TY - JOUR T1 - On the potential of discrete time survival analysis using latent variable modeling: An application to the study of the vascular depression hypothesis JF - Structural Equation Modeling: A Multidisciplinary Journal Y1 - 2017 A1 - Raykov, Tenko A1 - Gorelick, Philip B. A1 - Zajacova, Anna A1 - Marcoulides, George A. KW - Depressive symptoms KW - Survey Methodology AB - Analysis and modeling of time to event data have been traditionally associated with nonparametric, semiparametric, or parametric statistical frameworks. Recent advances in latent variable modeling have additionally provided unique analytic opportunities to methodologists and substantive researchers interested in survival time modeling. As a consequence, discrete time survival analyses can now be readily carried out using latent variable modeling, an approach that offers substantively important extensions to conventional survival models. Using data from the Health and Retirement Study, the discussed approach is applied to the study of the increasingly prominent vascular depression hypothesis in gerontology, geriatrics, and aging research, allowing examination of the unique predictive power of depression with respect to time to stroke in middle-aged and older adults. UR - https://www.tandfonline.com/doi/full/10.1080/10705511.2017.1315305https://www.tandfonline.com/doi/pdf/10.1080/10705511.2017.1315305 JO - Structural Equation Modeling: A Multidisciplinary Journal ER -