Date created: | Last Updated:

Category: Project

Description: Family health history (FHH) inherently involves collecting proxy reports of health statuses of related family members. Traditionally, such information has been collected from a single informant. More recently, research has suggested that a multiple in- formant approach to collecting FHH results in improved individual risk assessments. Likewise, recent work has emphasized the importance of incorporating health-related behaviors into FHH based risk calculations. Integrating both multiple accounts of FHH with behavioral information on family members represents a significant methodological challenge as such FHH data is hierarchical in nature and arises from potentially error-prone processes. In this paper, we introduce a statistical model that addresses that challenges using informative priors for background variation in disease prevalence and the effect of other, potentially correlated, variables jointly with handling the hierarchical structure nesting multiple FHH accounts into families. Our empirical example is drawn from previously published data on families with a history of diabetes. The results of the model assessment suggest that simply accounting for the structured na- ture of multiple informant FHH data improves classification accuracy over the baseline and that incorporating family member health-related behavioral information into the model is preferred over alternative specifications