Results 251 to 260 of about 328,309 (265)

Genetic and environmental influences on covariation in reproducible diet–metabolite associations

The American Journal of Clinical Nutrition, 2021
Early applications of metabolomics in nutrition and health research identified associations between dietary patterns and metabolomic profiles. Twin studies show that diet-related phenotypes and diet-associated metabolites are influenced by genes.
Kate M Bermingham, Lorraine Brennan, Ricardo Segurado, Rebecca E Barron, Eileen R Gibney, Miriam F Ryan, Michael J Gibney, Aifric M O’Sullivan   +7 more
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Sex steroids at birth: Genetic and environmental variation and covariation

Developmental Psychobiology, 1991
AbstractThree sex‐steroids (estradiol, progesterone, & testosterone) were assayed from the umbilical cord blood of 58 same‐sex twin pairs in an investigation of the effects of sex, as well as genetic and environmental factors, on neonatal hormone levels.
L M, Sakai, L A, Baker, C N, Jacklin, I, Shulman   +3 more
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Analysis of Spatial Covariance Structure for Environmental Data

2005
Formulation and evaluation of environmental policy depend upon a general class of latent variable models known as multivariate receptor models. Estimation of the number of pollution sources, the source composition profiles and the source contributions are the main interests in multivariate receptor modelling.
A. Lamberti, NISSI, Eugenia
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Model-driven development of covariances for spatiotemporal environmental health assessment

Environmental Monitoring and Assessment, 2012
Known conceptual and technical limitations of mainstream environmental health data analysis have directed research to new avenues. The goal is to deal more efficiently with the inherent uncertainty and composite space-time heterogeneity of key attributes, account for multi-sourced knowledge bases (health models, survey data, empirical relationships etc.
Alexander, Kolovos, José Miguel, Angulo, Konstantinos, Modis, George, Papantonopoulos, Jin-Feng, Wang, George, Christakos   +5 more
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Cormack–Jolly–Seber model with environmental covariates: A P‐spline approach

Biometrical Journal, 2012
In capture–recapture models, survival and capture probabilities can be modelled as functions of time‐varying covariates, such as temperature or rainfall. The Cormack–Jolly–Seber (CJS) model allows for flexible modelling of these covariates; however, the functional relationship may not be linear.
Stoklosa, Jakub, Huggins, Richard M.
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Distribution and variance/covariance structure of pesticide environmental fate data

Environmental Toxicology and Chemistry, 2008
Abstract Hydrophobicity, persistence, and volatility data for individual pesticides are widely used in risk assessment and transport modeling, so it is important to understand their distribution, variation, and covariation. Correlations (normalized covariance) among properties across a range of multiple pesticides are also important for ...
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MAXIMUM VARIANCE LINEAR COMBINATIONS FROM PHENOTYPIC, GENETIC, AND ENVIRONMENTAL COVARIANCE MATRICES

Multivariate Behavioral Research, 1970
Vectors of weights derived from principal components analysis of stan- dardized phenotypic, genetic, and environmental covariance matrices were applied to open-field behavioral scores from mice in order to obtain composite scores with maximum phenotypic (Vp), genetic (Va), and environmental (Ve)variance, respectively.
J P, Hegmann, J C, DeFries
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Candidate‐gene association studies with pedigree data: Controlling for environmental covariates

Genetic Epidemiology, 2003
AbstractCase‐control studies provide an important epidemiological tool to evaluate candidate genes. There are many different study designs available. We focus on a more recently proposed design, which we call a multiplex case‐control (MCC) design. This design compares allele frequencies between related cases, each of whom are sampled from multiplex ...
S L, Slager, D J, Schaid, L, Wang, S N, Thibodeau   +3 more
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Reduced Rank Covariances for the Analysis of Environmental Data

2011
In this work we propose a Monte Carlo estimator for non stationary covariances of large incomplete lattice or irregularly distributed data. In particular, we propose a method called “reduced rank covariance” (RRC), based on the multiresolution approach for reducing the dimensionality of the spatial covariances.
Orietta Nicolis, Doug Nychka
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The spatial analysis of covariates in a study of environmental epidemiology

Statistics in Medicine, 1995
AbstractKanawha County, West Virginia, includes a deep river valley with a large population living in close proximity to many chemical manufacturing centres. One study of this area combined an epidemiologic survey of children attending Kanawha County schools with the measurement of the concentrations of 15 volatile organic compounds at each of the 75 ...
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