title: A missing composite covariate in survival analysis: a case study of the Chinese Longitudinal Health and Longevity Survey.
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 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 the 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. Estimates are obtained by an E-M-type algorithm that reduces to the iterative maximization of three complete log-likelihood functions derived from two augmented data sets 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.
authors.affiliation: Department of Public Institutions, Economy and Society, University of Roma Tre, Via G. Chiabrera 199, 00145 Rome, Italy. lagona@uniroma3.it
authors.forename: Francesco
authors.initials: F
authors.lastname: Lagona
authors.forename: Zhen
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000369:Aged, 80 and over; D000465:Algorithms; D002681:China; D003072:Cognition Disorders / Q000175:diagnosis; D015340:Epidemiologic Research Design; D005260:Female; D006306:Health Surveys; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D016015:Logistic Models; D008136:Longevity; D008137:Longitudinal Studies; D008297:Male; D008603:Mental Health / Q000706:statistics & numerical data*; D008609:Mental Status Schedule; D016016:Proportional Hazards Models; D012306:Risk; D012737:Sex Factors; D011795:Surveys and Questionnaires; D016019:Survival Analysis