A PD criterion may predict cross-sectional AUD variance because of shared genetic factors or because of correlated environmental influences, and may or may not be predictive of future changes in individual differences. To better understand the underlying causal factors, (iii) we partitioned both cross-sectional and longitudinal associations between the selected PD criteria and AUD into their (additive) genetic and (shared and non-shared) environmental components using the biometric “ACE” model [41]. This is a structural equation model that partitions a between- and within-twin covariance matrix into additive genetic covariance (A), shared environmental covariance (C) that makes the twins similar with each other, and non-shared environmental covariance (E) that makes the twins different (E variance includes measurement error).
