STATISTICAL-METHODS FOR ANALYSES OF INCOMPLETE CLINICAL SERVICE RECORDS - CONCURRENT USE OF LONGITUDINAL AND CROSS-SECTIONAL DATA

Statistical procedures that have become routine in other social scienc es were used to analyze data from clinical service records. Despite th e absence of control groups, nonrandom assignment of clients to treatm ent conditions, and incomplete records, effective analyses of psychoth erapeutic processes were possible. Multivariate regression models, wit h variables that were transformed to significantly improve skewness an d regression linearity, were controlled for heteroskedasticity and for end-point censoring of dependent variables. They were also used to me asure the effects of a categorical variable (gender) and a scalable va riable (intake distress) on a reactive outcome measure (of acute distr ess) and on an unreactive one (of long-term life satisfaction). Graphi cal methods for summarizing large data sets helped identify intake var iables that could control for attrition-related sampling biases. These longitudinal covariates and corrections to adjust degrees of freedom for cases with repeated measures were then used to construct statistic al models that were equivalents of pure cross-sectional designs.