Quantitative genetic analysis of IQ development in young children: multivariate multiple regression with orthogonal polynomials.
The study of psychological development has recently benefited from innovative analytic methods for estimating and examining the correlates of individual growth curves. These methods are more consistent with a conceptualization of development as an ongoing, continuous process, rather than as increases or decreases in a trait between two discrete time points. Recent developmental behavior genetic models have focused on continuity and change in the genetic and environmental influences underlying phenotypes. In contrast, we present a model for genetic and environmental influences on phenotypic development per se. In this model, we adapted multiple regression methods developed for twin designs (DeFries and Fulker, 1985) to a parent-offspring adoption design and to a multivariate framework in which repeated measurements are decomposed into orthogonal polynomial trends. We applied these analyses to the development of IQ during infancy and early childhood using parent-offspring data from adoptive and nonadoptive families in the Colorado Adoption Project. The results suggested familial environmental influences on children's mean IQ for ages 1-4 but environmental influences specific to fathers' cognitive ability on children's IQ development. We also discuss advantages and disadvantages of the multivariate multiple regression method for studying genetic and environmental influences on development.
Waldman
I D
ID
Department of Psychology, University of Minnesota, Minneapolis 55455.
DeFries
J C
JC
Fulker
D W
DW
D000300:Adoption; D002657:Child Development; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D007360:Intelligence / Q000235:genetics*; D008137:Longitudinal Studies; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D009483:Neuropsychological Tests; D010641:Phenotype; D012931:Social Environment