Functional clustering methods for binary longitudinal data with temporal heterogeneity

• Published in: Computational statistics & data analysis Vol. 185; p. 107766
• Main Authors: Sohn, Jinwon, Jeong, Seonghyun, Cho, Young Min, Park, Taeyoung
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2023
• Subjects: data analysis; Dirichlet process; Longitudinal data; Partial collapsed Gibbs sampler; Probit mixed models; statistics; Varying-coefficients; Dirichlet process; Longitudinal data; Partial collapsed Gibbs sampler; Varying-coefficients; Probit mixed models

In the analysis of binary longitudinal data, it is of interest to model a dynamic relationship between a response and covariates as a function of time, while also investigating similar patterns of time-dependent interactions. We present a novel generalized varying-coefficient model that accounts for...