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Biomedical subjects

C V Dolan

Publications and source records attributed to C V Dolan.

8 recordsLinked to original sources
PubMed1994

Simultaneous genetic analysis of means and covariance structure: Pearson-Lawley selection rules.

The object of this paper is to indicate that the Pearson-Lawley selection rules form a plausible general theory for the simultaneous genetic analysis of means and covariance structure. Models are presented based on phenotypic selection and latent selection. Previously presented quantitative genetic models to decompose means and covariance structure simultaneously are reconsidered as instances of latent selection. The selection rules are very useful in the context of behavior genetic modeling because they lead to testable models and a conceptual framework for explaining variation between and within groups by the same genetic and environmental factors.

Genotype↗
PubMed1993

A third source of developmental differences.

An illustrative list is presented of human and animal studies which each point to the existence of a third source, in addition to genetic and environmental factors, underlying phenotypic differences in development. It is argued that this third source may consist of nonlinear epigenetic processes that can create variability at all phenotypical-somatic and behavioral-levels. In a quantitative genetic analysis with human subjects, these processes are confounded with within-family environmental influences. A preliminary model to quantify these influences is introduced.

Animals↗
PubMed1992

Decomposition of multivariate phenotypic means in multigroup genetic covariance structure analysis.

Observed differences in phenotypic means between groups such as parents and their offspring or male and female twins can be decomposed into genetic and environmental components. The decomposition is based on the assumption that the difference in phenotypic means is due to a difference in the location of the normal genetic and environmental distributions underlying the phenotypic individual differences. Differences between the groups in variance can be accommodated insofar as they are due to differences in unique variance or can be modeled using a scale parameter. The decomposition may be carried out in the standard analysis of genetic covariance structure using, for instance, LISREL. Illustrations are given using simulated data and twin data relating to blood pressure. Other possible applications are mentioned.

Blood Pressure↗
PubMed1991

Estimation of individual genetic and environmental profiles in longitudinal designs.

Parameter estimates obtained in the genetic analysis of longitudinal data can be used to construct individual genetic and environmental profiles across time. Such individual profiles enable the attribution of individual phenotypic change to changes in the underlying genetic or environmental processes and may lead to practical applications in genetic counseling and epidemiology. Simulations show that individual estimates of factor scores can be reliably obtained. Decomposition of univariate, and to a lesser extent of bivariate, phenotypic time series may yield estimates of independent individual G(t) and E(t), however, that are intercorrelated. The magnitude of these correlations depends somewhat on the autocorrelation structure of the underlying series, but to obtain completely independent estimates of genetic and environmental individual profiles, at least three measured indicators are needed at each point in time.

Humans↗
PubMed1991

Simultaneous genetic analysis of longitudinal means and covariance structure in the simplex model using twin data.

A longitudinal model based on the simplex model is presented to analyze simultaneously means and covariance structure using univariate longitudinal twin data. The objective of the model is to decompose the mean trend into components which can be attributed to those genetic and environmental factors which give rise to phenotypic individual differences and a component of unknown constitution which does not involve individual differences. Illustrations are given using simulated data and repeatedly measured weight obtained in a sample of 82 female twin pairs on six occasions.

Analysis of Variance↗
PubMed1990

Using factor scores to detect G X E interactive origin of "pure" genetic or environmental factors obtained in genetic covariance structure analysis.

Moment expressions for individual factor scores can serve as simple tests for the presence of a particular class of interaction factors that are disguised as pure genetic and/or environmental factors. That is, individual genetic and environmental factor scores may be used to construct fourth-order moments of these factors in order to test whether a common genetic or environmental factor in the multivariate genetic factor model is in fact of the interactive origin concerned. Expected fourth-order moments are derived for cases with and without interaction. Application of fourth-order moments of factor scores to detect interactive origin of common factors is illustrated with simulated twin data.

Environment↗
PubMed1989

LISREL analysis of twin data with structured means.

A method is introduced to test the hypothesis that both the phenotypic means and the phenotypic covariances can be modeled with the same common genetic and environmental factors. LISREL can be used to implement the method. An illustration is given with simulated twin data.

Computer Simulation↗