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Regression Analysis of Multivariate Current Status Data with Semiparametric Transformation Frailty Models

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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… Click to show full 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 illustrate the proposed method.

Keywords: status data; regression analysis; analysis multivariate; semiparametric transformation; current status; multivariate current

Journal Title: Statistica Sinica
Year Published: 2020

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