Abstract:
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Longitudinal data are widely available for research purposes using pre-existing data warehouses (e.g., cohort studies, administrative databases, electronic medical records). In this roundtable, I will lead a discussion regarding opportunities and considerations for conducting cost-efficient retrospective sub-studies to address longitudinal data analysis questions. Often, most of the data required to address such questions are contained in these rich resources; however, one or several key exposure variables must still be ascertained. The primary challenge is that exposure ascertainment is expensive and limits the sample size of the sub-study. Strategies for targeting the sampling scheme toward the most informative subjects will be discussed; analysis procedures for valid inferences will be described; and handouts will be provided that will include, among other material, URLs for references and software.
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