| Summary: | 碩士 === 淡江大學 === 數學學系碩士班 === 100 === Covariate measurement error problem has been recently studied in the context of current status data (Wen, Huang, and Chen 2011; Wen and Chen 2012) but not yet for such data with an immune subgroup. Motivated by the diabetes dataset from the 2005 National Health Interview Survey of Taiwan, where the occurrence time of diabetes was current status censored, covariate Body Mass Index was measured with error, and a fraction of participants seemed immune from diabetes, we develop a conditional score method under the proportional odds cure model for analyzing partially immune current status data with mismeasured covariates. The conditional score approach makes no distribu-
tional assumption on the error-prone covariate and hence enjoys wide application. We evaluate the proposed method through simulation studies and illustrate it with the diabetes data.
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