Author:
Joly-Burra Emilie,Cekic Sezen,Ghisletta Paolo
Abstract
AbstractIn many life-course research fields (e.g., sociology, psychology, economy, medicine, epidemiology) data often include repeated assessments of a variable and a dichotomous indicator of an event of interest. Such data naturally lend themselves to answering questions concerning the associations between individual trajectories and the occurrence and timing of discrete events. For instance, is one’s trajectory of health satisfaction spanning over dozens of years related to the risk of dying at a given age? Mixed-effect and survival models are well established to separately study such variables: mixed-effect models can conveniently be applied to characterize one’s trajectory, whereas survival models are ideally suited to study the risk of an event occurring. Joint longitudinal and survival models conveniently allow studying the associations between statistical characteristics of individual-based trajectories and individual survival features. In this chapter we first describe aspects of both longitudinal and survival models, to then discuss how the two can jointly be estimated, and thereby conditioned on each other, in joint models. We illustrate joint models on data from the publicly available Swiss Household Panel.
Funder
Swiss National Science Foundation
Publisher
Springer Nature Singapore
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