BIVARIATE LOGISTIC-REGRESSION ANALYSIS OF CHILDHOOD PSYCHOPATHOLOGY RATINGS USING MULTIPLE INFORMANTS

A central issue in studies of risk factors for childhood psychopathology is utilization of the information obtained about the child's mental health status from multiple informants, In this paper, the authors propose a new approach to the analysis of risk factor data when the outcomes are binary ratings (presence/absence of symptoms), This new approach has several attractive features in this setting, The strategy taken is to perform a single analysis using multivariate modeling, in which simultaneous logistic regressions are conducted for the outcomes given by each of several informants, The advantages of this approach include the following: 1) it retains the complete information about case status for each informant; 2) it permits assessment of informant-risk factor interactions as well as ''overall'' risk factor effects; 3) it provides measures of association between the multiple informants and adjusts for the association between responses in the analysis; and 4) missing data on a subset of respondents can be incorporated in a straightforward way, permitting all subjects with at least one informant to be used in the analysis, To illustrate the methods, the authors present findings on risk factors for measures of ''internalizing'' and ''Externalizing'' behaviors from two surveys using parent and teacher ratings of 6- to 11-year-old children in Connecticut between 1986 and 1989.