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A shared parameter model for the estimation of longitudinal concomitant intervention effects
Colin O Wu1, Xin Tian, Wenhua Jiang
1Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA. wuc@nhlbi.nih.gov
Abstract:
We investigate a change-point approach for modeling and estimating the regression effects caused by a concomitant intervention in a longitudinal study. Since a concomitant intervention is often introduced when a patient's health status exhibits undesirable trends, statistical models without properly incorporating the intervention and its starting time may lead to biased estimates of the intervention effects. We propose a shared parameter change-point model to evaluate the pre- and postintervention time trends of the response and develop a likelihood-based method for estimating the intervention effects and other parameters. Application and statistical properties of our method are demonstrated through a longitudinal clinical trial in depression and heart disease and a simulation study.
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