A confirmatory factor analysis indicated adequate support for a two-factor correlated model comprised of Positive Affect and Negative Affect with correlated item errors (Comparative Fit Index = .93, Root Mean Square Error of Approximation = .07, χ2 = 478.93, df = 156). Cronbach’s α indicated excellent internal consistency for both factors (.90 and .91, respectively). The PANAS factors had good convergence and discriminability (Composite Reliability >.7; Maximum Shared Variance < Average Variance Extracted). A comparison from baseline to Week 1 indicated acceptable test-retest reliability (Positive Affect = .80, Negative Affect = .76). Concurrent and discriminant validity were demonstrated with correlations with the Brief Symptom Inventory and Addiction Severity Index. The PANAS scores were also significantly correlated with treatment outcomes (e.g., Positive Affect was associated with the maximum days of consecutive abstinence from primary substance of abuse, r = .16, p = .001). Conclusion Our data suggest that the psychometric properties of the PANAS are retained in substance using populations. Although several studies have focused on the role of Negative Affect, our findings suggest that Positive Affect may also be an important factor in substance use treatment outcomes. PMID:26905228

Synthetic thermosphere winds based on CHAMP neutral and plasma density measurements

NASA Astrophysics Data System (ADS)

Gasperini, F.; Forbes, J. M.; Doornbos, E. N.; Bruinsma, S. L.

2016-04-01

Meridional winds in the thermosphere are key to understanding latitudinal coupling and thermosphere-ionosphere coupling, and yet global measurements of this wind component are scarce. In this work, neutral and electron densities measured by the Challenging Minisatellite Payload (CHAMP) satellite at solar low and geomagnetically quiet conditions are converted to pressure gradient and ion drag forces, which are then used to solve the horizontal momentum equation to estimate low latitude to midlatitude zonal and meridional "synthetic" winds. We validate the method by showing that neutral and electron densities output from National Center for Atmospheric Research (NCAR) Thermosphere Ionosphere Mesosphere Electrodynamics-General Circulation Model (TIME-GCM) can be used to derive solutions to the momentum equations that replicate reasonably well (over 85% of the variance) the winds self-consistently calculated within the TIME-GCM. CHAMP cross-track winds are found to share over 65% of the variance with the synthetic zonal winds, providing further reassurance that this wind product should provide credible results. Comparisons with the Horizontal Wind Model 14 (HWM14) show that the empirical model largely underestimates wind speeds and does not reproduce much of the observed variability. Additionally, in this work we reveal the longitude, latitude, local time, and seasonal variability in the winds; show evidence of ionosphere-thermosphere (IT) coupling, with enhanced postsunset eastward winds due to depleted ion drag; demonstrate superrotation speeds of ˜27 m/s at the equator; discuss vertical wave coupling due the diurnal eastward propagating tide with zonal wave number 3 and the semidiurnal eastward propagating tide with zonal wave number 2.

Persistence and innovation effects in genetic and environmental factors in negative emotionality during infancy: A twin study

PubMed Central

Boivin, Michel; Paquin, Stéphane; Lacourse, Eric; Brendgen, Mara; Vitaro, Frank; Dionne, Ginette; Tremblay, Richard E.; Booij, Linda

2017-01-01

Background Difficult temperament in infancy is a risk factor for forms of later internalizing and externalizing psychopathology, including depression and anxiety. A better understanding of the roots of difficult temperament requires assessment of its early development with a genetically informative design. The goal of this study was to estimate genetic and environmental contributions to individual differences in infant negative emotionality, their persistence over time and their influences on stability between 5 and 18 months of age. Method Participants were 244 monozygotic and 394 dizygotic twin pairs (49.7% male) recruited from birth. Mothers rated their twins for negative emotionality at 5 and 18 months. Longitudinal analysis of stability and innovation between the two time points was performed in Mplus. Results There were substantial and similar heritability (approximately 31%) and shared environmental (57.3%) contributions to negative emotionality at both 5 and 18 months. The trait’s interindividual stability across time was both genetically- and environmentally- mediated. Evidence of innovative effects (i.e., variance at 18 months independent from variance at 5 months) indicated that negative emotionality is developmentally dynamic and affected by persistent and new genetic and environmental factors at 18 months. Conclusions In the first two years of life, ongoing genetic and environmental influences support temperamental negative emotionality but new genetic and environmental factors also indicate dynamic change of those factors across time. A better understanding of the source and timing of factors on temperament in early development, and role of sex, could improve efforts to prevent related psychopathology. PMID:28448561

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.

Fuel cell stack monitoring and system control

DOEpatents

Keskula, Donald H.; Doan, Tien M.; Clingerman, Bruce J.

2004-02-17

A control method for monitoring a fuel cell stack in a fuel cell system in which the actual voltage and actual current from the fuel cell stack are monitored. A preestablished relationship between voltage and current over the operating range of the fuel cell is established. A variance value between the actual measured voltage and the expected voltage magnitude for a given actual measured current is calculated and compared with a predetermined allowable variance. An output is generated if the calculated variance value exceeds the predetermined variance. The predetermined voltage-current for the fuel cell is symbolized as a polarization curve at given operating conditions of the fuel cell.

Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2017-10-01

The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

NASA Astrophysics Data System (ADS)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

PubMed Central

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

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

Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com; Yusof, Fadhilah, E-mail: fadhilahy@utm.my; Daud, Zalina Mohd, E-mail: zalina@ic.utm.my

Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during themore » monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.« less

Social Science Methods for Twins Data: Integrating Causality, Endowments and Heritability

PubMed Central

Kohler, Hans-Peter; Behrman, Jere R.; Schnittker, Jason

2011-01-01

Twins have been extensively used in economics, sociology and behavioral genetics to investigate the role of genetic endowments on a broad range of social, demographic and economic outcomes. However, the focus in these literatures has been distinct: the economic literature has been primarily concerned with the need to control for unobserved endowments—including as an important subset, genetic endowments—in analyses that attempt to establish the impact of one variable, often schooling, on a variety of economic, demographic and health outcomes. Behavioral genetic analyses have mostly been concerned with decomposing the variation in the outcomes of interest into genetic, shared environmental and non-shared environmental components, with recent multivariate analyses investigating the contributions of genes and the environment to the correlation and causation between variables. Despite the fact that twins studies and the recognition of the role of endowments are central to both of these literatures, they have mostly evolved independently. In this paper we develop formally the relationship between the economic and behavioral genetic approaches to the analyses of twins, and we develop an integrative approach that combines the identification of causal effects, which dominates the economic literature, with the decomposition of variances and covariances into genetic and environmental factors that is the primary goal of behavioral genetic approaches. We apply this integrative ACE-β approach to an illustrative investigation of the impact of schooling on several demographic outcomes such as fertility and nuptiality and health. PMID:21845929

AN EXAMINATION OF THE OVERLAP BETWEEN GENETIC AND ENVIRONMENTAL RISK FACTORS FOR INTENTIONAL WEIGHT LOSS AND OVEREATING

PubMed Central

Wade, Tracey D.; Treloar, Susan A.; Heath, Andrew C.; Martin, Nicholas G

2009-01-01

Objective In order to further our understanding of how intentional weight loss (IWL) and overeating are related, we examined the shared genetic and environmental variance between lifetime IWL and overeating. Methods Interview data were available for 1976 female twins (both members of 439 and 264 pairs of monozygotic and dizygotic twins respectively), mean age=40.61, SD=4.72. We used lifetime diagnostic data for eating disorders obtained from a semi-structured psychiatric telephone interview, examined in a bivariate twin analysis. Both lifetime behaviours were measured on a 3-point scale, where absence of IWL or overeating formed one anchor on the scale and lifetime anorexia nervosa (AN) and bulimia nervosa (BN) formed the opposite anchors respectively. Results In line with previous findings, a higher body mass index was significantly associated with the lifetime presence of IWL and/or overeating (odds ratio=1.13, 95% confidence interval (CI): 1.08–1.19). The best fitting twin model contained additive genetic and non-shared environmental influence influencing both IWL and overeating, with correlations between these influences of 0.61 (95% CI: 0.35–0.92) and 0.24 (95% CI: 0.07–0.42) respectively. Conclusion About 37% of genetic risk factors were considered to overlap between IWL and overeating, and with only 6% of overlap between environmental risk factors. Thus considerable independence of risk factors was indicated. PMID:19235851

Optimal Superpositioning of Flexible Molecule Ensembles

PubMed Central

Gapsys, Vytautas; de Groot, Bert L.

2013-01-01

Analysis of the internal dynamics of a biological molecule requires the successful removal of overall translation and rotation. Particularly for flexible or intrinsically disordered peptides, this is a challenging task due to the absence of a well-defined reference structure that could be used for superpositioning. In this work, we started the analysis with a widely known formulation of an objective for the problem of superimposing a set of multiple molecules as variance minimization over an ensemble. A negative effect of this superpositioning method is the introduction of ambiguous rotations, where different rotation matrices may be applied to structurally similar molecules. We developed two algorithms to resolve the suboptimal rotations. The first approach minimizes the variance together with the distance of a structure to a preceding molecule in the ensemble. The second algorithm seeks for minimal variance together with the distance to the nearest neighbors of each structure. The newly developed methods were applied to molecular-dynamics trajectories and normal-mode ensembles of the Aβ peptide, RS peptide, and lysozyme. These new (to our knowledge) superpositioning methods combine the benefits of variance and distance between nearest-neighbor(s) minimization, providing a solution for the analysis of intrinsic motions of flexible molecules and resolving ambiguous rotations. PMID:23332072

Genetic variance of tolerance and the toxicant threshold model.

PubMed

Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

2012-04-01

A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change. Copyright © 2012 SETAC.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Analytic variance estimates of Swank and Fano factors

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

Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov

Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data frommore » a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.« less