Childhood aggression and the co-occurrence of behavioural and emotional problems

Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychop

Viewing Spearman's Hypothesis from the perspective of multi-group PCA: A comment on Schonemann's criticism

A. R. Jensen's (1985) test of Spearman's hypothesis is meant to demonstrate the importance of general intelligence in Black-White (B-W) differences in psychometric intelligence test scores. P. H. Schoenemann (1989) purports to demonstrate, through an analysis of real and simulated data and the presentation of a theorem, that Spearman correlations are artifacts. The present article discusses the theorem and concludes that the theorem cannot be advanced in support of the contention that Spearman correlations are positive and substantial by mathematical necessity. The theorem encompasses a multigroup principal component analysis (PCA), which is a viable model to investigate Jensen's proposition that Blacks and Whites differ mainly with respect to g. The authors view Schoenemann's simulation study in the light of the multigroup PCA model, and interpret it as a study of the specificity of Spearman correlations, given model violations. Based on recent studies, it is concluded that the Spearman correlation is a suboptimal test of Spearman's hypothesis, and it is contended that an explicit model-based approach should be used

Multivariate Genetic Analyses in Heterogeneous Populations

Martin and Eaves (Heredity 38(1):79-95, 1977) proposed a multivariate model for twin and family data in order to investigate potential differences in the genetic and environmental architecture of multivariate phenotypes. The general form of the model is the independent pathway model, which differentiates between genetic and environmental influences at the item level, and therefore permits the decomposition to differ across items. A restricted version is the common pathway model, where the decomposition takes place at the factor level. The paper has spurred numerous studies, and evidence for differences in genetic and environmental architecture has been established for personality and several other psychiatric phenotypes by showing a better fit of the independent pathway model compared to the common pathway model. We show that genome-wide association studies (GWAS) that use an aggregate score computed from multiple questionnaire items as a univariate phenotype implicitly assume a similar structure as the common pathway model. It has been shown that in case of a differential genetic and environmental architecture, multivariate GWAS methods can outperform the univariate GWAS approach. However, current multivariate methods rely on the assumptions of phenotypic and genetic homogeneity, that is, item responses are assumed to have the same means and covariances, and genetic effects are assumed to be the same for all subjects. We describe a distance-based regression technique that is designed to account for subgroups in the population, and that therefore can account for differential genetic effects. A first evaluation with simulated data shows a substantial increase of power compared to univariate GWAS. © 2014 Springer Science+Business Media New York