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Statistica Sinica 30 (2020), 1117-1134

REGRESSION ANALYSIS OF MULTIVARIATE
CURRENT STATUS DATA WITH SEMIPARAMETRIC
TRANSFORMATION FRAILTY MODELS
Shuwei Li, Tao Hu, Shishun Zhao and Jianguo Sun
Guangzhou University, Capital Normal University,
Jilin University and University of Missouri

Abstract: This study investigates regression analysis of multivariate current status data using a class of flexible semiparametric transformation frailty models. The maximum likelihood estimation procedure is derived for the problem. In particular, a novel EM algorithm, which is quite stable and can be easily implemented, is developed. In addition, the asymptotic properties of the resulting estimators are established, and a numerical study indicates that the proposed methodology works well in practical situations. An application is provided to llustrate the proposed method.

Key words and phrases: EM algorithm, multivariate current status data, semiparametric efficiency, transformation frailty models.

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