Internet Gaming Disorder Explains Unique Variance in Psychological Distress and Disability After Controlling for Comorbid Depression, OCD, ADHD, and Anxiety.

PubMed

Pearcy, Benjamin T D; McEvoy, Peter M; Roberts, Lynne D

2017-02-01

This study extends knowledge about the relationship of Internet Gaming Disorder (IGD) to other established mental disorders by exploring comorbidities with anxiety, depression, Attention Deficit Hyperactivity Disorder (ADHD), and obsessive compulsive disorder (OCD), and assessing whether IGD accounts for unique variance in distress and disability. An online survey was completed by a convenience sample that engages in Internet gaming (N = 404). Participants meeting criteria for IGD based on the Personal Internet Gaming Disorder Evaluation-9 (PIE-9) reported higher comorbidity with depression, OCD, ADHD, and anxiety compared with those who did not meet the IGD criteria. IGD explained a small proportion of unique variance in distress (1%) and disability (3%). IGD accounted for a larger proportion of unique variance in disability than anxiety and ADHD, and a similar proportion to depression. Replications with clinical samples using longitudinal designs and structured diagnostic interviews are required.

In vivo recovery of factor VIII and factor IX: intra- and interindividual variance in a clinical setting.

PubMed

Björkman, S; Folkesson, A; Berntorp, E

2007-01-01

In vivo recovery (IVR) is traditionally used as a parameter to characterize the pharmacokinetic properties of coagulation factors. It has also been suggested that dosing of factor VIII (FVIII) and factor IX (FIX) can be adjusted according to the need of the individual patient, based on an individually determined IVR value. This approach, however, requires that the individual IVR value is more reliably representative for the patient than the mean value in the population, i.e. that there is less variance within than between the individuals. The aim of this investigation was to compare intra- and interindividual variance in IVR (as U dL1 per U kg1) for FVIII and plasma-derived FIX in a cohort of non-bleeding patients with haemophilia. The data were collected retrospectively from six clinical studies, yielding 297 IVR determinations in 50 patients with haemophilia A and 93 determinations in 13 patients with haemophilia B. For FVIII, the mean variance within patients exceeded the between-patient variance. Thus, an individually determined IVR value is apparently no more informative than an average, or population, value for the dosing of FVIII. There was no apparent relationship between IVR and age of the patient (1.5-67 years). For FIX, the mean variance within patients was lower than the between-patient variance, and there was a significant positive relationship between IVR and age (13-69 years). From these data, it seems probable that using an individual IVR confers little advantage in comparison to using an age-specific population mean value. Dose tailoring of coagulation factor treatment has been applied successfully after determination of the entire single-dose curve of FVIII:C or FIX:C in the patient and calculation of the relevant pharmacokinetic parameters. However, the findings presented here do not support the assumption that dosing of FVIII or FIX can be individualized on the basis of a clinically determined IVR value.

An examination of multilevel factors that may explain gender differences in children's physical activity.

PubMed

Crespo, Noe C; Corder, Kirsten; Marshall, Simon; Norman, Gregory J; Patrick, Kevin; Sallis, Jim F; Elder, John P

2013-09-01

Girls are less physically active than boys, yet no single study has examined the factors that may explain gender differences in children's physical activity (PA). This study was a cross-sectional analysis of data from 116 caregivers and their children aged 5-8 years who participated in the MOVE study. Caregivers reported various factors that may relate to children's PA (eg, encouragement for child PA and PA equipment at home). Child PA was measured by 7-day accelerometry. Linear regression tested for the variance in moderate-to-vigorous physical activity (MVPA) explained by gender and several variables. Gender and ethnicity interactions were examined. Caregivers were mostly female (97%), mean age 38 ± 6 years, mean BMI 28 ± 6 (kg/m2). Child's mean age was 8.1 ± 0.7, 54% were female and 40% were overweight/obese. Girls were less physically active than boys (54.1 ± 19.7 vs. 65.2 ± 28.0 daily minutes of MVPA, respectively). Among girls, more days of PE/week was associated with greater MVPA. Among boys, greater parent support for PA, greater parent modeling for PA, and greater number of PA equipment in the home were associated with greater MVPA. This study supports that boys and girls have different correlates for MVPA, which may partly explain gender differences in PA.

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2018-05-01

Spontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These "resting state networks" (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a nonstationary process which could be described as state switching. In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal. We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also report some interesting characteristics that clearly support nonstationary features in the data. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics. Copyright © 2018 Elsevier Inc. All rights reserved.

Explaining mastitis incidence in Dutch dairy farming: the influence of farmers' attitudes and behaviour.

PubMed

Jansen, J; van den Borne, B H P; Renes, R J; van Schaik, G; Lam, T J G M; Leeuwis, C

2009-11-15

When mastitis incidence increases, either infection pressure has increased or cows' resistance has decreased. This usually indicates that farm management is not optimal. Numerous quantitative studies have demonstrated the effect of management practices on mastitis. In most of these studies, the identified risk factors could explain only part of the variance in mastitis incidence on farms. Several studies suggest that the unexplained variance is caused by farmers' attitudes towards different aspects of mastitis treatment and preventive behaviour. This study aims to determine, to quantify and to specify the extent to which farmers' attitudes, over and above farmers' behaviour, are factors that explain the variation in mastitis incidence, measured in terms of the quantifiable effect of management factors. An extensive survey on self-reported attitudes, behaviour and mastitis incidence was conducted on 336 Dutch dairy farms. Results of multiple linear regression analyses show that farmers' self-reported behaviour and attitudes together explain 48%, 31% and 23% of the variation within, respectively, the average farm bulk milk somatic cell count (BMSCC), the clinical mastitis incidence and the combined clinical and subclinical mastitis incidence. Both behaviour and attitudes explain part of the variance. However, most of the variance in all three dependant measures is explained solely by the attitude variables. The variation in BMSCC value is best explained by (1) farmers' normative frame of reference about mastitis, (2) farmers' perceptions about the control of mastitis and (3) the perceived effect of a BMSCC penalty level. The variation in clinical mastitis is best explained by farmers' perceptions about mastitis control. The variation in the combined clinical and subclinical mastitis incidence rate is best explained by the perceived effect of a BMSCC penalty level and the frequency of contact with others. The results of this study show that farmers' attitudes are a

Individual factors explain neighbourhood variations in accidents to children under 5 years of age.

PubMed

Reading, Richard; Jones, Andrew; Haynes, Robin; Daras, Konstantinos; Emond, Alan

2008-09-01

Previous studies have identified possible neighbourhood-level influences on the risk of injuries to preschool children, but none have had sufficient data at both household and area level to explain these neighbourhood effects. We used data from the Avon Longitudinal Study of Parents and Children, which recruited over 14,062 children at birth in the former county of Avon, UK, and collected information about accidents, as well as extensive social, health and developmental data throughout the first 5 years of life. This information was combined with census and geographical data in order to identify neighbourhood influences on accident risks and then attempt to explain these using multilevel regression modelling. A small but statistically significant amount of between-neighbourhood variance in accident risk was found, with neighbourhood intraclass correlation coefficients of 0.82% for any accident, and 0.84% for accidents resulting in injury requiring medical attention. This was entirely accounted for by a variety of child, parental and household level variables. Independent risk factors for both outcomes were children who were developmentally more advanced or displayed greater conduct and behavioural problems, mothers who were of younger age, who were without work, who were smokers, whose partners were unemployed or drank alcohol excessively, and households in which there had recently been adverse life events, or which were under financial stress. The mother's perceptions of neighbourhood quality also explained some of the risks for any accident, but not for medically attended accidents, and this was a variable that operated at the level of individual households rather than at the level of neighbourhoods. The implications of this study are that differences in accident risk between neighbourhoods are explained by geographical clustering of similar types of children, families and households. Interventions should focus more on parental factors and household social

Quantifying cosmic variance

NASA Astrophysics Data System (ADS)

Driver, Simon P.; Robotham, Aaron S. G.

2010-10-01

We determine an expression for the cosmic variance of any `normal' galaxy survey based on examination of M* +/- 1 mag galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) data cube. We find that cosmic variance will depend on a number of factors principally: total survey volume, survey aspect ratio and whether the area surveyed is contiguous or comprising independent sightlines. As a rule of thumb cosmic variance falls below 10 per cent once a volume of 107h-30.7Mpc3 is surveyed for a single contiguous region with a 1:1 aspect ratio. Cosmic variance will be lower for higher aspect ratios and/or non-contiguous surveys. Extrapolating outside our test region we infer that cosmic variance in the entire SDSS DR7 main survey region is ~7 per cent to z < 0.1. The equation obtained from the SDSS DR7 region can be generalized to estimate the cosmic variance for any density measurement determined from normal galaxies (e.g. luminosity densities, stellar mass densities and cosmic star formation rates) within the volume range 103-107h-30.7Mpc3. We apply our equation to show that two sightlines are required to ensure that cosmic variance is <10 per cent in any ASKAP galaxy survey (divided into Δ z ~ 0.1 intervals, i.e. ~1Gyr intervals for z < 0.5). Likewise 10 MeerKAT sightlines will be required to meet the same conditions. GAMA, VVDS and zCOSMOS all suffer less than 10 per cent cosmic variance (~3-8 per cent) in Δ z intervals of 0.1, 0.25 and 0.5, respectively. Finally we show that cosmic variance is potentially at the 50-70 per cent level, or greater, in the Hubble Space Telescope (HST) Ultra Deep Field depending on assumptions as to the evolution of clustering. 100 or 10 independent sightlines will be required to reduce cosmic variance to a manageable level (<10 per cent) for HST ACS or HST WFC3 surveys, respectively (in Δ z ~ 1 intervals). Cosmic variance is therefore a significant factor in the z > 6 HST studies currently underway.

Age-related variance in decisions under ambiguity is explained by changes in reasoning, executive functions, and decision-making under risk.

PubMed

Schiebener, Johannes; Brand, Matthias

2017-06-01

Previous literature has explained older individuals' disadvantageous decision-making under ambiguity in the Iowa Gambling Task (IGT) by reduced emotional warning signals preceding decisions. We argue that age-related reductions in IGT performance may also be explained by reductions in certain cognitive abilities (reasoning, executive functions). In 210 participants (18-86 years), we found that the age-related variance on IGT performance occurred only in the last 60 trials. The effect was mediated by cognitive abilities and their relation with decision-making performance under risk with explicit rules (Game of Dice Task). Thus, reductions in cognitive functions in older age may be associated with both a reduced ability to gain explicit insight into the rules of the ambiguous decision situation and with failure to choose the less risky options consequently after the rules have been understood explicitly. Previous literature may have underestimated the relevance of cognitive functions for age-related decline in decision-making performance under ambiguity.

Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.

PubMed

Rönnegård, L; Felleki, M; Fikse, W F; Mulder, H A; Strandberg, E

2013-04-01

Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Cognitive risk factors explain the relations between neuroticism and social anxiety for males and females.

PubMed

Allan, Nicholas P; Oglesby, Mary E; Uhl, Aubree; Schmidt, Norman B

2017-04-01

The hierarchical model of vulnerabilities to emotional distress contextualizes the relation between neuroticism and social anxiety as occurring indirectly through cognitive risk factors. In particular, inhibitory intolerance of uncertainty (IU; difficulty in uncertain circumstances), fear of negative evaluation (FNE; fear of being judged negatively), and anxiety sensitivity (AS) social concerns (fear of outwardly observable anxiety) are related to social anxiety. It is unclear whether these risk factors uniquely relate to social anxiety, and whether they account for the relations between neuroticism and social anxiety. The indirect relations between neuroticism and social anxiety through these and other risk factors were examined using structural equation modeling in a sample of 462 individuals (M age = 36.56, SD = 12.93; 64.3% female). Results indicated that the relations between neuroticism and social anxiety could be explained through inhibitory IU, FNE, and AS social concerns. No gender differences were found. These findings provide support for the hierarchical model of vulnerabilities to emotional distress disorders, although the cognitive risk factors accounted for variance beyond their contribution to the relation between neuroticism and social anxiety, suggesting a more complex model than that expressed in the hierarchical model of vulnerabilities.

Speed Variance and Its Influence on Accidents.

ERIC Educational Resources Information Center

Garber, Nicholas J.; Gadirau, Ravi

A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robust Programming Problems Based on the Mean-Variance Model Including Uncertainty Factors

NASA Astrophysics Data System (ADS)

Hasuike, Takashi; Ishii, Hiroaki

2009-01-01

This paper considers robust programming problems based on the mean-variance model including uncertainty sets and fuzzy factors. Since these problems are not well-defined problems due to fuzzy factors, it is hard to solve them directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed models are transformed into the deterministic equivalent problems. Furthermore, in order to solve these equivalent problems efficiently, the solution method is constructed introducing the mean-absolute deviation and doing the equivalent transformations.

Key factors in children's competence to consent to clinical research.

PubMed

Hein, Irma M; Troost, Pieter W; Lindeboom, Robert; Benninga, Marc A; Zwaan, C Michel; van Goudoever, Johannes B; Lindauer, Ramón J L

2015-10-24

Although law is established on a strong presumption that persons younger than a certain age are not competent to consent, statutory age limits for asking children's consent to clinical research differ widely internationally. From a clinical perspective, competence is assumed to involve many factors including the developmental stage, the influence of parents and peers, and life experience. We examined potential determining factors for children's competence to consent to clinical research and to what extent they explain the variation in competence judgments. From January 1, 2012 through January 1, 2014, pediatric patients aged 6 to 18 years, eligible for clinical research studies were enrolled prospectively at various in- and outpatient pediatric departments. Children's competence to consent was assessed by MacArthur Competence Assessment Tool for Clinical Research. Potential determining child variables included age, gender, intelligence, disease experience, ethnicity and socio-economic status (SES). We used logistic regression analysis and change in explained variance in competence judgments to quantify the contribution of a child variable to the total explained variance. Contextual factors included risk and complexity of the decision to participate, parental competence judgment and the child's or parents decision to participate. Out of 209 eligible patients, 161 were included (mean age, 10.6 years, 47.2 % male). Age, SES, intelligence, ethnicity, complexity, parental competence judgment and trial participation were univariately associated with competence (P < 0.05). Total explained variance in competence judgments was 71.5 %. Only age and intelligence significantly and independently explained the variance in competence judgments, explaining 56.6 % and 12.7 % of the total variance respectively. SES, male gender, disease experience and ethnicity each explained less than 1 % of the variance in competence judgments. Contextual factors together explained an extra 2

Critical Factors Explaining the Leadership Performance of High-Performing Principals

ERIC Educational Resources Information Center

Hutton, Disraeli M.

2018-01-01

The study explored critical factors that explain leadership performance of high-performing principals and examined the relationship between these factors based on the ratings of school constituents in the public school system. The principal component analysis with the use of Varimax Rotation revealed that four components explain 51.1% of the…

On the Endogeneity of the Mean-Variance Efficient Frontier.

ERIC Educational Resources Information Center

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study

PubMed Central

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-01-01

Objectives Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. Setting The USA, the UK and France. Participants A total of 2412 participants were surveyed across the three countries. Outcome measures Self-reported influenza vaccination. Methods Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. Results The models were able to explain 64%–80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Conclusions Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public’s views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. PMID:28706088

Predicting College Success: The Relative Contributions of Five Social/Personality Factors, Five Cognitive/Learning Factors, and SAT Scores

PubMed Central

Hannon, Brenda

2014-01-01

To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results revealed many significant predictors of GPA for both freshmen and non-freshmen. However, subsequent regressions showed that only academic self-efficacy, epistemic belief of learning, and high-knowledge integration explained unique variance in GPA (19%-freshmen, 23.2%-non-freshmen). Further for freshmen, SAT scores explained an additional unique 10.6% variance after the influences attributed to these three predictors was removed whereas for non-freshmen, SAT scores failed to explain any additional variance. These results highlight the unique and important contributions of academic self-efficacy, epistemic belief of learning and high-knowledge integration to GPA beyond other previously-identified predictors. PMID:25568884

Explaining the Sex Difference in Dyslexia

ERIC Educational Resources Information Center

Arnett, Anne B.; Pennington, Bruce F.; Peterson, Robin L.; Willcutt, Erik G.; DeFries, John C.; Olson, Richard K.

2017-01-01

Background: Males are diagnosed with dyslexia more frequently than females, even in epidemiological samples. This may be explained by greater variance in males' reading performance. Methods: We expand on previous research by rigorously testing the variance difference theory, and testing for mediation of the sex difference by cognitive correlates.…

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

PubMed

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/m(2)) 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, h (2) = 0.58), WC (h (2) = 0.57), and FA (h (2) = 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.

Clock Genes Explain a Large Proportion of Phenotypic Variance in Systolic Blood Pressure and This Control Is Not Modified by Environmental Temperature.

PubMed

Dashti, Hassan S; Aslibekyan, Stella; Scheer, Frank A J L; Smith, Caren E; Lamon-Fava, Stefania; Jacques, Paul; Lai, Chao-Qiang; Tucker, Katherine L; Arnett, Donna K; Ordovás, José M

2016-01-01

Diurnal variation in blood pressure (BP) is regulated, in part, by an endogenous circadian clock; however, few human studies have identified associations between clock genes and BP. Accounting for environmental temperature may be necessary to correct for seasonal bias. We examined whether environmental temperature on the day of participants' assessment was associated with BP, using adjusted linear regression models in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) (n = 819) and the Boston Puerto Rican Health Study (BPRHS) (n = 1,248) cohorts. We estimated phenotypic variance in BP by 18 clock genes and examined individual single-nucleotide polymorphism (SNP) associations with BP using an additive genetic model, with further consideration of environmental temperature. In GOLDN, each additional 1 °C increase in environmental temperature was associated with 0.18 mm Hg lower systolic BP [SBP; β ± SE = -0.18 ± 0.05 mm Hg; P = 0.0001] and 0.10mm Hg lower diastolic BP [DBP; -0.10 ± 0.03 mm Hg; P = 0.001]. Similar results were seen in the BPRHS for SBP only. Clock genes explained a statistically significant proportion of the variance in SBP [V G/V P ± SE = 0.071 ± 0.03; P = 0.001] in GOLDN, but not in the BPRHS, and we did not observe associations between individual SNPs and BP. Environmental temperature did not influence the identified genetic associations. We identified clock genes that explained a statistically significant proportion of the phenotypic variance in SBP, supporting the importance of the circadian pathway underlying cardiac physiology. Although temperature was associated with BP, it did not affect results with genetic markers in either study. Therefore, it does not appear that temperature measures are necessary for interpreting associations between clock genes and BP. Trials related to this study were registered at clinicaltrials.gov as NCT00083369 (Genetic and Environmental Determinants of Triglycerides) and NCT01231958 (Boston Puerto

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study.

PubMed

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-07-12

Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. The USA, the UK and France. A total of 2412 participants were surveyed across the three countries. Self-reported influenza vaccination. Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. The models were able to explain 64%-80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public's views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A study into psychosocial factors as predictors of work-related fatigue.

PubMed

Rahman, Hanif Abdul; Abdul-Mumin, Khadizah; Naing, Lin

2016-07-14

To explore and determine relationship between psychosocial factors and work-related fatigue among emergency and critical care nurses in Brunei. Cross-sectional study conducted on all emergency and critical care nurses across Brunei public hospitals from February to April 2016. 201 nurses participated in the study (82% response rate). A total of 36% of the variance of chronic fatigue was explained by stress, trust in management, decision latitude, self-rated health, and work-family conflict. Burnout, self-rated health, commitment to workplace, and trust in management explained 30% of the variance of acute fatigue. Stress, work-family conflict and reward explained 28% of the variance of intershift recovery after controlling for significant sociodemographic variables. Smoking was identified as an important sociodemographic factor for work-related fatigue. Psychosocial factors were good predictors of work-related fatigue. A range of psychosocial factors were established, however more research is required to determine all possible causation factors of nurses' work-related fatigue.

Explaining variance in self-directed learning readiness of first year students in health professional programs.

PubMed

Slater, Craig E; Cusick, Anne; Louie, Jimmy C Y

2017-11-13

Self-directed learning (SDL) is expected of health science graduates; it is thus a learning outcome in many pre-certification programs. Previous research identified age, gender, discipline and prior education as associated with variations in students' self-directed learning readiness (SDLR). Studies in other fields also propose personality as influential. This study investigated relationships between SDLR and age, gender, discipline, previous education, and personality traits. The Self-Directed Learning Readiness Scale and the 50-item 'big five' personality trait inventory were administered to 584 first-year undergraduate students (n = 312 female) enrolled in a first-session undergraduate interprofessional health sciences subject. Students were from health promotion, health services management, therapeutic recreation, sports and exercise science, occupational therapy, physiotherapy, and podiatry. Four hundred and seven responses (n = 230 females) were complete. SDLR was significantly higher in females and students in occupational therapy and physiotherapy. SDLR increased with age and higher levels of previous education. It was also significantly associated with 'big five' personality trait scores. Regression analysis revealed 52.9% of variance was accounted for by personality factors, discipline and prior experience of tertiary education. Demographic, discipline and personality factors are associated with SDLR in the first year of study. Teachers need to be alert to individual student variation in SDLR.

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

Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

Parents of children with cancer: which factors explain differences in health-related quality of life.

PubMed

Klassen, Anne F; Raina, Parminder; McIntosh, Cameron; Sung, Lillian; Klaassen, Robert J; O'Donnell, Maureen; Yanofsky, Rochelle; Dix, David

2011-09-01

Research with parents of children with cancer has identified factors related to their adjustment and coping, but it is not fully understood why some parents do well and others do not. Guided by a stress process model, we examined the interrelationships among a comprehensive set of factors to identify the most important determinants of health-related quality of life (HRQoL) in parents of children in active treatment for cancer. A cross-sectional survey of 411 parents (80% response rate) of children receiving cancer treatment in Canada was conducted between November 2004 and February 2007. The following constructs were measured: background and context factors, child characteristics, family-centered service delivery, caregiver strain, intrapsychic factors, coping/supportive factors and parental HRQoL. The model was evaluated using structural equation modeling. Analysis was stratified by time since diagnosis (i.e., <12 months and ≥12 months). For those within 12 months of their child's diagnosis, family-centred service provision, caregiver strain, and self-perception accounted for 58% of the variation in psychosocial health, whereas caregiver strain and social support explained 50% of the variation in physical health. For parents in the >12 month group, caregiving strain was the only factor with a direct relationship with parental psychosocial and physical health, accounting for 66% and 55% of the variance in these constructs, respectively. Our findings reinforce the need for health professionals to be particularly attuned to family caregivers in the early stages of treatment and identify potential areas for interventions to promote parental health. Copyright © 2010 UICC.

Explaining the sex difference in dyslexia.

PubMed

Arnett, Anne B; Pennington, Bruce F; Peterson, Robin L; Willcutt, Erik G; DeFries, John C; Olson, Richard K

2017-06-01

Males are diagnosed with dyslexia more frequently than females, even in epidemiological samples. This may be explained by greater variance in males' reading performance. We expand on previous research by rigorously testing the variance difference theory, and testing for mediation of the sex difference by cognitive correlates. We developed an analytic framework that can be applied to group differences in any psychiatric disorder. Males' overrepresentation in the low performance tail of the reading distribution was accounted for by mean and variance differences across sex. There was no sex difference at the high performance tail. Processing speed (PS) and inhibitory control partially mediated the sex difference. Verbal reasoning emerged as a strength in males. Our results complement a previous finding that PS partially mediates the sex difference in symptoms of attention deficit/hyperactivity disorder (ADHD), and helps explain the sex difference in both dyslexia and ADHD and their comorbidity. © 2017 Association for Child and Adolescent Mental Health.

Examining age-related shared variance between face cognition, vision, and self-reported physical health: a test of the common cause hypothesis for social cognition

PubMed Central

Olderbak, Sally; Hildebrandt, Andrea; Wilhelm, Oliver

2015-01-01

The shared decline in cognitive abilities, sensory functions (e.g., vision and hearing), and physical health with increasing age is well documented with some research attributing this shared age-related decline to a single common cause (e.g., aging brain). We evaluate the extent to which the common cause hypothesis predicts associations between vision and physical health with social cognition abilities specifically face perception and face memory. Based on a sample of 443 adults (17–88 years old), we test a series of structural equation models, including Multiple Indicator Multiple Cause (MIMIC) models, and estimate the extent to which vision and self-reported physical health are related to face perception and face memory through a common factor, before and after controlling for their fluid cognitive component and the linear effects of age. Results suggest significant shared variance amongst these constructs, with a common factor explaining some, but not all, of the shared age-related variance. Also, we found that the relations of face perception, but not face memory, with vision and physical health could be completely explained by fluid cognition. Overall, results suggest that a single common cause explains most, but not all age-related shared variance with domain specific aging mechanisms evident. PMID:26321998

Mapping information exposure on social media to explain differences in HPV vaccine coverage in the United States.

PubMed

Dunn, Adam G; Surian, Didi; Leask, Julie; Dey, Aditi; Mandl, Kenneth D; Coiera, Enrico

2017-05-25

Together with access, acceptance of vaccines affects human papillomavirus (HPV) vaccine coverage, yet little is known about media's role. Our aim was to determine whether measures of information exposure derived from Twitter could be used to explain differences in coverage in the United States. We conducted an analysis of exposure to information about HPV vaccines on Twitter, derived from 273.8 million exposures to 258,418 tweets posted between 1 October 2013 and 30 October 2015. Tweets were classified by topic using machine learning methods. Proportional exposure to each topic was used to construct multivariable models for predicting state-level HPV vaccine coverage, and compared to multivariable models constructed using socioeconomic factors: poverty, education, and insurance. Outcome measures included correlations between coverage and the individual topics and socioeconomic factors; and differences in the predictive performance of the multivariable models. Topics corresponding to media controversies were most closely correlated with coverage (both positively and negatively); education and insurance were highest among socioeconomic indicators. Measures of information exposure explained 68% of the variance in one dose 2015 HPV vaccine coverage in females (males: 63%). In comparison, models based on socioeconomic factors explained 42% of the variance in females (males: 40%). Measures of information exposure derived from Twitter explained differences in coverage that were not explained by socioeconomic factors. Vaccine coverage was lower in states where safety concerns, misinformation, and conspiracies made up higher proportions of exposures, suggesting that negative representations of vaccines in the media may reflect or influence vaccine acceptance. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

An Underlying Common Factor, Influenced by Genetics and Unique Environment, Explains the Covariation Between Major Depressive Disorder, Generalized Anxiety Disorder, and Burnout: A Swedish Twin Study.

PubMed

Mather, Lisa; Blom, Victoria; Bergström, Gunnar; Svedberg, Pia

2016-12-01

Depression and anxiety are highly comorbid due to shared genetic risk factors, but less is known about whether burnout shares these risk factors. We aimed to examine whether the covariation between major depressive disorder (MDD), generalized anxiety disorder (GAD), and burnout is explained by common genetic and/or environmental factors. This cross-sectional study included 25,378 Swedish twins responding to a survey in 2005-2006. Structural equation models were used to analyze whether the trait variances and covariances were due to additive genetics, non-additive genetics, shared environment, and unique environment. Univariate analyses tested sex limitation models and multivariate analysis tested Cholesky, independent pathway, and common pathway models. The phenotypic correlations were 0.71 (0.69-0.74) between MDD and GAD, 0.58 (0.56-0.60) between MDD and burnout, and 0.53 (0.50-0.56) between GAD and burnout. Heritabilities were 45% for MDD, 49% for GAD, and 38% for burnout; no statistically significant sex differences were found. A common pathway model was chosen as the final model. The common factor was influenced by genetics (58%) and unique environment (42%), and explained 77% of the variation in MDD, 69% in GAD, and 44% in burnout. GAD and burnout had additive genetic factors unique to the phenotypes (11% each), while MDD did not. Unique environment explained 23% of the variability in MDD, 20% in GAD, and 45% in burnout. In conclusion, the covariation was explained by an underlying common factor, largely influenced by genetics. Burnout was to a large degree influenced by unique environmental factors not shared with MDD and GAD.

Genetic and environmental factors affecting birth size variation: a pooled individual-based analysis of secular trends and global geographical differences using 26 twin cohorts.

PubMed

Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi; Sund, Reijo; Fagnani, Corrado; Stazi, Maria A; Brescianini, Sonia; Ji, Fuling; Ning, Feng; Pang, Zengchang; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Rebato, Esther; Hopper, John L; Cutler, Tessa L; Saudino, Kimberly J; Nelson, Tracy L; Whitfield, Keith E; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Llewellyn, Clare H; Fisher, Abigail; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Bartels, Meike; van Beijsterveldt, Catharina E M; Willemsen, Gonneke; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas S; Craig, Jeffrey M; Saffery, Richard; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Haworth, Claire M A; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Rasmussen, Finn; Tynelius, Per; Tarnoki, Adam D; Tarnoki, David L; Ooki, Syuichi; Rose, Richard J; Pietiläinen, Kirsi H; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko; Silventoinen, Karri

2018-05-19

The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia) and across birth cohorts, and how gestational age modifies these effects. Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling. The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographical-cultural regions, but shared environmental variance was smaller in East Asia than in Europe and North America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-99 onwards compared with the birth cohorts from 1970-79 to 1980-89. The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographical-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

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

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Explaining regional variation in home care use by demand and supply variables.

PubMed

van Noort, Olivier; Schotanus, Fredo; van de Klundert, Joris; Telgen, Jan

2018-02-01

In the Netherlands, home care services like district nursing and personal assistance are provided by private service provider organizations and covered by private health insurance companies which bear legal responsibility for purchasing these services. To improve value for money, their procurement increasingly replaces fee-for-service payments with population based budgets. Setting appropriate population budgets requires adaptation to the legitimate needs of the population, whereas historical costs are likely to be influenced by supply factors as well, not all of which are necessarily legitimate. Our purpose is to explain home care costs in terms of demand and supply factors. This allows for adjusting historical cost patterns when setting population based budgets. Using expenses claims of 60 Dutch municipalities, we analyze eight demand variables and five supply variables with a multiple regression model to explain variance in the number of clients per inhabitant, costs per client and costs per inhabitant. Our models explain 69% of variation in the number of clients per inhabitant, 28% of costs per client and 56% of costs per inhabitant using demand factors. Moreover, we find that supply factors explain an additional 17-23% of variation. Predictors of higher utilization are home care organizations that are integrated with intramural nursing homes, higher competition levels among home care organizations and the availability of complementary services. Copyright © 2017. Published by Elsevier B.V.

Do Lower-Body Dimensions and Body Composition Explain Vertical Jump Ability?

PubMed

Caia, Johnpaul; Weiss, Lawrence W; Chiu, Loren Z F; Schilling, Brian K; Paquette, Max R; Relyea, George E

2016-11-01

Caia, J, Weiss, LW, Chiu, LZF, Schilling, BK, Paquette, MR, and Relyea, GE. Do lower-body dimensions and body composition explain vertical jump ability? J Strength Cond Res 30(11): 3073-3083, 2016-Vertical jump (VJ) capability is integral to the level of success attained by individuals participating in numerous sport and physical activities. Knowledge of factors related to jump performance may help with talent identification and/or optimizing training prescription. Although myriad variables are likely related to VJ, this study focused on determining if various lower-body dimensions and/or body composition would explain some of the variability in performance. Selected anthropometric dimensions were obtained from 50 university students (25 men and 25 women) on 2 occasions separated by 48 or 72 hours. Estimated body fat percentage (BF%), height, body weight, hip width, pelvic width, bilateral quadriceps angle (Q-angle), and bilateral longitudinal dimensions of the feet, leg, thigh, and lower limb were obtained. Additionally, participants completed countermovement VJs. Analysis showed BF% to have the highest correlation with countermovement VJ displacement (r = -0.76, p < 0.001). When examining lower-body dimensions, right-side Q-angle displayed the strongest association with countermovement VJ displacement (r = -0.58, p < 0.001). Regression analysis revealed that 2 different pairs of variables accounted for the greatest variation (66%) in VJ: (a) BF% and sex and (b) BF% and body weight. Regression models involving BF% and lower-body dimensions explained up to 61% of the variance observed in VJ. Although the variance explained by BF% may be increased by using several lower-body dimensions, either sex identification or body weight explains comparatively more. Therefore, these data suggest that the lower-body dimensions measured herein have limited utility in explaining VJ performance.

Fibrinogen and associated risk factors in a high-risk population: urban Indigenous Australians, the DRUID Study.

PubMed

Maple-Brown, Louise J; Cunningham, Joan; Nandi, Nirjhar; Hodge, Allison; O'Dea, Kerin

2010-10-29

Epidemiological evidence suggests that fibrinogen and CRP are associated with coronary heart disease risk. High CRP in Indigenous Australians has been reported in previous studies including our 'Diabetes and Related diseases in Urban Indigenous population in Darwin region' (DRUID) Study. We studied levels of fibrinogen and its cross-sectional relationship with traditional and non-traditional cardiovascular risk factors in an urban Indigenous Australian cohort. Fibrinogen data were available from 287 males and 628 females (aged ≥ 15 years) from the DRUID study. Analysis was performed for associations with the following risk factors: diabetes, HbA1c, age, BMI, waist circumference, waist-hip ratio, total cholesterol, triglyceride, HDL cholesterol, C-reactive protein, homocysteine, blood pressure, heart rate, urine ACR, smoking status, alcohol abstinence. Fibrinogen generally increased with age in both genders; levels by age group were higher than those previously reported in other populations, including Native Americans. Fibrinogen was higher in those with than without diabetes (4.24 vs 3.56 g/L, p < 0.001). After adjusting for age and sex, the following were significantly associated with fibrinogen: BMI, waist, waist-hip ratio, systolic blood pressure, heart rate, fasting triglycerides, HDL cholesterol, HbA1c, CRP, ACR and alcohol abstinence. On multivariate regression (age and sex-adjusted) CRP and HbA1c were significant independent predictors of fibrinogen, explaining 27% of its variance; CRP alone explained 25% of fibrinogen variance. On factor analysis, both CRP and fibrinogen clustered with obesity in women (this factor explained 20% of variance); but in men, CRP clustered with obesity (factor explained 18% of variance) whilst fibrinogen clustered with HbA1c and urine ACR (factor explained 13% of variance). Fibrinogen is associated with traditional and non-traditional cardiovascular risk factors in this urban Indigenous cohort and may be a useful biomarker of

Using the theory of planned behaviour and self-identity to explain chlamydia testing intentions in young people living in deprived areas.

PubMed

Booth, Amy R; Norman, Paul; Harris, Peter R; Goyder, Elizabeth

2014-02-01

The study sought to (1) explain intentions to get tested for chlamydia regularly in a group of young people living in deprived areas using the theory of planned behaviour (TPB); and (2) test whether self-identity explained additional variance in testing intentions. A cross-sectional design was used for this study. Participants (N = 278, 53% male; M = 17.05 years) living in deprived areas of a UK city were recruited from a vocational education setting. Participants completed a self-administered questionnaire, including measures of attitude, injunctive subjective norm, descriptive norm, perceived behavioural control, self-identity, intention and past behaviour in relation to getting tested for chlamydia regularly. The TPB explained 43% of the variance in chlamydia testing intentions with all variables emerging as significant predictors. However, self-identity explained additional variance in intentions (ΔR(2)  = .22) and emerged as the strongest predictor, even when controlling for past behaviour. The study identified the key determinants of intention to get tested for chlamydia regularly in a sample of young people living in areas of increased deprivation: a hard-to-reach, high-risk population. The findings indicate the key variables to target in interventions to promote motivation to get tested for chlamydia regularly in equivalent samples, amongst which self-identity is critical. What is already known on this subject? Young people living in deprived areas have been identified as an at-risk group for chlamydia. Qualitative research has identified several themes in relation to factors affecting the uptake of chlamydia testing, which fit well with the constructs of the Theory of Planned Behaviour (TPB). Identity concerns have also been identified as playing an important part in young people's chlamydia testing decisions. What does this study add? TPB explained 43% of the variance in chlamydia testing intentions and all variables were significant predictors

Relative importance of local habitat complexity and regional factors for assemblages of oribatid mites (Acari: Oribatida) in Sphagnum peat bogs.

PubMed

Minor, M A; Ermilov, S G; Philippov, D A; Prokin, A A

2016-11-01

We investigated communities of oribatid mites in five peat bogs in the north-west of the East European plain. We aimed to determine the extent to which geographic factors (latitude, separation distance), local environment (Sphagnum moss species, ground water level, biogeochemistry) and local habitat complexity (diversity of vascular plants and bryophytes in the surrounding plant community) influence diversity and community composition of Oribatida. There was a significant north-to-south increase in Oribatida abundance. In the variance partitioning, spatial factors explained 33.1 % of variability in abundance across samples; none of the environmental factors were significant. Across all bogs, Oribatida species richness and community composition were similar in Sphagnum rubellum and Sphagnum magellanicum, but significantly different and less diverse in Sphagnum cuspidatum. Sphagnum microhabitat explained 52.2 % of variability in Oribatida species richness, whereas spatial variables explained only 8.7 %. There was no distance decay in community similarity between bogs with increased geographical distance. The environmental variables explained 34.9 % of the variance in community structure, with vascular plants diversity, bryophytes diversity, and ground water level all contributing significantly; spatial variables explained 15.1 % of the total variance. Overall, only 50 % of the Oribatida community variance was explained by the spatial structure and environmental variables. We discuss relative importance of spatial and local environmental factors, and make general inferences about the formation of fauna in Sphagnum bogs.

