A missing composite covariate in survival analysis: a case study of the Chinese Longitudinal Health and Longevity Survey

Francesco Lagona and Zhen Zhang
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Francesco Lagona: Max Planck Institute for Demographic Research, Rostock, Germany
Zhen Zhang: Max Planck Institute for Demographic Research, Rostock, Germany

No WP-2008-022, MPIDR Working Papers from Max Planck Institute for Demographic Research, Rostock, Germany

Abstract: We estimate a Cox proportional hazards model where one of the covariates measures the level of a subject´s cognitive functioning by grading the total score obtained by the subject on the items of a questionnaire. A case study is presented where the sample includes partial respondents, who did not answer some or all of the questionnaire items. The total score takes hence the form of an interval-censored variable and, as a result, the level of cognitive functioning is missing on some subjects. We handle partial respondents by taking a likelihood-based approach where survival time is jointly modelled with the censored total score and the size of the censoring interval. Parameter estimates are obtained by an E-M-type algorithm that essentially reduces to the iterative maximization of three complete log-likelihood functions derived from two augmented datasets with case weights, alternated with weights updating. This methodology is exploited to assess the Mini Mental State Examination index as a prognostic factor of survival in a sample of Chinese older adults.

Keywords: China; health (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Pages: 9 pages
Date: 2008
New Economics Papers: this item is included in nep-cna and nep-hea
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Persistent link: https://EconPapers.repec.org/RePEc:dem:wpaper:wp-2008-022

DOI: 10.4054/MPIDR-WP-2008-022

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