The equivalence of regression models using difference scores and models using separate scores for each informant: implications for the study of informant discrepancies

Research on informant discrepancies has increasingly utilized difference scores. This article demonstrates the statistical equivalence of regression models using difference scores (raw or standardized) and regression models using separate scores for each informant to show that interpretations should be consistent with both models. First, regression equations were used to demonstrate that difference score models are equivalent to models using separate scores for each informant. Second, a hypothesis-driven empirical example (218 mother-child dyads, mean age = 11.5 years, 49% female participants, 49% White, 47% African American) was used to provide an illustration of the equivalence of the 2 models. Implications of the equivalence of models using difference scores and models using separate scores for each informant are discussed in terms of the growing prevalence of an interpretation in the literature of difference score analyses that is inconsistent with results from equivalent separate informant analyses. Differences in the separate predictive ability of informants should be acknowledged as an alternative interpretation of the difference score regression coefficient.