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Andishe 2021, 26(1): 71-87 Back to browse issues page
A review on latent class models for joint modeling of longitudinal measurements and survival data
Taban Baghfalaki *, Parvaneh Mehdizadeh, Mahdy Esmailian
Tarbiat Modares University
Abstract:   (867 Views)
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.
Keywords: Competing risks, EM Algorithm, Joint latent class model, Longitudinal measurements, Maximum likelihood estimator, Survival model.
Full-Text [PDF 330 kb]   (279 Downloads)    
Type of Study: Research | Subject: General
Received: 2021/09/4 | Accepted: 2021/11/22 | Published: 2021/12/1
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Baghfalaki T, Mehdizadeh P, Esmailian M. A review on latent class models for joint modeling of longitudinal measurements and survival data. Andishe. 2021; 26 (1) :71-87
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Volume 26, Issue 1 (12-2021) Back to browse issues page
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