Joint models of dynamics of mothers’ stress and children’s disease

DOI10.1080/03610918.2018.1468455OpenAlexW2900307045WikidataQ128990010 ScholiaQ128990010MaRDI QIDQ5087551

Wenyaw Chan, Linda B. Piller, Xiaoying Yu, Michael D. Swartz

Publication date: 1 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1468455

zbMATH Keywords

joint modelcontinuous time Markov chainlongitudinal modelbivariate binary outcome

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05) Applications of continuous-time Markov processes on discrete state spaces (60J28)

Uses Software

• SAS
• PROC NLMIXED
• SAS/STAT

Cites Work

• Unnamed Item
• Models for discrete longitudinal data.
• A Conditional Markov Model for Clustered Progressive Multistate Processes under Incomplete Observation
• A Random Effects Transition Model For Longitudinal Binary Data With Informative Missingness
• Analysis of Longitudinal Multinomial Outcome Data
• Transition Models for Multivariate Longitudinal Binary Data
• Marginalized transition shared random effects models for longitudinal binary data with nonignorable dropout
• Marginalized transition random effect models for multivariate longitudinal binary data
• Markov transition models for binary repeated measures with ignorable and nonignorable missing values

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