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

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

Research output: Contribution to journalArticle

Abstract

We propose two types of joint two-state continuous time Markov models using shared random effect(s). A simulation study is conducted to evaluate the performance of the parameter estimations under various scenarios and to compare each type of joint model approach to the separate model approach. The proposed method is applied to the Mothers’ Stress and Children’s Morbidity study. The concept of the transition odds ratio is introduced to illustrate the association between two continuous time Markov chains over time. We find that the proposed method is more efficient in estimating parameters of interest.

Original languageEnglish (US)
JournalCommunications in Statistics: Simulation and Computation
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Joint Model
Morbidity
Continuous-time Model
Continuous-time Markov Chain
Odds Ratio
Random Effects
Markov Model
Parameter Estimation
Simulation Study
Parameter estimation
Scenarios
Markov processes
Evaluate
Model
Concepts

Keywords

  • 60J28
  • 62F09
  • 62G34
  • 62M05
  • 62P10
  • Bivariate binary outcome
  • Continuous time Markov chain
  • Joint model
  • Longitudinal model

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation

Cite this

Joint models of dynamics of mothers’ stress and children’s disease. / Yu, Xiaoying; Chan, Wenyaw; Swartz, Michael D.; Piller, Linda B.

In: Communications in Statistics: Simulation and Computation, 01.01.2018.

Research output: Contribution to journalArticle

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