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.

Relationships between Adaptive Behaviours, Personal Factors, and Participation of Young Children.

PubMed

Killeen, Hazel; Shiel, Agnes; Law, Mary; O'Donovan, Donough J; Segurado, Ricardo; Anaby, Dana

2017-12-19

To examine the extent to which personal factors (age, socioeconomic grouping, and preterm birth) and adaptive behaviour explain the participation patterns of young children. 65 Children 2-5 years old with and without a history of preterm birth and no physical or intellectual disability were selected by convenience sampling from Galway University Hospital, Ireland. Interviews with parents were conducted using the Adaptive Behaviour Assessment System, Second Edition (ABAS-II) and the Assessment of Preschool Children's Participation (APCP). Linear regression models were used to identify associations between the ABAS-II scores, personal factors, and APCP scores for intensity and diversity of participation. Adaptive behaviour explained 21% of variance in intensity of play, 18% in intensity of Skill Development, 7% in intensity of Active Physical Recreation, and 6% in intensity of Social Activities controlling for age, preterm birth, and socioeconomic grouping. Age explained between 1% and 11% of variance in intensity of participation scores. Adapted behaviour (13%), Age (17%), and socioeconomic grouping (5%) explained a significant percentage of variance in diversity of participation controlling for the other variables.  Adaptive behaviour had a unique contribution to children's intensity and diversity of participation, suggesting its importance.

WASP (Write a Scientific Paper) using Excel 9: Analysis of variance.

PubMed

Grech, Victor

2018-06-01

Analysis of variance (ANOVA) may be required by researchers as an inferential statistical test when more than two means require comparison. This paper explains how to perform ANOVA in Microsoft Excel. Copyright © 2018 Elsevier B.V. All rights reserved.

Mechanical factors relate to pain in knee osteoarthritis.

PubMed

Maly, Monica R; Costigan, Patrick A; Olney, Sandra J

2008-07-01

Pain experienced by people with knee osteoarthritis is related to psychosocial factors and damage to articular tissues and/or the pain pathway itself. Mechanical factors have been speculated to trigger this pain experience; yet mechanics have not been identified as a source of pain in this population. The purpose of this study was to identify whether mechanics could explain variance in pain intensity in people with knee osteoarthritis. Data from 53 participants with physician-diagnosed knee osteoarthritis (mean age=68.5 years; standard deviation=8.6 years) were analyzed. Pain intensity was reported on the Western Ontario and McMaster Universities Osteoarthritis Index. Mechanical measures included weight-bearing varus-valgus alignment, body mass index and isokinetic quadriceps torque. Gait analysis captured the range of adduction-abduction angle, range of flexion-extension angle and external knee adduction moment during level walking. Pain intensity was significantly related to the dynamic range of flexion-extension during gait and body mass index. A total of 29% of the variance in pain intensity was explained by mechanical variables. The range of flexion-extension explained 18% of variance in pain intensity. Body mass index added 11% to the model. The knee adduction moment was unrelated to pain intensity. The findings support that mechanical factors are related to knee osteoarthritis pain. Because limitations in flexion-extension range of motion and body size are modifiable factors, future research could examine whether interventions targeting these mechanics would facilitate pain management.

Most of the genetic covariation between major depressive and alcohol use disorders is explained by trait measures of negative emotionality and behavioral control.

PubMed

Ellingson, J M; Richmond-Rakerd, L S; Statham, D J; Martin, N G; Slutske, W S

2016-10-01

Mental health disorders commonly co-occur, even between conceptually distinct syndromes, such as internalizing and externalizing disorders. The current study investigated whether phenotypic, genetic, and environmental variance in negative emotionality and behavioral control account for the covariation between major depressive disorder (MDD) and alcohol use disorder (AUD). A total of 3623 members of a national twin registry were administered structured diagnostic telephone interviews that included assessments of lifetime histories of MDD and AUD, and were mailed self-report personality questionnaires that assessed stress reactivity (SR) and behavioral control (CON). A series of biometric models were fitted to partition the proportion of covariance between MDD and AUD into SR and CON. A statistically significant proportion of the correlation between MDD and AUD was due to variance specific to SR (men = 0.31, women = 0.27) and CON (men = 0.20, women = 0.19). Further, genetic factors explained a large proportion of this correlation (0.63), with unique environmental factors explaining the rest. SR explained a significant proportion of the genetic (0.33) and environmental (0.23) overlap between MDD and AUD. In contrast, variance specific to CON accounted for genetic overlap (0.32), but not environmental overlap (0.004). In total, SR and CON accounted for approximately 70% of the genetic and 20% of the environmental covariation between MDD and AUD. This is the first study to demonstrate that negative emotionality and behavioral control confer risk for the co-occurrence of MDD and AUD via genetic factors. These findings are consistent with the aims of NIMH's RDoC proposal to elucidate how transdiagnostic risk factors drive psychopathology.

Assessing variance components in multilevel linear models using approximate Bayes factors: A case study of ethnic disparities in birthweight

PubMed Central

Saville, Benjamin R.; Herring, Amy H.; Kaufman, Jay S.

2013-01-01

Racial/ethnic disparities in birthweight are a large source of differential morbidity and mortality worldwide and have remained largely unexplained in epidemiologic models. We assess the impact of maternal ancestry and census tract residence on infant birth weights in New York City and the modifying effects of race and nativity by incorporating random effects in a multilevel linear model. Evaluating the significance of these predictors involves the test of whether the variances of the random effects are equal to zero. This is problematic because the null hypothesis lies on the boundary of the parameter space. We generalize an approach for assessing random effects in the two-level linear model to a broader class of multilevel linear models by scaling the random effects to the residual variance and introducing parameters that control the relative contribution of the random effects. After integrating over the random effects and variance components, the resulting integrals needed to calculate the Bayes factor can be efficiently approximated with Laplace’s method. PMID:24082430

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

Do factors related to combustion-based sources explain ...

EPA Pesticide Factsheets

Introduction: Spatial heterogeneity of effect estimates in associations between PM2.5 and total non-accidental mortality (TNA) in the United States (US), is an issue in epidemiology. This study uses rate ratios generated from the Multi-City/Multi-Pollutant study (1999-2005) for 313 core-based statistical areas (CBSA) and their metropolitan divisions (MD) to examine combustion-based sources of heterogeneity.Methods: For CBSA/MDs, area-specific log rate ratios (betas) were derived from a model adjusting for time, an interaction with age-group, day of week, and natural splines of current temperature, current dew point, and unconstrained temperature at lags 1, 2, and 3. We assessed the heterogeneity in the betas by linear regression with inverse variance weights, using average NO2, SO2, and CO, which may act as a combustion source proxy, and these pollutants’ correlations with PM2.5. Results: We found that weighted mean PM2.5 association (0.96 percent increase in total non-accidental mortality for a 10 µg/m3 increment in PM2.5) increased by 0.26 (95% confidence interval 0.08 , 0.44) for an interquartile change (0.2) in the correlation of SO2 and PM2.5., but betas showed less dependence on the annual averages of SO2 or NO2. Spline analyses suggest departures from linearity, particularly in a model that examined correlations between PM2.5 and CO.Conclusions: We conclude that correlations between SO2 and PM2.5 as an indicator of combustion sources explains some hete

Can individual health differences be explained by workplace characteristics?--A multilevel analysis.

PubMed

Marklund, Staffan; Bolin, Malin; von Essen, Jan

2008-02-01

Research on work-related health has mainly focused on individual factors. The present study expands the focus by exploring the role of organizational characteristics of workplaces for different individual health outcomes. The aim of the study was to look at differences in relative effect of workplace variations on five health outcomes, and to explain those differences in health outcomes by organizational characteristics. The sample encompassed 90 workplaces in Sweden and about 4300 individuals employed within these workplaces. Measurement of the workplace characteristics was carried out independently of the measurement of the individual's working conditions and health. Organizational data were collected by interviews with local managers at participating workplaces, and individual data were obtained by means of a survey of the employees. The results showed that a significant proportion of the variance in sickness absence, work ability, general health, and musculoskeletal disorders was attributed to the workplace. Of eight tested organizational characteristics, customer adaptation, lean production, and performance control could explain some of this workplace variance. The results also showed that only one organizational effect remained significant when controlled for the individual confounder of age and gender. High customer adaptation is associated with higher sickness absence. This association is not mediated via differences in mental and physical job strain.

Exploratory factor analysis of signalment and conformational measurements in Thoroughbred horses with and without recurrent laryngeal neuropathy.

PubMed

McGivney, C L; Gough, K F; McGivney, B A; Farries, G; Hill, E W; Katz, L M

2018-06-23

Conflicting results have been reported for risk factors for recurrent laryngeal neuropathy (RLN) based on resting endoscopic evaluation and comparison of single conformation traits, with many traits correlated to one another. To simplify identification of signalment and conformation traits (i.e. variables) associated with RLN cases and controls diagnosed with exercising overground endoscopy (OGE) using exploratory factor analysis (EFA). Prospective cohort. Pearson's rank correlation was used to establish significance and association between variables collected from n = 188 Thoroughbreds from one stable by observers blinded to OGE results. Exploratory factor analysis was conducted on 9 variables for cases and controls; common elements between variables developed a factor, with variables grouped into 3 factors for cases and controls, respectively. Correlation (loading) between each variable and factor was calculated to rank relationships between variables and cases/controls, with factors retrospectively named based on their underlying correlations with variables. Numerous inter-correlations were present between variables. Most strongly correlated in cases were wither height with body weight (r = 0.70) and ventral neck length (r = 0.68) and in controls body weight with rostral neck circumference (r = 0.58). Wither height (r = 0.61) significantly loaded the top-ranked factor for cases ('height RLN '), explaining 25% of conformational variance. Ventral neck length (r = 0.69) and age (r = 0.57) significantly loaded the second-ranked factor for cases ('neck length RLN '), explaining 16% of conformational variance. Rostral neck circumference (r = 0.86) and body weight (r = 0.6) significantly loaded the top-ranked factor for controls ('body size CON '), explaining 19% of the variance. Wither height (r = 0.84) significantly loaded the second-ranked factor for controls ('height CON '), explaining 13% of the variance. Horses had not reached skeletal maturity. Exploratory

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

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

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

Environmental factors explaining the vegetation patterns in a temperate peatland.

PubMed

Pellerin, Stéphanie; Lagneau, Louis-Adrien; Lavoie, Martin; Larocque, Marie

2009-08-01

Although ombrotrophic temperate peatlands are important ecosystems for maintaining biodiversity in eastern North America, the environmental factors influencing their flora are only partly understood. The relationships between plant species distribution and environmental factors were thus studied within the oldest temperate peatland of Québec. Plant assemblages were identified by cluster analysis while CCA was used to related vegetation gradients to environmental factors. Five assemblages were identified; three typical of open bog and two characterized by more minerotrophic vegetation. Thicker peat deposit was encounter underlying the bog assemblages while higher water table level and percentage of free surface water distinguished the minerotrophic assemblages. Overall, the floristic patterns observed were spatially structured along the margins and the expanse. The most important environmental factors explaining this spatial gradient were the percentage of free surface water and the highest water-table level.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Enlarged leukocyte referent libraries can explain additional variance in blood-based epigenome-wide association studies.

PubMed

Kim, Stephanie; Eliot, Melissa; Koestler, Devin C; Houseman, Eugene A; Wetmur, James G; Wiencke, John K; Kelsey, Karl T

2016-09-01

We examined whether variation in blood-based epigenome-wide association studies could be more completely explained by augmenting existing reference DNA methylation libraries. We compared existing and enhanced libraries in predicting variability in three publicly available 450K methylation datasets that collected whole-blood samples. Models were fit separately to each CpG site and used to estimate the additional variability when adjustments for cell composition were made with each library. Calculation of the mean difference in the CpG-specific residual sums of squares error between models for an arthritis, aging and metabolic syndrome dataset, indicated that an enhanced library explained significantly more variation across all three datasets (p < 10(-3)). Pathologically important immune cell subtypes can explain important variability in epigenome-wide association studies done in blood.

A Two-Factor Model Better Explains Heterogeneity in Negative Symptoms: Evidence from the Positive and Negative Syndrome Scale.

PubMed

Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong

2016-01-01

Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.

Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps

NASA Astrophysics Data System (ADS)

Treiber, Martin; Kesting, Arne; Helbing, Dirk

2006-07-01

We investigate the adaptation of the time headways in car-following models as a function of the local velocity variance, which is a measure of the inhomogeneity of traffic flow. We apply this mechanism to several car-following models and simulate traffic breakdowns in open systems with an on-ramp as bottleneck and in a closed ring road. Single-vehicle data and one-minute aggregated data generated by several virtual detectors show a semiquantitative agreement with microscopic and flow-density data from the Dutch freeway A9. This includes the observed distributions of the net time headways for free and congested traffic, the velocity variance as a function of density, and the fundamental diagram. The modal value of the time headway distribution is shifted by a factor of about 2 under congested conditions. Macroscopically, this corresponds to the capacity drop at the transition from free to congested traffic. The simulated fundamental diagram shows free, synchronized, and jammed traffic, and a wide scattering in the congested traffic regime. We explain this by a self-organized variance-driven process that leads to the spontaneous formation and decay of long-lived platoons even for a deterministic dynamics on a single lane.

Examining General and Specific Factors in the Dimensionality of Oral Language and Reading in 4th–10th Grades

PubMed Central

Foorman, Barbara R.; Koon, Sharon; Petscher, Yaacov; Mitchell, Alison; Truckenmiller, Adrea

2015-01-01

The objective of this study was to explore dimensions of oral language and reading and their influence on reading comprehension in a relatively understudied population—adolescent readers in 4th through 10th grades. The current study employed latent variable modeling of decoding fluency, vocabulary, syntax, and reading comprehension so as to represent these constructs with minimal error and to examine whether residual variance unaccounted for by oral language can be captured by specific factors of syntax and vocabulary. A 1-, 3-, 4-, and bifactor model were tested with 1,792 students in 18 schools in 2 large urban districts in the Southeast. Students were individually administered measures of expressive and receptive vocabulary, syntax, and decoding fluency in mid-year. At the end of the year students took the state reading test as well as a group-administered, norm-referenced test of reading comprehension. The bifactor model fit the data best in all 7 grades and explained 72% to 99% of the variance in reading comprehension. The specific factors of syntax and vocabulary explained significant unique variance in reading comprehension in 1 grade each. The decoding fluency factor was significantly correlated with the reading comprehension and oral language factors in all grades, but, in the presence of the oral language factor, was not significantly associated with the reading comprehension factor. Results support a bifactor model of lexical knowledge rather than the 3-factor model of the Simple View of Reading, with the vast amount of variance in reading comprehension explained by a general oral language factor. PMID:26346839

Performance of the Santa Ines breed raised on pasture in semiarid tropical regions and factors that explain trait variation.

PubMed

de Farias Jucá, Adriana; Faveri, Juliana Cantos; Melo Filho, Geraldo Magalhães; de Lisboa Ribeiro Filho, Antônio; Azevedo, Hymerson Costa; Muniz, Evandro Neves; Pinto, Luís Fernando Batista

2014-10-01

This study aimed to evaluate sex, the number of lambs per birth, and the family effects on production traits in the Santa Ines breed of sheep by estimating the least square means and coefficient of variance for those traits. A total of 484 lambs were evaluated for the following traits: weight at birth, at weaning, and at 240 days of age; weight gain during the pre-weaning and post-weaning periods; height, width, and length of different body regions; and rib eye area and fat thickness between the 12th and 13th ribs. We observed coefficients of variation higher than 10 % for several traits. Generally, males were larger than females (P < 0.05), while lambs from single and double births were larger than lambs from triple births (P < 0.05). Family effect was significant (P < 0.05) for most traits and explained the highest percentage of residual variance. The results showed good development of Santa Ines sheep, especially during the pre-weaning period but no in post-weaning. Our study also showed that there is an effect of sex, birth type, and family, which must be included in any statistical model for the estimation of least square means and residual variance in ANOVA.

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

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

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

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

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.

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

Modeling factors explaining physicians' satisfaction with competence.

PubMed

Lepnurm, Rein; Dobson, Roy Thomas; Peña-Sánchez, Juan-Nicolás; Nesdole, Robert

2015-01-01

Attention to physician wellness has increased as medical practice gains in complexity. Physician satisfaction with practice is critical for quality of care and practice growth. The purpose of this study was to model physicians' self-reported Satisfaction with Competence as a function of their perceptions of the Quality of Health Services, Distress, Coping, Practice Management, Personal Satisfaction and Professional Equity. Comprehensive questionnaires were sent to a stratified sample of 5300 physicians across Canada. This cross-sectional study focused on physicians who examined and treated individual patients for a final study population of 2639 physicians. Response bias was negligible. The questionnaires contained measures of Satisfaction with Competence, Quality of Health Services, Distress, Coping, Personal Satisfaction, Practice Management and Professional Equity. Exploring relationships was done using Pearson correlations and one-way analysis of variance. Modeling was by hierarchical regressions. The measures were reliable: Satisfaction with Competence (α = .86), Quality (α = .86), Access (α = .82), Distress (α = .82), Coping (α = .76), Personal Satisfaction (α = .78), Practice Management (α = .89) and the dimensions of Professional Equity (Fulfillment, α = .81; Financial, α = .93; and Recognition, α = .75) with comparative validity. Satisfaction with Competence was positively correlated with Quality (r = .32), Efficiency (r = .37) and Access (r = .32); negatively correlated with Distress (r = -.54); and positively correlated with Coping strategies (r = .43), Personal Satisfaction (r = .57), Practice Management (r = .17), Fulfillment (r = .53), Financial (r = .36) and Recognition (r = .54). Physicians' perceptions on Quality, Efficiency, Access, Distress, Coping, Personal Satisfaction, Practice Management, Fulfillment, Pay and Recognition explained 60.2% of the variation

Exposure to Pre- and Perinatal Risk Factors Partially Explains Mean Differences in Self-Regulation between Races.

PubMed

Barnes, J C; Boutwell, Brian B; Miller, J Mitchell; DeShay, Rashaan A; Beaver, Kevin M; White, Norman

2016-01-01

To examine whether differential exposure to pre- and perinatal risk factors explained differences in levels of self-regulation between children of different races (White, Black, Hispanic, Asian, and Other). Multiple regression models based on data from the Early Childhood Longitudinal Study, Birth Cohort (n ≈ 9,850) were used to analyze the impact of pre- and perinatal risk factors on the development of self-regulation at age 2 years. Racial differences in levels of self-regulation were observed. Racial differences were also observed for 9 of the 12 pre-/perinatal risk factors. Multiple regression analyses revealed that a portion of the racial differences in self-regulation was explained by differential exposure to several of the pre-/perinatal risk factors. Specifically, maternal age at childbirth, gestational timing, and the family's socioeconomic status were significantly related to the child's level of self-regulation. These factors accounted for a statistically significant portion of the racial differences observed in self-regulation. The findings indicate racial differences in self-regulation may be, at least partially, explained by racial differences in exposure to pre- and perinatal risk factors.

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

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Explaining variation in perceived team effectiveness: results from eleven quality improvement collaboratives.

PubMed

Strating, Mathilde M H; Nieboer, Anna P

2013-06-01

Explore effectiveness of 11 collaboratives focusing on 11 different topics, as perceived by local improvement teams and to explore associations with collaborative-, organisational- and team-level factors. Evidence underlying the effectiveness of quality improvement collaboratives is inconclusive and few studies investigated determinants of implementation success. Moreover, most evaluation studies on quality improvement collaboratives are based on one specific topic or quality problem, making it hard to compare across collaboratives addressing different topics. A multiple-case cross-sectional study. Quality improvement teams in 11 quality improvement collaboratives focusing on 11 different topics. Team members received a postal questionnaire at the end of each collaborative. Of the 283 improvement teams, 151 project leaders and 362 team members returned the questionnaire. Analysis of variance revealed that teams varied widely on perceived effectiveness. Especially, members in the Prevention of Malnutrition and Prevention of Medication Errors collaboratives perceived a higher effectiveness than other groups. Multilevel regression analyses showed that educational level of professionals, innovation attributes, organisational support, innovative culture and commitment to change were all significant predictors of perceived effectiveness. In total, 27·9% of the individual-level variance, 57·6% of the team-level variance and 80% of the collaborative-level variance could be explained. The innovation's attributes, organisational support, an innovative team culture and professionals' commitment to change are instrumental to perceived effectiveness. The results support the notion that a layered approach is necessary to achieve improvements in quality of care and provides further insight in the determinants of success of quality improvement collaboratives. Understanding which factors enhance the impact of quality improvement initiatives can help professionals to achieve

VARIANCE ANISOTROPY IN KINETIC PLASMAS

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

Parashar, Tulasi N.; Matthaeus, William H.; Oughton, Sean

Solar wind fluctuations admit well-documented anisotropies of the variance matrix, or polarization, related to the mean magnetic field direction. Typically, one finds a ratio of perpendicular variance to parallel variance of the order of 9:1 for the magnetic field. Here we study the question of whether a kinetic plasma spontaneously generates and sustains parallel variances when initiated with only perpendicular variance. We find that parallel variance grows and saturates at about 5% of the perpendicular variance in a few nonlinear times irrespective of the Reynolds number. For sufficiently large systems (Reynolds numbers) the variance approaches values consistent with the solarmore » wind observations.« less

Inheritance of dermatoglyphic asymmetry and diversity traits in twins based on factor: variance decomposition analysis.

PubMed

Karmakar, Bibha; Malkin, Ida; Kobyliansky, Eugene

2013-06-01

Dermatoglyphic asymmetry and diversity traits from a large number of twins (MZ and DZ) were analyzed based on principal factors to evaluate genetic effects and common familial environmental influences on twin data by the use of maximum likelihood-based Variance decomposition analysis. Sample consists of monozygotic (MZ) twins of two sexes (102 male pairs and 138 female pairs) and 120 pairs of dizygotic (DZ) female twins. All asymmetry (DA and FA) and diversity of dermatoglyphic traits were clearly separated into factors. These are perfectly corroborated with the earlier studies in different ethnic populations, which indicate a common biological validity perhaps exists of the underlying component structures of dermatoglyphic characters. Our heritability result in twins clearly showed that DA_F2 is inherited mostly in dominant type (28.0%) and FA_F1 is additive (60.7%), but no significant difference in sexes was observed for these factors. Inheritance is also very prominent in diversity Factor 1, which is exactly corroborated with our previous findings. The present results are similar with the earlier results of finger ridge count diversity in twin data, which suggested that finger ridge count diversity is under genetic control.

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.

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Variance-Stable R-Estimators.

DTIC Science & Technology

1984-05-01

By means of the concept of change-of variance function we investigate the stability properties of the asymptotic variance of R-estimators. This allows us to construct the optimal V-robust R-estimator that minimizes the asymptotic variance at the model, under the side condition of a bounded change-of variance function. Finally, we discuss the connection between this function and an influence function for two-sample rank tests introduced by Eplett (1980). (Author)

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.

Factors that Explain the Cancer-Related Insomnia.

PubMed

Galiano-Castillo, Noelia; Arroyo-Morales, Manuel; Ariza-Garcia, Angélica; Fernández-Lao, Carolina; Fernández-Fernández, Andrés J; Cantarero-Villanueva, Irene

2017-07-01

A better understanding of cancer related insomnia and its relationship with other associated factors is necessary to improve its management. To clarify the relationship between insomnia and treatment related variables, sociodemographic data, health related fitness, pain, anxiety, and depression in breast cancer patients. One hundred twenty-three patients participated in this cross-sectional study. As a primary variable was insomnia using The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 version. Other variables included: stage of treatment, type of treatment, multiple sit to stand test, trunk curl test, 6-min walk test, back muscle strength test, the Brief Pain Inventory short form and the Hospital Anxiety and Depression Scale. Insomnia was negatively associated with the treatment stage (p = 0.01), the 6-min walk test (p = 0.01) and the back muscle strength test (p = 0.01), while it was positively associated with the type of treatment (p = 0.01) and the multiple sit-to-stand test (p = 0.05). In addition, higher levels of insomnia were associated with higher scores on the Brief Pain Inventory short form (p = 0.01) and the Hospital Anxiety and Depression Scale (p = 0.01). Anxiety, type of treatment, back muscle strength, pain severity and stage of treatment were predictors of insomnia, and when they were combined they explained 51.2% of insomnia in our sample. The variability in insomnia related breast cancer is explained by anxiety, type of treatment, pain, treatment stage, and back muscle strength. Clinicians should take these results into account when generating cancer care programs to control pain and health-related-fitness (Registration of Trials NCT01801527). © 2017 Wiley Periodicals, Inc.

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.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

A Cosmic Variance Cookbook

NASA Astrophysics Data System (ADS)

Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

2011-04-01

Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is

Relationship between extrinsic factors and the acromio-humeral distance.

PubMed

Mackenzie, Tanya Anne; Herrington, Lee; Funk, Lenard; Horsley, Ian; Cools, Ann

2016-06-01

Maintenance of the subacromial space is important in impingement syndromes. Research exploring the correlation between biomechanical factors and the subacromial space would be beneficial. To establish if relationship exists between the independent variables of scapular rotation, shoulder internal rotation, shoulder external rotation, total arc of shoulder rotation, pectoralis minor length, thoracic curve, and shoulder activity level with the dependant variables: AHD in neutral, AHD in 60° arm abduction, and percentage reduction in AHD. Controlled laboratory study. Data from 72 male control shoulders (24.28years STD 6.81 years) and 186 elite sportsmen's shoulders (25.19 STD 5.17 years) were included in the analysis. The independent variables were quantified and real time ultrasound was used to measure the dependant variable acromio-humeral distance. Shoulder internal rotation and pectoralis minor length, explained 8% and 6% respectively of variance in acromio-humeral distance in neutral. Pectoralis minor length accounted for 4% of variance in 60° arm abduction. Total arc of rotation, shoulder external rotation range, and shoulder activity levels explained 9%, 15%, and 16%-29% of variance respectively in percentage reduction in acromio-humeral distance during arm abduction to 60°. Pectorals minor length, shoulder rotation ranges, total arc of shoulder rotation, and shoulder activity levels were found to have weak to moderate relationships with acromio-humeral distance. Existence and strength of relationship was population specific and dependent on arm position. Relationships only accounted for small variances in AHD indicating that in addition to these factors there are other factors involved in determining AHD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling factors explaining physicians’ satisfaction with competence

PubMed Central

Lepnurm, Rein; Dobson, Roy Thomas; Peña-Sánchez, Juan-Nicolás; Nesdole, Robert

2015-01-01

Objective: Attention to physician wellness has increased as medical practice gains in complexity. Physician satisfaction with practice is critical for quality of care and practice growth. The purpose of this study was to model physicians’ self-reported Satisfaction with Competence as a function of their perceptions of the Quality of Health Services, Distress, Coping, Practice Management, Personal Satisfaction and Professional Equity. Methods: Comprehensive questionnaires were sent to a stratified sample of 5300 physicians across Canada. This cross-sectional study focused on physicians who examined and treated individual patients for a final study population of 2639 physicians. Response bias was negligible. The questionnaires contained measures of Satisfaction with Competence, Quality of Health Services, Distress, Coping, Personal Satisfaction, Practice Management and Professional Equity. Exploring relationships was done using Pearson correlations and one-way analysis of variance. Modeling was by hierarchical regressions. Results: The measures were reliable: Satisfaction with Competence (α = .86), Quality (α = .86), Access (α = .82), Distress (α = .82), Coping (α = .76), Personal Satisfaction (α = .78), Practice Management (α = .89) and the dimensions of Professional Equity (Fulfillment, α = .81; Financial, α = .93; and Recognition, α = .75) with comparative validity. Satisfaction with Competence was positively correlated with Quality (r = .32), Efficiency (r = .37) and Access (r = .32); negatively correlated with Distress (r = −.54); and positively correlated with Coping strategies (r = .43), Personal Satisfaction (r = .57), Practice Management (r = .17), Fulfillment (r = .53), Financial (r = .36) and Recognition (r = .54). Physicians’ perceptions on Quality, Efficiency, Access, Distress, Coping, Personal Satisfaction, Practice Management, Fulfillment, Pay and

Spectral Ambiguity of Allan Variance

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

1996-01-01

We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

Host nutrition alters the variance in parasite transmission potential

PubMed Central

Vale, Pedro F.; Choisy, Marc; Little, Tom J.

2013-01-01

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts. PMID:23407498

Host nutrition alters the variance in parasite transmission potential.

PubMed

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

The association of trail use with weather-related factors on an urban greenway.

PubMed

Burchfield, Ryan A; Fitzhugh, Eugene C; Bassett, David R

2012-02-01

To study the association between weather-related measures and objectively measured trail use across 3 seasons. Weather has been reported as a barrier to outdoor physical activity (PA), but previous studies have explained only a small amount of the variance in PA using weather-related measures. The dependent variable of this study was trail use measured as mean hourly trail counts by an infrared trail counter located on a greenway. Each trail count represents 1 person breaking the infrared beam of the trail counter. Two sources of weather-related measures were obtained by a site-specific weather station and a public domain weather source. Temperature, relative humidity, and precipitation were significantly correlated with trail counts recorded during daylight hours. More precise hourly weather-related measures explained 42% of the variance in trail counts, regardless of the weather data source with temperature alone explaining 18% of the variance in trail counts. After controlling for all seasonal and weekly factors, every 1°F increase in temperature was associated with an increase of 1.1 trail counts/hr up to 76°F, at which point trail use began to slightly decrease. Weather-related factors have a moderate association with trail use along an urban greenway.

Attributing variance in supportive care needs during cancer: culture-service, and individual differences, before clinical factors.

PubMed

Fielding, Richard; Lam, Wendy Wing Tak; Shun, Shiow Ching; Okuyama, Toru; Lai, Yeur Hur; Wada, Makoto; Akechi, Tatsuo; Li, Wylie Wai Yee

2013-01-01

Studies using the Supportive Care Needs Survey (SCNS) report high levels of unmet supportive care needs (SCNs) in psychological and less-so physical & daily living domains, interpreted as reflecting disease/treatment-coping deficits. However, service and culture differences may account for unmet SCNs variability. We explored if service and culture differences better account for observed SCNs patterns. Hong Kong (n = 180), Taiwanese (n = 263) and Japanese (n = 109) CRC patients' top 10 ranked SCNS-34 items were contrasted. Mean SCNS-34 domain scores were compared by sample and treatment status, then adjusted for sample composition, disease stage and treatment status using multivariate hierarchical regression. All samples were assessed at comparable time-points. SCNs were most prevalent among Japanese and least among Taiwanese patients. Japanese patients emphasized Psychological (domain mean = 40.73) and Health systems and information (HSI) (38.61) SCN domains, whereas Taiwanese and Hong Kong patients emphasized HSI (27.41; 32.92) and Patient care & support (PCS) (19.70; 18.38) SCN domains. Mean Psychological domain scores differed: Hong Kong = 9.72, Taiwan = 17.84 and Japan = 40.73 (p<0.03-0.001, Bonferroni). Other SCN domains differed only between Chinese and Japanese samples (all p<0.001). Treatment status differentiated Taiwanese more starkly than Hong Kong patients. After adjustment, sample origin accounted for most variance in SCN domain scores (p<0.001), followed by age (p = 0.01-0.001) and employment status (p = 0.01-0.001). Treatment status and Disease stage, though retained, accounted for least variance. Overall accounted variance remained low. Health service and/or cultural influences, age and occupation differences, and less so clinical factors, differentially account for significant variation in published studies of SCNs.

Attributing Variance in Supportive Care Needs during Cancer: Culture-Service, and Individual Differences, before Clinical Factors

PubMed Central

Fielding, Richard; Lam, Wendy Wing Tak; Shun, Shiow Ching; Okuyama, Toru; Lai, Yeur Hur; Wada, Makoto; Akechi, Tatsuo; Li, Wylie Wai Yee

2013-01-01

Background Studies using the Supportive Care Needs Survey (SCNS) report high levels of unmet supportive care needs (SCNs) in psychological and less-so physical & daily living domains, interpreted as reflecting disease/treatment-coping deficits. However, service and culture differences may account for unmet SCNs variability. We explored if service and culture differences better account for observed SCNs patterns. Methods Hong Kong (n = 180), Taiwanese (n = 263) and Japanese (n = 109) CRC patients’ top 10 ranked SCNS-34 items were contrasted. Mean SCNS-34 domain scores were compared by sample and treatment status, then adjusted for sample composition, disease stage and treatment status using multivariate hierarchical regression. Results All samples were assessed at comparable time-points. SCNs were most prevalent among Japanese and least among Taiwanese patients. Japanese patients emphasized Psychological (domain mean = 40.73) and Health systems and information (HSI) (38.61) SCN domains, whereas Taiwanese and Hong Kong patients emphasized HSI (27.41; 32.92) and Patient care & support (PCS) (19.70; 18.38) SCN domains. Mean Psychological domain scores differed: Hong Kong = 9.72, Taiwan = 17.84 and Japan = 40.73 (p<0.03–0.001, Bonferroni). Other SCN domains differed only between Chinese and Japanese samples (all p<0.001). Treatment status differentiated Taiwanese more starkly than Hong Kong patients. After adjustment, sample origin accounted for most variance in SCN domain scores (p<0.001), followed by age (p = 0.01–0.001) and employment status (p = 0.01–0.001). Treatment status and Disease stage, though retained, accounted for least variance. Overall accounted variance remained low. Conclusions Health service and/or cultural influences, age and occupation differences, and less so clinical factors, differentially account for significant variation in published studies of SCNs. PMID:23741467

Reduction of variance in spectral estimates for correction of ultrasonic aberration.

PubMed

Astheimer, Jeffrey P; Pilkington, Wayne C; Waag, Robert C

2006-01-01

A variance reduction factor is defined to describe the rate of convergence and accuracy of spectra estimated from overlapping ultrasonic scattering volumes when the scattering is from a spatially uncorrelated medium. Assuming that the individual volumes are localized by a spherically symmetric Gaussian window and that centers of the volumes are located on orbits of an icosahedral rotation group, the factor is minimized by adjusting the weight and radius of each orbit. Conditions necessary for the application of the variance reduction method, particularly for statistical estimation of aberration, are examined. The smallest possible value of the factor is found by allowing an unlimited number of centers constrained only to be within a ball rather than on icosahedral orbits. Computations using orbits formed by icosahedral vertices, face centers, and edge midpoints with a constraint radius limited to a small multiple of the Gaussian width show that a significant reduction of variance can be achieved from a small number of centers in the confined volume and that this reduction is nearly the maximum obtainable from an unlimited number of centers in the same volume.

Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?

PubMed Central

Wang, Sha

2017-01-01

Cryptocurrencies have become increasingly popular since the introduction of bitcoin in 2009. In this paper, we identify factors associated with variations in cryptocurrencies’ market values. In the past, researchers argued that the “buzz” surrounding cryptocurrencies in online media explained their price variations. But this observation obfuscates the notion that cryptocurrencies, unlike fiat currencies, are technologies entailing a true innovation potential. By using, for the first time, a unique measure of innovation potential, we find that the latter is in fact the most important factor associated with increases in cryptocurrency returns. By contrast, we find that the buzz surrounding cryptocurrencies is negatively associated with returns after controlling for a variety of factors, such as supply growth and liquidity. Also interesting is our finding that a cryptocurrency’s association with fraudulent activity is not negatively associated with weekly returns—a result that further qualifies the media’s influence on cryptocurrencies. Finally, we find that an increase in supply is positively associated with weekly returns. Taken together, our findings show that cryptocurrencies do not behave like traditional currencies or commodities—unlike what most prior research has assumed—and depict an industry that is much more mature, and much less speculative, than has been implied by previous accounts. PMID:28085906

Buzz Factor or Innovation Potential: What Explains Cryptocurrencies' Returns?

PubMed

Wang, Sha; Vergne, Jean-Philippe

2017-01-01

Cryptocurrencies have become increasingly popular since the introduction of bitcoin in 2009. In this paper, we identify factors associated with variations in cryptocurrencies' market values. In the past, researchers argued that the "buzz" surrounding cryptocurrencies in online media explained their price variations. But this observation obfuscates the notion that cryptocurrencies, unlike fiat currencies, are technologies entailing a true innovation potential. By using, for the first time, a unique measure of innovation potential, we find that the latter is in fact the most important factor associated with increases in cryptocurrency returns. By contrast, we find that the buzz surrounding cryptocurrencies is negatively associated with returns after controlling for a variety of factors, such as supply growth and liquidity. Also interesting is our finding that a cryptocurrency's association with fraudulent activity is not negatively associated with weekly returns-a result that further qualifies the media's influence on cryptocurrencies. Finally, we find that an increase in supply is positively associated with weekly returns. Taken together, our findings show that cryptocurrencies do not behave like traditional currencies or commodities-unlike what most prior research has assumed-and depict an industry that is much more mature, and much less speculative, than has been implied by previous accounts.

