There is little question that most psychosocial interventions used to treat alcohol abuse and dependence are delivered in a group therapy format. In many settings, therapy groups are sustained and replenished using open enrollment, or """"""""rolling"""""""" admission, whereby patients enter ongoing therapy groups at various times, while other members leave (due to graduation or dropout). This process of session-to-session change in therapy group membership over time (usually occurring in a nonrandom fashion) creates unique analytic challenges for investigators who wish to account for and understand the dependencies created by open enrollment into therapy groups and for the proper modeling of treatment effects in this context. Difficulties in handling session-to-session changes in group membership in the analysis of alcohol treatment trial data have been cited as one of the major reasons that many investigators avoid the analytic challenges of open enrollment data. To avoid these difficulties, investigators have (a) ignored dependencies created by rolling treatment groups (leading to biased parameter estimation and/or standard errors), (b) designed studies that center on individual-based interventions (as opposed to groups), or (c) designed studies that restrict enrollment after a certain period (i.e., """"""""closed"""""""" groups). The major costs of each of these three approaches are incorrect inferences concerning treatment effects (i.e., Type I and/or Type II errors) (under condition [a]) and a disconnect between how treatment efficacy trials are conducted and how treatment takes place in community settings (under conditions [b] and [c]). ? ? In the face of many of these analytic and design challenges, further development and dissemination of approaches to handle open enrollment data in the context of alcohol treatment trials (i.e., multiple membership models, pattern mixture models) are sorely needed. The purpose of this exploratory- developmental R21 project is to explore the utility of analytic frameworks that may serve as the foundation for handling open enrollment data for three specific design and/or analytic problems: ? (a) incorporation into common alcohol treatment trial designs, (b) modeling of mechanisms of treatment action in trials with open enrollment, and (c) statistical power analysis for various group-based alcohol treatment designs (e.g., group-based tx A versus group-based tx B, group tx versus individual tx) under open enrollment. This exploratory/developmental grant application will use a combination of statistical simulation modeling and data from an ongoing alcohol treatment trial with the ultimate goal of providing alcohol treatment researchers with clear pedagogical examples on how to analyze such data and providing guidelines for sample size estimation specifically for open enrollment trial designs. ? ? ?
