This paper applies new statistical procedures for analyzing multiple-source information about the relation of psychiatric diagnoses to mortality. The data come from the Stirling County Study, a longitudinal community investigation of adults, that collected multiple-source reports (self-report and physician-report) about psychiatric disorders. These reports are used as predictors of mortality risk over a 16-year follow-up period (1952-1968). Despite extensive efforts, one or both of these reports were sometimes missing. Missingness of self-report was related to demographic characteristics as well as to physician-reports of psychiatric diagnosis. The statistical procedures used here draw together into a single frame of reference both informant reports for the initial Stirling survey and relate these to mortality risk using weighted generalized estimating equation regression models for time to event data. This unified method has two advantages over traditional approaches: 1) the relative predictiveness of each informant can be assessed and 2) all subjects contribute to the analysis. The methods are applicable to other areas of epidemiology where multiple informant reports are used. The results for self-reports and physician-reports of disorders were comparable: Psychiatric diagnosis was associated with higher mortality, particularly among younger subjects.