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.

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.

Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

PubMed

Ehsani, A; Janss, L; Pomp, D; Sørensen, P

2016-04-01

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

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.

Variance Assistance Document: Land Disposal Restrictions Treatability Variances and Determinations of Equivalent Treatment

EPA Pesticide Factsheets

This document provides assistance to those seeking to submit a variance request for LDR treatability variances and determinations of equivalent treatment regarding the hazardous waste land disposal restrictions program.

Variance of transionospheric VLF wave power absorption

NASA Astrophysics Data System (ADS)

Tao, X.; Bortnik, J.; Friedrich, M.

2010-07-01

To investigate the effects of D-region electron-density variance on wave power absorption, we calculate the power reduction of very low frequency (VLF) waves propagating through the ionosphere with a full wave method using the standard ionospheric model IRI and in situ observational data. We first verify the classic absorption curves of Helliwell's using our full wave code. Then we show that the IRI model gives overall smaller wave absorption compared with Helliwell's. Using D-region electron densities measured by rockets during the past 60 years, we demonstrate that the power absorption of VLF waves is subject to large variance, even though Helliwell's absorption curves are within ±1 standard deviation of absorption values calculated from data. Finally, we use a subset of the rocket data that are more representative of the D region of middle- and low-latitude VLF wave transmitters and show that the average quiet time wave absorption is smaller than that of Helliwell's by up to 100 dB at 20 kHz and 60 dB at 2 kHz, which would make the model-observation discrepancy shown by previous work even larger. This result suggests that additional processes may be needed to explain the discrepancy.

Personal and environmental factors contributing to participation in romantic relationships and sexual activity of young adults with cerebral palsy.

PubMed

Wiegerink, Diana J H G; Stam, Henk J; Ketelaar, Marjolijn; Cohen-Kettenis, Peggy T; Roebroeck, Marij E

2012-01-01

To study determinants of romantic relationships and sexual activity of young adults with cerebral palsy (CP), focusing on personal and environmental factors. A cohort study was performed with 74 young adults (46 men; 28 women) aged 20-25 years (SD 1.4) with CP (49% unilateral CP, 76% GMFCS level I, 85% MACS level I). All participants were of normal intelligence. Romantic relationships, sexual activity (outcome measures), personal and environmental factors (associated factors) were assessed. Associations were analyzed using logistic regression analyses. More females than males with CP were in a current romantic relationship. Self-esteem, sexual esteem and feelings of competence regarding self-efficacy contributed positively to having current romantic relationships. A negative parenting style contributed negatively. Age and gross motor functioning explained 20% of the variance in experience with intercourse. In addition, sexual esteem and taking initiative contributed significantly to intercourse experience. For young adults with CP personal factors (20-35% explained variances) seem to contribute more than environmental factors (9-12% explained variances) to current romantic relationships and sexual experiences. We advice parents and professionals to focus on self-efficacy, self-esteem and sexual self-esteem in development of young adults with CP. [ • The severity of gross motor functioning contributed somewhat to sexual activities, but not to romantic relationships.• High self-efficacy, self-esteem and sexual self-esteem can facilitate involvement in romantic and sexual relationships for young adults with CP.

River meanders - Theory of minimum variance

USGS Publications Warehouse

Langbein, Walter Basil; Leopold, Luna Bergere

1966-01-01

Meanders are the result of erosion-deposition processes tending toward the most stable form in which the variability of certain essential properties is minimized. This minimization involves the adjustment of the planimetric geometry and the hydraulic factors of depth, velocity, and local slope.The planimetric geometry of a meander is that of a random walk whose most frequent form minimizes the sum of the squares of the changes in direction in each successive unit length. The direction angles are then sine functions of channel distance. This yields a meander shape typically present in meandering rivers and has the characteristic that the ratio of meander length to average radius of curvature in the bend is 4.7.Depth, velocity, and slope are shown by field observations to be adjusted so as to decrease the variance of shear and the friction factor in a meander curve over that in an otherwise comparable straight reach of the same riverSince theory and observation indicate meanders achieve the minimum variance postulated, it follows that for channels in which alternating pools and riffles occur, meandering is the most probable form of channel geometry and thus is more stable geometry than a straight or nonmeandering alinement.

Interactions between psychosocial and built environment factors in explaining older adults' physical activity.

PubMed

Carlson, Jordan A; Sallis, James F; Conway, Terry L; Saelens, Brian E; Frank, Lawrence D; Kerr, Jacqueline; Cain, Kelli L; King, Abby C

2012-01-01

To evaluate ecological model predictions of cross-level interactions among psychosocial and environmental correlates of physical activity in 719 community-dwelling older adults in the Baltimore, Maryland and Seattle, Washington areas during 2005-2008. Walkability, access to parks and recreation facilities and moderate-to-vigorous physical activity (MVPA) minutes per week (min/week) were measured objectively. Neighborhood aesthetics, walking facilities, social support, self-efficacy, barriers and transportation and leisure walking min/week were self-reported. Walkability interacted with social support in explaining total MVPA (B=13.71) and with social support (B=7.90), self-efficacy (B=7.66) and barriers (B=-8.26) in explaining walking for transportation. Aesthetics interacted with barriers in explaining total MVPA (B=-12.20) and walking facilities interacted with self-efficacy in explaining walking for leisure (B=-10.88; Ps<.05). Summarizing across the interactions, living in a supportive environment (vs. unsupportive) was related to 30-59 more min/week of physical activity for participants with more positive psychosocial attributes, but only 0-28 more min/week for participants with less positive psychosocial attributes. Results supported synergistic interactions between built environment and psychosocial factors in explaining physical activity among older adults. Findings suggest multilevel interventions may be most effective in increasing physical activity. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Socioeconomic Factors Explain Racial Disparities in Invasive Community-Associated Methicillin-Resistant Staphylococcus aureus Disease Rates.

PubMed

See, Isaac; Wesson, Paul; Gualandi, Nicole; Dumyati, Ghinwa; Harrison, Lee H; Lesher, Lindsey; Nadle, Joelle; Petit, Susan; Reisenauer, Claire; Schaffner, William; Tunali, Amy; Mu, Yi; Ahern, Jennifer

2017-03-01

Invasive community-associated methicillin-resistant Staphylococcus aureus (MRSA) incidence in the United States is higher among black persons than white persons. We explored the extent to which socioeconomic factors might explain this racial disparity. A retrospective cohort was based on the Centers for Disease Control and Prevention's Emerging Infections Program surveillance data for invasive community-associated MRSA cases (isolated from a normally sterile site of an outpatient or on hospital admission day ≤3 in a patient without specified major healthcare exposures) from 2009 to 2011 in 33 counties of 9 states. We used generalized estimating equations to determine census tract-level factors associated with differences in MRSA incidence and inverse odds ratio-weighted mediation analysis to determine the proportion of racial disparity mediated by socioeconomic factors. Annual invasive community-associated MRSA incidence was 4.59 per 100000 among whites and 7.60 per 100000 among blacks (rate ratio [RR], 1.66; 95% confidence interval [CI], 1.52-1.80). In the mediation analysis, after accounting for census tract-level measures of federally designated medically underserved areas, education, income, housing value, and rural status, 91% of the original racial disparity was explained; no significant association of black race with community-associated MRSA remained (RR, 1.05; 95% CI, .92-1.20). The racial disparity in invasive community-associated MRSA rates was largely explained by socioeconomic factors. The specific factors that underlie the association between census tract-level socioeconomic measures and MRSA incidence, which may include modifiable social (eg, poverty, crowding) and biological factors (not explored in this analysis), should be elucidated to define strategies for reducing racial disparities in community-associated MRSA rates. Published by Oxford University Press for the Infectious Diseases Society of America 2017. This work is written by (a) US

Contrast discrimination: Second responses reveal the relationship between the mean and variance of visual signals

PubMed Central

Solomon, Joshua A.

2007-01-01

To explain the relationship between first- and second-response accuracies in a detection experiment, Swets, Tanner, and Birdsall [Swets, J., Tanner, W. P., Jr., & Birdsall, T. G. (1961). Decision processes in perception. Psychological Review, 68, 301–340] proposed that the variance of visual signals increased with their means. However, both a low threshold and intrinsic uncertainty produce similar relationships. I measured the relationship between first- and second-response accuracies for suprathreshold contrast discrimination, which is thought to be unaffected by sensory thresholds and intrinsic uncertainty. The results are consistent with a slowly increasing variance. PMID:17961625

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2014 CFR

2014-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2013 CFR

2013-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2011 CFR

2011-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2012 CFR

2012-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

Neural Mechanisms and Children's Intellectual Development: Multiple Impacts of Environmental Factors.

PubMed

Takeuchi, Hikaru; Kawashima, Ryuta

2016-12-01

Human psychometric intelligence can predict a number of important social and academic outcomes. Substantial parts of the variances of human intelligence and the brain volume supporting those abilities are explained by environmental factors, and during childhood, human brains have higher plasticity and also 60% of variance of intelligence that is explained by environmental factors. Here, we review the representative environmental factors known to affect human intellectual development during each developmental stage. We describe what is (and what is not) being investigated to determine how these factors affect human brain development through analyses of volumetrical and cortical structures. In conclusion, environmental factors that affect children's intellectual development lead to three patterns of brain structural change. The first is global change in the brain structure, observed more often in the earlier phase of development. The second is structural changes concentrated in the medial prefrontal and adjacent areas and medial temporal areas, which are likely to be induced by stress in many cases. The third is sporadic region-specific change, likely to be primarily caused by use-dependent plasticity of the areas that is often observed in the later phase of development. These changes may underlie the alterations in children's intellectual development that is induced by environmental factors. © The Author(s) 2015.

40 CFR 142.42 - Consideration of a variance request.

Code of Federal Regulations, 2010 CFR

2010-07-01

... water source, the Administrator shall consider such factors as the following: (1) The availability and.... 142.42 Section 142.42 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the...

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

PubMed

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

2011-01-01

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

Environmental and Genetic Factors Explain Differences in Intraocular Scattering.

PubMed

Benito, Antonio; Hervella, Lucía; Tabernero, Juan; Pennos, Alexandros; Ginis, Harilaos; Sánchez-Romera, Juan F; Ordoñana, Juan R; Ruiz-Sánchez, Marcos; Marín, José M; Artal, Pablo

2016-01-01

To study the relative impact of genetic and environmental factors on the variability of intraocular scattering within a classical twin study. A total of 64 twin pairs, 32 monozygotic (MZ) (mean age: 54.9 ± 6.3 years) and 32 dizygotic (DZ) (mean age: 56.4 ± 7.0 years), were measured after a complete ophthalmologic exam had been performed to exclude all ocular pathologies that increase intraocular scatter as cataracts. Intraocular scattering was evaluated by using two different techniques based on a straylight parameter log(S) estimation: a compact optical instrument based in the principle of optical integration and a psychophysical measurement. Intraclass correlation coefficients (ICC) were used as descriptive statistics of twin resemblance, and genetic models were fitted to estimate heritability. No statistically significant difference was found for MZ and DZ groups for age (P = 0.203), best-corrected visual acuity (P = 0.626), cataract gradation (P = 0.701), sex (P = 0.941), optical log(S) (P = 0.386), or psychophysical log(S) (P = 0.568), with only a minor difference in equivalent sphere (P = 0.008). Intraclass correlation coefficients between siblings were similar for scatter parameters: 0.676 in MZ and 0.471 in DZ twins for optical log(S); 0.533 in MZ twins and 0.475 in DZ twins for psychophysical log(S). For equivalent sphere, ICCs were 0.767 in MZ and 0.228 in DZ twins. Conservative estimates of heritability for the measured scattering parameters were 0.39 and 0.20, respectively. Correlations of intraocular scatter (straylight) parameters in the groups of identical and nonidentical twins were similar. Heritability estimates were of limited magnitude, suggesting that genetic and environmental factors determine the variance of ocular straylight in healthy middle-aged adults.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

PubMed

Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

2015-01-01

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance

Island phytophagy: explaining the remarkable diversity of plant-feeding insects

PubMed Central

Joy, Jeffrey B.; Crespi, Bernard J.

2012-01-01

Plant-feeding insects have undergone unparalleled diversification among different plant taxa, yet explanations for variation in their diversity lack a quantitative, predictive framework. Island biogeographic theory has been applied to spatially discrete habitats but not to habitats, such as host plants, separated by genetic distance. We show that relationships between the diversity of gall-inducing flies and their host plants meet several fundamental predictions from island biogeographic theory. First, plant-taxon genetic distinctiveness, an integrator for long-term evolutionary history of plant lineages, is a significant predictor of variance in the diversity of gall-inducing flies among host-plant taxa. Second, range size and structural complexity also explain significant proportions of the variance in diversity of gall-inducing flies among different host-plant taxa. Third, as with other island systems, plant-lineage age does not predict species diversity. Island biogeographic theory, applied to habitats defined by genetic distance, provides a novel, comprehensive framework for analysing and explaining the diversity of plant-feeding insects and other host-specific taxa. PMID:22553094

Island phytophagy: explaining the remarkable diversity of plant-feeding insects.

PubMed

Joy, Jeffrey B; Crespi, Bernard J

2012-08-22

Plant-feeding insects have undergone unparalleled diversification among different plant taxa, yet explanations for variation in their diversity lack a quantitative, predictive framework. Island biogeographic theory has been applied to spatially discrete habitats but not to habitats, such as host plants, separated by genetic distance. We show that relationships between the diversity of gall-inducing flies and their host plants meet several fundamental predictions from island biogeographic theory. First, plant-taxon genetic distinctiveness, an integrator for long-term evolutionary history of plant lineages, is a significant predictor of variance in the diversity of gall-inducing flies among host-plant taxa. Second, range size and structural complexity also explain significant proportions of the variance in diversity of gall-inducing flies among different host-plant taxa. Third, as with other island systems, plant-lineage age does not predict species diversity. Island biogeographic theory, applied to habitats defined by genetic distance, provides a novel, comprehensive framework for analysing and explaining the diversity of plant-feeding insects and other host-specific taxa.

Explaining worker strain and learning: how important are emotional job demands?

PubMed

Taris, Toon W; Schreurs, Paul J G

2009-05-01

This study examined the added value of emotional job demands in explaining worker well-being, relative to the effects of task characteristics, such as quantitative job demands, job control, and coworker support. Emotional job demands were expected to account for an additional proportion of the variance in well-being. Cross-sectional data were obtained from 11,361 female Dutch home care employees. Hierarchical stepwise regression analysis demonstrated that low control, low support and high quantitative demands were generally associated with lower well-being (as measured in terms of emotional exhaustion, dedication, professional accomplishment and learning). Moreover, high emotional demands were in three out of four cases significantly associated with adverse well-being, in these cases accounting for an additional 1-6% of the variance in the outcome variables. In three out of eight cases the main effects of emotional demands on well-being were qualified by support and control, such that high control and high support either buffered the adverse effects of high emotional demands on well-being or increased the positive effects thereof. All in all, high emotional demands are as important a risk factor for worker well-being as well-established concepts like low job control and high quantitative job demands.

Student, teacher, and classroom predictors of between-teacher variance of students' teacher-rated behavior.

PubMed

Splett, Joni W; Smith-Millman, Marissa; Raborn, Anthony; Brann, Kristy L; Flaspohler, Paul D; Maras, Melissa A

2018-03-08

The current study examined between-teacher variance in teacher ratings of student behavioral and emotional risk to identify student, teacher and classroom characteristics that predict such differences and can be considered in future research and practice. Data were taken from seven elementary schools in one school district implementing universal screening, including 1,241 students rated by 68 teachers. Students were mostly African America (68.5%) with equal gender (female 50.1%) and grade-level distributions. Teachers, mostly White (76.5%) and female (89.7%), completed both a background survey regarding their professional experiences and demographic characteristics and the Behavior Assessment System for Children (Second Edition) Behavioral and Emotional Screening System-Teacher Form for all students in their class, rating an average of 17.69 students each. Extant student data were provided by the district. Analyses followed multilevel linear model stepwise model-building procedures. We detected a significant amount of variance in teachers' ratings of students' behavioral and emotional risk at both student and teacher/classroom levels with student predictors explaining about 39% of student-level variance and teacher/classroom predictors explaining about 20% of between-teacher differences. The final model fit the data (Akaike information criterion = 8,687.709; pseudo-R2 = 0.544) significantly better than the null model (Akaike information criterion = 9,457.160). Significant predictors included student gender, race ethnicity, academic performance and disciplinary incidents, teacher gender, student-teacher gender interaction, teacher professional development in behavior screening, and classroom academic performance. Future research and practice should interpret teacher-rated universal screening of students' behavioral and emotional risk with consideration of the between-teacher variance unrelated to student behavior detected. (PsycINFO Database Record (c) 2018 APA, all

Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging.

PubMed

Terluin, Berend; de Boer, Michiel R; de Vet, Henrica C W

2016-01-01

The network approach to psychopathology conceives mental disorders as sets of symptoms causally impacting on each other. The strengths of the connections between symptoms are key elements in the description of those symptom networks. Typically, the connections are analysed as linear associations (i.e., correlations or regression coefficients). However, there is insufficient awareness of the fact that differences in variance may account for differences in connection strength. Differences in variance frequently occur when subgroups are based on skewed data. An illustrative example is a study published in PLoS One (2013;8(3):e59559) that aimed to test the hypothesis that the development of psychopathology through "staging" was characterized by increasing connection strength between mental states. Three mental states (negative affect, positive affect, and paranoia) were studied in severity subgroups of a general population sample. The connection strength was found to increase with increasing severity in six of nine models. However, the method used (linear mixed modelling) is not suitable for skewed data. We reanalysed the data using inverse Gaussian generalized linear mixed modelling, a method suited for positively skewed data (such as symptoms in the general population). The distribution of positive affect was normal, but the distributions of negative affect and paranoia were heavily skewed. The variance of the skewed variables increased with increasing severity. Reanalysis of the data did not confirm increasing connection strength, except for one of nine models. Reanalysis of the data did not provide convincing evidence in support of staging as characterized by increasing connection strength between mental states. Network researchers should be aware that differences in connection strength between symptoms may be caused by differences in variances, in which case they should not be interpreted as differences in impact of one symptom on another symptom.

Trans-Ethnic Fine-Mapping of Lipid Loci Identifies Population-Specific Signals and Allelic Heterogeneity That Increases the Trait Variance Explained

PubMed Central

Wu, Ying; Waite, Lindsay L.; Jackson, Anne U.; Sheu, Wayne H-H.; Buyske, Steven; Absher, Devin; Arnett, Donna K.; Boerwinkle, Eric; Bonnycastle, Lori L.; Carty, Cara L.; Cheng, Iona; Cochran, Barbara; Croteau-Chonka, Damien C.; Dumitrescu, Logan; Eaton, Charles B.; Franceschini, Nora; Guo, Xiuqing; Henderson, Brian E.; Hindorff, Lucia A.; Kim, Eric; Kinnunen, Leena; Komulainen, Pirjo; Lee, Wen-Jane; Le Marchand, Loic; Lin, Yi; Lindström, Jaana; Lingaas-Holmen, Oddgeir; Mitchell, Sabrina L.; Narisu, Narisu; Robinson, Jennifer G.; Schumacher, Fred; Stančáková, Alena; Sundvall, Jouko; Sung, Yun-Ju; Swift, Amy J.; Wang, Wen-Chang; Wilkens, Lynne; Wilsgaard, Tom; Young, Alicia M.; Adair, Linda S.; Ballantyne, Christie M.; Bůžková, Petra; Chakravarti, Aravinda; Collins, Francis S.; Duggan, David; Feranil, Alan B.; Ho, Low-Tone; Hung, Yi-Jen; Hunt, Steven C.; Hveem, Kristian; Juang, Jyh-Ming J.; Kesäniemi, Antero Y.; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A.; Lee, I-Te; Leppert, Mark F.; Matise, Tara C.; Moilanen, Leena; Njølstad, Inger; Peters, Ulrike; Quertermous, Thomas; Rauramaa, Rainer; Rotter, Jerome I.; Saramies, Jouko; Tuomilehto, Jaakko; Uusitupa, Matti; Wang, Tzung-Dau; Mohlke, Karen L.

2013-01-01

Genome-wide association studies (GWAS) have identified ∼100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1×10−4 in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies. PMID:23555291

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.

PubMed

Blonigen, Daniel M; Patrick, Christopher J; Douglas, Kevin S; Poythress, Norman G; Skeem, Jennifer L; Lilienfeld, Scott O; Edens, John F; Krueger, Robert F

2010-03-01

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 across distinct measures of psychopathy. Using a large correctional sample, the current study employed a multimethod approach to psychopathy assessment (self-report, interview and file review) to explore convergent and discriminant relations between factors of psychopathy measures and latent criteria of INT and EXT derived from the Personality Assessment Inventory (Morey, 2007). Consistent with prediction, scores on the affective-interpersonal factor of psychopathy were negatively associated with INT and negligibly related to EXT, whereas scores on the social deviance factor exhibited positive associations (moderate and large, respectively) with both INT and EXT. Notably, associations were highly comparable across the psychopathy measures when accounting for method variance (in the case of EXT) and when assessing for suppressor effects (in the case of INT). Findings are discussed in terms of implications for clinical assessment and evaluation of the validity of interpretations drawn from scores on psychopathy measures. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Handgrip strength deficits best explain limitations in performing bimanual activities after stroke.

PubMed

Basílio, Marluce Lopes; de Faria-Fortini, Iza; Polese, Janaine Cunha; Scianni, Aline A; Faria, Christina Dcm; Teixeira-Salmela, Luci Fuscaldi

2016-04-01

[Purpose] To evaluate the relationships between residual strength deficits (RSD) of the upper limb muscles and the performance in bimanual activities and to determine which muscular group would best explain the performance in bimanual activities of chronic stroke individuals. [Subjects and Methods] Strength measures of handgrip, wrist extensor, elbow flexor/extensor, and shoulder flexor muscles of 107 subjects were obtained and expressed as RSD. The performance in bimanual activities was assessed by the ABILHAND questionnaire. [Results] The correlations between the RSD of handgrip and wrist extensor muscles with the ABILHAND scores were negative and moderate, whereas those with the elbow flexor/extensor and shoulder flexor muscles were negative and low. Regression analysis showed that the RSD of handgrip and wrist extensor muscles explained 38% of the variance in the ABILHAND scores. Handgrip RSD alone explained 33% of the variance. [Conclusion] The RSD of the upper limb muscles were negatively associated with the performance in bimanual activities and the RSD of handgrip muscles were the most relevant variable. It is possible that stroke subjects would benefit from interventions aiming at improving handgrip strength, when the goal is to increase the performance in bimanual activities.

[Factors influencing the quality of life of elderly living in a pre-fabricated housing complex in the Sichuan earthquake area].

PubMed

Guo, Hong-Xia; Chen, Hong; Wong, Teresa Bik-Kwan Tsien; Chen, Qian; Au, May-Lan; Li, Yun

2012-02-01

The 2008 Sichuan Earthquake caused great damage to the environment and property. In the aftermath, many citizens were relocated to live in newly constructed prefabricated (prefab) communities. This paper explored the current quality of life (QOL) of elderly residents living in prefabricated communities in areas damaged by the Sichuan earthquake and identified factors of influence on QOL values. The ultimate objective was to provide evidence-based guidance for heath improvement measures. The authors used the short form WHOQOL-BREF to assess the quality of life of 191 elderly residents of prefabricated communities in the Sichuan Province 2008 earthquake zone. A Student's t-test, variance analysis, and stepwise multivariate regression methods were used to test the impact of various factors on QOL. Results indicate the self-assessed QOL of participants as good, although scores in the physical (average 56.2) and psychological (average 45.7) domains were significantly lower than the norm in China. Marital status, capital loss in the earthquake, number of children, level of perceived stress, income, interest, and family harmony each correlated with at least one of the short form WHOQOL-BREF domains in t-test and one-way analyses. After excluding for factor interaction effects using multivariate regression, we found interest, family harmony, monthly income and stress to be significant predictors of physical domain QOL, explaining 13.8% of total variance. Family harmony and interest explained 15.3% of total variance for psychological domain QOL; stress, marital status, family harmony, capital loss in the earthquake, number of children and interest explained 19.5% of total variance for social domain QOL; and stress, family harmony and interest explained 16.5% of total variance for environmental domain QOL. Family harmony and interest were significant factors across all domains, while others influenced a smaller proportion. Quality of life for elderly living in prefab

Mediating Factors Explaining the Association Between Sexual Minority Status and Dating Violence.

PubMed

Martin-Storey, Alexa; Fromme, Kim

2017-08-01

Dating violence presents a serious threat for individual health and well-being. A growing body of literature suggests that starting in adolescence, individuals with sexual minority identities (e.g., individuals who identify as gay, lesbian, or bisexual) may be at an increased risk for dating violence compared with heterosexuals. Research has not, however, identified the mechanisms that explain this vulnerability. Using a diverse sample of young adults ( n = 2,474), the current study explored how minority stress theory, revictimization theory, sex of sexual partners, and risky sexual behavior explained differences in dating violence between sexual minority and heterosexual young adults. Initial analyses suggested higher rates of dating violence among individuals who identified as bisexual, and individuals who identified as gay or lesbian when compared with heterosexuals, and further found that these associations failed to differ across gender. When mediating and control variables were included in the analyses, however, the association between both sexual minority identities and higher levels of dating violence became nonsignificant. Of particular interest was the role of discrimination, which mediated the association between bisexual identity and dating violence. Other factors, including sex and number of sexual partners, alcohol use, and childhood maltreatment, were associated with higher rates of dating violence but did not significantly explain vulnerability among sexual minority individuals compared with their heterosexual peers. These findings suggest the importance of minority stress theory in explaining vulnerability to dating violence victimization among bisexuals in particular, and generally support the importance of sexual-minority specific variables in understanding risk for dating violence within this vulnerable population.

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…

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Portfolio optimization using median-variance approach

NASA Astrophysics Data System (ADS)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Which early life events or current environmental and lifestyle factors influence lung function in adolescents? - results from the GINIplus & LISAplus studies.

PubMed

Luzak, Agnes; Fuertes, Elaine; Flexeder, Claudia; Standl, Marie; von Berg, Andrea; Berdel, Dietrich; Koletzko, Sibylle; Heinrich, Joachim; Nowak, Dennis; Schulz, Holger

2017-07-12

Various factors may affect lung function at different stages in life. Since investigations that simultaneously consider several factors are rare, we examined the relative importance of early life, current environmental/lifestyle factors and allergic diseases on lung function in 15-year-olds. Best subset selection was performed for linear regression models to investigate associations between 21 diverse early life events and current factors with spirometric parameters (forced vital capacity, forced expiratory volume in 1 s and maximal mid-expiratory flow (FEF 25-75 )) in 1326 participants of the German GINIplus and LISAplus birth cohorts. To reduce model complexity, one model for each spirometric parameter was replicated 1000 times in random subpopulations (N = 884). Only those factors that were included in >70% of the replication models were retained in the final analysis. A higher peak weight velocity and early lung infections were the early life events prevalently associated with airflow limitation and FEF 25-75 . Current environmental/lifestyle factors at age 15 years and allergic diseases that were associated with lung function were: indoor second-hand smoke exposure, vitamin D concentration, body mass index (BMI) and asthma status. Sex and height captured the majority of the explained variance (>75%), followed by BMI (≤23.7%). The variance explained by early life events was comparatively low (median: 4.8%; range: 0.2-22.4%), but these events were consistently negatively associated with airway function. Although the explained variance was mainly captured by well-known factors included in lung function prediction equations, our findings indicate early life and current factors that should be considered in studies on lung health among adolescents.

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

Usefulness of the protection motivation theory in explaining hearing protection device use among male industrial workers.

PubMed

Melamed, S; Rabinowitz, S; Feiner, M; Weisberg, E; Ribak, J

1996-05-01

The present study examined the usefulness of personal variables: noise annoyance, and components of the protection motivation theory (R. W. Rogers, 1983) along with social-organizational factors in explaining hearing protection device (HPD) use among Israeli manufacturing workers. Participants were 281 men exposed to harmful noise levels for which routine HPD use is required by regulation. In practice, 3 HPD user groups were identified: nonusers (n = 38), occasional users (n = 125), and regular users (n = 118). HPD use was objectively verified. HPD use was primarily related to the personal variables but not to management pressure, coworker pressure, or family support. The most powerful predictors of HPD use were perceived self-efficacy (for long-term HPD use), perceived susceptibility (to hearing loss), and noise annoyance, together explaining 48% of the outcome variance. These findings have implications for interventions aimed at motivating workers to use HPDs regularly.

Social anxiety following traumatic brain injury: an exploration of associated factors.

PubMed

Curvis, William; Simpson, Jane; Hampson, Natalie

2018-06-01

Social anxiety (SA) following traumatic brain injury (TBI) has the potential to affect an individual's general psychological well-being and social functioning, however little research has explored factors associated with its development. The present study used hierarchical multiple regression to investigate the demographic, clinical and psychological factors associated with SA following TBI. A sample of 85 people who experienced TBI were recruited through social media websites and brain injury services across the North-West of England. The overall combined biopsychosocial model was significant, explaining 52-54.3% of the variance in SA (across five imputations of missing data). The addition of psychological variables (self-esteem, locus of control, self-efficacy) made a significant contribution to the overall model, accounting for an additional 12.2-13% of variance in SA above that explained by demographic and clinical variables. Perceived stigma was the only significant independent predictor of SA (B = .274, p = .005). The findings suggest that psychological variables are important in the development of SA following TBI and must be considered alongside clinical factors. Furthermore, the significant role of stigma highlights the need for intervention at both an individualised and societal level.

Genetic and environmental variances of bone microarchitecture and bone remodeling markers: a twin study.

PubMed

Bjørnerem, Åshild; Bui, Minh; Wang, Xiaofang; Ghasem-Zadeh, Ali; Hopper, John L; Zebaze, Roger; Seeman, Ego

2015-03-01

All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p < 0.001). For the corresponding distal radius traits, genetic factors accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ  = 0.49) than DZ (rDZ  = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling

Explaining IT Professionals' Organizational Commitment Based on Age, Gender, and Personality Trait Factor

ERIC Educational Resources Information Center

Syed, Javaid A.

2017-01-01

The purpose of the present study was to test the Emotional Stability dimension of the Big Five factors of personality traits theory to predict or explain a relationship with Employee Organizational Commitment, when the relationship between Emotional Stability (ES) and Employee Organizational Commitment (EOC) was moderated by Gender and AgeGroup.…

Quantifying the Relative Contribution of Factors to Household Vehicle Miles of Travel

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

Garikapati, Venu; Singh, Abhilash C.; Astroza, Sebastian

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes,more » residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.« less

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

Environmental factors explain socioeconomic prevalence differences in myopia in 6-year-old children.

PubMed

Tideman, J Willem L; Polling, Jan Roelof; Hofman, Albert; Jaddoe, Vincent Wv; Mackenbach, Johan P; Klaver, Caroline Cw

2018-02-01

High myopia (≤-6 D) usually has its onset before 10 years of age and can lead to blinding complications later in life. We examined whether differences in myopia prevalences in socioeconomic risk groups could be explained by differences in lifestyle factors. A total of 5711 six-year-old children participating in the prospective population-based birth cohort study Generation R underwent a stepwise ophthalmic examination, which included visual acuity and objective cycloplegic refraction to identify children with myopia (≤-0.5D). Daily activities, ethnicity, factors representing family socioeconomic status and housing were ascertained by questionnaire. Risk assessments of myopia and mediation analyses were performed using logistic regression; attenuation of risks was calculated by bootstrapping. Prevalence of myopia was 2.4% (n=137). Myopic children spent more time indoors and less outdoors than non-myopic children (p<0.01), had lower vitamin D (p=0.01), had a higher body mass index and participated less in sports (p=0.03). Children of non-European descent (OR 2.60; 95% CI 1.84 to 3.68), low maternal education (OR 2.27; 95% CI 1.57 to 3.28) and low family income (OR 2.62; 95% CI 1.8 to 3.74) were more often myopic. Lifestyle factors explained the majority of the increased risk for ethnicity (82%; 95% CI 55 to 120), maternal education (69%; 95% CI 45 to 109) and family socioeconomic status (71%; 95% CI 46 to 104). This study found environmental factors to be strong risk factors for myopia already at the age of 6 years. The myopia prevalence differences in socioeconomic groups were greatly determined by differences in distribution of these environmental risk factors, highlighting the importance of lifestyle adjustments in young children developing myopia. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparing the Performance of Approaches for Testing the Homogeneity of Variance Assumption in One-Factor ANOVA Models

ERIC Educational Resources Information Center

Wang, Yan; Rodríguez de Gil, Patricia; Chen, Yi-Hsin; Kromrey, Jeffrey D.; Kim, Eun Sook; Pham, Thanh; Nguyen, Diep; Romano, Jeanine L.

2017-01-01

Various tests to check the homogeneity of variance assumption have been proposed in the literature, yet there is no consensus as to their robustness when the assumption of normality does not hold. This simulation study evaluated the performance of 14 tests for the homogeneity of variance assumption in one-way ANOVA models in terms of Type I error…

Factor structure of the Brief Negative Symptom Scale.

PubMed

Strauss, Gregory P; Hong, L Elliot; Gold, James M; Buchanan, Robert W; McMahon, Robert P; Keller, William R; Fischer, Bernard A; Catalano, Lauren T; Culbreth, Adam J; Carpenter, William T; Kirkpatrick, Brian

2012-12-01

The current study examined the factor structure of the Brief Negative Symptom Scale (BNSS), a next-generation negative symptom rating instrument developed in response to the NIMH-sponsored Consensus Development Conference on Negative Symptoms. Participants included 146 individuals with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder. Principal axis factoring indicated two distinct factors explaining 68.7% of the variance. Similar to previous findings, the factors reflected motivation and pleasure and emotional expressivity. These findings provide further support for the construct validity of the BNSS, and for the existence of these two negative symptom factors. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-method Assessment of Psychopathy in Relation to Factors of Internalizing and Externalizing from the Personality Assessment Inventory: The Impact of Method Variance and Suppressor Effects

PubMed Central

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 across distinct measures of psychopathy. Using a large correctional sample, the current study employed a multi-method approach to psychopathy assessment (self-report, interview/file review) to explore convergent and discriminant relations between factors of psychopathy measures and latent criteria of INT and EXT derived from the Personality Assessment Inventory (PAI; L. Morey, 2007). Consistent with prediction, scores on the affective-interpersonal factor of psychopathy were negatively associated with INT and negligibly related to EXT, whereas scores on the social deviance factor exhibited positive associations (moderate and large, respectively) with both INT and EXT. Notably, associations were highly comparable across the psychopathy measures when accounting for method variance (in the case of EXT) and when assessing for suppressor effects (in the case of INT). Findings are discussed in terms of implications for clinical assessment and evaluation of the validity of interpretations drawn from scores on psychopathy measures. PMID:20230156

Exploring the factor structure of the Food Cravings Questionnaire-Trait in Cuban adults

PubMed Central

Rodríguez-Martín, Boris C.; Molerio-Pérez, Osana

2014-01-01

Food cravings refer to an intense desire to eat specific foods. The Food Cravings Questionnaire-Trait (FCQ-T) is the most commonly used instrument to assess food cravings as a multidimensional construct. Its 39 items have an underlying nine-factor structure for both the original English and Spanish version; but subsequent studies yielded fewer factors. As a result, a 15-item version of the FCQ-T with one-factor structure has been proposed (FCQ-T-reduced; see this Research Topic). The current study aimed to explore the factor structure of the Spanish version for both the FCQ-T and FCQ-T-reduced in a sample of 1241 Cuban adults. Results showed a four-factor structure for the FCQ-T, which explained 55% of the variance. Factors were highly correlated. Using the items of the FCQ-T-reduced only showed a one-factor structure, which explained 52% of the variance. Both versions of the FCQ-T were positively correlated with body mass index (BMI), scores on the Food Thoughts Suppression Inventory and weight cycling. In addition, women had higher scores than men and restrained eaters had higher scores than unrestrained eaters. To summarize, results showed that (1) the FCQ-T factor structure was significantly reduced in Cuban adults and (2) the FCQ-T-reduced may represent a good alternative to efficiently assess food craving on a trait level. PMID:24672503

Socioeconomic factors outweigh climate in the regional difference of suicide death rate in Taiwan.

