We fitted all four models adjusted for age at interview to raw ordinal data using Mx (Version 1.66b) (33) using the total number of abuse symptoms as our outcome measure. Model 1, which has the most parameters, was compared to the nested Models 2, 3 and 4 using a likelihood ratio chi-square statistic in which the degrees of freedom equal the difference between the degrees of freedom between the full and nested sub models. Sample size adjusted Bayesian Information Criterion (BIC) was also used as an index of fit and parsimony (35) to judge the best fitting model.
