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文章基本信息

  • 标题:Covariate Dependent Markov Models for Analysis of Repeated Binary Outcomes
  • 本地全文:下载
  • 作者:Islam, M.A. ; Chowdhury, R.I. ; Singh, K.P.
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2007
  • 卷号:6
  • 期号:2
  • 页码:21
  • 出版社:Wayne State University
  • 摘要:The covariate dependence in a higher order Markov models is examined. First order Markov models with covariate dependence are discussed and are generalized for higher order. A simple alternative is also proposed. The estimation procedure is discussed for higher order with a number of covariates. The proposed model takes into account the past transitions. Transitions are fitted and are tested in order to examine their influence on the most recent transitions. Applications are illustrated using maternal morbidity during pregnancy. The binary outcome at each visit during pregnancy is observed for each subject and then the covariate dependent Markov models are fitted. The results indicate that the proposed model can be employed for analyzing repeated observations conveniently.
  • 关键词:Markov Models; higher order; covariate dependence; repeated observations; transitions
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