PubMed

Tsai, Jui-Feng

2010-09-30

The present study explored both socioeconomic and climatic factors to obtain a more comprehensive view of the asymmetric regional suicide death rate during 1998-2006 in Taiwan. The annual suicide death rate, population and meteorological data from 19 cities/counties in Taiwan were analysed by multiple regression. Five socioeconomic (sex ratio, no spouse, aged, unemployment and low income) and three climatic (temperature, rainfall and sunshine) factors were identified as significant, explaining 59.0% of the variance in the total suicide death rate. 'Without spouse' and 'aged' were associated with the highest risk, while 'low income with financial aids' was strongly protective. The most influential climatic factor was 'temperature,' which was negatively correlated with suicide. 'Sunshine' was positively associated with suicide. The socioeconomic and climatic factors contributed 52.7% and 6.8%, respectively, to the variance of the total suicide death rate. Limitations of the study included the fact that no individual events were considered, the study was of relatively short duration and it was confined to the territory of Taiwan. Socioeconomic factors outweighed climatic factors in explaining regional differences in the suicide death rate in Taiwan. Temperature weighed more than sunshine. 'Thermotherapy' seems more clinically relevant than the popular light therapy, at least in Taiwan. Copyright © 2008 Elsevier Ltd. All rights reserved.

10 CFR 851.30 - Consideration of variances.

Code of Federal Regulations, 2010 CFR

2010-01-01

... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.30 Consideration of variances. (a) Variances shall be granted by the Under Secretary after considering the recommendation of the Chief Health, Safety and Security Officer. The authority to grant a variance cannot be delegated. (b) The application...

10 CFR 851.31 - Variance process.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.31 Variance process. (a) Application. Contractors desiring a variance from a safety and health standard, or portion thereof, may submit a written...) The CSO may forward the application to the Chief Health, Safety and Security Officer. (2) If the CSO...

Application of factor analysis to the water quality in reservoirs

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this work we present a Factor Analysis of chemical and environmental variables of the water column and hydro-morphological features of several Portuguese reservoirs. The objective is to reduce the initial number of variables, keeping their common characteristics. Using the Factor Analysis, the environmental variables measured in the epilimnion and in the hypolimnion, together with the hydromorphological characteristics of the dams were reduced from 63 variables to only 13 factors, which explained a total of 83.348% of the variance in the original data. After performing rotation using the Varimax method, the relations between the factors and the original variables got clearer and more explainable, which provided a Factor Analysis model for these environmental variables using 13 varifactors: Water quality and distance to the source, Hypolimnion chemical composition, Sulfite-reducing bacteria and nutrients, Coliforms and faecal streptococci, Reservoir depth, Temperature, Location, among other factors.

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

PubMed

Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

2009-12-01

Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

Factors explaining children's responses to intravenous needle insertions.

PubMed

McCarthy, Ann Marie; Kleiber, Charmaine; Hanrahan, Kirsten; Zimmerman, M Bridget; Westhus, Nina; Allen, Susan

2010-01-01

Previous research shows that numerous child, parent, and procedural variables affect children's distress responses to procedures. Cognitive-behavioral interventions such as distraction are effective in reducing pain and distress for many children undergoing these procedures. The purpose of this report was to examine child, parent, and procedural variables that explain child distress during a scheduled intravenous insertion when parents are distraction coaches for their children. A total of 542 children, between 4 and 10 years of age, and their parents participated. Child age, gender, diagnosis, and ethnicity were measured by questions developed for this study. Standardized instruments were used to measure child experience with procedures, temperament, ability to attend, anxiety, coping style, and pain sensitivity. Questions were developed to measure parent variables, including ethnicity, gender, previous experiences, and expectations, and procedural variables, including use of topical anesthetics and difficulty of procedure. Standardized instruments were used to measure parenting style and parent anxiety, whereas a new instrument was developed to measure parent performance of distraction. Children's distress responses were measured with the Observation Scale of Behavioral Distress-Revised (behavioral), salivary cortisol (biological), Oucher Pain Scale (self-report), and parent report of child distress (parent report). Regression methods were used for data analyses. Variables explaining behavioral, child-report and parent-report measures include child age, typical coping response, and parent expectation of distress (p < .01). Level of parents' distraction coaching explained a significant portion of behavioral, biological, and parent-report distress measures (p < .05). Child impulsivity and special assistance at school also significantly explained child self-report of pain (p < .05). Additional variables explaining cortisol response were child's distress in the

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

DOE PAGES

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

2016-09-12

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

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

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

PubMed

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Host‐related factors explaining interindividual variability of carotenoid bioavailability and tissue concentrations in humans

PubMed Central

Desmarchelier, Charles; Dragsted, Lars O.; Nielsen, Charlotte S.; Stahl, Wilhelm; Rühl, Ralph; Keijer, Jaap; Borel, Patrick

2017-01-01

Carotenoid dietary intake and their endogenous levels have been associated with a decreased risk of several chronic diseases. There are indications that carotenoid bioavailability depends, in addition to the food matrix, on host factors. These include diseases (e.g. colitis), life‐style habits (e.g. smoking), gender and age, as well as genetic variations including single nucleotide polymorphisms that govern carotenoid metabolism. These are expected to explain interindividual differences that contribute to carotenoid uptake, distribution, metabolism and excretion, and therefore possibly also their association with disease risk. For instance, digestion enzymes fostering micellization (PNLIP, CES), expression of uptake/efflux transporters (SR‐BI, CD36, NPC1L1), cleavage enzymes (BCO1/2), intracellular transporters (FABP2), secretion into chylomicrons (APOB, MTTP), carotenoid metabolism in the blood and liver (LPL, APO C/E, LDLR), and distribution to target tissues such as adipose tissue or macula (GSTP1, StARD3) depend on the activity of these proteins. In addition, human microbiota, e.g. via altering bile‐acid concentrations, may play a role in carotenoid bioavailability. In order to comprehend individual, variable responses to these compounds, an improved knowledge on intra‐/interindividual factors determining carotenoid bioavailability, including tissue distribution, is required. Here, we highlight the current knowledge on factors that may explain such intra‐/interindividual differences. PMID:28101967

Portfolio optimization with mean-variance model

NASA Astrophysics Data System (ADS)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

40 CFR 59.106 - Variance.

Code of Federal Regulations, 2010 CFR

2010-07-01

... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated entity... confidential information in reaching a decision on a variance application. Interested members of the public...

The dynamics of narrative writing in primary grade children: writing process factors predict story quality.

PubMed

von Koss Torkildsen, Janne; Morken, Frøydis; Helland, Wenche A; Helland, Turid

In this study of third grade school children, we investigated the association between writing process measures recorded with key stroke logging and the final written product. Moreover, we examined the cognitive predictors of writing process and product measures. Analyses of key strokes showed that while most children spontaneously made local online revisions while writing, few revised previously written text. Children with good reading and spelling abilities made more online revisions than their peers. Two process factors, transcription fluency and online revision activity, contributed to explaining variance in narrative macrostructural quality and story length. As for cognitive predictors, spelling was the only factor that gave a unique contribution to explaining variance in writing process factors. Better spelling was associated with more revisions and faster transcription. The results show that developing writers' ability to make online revisions in creative writing tasks is related to both the quality of the final written product and to individual literacy skills. More generally, the findings indicate that investigations of the dynamics of the writing process may provide insights into the factors that contribute to creative writing during early stages of literacy.

The Development of Spoken Language in Deaf Children: Explaining the Unexplained Variance.

ERIC Educational Resources Information Center

Musselman, Carol; Kircaali-Iftar, Gonul

1996-01-01

This study compared 20 young deaf children with either exceptionally good or exceptionally poor spoken language for their hearing loss, age, and intelligence. Factors associated with high performance included earlier use of binaural ear-level aids, better educated mothers, auditory/verbal or auditory/oral instruction, reliance on spoken language…

Commentary--A United Front: Using the Range of Psychological Variance in Cutting-Edge Practice and Emerging Research

ERIC Educational Resources Information Center

Jackson, Simon Anthony; Kleitman, Sabina

2015-01-01

Psychological and behavioral variance can be explained by differences in the environment, and between and within individuals. Almost 60 years ago, Cronbach (1957) called for converging investigations into all three sources as important for the development of accurate science and useful applications in the real world. Yet rifts among researchers…

Assessing the Structure of the Ways of Coping Questionnaire in Fibromyalgia Patients Using Common Factor Analytic Approaches.

PubMed

Van Liew, Charles; Santoro, Maya S; Edwards, Larissa; Kang, Jeremy; Cronan, Terry A

2016-01-01

The Ways of Coping Questionnaire (WCQ) is a widely used measure of coping processes. Despite its use in a variety of populations, there has been concern about the stability and structure of the WCQ across different populations. This study examines the factor structure of the WCQ in a large sample of individuals diagnosed with fibromyalgia. The participants were 501 adults (478 women) who were part of a larger intervention study. Participants completed the WCQ at their 6-month assessment. Foundational factoring approaches were performed on the data (i.e., maximum likelihood factoring [MLF], iterative principal factoring [IPF], principal axis factoring (PAF), and principal components factoring [PCF]) with oblique oblimin rotation. Various criteria were evaluated to determine the number of factors to be extracted, including Kaiser's rule, Scree plot visual analysis, 5 and 10% unique variance explained, 70 and 80% communal variance explained, and Horn's parallel analysis (PA). It was concluded that the 4-factor PAF solution was the preferable solution, based on PA extraction and the fact that this solution minimizes nonvocality and multivocality. The present study highlights the need for more research focused on defining the limits of the WCQ and the degree to which population-specific and context-specific subscale adjustments are needed.

Assessing the Structure of the Ways of Coping Questionnaire in Fibromyalgia Patients Using Common Factor Analytic Approaches

PubMed Central

Edwards, Larissa; Kang, Jeremy

2016-01-01

The Ways of Coping Questionnaire (WCQ) is a widely used measure of coping processes. Despite its use in a variety of populations, there has been concern about the stability and structure of the WCQ across different populations. This study examines the factor structure of the WCQ in a large sample of individuals diagnosed with fibromyalgia. The participants were 501 adults (478 women) who were part of a larger intervention study. Participants completed the WCQ at their 6-month assessment. Foundational factoring approaches were performed on the data (i.e., maximum likelihood factoring [MLF], iterative principal factoring [IPF], principal axis factoring (PAF), and principal components factoring [PCF]) with oblique oblimin rotation. Various criteria were evaluated to determine the number of factors to be extracted, including Kaiser's rule, Scree plot visual analysis, 5 and 10% unique variance explained, 70 and 80% communal variance explained, and Horn's parallel analysis (PA). It was concluded that the 4-factor PAF solution was the preferable solution, based on PA extraction and the fact that this solution minimizes nonvocality and multivocality. The present study highlights the need for more research focused on defining the limits of the WCQ and the degree to which population-specific and context-specific subscale adjustments are needed. PMID:28070160

40 CFR 59.206 - Variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who cannot... reaching a decision on a variance application. Interested members of the public will be allowed a...

Applying the theory of planned behaviour to explain HIV testing in antenatal settings in Addis Ababa - a cohort study

PubMed Central

2011-01-01

Background To facilitate access to the prevention of mother-to-child HIV transmission (PMTCT) services, HIV counselling and testing are offered routinely in antenatal care settings. Focusing a cohort of pregnant women attending public and private antenatal care facilities, this study applied an extended version of the Theory of Planned Behaviour (TPB) to explain intended- and actual HIV testing. Methods A sequential exploratory mixed methods study was conducted in Addis Ababa in 2009. The study involved first time antenatal attendees from public- and private health care facilities. Three Focus Group Discussions were conducted to inform the TPB questionnaire. A total of 3033 women completed the baseline TPB interviews, including attitudes, subjective norms, perceived behavioural control and intention with respect to HIV testing, whereas 2928 completed actual HIV testing at follow up. Data were analysed using descriptive statistics, Chi-square tests, Fisher's Exact tests, Internal consistency reliability, Pearson's correlation, Linear regression, Logistic regression and using Epidemiological indices. P-values < 0.05 was considered significant and 95% Confidence Interval (CI) was used for the odds ratio. Results The TPB explained 9.2% and 16.4% of the variance in intention among public- and private health facility attendees. Intention and perceived barriers explained 2.4% and external variables explained 7% of the total variance in HIV testing. Positive and negative predictive values of intention were 96% and 6% respectively. Across both groups, subjective norm explained a substantial amount of variance in intention, followed by attitudes. Women intended to test for HIV if they perceived social support and anticipated positive consequences following test performance. Type of counselling did not modify the link between intended and actual HIV testing. Conclusion The TPB explained substantial amount of variance in intention to test but was less sufficient in explaining

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

PubMed

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

2013-06-01

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

Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

PubMed

Essers, Geurt; van Dulmen, Sandra; van Weel, Chris; van der Vleuten, Cees; Kramer, Anneke

2011-12-13

Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication performance levels, on average, do not appear adequate. The context of daily practice may require different skills or specific ways of handling these skills, whereas communication skills are mostly treated as generic. So far no empirical analysis of the context has been made. Our aim was to identify context factors that could be related to GP communication. A purposive sample of real-life videotaped GP consultations was analyzed (N = 17). As a frame of reference we chose the MAAS-Global, a widely used assessment instrument for medical communication. By inductive reasoning, we analyzed the GP behaviour in the consultation leading to poor item scores on the MAAS-Global. In these cases we looked for the presence of an intervening context factor, and how this might explain the actual GP communication behaviour. We reached saturation after having viewed 17 consultations. We identified 19 context factors that could potentially explain the deviation from generic recommendations on communication skills. These context factors can be categorized into doctor-related, patient-related, and consultation-related factors. Several context factors seem to influence doctor-patient communication, requiring the GP to apply communication skills differently from recommendations on communication. From this study we conclude that there is a need to explicitly account for context factors in the assessment of GP (and GP registrar) communication performance. The next step is to validate our findings.

Explaining Academic Progress via Combining Concepts of Integration Theory and Rational Choice Theory.

ERIC Educational Resources Information Center

Beekhoven, S.; De Jong, U.; Van Hout, H.

2002-01-01

Compared elements of rational choice theory and integration theory on the basis of their power to explain variance in academic progress. Asserts that the concepts should be combined, and the distinction between social and academic integration abandoned. Empirical analysis showed that an extended model, comprising both integration and rational…

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

Cognitive and Linguistic Sources of Variance in 2-Year-Olds’ Speech-Sound Discrimination: A Preliminary Investigation

PubMed Central

Lalonde, Kaylah; Holt, Rachael Frush

2017-01-01

Purpose This preliminary investigation explored potential cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination by using the toddler change/no-change procedure and examined whether modifications would result in a procedure that can be used consistently with younger 2-year-olds. Method Twenty typically developing 2-year-olds completed the newly modified toddler change/no-change procedure. Behavioral tests and parent report questionnaires were used to measure several cognitive and linguistic constructs. Stepwise linear regression was used to relate discrimination sensitivity to the cognitive and linguistic measures. In addition, discrimination results from the current experiment were compared with those from 2-year-old children tested in a previous experiment. Results Receptive vocabulary and working memory explained 56.6% of variance in discrimination performance. Performance was not different on the modified toddler change/no-change procedure used in the current experiment from in a previous investigation, which used the original version of the procedure. Conclusions The relationship between speech discrimination and receptive vocabulary and working memory provides further evidence that the procedure is sensitive to the strength of perceptual representations. The role for working memory might also suggest that there are specific subject-related, nonsensory factors limiting the applicability of the procedure to children who have not reached the necessary levels of cognitive and linguistic development. PMID:24023371

Cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination: a preliminary investigation.

PubMed

Lalonde, Kaylah; Holt, Rachael Frush

2014-02-01

This preliminary investigation explored potential cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination by using the toddler change/ no-change procedure and examined whether modifications would result in a procedure that can be used consistently with younger 2-year-olds. Twenty typically developing 2-year-olds completed the newly modified toddler change/no-change procedure. Behavioral tests and parent report questionnaires were used to measure several cognitive and linguistic constructs. Stepwise linear regression was used to relate discrimination sensitivity to the cognitive and linguistic measures. In addition, discrimination results from the current experiment were compared with those from 2-year-old children tested in a previous experiment. Receptive vocabulary and working memory explained 56.6% of variance in discrimination performance. Performance was not different on the modified toddler change/no-change procedure used in the current experiment from in a previous investigation, which used the original version of the procedure. The relationship between speech discrimination and receptive vocabulary and working memory provides further evidence that the procedure is sensitive to the strength of perceptual representations. The role for working memory might also suggest that there are specific subject-related, nonsensory factors limiting the applicability of the procedure to children who have not reached the necessary levels of cognitive and linguistic development.

Socioeconomic factors explain racial disparities in invasive community-associated methicillin-resistant Staphylococcus aureus disease rates

PubMed Central

See, Isaac; Wesson, Paul; Gualandi, Nicole; Dumyati, Ghinwa; Harrison, Lee H.; Lesher, Lindsey; Nadle, Joelle; Petit, Susan; Reisenauer, Claire; Schaffner, William; Tunali, Amy; Mu, Yi; Ahern, Jennifer

2017-01-01

Introduction Invasive community-associated methicillin-resistant Staphylococcus aureus (MRSA) incidence in the United States is higher among black persons than white persons. We explored the extent to which socioeconomic factors might explain this racial disparity. Methods A retrospective cohort was based on CDC’s Emerging Infections Program surveillance data for invasive community-associated MRSA cases (isolated from a normally sterile site of an outpatient or on hospital admission day ≤3 in a patient without specified major healthcare exposures) from 2009–2011 in 33 counties of 9 states. We used generalized estimating equations to determine census tract-level factors associated with differences in MRSA incidence and inverse odds ratio weighted mediation analysis to determine the proportion of racial disparity mediated by socioeconomic factors. Results Annual invasive community-associated MRSA incidence was 4.59/100,000 among whites and 7.60/100,000 among blacks (rate ratio: 1.66, 95% CI, 1.52–1.80). In the mediation analysis, after accounting for census tract-level measures of federally-designated medically underserved areas, education, income, housing value, and rural status, 91% of the original racial disparity was explained; no significant association of black race with community-associated MRSA remained (rate ratio: 1.05, 95% CI, 0.92–1.20). Conclusions The racial disparity in invasive community-associated MRSA rates was almost entirely mediated by socioeconomic factors. The specific factors that underlie the association between tract-level socioeconomic measures and MRSA incidence, which may include modifiable social (e.g., poverty, crowding) and biological factors (not explored in this analysis), should be elucidated to define strategies for reducing racial disparities in community-associated MRSA rates. PMID:28362911

Assessing the impact of autonomous motivation and psychological need satisfaction in explaining adherence to an exercise referral scheme.

PubMed

Eynon, Michael John; O'Donnell, Christopher; Williams, Lynn

2017-10-01

Given the mixed findings concerning self-determination theory in explaining adherence to exercise referral schemes (ERS), the present study attempted to examine whether autonomous motivation and psychological need satisfaction could predict ERS adherence. Participants referred to an 8-week ERS completed self-report measures grounded in self-determination theory and basic needs theory at baseline (N = 124), mid-scheme (N = 58), and at the end of the scheme (N = 40). Logistic regressions were used to analyse the data. Autonomous motivation measured at mid-scheme explained between 12 and 16% of the variance in ERS adherence. Autonomy, relatedness and competence measured at mid-scheme explained between 18 and 26% of the variance in ERS adherence. This model also explained between 18 and 25% when measured at the end of the scheme. The study found limited evidence for the role of autonomous motivation in explaining ERS adherence. Stronger support was found for the satisfaction of the three needs for autonomy, relatedness and competence in predicting ERS adherence. Future research should tap into the satisfaction of all three needs collectively to help foster ERS adherence.

Testing five social-cognitive models to explain predictors of personal oral health behaviours and intention to improve them.

PubMed

Dumitrescu, Alexandrina L; Dogaru, Beatrice C; Duta, Carmen; Manolescu, Bogdan N

2014-01-01

To test the ability of several social-cognitive models to explain current behaviour and to predict intentions to engage in three different health behaviours (toothbrushing, flossing and mouthrinsing). Constructs from the health belief model (HBM), theory of reasoned action (TRA), theory of planned behaviour (TPB) and the motivational process of the health action process approach (HAPA) were measured simultaneously in an undergraduate student sample of 172 first-year medical students. Regarding toothbrushing, the TRA, TPB, HBM (without the inclusion of self-efficacy SE), HBM+SE and HAPA predictor models explained 7.4%, 22.7%, 10%, 10.2% and 10.1%, respectively, of the variance in behaviour and 7.5%, 25.6%, 12.1%, 17.5% and 17.2%, respectively, in intention. Regarding dental flossing, the TRA, TPB, HBM, HBM+SE and HAPA predictor models explained 39%, 50.6, 24.1%, 25.4% and 27.7%, respectively, of the variance in behaviour and 39.4%, 52.7%, 33.7%, 35.9% and 43.2%, respectively, in intention. Regarding mouthrinsing, the TRA, TPB, HBM, HBM+SE and HAPA predictor models explained 43.9%, 45.1%, 20%, 29% and 36%, respectively, of the variance in behaviour and 58%, 59.3%, 49.2%, 59.8% and 66.2%, respectively, in intention. The individual significant predictors for current behaviour were attitudes, barriers and outcome expectancy. Our findings revealed that the theory of planned behaviours and the health action process approach were the best predictor of intentions to engage in both behaviours.

Color constancy in natural scenes explained by global image statistics.

PubMed

Foster, David H; Amano, Kinjiro; Nascimento, Sérgio M C

2006-01-01

To what extent do observers' judgments of surface color with natural scenes depend on global image statistics? To address this question, a psychophysical experiment was performed in which images of natural scenes under two successive daylights were presented on a computer-controlled high-resolution color monitor. Observers reported whether there was a change in reflectance of a test surface in the scene. The scenes were obtained with a hyperspectral imaging system and included variously trees, shrubs, grasses, ferns, flowers, rocks, and buildings. Discrimination performance, quantified on a scale of 0 to 1 with a color-constancy index, varied from 0.69 to 0.97 over 21 scenes and two illuminant changes, from a correlated color temperature of 25,000 K to 6700 K and from 4000 K to 6700 K. The best account of these effects was provided by receptor-based rather than colorimetric properties of the images. Thus, in a linear regression, 43% of the variance in constancy index was explained by the log of the mean relative deviation in spatial cone-excitation ratios evaluated globally across the two images of a scene. A further 20% was explained by including the mean chroma of the first image and its difference from that of the second image and a further 7% by the mean difference in hue. Together, all four global color properties accounted for 70% of the variance and provided a good fit to the effects of scene and of illuminant change on color constancy, and, additionally, of changing test-surface position. By contrast, a spatial-frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5% of the variance.

Explaining the impact of poverty on old-age frailty in Europe: material, psychosocial and behavioural factors.

PubMed

Stolz, Erwin; Mayerl, Hannes; Waxenegger, Anja; Freidl, Wolfgang

2017-12-01

Previous research found poverty to be associated with adverse health outcomes among older adults but the factors that translate low economic resources into poor physical health are not well understood. The goal of this analysis was to assess the impact of material, psychosocial, and behavioural factors as well as education in explaining the poverty-health link. In total, 28 360 observations from 11 390 community-dwelling respondents (65+) in the Survey of Health, Ageing and Retirement in Europe (2004-13, 10 countries) were analysed. Multilevel growth curve models were used to assess the impact of combined income and asset poverty risk on old-age frailty (frailty index) and associated pathway variables. In total, 61.8% of the variation of poverty risk on frailty level was explained by direct and indirect effects. Results stress the role of material and particularly psychosocial factors such as perceived control and social isolation, whereas the role of health behaviour was negligible. We suggest to strengthen social policy and public health efforts in order to fight poverty and its deleterious health effects from early age on as well as to broaden the scope of interventions with regard to psychosocial factors. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

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.

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

Intellectual Functioning in In-Patients with Substance Use Disorders: Preliminary Results from a Clinical Mediation Study of Factors Contributing to IQ Variance.

PubMed

Braatveit, Kirsten J; Torsheim, Torbjørn; Hove, Oddbjørn

2018-01-01

To investigate the direct effect of different childhood difficulties on adult intelligence coefficient (IQ) and their possible indirect effect through the mediating pathways of education and severity substance use. Ninety in-patients aged 19-64. The participants had abstained from substance use for at least 6 weeks and had different substance use profiles. Substance use disorder (SUD) and psychiatric illnesses were diagnosed according to the International Classification of Diseases 10th edition criteria. IQ was measured with the Wechsler Adult Intelligence Scale, 4th edition. Childhood difficulties, severity of substance use and level of education were assessed through a self-report questionnaire. Mean full scale IQ for the studied population was 87.3. Learning and attention deficit/hyperactivity difficulties in childhood were directly related to adult IQ. Education had a mediating effect between childhood learning difficulties/conduct problems and the verbal comprehension index. There was no significant difference in IQ due to the specific substance used or severity of substance use. IQ variance in in-treatment individuals with SUD was related to childhood functioning alone or through the mediator of education. Substance-related factors did not contribute to IQ variance. The results fit a normal theory of IQ development with commonly known risk factors and no disturbing effect of substance use. © 2018 S. Karger AG, Basel.

The impact of extrinsic demographic factors on Cantonese speech acquisition.

PubMed

To, Carol K S; Cheung, Pamela S P; McLeod, Sharynne

2013-05-01

This study modeled the associations between extrinsic demographic factors and children's speech acquisition in Hong Kong Cantonese. The speech of 937 Cantonese-speaking children aged 2;4 to 6;7 in Hong Kong was assessed using a standardized speech test. Demographic information regarding household income, paternal education, maternal education, presence of siblings and having a domestic helper as the main caregiver was collected via parent questionnaires. After controlling for age and sex, higher maternal education and higher household income were significantly associated with better speech skills; however, these variables explained a negligible amount of variance. Paternal education, number of siblings and having a foreign domestic helper did not associate with a child's speech acquisition. Extrinsic factors only exerted minimal influence on children's speech acquisition. A large amount of unexplained variance in speech ability still warrants further research.

Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants.

PubMed

Bonetti, Debbie; Johnston, Marie; Clarkson, Jan E; Grimshaw, Jeremy; Pitts, Nigel B; Eccles, Martin; Steen, Nick; Thomas, Ruth; Maclennan, Graeme; Glidewell, Liz; Walker, Anne

2010-04-08

Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value. Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention. The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

PubMed Central

Mulder, Herman A.; Hill, William G.; Knol, Egbert F.

2015-01-01

There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others. PMID:25631318

Individual and contextual factors associated with verbal bullying among Brazilian adolescents.

PubMed

Azeredo, Catarina Machado; Levy, Renata Bertazzi; Araya, Ricardo; Menezes, Paulo Rossi

2015-05-01

Few studies have been carried out in low- middle-income countries assessing contextual characteristics associated with bullying. This study aimed to assess the relative importance of contextual (school and city) and individual-level factors to explain the variance in verbal bullying among a nationally representative sample of Brazilian adolescents. 59,348 students from 1,453 schools and 26 state capitals and the Federal District participated in the National Survey of School Health among 9th Grade Students (PeNSE, 2009). We performed multilevel logistic regression in a three level model (individual, school and city). The 30-day prevalence of verbal bullying among these students was 14.2%. We found that 1.8% and 0.3% of the total variance in bullying occurred at school-level and city-level, respectively, and 97.9% at individual-level. At city-level, all factors included failed to demonstrate a significant association with bullying (p < 0.05) whereas at school-level, private schools presented more bullying than public schools (OR = 1.17, CI 1.04-1.31). At individual-level, male gender, younger age, not living with both parents, exposed to domestic violence, under or overweight were all associated with bullying. All socioeconomic indicators assessed contributed little to explain the variance in bullying at individual, school or city-level. Population subgroups at risk identified according to their individual profile could be targeted in future interventions in Brazil.

On the Design of Attitude-Heading Reference Systems Using the Allan Variance.

PubMed

Hidalgo-Carrió, Javier; Arnold, Sascha; Poulakis, Pantelis

2016-04-01

The Allan variance is a method to characterize stochastic random processes. The technique was originally developed to characterize the stability of atomic clocks and has also been successfully applied to the characterization of inertial sensors. Inertial navigation systems (INS) can provide accurate results in a short time, which tend to rapidly degrade in longer time intervals. During the last decade, the performance of inertial sensors has significantly improved, particularly in terms of signal stability, mechanical robustness, and power consumption. The mass and volume of inertial sensors have also been significantly reduced, offering system-level design and accommodation advantages. This paper presents a complete methodology for the characterization and modeling of inertial sensors using the Allan variance, with direct application to navigation systems. Although the concept of sensor fusion is relatively straightforward, accurate characterization and sensor-information filtering is not a trivial task, yet they are essential for good performance. A complete and reproducible methodology utilizing the Allan variance, including all the intermediate steps, is described. An end-to-end (E2E) process for sensor-error characterization and modeling up to the final integration in the sensor-fusion scheme is explained in detail. The strength of this approach is demonstrated with representative tests on novel, high-grade inertial sensors. Experimental navigation results are presented from two distinct robotic applications: a planetary exploration rover prototype and an autonomous underwater vehicle (AUV).

Factors influencing self-reported vision-related activity limitation in the visually impaired.

PubMed

Tabrett, Daryl R; Latham, Keziah

2011-07-15

The use of patient-reported outcome (PRO) measures to assess self-reported difficulty in visual activities is common in patients with impaired vision. This study determines the visual and psychosocial factors influencing patients' responses to self-report measures, to aid in understanding what is being measured. One hundred visually impaired participants completed the Activity Inventory (AI), which assesses self-reported, vision-related activity limitation (VRAL) in the task domains of reading, mobility, visual information, and visual motor tasks. Participants also completed clinical tests of visual function (distance visual acuity and near reading performance both with and without low vision aids [LVAs], contrast sensitivity, visual fields, and depth discrimination), and questionnaires assessing depressive symptoms, social support, adjustment to visual loss, and personality. Multiple regression analyses identified that an acuity measure (distance or near), and, to a lesser extent, near reading performance without LVAs, visual fields, and contrast sensitivity best explained self-reported VRAL (28%-50% variance explained). Significant psychosocial correlates were depression and adjustment, explaining an additional 6% to 19% unique variance. Dependent on task domain, the parameters assessed explained 59% to 71% of the variance in self-reported VRAL. Visual function, most notably acuity without LVAs, is the best predictor of self-reported VRAL assessed by the AI. Depression and adjustment to visual loss also significantly influence self-reported VRAL, largely independent of the severity of visual loss and most notably in the less vision-specific tasks. The results suggest that rehabilitation strategies addressing depression and adjustment could improve perceived visual disability.

Scale dependence in species turnover reflects variance in species occupancy.

PubMed

McGlinn, Daniel J; Hurlbert, Allen H

2012-02-01

Patterns of species turnover may reflect the processes driving community dynamics across scales. While the majority of studies on species turnover have examined pairwise comparison metrics (e.g., the average Jaccard dissimilarity), it has been proposed that the species-area relationship (SAR) also offers insight into patterns of species turnover because these two patterns may be analytically linked. However, these previous links only apply in a special case where turnover is scale invariant, and we demonstrate across three different plant communities that over 90% of the pairwise turnover values are larger than expected based on scale-invariant predictions from the SAR. Furthermore, the degree of scale dependence in turnover was negatively related to the degree of variance in the occupancy frequency distribution (OFD). These findings suggest that species turnover diverges from scale invariance, and as such pairwise turnover and the slope of the SAR are not redundant. Furthermore, models developed to explain the OFD should be linked with those developed to explain species turnover to achieve a more unified understanding of community structure.

Low Impact of Traditional Risk Factors on Carotid Intima-Media Thickness: The ELSA-Brasil Cohort.

PubMed

Santos, Itamar S; Alencar, Airlane P; Rundek, Tatjana; Goulart, Alessandra C; Barreto, Sandhi M; Pereira, Alexandre C; Benseñor, Isabela M; Lotufo, Paulo A

2015-09-01

There is little information about how much traditional cardiovascular risk factors explain common carotid artery intima-media thickness (CCA-IMT) variance. We aimed to study to which extent CCA-IMT values are determined by traditional risk factors and which commonly used measurements of blood pressure, glucose metabolism, lipid profile, and adiposity contribute the most to this determination in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort baseline. We analyzed 9792 individuals with complete data and CCA-IMT measurements. We built multiple linear regression models using mean left and right CCA-IMT as the dependent variable. All models were stratified by sex. We also analyzed individuals stratified by 10-year coronary heart disease risk and, in separate, those with no traditional risk factors. Main models' R(2) varied between 0.141 and 0.373. The major part of the explained variance in CCA-IMT was because of age and race. Indicators of blood pressure, lipid profile, and adiposity that most frequently composed the best models were pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference. The association between neck circumference and CCA-IMT persisted significant even after further adjustment for vessel sizes and body mass index. Indicators of glucose metabolism had smaller contribution. We found that >60% of CCA-IMT were not explained by demographic and traditional cardiovascular risk factors, which highlights the need to study novel risk factors. Pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference were the most consistent contributors. © 2015 American Heart Association, Inc.

[Validity and factorial invariance of the social ecological model in explaining fruit intake in Mexican schoolchildren].

PubMed

Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A

2014-11-24

To test the goodness of fit of a Motivation-Ability-Opportunity model (MAO-model) to evaluate the observed variance in Mexican schoolchildren's preferences to eat fruit and daily fruit intake; also to evaluate the factorial invariance across the gender and type of population (urban and semi-urban) in which children reside. A model with seven constructs was designed from a validated questionnaire to assess preferences, cognitive abilities, attitude, modelling, perceived barriers, accessibility at school, accessibility at home, and fruit intake frequency. The instrument was administered in a representative sample of 1434 schoolchildren of 5th and 6th grade of primary school in a cross-sectional and ex post fact study conducted in 2013 in six cities of the State of Chihuahua, Mexico. The goodness of fit indexes was adequate for the MAO-model and explained 39% of the variance in preference to eat fruit. The structure of the model showed very good factor structure stability and the dimensions of the scale were equivalent in the different samples analyzed. The model analyzed with structural equation modeling showed a parsimonious model that can be used to explain the variation in fruit intake of 10 to 12 year old Mexican schoolchildren. The structure of the model was strictly invariant in the different samples analyzed and showed evidence of cross validation. Finally, implications about the modification model to fit data from scholar settings and guidelines for future research are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

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.

Using social cognitive theory to explain discretionary, "leisure-time" physical exercise among high school students.

PubMed

Winters, Eric R; Petosa, Rick L; Charlton, Thomas E

2003-06-01

To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.

Body fat distribution in the Finnish population: environmental determinants and predictive power for cardiovascular risk factor levels.

PubMed Central

Marti, B; Tuomilehto, J; Salomaa, V; Kartovaara, L; Korhonen, H J; Pietinen, P

1991-01-01

STUDY OBJECTIVE--The aim was to examine (1) whether health habits are associated with body fat distribution, as measured by the waist/hip girth ratio, and (2) to what extent environmental factors, including anthropometric characteristics, explain the variability in levels of cardiovascular risk factors. DESIGN--The study was a population based cross sectional survey, conducted in the spring of 1987 as a part of an international research project on cardiovascular epidemiology. SETTING--The survey was conducted in three geographical areas of eastern and south western Finland. SUBJECTS--2526 men and 2756 women aged 25-64 years took part in the study, corresponding to a survey participation rate of 82%. MEASUREMENTS AND MAIN RESULTS--In men, waist/hip ratio showed stronger associations with exercise (Pearson's r = -0.24), resting heart rate (r = 0.10), alcohol consumption (r = 0.07), smoking (r = 0.05), and education (r = -0.23) than did body mass index. Jointly, exercise, resting heart rate, alcohol consumption, education, and age explained 18% of variance in male waist/hip ratio, but only 9% of variance in male body mass index. In women, environmental factors were more predictive for body mass index than for waist/hip ratio, with age and education being the strongest determinants. Waist/hip ratio and body mass index were approximately equally strong predictors of cardiovascular risk factor levels. The additional predictive power of waist/hip ratio over and above body mass index was tested in a hierarchical, stepwise regression. In this conservative type of analysis the increase in explained variance uniquely attributable to waist/hip ratio was 2-3% for female and 1-2% for male lipoprotein levels, and less than 0.5% for female and 0-2% for male blood pressure values. CONCLUSIONS--The distribution of abdominal obesity in Finland is significantly influenced by health habits and sociodemographic factors in both men and women. This in turn is obviously one reason for the

Polarization in Raman spectroscopy helps explain bone brittleness in genetic mouse models

NASA Astrophysics Data System (ADS)

Makowski, Alexander J.; Pence, Isaac J.; Uppuganti, Sasidhar; Zein-Sabatto, Ahbid; Huszagh, Meredith C.; Mahadevan-Jansen, Anita; Nyman, Jeffry S.

