RT - Journal Article T1 - A review on latent class models for joint modeling of longitudinal measurements and survival data JF - Andishe-_ye-Amari YR - 2021 JO - Andishe-_ye-Amari VO - 26 IS - 1 UR - http://andisheyeamari.irstat.ir/article-1-869-en.html SP - 71 EP - 87 K1 - Competing risks K1 - EM Algorithm K1 - Joint latent class model K1 - Longitudinal measurements K1 - Maximum likelihood estimator K1 - Survival model. AB - Joint models use in follow-up studies to investigate the relationship between longitudinal markers and survival outcomes and have been generalized to multiple markers or competing risks data. Many statistical achievements in the field of joint modeling focuse on shared random effects models which include characteristics of longitudinal markers as explanatory variables in the survival model. A less-known approach is the joint latent class model, assuming that a latent class structure fully captures the relationship between the longitudinal marker and the event risk. The latent class model may be appropriate because of the flexibility in modeling the relationship between the longitudinal marker and the time of event, as well as the ability to include explanatory variables, especially for predictive problems. In this paper, we provide an overview of the joint latent class model and its generalizations. In this regard, first a review of the discussed models is introduced and then the estimation of the model parameters is discussed. In the application section, two real data sets are analyzed. LA eng UL http://andisheyeamari.irstat.ir/article-1-869-en.html M3 ER -