title: Bayesian joint analysis of heterogeneous- and skewed-longitudinal data and a binary outcome, with application to AIDS clinical studies.
abstract: In medical studies, heterogeneous- and skewed-longitudinal data with mis-measured covariates are often observed together with a clinically important binary outcome. A finite mixture of joint models is currently used to fit heterogeneous-longitudinal data and binary outcome, in which these two parts are connected by the individual latent class membership. The skew distributions, such as skew-normal and skew-t, have shown beneficial in dealing with asymmetric data in various applications in literature. However, there has been relatively few studies concerning joint modeling of heterogeneous- and skewed-longitudinal data and a binary outcome. In this article, we propose a joint model in which a flexible finite mixture of nonlinear mixed-effects models with skew distributions is connected with binary logistic model by a latent class membership indicator. Simulation studies are conducted to assess the performance of the proposed models and method, and a real example from an AIDS clinical trial study illustrates the methodology by modeling the viral dynamics to compare potential models with different distribution specifications; the analysis results are reported.
authors.affiliation: 1 Department of Biostatistics, Medpace Inc., Cincinnati, OH, USA.
authors.forename: Xiaosun
authors.initials: X
authors.lastname: Lu
authors.affiliation: 2 Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, FL, USA.
authors.forename: Yangxin
authors.initials: Y
authors.lastname: Huang
authors.affiliation: 3 Department of Statistics, Wuhan University of Technology, Wuhan, Hubei, P.R. China.
authors.forename: Jiaqing
authors.initials: J
authors.lastname: Chen
authors.affiliation: 1 Department of Biostatistics, Medpace Inc., Cincinnati, OH, USA.
authors.forename: Rong
authors.initials: R
authors.lastname: Zhou
authors.affiliation: 1 Department of Biostatistics, Medpace Inc., Cincinnati, OH, USA.
authors.forename: Shuli
authors.initials: S
authors.lastname: Yu
authors.affiliation: 4 Department of Epidemiology and Biostatistics, School of Public Health, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China.
authors.forename: Ping
authors.initials: P
authors.lastname: Yin
mesh_terms: D000163:Acquired Immunodeficiency Syndrome; D001499:Bayes Theorem; D015982:Bias; D000068456:Clinical Studies as Topic / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D009010:Monte Carlo Method
keywords: AIDS clinical trials; Bayesian inference; longitudinal data analysis; mixture joint models; skew distributions