B1582
Title: Efficient designs and analysis of two-phase studies with longitudinal binary data
Authors: Ran Tao - Vanderbilt University Medical Center (United States) [presenting]
Abstract: Researchers interested in understanding the relationship between a readily available longitudinal binary outcome and a novel biomarker exposure can be confronted with ascertainment costs that limit sample size. In such settings, two-phase studies can be cost-effective solutions that allow researchers to target informative individuals for exposure ascertainment and increase estimation precision for time-varying and/or time-fixed exposure coefficients. A novel class of residual-dependent sampling (RDS) designs is introduced that select informative individuals using data available on the longitudinal outcome and inexpensive covariates. A semiparametric analysis approach is proposed with the RDS designs that efficiently uses all data to estimate the parameters. A numerically stable and computationally efficient EM algorithm is described to maximize the semiparametric likelihood. The finite sample operating characteristics of the proposed approaches through extensive simulation studies are examined and the efficiency of the designs and analysis approach is compared with existing ones. The usefulness of the proposed RDS designs and analysis method is illustrated in practice by studying the association between a genetic marker and poor lung function among patients enrolled in the lung health study.