2014-11-01

Raman spectroscopy (RS) has been extensively used to characterize bone composition. However, the link between bone biomechanics and RS measures is not well established. Here, we leveraged the sensitivity of RS polarization to organization, thereby assessing whether RS can explain differences in bone toughness in genetic mouse models for which traditional RS peak ratios are not informative. In the selected mutant mice-activating transcription factor 4 (ATF4) or matrix metalloproteinase 9 (MMP9) knock-outs-toughness is reduced but differences in bone strength do not exist between knock-out and corresponding wild-type controls. To incorporate differences in the RS of bone occurring at peak shoulders, a multivariate approach was used. Full spectrum principal components analysis of two paired, orthogonal bone orientations (relative to laser polarization) improved genotype classification and correlation to bone toughness when compared to traditional peak ratios. When applied to femurs from wild-type mice at 8 and 20 weeks of age, the principal components of orthogonal bone orientations improved age classification but not the explanation of the maturation-related increase in strength. Overall, increasing polarization information by collecting spectra from two bone orientations improves the ability of multivariate RS to explain variance in bone toughness, likely due to polarization sensitivity to organizational changes in both mineral and collagen.

Risk factors cannot explain the higher prevalence rates of precancerous colorectal lesions in men

PubMed Central

Waldmann, Elisabeth; Heinze, Georg; Ferlitsch, Arnulf; GessI, Irina; Sallinger, Daniela; Jeschek, Philip; Britto-Arias, Martha; Salzl, Petra; Fasching, Elisabeth; Jilma, Bernd; Kundi, Michael; Trauner, Michael; Ferlitsch, Monika

2016-01-01

Background: Prevalence of (pre)cancerous colorectal lesions are higher in men than in women, although transition rates from advanced lesions to cancer is similar in both sexes. Our aim was to investigate whether the sex-specific difference in incidence of premalignant colorectal lesions might be explained by the impact of risk factors. Methods: A cross-sectional study analysing health check-up examinations and screening colonoscopies performed within a national quality assurance program. Results: A total of 25 409 patients were included in this study, 50.8% were women. Median age for both sexes was 60 years (interquartile range (IQR) 54–67). A multivariable model showed that risk factors mediated only 0.6 of the 10.4% gender gap in adenoma and 0.47 of the 3.2% gender gap in advanced adenoma detection rate. Smoking was the only independent risk factor with a varying sex-specific effect (men OR 1.46, CI 1.29, 1.64, women OR 1.76, CI 1.53, 2.06) and advanced adenomas (men OR 1.06, CI 0.80–1.42; women OR 2.08, CI 1.52–2.83). Independent risk factors for adenomas were BMI (OR 1.35 per IQR, CI 1.25–1.47) and triglyceride level (OR 1.03 per IQR, CI 1.00–1.06); for advanced adenomas physical activity (none vs regular: OR 1.54, CI 1.18–2.00, occasional vs regular: OR 1.17, CI 1.00–1.38), cholesterol level (OR 1.13 per IQR, CI 1.02–1.25), blood glucose level (OR 1.05 per IQR, CI 1.01–1.09) and alcohol score (OR 1.09 per IQR, CI 1.01–1.18). Conclusions: Risk factors cannot explain higher prevalence rates in men. Results of this study strongly underline the need for sex-specific screening recommendations. PMID:27764840

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

PubMed

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

2011-02-01

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

Color constancy in natural scenes explained by global image statistics

PubMed Central

Foster, David H.; Amano, Kinjiro; Nascimento, Sérgio M. C.

2007-01-01

To what extent do observers' judgments of surface color with natural scenes depend on global image statistics? To address this question, a psychophysical experiment was performed in which images of natural scenes under two successive daylights were presented on a computer-controlled high-resolution color monitor. Observers reported whether there was a change in reflectance of a test surface in the scene. The scenes were obtained with a hyperspectral imaging system and included variously trees, shrubs, grasses, ferns, flowers, rocks, and buildings. Discrimination performance, quantified on a scale of 0 to 1 with a color-constancy index, varied from 0.69 to 0.97 over 21 scenes and two illuminant changes, from a correlated color temperature of 25,000 K to 6700 K and from 4000 K to 6700 K. The best account of these effects was provided by receptor-based rather than colorimetric properties of the images. Thus, in a linear regression, 43% of the variance in constancy index was explained by the log of the mean relative deviation in spatial cone-excitation ratios evaluated globally across the two images of a scene. A further 20% was explained by including the mean chroma of the first image and its difference from that of the second image and a further 7% by the mean difference in hue. Together, all four global color properties accounted for 70% of the variance and provided a good fit to the effects of scene and of illuminant change on color constancy, and, additionally, of changing test-surface position. By contrast, a spatial-frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5% of the variance. PMID:16961965

Factor Analysis of the Community Balance and Mobility Scale in Individuals with Knee Osteoarthritis.

PubMed

Takacs, Judit; Krowchuk, Natasha M; Goldsmith, Charles H; Hunt, Michael A

2017-10-01

The clinical assessment of balance is an important first step in characterizing the risk of falls. The Community Balance and Mobility Scale (CB&M) is a test of balance and mobility that was designed to assess performance on advanced tasks necessary for independence in the community. However, other factors that can affect balancing ability may also be present during performance of the real-world tasks on the CB&M. It is important for clinicians to understand fully what other modifiable factors the CB&M may encompass. The purpose of this study was to evaluate the underlying constructs in the CB&M in individuals with knee osteoarthritis (OA). This was an observational study, with a single testing session. Participants with knee OA aged 50 years and older completed the CB&M, a clinical test of balance and mobility. Confirmatory factor analysis was then used to examine whether the tasks on the CB&M measure distinct factors. Three a priori theory-driven models with three (strength, balance, mobility), four (range of motion added) and six (pain and fear added) constructs were evaluated using multiple fit indices. A total of 131 participants (mean [SD] age 66.3 [8.5] years, BMI 27.3 [5.2] kg m -2 ) participated. A three-factor model in which all tasks loaded on these three factors explained 65% of the variance and yielded the most optimal model, as determined using scree plots, chi-squared values and explained variance. The first factor accounted for 49% of the variance and was interpreted as lower limb muscle strength. The second and third factors were interpreted as mobility and balance, respectively. The CB&M demonstrated the measurement of three distinct factors, interpreted as lower limb strength, balance and mobility, supporting the use of the CB&M with people with knee OA for evaluation of these important factors in falls risk and functional mobility. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A single question about a respondent's perceived financial ability to pay monthly bills explains more variance in health utility scores than absolute income and assets questions.

PubMed

Hanmer, Janel; Cherepanov, Dasha

2016-09-01

To evaluate a general question about ability to meet monthly bills as an alternative to direct questions about income and assets in health utility studies. We used data from the National Health Measurement Study-a US nationally representative telephone survey collected in 2005-2006. It included health utility measures (EuroQol-5D-3L, Health Utilities Index Mark 3, Short Form-6D, and Quality of Well-being Index) and household income, assets, and financial ability to meet monthly bills questions. Each utility score was regressed on: income and assets (Model 1); difficulty paying bills (DPB) (Model 2); income, assets, and DPB (Model 3). All models used survey weights and adjusted for demographics and education. Among 3666 respondents, as income and assets increased, DPB decreased. The DPB question had fewer missing values (n = 30) than income (n = 311) or assets (n = 373). Model 2 (DPB only) explained more variance in health utility than Model 1 (income and assets only). Including all measures (Model 3) had very modest improvement in R (2), e.g., values were 0.112 (Model 1), 0.166 (Model 2), and 0.175 (Model 3) for EuroQol-5D-3L. The single question on DPB yields more information and has less missing values than the traditionally used income and assets questions.

African American patients' intent to screen for colorectal cancer: Do cultural factors, health literacy, knowledge, age and gender matter?

PubMed

Brittain, Kelly; Christy, Shannon M; Rawl, Susan M

2016-02-01

African Americans have higher colorectal cancer (CRC) mortality rates. Research suggests that CRC screening interventions targeting African Americans be based upon cultural dimensions. Secondary analysis of data from African-Americans who were not up-to-date with CRC screening (n=817) was conducted to examine: 1) relationships among cultural factors (i.e., provider trust, cancer fatalism, health temporal orientation (HTO)), health literacy, and CRC knowledge; 2) age and gender differences; and 3) relationships among the variables and CRC screening intention. Provider trust, fatalism, HTO, health literacy and CRC knowledge had significant relationships among study variables. The FOBT intention model explained 43% of the variance with age and gender being significant predictors. The colonoscopy intention model explained 41% of the variance with gender being a significant predictor. Results suggest that when developing CRC interventions for African Americans, addressing cultural factors remain important, but particular attention should be given to the age and gender of the patient.

Explaining Vegetable Consumption among Young Adults: An Application of the Theory of Planned Behaviour.

PubMed

Menozzi, Davide; Sogari, Giovanni; Mora, Cristina

2015-09-10

Although fruit and vegetable consumption is highly recommended for a healthy and balanced daily diet, several European countries do not meet these recommendations. In Italy, only 45% of young people are consuming at least one portion of vegetables per day. Therefore, this paper aims to understand the main determinants of vegetables consumption among young adults to suggest possible intervention strategies. A cross-sectional study was conducted on a samples of Italian students (n = 751), using the theory of planned behaviour (TPB) as a conceptual framework. A structural equation model (SEM) was developed to test the TPB predictors for vegetable consumption, and the role of background factors (socio-demographic and personal characteristics) in improving the TPB model's explaining power. Overall, 81% and 68%, respectively, of intentions and behaviour variance is explained by the TPB model. Socio-demographic and personal characteristics were found to influence intentions and behaviour indirectly by their effects on the theory's more proximal determinants. Interventions should be targeted to improve perceived behavioural control (PBC), attitudes and subjective norms that significantly affect intentions. Tailored interventions for male students, enrolled in courses other than food science, and doing less physical activity may have a larger effect on behavioural change.

Analysis of Variance with Summary Statistics in Microsoft® Excel®

ERIC Educational Resources Information Center

Larson, David A.; Hsu, Ko-Cheng

2010-01-01

Students regularly are asked to solve Single Factor Analysis of Variance problems given only the sample summary statistics (number of observations per category, category means, and corresponding category standard deviations). Most undergraduate students today use Excel for data analysis of this type. However, Excel, like all other statistical…

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

Schizophrenia with prominent catatonic features ('catatonic schizophrenia'). II. Factor analysis of the catatonic syndrome.

PubMed

Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Gerevich, Jozsef

2007-03-30

Previous factor analyses of catatonia have yielded conflicting results for several reasons including small and/or diagnostically heterogeneous samples and incomparability or lack of standardized assessment. This study examined the factor structure of catatonia in a large, diagnostically homogenous sample of patients with chronic schizophrenia using standardized rating instruments. A random sample of 225 Chinese inpatients diagnosed with schizophrenia according to DSM-IV criteria were selected from the long-stay wards of a psychiatric hospital. They were assessed with a battery of rating scales measuring psychopathology, extrapyramidal motor status, and level of functioning. Catatonia was rated using the Bush-Francis Catatonia Rating Scale. Factor analysis using principal component analysis and Varimax rotation with Kaiser normalization was performed. Four factors were identified with Eigenvalues of 3.27, 2.58, 2.28 and 1.88. The percentage of variance explained by each of the four factors was 15.9%, 12.0%, 11.8% and 10.2% respectively, and together they explained 49.9% of the total variance. Factor 1 loaded on "negative/withdrawn" phenomena, Factor 2 on "automatic" phenomena, Factor 3 on "repetitive/echo" phenomena and Factor 4 on "agitated/resistive" phenomena. In multivariate linear regression analysis negative symptoms and akinesia were associated with 'negative' catatonic symptoms, antipsychotic doses and atypical antipsychotics with 'automatic' symptoms, length of current admission, severity of psychopathology and younger age at onset with 'repetitive' symptoms and age, poor functioning and severity of psychopathology with 'agitated' catatonic symptom scores. The results support recent findings that four main factors underlie catatonic signs/symptoms in chronic schizophrenia.

Genome-Wide Mapping of Loci Explaining Variance in Scrotal Circumference in Nellore Cattle

PubMed Central

Utsunomiya, Yuri T.; Carmo, Adriana S.; Neves, Haroldo H. R.; Carvalheiro, Roberto; Matos, Márcia C.; Zavarez, Ludmilla B.; Ito, Pier K. R. K.; Pérez O'Brien, Ana M.; Sölkner, Johann; Porto-Neto, Laercio R.; Schenkel, Flávio S.; McEwan, John; Cole, John B.; da Silva, Marcos V. G. B.; Van Tassell, Curtis P.; Sonstegard, Tad S.; Garcia, José Fernando

2014-01-01

The reproductive performance of bulls has a high impact on the beef cattle industry. Scrotal circumference (SC) is the most recorded reproductive trait in beef herds, and is used as a major selection criterion to improve precocity and fertility. The characterization of genomic regions affecting SC can contribute to the identification of diagnostic markers for reproductive performance and uncover molecular mechanisms underlying complex aspects of bovine reproductive biology. In this paper, we report a genome-wide scan for chromosome segments explaining differences in SC, using data of 861 Nellore bulls (Bos indicus) genotyped for over 777,000 single nucleotide polymorphisms. Loci that excel from the genome background were identified on chromosomes 4, 6, 7, 10, 14, 18 and 21. The majority of these regions were previously found to be associated with reproductive and body size traits in cattle. The signal on chromosome 14 replicates the pleiotropic quantitative trait locus encompassing PLAG1 that affects male fertility in cattle and stature in several species. Based on intensive literature mining, SP4, MAGEL2, SH3RF2, PDE5A and SNAI2 are proposed as novel candidate genes for SC, as they affect growth and testicular size in other animal models. These findings contribute to linking reproductive phenotypes to gene functions, and may offer new insights on the molecular biology of male fertility. PMID:24558400

40 CFR 142.41 - Variance request.

Code of Federal Regulations, 2011 CFR

2011-07-01

....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

40 CFR 142.41 - Variance request.

Code of Federal Regulations, 2010 CFR

2010-07-01

....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

To what extent is the familial risk of rheumatoid arthritis explained by established rheumatoid arthritis risk factors?

PubMed

Jiang, Xia; Frisell, Thomas; Askling, Johan; Karlson, Elizabeth W; Klareskog, Lars; Alfredsson, Lars; Källberg, Henrik

2015-02-01

Family history of rheumatoid arthritis (RA) is one of the strongest risk factors for developing RA, and information on family history is, therefore, routinely collected in clinical practice. However, as more genetic and environmental risk factors shared by relatives are identified, the importance of family history may diminish. The aim of this study was to determine how much of the familial risk of RA can be explained by established genetic and nongenetic risk factors. History of RA among first-degree relatives of individuals in the Epidemiological Investigation of Rheumatoid Arthritis case-control study was assessed through linkage to the Swedish Multigeneration Register and the Swedish Patient Register. We used logistic regression models to investigate the decrease in familial risk after successive adjustment for combinations of nongenetic risk factors (smoking, alcohol intake, parity, silica exposure, body mass index, fatty fish consumption, and education), and genetic risk factors (shared epitope [SE] and 76 single-nucleotide polymorphisms [SNPs]). Established nongenetic risk factors did not explain familial risk of either seropositive or seronegative RA to any significant degree. Genetic risk factors accounted for a limited proportion of the familial risk of seropositive RA (unadjusted odds ratio [OR] 4.10, SE-adjusted OR 3.72, SNP-adjusted OR 3.46, and SE and SNP-adjusted OR 3.35). Established risk factors only provided an explanation for familial risk of RA in minor part, suggesting that many (familial) risk factors remain to be identified, in particular for seronegative RA. Family history of RA therefore remains an important clinical risk factor for RA, the value of which has not yet been superseded by other information. There is thus a need for further etiologic studies of both seropositive and seronegative RA. Copyright © 2015 by the American College of Rheumatology.

Estimating the encounter rate variance in distance sampling

USGS Publications Warehouse

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

Explaining outputs of primary health care: population and practice factors.

PubMed Central

Baker, D; Klein, R

1991-01-01

OBJECTIVE--To examine whether variations in the activities of general practice among family health service authorities can be explained by the populations characteristics and the organisation and resourcing of general practice. DESIGN--The family health services authorities were treated as discrete primary health care systems. Nineteen performance indicators reflecting the size, distribution, and characteristics of the population served; the organisation of general practice (inputs); and the activities generated by general practitioners and their staff (output) were analysed by stepwise regression. SETTING--90 family health services authorities in England. MAIN OUTCOME MEASURES--Rates of cervical smear testing, immunisation, prescribing, and night visiting. RESULTS--53% of the variation in uptake of cervical cytology was accounted for by Jarman score (t = -3.3), list inflation (-0.41), the proportion of practitioners over 65 (-0.64), the number of ancillary staff per practitioner (2.5), and 70% of the variation in immunisation rates by standardised mortality ratios (-6.6), the proportion of practitioners aged over 65 (-4.8), and the number of practice nurses per practitioner (3.5). Standardised mortality ratios (8.4), the number of practitioners (2.3), and the proportion over 65 (2.2), and the number of ancillary staff per practitioner (-3.1) accounted for 69% of variation in prescribing rates. 54% of the variation in night visiting was explained by standardised mortality ratios (7.1), the proportion of practitioners with lists sizes below 1000 (-2.2), the proportion aged over 65 (-0.4), and the number of practice nurses per practitioner (-2.5). CONCLUSIONS--Family health services authorities are appropriate systems for studying output of general practice. Their performance indicators need to be refined and to be linked to other relevant factors, notably the performance of hospital, community, and social services. PMID:1653065

Structure analysis of simulated molecular clouds with the Δ-variance

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

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

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

Structure analysis of simulated molecular clouds with the Δ-variance

DOE PAGES

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

2015-05-27

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

An attempt to explain why Tanzanian children drinking water containing 0.2 or 3.6 mg fluoride per liter exhibit a similar level of dental fluorosis.

PubMed

Awadia, A K; Birkeland, J M; Haugejorden, O; Bjorvatn, K

2000-12-01

The aim of this study was to identify factors that might explain the similar level of prevalence and severity of dental fluorosis in two neighboring areas in Tanzania: Kibosho; 0.2 mg fluoride/l, n = 96 and Arusha; 3.6 mg fluoride/l in drinking water, n = 80. Subjects aged 8-16 years were examined for dental fluorosis using the Thylstrup and Fejerskov Index (TFI). Based on the score on the upper left central incisor, the prevalence was not significantly different between the communities (TFI > or = 1). The severity, however, was significantly higher in Arusha. The areas had different food habits, e.g., type of weaning food used, and the use of magadi, a fluoride containing salt. In Arusha, 99% of the children had been given lishe, which is a magadi-free weaning food. Conversely in Kibosho, 61% used lishe while 39% used the magadi-containing weaning food kiborou. Magadi was used as food tenderizer in 'adult food' by 98% in Kibosho and 45% in Arusha. Residential area and use of magadi explained 5% of the variance in TFI scores in inter-area analyses. In intra-area analyses, weaning food in Kibosho and use of magadi in Arusha had a significant effect, but the total explained variance was only 5 and 4%, respectively. Apart from fluoride in the drinking water, other sources of fluoride such as use of magadi in weaning food (kiborou) and in the adult food may partly explain the high prevalence and severity of dental fluorosis in the community with 0.2 mg fluoride per liter in the drinking water.

Personal and macro-systemic factors as predictors of quality of life in chronic schizophrenia.

PubMed

Fontanil-Gómez, Yolanda; Alcedo Rodríguez, María A; Gutiérrez López, María I

2017-05-01

The goal of this research was to establish possible predictive factors for both subjective and externally assessed quality of life in people with chronic schizophrenia. Sixty-eight people with schizophrenia took part in the study and were assessed using the World Health Organisation Quality of Life Assessment - Brief Version (WHOQOL-BREF), the Quality of Life Scale (QLS), the Positive and Negative Syndrome Scale for Schizophrenia (PANSS), the Global Assessment of Functioning (GAF), the Social Functioning Scale (SFS) tests. Correlations and multiple regression analysis were conducted to determine possible predictors of quality of life. The residential environment (rural/urban), diagnosis, age at onset of disorder, global functioning and social functioning explained 68% of the total variance based on proxies’ assessment quality of life. Living arrangements and social functioning emerged as predictor variables for subjective quality of life, explaining a 47.3% of the total variance. Socio-cultural factors, such as social integration or the quality of interpersonal relationships, have more influence on these peoples’ physical and psychological health than certain personal factors, such as psychopathology. It is therefore advisable to pay attention to the environment and macro-systemic variables when developing intervention plans to improve their quality of life.

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

Factor analysis of responses to the Irrational Beliefs Scale in a sample of Iraqi university students.

PubMed

Hassan, Namir; Ismail, Hairul Nizam

2004-06-01

In a study of irrational beliefs within a university population, 282 male and 238 female students responded to the 33-item Students' Irrational Beliefs Scale, and their responses were factor analyzed. Analysis suggested six dimensions could explain 39.5% of the variance. These dimensions were Perfectionism, Negativism, Blame Proneness, Escapism, Anxious Over Concern, and Absolute Demands.

The extended Theory of Planned Behavior in explaining exclusive breastfeeding intention and behavior among women in Kelantan, Malaysia.

PubMed

Tengku Ismail, Tengku Alina; Wan Muda, Wan Abdul Manan; Bakar, Mohd Isa

2016-02-01

The purpose of this study is to utilize an extended Theory of Planned Behavior in identifying predictors of exclusive breastfeeding intention and behavior among women in Kelantan, Malaysia. A prospective cohort study was conducted, recruiting pregnant womenthrough two-stage cluster sampling. Their exclusive breastfeeding intention, attitude, perceived norm, perceived behavioral control and past behavior were obtained at baseline through interviewer-guided questionnaire. At one month after delivery, another interview was conducted to determine the two additional variables in the extended theory, which were their postpartum support and breastfeeding difficulty. The behavior, which was the actual duration of exclusive breastfeeding, was obtained from the second follow-up at six months. Pearson correlation and two hierarchical regression analyses were conducted. A total of 200 women completed the study follow-up. Their median intended exclusive breastfeeding duration was 4.0 (IQR 5) months, and the median actual duration was 1.0 (IQR 4) month. The Theory of Planned Behavior explained 51.0% of the variance in intention, with perceived behavioral control and attitude were the significant predictors. It also explained 10.0% of the variance in behavior, but the addition of postpartum support and breastfeeding difficulty increased the amount of explained variance in behavior by 6.0%. The significant predictors of exclusive breastfeeding behavior were intention, postpartum support and breastfeeding difficulty. The extended Theory of Planned Behaviorhad a good predictive ability in explaining exclusive breastfeedingintention and behavior. The women's intention to practice exclusive breastfeeding may be improved by improving their perceived behavioral control and attitude. Providing correct postpartum support and skills to handle breastfeeding difficulties after delivery will improve their exclusive breastfeeding behavior.

The extended Theory of Planned Behavior in explaining exclusive breastfeeding intention and behavior among women in Kelantan, Malaysia

PubMed Central

Wan Muda, Wan Abdul Manan; Bakar, Mohd Isa

2016-01-01

BACKGROUND/OBJECTIVES The purpose of this study is to utilize an extended Theory of Planned Behavior in identifying predictors of exclusive breastfeeding intention and behavior among women in Kelantan, Malaysia. SUBJECTS/METHODS A prospective cohort study was conducted, recruiting pregnant womenthrough two-stage cluster sampling. Their exclusive breastfeeding intention, attitude, perceived norm, perceived behavioral control and past behavior were obtained at baseline through interviewer-guided questionnaire. At one month after delivery, another interview was conducted to determine the two additional variables in the extended theory, which were their postpartum support and breastfeeding difficulty. The behavior, which was the actual duration of exclusive breastfeeding, was obtained from the second follow-up at six months. Pearson correlation and two hierarchical regression analyses were conducted. RESULTS A total of 200 women completed the study follow-up. Their median intended exclusive breastfeeding duration was 4.0 (IQR 5) months, and the median actual duration was 1.0 (IQR 4) month. The Theory of Planned Behavior explained 51.0% of the variance in intention, with perceived behavioral control and attitude were the significant predictors. It also explained 10.0% of the variance in behavior, but the addition of postpartum support and breastfeeding difficulty increased the amount of explained variance in behavior by 6.0%. The significant predictors of exclusive breastfeeding behavior were intention, postpartum support and breastfeeding difficulty. CONCLUSION The extended Theory of Planned Behaviorhad a good predictive ability in explaining exclusive breastfeedingintention and behavior. The women's intention to practice exclusive breastfeeding may be improved by improving their perceived behavioral control and attitude. Providing correct postpartum support and skills to handle breastfeeding difficulties after delivery will improve their exclusive breastfeeding

Nonlinear Epigenetic Variance: Review and Simulations

ERIC Educational Resources Information Center

Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.

2010-01-01

We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…

The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

PubMed

Pressley, Joanna; Troyer, Todd W

2011-05-01

The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

Increasing selection response by Bayesian modeling of heterogeneous environmental variances

USDA-ARS?s Scientific Manuscript database

Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

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

Factors That May Explain Differences between Home and Clinic Meal Preparation Task Assessments in Frail Older Adults

ERIC Educational Resources Information Center

Provencher, Veronique; Demers, Louise; Gelinas, Isabelle

2012-01-01

Meal preparation assessments conducted in clinical environments (such as rehabilitation settings) might not reflect frail patients' performance at home. In addition, factors that may explain differences in performance between settings remain unknown. The aim of this study was to compare home and clinic performance on meal preparation tasks in…

The Pricing of European Options Under the Constant Elasticity of Variance with Stochastic Volatility

NASA Astrophysics Data System (ADS)

Bock, Bounghun; Choi, Sun-Yong; Kim, Jeong-Hoon

This paper considers a hybrid risky asset price model given by a constant elasticity of variance multiplied by a stochastic volatility factor. A multiscale analysis leads to an asymptotic pricing formula for both European vanilla option and a Barrier option near the zero elasticity of variance. The accuracy of the approximation is provided in a rigorous manner. A numerical experiment for implied volatilities shows that the hybrid model improves some of the well-known models in view of fitting the data for different maturities.

Macro-organizational factors, the incidence of work disability, and work ability among the total workforce of home care workers in Sweden.

PubMed

Dellve, Lotta; Karlberg, Catarina; Allebeck, Peter; Herloff, Birgitta; Hagberg, Mats

2006-01-01

To investigate the importance of macro-organizational factors, i.e. organizational sociodemographic and socioeconomic preconditions, of the municipal incidence of long-term sick leave, disability pension, and prevalence of workers with long-term work ability among home care workers. In an ecological study design, data from national databases were combined by record linkage. Descriptive and analytical statistics were used to estimate and interpret macro-organizational factors (economic resources, region, unemployment, employment, occupational rehabilitation, return to work, age structures of inhabitants and home care workers). The incidence of long-term sick leave among female home care workers was twice as high as that of male home care workers, and incidence of disability pension was about four times as high for the women. A great variation in municipal incidence of long-term sick leave, disability pension, and long-term work ability (101-264, 0.6-19.6, and 913-1,279 per 1,000 full-time equivalent workers and year) was also found. The strongest single factor for long-term work ability was a high proportion of part-time or hourly paid employees, which explained 35% of the municipal variation. Macro-organizational factors explained long-term work ability (47-62% explained variance) better than long-term sick leave (33% explained variance). There was a low rehabilitation activity; only 2% received occupational rehabilitation and 5% of those on sick leave longer than 2 weeks returned to work within 30 days. The differences in the municipal proportion of work ability incidence indicate a preventive potential, especially related to employment and return to work after sick leave.

A case-mix classification system for explaining healthcare costs using administrative data in Italy.

PubMed

Corti, Maria Chiara; Avossa, Francesco; Schievano, Elena; Gallina, Pietro; Ferroni, Eliana; Alba, Natalia; Dotto, Matilde; Basso, Cristina; Netti, Silvia Tiozzo; Fedeli, Ugo; Mantoan, Domenico

2018-03-04

The Italian National Health Service (NHS) provides universal coverage to all citizens, granting primary and hospital care with a copayment system for outpatient and drug services. Financing of Local Health Trusts (LHTs) is based on a capitation system adjusted only for age, gender and area of residence. We applied a risk-adjustment system (Johns Hopkins Adjusted Clinical Groups System, ACG® System) in order to explain health care costs using routinely collected administrative data in the Veneto Region (North-eastern Italy). All residents in the Veneto Region were included in the study. The ACG system was applied to classify the regional population based on the following information sources for the year 2015: Hospital Discharges, Emergency Room visits, Chronic disease registry for copayment exemptions, ambulatory visits, medications, the Home care database, and drug prescriptions. Simple linear regressions were used to contrast an age-gender model to models incorporating more comprehensive risk measures aimed at predicting health care costs. A simple age-gender model explained only 8% of the variance of 2015 total costs. Adding diagnoses-related variables provided a 23% increase, while pharmacy based variables provided an additional 17% increase in explained variance. The adjusted R-squared of the comprehensive model was 6 times that of the simple age-gender model. ACG System provides substantial improvement in predicting health care costs when compared to simple age-gender adjustments. Aging itself is not the main determinant of the increase of health care costs, which is better explained by the accumulation of chronic conditions and the resulting multimorbidity. Copyright © 2018. Published by Elsevier B.V.

Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

PubMed

Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

2016-04-07

Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

Hidden Item Variance in Multiple Mini-Interview Scores

ERIC Educational Resources Information Center

Zaidi, Nikki L.; Swoboda, Christopher M.; Kelcey, Benjamin M.; Manuel, R. Stephen

2017-01-01

The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation…

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

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…

Why risk is not variance: an expository note.

PubMed

Cox, Louis Anthony Tony

2008-08-01

Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

Going Mobile: An Empirical Model for Explaining Successful Information Logistics in Ward Rounds.

PubMed

Esdar, Moritz; Liebe, Jan-David; Babitsch, Birgit; Hübner, Ursula

2018-01-01

Medical ward rounds are critical focal points of inpatient care that call for uniquely flexible solutions to provide clinical information at the bedside. While this fact is undoubted, adoption rates of mobile IT solutions remain rather low. Our goal was to investigate if and how mobile IT solutions influence successful information provision at the bedside, i.e. clinical information logistics, as well as to shed light at socio-organizational factors that facilitate adoption rates from a user-centered perspective. Survey data were collected from 373 medical and nursing directors of German, Austrian and Swiss hospitals and analyzed using variance-based Structural Equation Modelling (SEM). The adoption of mobile IT solutions explains large portions of clinical information logistics and is in itself associated with an organizational culture of innovation and end user participation. Results should encourage decision makers to understand mobility as a core constituent of information logistics and thus to promote close end-user participation as well as to work towards building a culture of innovation.

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.

Do climate variables and human density affect Achatina fulica (Bowditch) (Gastropoda: Pulmonata) shell length, total weight and condition factor?

PubMed

Albuquerque, F S; Peso-Aguiar, M C; Assunção-Albuquerque, M J T; Gálvez, L

2009-08-01

The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm). The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.

Variance adaptation in navigational decision making

NASA Astrophysics Data System (ADS)

Gershow, Marc; Gepner, Ruben; Wolk, Jason; Wadekar, Digvijay

Drosophila larvae navigate their environments using a biased random walk strategy. A key component of this strategy is the decision to initiate a turn (change direction) in response to declining conditions. We modeled this decision as the output of a Linear-Nonlinear-Poisson cascade and used reverse correlation with visual and fictive olfactory stimuli to find the parameters of this model. Because the larva responds to changes in stimulus intensity, we used stimuli with uncorrelated normally distributed intensity derivatives, i.e. Brownian processes, and took the stimulus derivative as the input to our LNP cascade. In this way, we were able to present stimuli with 0 mean and controlled variance. We found that the nonlinear rate function depended on the variance in the stimulus input, allowing larvae to respond more strongly to small changes in low-noise compared to high-noise environments. We measured the rate at which the larva adapted its behavior following changes in stimulus variance, and found that larvae adapted more quickly to increases in variance than to decreases, consistent with the behavior of an optimal Bayes estimator. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Theory of Planned Behavior including self-stigma and perceived barriers explain help-seeking behavior for sexual problems in Iranian women suffering from epilepsy.

PubMed

Lin, Chung-Ying; Oveisi, Sonia; Burri, Andrea; Pakpour, Amir H

2017-03-01

To apply the Theory of Planned Behavior (TPB) and the two additional concepts self-stigma and perceived barriers to the help-seeking behavior for sexual problems in women with epilepsy. In this 18-month follow-up study, TPB elements, including attitude, subjective norm, perceived behavioral control, and behavioral intention along with self-stigma and perceived barriers in seeking help for sexual problems were assessed in n=818 women with epilepsy (94.0% aged ≤40years). The basic TPB model (model 1) and the TPB model additionally including self-stigma and perceived barriers (Model 2) were analyzed using structural equation modeling (SEM). Both SEM models showed satisfactory model fits. According to model, attitude, subjective norms, perceived behavioral control, and intention explained 63.1% of the variance in help-seeking behavior. Variance was slightly higher (64.5%) when including self-stigma and perceived barriers (model 2). In addition, the fit indices of the models were better highlighting the importance of self-stigma and perceived barriers in help-seeking behavior for sexual problems. Theory of Planned Behavior is useful in explaining help-seeking behavior for sexual problems in women with epilepsy. Self-stigma and perceived barriers are additional factors that should be considered in future interventions aiming to adopt TPB to improve help-seeking behavior for sexual problems. Copyright © 2017 Elsevier Inc. All rights reserved.

Explaining Vegetable Consumption among Young Adults: An Application of the Theory of Planned Behaviour

PubMed Central

Menozzi, Davide; Sogari, Giovanni; Mora, Cristina

2015-01-01

Although fruit and vegetable consumption is highly recommended for a healthy and balanced daily diet, several European countries do not meet these recommendations. In Italy, only 45% of young people are consuming at least one portion of vegetables per day. Therefore, this paper aims to understand the main determinants of vegetables consumption among young adults to suggest possible intervention strategies. A cross-sectional study was conducted on a samples of Italian students (n = 751), using the theory of planned behaviour (TPB) as a conceptual framework. A structural equation model (SEM) was developed to test the TPB predictors for vegetable consumption, and the role of background factors (socio-demographic and personal characteristics) in improving the TPB model’s explaining power. Overall, 81% and 68%, respectively, of intentions and behaviour variance is explained by the TPB model. Socio-demographic and personal characteristics were found to influence intentions and behaviour indirectly by their effects on the theory’s more proximal determinants. Interventions should be targeted to improve perceived behavioural control (PBC), attitudes and subjective norms that significantly affect intentions. Tailored interventions for male students, enrolled in courses other than food science, and doing less physical activity may have a larger effect on behavioural change. PMID:26378570

The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference

USGS Publications Warehouse

Carlisle, Daren M.; Bryant, Wade L.

2011-01-01

Many physicochemical factors potentially impair stream ecosystems in urbanizing basins, but few studies have evaluated their relative importance simultaneously, especially in different environmental settings. We used data collected in 25 to 30 streams along a gradient of urbanization in each of 6 metropolitan areas (MAs) to evaluate the relative importance of 11 physicochemical factors on the condition of algal, macroinvertebrate, and fish assemblages. For each assemblage, biological condition was quantified using 2 separate metrics, nonmetric multidimensional scaling ordination site scores and the ratio of observed/expected taxa, both derived in previous studies. Separate linear regression models with 1 or 2 factors as predictors were developed for each MA and assemblage metric. Model parsimony was evaluated based on Akaike’s Information Criterion for small sample size (AICc) and Akaike weights, and variable importance was estimated by summing the Akaike weights across models containing each stressor variable. Few of the factors were strongly correlated (Pearson |r| > 0.7) within MAs. Physicochemical factors explained 17 to 81% of variance in biological condition. Most (92 of 118) of the most plausible models contained 2 predictors, and generally more variance could be explained by the additive effects of 2 factors than by any single factor alone. None of the factors evaluated was universally important for all MAs or biological assemblages. The relative importance of factors varied for different measures of biological condition, biological assemblages, and MA. Our results suggest that the suite of physicochemical factors affecting urban stream ecosystems varies across broad geographic areas, along gradients of urban intensity, and among basins within single MAs.

Factor structure of the Spanish version of the Object-Spatial Imagery and Verbal Questionnaire.

PubMed

Campos, Alfredo; Pérez-Fabello, María José

2011-04-01

The reliability and factor structure of the Spanish version of the Object-Spatial Imagery and Verbal Questionnaire (OSIVQ) were assessed in a sample of 213 Spanish university graduates. The questionnaire measures three types of processing preferences (verbal, object imagery, and spatial imagery). Principal components analysis with varimax rotation identified three factors, corresponding to the three scales proposed in the original version, explaining 33.1% of the overall variance. Cronbach's alphas were .72, .77, and .81 for the verbal, object imagery, and spatial imagery scales, respectively.

Does Social Capital Explain Community-Level Differences in Organ Donor Designation?

