Published online by Cambridge University Press: 21 February 2012
Using longitudinal cross-lagged analysis to infer causal directions of reciprocal effects is one of the most important tools in the developmental armamentarium. The strength of these analyses can be enhanced by analyzing the genetic and environmental aetiology underlying cross-lagged relationships, for which we present a novel approach here. Our approach is based on standard Cholesky decomposition. Standardized path coefficients are employed to assess genetic and environmental contributions to cross-lagged associations. We indicate how our model differs importantly from another approach that does not in fact analyze genetic and environmental contributions to cross-lagged associations. As an illustration, we apply our approach to the analysis of the cross-lagged relationships between self-perceived abilities and school achievement from age 9 to age 12. Self-perceived abilities of 3852 pairs of twins from the UK Twins Early Development Study were assessed using a self-report scale. School achievement was assessed by teachers based on UK National Curriculum criteria. The key cross-lagged association between self-perceived abilities at age 9 and school achievement at age 12 was mediated by genetic influences (28%) as well as shared (55%) and non-shared (16%) environment. The reverse cross-lagged association from school achievement at 9 to self-perceived abilities at 12 was primarily genetically mediated (73%). Unlike the approach to cross-lagged genetic analysis used in recent research, our approach assesses genetic and environmental contributions to cross-lagged associations per se. We discuss implications of finding that genetic factors contribute to the cross-lag between self-perceived abilities at age 9 and school achievement at age 12.