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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/58690


    Title: Analysis of Current Status Data with Missing Covariates
    Authors: Wen, Chi-Chung;Lin, Chien-Tai
    Contributors: 淡江大學數學學系
    Keywords: PH model;Profile likelihood;Semiparametric maximum likelihood estimate
    Date: 2011-09
    Issue Date: 2011-10-01 21:03:35 (UTC+8)
    Publisher: Chichester: Wiley-Blackwell Publishing Ltd.
    Abstract: Statistical inference based on right-censored data for the proportional hazards (PH) model with missing covariates has received considerable attention, but interval-censored or current status data with missing covariates has not yet been investigated. Our study is partly motivated by the analysis of fracture data from the 2005 National Health Interview Survey Original Database in Taiwan, where the occurrence of fractures was interval censored and the covariate osteoporosis was not reported for all residents. We assume that the data are realized from a PH model. A semiparametric maximum likelihood estimate implemented by a hybrid algorithm is proposed to analyze current status data with missing covariates. A comparison of the performance of our method with full-cohort analysis, complete-case analysis, and surrogate analysis is made via simulation with moderate sample sizes. The fracture data are then analyzed.
    Relation: Biometrics 67(3), pp.760–769
    DOI: 10.1111/j.1541-0420.2010.01505.x
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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