Inverse probability weightedmethod for current status data with missing status indicator

• Main Authors: Tzu-Jung Wang, 王姿蓉
• Other Authors: Chi-Chung Wen
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/7xkbk9

碩士 === 淡江大學 === 數學學系碩士班 === 102 === Current status data are commonly encountered in demographic or biomedical studies, in which the observation consists of an examination time and a status indicator for whether or not the event of interest has occurred by the examination time. In this thesis, we propose an inverse probability weighted method for analyzing current status data where the status indicator is subject to missing but a surrogate for status indictor is available instead. Our method is based on the proportional hazards survival model and missing at random mechanism. Simulation results confirm that the proposed estimator is asymptotically normal and it removes the bias resulted from the naive “complete case” analysis discarding subjects with missing value. Besides we illustrate our proposal by analyzing an osteoporosis survey data.