PubMed Central

Ladin, Keren; Wang, Rui; Fleishman, Aaron; Boger, Matthew; Rodrigue, James R

2015-01-01

Context The growing shortage of organs has reached unprecedented levels. Despite national attempts to increase donation and federal laws mandating the equitable allocation of organs, their availability and waiting times vary significantly nationwide. Organ donor designation is a collective action problem in public health, in which the regional organ supply and average waiting times are determined by the willingness of individuals to be listed as organ donors. Social capital increases the probability of collective action by fostering norms of reciprocity and cooperation while increasing costs to defectors. We examine whether social capital and other community-level factors explain geographic variation in organ donor designation rates in Massachusetts. Methods We obtained a sample of 3,281,532 registered drivers in 2010 from the Massachusetts Department of Transportation Registry of Motor Vehicles (MassDOT RMV). We then geocoded the registry data, matched them to 4,466 census blocks, and linked them to the 2010 US Census, the American Community Survey (ACS), and other sources to obtain community-level sociodemographic, social capital (residential segregation, voter registration and participation, residential mobility, violent-death rate), and religious characteristics. We used spatial modeling, including lagged variables to account for the effect of adjacent block groups, and multivariate regression analysis to examine the relationship of social capital and community-level characteristics with organ donor designation rates. Findings Block groups with higher levels of social capital, racial homogeneity, income, workforce participation, owner-occupied housing, native-born residents, and white residents had higher rates of organ donor designation (p < 0.001). These factors remained significant in the multivariate model, which explained more than half the geographic variance in organ donor designation (R2 = 0.52). Conclusions The findings suggest that community

Integrating Variances into an Analytical Database

NASA Technical Reports Server (NTRS)

Sanchez, Carlos

2010-01-01

For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

Motor selection dynamics in FEF explain the reaction time variance of saccades to single targets

PubMed Central

Hauser, Christopher K; Zhu, Dantong; Stanford, Terrence R

2018-01-01

In studies of voluntary movement, a most elemental quantity is the reaction time (RT) between the onset of a visual stimulus and a saccade toward it. However, this RT demonstrates extremely high variability which, in spite of extensive research, remains unexplained. It is well established that, when a visual target appears, oculomotor activity gradually builds up until a critical level is reached, at which point a saccade is triggered. Here, based on computational work and single-neuron recordings from monkey frontal eye field (FEF), we show that this rise-to-threshold process starts from a dynamic initial state that already contains other incipient, internally driven motor plans, which compete with the target-driven activity to varying degrees. The ensuing conflict resolution process, which manifests in subtle covariations between baseline activity, build-up rate, and threshold, consists of fundamentally deterministic interactions, and explains the observed RT distributions while invoking only a small amount of intrinsic randomness. PMID:29652247

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models.

PubMed

Mulder, Han A; Rönnegård, Lars; Fikse, W Freddy; Veerkamp, Roel F; Strandberg, Erling

2013-07-04

Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike's information criterion using h-likelihood to select the best fitting model. We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike's information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike's information criterion the true genetic

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

PubMed Central

2013-01-01

Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike�

Hydraulic geometry of river cross sections; theory of minimum variance

USGS Publications Warehouse

Williams, Garnett P.

1978-01-01

This study deals with the rates at which mean velocity, mean depth, and water-surface width increase with water discharge at a cross section on an alluvial stream. Such relations often follow power laws, the exponents in which are called hydraulic exponents. The Langbein (1964) minimum-variance theory is examined in regard to its validity and its ability to predict observed hydraulic exponents. The variables used with the theory were velocity, depth, width, bed shear stress, friction factor, slope (energy gradient), and stream power. Slope is often constant, in which case only velocity, depth, width, shear and friction factor need be considered. The theory was tested against a wide range of field data from various geographic areas of the United States. The original theory was intended to produce only the average hydraulic exponents for a group of cross sections in a similar type of geologic or hydraulic environment. The theory does predict these average exponents with a reasonable degree of accuracy. An attempt to forecast the exponents at any selected cross section was moderately successful. Empirical equations are more accurate than the minimum variance, Gauckler-Manning, or Chezy methods. Predictions of the exponent of width are most reliable, the exponent of depth fair, and the exponent of mean velocity poor. (Woodard-USGS)

Explaining Gender Gaps in English Composition and College Algebra in College: The Mediating Role of Psychosocial Factors

ERIC Educational Resources Information Center

Ndum, Edwin; Allen, Jeff; Way, Jason; Casillas, Alex

2018-01-01

We examined the role of six psychosocial factors (PSFs) in explaining gender gaps in English Composition (n = 8,633) and College Algebra (n = 2,261) using data of first-year female (55%) and male students from 42 colleges. Using a multilevel model and controlling for prior achievement, we found that PSFs mediated between 3% and 41% of the gender…

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

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

29 CFR 1905.5 - Effect of variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

An Investigation of Factors Influencing Nurses' Clinical Decision-Making Skills.

PubMed

Wu, Min; Yang, Jinqiu; Liu, Lingying; Ye, Benlan

2016-08-01

This study aims to investigate the influencing factors on nurses' clinical decision-making (CDM) skills. A cross-sectional nonexperimental research design was conducted in the medical, surgical, and emergency departments of two university hospitals, between May and June 2014. We used a quantile regression method to identify the influencing factors across different quantiles of the CDM skills distribution and compared the results with the corresponding ordinary least squares (OLS) estimates. Our findings revealed that nurses were best at the skills of managing oneself. Educational level, experience, and the total structural empowerment had significant positive impacts on nurses' CDM skills, while the nurse-patient relationship, patient care and interaction, formal empowerment, and information empowerment were negatively correlated with nurses' CDM skills. These variables explained no more than 30% of the variance in nurses' CDM skills and mainly explained the lower quantiles of nurses' CDM skills distribution. © The Author(s) 2016.

Biological maturity-associated variance in peak power output and momentum in academy rugby union players.

PubMed

Howard, Sean M A; Cumming, Sean P; Atkinson, Mark; Malina, Robert M

2016-11-01

The study aimed to evaluate the mediating effect of biological maturation on anthropometrical measurements, performance indicators and subsequent selection in a group of academy rugby union players. Fifty-one male players 14-17 years of age were assessed for height, weight and BMI, and percentage of predicted mature status attained at the time of observation was used as an indicator of maturity status. Following this, initial sprint velocity (ISV), Wattbike peak power output (PPO) and initial sprint momentum (ISM) were assessed. A bias towards on-time (n = 44) and early (n = 7) maturers was evident in the total sample and magnified with age cohort. Relative to UK reference values, weight and height were above the 90th and 75th centiles, respectively. Significant (p ≤ .01) correlations were observed between maturity status and BMI (r = .48), weight (r = .63) and height (r = .48). Regression analysis (controlling for age) revealed that maturity status and height explained 68% of ISM variance; however, including BMI in the model attenuated the influence of maturity status below statistical significance (p = .72). Height and BMI explained 51% of PPO variance, while no initial significant predictors were identified for ISV. The sample consisted of players who were on-time and early in maturation with no late maturers represented. This was attributable, in part, to the mediating effect of maturation on body size, which, in turn, predicted performance variables.

White matter tract network disruption explains reduced conscientiousness in multiple sclerosis.

PubMed

Fuchs, Tom A; Dwyer, Michael G; Kuceyeski, Amy; Choudhery, Sanjeevani; Carolus, Keith; Li, Xian; Mallory, Matthew; Weinstock-Guttman, Bianca; Jakimovski, Dejan; Ramasamy, Deepa; Zivadinov, Robert; Benedict, Ralph H B

2018-05-08

Quantifying white matter (WM) tract disruption in people with multiple sclerosis (PwMS) provides a novel means for investigating the relationship between defective network connectivity and clinical markers. PwMS exhibit perturbations in personality, where decreased Conscientiousness is particularly prominent. This trait deficit influences disease trajectory and functional outcomes such as work capacity. We aimed to identify patterns of WM tract disruption related to decreased Conscientiousness in PwMS. Personality assessment and brain MRI were obtained in 133 PwMS and 49 age- and sex-matched healthy controls (HC). Lesion maps were applied to determine the severity of WM tract disruption between pairs of gray matter regions. Next, the Network-Based-Statistics tool was applied to identify structural networks whose disruption negatively correlates with Conscientiousness. Finally, to determine whether these networks explain unique variance above conventional MRI measures and cognition, regression models were applied controlling for age, sex, brain volume, T2-lesion volume, and cognition. Relative to HCs, PwMS exhibited lower Conscientiousness and slowed cognitive processing speed (p = .025, p = .006). Lower Conscientiousness in PwMS was significantly associated with WM tract disruption between frontal, frontal-parietal, and frontal-cingulate pathways in the left (p = .02) and right (p = .01) hemisphere. The mean disruption of these pathways explained unique additive variance in Conscientiousness, after accounting for conventional MRI markers of pathology and cognition (ΔR 2  = .049, p = .029). Damage to WM tracts between frontal, frontal-parietal, and frontal-cingulate cortical regions is significantly correlated with reduced Conscientiousness in PwMS. Tract disruption within these networks explains decreased Conscientiousness observed in PwMS as compared with HCs. © 2018 Wiley Periodicals, Inc.

Does the Theory of Planned Behaviour Explain Condom Use Behaviour Among Men Who have Sex with Men? A Meta-analytic Review of the Literature.

PubMed

Andrew, Benjamin J; Mullan, Barbara A; de Wit, John B F; Monds, Lauren A; Todd, Jemma; Kothe, Emily J

2016-12-01

The aim of this meta-analysis was to explore whether the constructs in the theory of planned behaviour (TPB; i.e., attitude, subjective norm, perceived behavioural control, intention) explain condom use behaviour among men who have sex with men (MSM). Electronic databases were searched for studies that measured TPB variables and MSM condom use. Correlations were meta-analysed using a random effects model and path analyses. Moderation analyses were conducted for the time frame of the behavioural measure used (retrospective versus prospective). Attitude, subjective norm and perceived behavioural control accounted for 24.0 % of the variance in condom use intention and were all significant correlates. Intention and PBC accounted for 12.4 % of the variance in condom use behaviour. However, after taking intention into account, PBC was no longer significantly associated with condom use. The strength of construct relationships did not differ between retrospective and prospective behavioural assessments. The medium to large effect sizes of the relationships between the constructs in the TPB, which are consistent with previous meta-analyses with different behaviours or target groups, suggest that the TPB is also a useful model for explaining condom use behaviour among MSM. However, the research in this area is rather small, and greater clarity over moderating factors can only be achieved when the literature expands.

Finger gnosis predicts a unique but small part of variance in initial arithmetic performance.

PubMed

Wasner, Mirjam; Nuerk, Hans-Christoph; Martignon, Laura; Roesch, Stephanie; Moeller, Korbinian

2016-06-01

Recent studies indicated that finger gnosis (i.e., the ability to perceive and differentiate one's own fingers) is associated reliably with basic numerical competencies. In this study, we aimed at examining whether finger gnosis is also a unique predictor for initial arithmetic competencies at the beginning of first grade-and thus before formal math instruction starts. Therefore, we controlled for influences of domain-specific numerical precursor competencies, domain-general cognitive ability, and natural variables such as gender and age. Results from 321 German first-graders revealed that finger gnosis indeed predicted a unique and relevant but nevertheless only small part of the variance in initial arithmetic performance (∼1%-2%) as compared with influences of general cognitive ability and numerical precursor competencies. Taken together, these results substantiated the notion of a unique association between finger gnosis and arithmetic and further corroborate the theoretical idea of finger-based representations contributing to numerical cognition. However, the only small part of variance explained by finger gnosis seems to limit its relevance for diagnostic purposes. Copyright © 2016. Published by Elsevier Inc.

42 CFR 456.521 - Conditions for granting variance requests.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... is unable to meet the time requirements for which the variance is requested; and (2) A revised UR...

Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

PubMed Central

Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

2012-01-01

Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778

One-shot estimate of MRMC variance: AUC.

PubMed

Gallas, Brandon D

2006-03-01

One popular study design for estimating the area under the receiver operating characteristic curve (AUC) is the one in which a set of readers reads a set of cases: a fully crossed design in which every reader reads every case. The variability of the subsequent reader-averaged AUC has two sources: the multiple readers and the multiple cases (MRMC). In this article, we present a nonparametric estimate for the variance of the reader-averaged AUC that is unbiased and does not use resampling tools. The one-shot estimate is based on the MRMC variance derived by the mechanistic approach of Barrett et al. (2005), as well as the nonparametric variance of a single-reader AUC derived in the literature on U statistics. We investigate the bias and variance properties of the one-shot estimate through a set of Monte Carlo simulations with simulated model observers and images. The different simulation configurations vary numbers of readers and cases, amounts of image noise and internal noise, as well as how the readers are constructed. We compare the one-shot estimate to a method that uses the jackknife resampling technique with an analysis of variance model at its foundation (Dorfman et al. 1992). The name one-shot highlights that resampling is not used. The one-shot and jackknife estimators behave similarly, with the one-shot being marginally more efficient when the number of cases is small. We have derived a one-shot estimate of the MRMC variance of AUC that is based on a probabilistic foundation with limited assumptions, is unbiased, and compares favorably to an established estimate.

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2013 CFR

2013-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2014 CFR

2014-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2012 CFR

2012-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

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-...

Dominance genetic variance for traits under directional selection in Drosophila serrata.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

PubMed Central

Sztepanacz, Jacqueline L.; Blows, Mark W.

2015-01-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700

CMB-S4 and the hemispherical variance anomaly

NASA Astrophysics Data System (ADS)

O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

2017-09-01

Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

Modeling Heterogeneous Variance-Covariance Components in Two-Level Models

ERIC Educational Resources Information Center

Leckie, George; French, Robert; Charlton, Chris; Browne, William

2014-01-01

Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…

Effects of state and trait factors on nightmare frequency.

PubMed

Schredl, Michael

2003-10-01

In a new approach, this study compared the effects of trait and state factors on nightmare frequency in a non-clinical sample. Although neuroticism and boundary thinness were related to nightmare frequency, regression analyses indicated that the trait measures did not add to the variance explained by the state measures. This finding supports the so-called continuity hypothesis of dreaming, i. e., nightmares reflect negative waking-life experiences. Second, the moderate relationship between nightmare frequency and poor sleep quality was partly explained by the day-time measures of neuroticism and stress, but it can be assumed that nightmares are an independent factor contributing to complaints of insomnia. Longitudinal studies measuring nightmare frequency and stress on a daily basis will shed light on the temporal relationship between daytime measures and the occurrence of nightmares. It will be also very interesting to study the relationship between stress and nightmare frequency in a sample who have undergone cognitive-behavioral treatment for nightmares.

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

PubMed

Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D

2013-07-03

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.

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

Bootstrap Estimation and Testing for Variance Equality.

ERIC Educational Resources Information Center

Olejnik, Stephen; Algina, James

The purpose of this study was to develop a single procedure for comparing population variances which could be used for distribution forms. Bootstrap methodology was used to estimate the variability of the sample variance statistic when the population distribution was normal, platykurtic and leptokurtic. The data for the study were generated and…

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and exceptions. (a... the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood plain...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2011 CFR

2011-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2010 CFR

2010-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

PubMed Central

Verdery, Ashton M.; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J.

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network. PMID:26679927

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

PubMed

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs

USGS Publications Warehouse

Gray, Brian R.; Gitzen, Robert A.; Millspaugh, Joshua J.; Cooper, Andrew B.; Licht, Daniel S.

2012-01-01

Variance components may play multiple roles (cf. Cox and Solomon 2003). First, magnitudes and relative magnitudes of the variances of random factors may have important scientific and management value in their own right. For example, variation in levels of invasive vegetation among and within lakes may suggest causal agents that operate at both spatial scales – a finding that may be important for scientific and management reasons. Second, variance components may also be of interest when they affect precision of means and covariate coefficients. For example, variation in the effect of water depth on the probability of aquatic plant presence in a study of multiple lakes may vary by lake. This variation will affect the precision of the average depth-presence association. Third, variance component estimates may be used when designing studies, including monitoring programs. For example, to estimate the numbers of years and of samples per year required to meet long-term monitoring goals, investigators need estimates of within and among-year variances. Other chapters in this volume (Chapters 7, 8, and 10) as well as extensive external literature outline a framework for applying estimates of variance components to the design of monitoring efforts. For example, a series of papers with an ecological monitoring theme examined the relative importance of multiple sources of variation, including variation in means among sites, years, and site-years, for the purposes of temporal trend detection and estimation (Larsen et al. 2004, and references therein).

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.

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.

Explaining use of food parenting practices: the importance of predisposing factors and parental cognitions.

PubMed

Gevers, Dorus Wm; van Assema, Patricia; de Vries, Nanne K; Kremers, Stef Pj

2017-09-01

The high energy intake from energy-dense foods among children in developed countries is undesirable. Improving food parenting practices has the potential to lower snack intakes among children. To inform the development of interventions, we aimed to predict food parenting practice patterns around snacking (i.e. 'high covert control and rewarding', 'low covert control and non-rewarding', 'high involvement and supportive' and 'low involvement and indulgent'). A cross-sectional survey was conducted. To predict the patterns of food parenting practices, multinomial logistic regression analyses were run with 888 parents. Predictors included predisposing factors (i.e. parents' and children's demographics and BMI, parents' personality, general parenting, and parenting practices used by their own parents) and parents' cognitions (i.e. perceived behaviour of other parents, subjective norms, attitudes, self-efficacy and outcome expectations). The Netherlands (October-November 2014). Dutch parents of children aged 4-12 years old. After backward elimination, nineteen factors had a statistically significant contribution to the model (Nagelkerke R 2=0·63). Overall, self-efficacy and outcome expectations were among the strongest explanatory factors. Considering the predisposing factors only, the general parenting factor nurturance most strongly predicted the food parenting clusters. Nurturance particularly distinguished highly involved parents from parents employing a pattern of low involvement. Parental cognitions and nurturance are important factors to explain the use of food parenting practices around snacking. The results suggest that intervention developers should attempt to increase self-efficacy and educate parents about what constitute effective and ineffective parenting practices. Promoting nurturance might be a prerequisite to achieve prolonged change.

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

Does sexual selection explain human sex differences in aggression?

PubMed

Archer, John

2009-08-01

I argue that the magnitude and nature of sex differences in aggression, their development, causation, and variability, can be better explained by sexual selection than by the alternative biosocial version of social role theory. Thus, sex differences in physical aggression increase with the degree of risk, occur early in life, peak in young adulthood, and are likely to be mediated by greater male impulsiveness, and greater female fear of physical danger. Male variability in physical aggression is consistent with an alternative life history perspective, and context-dependent variability with responses to reproductive competition, although some variability follows the internal and external influences of social roles. Other sex differences, in variance in reproductive output, threat displays, size and strength, maturation rates, and mortality and conception rates, all indicate that male aggression is part of a sexually selected adaptive complex. Physical aggression between partners can be explained using different evolutionary principles, arising from the conflicts of interest between males and females entering a reproductive alliance, combined with variability following differences in societal gender roles. In this case, social roles are particularly important since they enable both the relatively equality in physical aggression between partners from Western nations, and the considerable cross-national variability, to be explained.

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

PubMed

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

2007-08-29

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

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).

Save money by understanding variance and tolerancing.

PubMed

Stuart, K

2007-01-01

Manufacturing processes are inherently variable, which results in component and assembly variance. Unless process capability, variance and tolerancing are fully understood, incorrect design tolerances may be applied, which will lead to more expensive tooling, inflated production costs, high reject rates, product recalls and excessive warranty costs. A methodology is described for correctly allocating tolerances and performing appropriate analyses.

Conceptual Complexity and the Bias/Variance Tradeoff

ERIC Educational Resources Information Center

Briscoe, Erica; Feldman, Jacob

2011-01-01

In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an instance of what is known in the statistical learning literature as the "bias/variance tradeoff". The bias/variance tradeoff can be thought of as a sliding scale that modulates how closely any…

Male Role Endorsement Explains Negative Attitudes Toward Lesbians and Gay Men Among Students in Mexico More Than in Germany.

PubMed

Steffens, Melanie C; Jonas, Kai J; Denger, Lisa

2015-01-01

Anti-gay attitudes vary across cultures because the larger social context plays a role in attitude formation. Psychological correlates of these attitudes have been investigated in the United States and Europe. Endorsement of traditional gender roles has emerged from that research as a central correlate, next to religiosity and personal contact with lesbians/gay men. In a cross-sectional study, we tested whether these correlates are relevant in Mexico, characterized as an androcentric culture in which both gender-role traditionalism and religiosity are high, using a college-age student sample (N = 63). Because we relied on self-reports, the motivation to appear nonprejudiced was also assessed. We found typical gender differences in attitudes toward gay men. In bivariate tests, anti-gay attitudes were related to male role endorsement, contact with lesbians/gay men, and religiosity. In a multivariate analysis, variance in attitudes was explained by male role endorsement; personal contact or religiosity did not explain additional variance. In a German comparison sample (N = 112), male role endorsement played a smaller role. Variance in anti-gay attitudes in the German sample was also related to personal contact, religiosity, and the motivation to appear nonprejudiced. We discuss the centrality of (male) gender-role endorsement in cultures with high gender-role traditionalism.

A confirmatory factor analysis of the Beck Depression Inventory-II in end-stage renal disease patients.

PubMed

Chilcot, Joseph; Norton, Sam; Wellsted, David; Almond, Mike; Davenport, Andrew; Farrington, Ken

2011-09-01

We sought to examine several competing factor structures of the Beck Depression Inventory-II (BDI) in a sample of patients with End-Stage Renal Disease (ESRD), in which setting the factor structure is poorly defined, though depression symptoms are common. In addition, demographic and clinical correlates of the identified factors were examined. The BDI was administered to clinical sample of 460 ESRD patients attending 4 UK renal centres. Competing models of the factor structure of the BDI were evaluated using confirmatory factor analysis. The best fitting model consisted of general depression factor that accounted for 81% of the common variance between all items along with orthogonal cognitive and somatic factors (G-S-C model, CFI=.983, TLI=.979, RMSEA=.037), which explained 8% and 9% of the common variance, respectively. Age, diabetes, and ethnicity were significantly related to the cognitive factor, whereas albumin, dialysis adequacy, and ethnicity were related to the somatic factor. No demographic or clinical variable was associated with the general factor. The general-factor model provides the best fitting and conceptually most acceptable interpretation of the BDI. Furthermore, the cognitive and somatic factors appear to be related to specific demographic and clinical factors. Copyright © 2011 Elsevier Inc. All rights reserved.

Utility functions predict variance and skewness risk preferences in monkeys

PubMed Central

Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

2016-01-01

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

Utility functions predict variance and skewness risk preferences in monkeys.

PubMed

Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

2016-07-26

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

Ten-year changes in smoking among young adults: are racial differences explained by socioeconomic factors in the CARDIA study?

PubMed Central

Kiefe, C I; Williams, O D; Lewis, C E; Allison, J J; Sekar, P; Wagenknecht, L E

2001-01-01

OBJECTIVES: This study investigated whether socioeconomic factors explain racial/ethnic differences in regular smoking initiation and cessation. METHODS: Data were derived from the CARDIA study, a cohort of 5115 healthy adults aged 18 to 30 years at baseline (1985-1986) and recruited from the populations of 4 US cities. Respondents were followed over 10 years. RESULTS: Among 3950 respondents reexamined in 1995-1996, 20% of Whites and 33% of African Americans were smokers, as compared with 25% and 32%, respectively, in 1985-1986. On average, African Americans were of lower socioeconomic status. Ten-year regular smoking initiation rates for African American women, White women, African American men, and White men were 7.1%, 3.5%, 13.2%, and 5.1%, respectively, and the corresponding cessation rates were 25%, 35.1%, 19.2%, and 31.3%. After adjustment for socioeconomic factors, most 95% confidence intervals of the odds ratios for regular smoking initiation and cessation in African Americans vs Whites included 1. CONCLUSIONS: Less beneficial 10-year changes in smoking were observed in African Americans, but socioeconomic factors explained most of the racial disparity. PMID:11211629

Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

ERIC Educational Resources Information Center

Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

2016-01-01

The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

Relative variances of the cadence frequency of cycling under two differential saddle heights

PubMed Central

Chang, Wen-Dien; Fan Chiang, Chin-Yun; Lai, Ping-Tung; Lee, Chia-Lun; Fang, Sz-Ming

2016-01-01

[Purpose] Bicycle saddle height is a critical factor for cycling performance and injury prevention. The present study compared the variance in cadence frequency after exercise fatigue between saddle heights with 25° and 35° knee flexion. [Methods] Two saddle heights, which were determined by setting the pedal at the bottom dead point with 35° and 25° knee flexion, were used for testing. The relative variances of the cadence frequency were calculated at the end of a 5-minute warm-up period and 5 minutes after inducing exercise fatigue. Comparison of the absolute values of the cadence frequency under the two saddle heights revealed a difference in pedaling efficiency. [Results] Five minutes after inducing exercise fatigue, the relative variances of the cadence frequency for the saddle height with 35° knee flexion was higher than that for the saddle height with 25° knee flexion. [Conclusion] The current finding demonstrated that a saddle height with 25° knee flexion is more appropriate for cyclists than a saddle height with 35° knee flexion. PMID:27065522

Psychosocial factors and pre-abortion psychological health: The significance of stigma.

PubMed

Steinberg, Julia R; Tschann, Jeanne M; Furgerson, Dorothy; Harper, Cynthia C

2016-02-01

Most research in mental health and abortion has examined factors associated with post-abortion psychological health. However, research that follows women from before to after their abortion consistently finds that depressive, anxiety, and stress symptoms are highest just before an abortion compared to any time afterwards. This finding suggests that studies investigating psychosocial factors related to pre-abortion mental health are warranted. The current study uses data from 353 women seeking abortions at three community reproductive health clinics to examine predictors of pre-abortion psychological health. Drawing from three perspectives in the abortion and mental health literature, common risks, stress and coping, and sociocultural context, we conducted multivariable analyses to examine the contribution of important factors on depressive, anxiety, and stress symptoms just before an abortion, including sociodemographics, abortion characteristics, childhood adversities, recent adversities with an intimate partner, relationship context, future pregnancy desires, and perceived abortion stigma. Childhood and partner adversities, including reproductive coercion, were associated with negative mental health symptoms, as was perceived abortion stigma. Before perceived abortion stigma was entered into the model, 18.6%, 20.7%, and 16.8% of the variance in depressive, anxiety, and stress symptoms respectively, was explained. Perceived abortion stigma explained an additional 13.2%, 9.7%, and 10.7% of the variance in depressive, anxiety, and stress symptoms pre-abortion. This study, one of the first to focus on pre-abortion mental health as an outcome, suggests that addressing stigma among women seeking abortions may significantly lower their psychological distress. Copyright © 2015 Elsevier Ltd. All rights reserved.

Psychosocial factors and pre-abortion psychological health: The significance of stigma

PubMed Central

Steinberg, Julia R.; Tschann, Jeanne M.; Furgerson, Dorothy; Harper, Cynthia C.

2016-01-01

Rationale Most research in mental health and abortion has examined factors associated with post-abortion psychological health. However, research that follows women from before to after their abortion consistently finds that depressive, anxiety, and stress symptoms are highest just before an abortion compared to any time afterwards. Objective This finding suggests that studies investigating psychosocial factors related to pre-abortion mental health are warranted. Methods The current study uses data from 353 women seeking abortions at three community reproductive health clinics to examine predictors of pre-abortion psychological health. Drawing from three perspectives in the abortion and mental health literature, common risks, stress and coping, and sociocultural context, we conducted multivariable analyses to examine the contribution of important factors on depressive, anxiety, and stress symptoms just before an abortion, including sociodemographics, abortion characteristics, childhood adversities, recent adversities with an intimate partner, relationship context, future pregnancy desires, and perceived abortion stigma. Results Childhood and partner adversities, including reproductive coercion, were associated with negative mental health symptoms, as was perceived abortion stigma. Before perceived abortion stigma was entered into the model, 18.6 %, 20.7 %, and 16.8% of the variance in depressive, anxiety, and stress symptoms respectively, was explained. Perceived abortion stigma explained an additional 13.2 %, 9.7 %, and 10.7 % of the variance in depressive, anxiety, and stress symptoms pre-abortion. Conclusion This study, one of the first to focus on pre-abortion mental health as an outcome, suggests that addressing stigma among women seeking abortions may significantly lower their psychological distress. PMID:26735332

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Integrating mean and variance heterogeneities to identify differentially expressed genes.

PubMed

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Risk factors for childhood obesity in elementary school-age Taiwanese children.

PubMed

Chen, Jyu-Lin; Kennedy, Christine; Yeh, Chao-Hsing; Kools, Susan

2005-01-01

A cross-sectional study design was used to examine factors that contribute to high relative weight in children in Taiwan. A total sample of 331 Chinese children (ages 7 and 8) and their parents participated in the study. Parents completed questionnaires regarding demographic information, family functioning, parenting styles, physical activity, and dietary intake. Children completed physical fitness tests and questionnaires regarding physical activity, dietary intake, coping strategies, and self-esteem. The weight-for-length index was used to measure children's relative weight. The findings revealed that four variables contributed to higher weight-for-length index in boys compared with girls and explained 37.7% of the variance: high maternal body mass index, poor aerobic capacity, healthy family role functioning, and poor family affective responsiveness. Two variables were found to contribute to higher weight-for-length index in girls and explained 12.8% of the variance: high household income and high maternal body mass index. Taken together, the results indicate the importance of assessment of children's weight status, maternal weight status, and family functioning as part of routine child health care and the need for developmentally appropriate and gender-specific approaches to prevent childhood obesity.

Minimum variance geographic sampling

NASA Technical Reports Server (NTRS)

Terrell, G. R. (Principal Investigator)

1980-01-01

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

Comparing estimates of genetic variance across different relationship models.

PubMed

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Rumination and behavioural factors in Parkinson's disease depression.

PubMed

Julien, Camille L; Rimes, Katharine A; Brown, Richard G

2016-03-01

Parkinson's disease is associated with high rates of depression. There is growing interest in non-pharmacological management including psychological approaches such as Cognitive Behaviour Therapy. To date, little research has investigated whether processes that underpin cognitive models of depression, on which such treatment is based, apply in patients with Parkinson's disease. The study aimed to investigate the contribution of core psychological factors to the presence and degree of depressive symptoms. 104 participants completed questionnaires measuring mood, motor disability and core psychological variables, including maladaptive assumptions, rumination, cognitive-behavioural avoidance, illness representations and cognitive-behavioural responses to symptoms. Regression analyses revealed that a small number of psychological factors accounted for the majority of depression variance, over and above that explained by overall disability. Participants reporting high levels of rumination, avoidance and symptom focusing experienced more severe depressive symptoms. In contrast, pervasive negative dysfunctional beliefs did not independently contribute to depression variance. Specific cognitive (rumination and symptom focusing) and behavioural (avoidance) processes may be key psychological markers of depression in Parkinson's disease and therefore offer important targets for tailored psychological interventions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant.

PubMed

Azadeh, Ali; Salehi, Vahid; Mirzayi, Mahsa

2016-12-01

Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors-self-organization, teamwork, redundancy, and fault-tolerance-in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different α-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four above-mentioned factors. The results showed that as α approached 0 and the system became fuzzier (α = 0.3 and α = 0.1), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as α approached 1 and the fuzzy system went toward a certain mode (α = 0.9 and α = 1), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.

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.

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")…

RR-Interval variance of electrocardiogram for atrial fibrillation detection

NASA Astrophysics Data System (ADS)

Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

2016-11-01

Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

Impact of Operative and Postoperative Factors on Neurodevelopmental Outcomes After Cardiac Operations.

PubMed

2016-09-01

Neurodevelopmental disability is common after operations for congenital heart defects. We previously showed that patient and preoperative factors, center, and calendar year of birth explained less than 30% of the variance for the Psychomotor Development Index (PDI) and the Mental Development Index (MDI) of the Bayley Scales of Infant Development-Second Edition. Here we investigate how much additional variance in PDI and MDI is contributed by operative variables and postoperative events. We analyzed neurodevelopmental outcomes after operations with cardiopulmonary bypass at age 9 months or younger between 1996 and 2009. We used linear regression to investigate the effect of operative factors (age, weight, and cardiopulmonary bypass variables) and postoperative events on neurodevelopmental outcomes, adjusting for center, type of congenital heart defect, year of birth, and preoperative factors. We analyzed 1,770 children from 22 institutions with neurodevelopmental testing at age 13.3 months (range, 6 to 30 months). Among operative factors, longer total support time was associated with lower PDI and MDI (p < 0.05). When postoperative events were added, use of either extracorporeal membrane oxygenation or ventricular assist device support, and longer postoperative length of stay were associated with lower PDI and MDI (p < 0.05). Longer total support time was not a significant predictor in these models. After adjusting for patient, preoperative, intraoperative, and postoperative factors, measured intraoperative and postoperative factors accounted for 5% of the variances in PDI and MDI. Operative factors may be less important than innate patient and preoperative factors and postoperative events in predicting early neurodevelopmental outcomes after cardiac operations in infants. Neurodevelopmental outcomes improved over calendar time when adjusted for patient and medical variables. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights

Sexual possibility situations and sexual behaviors among young adolescents: the moderating role of protective factors.

PubMed

DiLorio, Colleen; Dudley, William N; Soet, Johanna E; McCarty, Frances

2004-12-01

To examine sexual possibility situations (SPS) and protective practices associated with involvement in intimate sexual behaviors and the initiation of sexual intercourse among young adolescents and to determine if protective factors moderate the relationship between SPS and sexual behaviors. Data for these analyses were obtained from the baseline assessment for adolescents conducted as part of an HIV prevention study called "Keepin' it R.E.A.L.!" The study was conducted with a community-based organization (CBO) in an urban area serving a predominantly African-American population. In addition to items assessing SPS, intimate sexual behaviors, and initiation of sexual intercourse, adolescents provided information on the following protective factors: educational goals, self-concept, future time perspective, orientation to health, self-efficacy, outcome expectations, parenting, communication, values, and prosocial activities. Background personal information, including age and gender, was also collected. The analyses were conducted on data from 491 predominantly African-American adolescents, 61% of whom were boys. Variables were combined to form SPS and protective indices that were used in the first set of regression analyses. In a second set of analyses, the indices were unbundled and individual variables were entered into regression analyses. Both SPS and protective indices explained significant portions of variance in intimate sexual behaviors, and the SPS index explained a significant portion of variance in the initiation of sexual intercourse. The regression analysis using the unbundled SPS and protective factors revealed the following statistically significant predictors for intimate sexual behaviors: age, gender, time alone with groups of peers, time alone with a member of the opposite sex, behavior self-concept, popularity self-concept, self-efficacy for abstinence, outcome expectations for abstinence, parental control, personal values, and parental values. A

[The influencing factors on alienation in high school students].

PubMed

Lee, Eun-Sook

2004-02-01

This study was performed to identify the influencing factors on alienation among high school students. Data was collected by questionnaires from 550 students of academic and vocational high schools in G city. The data was analyzed using descriptive statistics, pearson correlation coefficients, and stepwise multiple regression. The scores of alienation among students in financially lower middle class and lower class were higher than those of the upper middle class students, resulting in significant differences(F=6.87, p=.00). A sense of alienation showed a significantly negative correlation with the scores of responding parenting style(r=-.32), family cohesion(r=-.33), school attachment(r=-.51), academic performance(r=-.34), peer relationships(r=-.38), self-control (r=-.43), and social skills(r=-.33). The most powerful predictor of alienation among high school students was school attachment and the variance explained was 26%. A combination of school attachment, self control, peer relationships, family cohesion, demanding parenting style, and academic performance account for 40% of the variance in alienation among high school students. This study suggests that school attachment, self control, peer relationships, family cohesion, demanding parenting style, and academic performance are significant influencing factors on alienation in high school students. Therefore, nursing strategy is needed to manage these revealed factors.

Temporal patterns of phyto- and bacterioplankton and their relationships with environmental factors in Lake Taihu, China.

PubMed

Su, Xiaomei; Steinman, Alan D; Xue, Qingju; Zhao, Yanyan; Tang, Xiangming; Xie, Liqiang

2017-10-01

Phytoplankton and bacterioplankton are integral components of aquatic food webs and play essential roles in the structure and function of freshwater ecosystems. However, little is known about how phyto- and bacterioplankton may respond synchronously to changing environmental conditions. Thus, we analyzed simultaneously the composition and structure of phyto- and bacterioplankton on a monthly basis over 12 months in cyanobacteria-dominated areas of Lake Taihu and compared their responses to changes in environmental factors. Metric multi-dimensional scaling (mMDS) revealed that the temporal variations of phyto- and bacterioplankton were significant. Time lag analysis (TLA) indicated that the temporal pattern of phytoplankton tended to exhibit convergent dynamics while bacterioplankton showed highly stable or stochastic variation. A significant directional change was found for bacterioplankton at the genus level and the slopes (rate of change) and regression R 2 (low stochasticity or stability) were greater if Cyanobacteria were included, suggesting a higher level of instability in the bacterial community at lower taxonomy level. Consequently, phytoplankton responded more rapidly to the change in environmental conditions than bacterioplankton when analyzed at the phylum level, while bacterioplankton were more sensitive at the finer taxonomic resolution in Lake Taihu. Redundancy analysis (RDA) results showed that environmental variables collectively explained 51.0% variance of phytoplankton and 46.7% variance of bacterioplankton, suggesting that environmental conditions have a significant influence on the temporal variations of phyto- and bacterioplankton. Furthermore, variance partitioning indicated that the bacterial community structure was largely explained by water temperature and nitrogen, suggesting that these factors were the primary drivers shaping bacterioplankton. Copyright © 2017. Published by Elsevier Ltd.

