A longitudinal behavior genetic model for ordered categorical variables
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A model for the analysis of longitudinal twin data consisting of ordered categorical variables was proposed. Proportional changes in response categories across time were modeled within growth curve by means of mean and variance changes in underlying continuous variables. Variances of the growth factors were decomposed into genetic and environmental components. In simulation analyses, parameters were successfully estimated in all conditions although estimates of standard errors were biased and statistical powers to detect non-zero parameters were not sufficient for some parameters. A potential solution for these irregularities was discussed. Despite these limitations, the relative contributions of genetic and environmental components on growth factors were well estimated. Possible refinement of simulation analysis and expansion of the proposed model for multiple indicators at each measurement occasion were discussed.
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