Literature DB >> 8192617

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

C V Dolan1, P C Molenaar, D I Boomsma.   

Abstract

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.

Mesh:

Year:  1994        PMID: 8192617     DOI: 10.1007/bf01067925

Source DB:  PubMed          Journal:  Behav Genet        ISSN: 0001-8244            Impact factor:   2.805


  9 in total

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

Authors:  C V Dolan; P C Molenaar; D I Boomsma
Journal:  Behav Genet       Date:  1991-01       Impact factor: 2.805

2.  Testing Specific Hypotheses Concerning Latent Group Differences in Multi-group Covariance Structure Analysis with Structured Means.

Authors:  C V Dolan; P C Molenaar
Journal:  Multivariate Behav Res       Date:  1994-07-01       Impact factor: 5.923

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

Authors:  C V Dolan; P C Molenaar; D I Boomsma
Journal:  Behav Genet       Date:  1992-05       Impact factor: 2.805

4.  Estimation of individual genetic and environmental factor scores.

Authors:  D I Boomsma; P C Molenaar; J F Orlebeke
Journal:  Genet Epidemiol       Date:  1990       Impact factor: 2.135

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

Authors:  P C Molenaar; D I Boomsma; D Neeleman; C V Dolan
Journal:  Genet Epidemiol       Date:  1990       Impact factor: 2.135

6.  Testing structural equation models for twin data using LISREL.

Authors:  A C Heath; M C Neale; J K Hewitt; L J Eaves; D W Fulker
Journal:  Behav Genet       Date:  1989-01       Impact factor: 2.805

7.  Bias in correlations from selected samples of relatives: the effects of soft selection.

Authors:  M C Neale; L J Eaves; K S Kendler; J K Hewitt
Journal:  Behav Genet       Date:  1989-03       Impact factor: 2.805

8.  The genetical analysis of covariance structure.

Authors:  N G Martin; L J Eaves
Journal:  Heredity (Edinb)       Date:  1977-02       Impact factor: 3.821

9.  Application of nonlinear factor analysis to genotype-environment interaction.

Authors:  P C Molenaar; D I Boomsma
Journal:  Behav Genet       Date:  1987-01       Impact factor: 2.805

  9 in total
  2 in total

1.  Racial differences in birth health risk: a quantitative genetic approach.

Authors:  E J van den Oord; D C Rowe
Journal:  Demography       Date:  2000-08

2.  Notes on Three Decades of Methodology Workshops.

Authors:  Hermine H Maes
Journal:  Behav Genet       Date:  2021-02-14       Impact factor: 2.805

  2 in total

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