Effect of soy on metabolic syndrome and cardiovascular risk factors: a randomized controlled trial.

PubMed

Ruscica, Massimiliano; Pavanello, Chiara; Gandini, Sara; Gomaraschi, Monica; Vitali, Cecilia; Macchi, Chiara; Morlotti, Beatrice; Aiello, Gilda; Bosisio, Raffaella; Calabresi, Laura; Arnoldi, Anna; Sirtori, Cesare R; Magni, Paolo

2018-03-01

Cardiovascular diseases are currently the commonest cause of death worldwide. Different strategies for their primary prevention have been planned, taking into account the main known risk factors, which include an atherogenic lipid profile and visceral fat excess. The study was designed as a randomized, parallel, single-center study with a nutritional intervention duration of 12 weeks. Whole soy foods corresponding to 30 g/day soy protein were given in substitution of animal foods containing the same protein amount. Soy nutritional intervention resulted in a reduction in the number of MetS features in 13/26 subjects. Moreover, in the soy group we observed a significant improvement of median percentage changes for body weight (-1.5 %) and BMI (-1.5 %), as well as for atherogenic lipid markers, namely TC (-4.85 %), LDL-C (-5.25 %), non-HDL-C (-7.14 %) and apoB (-14.8 %). Since the majority of the studied variables were strongly correlated, three factors were identified which explained the majority (52 %) of the total variance in the whole data set. Among them, factor 1, which loaded lipid and adipose variables, explained the 22 % of total variance, showing a statistically significant difference between treatment arms (p = 0.002). The inclusion of whole soy foods (corresponding to 30 g/day protein) in a lipid-lowering diet significantly improved a relevant set of biomarkers associated with cardiovascular risk.

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

East-West gradient in cardio-vascular mortality in Austria: how much can we explain by following the pattern of risk factors?

PubMed Central

2011-01-01

Background Various studies show major regional differences in the prevalence of cardio-vascular disease morbidity and mortality, both in Europe and within European countries. In Austria, these differences are documented by an East-West gradient with declining morbidity and mortality rates when moving from the East to the West of the country. It was the aim of this study to analyse if, and to what extent, socio-demographic and socio-economic determinants, social resources and health behaviour can contribute to the clarification of this East-West gradient by conducting secondary analyses of an existing Austrian health dataset. Results The data were analysed using bivariate analyses, as well as univariate and multivariate logistic regression models. These analyses revealed significant East-West gradients for various risk factors, as well as socio-demographic and socio-economic health determinants. There was a gradual decrease of hypertension, diabetes mellitus, obesity, and psycho-social discomfort in both sexes, with the highest prevalences in those Austrian regions with the highest cardio-vascular mortality and a stepwise decrease to the regions with the lowest cardio-vascular mortality. Controlling for educational level significantly raised the odds for diabetes, hypertension and obesity. In the results of the multivariate analyses, factors that significantly and independently predicted diabetes mellitus were geographic location, psycho-social discomfort, lack of physical exercise, and age in both sexes. For women these factors additionally included a low educational level, lack of social support, and being born abroad. Conclusions Our study shows a clear gradual decline of cardio-vascular mortality and some of its risk factors from East to West in Austria. Concerning these risk factors, the geographic region and psycho-social discomfort showed the greatest association with diabetes mellitus, hypertension, and obesity. Hence, they contribute to the explanation of

High Spending on Maternity Care in India: What Are the Factors Explaining It?

PubMed Central

Moradhvaj; Rammohan, Anu; Shruti; Pradhan, Jalandhar

2016-01-01

Background and Objectives High maternity-related health care spending is often cited as an important barrier in utilizing quality health care during pregnancy and childbirth. This study has two objectives: (i) to measure the levels of expenditure on total maternity care in disaggregated components such as ANCs, PNCs, and Natal care expenditure; (ii) to quantify the extent of catastrophic maternity expenditure (CME) incurred by households and identify the factors responsible for it. Methods and Findings Data from the 71st round of the National Sample Survey (2014) was used to estimate maternity expenditure and its predictors. CME was measured as a share of consumption expenditure by different cut-offs. The two-part model was used to identify the factors associated with maternity spending and CME. The findings show that household spending on maternity care (US$ 149 in constant price) is much higher than previous estimates (US$ 50 in constant price). A significant proportion of households in India (51%) are incurring CME. Along with economic and educational status, type of health care and place of residence emerged as significant factors in explaining CME. Conclusion Findings from this study assume importance in the context of an emerging demand for higher maternity entitlements and government spending on public health care in India. To reduce CME, India needs to improve the availability and accessibility of better-quality public health services and increase maternity entitlements in line with maternity expenditure identified in this study. PMID:27341520

High Spending on Maternity Care in India: What Are the Factors Explaining It?

PubMed

Goli, Srinivas; Moradhvaj; Rammohan, Anu; Shruti; Pradhan, Jalandhar

2016-01-01

High maternity-related health care spending is often cited as an important barrier in utilizing quality health care during pregnancy and childbirth. This study has two objectives: (i) to measure the levels of expenditure on total maternity care in disaggregated components such as ANCs, PNCs, and Natal care expenditure; (ii) to quantify the extent of catastrophic maternity expenditure (CME) incurred by households and identify the factors responsible for it. Data from the 71st round of the National Sample Survey (2014) was used to estimate maternity expenditure and its predictors. CME was measured as a share of consumption expenditure by different cut-offs. The two-part model was used to identify the factors associated with maternity spending and CME. The findings show that household spending on maternity care (US$ 149 in constant price) is much higher than previous estimates (US$ 50 in constant price). A significant proportion of households in India (51%) are incurring CME. Along with economic and educational status, type of health care and place of residence emerged as significant factors in explaining CME. Findings from this study assume importance in the context of an emerging demand for higher maternity entitlements and government spending on public health care in India. To reduce CME, India needs to improve the availability and accessibility of better-quality public health services and increase maternity entitlements in line with maternity expenditure identified in this study.

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.

42 CFR 456.521 - Conditions for granting variance requests.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

42 CFR 456.525 - Request for renewal of variance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

42 CFR 456.525 - Request for renewal of variance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

Relating the Hadamard Variance to MCS Kalman Filter Clock Estimation

NASA Technical Reports Server (NTRS)

Hutsell, Steven T.

1996-01-01

The Global Positioning System (GPS) Master Control Station (MCS) currently makes significant use of the Allan Variance. This two-sample variance equation has proven excellent as a handy, understandable tool, both for time domain analysis of GPS cesium frequency standards, and for fine tuning the MCS's state estimation of these atomic clocks. The Allan Variance does not explicitly converge for the nose types of alpha less than or equal to minus 3 and can be greatly affected by frequency drift. Because GPS rubidium frequency standards exhibit non-trivial aging and aging noise characteristics, the basic Allan Variance analysis must be augmented in order to (a) compensate for a dynamic frequency drift, and (b) characterize two additional noise types, specifically alpha = minus 3, and alpha = minus 4. As the GPS program progresses, we will utilize a larger percentage of rubidium frequency standards than ever before. Hence, GPS rubidium clock characterization will require more attention than ever before. The three sample variance, commonly referred to as a renormalized Hadamard Variance, is unaffected by linear frequency drift, converges for alpha is greater than minus 5, and thus has utility for modeling noise in GPS rubidium frequency standards. This paper demonstrates the potential of Hadamard Variance analysis in GPS operations, and presents an equation that relates the Hadamard Variance to the MCS's Kalman filter process noises.

Naive Analysis of Variance

ERIC Educational Resources Information Center

Braun, W. John

2012-01-01

The Analysis of Variance is often taught in introductory statistics courses, but it is not clear that students really understand the method. This is because the derivation of the test statistic and p-value requires a relatively sophisticated mathematical background which may not be well-remembered or understood. Thus, the essential concept behind…

Evaluation of Mean and Variance Integrals without Integration

ERIC Educational Resources Information Center

Joarder, A. H.; Omar, M. H.

2007-01-01

The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

Polymorphism in the ADRB2 gene explains a small portion of intersubject variability in pain relative to cervical dilation in the first stage of labor.

PubMed

Terkawi, Abdullah S; Jackson, William M; Hansoti, Shehnaz; Tabassum, Rabeena; Flood, Pamela

2014-07-01

Variability in labor pain has been associated with demographic, clinical, and psychological factors. Polymorphisms of the β2-adrenergic receptor gene (ADRB2) influence sensitivity to experimental pain in humans and are a risk factor for chronic pain. The authors hypothesized that polymorphisms in ADRB2 may influence labor pain. After Institutional Review Board approval and written informed consent, the authors prospectively obtained hourly pain reports from 233 nulliparous parturients during the first stage of labor, of which 199 were included in the current analysis. DNA from blood samples was genotyped at polymorphisms in the genes for the β2-adrenergic receptor, the μ opioid receptor subtype 1, catechol-O-methyltransferase, fatty acid amide hydrolase, and the oxytocin receptor. Labor pain as a function of cervical dilation was modeled with previously described methods. Patient covariates, ADRB2 genotype, and obstetrical and anesthesia treatment were evaluated as covariates in the model. Labor pain more rapidly became severe in parturients heterozygous or homozygous for the G allele at rs1042714 in the ADRB2 gene. Labor pain increased more rapidly after artificial rupture of membranes, augmentation with oxytocin, and in younger women. Inclusion of covariates explained approximately 10% of the variability between subjects. ADRB2 genotype explained less than 1% of the intersubject variability. ADRB2 genotype correlates with labor pain but explained less than 1% of the intersubject variance in the model.

Variance in binary stellar population synthesis

NASA Astrophysics Data System (ADS)

Breivik, Katelyn; Larson, Shane L.

2016-03-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

The role of attitudes about vaccine safety, efficacy, and value in explaining parents' reported vaccination behavior.

PubMed

Lavail, Katherine Hart; Kennedy, Allison Michelle

2013-10-01

To explain vaccine confidence as it related to parents' decisions to vaccinate their children with recommended vaccines, and to develop a confidence measure to efficiently and effectively predict parents' self-reported vaccine behaviors. A sample of parents with at least one child younger than 6 years (n = 376) was analyzed using data from the HealthStyles 2010 survey. Questions were grouped into block variables to create three confidence constructs: value, safety, and efficacy. Regression equations controlling for demographic characteristics were used to identify the confidence construct(s) that best predicted parents' self-reported vaccination decisions (accept all, some, or none of the recommended childhood vaccines). Among the three constructs evaluated, confidence in the value of vaccines, that is the belief that vaccines are important and vaccinating one's children is the right thing to do, was the best predictor of parents' vaccine decisions, F(2, 351) = 119.199, p < .001. When combined into a block variable for analysis, two survey items measuring confidence in the value of vaccines accounted for 40% of the variance in parents' self-reported vaccine decisions. Confidence in the safety or efficacy of vaccines failed to account for additional significant variance in parent-reported vaccination behavior. Confidence in the value of vaccines is a helpful predictor of parent-reported vaccination behavior. Attitudinal constructs of confidence in the safety and efficacy of vaccines failed to account for additional significant variance in parents' vaccination behaviors. Future research should assess the role of vaccine knowledge and tangible barriers, such as access and cost, to further explain parents' vaccination behaviors.

10 CFR 851.32 - Action on variance requests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... cited by the Chief Health, Safety and Security Officer; or (ii) Forward to the Under Secretary the... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.32 Action on variance requests. (a) Procedures for an approval recommendation. (1) If the Chief Health, Safety and Security Officer recommends...

A Mean variance analysis of arbitrage portfolios

NASA Astrophysics Data System (ADS)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Jackknife for Variance Analysis of Multifactor Experiments.

DTIC Science & Technology

1982-05-01

variance-covariance matrix is generated y a subroutine named CORAN (UNIVAC, 1969). The jackknife variances are then punched on computer cards in the same...LEVEL OF: InMte CALL cORAN (oaILa.NSUR.NOAY.D,*OXflRRORR.PCOF.2K.1’)I WRITE IP97111 )1RRN.4 .1:NDAY) 0 a 3fill1UR I .’t UN 001f’..1uŔ:1 .w100710n

Mesoscale Gravity Wave Variances from AMSU-A Radiances

NASA Technical Reports Server (NTRS)

Wu, Dong L.

2004-01-01

A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.

Gender Variance and Educational Psychology: Implications for Practice

ERIC Educational Resources Information Center

Yavuz, Carrie

2016-01-01

The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

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.

Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions

NASA Astrophysics Data System (ADS)

Luhar, Ashok K.

2010-05-01

Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.

Heterogeneity of long-history migration explains cultural differences in reports of emotional expressivity and the functions of smiles

PubMed Central

Rychlowska, Magdalena; Miyamoto, Yuri; Matsumoto, David; Hess, Ursula; Gilboa-Schechtman, Eva; Kamble, Shanmukh; Muluk, Hamdi; Masuda, Takahiko; Niedenthal, Paula Marie

2015-01-01

A small number of facial expressions may be universal in that they are produced by the same basic affective states and recognized as such throughout the world. However, other aspects of emotionally expressive behavior vary widely across culture. Just why do they vary? We propose that some cultural differences in expressive behavior are determined by historical heterogeneity, or the extent to which a country’s present-day population descended from migration from numerous vs. few source countries over a period of 500 y. Our reanalysis of data on cultural rules for displaying emotion from 32 countries [n = 5,340; Matsumoto D, Yoo S, Fontaine J (2008) J Cross Cult Psychol 39(1):55–74] reveals that historical heterogeneity explains substantial, unique variance in the degree to which individuals believe that emotions should be openly expressed. We also report an original study of the underlying states that people believe are signified by a smile. Cluster analysis applied to data from nine countries (n = 726), including Canada, France, Germany, India, Indonesia, Israel, Japan, New Zealand, and the United States, reveals that countries group into “cultures of smiling” determined by historical heterogeneity. Factor analysis shows that smiles sort into three social-functional subtypes: pleasure, affiliative, and dominance. The relative importance of these smile subtypes varies as a function of historical heterogeneity. These findings thus highlight the power of social-historical factors to explain cross-cultural variation in emotional expression and smile behavior. PMID:25902500

Heterogeneity of long-history migration explains cultural differences in reports of emotional expressivity and the functions of smiles.

PubMed

Rychlowska, Magdalena; Miyamoto, Yuri; Matsumoto, David; Hess, Ursula; Gilboa-Schechtman, Eva; Kamble, Shanmukh; Muluk, Hamdi; Masuda, Takahiko; Niedenthal, Paula Marie

2015-05-12

A small number of facial expressions may be universal in that they are produced by the same basic affective states and recognized as such throughout the world. However, other aspects of emotionally expressive behavior vary widely across culture. Just why do they vary? We propose that some cultural differences in expressive behavior are determined by historical heterogeneity, or the extent to which a country's present-day population descended from migration from numerous vs. few source countries over a period of 500 y. Our reanalysis of data on cultural rules for displaying emotion from 32 countries [n = 5,340; Matsumoto D, Yoo S, Fontaine J (2008) J Cross Cult Psychol 39(1):55-74] reveals that historical heterogeneity explains substantial, unique variance in the degree to which individuals believe that emotions should be openly expressed. We also report an original study of the underlying states that people believe are signified by a smile. Cluster analysis applied to data from nine countries (n = 726), including Canada, France, Germany, India, Indonesia, Israel, Japan, New Zealand, and the United States, reveals that countries group into "cultures of smiling" determined by historical heterogeneity. Factor analysis shows that smiles sort into three social-functional subtypes: pleasure, affiliative, and dominance. The relative importance of these smile subtypes varies as a function of historical heterogeneity. These findings thus highlight the power of social-historical factors to explain cross-cultural variation in emotional expression and smile behavior.

An Analysis of Variance Framework for Matrix Sampling.

ERIC Educational Resources Information Center

Sirotnik, Kenneth

Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

Model-based variance-stabilizing transformation for Illumina microarray data.

PubMed

Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

2008-02-01

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

PubMed

Koyama, Shinsuke

2015-07-01

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

Using Carl Rogers' person-centered model to explain interpersonal relationships at a school of nursing.

PubMed

Bryan, Venise D; Lindo, Jascinth; Anderson-Johnson, Pauline; Weaver, Steve

2015-01-01

Faculty members are viewed as nurturers within the academic setting and may be able to influence students' behaviors through the formation of positive interpersonal relationships. Faculty members' attributes that best facilitated positive interpersonal relationships according to Carl Rogers' Person-Centered Model was studied. Students (n = 192) enrolled in a 3-year undergraduate nursing program in urban Jamaica were randomly selected to participate in this descriptive cross-sectional study. A 38-item questionnaire on interpersonal relationships with nursing faculty and students' perceptions of their teachers was utilized to collect data. Factor analysis was used to create factors of realness, prizing, and empathetic understanding. Multiple linear regression analysis on the interaction of the 3 factors and interpersonal relationship scores was performed while controlling for nursing students' study year and age. One hundred sixty-five students (mean age: 23.18 ± 4.51years; 99% female) responded. The regression model explained over 46% of the variance. Realness (β = 0.50, P < .001) was the only significant predictor of the interpersonal relationship scores assigned by the nursing students. Of the total number of respondents, 99 students (60%) reported satisfaction with the interpersonal relationships shared with faculty. Nursing students' perception of faculty members' realness appeared to be the most significant attribute in fostering positive interpersonal relationships. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying the Strength of General Factors in Psychopathology: A Comparison of CFA with Maximum Likelihood Estimation, BSEM, and ESEM/EFA Bifactor Approaches.

PubMed

Murray, Aja Louise; Booth, Tom; Eisner, Manuel; Obsuth, Ingrid; Ribeaud, Denis

2018-05-22

Whether or not importance should be placed on an all-encompassing general factor of psychopathology (or p factor) in classifying, researching, diagnosing, and treating psychiatric disorders depends (among other issues) on the extent to which comorbidity is symptom-general rather than staying largely within the confines of narrower transdiagnostic factors such as internalizing and externalizing. In this study, we compared three methods of estimating p factor strength. We compared omega hierarchical and explained common variance calculated from confirmatory factor analysis (CFA) bifactor models with maximum likelihood (ML) estimation, from exploratory structural equation modeling/exploratory factor analysis models with a bifactor rotation, and from Bayesian structural equation modeling (BSEM) bifactor models. Our simulation results suggested that BSEM with small variance priors on secondary loadings might be the preferred option. However, CFA with ML also performed well provided secondary loadings were modeled. We provide two empirical examples of applying the three methodologies using a normative sample of youth (z-proso, n = 1,286) and a university counseling sample (n = 359).

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.

Explaining Student and Home Variance of Chinese Reading Achievement of the PIRLS 2011 Hong Kong

ERIC Educational Resources Information Center

Cheung, Wai Ming; Lam, Joseph W. I.; Au, Doreen W. H.; So, Wendy W. Y.; Huang, Yanli; Tsang, Hector W. H.

2017-01-01

Hong Kong attained the top place in the Progress in International Reading Literacy Study (PIRLS) 2011, an international study of reading achievement, which arouses keen interest in understanding the reasons behind this remarkable achievement. Although factors associated with reading achievement in English have been widely studied, similar studies…

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

Living in Latvia after stroke: the association between functional, social and personal factors and the level of self-perceived disability-a cross-sectional study.

PubMed

Bērziņa, Guna; Smilškalne, Baiba; Vētra, Anita; Sunnerhagen, Katharina S

2016-06-24

To investigate how functional, social and personal factors are associated with self-perceived level of disability in the chronic phase of stroke in a Latvian stroke population. The consequences of stroke can vary greatly and often leads to long-term disability that, according to the WHO definitions, depends on the interaction between the person and his/her context. Cross-sectional study with retrospective data gathering. Community-dwelling persons who received specialised in-patient rehabilitation after stroke in Latvia. Of 600 persons after stroke who were identified through hospital register and selected for the study, 255 were included in the analysis. The medical information and discharge data of the Functional Independence Measure (FIM) was extracted from medical records. Participants filled out a questionnaire on sociodemographic information and the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0), either in Latvian or Russian, depending on their wish when contacted for their oral agreement to participate. Stepwise multiple regression analysis was conducted to find a model that best explains the variance in WHODAS 2.0 scores. The models explained 23-43.5% of variance in outcomes. The best explained WHODAS 2.0 domains were 'mobility' and 'self-care'. The significant factors were level of independence in 'self-care', 'locomotion' and 'communication' according to FIM, as well as working status, time since rehabilitation, age, gender, living alone or in family and preferred language. Functional, social and personal factors are of similar importance when explaining self-perceived disability in the chronic phase of stroke. Some, but not all, of the factors are modifiable by the healthcare system. Therefore, a complex approach and involvement of medical, social and political systems is needed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Small Drinking Water System Variances

EPA Pesticide Factsheets

Small system variances allow a small system to install and maintain technology that can remove a contaminant to the maximum extent that is affordable and protective of public health in lieu of technology that can achieve compliance with the regulation.

The Influence of Contextual and Psychosocial Factors on Handwashing.

PubMed

Seimetz, Elisabeth; Boyayo, Anne-Marie; Mosler, Hans-Joachim

2016-06-01

Even though washing hands with soap is among the most effective measures to reduce the risk of infection, handwashing rates in infrastructure-restricted settings remain seriously low. Little is known about how context alone and in interaction with psychosocial factors influence hand hygiene behavior. The aim of this article was to explore how both contextual and psychosocial factors affect handwashing practices. A cross-sectional survey was conducted with 660 caregivers of primary school children in rural Burundi. Hierarchical regression analyses revealed that household wealth, the amount of water per person, and having a designated place for washing hands were contextual factors significantly predicting handwashing frequency, whereas the contextual factors, time spent collecting water and amount of money spent on soap, were not significant predictors. The contextual factors explained about 13% of the variance of reported handwashing frequency. The addition of the psychosocial factors to the regression model resulted in a significant 41% increase of explained variation in handwashing frequency. In this final model, the amount of water was the only contextual factor that remained a significant predictor. The most important predictors were a belief of self-efficacy, planning how, when, and where to wash hands, and always remembering to do so. The findings suggest that contextual constraints might be perceived rather than actual barriers and highlight the role of psychosocial factors in understanding hygiene behaviors. © The American Society of Tropical Medicine and Hygiene.

Genetic Factors of Individual Differences in Decision Making in Economic Behavior: A Japanese Twin Study using the Allais Problem.

PubMed

Shikishima, Chizuru; Hiraishi, Kai; Yamagata, Shinji; Ando, Juko; Okada, Mitsuhiro

2015-01-01

Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary) utility even when objective information of probabilities and reward are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more "rational." We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20-47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of "rational" decision making from the perspective of genetic correlations with cognitive abilities.

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.

The evolution and consequences of sex-specific reproductive variance.

PubMed

Mullon, Charles; Reuter, Max; Lehmann, Laurent

2014-01-01

Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

The Evolution and Consequences of Sex-Specific Reproductive Variance

PubMed Central

Mullon, Charles; Reuter, Max; Lehmann, Laurent

2014-01-01

Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction. PMID:24172130

Depression in Intimate Partner Violence Victims in Slovenia: A Crippling Pattern of Factors Identified in Family Practice Attendees.

PubMed

Guček, Nena Kopčavar; Selič, Polona

2018-01-26

This multi-centre cross-sectional study explored associations between prevalence of depression and exposure to intimate partner violence (IPV) at any time in patients' adult life in 471 participants of a previous IPV study. In 2016, 174 interviews were performed, using the Short Form Domestic Violence Exposure Questionnaire, the Zung Scale and questions about behavioural patterns of exposure to IPV. Family doctors reviewed patients' medical charts for period from 2012 to 2016, using the Domestic Violence Exposure Medical Chart Check List, for conditions which persisted for at least three years. Depression was found to be associated with any exposure to IPV in adult life and was more likely to affect women. In multivariable logistic regression modelling, factors associated with self-rated depression were identified (p < 0.05). Exposure to emotional and physical violence was identified as a risk factor in the first model, explaining 23% of the variance. The second model explained 66% of the variance; past divorce, dysfunctional family relationships and a history of incapacity to work increased the likelihood of depression in patients. Family doctors should consider IPV exposure when detecting depression, since lifetime IPV exposure was found to be 40.4% and 36.9% of depressed revealed it.

The Genealogical Consequences of Fecundity Variance Polymorphism

PubMed Central

Taylor, Jesse E.

2009-01-01

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

Assessment of the magnitude of geographical variations in the duration of non-work-related sickness absence by individual and contextual factors.

PubMed

Torá-Rocamora, Isabel; Martínez, José Miguel; Gimeno, David; Alberti, Constança; Jardí, Josefina; Manzanera, Rafael; Benavides, Fernando G; Delclos, George

2015-01-01

To examine variation in the duration of non-work-related sickness absence (NWRSA) across geographical areas and the degree to which this variation can be explained by individual and/or contextual factors. All first NWRSA episodes ending in 2007 and 2010 were analyzed. Individual (diagnosis, age, sex) and contextual factors (healthcare resources, socioeconomic factors) were analyzed to assess how much of the geographical variation was explained by these factors. Median NWRSA durations in quartiles were mapped by counties in Catalonia. Multilevel Cox proportional hazard regression models with episodes nested within counties were fitted to quantify the magnitude of this variation. The proportional change in variance (PCV), median hazard ratios (MHR) and interquartile hazard ratios (IHR) were calculated. We found a geographical pattern in the duration of NWRSA, with longer duration in northwestern Catalonia. There was a small, but statistically significant, geographical variation in the duration of NWRSA, which mostly decreased after adjustment for individual factors in both women (PCV=34.98%, MHR=1.09, IHR=1.13 in 2007; PCV=34.68%, MHR=1.11, IHR=1.28 in 2010) and men (PCV=39.88%, MHR=1.10, IHR=1.27 in 2007; PCV=45.93%, MHR=1.10, IHR=1.25 in 2010); only in the case of women in 2010 was there a reduction in county-level variance due to contextual covariates (PCV=16.18%, MHR=1.12, IHR=1.32). County-level variation in the duration of NWRSA was small and was explained more by individual than by contextual variables. Knowledge of geographic differences in NWRSA duration is needed to plan specific programs and interventions to minimize these differences. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

An examination of three theoretical models to explain the organ donation attitude--registration discrepancy among mature adults.

PubMed

Quick, Brian L; Anker, Ashley E; Feeley, Thomas Hugh; Morgan, Susan E

2016-01-01

An inconsistency in the research indicates positive attitudes toward organ donation do not map reliably onto organ donor registrations. Various models have sought to explain this inconsistency and the current analysis formally compared three models: the Bystander Intervention Model (BIM), the Organ Donor Model (ODM), and Vested Interest Theory (VIT). Mature (N = 688) adults between the ages of 50 to 64 years completed surveys related to organ donation. Results revealed that VIT accounted for the most variance in organ donation registrations followed by the BIM and ODM. The discussion emphasizes the importance of employing theories to explain a phenomenon as well as the practical implications of the findings.

Comparison between several insulin sensitivity indices and metabolic risk factors in overweight and obese postmenopausal women: a MONET study.

PubMed

Malita, F M; Messier, V; Lavoie, J-M; Bastard, J-P; Rabasa-Lhoret, R; Karelis, A D

2010-03-01

The purpose of this study was to compare the relationship of several insulin sensitivity indices with cardiometabolic risk factors in overweight and obese postmenopausal women. This was a cross-sectional study involving 137 overweight and obese postmenopausal women (age: 57.7+/-4.8 yrs; body mass index: 32.4+/-4.6 kg/m(2); body fat: 38.6+/-9.2 kg). Insulin sensitivity was determined by the euglycaemic-hyperinsulinemic (EH) clamp technique as well as by oral glucose tolerance test (OGTT) derived indices (Stumvoll, Matsuda and SI(is)) and fasting surrogate indices (HOMA, QUICKI). Cardiometabolic risk factors included: body composition and visceral fat that were measured using dual energy X-ray absorptiometry and computed tomography, respectively. Peak oxygen consumption, lower body muscle strength (using weight training equipment), physical activity energy expenditure (doubly labeled water), plasma lipids and C-reactive protein were also measured. Correlations of insulin sensitivity indices with metabolic risk factors showed some similarities, however, a wide range of variations were also observed. Furthermore, our results showed that visceral fat was the primary predictor for surrogate and OGTT indices, explaining 15-28% of the variance and the triglycerides/HDL-C ratio was the primary predictor for the EH clamp indices, explaining 15-17% of the variance. The present study indicates that the different methods of measuring and/or expressing insulin sensitivity display variations for associations with cardiometabolic risk factors. Therefore, interpretations of relationships between insulin sensitivity indices and cardiometabolic risk factors should take into account the method used to estimate and express insulin sensitivity. (c) 2009 Elsevier B.V. All rights reserved.

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

An improved optimization algorithm and Bayes factor termination criterion for sequential projection pursuit

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

Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.

2005-05-28

A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure inmore » the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.« less

42 CFR 456.522 - Content of request for variance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... travel time between the remote facility and each facility listed in paragraph (e) of this section; (f...

On the Performance of Maximum Likelihood versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA

ERIC Educational Resources Information Center

Beauducel, Andre; Herzberg, Philipp Yorck

2006-01-01

This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…

Explaining overweight and obesity in children and adolescents of Asian Indian origin: the Calcutta childhood obesity study.

PubMed

Ghosh, Arnab

2014-01-01

The present study was aimed to find out the prevalence of overweight and obesity and its associated factors among Bengalee children and adolescents in the Kolkata, India. A total of 1061 Bengalee school children and adolescents (610 boys and 451 girls) participated and were divided into three age groups: Group I = 8-11 years; Group II = 12-15 years and Group III = 16-18 years. Overweight and obesity were defined as: Overweight (between ≥85 th and <95 th percentile) and obesity (≥95 th percentile). Multivariate regression analyses (adjusted for age and sex) of body mass index (BMI) revealed that about 18% (R2 = 0.185) of total variance of BMI could be explained by monthly family income, participants think obese, consumption of too much junk foodstuffs, breakfast skip, extra consumption of salt, and computer hours. Sedentary lifestyles, including increasing fast food preferences may be responsible for increasing occurrence of pediatric and adolescent obesity in this population.

Modeling genetic and environmental factors to increase heritability and ease the identification of candidate genes for birth weight: a twin study.

PubMed

Gielen, M; Lindsey, P J; Derom, C; Smeets, H J M; Souren, N Y; Paulussen, A D C; Derom, R; Nijhuis, J G

2008-01-01

Heritability estimates of birth weight have been inconsistent. Possible explanations are heritability changes during gestational age or the influence of covariates (e.g. chorionicity). The aim of this study was to model birth weights of twins across gestational age and to quantify the genetic and environmental components. We intended to reduce the common environmental variance to increase heritability and thereby the chance of identifying candidate genes influencing the genetic variance of birth weight. Perinatal data were obtained from 4232 live-born twin pairs from the East Flanders Prospective Twin Survey, Belgium. Heritability of birth weights across gestational ages was estimated using a non-linear multivariate Gaussian regression with covariates in the means model and in covariance structure. Maternal, twin-specific, and placental factors were considered as covariates. Heritability of birth weight decreased during gestation from 25 to 42 weeks. However, adjusting for covariates increased the heritability over this time period, with the highest heritability for first-born twins of multipara with separate placentas, who were staying alive (from 52% at 25 weeks to 30% at 42 weeks). Twin-specific factors revealed latent genetic components, whereas placental factors explained common and unique environmental factors. The number of placentas and site of the insertion of the umbilical cord masked the effect of chorionicity. Modeling genetic and environmental factors leads to a better estimate of their role in growth during gestation. For birth weight, mainly environmental factors were explained, resulting in an increase of the heritability and thereby the chance of finding genes influencing birth weight in linkage and association studies.

Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

PubMed

Zapko-Willmes, Alexandra; Kandler, Christian

2018-01-01

The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

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

PubMed Central

2012-01-01

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

Factor analysis of an instrument to measure the impact of disease on daily life.

PubMed

Pedrosa, Rafaela Batista Dos Santos; Rodrigues, Roberta Cunha Matheus; Padilha, Kátia Melissa; Gallani, Maria Cecília Bueno Jayme; Alexandre, Neusa Maria Costa

2016-01-01

to verify the structure of factors of an instrument to measure the Heart Valve Disease Impact on Daily Life (IDCV) when applied to coronary artery disease patients. the study included 153 coronary artery disease patients undergoing outpatient follow-up care. The IDCV structure of factors was initially assessed by means of confirmatory factor analysis and, subsequently, by exploratory factor analysis. The Varimax rotation method was used to estimate the main components of analysis, eigenvalues greater than one for extraction of factors, and factor loading greater than 0.40 for selection of items. Internal consistency was estimated using Cronbach's alpha coefficient. confirmatory factor analysis did not confirm the original structure of factors of the IDCV. Exploratory factor analysis showed three dimensions, which together explained 78% of the measurement variance. future studies with expansion of case selection are necessary to confirm the IDCV new structure of factors.

42 CFR 456.522 - Content of request for variance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time..., mental hospital, and ICF located within a 50-mile radius of the facility; (e) The distance and average...

21 CFR 1010.4 - Variances.

Code of Federal Regulations, 2010 CFR

2010-04-01

... (formerly the Radiation Control for Health and Safety Act of 1968), and: (i) The scope of the requested... FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) RADIOLOGICAL HEALTH... and Radiological Health, Food and Drug Administration, may grant a variance from one or more...

Variance decomposition in stochastic simulators.

PubMed

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

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

Le Maître, O. P., E-mail: olm@limsi.fr; Knio, O. M., E-mail: knio@duke.edu; Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance.more » Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.« less

Variance decomposition in stochastic simulators

NASA Astrophysics Data System (ADS)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Home on the Range: Factors Explaining Partial Migration of African Buffalo in a Tropical Environment

PubMed Central

Naidoo, Robin; Du Preez, Pierre; Stuart-Hill, Greg; Jago, Mark; Wegmann, Martin

2012-01-01

Partial migration (when only some individuals in a population undertake seasonal migrations) is common in many species and geographical contexts. Despite the development of modern statistical methods for analyzing partial migration, there have been no studies on what influences partial migration in tropical environments. We present research on factors affecting partial migration in African buffalo (Syncerus caffer) in northeastern Namibia. Our dataset is derived from 32 satellite tracking collars, spans 4 years and contains over 35,000 locations. We used remotely sensed data to quantify various factors that buffalo experience in the dry season when making decisions on whether and how far to migrate, including potential man-made and natural barriers, as well as spatial and temporal heterogeneity in environmental conditions. Using an information-theoretic, non-linear regression approach, our analyses showed that buffalo in this area can be divided into 4 migratory classes: migrants, non-migrants, dispersers, and a new class that we call “expanders”. Multimodel inference from least-squares regressions of wet season movements showed that environmental conditions (rainfall, fires, woodland cover, vegetation biomass), distance to the nearest barrier (river, fence, cultivated area) and social factors (age, size of herd at capture) were all important in explaining variation in migratory behaviour. The relative contributions of these variables to partial migration have not previously been assessed for ungulates in the tropics. Understanding the factors driving migratory decisions of wildlife will lead to better-informed conservation and land-use decisions in this area. PMID:22570722

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.

PubMed

Yang, Jian; Bakshi, Andrew; Zhu, Zhihong; Hemani, Gibran; Vinkhuyzen, Anna A E; Lee, Sang Hong; Robinson, Matthew R; Perry, John R B; Nolte, Ilja M; van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Esko, Tonu; Milani, Lili; Mägi, Reedik; Metspalu, Andres; Hamsten, Anders; Magnusson, Patrik K E; Pedersen, Nancy L; Ingelsson, Erik; Soranzo, Nicole; Keller, Matthew C; Wray, Naomi R; Goddard, Michael E; Visscher, Peter M

2015-10-01

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.

Experimental cosmic statistics - I. Variance

NASA Astrophysics Data System (ADS)

Colombi, Stéphane; Szapudi, István; Jenkins, Adrian; Colberg, Jörg

2000-04-01

Counts-in-cells are measured in the τCDM Virgo Hubble Volume simulation. This large N-body experiment has 109 particles in a cubic box of size 2000h-1Mpc. The unprecedented combination of size and resolution allows, for the first time, a realistic numerical analysis of the cosmic errors and cosmic correlations of statistics related to counts-in-cells measurements, such as the probability distribution function PN itself, its factorial moments Fk and the related cumulants ψ and SNs. These statistics are extracted from the whole simulation cube, as well as from 4096 subcubes of size 125h-1Mpc, each representing a virtual random realization of the local universe. The measurements and their scatter over the subvolumes are compared to the theoretical predictions of Colombi, Bouchet & Schaeffer for P0, and of Szapudi & Colombi and Szapudi, Colombi & Bernardeau for the factorial moments and the cumulants. The general behaviour of experimental variance and cross-correlations as functions of scale and order is well described by theoretical predictions, with a few per cent accuracy in the weakly non-linear regime for the cosmic error on factorial moments. On highly non-linear scales, however, all variants of the hierarchical model used by SC and SCB to describe clustering appear to become increasingly approximate, which leads to a slight overestimation of the error, by about a factor of two in the worst case. Because of the needed supplementary perturbative approach, the theory is less accurate for non-linear estimators, such as cumulants, than for factorial moments. The cosmic bias is evaluated as well, and, in agreement with SCB, is found to be insignificant compared with the cosmic variance in all regimes investigated. While higher order statistics were previously evaluated in several simulations, this work presents textbook quality measurements of SNs, 3<=N<=10, in an unprecedented dynamic range of 0.05 <~ ψ <~ 50. In the weakly non-linear regime the results confirm

Robust versus consistent variance estimators in marginal structural Cox models.

