Statistical methods for the analysis of critical life events

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Abstract
Problems such as family disruption, mental illness, child abuse, and juvenile delinquency are often conceptualized as episodic events that define the success or failure of social intervention. This article examines the methodological problems associated with the analysis of event data by comparing five alternative statistical specifications: (1) multiple regression, (2) discriminant analysis, (3) logistic regression, (4) tobit regression, and (5) event history analysis. Each procedure is used to estimate risk factors for out-of-home placement among children in families that received intensive family preservation services. The accuracy and precision of models produced by each method are discussed. Implications for the analysis of event data are explored.

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