PubMed

Enders, Dirk; Engel, Susanne; Linder, Roland; Pigeot, Iris

2018-06-11

In survival analyses, inverse-probability-of-treatment (IPT) and inverse-probability-of-censoring (IPC) weighted estimators of parameters in marginal structural Cox models are often used to estimate treatment effects in the presence of time-dependent confounding and censoring. In most applications, a robust variance estimator of the IPT and IPC weighted estimator is calculated leading to conservative confidence intervals. This estimator assumes that the weights are known rather than estimated from the data. Although a consistent estimator of the asymptotic variance of the IPT and IPC weighted estimator is generally available, applications and thus information on the performance of the consistent estimator are lacking. Reasons might be a cumbersome implementation in statistical software, which is further complicated by missing details on the variance formula. In this paper, we therefore provide a detailed derivation of the variance of the asymptotic distribution of the IPT and IPC weighted estimator and explicitly state the necessary terms to calculate a consistent estimator of this variance. We compare the performance of the robust and consistent variance estimators in an application based on routine health care data and in a simulation study. The simulation reveals no substantial differences between the 2 estimators in medium and large data sets with no unmeasured confounding, but the consistent variance estimator performs poorly in small samples or under unmeasured confounding, if the number of confounders is large. We thus conclude that the robust estimator is more appropriate for all practical purposes. Copyright © 2018 John Wiley & Sons, Ltd.

Metropolitan isolation segregation and Black-White disparities in very preterm birth: a test of mediating pathways and variance explained.

PubMed

Kramer, Michael R; Cooper, Hannah L; Drews-Botsch, Carolyn D; Waller, Lance A; Hogue, Carol R

2010-12-01

Residential isolation segregation (a measure of residential inter-racial exposure) has been associated with rates of preterm birth (<37 weeks gestation) experienced by Black women. Epidemiologic differences between very preterm (<32 weeks gestation) and moderately preterm births (32-36 weeks) raise questions about whether this association is similar across gestational ages, and through what pathways it might be mediated. Hierarchical Bayesian models were fit to answer three questions: is the isolation-prematurity association similar for very and moderately preterm birth; is this association mediated by maternal chronic disease, socioeconomic status, or metropolitan area crime and poverty rates; and how much of the geographic variation in Black-White very preterm birth disparities is explained by isolation segregation? Singleton births to Black and White women in 231 U.S. metropolitan statistical areas in 2000-2002 were analyzed and isolation segregation was calculated for each. We found that among Black women, isolation is associated with very preterm birth and moderately preterm birth. The association may be partially mediated by individual level socioeconomic characteristics and metropolitan level violent crime rates. There is no association between segregation and prematurity among White women. Isolation segregation explains 28% of the geographic variation in Black-White very preterm birth disparities. Our findings highlight the importance of isolation segregation for the high-burden outcome of very preterm birth, but unexplained excess risk for prematurity among Black women is substantial. Copyright © 2010 Elsevier Ltd. All rights reserved.

40 CFR 142.302 - Who can issue a small system variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Who can issue a small system variance? 142.302 Section 142.302 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER... General Provisions § 142.302 Who can issue a small system variance? A small system variance under this...

The lesser known challenge of climate change: thermal variance and sex-reversal in vertebrates with temperature-dependent sex determination.

PubMed

Neuwald, Jennifer L; Valenzuela, Nicole

2011-03-23

Climate change is expected to disrupt biological systems. Particularly susceptible are species with temperature-dependent sex determination (TSD), as in many reptiles. While the potentially devastating effect of rising mean temperatures on sex ratios in TSD species is appreciated, the consequences of increased thermal variance predicted to accompany climate change remain obscure. Surprisingly, no study has tested if the effect of thermal variance around high-temperatures (which are particularly relevant given climate change predictions) has the same or opposite effects as around lower temperatures. Here we show that sex ratios of the painted turtle (Chrysemys picta) were reversed as fluctuations increased around low and high unisexual mean-temperatures. Unexpectedly, the developmental and sexual responses around female-producing temperatures were decoupled in a more complex manner than around male-producing values. Our novel observations are not fully explained by existing ecological models of development and sex determination, and provide strong evidence that thermal fluctuations are critical for shaping the biological outcomes of climate change.

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

USGS Publications Warehouse

Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

[Factors of psychiatric treatment satisfaction in inpatients with neurotic and depressive disorders].

PubMed

Tsygankov, B D; Malygin, Ya V; Gatin, F F

2015-01-01

Factors of patients' satisfaction with medical care vary depending on the level of care and medical specialty. Patient's satisfaction with psychiatric care is understudied. An aim of the present study is to find out the factors of satisfaction with psychiatric care in inpatients with neurotic and depressive disorders. The sample included 356 inpatients suffering from neurotic or depressive disorders. The patients were questioned using PAPI questionnaire designed for this study. Statistical analysis was performed using multiple regression. Key factors of satisfaction with medical care included quality of work of nurses and psychiatrists, hospital ward comfort, the number and quality of psychotherapeutic sessions, psychiatrists' empathy and aptitude to provide the patient with information about the disease and treatment. Multiple regression equation explained 81% of the variance of patients' satisfaction.

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

PubMed

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

2017-12-05

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

A stochastic hybrid model for pricing forward-start variance swaps

NASA Astrophysics Data System (ADS)

Roslan, Teh Raihana Nazirah

2017-11-01

Recently, market players have been exposed to the astounding increase in the trading volume of variance swaps. In this paper, the forward-start nature of a variance swap is being inspected, where hybridizations of equity and interest rate models are used to evaluate the price of discretely-sampled forward-start variance swaps. The Heston stochastic volatility model is being extended to incorporate the dynamics of the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. This is essential since previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps without considering the interest rate effects. This hybrid model produces an efficient semi-closed form pricing formula through the development of forward characteristic functions. The performance of this formula is investigated via simulations to demonstrate how the formula performs for different sampling times and against the real market scenario. Comparison done with the Monte Carlo simulation which was set as our main reference point reveals that our pricing formula gains almost the same precision in a shorter execution time.

Five Describing Factors of Dyslexia.

PubMed

Tamboer, Peter; Vorst, Harrie C M; Oort, Frans J

2016-09-01

Two subtypes of dyslexia (phonological, visual) have been under debate in various studies. However, the number of symptoms of dyslexia described in the literature exceeds the number of subtypes, and underlying relations remain unclear. We investigated underlying cognitive features of dyslexia with exploratory and confirmatory factor analyses. A sample of 446 students (63 with dyslexia) completed a large test battery and a large questionnaire. Five factors were found in both the test battery and the questionnaire. These 10 factors loaded on 5 latent factors (spelling, phonology, short-term memory, rhyme/confusion, and whole-word processing/complexity), which explained 60% of total variance. Three analyses supported the validity of these factors. A confirmatory factor analysis fit with a solution of five factors (RMSEA = .03). Those with dyslexia differed from those without dyslexia on all factors. A combination of five factors provided reliable predictions of dyslexia and nondyslexia (accuracy >90%). We also looked for factorial deficits on an individual level to construct subtypes of dyslexia, but found varying profiles. We concluded that a multiple cognitive deficit model of dyslexia is supported, whereas the existence of subtypes remains unclear. We discussed the results in relation to advanced compensation strategies of students, measures of intelligence, and various correlations within groups of those with and without dyslexia. © Hammill Institute on Disabilities 2014.

What Factors Explain Harmful Algal Blooms of Dinophysis Along the Texas Coast?

NASA Astrophysics Data System (ADS)

Replogle, L.; Henrichs, D.; Campbell, L.

2016-02-01

The toxic dinoflagellate Dinophysis ovum is one of the harmful algal species that bloom along the Texas coast. Blooms of D. ovum can be explained by several factors that work together to cause bloom initiation. This work utilized image counts collected by the Imaging FlowCytobot (IFCB) at Port Aransas, TX and modeled winds from the European Centre for Medium-range Weather Forecasts. Based on a previous study of another dinoflagellate species, it was hypothesized that winds will be highly correlated with harmful algal bloom (HAB) years versus non-HAB years for D. ovum. Weak northerly winds and downwelling along the coast will be associated with HAB years, while strong northerly or southerly winds will be associated with non-HAB years. In non-HAB years, wind-driven currents caused by upcoast or strongly flowing downcoast winds will result in northward or southward movement of D. ovum cells. In HAB years, weaker downcoast winds will allow for accumulation of D. ovum at the coast. Results showed that weak downcoast, along-shore winds occurred in the weeks preceding HAB events in 2008, 2010, 2011, 2012 and 2014, and likely contributed to the accumulation of Dinophysis cells along the Texas coast. When winds moved upcoast or strongly downcoast in the weeks preceding bloom months, Dinophysis blooms did not occur. Additional factors (e.g. sea surface temperature, surface-based runoff, El Niño Southern Oscillation, North Atlantic Oscillation and salinity) were analyzed to better define a favorable environment for bloom formation. Sea surface temperature and surface based runoff were significantly correlated with bloom occurrence, whereas El Niño Southern Oscillation and the North Atlantic Oscillation were not.

Factor analysis of the Colombian translation of the Delirium Rating Scale (DRS), Revised-98.

PubMed

Franco, José G; Trzepacz, Paula T; Mejía, Mario A; Ochoa, Sol B

2009-01-01

The phenomenology of delirium needs further elucidation using validated tools. The authors sought to derive valid factors from the Delirium Rating Scale (DRS), Revised -98. A factor analysis of the DRS-R-98 was performed among 161 medical-surgical patients. Scores ranged from 0 to 7 in 120 patients (74.53%; no delirium), 8 to 13 in 19 (11.80%; subclinical/prodromal delirium), and > or = 14 in 22 (13.66%; delirium). The DSM-IV-TR delirium incidence was 19.87%. The first two rotated factors explained 63.37% of the variance and may correspond to Cognition and Psychosis/Agitation factors. The dimension of motor retardation loaded with cognitive items. Motor agitation and retardation clustered with inattention, which is the cardinal symptom of delirium. The DRS-R-98 has good construct validity in this Latino population.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

PubMed

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance

A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

PubMed Central

Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

Variance and covariance estimates for weaning weight of Senepol cattle.

PubMed

Wright, D W; Johnson, Z B; Brown, C J; Wildeus, S

1991-10-01

Variance and covariance components were estimated for weaning weight from Senepol field data for use in the reduced animal model for a maternally influenced trait. The 4,634 weaning records were used to evaluate 113 sires and 1,406 dams on the island of St. Croix. Estimates of direct additive genetic variance (sigma 2A), maternal additive genetic variance (sigma 2M), covariance between direct and maternal additive genetic effects (sigma AM), permanent maternal environmental variance (sigma 2PE), and residual variance (sigma 2 epsilon) were calculated by equating variances estimated from a sire-dam model and a sire-maternal grandsire model, with and without the inverse of the numerator relationship matrix (A-1), to their expectations. Estimates were sigma 2A, 139.05 and 138.14 kg2; sigma 2M, 307.04 and 288.90 kg2; sigma AM, -117.57 and -103.76 kg2; sigma 2PE, -258.35 and -243.40 kg2; and sigma 2 epsilon, 588.18 and 577.72 kg2 with and without A-1, respectively. Heritability estimates for direct additive (h2A) were .211 and .210 with and without A-1, respectively. Heritability estimates for maternal additive (h2M) were .47 and .44 with and without A-1, respectively. Correlations between direct and maternal (IAM) effects were -.57 and -.52 with and without A-1, respectively.

Cosmic variance and the measurement of the local Hubble parameter.

PubMed

Marra, Valerio; Amendola, Luca; Sawicki, Ignacy; Valkenburg, Wessel

2013-06-14

There is an approximately 9% discrepancy, corresponding to 2.4 σ, between two independent constraints on the expansion rate of the Universe: one indirectly arising from the cosmic microwave background and baryon acoustic oscillations and one more directly obtained from local measurements of the relation between redshifts and distances to sources. We argue that by taking into account the local gravitational potential at the position of the observer this tension--strengthened by the recent Planck results--is partially relieved and the concordance of the Standard Model of cosmology increased. We estimate that measurements of the local Hubble constant are subject to a cosmic variance of about 2.4% (limiting the local sample to redshifts z > 0.010) or 1.3% (limiting it to z > 0.023), a more significant correction than that taken into account already. Nonetheless, we show that one would need a very rare fluctuation to fully explain the offset in the Hubble rates. If this tension is further strengthened, a cosmology beyond the Standard Model may prove necessary.

Estimation of Variance in the Case of Complex Samples.

ERIC Educational Resources Information Center

Groenewald, A. C.; Stoker, D. J.

In a complex sampling scheme it is desirable to select the primary sampling units (PSUs) without replacement to prevent duplications in the sample. Since the estimation of the sampling variances is more complicated when the PSUs are selected without replacement, L. Kish (1965) recommends that the variance be calculated using the formulas…

Factor contribution to fire occurrence, size, and burn probability in a subtropical coniferous forest in East China.

PubMed

Ye, Tao; Wang, Yao; Guo, Zhixing; Li, Yijia

2017-01-01

The contribution of factors including fuel type, fire-weather conditions, topography and human activity to fire regime attributes (e.g. fire occurrence, size distribution and severity) has been intensively discussed. The relative importance of those factors in explaining the burn probability (BP), which is critical in terms of fire risk management, has been insufficiently addressed. Focusing on a subtropical coniferous forest with strong human disturbance in East China, our main objective was to evaluate and compare the relative importance of fuel composition, topography, and human activity for fire occurrence, size and BP. Local BP distribution was derived with stochastic fire simulation approach using detailed historical fire data (1990-2010) and forest-resource survey results, based on which our factor contribution analysis was carried out. Our results indicated that fuel composition had the greatest relative importance in explaining fire occurrence and size, but human activity explained most of the variance in BP. This implies that the influence of human activity is amplified through the process of overlapping repeated ignition and spreading events. This result emphasizes the status of strong human disturbance in local fire processes. It further confirms the need for a holistic perspective on factor contribution to fire likelihood, rather than focusing on individual fire regime attributes, for the purpose of fire risk management.

29 CFR 1920.2 - Variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

Variance in prey abundance influences time budgets of breeding seabirds: Evidence from pigeon guillemots Cepphus columba

USGS Publications Warehouse

Litzow, Michael A.; Piatt, John F.

2003-01-01

We use data on pigeon guillemots Cepphus columba to test the hypothesis that discretionary time in breeding seabirds is correlated with variance in prey abundance. We measured the amount of time that guillemots spent at the colony before delivering fish to chicks ("resting time") in relation to fish abundance as measured by beach seines and bottom trawls. Radio telemetry showed that resting time was inversely correlated with time spent diving for fish during foraging trips (r = -0.95). Pigeon guillemots fed their chicks either Pacific sand lance Ammodytes hexapterus, a schooling midwater fish, which exhibited high interannual variance in abundance (CV = 181%), or a variety of non-schooling demersal fishes, which were less variable in abundance (average CV = 111%). Average resting times were 46% higher at colonies where schooling prey dominated the diet. Individuals at these colonies reduced resting times 32% during years of low food abundance, but did not reduce meal delivery rates. In contrast, individuals feeding on non-schooling fishes did not reduce resting times during low food years, but did reduce meal delivery rates by 27%. Interannual variance in resting times was greater for the schooling group than for the non-schooling group. We conclude from these differences that time allocation in pigeon guillemots is more flexible when variable schooling prey dominate diets. Resting times were also 27% lower for individuals feeding two-chick rather than one-chick broods. The combined effects of diet and brood size on adult time budgets may help to explain higher rates of brood reduction for pigeon guillemot chicks fed non-schooling fishes.

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

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.

40 CFR 59.509 - Can I get a variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Can I get a variance? 59.509 Section 59... Volatile Organic Compound Emission Standards for Aerosol Coatings § 59.509 Can I get a variance? (a) Any... compliance plan proposed by the applicant can reasonably be implemented and will achieve compliance as...

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

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

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

Alcohol-related Genes Show an Enrichment of Associations with a Persistent Externalizing Factor

PubMed Central

Ashenhurst, James R.; Harden, K. Paige; Corbin, William R.; Fromme, Kim

2016-01-01

Research using twins has found that much of the variability in externalizing phenotypes – including alcohol and drug use, impulsive personality traits, risky sex and property crime – is explained by genetic factors. Nevertheless, identification of specific genes and variants associated with these traits has proven to be difficult, likely because individual differences in externalizing are explained by many genes of small individual effect. Moreover, twin research indicates that heritable variance in externalizing behaviors is mostly shared across the externalizing spectrum rather than specific to any behavior. We use a longitudinal, “deep phenotyping” approach to model a general externalizing factor reflecting persistent engagement in a variety of socially problematic behaviors measured at eleven assessment occasions spanning early adulthood (ages 18 to 28). In an ancestrally homogenous sample of non-Hispanic Whites (N = 337), we then tested for enrichment of associations between the persistent externalizing factor and a set of 3,281 polymorphisms within 104 genes that were previously identified as associated with alcohol-use behaviors. Next we tested for enrichment among domain-specific factors (e.g., property crime) composed of residual variance not accounted for by the common factor. Significance was determined relative to bootstrapped empirical thresholds derived from permutations of phenotypic data. Results indicated significant enrichment of genetic associations for persistent externalizing, but not for domain-specific factors. Consistent with twin research findings, these results suggest that genetic variants are broadly associated with externalizing behaviors rather than unique to specific behaviors. General Scientific Summary This study shows that variation in 104 genes is associated with socially problematic “externalizing” behavior, including substance misuse, property crime, risky sex, and aspects of impulsive personality. Importantly, this

Associations between factors within the home setting and screen time among children aged 0–5 years: a cross-sectional study

PubMed Central

2012-01-01

Background Excessive engagement in screen time has several immediate and long-term health implications among pre-school children. However, little is known about the factors that influence screen time in this age group. Therefore, the purpose of this study was to use the Ecologic Model of Sedentary Behavior as a guide to examine associations between intrapersonal, interpersonal, and physical environment factors within the home setting and screen time among pre-school children. Methods Participants were 746 pre-school children (≤ 5 years old) from the Kingston, Ontario, Canada area. From May to September, 2011, parents completed a questionnaire regarding several intrapersonal (child demographics), interpersonal (family demographics, parental cognitions, parental behavior), and physical environment (television, computer, or video games in the bedroom) factors within the home setting. Parents also reported the average amount of time per day their child spent watching television and playing video/computer games. Associations were examined using linear and logistic regression models. Results Most participants (93.7%) watched television and 37.9% played video/computer games. Several intrapersonal, interpersonal, and physical environment factors within the home setting were associated with screen time. More specifically, age, parental attitudes, parental barriers, parental descriptive norms, parental screen time, and having a television in the bedroom were positive predictors of screen time; whereas, parental education, parental income, and parental self-efficacy were negative predictors of screen time in the linear regression analysis. Collectively these variables explained 64.2% of the variance in screen time. Parental cognitive factors (self-efficacy, attitudes, barriers, descriptive norms) at the interpersonal level explained a large portion (37.9%) of this variance. Conclusions A large proportion of screen time in pre-school children was explained by factors

Does Social Capital Explain Community-Level Differences in Organ Donor Designation?

PubMed

Ladin, Keren; Wang, Rui; Fleishman, Aaron; Boger, Matthew; Rodrigue, James R

2015-09-01

mobility, violent-death rate), and religious characteristics. We used spatial modeling, including lagged variables to account for the effect of adjacent block groups, and multivariate regression analysis to examine the relationship of social capital and community-level characteristics with organ donor designation rates. Block groups with higher levels of social capital, racial homogeneity, income, workforce participation, owner-occupied housing, native-born residents, and white residents had higher rates of organ donor designation (p < 0.001). These factors remained significant in the multivariate model, which explained more than half the geographic variance in organ donor designation (R(2) = 0.52). The findings suggest that community-level factors, including social capital, predict more than half the variation in donor designation. Future interventions should target the community as the unit of intervention and should tailor messaging for areas with low social capital. © 2015 Milbank Memorial Fund.

The role of NT-proBNP in explaining the variance in anaerobic threshold and VE/VCO(2) slope.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2011-01-01

We investigated whether anaerobic threshold (AT) and ventilatory efficiency (minute ventilation/carbon dioxide production slope, VE/VCO2 slope), both significantly associated with mortality, can be predicted by questionnaire scores and/or other laboratory measurements. Anaerobic threshold and VE/VCO(2) slope, plasma N-terminal pro-brain natriuretic peptide (NT-proBNP), and the echocardiographic markers left ventricular ejection fraction (LVEF) and left atrial (LA) diameter were measured in 62 patients with heart failure (HF), who also completed the Minnesota Living with Heart Failure Questionnaire (MLHF), and the Specific Activity Questionnaire (SAQ). Linear regression models, adjusting for age and gender, were fitted. While the etiology of HF, SAQ score, MLHF score, LVEF, LA diameter, and logNT-proBNP were each significantly predictive of both AT and VE/VCO2 slope on stepwise multiple linear regression, only SAQ score (P < .001) and logNT-proBNP (P = .001) were significantly predictive of AT, explaining 56% of the variability (adjusted R(2) = 0.525), while logNT-proBNP (P < .001) and etiology of HF (P = .003) were significantly predictive of VE/VCO(2) slope, explaining 49% of the variability (adjusted R(2) = 0.45). The area under the ROC curve for NT-proBNP to identify patients with a VE/VCO(2) slope greater than 34 and AT less than 11 mL · kg(-1) · min(-1) was 0.797; P < .001 and 0.712; P = .044, respectively. A plasma concentration greater than 429.5 pg/mL (sensitivity: 78%; specificity: 70%) and greater than 674.5 pg/mL (sensitivity: 77.8%; specificity: 65%) identified a VE/VCO(2) slope greater than 34 and AT lower than 11 mL · kg(-1) · min(-1), respectively. NT-proBNP is independently related to both AT and VE/VCO(2) slope. Specific Activity Questionnaire score is independently related only to AT and the etiology of HF only to VE/VCO(2) slope.

Validating Variance Similarity Functions in the Entrainment Zone

NASA Astrophysics Data System (ADS)

Osman, M.; Turner, D. D.; Heus, T.; Newsom, R. K.

2017-12-01

In previous work, the water vapor variance in the entrainment zone was proposed to be proportional to the convective velocity scale, gradient water vapor mixing ratio and the Brunt-Vaisala frequency in the interfacial layer, while the variance of the vertical wind at in the entrainment zone was defined in terms of the convective velocity scale. The variances in the entrainment zone have been hypothesized to depend on two distinct functions, which also depend on the Richardson number. To the best of our knowledge, these hypotheses have never been tested observationally. Simultaneous measurements of the Eddy correlation surface flux, wind shear profiles from wind profilers, and variance profile measurements of vertical motions and water vapor by Doppler and Raman lidars, respectively, provide a unique opportunity to thoroughly examine the functions used in defining the variances and validate them. These observations were made over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. We have identified about 30 cases from 2016 during which the convective boundary layer (CBL) is quasi-stationary and well mixed for at least 2 hours. The vertical profiles of turbulent fluctuations of the vertical wind and water vapor have been derived using an auto covariance technique to separate out the instrument random error to a set of 2-h period time series. The error analysis of the lidars observations demonstrates that the lidars are capable of resolving the vertical structure of turbulence around the entrainment zone. Therefore, utilizing this unique combination of observations, this study focuses on extensively testing the hypotheses that the second-order moments are indeed proportional to the functions which also depend on Richardson number. The coefficients that are used in defining the functions will also be determined observationally and compared against with the values suggested by Large eddy simulation (LES) studies.

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

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2010 CFR

2010-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... which the employer has taken to protect the health and safety of workers and adequately show that such... local Job Service office shall send the request to the State office which, in turn, shall forward it to...

The Variance Reaction Time Model

ERIC Educational Resources Information Center

Sikstrom, Sverker

2004-01-01

The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…

The use of analysis of variance procedures in biological studies

USGS Publications Warehouse

Williams, B.K.

1987-01-01

The analysis of variance (ANOVA) is widely used in biological studies, yet there remains considerable confusion among researchers about the interpretation of hypotheses being tested. Ambiguities arise when statistical designs are unbalanced, and in particular when not all combinations of design factors are represented in the data. This paper clarifies the relationship among hypothesis testing, statistical modelling and computing procedures in ANOVA for unbalanced data. A simple two-factor fixed effects design is used to illustrate three common parametrizations for ANOVA models, and some associations among these parametrizations are developed. Biologically meaningful hypotheses for main effects and interactions are given in terms of each parametrization, and procedures for testing the hypotheses are described. The standard statistical computing procedures in ANOVA are given along with their corresponding hypotheses. Throughout the development unbalanced designs are assumed and attention is given to problems that arise with missing cells.

Suicidal and nonsuicidal adolescents: different factors contribute to self-esteem.

PubMed

Grøholt, Berit; Ekeberg, Oivind; Wichstrøm, Lars; Haldorsen, Tor

2005-10-01

Some risk and protective factors differ in their importance to suicidal and nonsuicidal people. In this research we explore the cross-sectional differences between risk factors among suicidal adolescents and nonsuicidal adolescents by focusing on self-esteem. Sixty-five suicidal and 390 nonsuicidal adolescents were compared on Harter's Self-Perceived Profile for Adolescents, self-concept stability, seeking support, loneliness, and depression. Self-concept stability, loneliness, and peer support correlated differently with self-esteem. In multivariate regression analyses, variance in self-esteem was explained by depression and loneliness, and among nonsuicidal adolescents also by self-concept stability, support, and competencies. Loneliness and self-concept stability related differently to self-esteem in suicidal and nonsuicidal adolescents. When the aim is to enhance self-esteem, this difference may delineate suicidal subgroups that need special interventions.

Variance in population firing rate as a measure of slow time-scale correlation

PubMed Central

Snyder, Adam C.; Morais, Michael J.; Smith, Matthew A.

2013-01-01

Correlated variability in the spiking responses of pairs of neurons, also known as spike count correlation, is a key indicator of functional connectivity and a critical factor in population coding. Underscoring the importance of correlation as a measure for cognitive neuroscience research is the observation that spike count correlations are not fixed, but are rather modulated by perceptual and cognitive context. Yet while this context fluctuates from moment to moment, correlation must be calculated over multiple trials. This property undermines its utility as a dependent measure for investigations of cognitive processes which fluctuate on a trial-to-trial basis, such as selective attention. A measure of functional connectivity that can be assayed on a moment-to-moment basis is needed to investigate the single-trial dynamics of populations of spiking neurons. Here, we introduce the measure of population variance in normalized firing rate for this goal. We show using mathematical analysis, computer simulations and in vivo data how population variance in normalized firing rate is inversely related to the latent correlation in the population, and how this measure can be used to reliably classify trials from different typical correlation conditions, even when firing rate is held constant. We discuss the potential advantages for using population variance in normalized firing rate as a dependent measure for both basic and applied neuroscience research. PMID:24367326

How does variance in fertility change over the demographic transition?

PubMed Central

Hruschka, Daniel J.; Burger, Oskar

2016-01-01

Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45–49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. PMID:27022082

Infinite variance in fermion quantum Monte Carlo calculations.

PubMed

Shi, Hao; Zhang, Shiwei

2016-03-01

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

Evaluation of potentially modifiable physical factors as predictors of health status in knee osteoarthritis patients referred for physical therapy.

PubMed

Gonçalves, Rui Soles; Pinheiro, João Páscoa; Cabri, Jan

2012-08-01

The purpose of this cross sectional study was to estimate the contributions of potentially modifiable physical factors to variations in perceived health status in knee osteoarthritis (OA) patients referred for physical therapy. Health status was measured by three questionnaires: Knee injury and Osteoarthritis Outcome Score (KOOS); Knee Outcome Survey - Activities of Daily Living Scale (KOS-ADLS); and Medical Outcomes Study - 36 item Short Form (SF-36). Physical factors were measured by a battery of tests: body mass index (BMI); visual analog scale (VAS) of pain intensity; isometric dynamometry; universal goniometry; step test (ST); timed "up and go" test (TUGT); 20-meter walk test (20MWT); and 6-minute walk test (6MWT). All tests were administered to 136 subjects with symptomatic knee OA (94 females, 42 males; age: 67.2 ± 7.1 years). Multiple stepwise regression analyses revealed that knee muscle strength, VAS of pain intensity, 6MWT, degree of knee flexion and BMI were moderate predictors of health status. In the final models, selected combinations of these potentially modifiable physical factors explained 22% to 37% of the variance in KOOS subscale scores, 40% of the variance in the KOS-ADLS scale score, and 21% to 34% of the variance in physical health SF-36 subscale scores. More research is required in order to evaluate whether therapeutic interventions targeting these potentially modifiable physical factors would improve health status in knee OA patients. Copyright © 2011 Elsevier B.V. All rights reserved.

Hypothesis exploration with visualization of variance

PubMed Central

2014-01-01

Background The Consortium for Neuropsychiatric Phenomics (CNP) at UCLA was an investigation into the biological bases of traits such as memory and response inhibition phenotypes—to explore whether they are linked to syndromes including ADHD, Bipolar disorder, and Schizophrenia. An aim of the consortium was in moving from traditional categorical approaches for psychiatric syndromes towards more quantitative approaches based on large-scale analysis of the space of human variation. It represented an application of phenomics—wide-scale, systematic study of phenotypes—to neuropsychiatry research. Results This paper reports on a system for exploration of hypotheses in data obtained from the LA2K, LA3C, and LA5C studies in CNP. ViVA is a system for exploratory data analysis using novel mathematical models and methods for visualization of variance. An example of these methods is called VISOVA, a combination of visualization and analysis of variance, with the flavor of exploration associated with ANOVA in biomedical hypothesis generation. It permits visual identification of phenotype profiles—patterns of values across phenotypes—that characterize groups. Visualization enables screening and refinement of hypotheses about variance structure of sets of phenotypes. Conclusions The ViVA system was designed for exploration of neuropsychiatric hypotheses by interdisciplinary teams. Automated visualization in ViVA supports ‘natural selection’ on a pool of hypotheses, and permits deeper understanding of the statistical architecture of the data. Large-scale perspective of this kind could lead to better neuropsychiatric diagnostics. PMID:25097666

Analysis of Variance: Variably Complex

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2012-01-01

These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution…

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2011 CFR

2011-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2012 CFR

2012-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2013 CFR

2013-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2014 CFR

2014-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

Factors Contributing to 50-ft Walking Speed and Observed Ethnic Differences in Older Community-Dwelling Mexican Americans and European Americans

PubMed Central

Hazuda, Helen P.

2015-01-01

Background Mexican Americans comprise the most rapidly growing segment of the older US population and are reported to have poorer functional health than European Americans, but few studies have examined factors contributing to ethnic differences in walking speed between Mexican Americans and European Americans. Objective The purpose of this study was to examine factors that contribute to walking speed and observed ethnic differences in walking speed in older Mexican Americans and European Americans using the disablement process model (DPM) as a guide. Design This was an observational, cross-sectional study. Methods Participants were 703 Mexican American and European American older adults (aged 65 years and older) who completed the baseline examination of the San Antonio Longitudinal Study of Aging (SALSA). Hierarchical regression models were performed to identify the contribution of contextual, lifestyle/anthropometric, disease, and impairment variables to walking speed and to ethnic differences in walking speed. Results The ethic difference in unadjusted mean walking speed (Mexican Americans=1.17 m/s, European Americans=1.29 m/s) was fully explained by adjustment for contextual (ie, age, sex, education, income) and lifestyle/anthropometric (ie, body mass index, height, physical activity) variables; adjusted mean walking speed in both ethnic groups was 1.23 m/s. Contextual variables explained 20.3% of the variance in walking speed, and lifestyle/anthropometric variables explained an additional 8.4%. Diseases (ie, diabetes, stroke, chronic obstructive pulmonary disease) explained an additional 1.9% of the variance in walking speed; impairments (ie, FEV1, upper leg pain, and lower extremity strength and range of motion) contributed an additional 5.5%. Thus, both nonmodifiable (ie, contextual, height) and modifiable (ie, impairments, body mass index, physical activity) factors contributed to walking speed in older Mexican Americans and European Americans. Limitations

Risk factors for suicidal ideation among college students: 6-month follow-up.

PubMed

Shtayermman, Oren; Fayda, Matthew G; Knight, Kim L

This study was a 6-month follow-up study examining risk factors for suicide among college students. The sample included 95 participants who also participated in the first data collection period. Online questionnaires were completed by participants from the first wave. Thirteen percent of the sample had clinically significant levels of suicidal ideation, 3.2% met the criteria for dysthymia, and 15.8% and 17.9% met the DSM-IV criteria for a diagnosis of Major Depressive Disorder and Generalized Anxiety Disorder, respectfully. About 9.5% met criteria for alcohol dependence and 16.8% met criteria for drug abuse. Overall, 23% of the variance was explained in suicidal ideation with depressive symptoms, presence of anxiety, and high relational victimization scores attributing to 15% of the variance. Results of the 6-month follow-up support prior research suggesting high correlation between Major Depressive Disorder and suicidal ideation. However, there was no correlation found between levels of suicidal ideation and Generalized Anxiety Disorders.

Repeat sample intraocular pressure variance in induced and naturally ocular hypertensive monkeys.

PubMed

Dawson, William W; Dawson, Judyth C; Hope, George M; Brooks, Dennis E; Percicot, Christine L

2005-12-01

To compare repeat-sample means variance of laser induced ocular hypertension (OH) in rhesus monkeys with the repeat-sample mean variance of natural OH in age-range matched monkeys of similar and dissimilar pedigrees. Multiple monocular, retrospective, intraocular pressure (IOP) measures were recorded repeatedly during a short sampling interval (SSI, 1-5 months) and a long sampling interval (LSI, 6-36 months). There were 5-13 eyes in each SSI and LSI subgroup. Each interval contained subgroups from the Florida with natural hypertension (NHT), induced hypertension (IHT1) Florida monkeys, unrelated (Strasbourg, France) induced hypertensives (IHT2), and Florida age-range matched controls (C). Repeat-sample individual variance means and related IOPs were analyzed by a parametric analysis of variance (ANOV) and results compared to non-parametric Kruskal-Wallis ANOV. As designed, all group intraocular pressure distributions were significantly different (P < or = 0.009) except for the two (Florida/Strasbourg) induced OH groups. A parametric 2 x 4 design ANOV for mean variance showed large significant effects due to treatment group and sampling interval. Similar results were produced by the nonparametric ANOV. Induced OH sample variance (LSI) was 43x the natural OH sample variance-mean. The same relationship for the SSI was 12x. Laser induced ocular hypertension in rhesus monkeys produces large IOP repeat-sample variance mean results compared to controls and natural OH.

Job demand and control in mid-life and physical and mental functioning in early old age: do childhood factors explain these associations in a British birth cohort?

PubMed Central

von Bonsdorff, Mikaela B; Cooper, Rachel; Kuh, Diana

2014-01-01

Objectives Adverse work-related exposures have been linked with decreased physical and mental functioning in later life, however, whether childhood factors explain the associations between work exposures and functioning is unknown. Our aim was to investigate if job demand and control in mid-life were related to self-reported physical and mental functioning in early old age and whether childhood factors explained these associations. Design Prospective cohort study. Setting England, Scotland and Wales. Participants and outcome measures Data come from the UK Medical Research Council National Survey of Health and Development, a cohort with follow-up since birth in 1946. 1485 occupationally active study members had data available on job demand and control in mid-life and on physical and mental functioning assessed using the Short Form-36 questionnaire at 60–64 years. Results Those with higher job control in mid-life had better physical functioning than those who reported lower job control (β 0.51, 95% CI 0.02 to 1.01, p=0.04 adjusted for adult confounders). Those with higher job demand in mid-life had poorer mental functioning (β −0.82, 95% CI −1.14 to −0.51, p<0.001). Associations between job control and mental functioning were similar but less pronounced. Adjustment for childhood factors (father's and mother's educational attainment, parents’ interest in school at age 7 and cognitive ability at age 8) partially explained the association between job control and physical functioning, but did not explain the association between job demand and mental functioning. Conclusions Job demand and control in mid-life are differentially associated with mental and physical functioning in early old age and some of these associations may be partially explained by childhood factors. PMID:25319998