Properties of the Estimators for Additive-Accelerated Hazard Ratio Model

Recurrent events gap time is the time difference between two adjacent failures of recurrent events. In this paper, an additive-accelerated hazard ratio model is presented for multiple type recurrent events gap time data, and the estimation methods of unknown parameter and non-parameter function is given. Moreover, the asymptotic properties of estimators are proved.

Additive-Accelerated Hazard Ratio Model for Multiple Type Recurrent Events Gap Time

Multiple type recurrent event data is often observed in clinical medicine, epidemiology, biostatistics, and other related applied research fields. This paper presents an additive-accelerated hazard ratio model for multiple type recurrent events data, and gives the estimation methods of unknown parameter and non-parameter function based on the idea of estimating equation. In addition, it provides the expression of unknown regression coefficient as well as the benchmark hazard ratio function.

Study on Asymptotic Property of Additive-Accelerated Mean Regression Model

Recurrent event data is a kind of important incomplete data existed in survival analysis, biological medicine research, reliability life test and other practical problems. This paper presents an additive-accelerated mean regression model for multiple type recurrent events data, and gives the estimation methods of unknown parameter and non-parameter function. Specially, the asymptotic properties of parameters estimation are proved.

Additive-Accelerated Mean Regression Model for Multiple Type Recurrent Events

Recurrent events data is often observed in applied research fields like biostatistics, clinical experiment, and so on. In this paper, an additive-accelerated mean regression model is established for multiple type recurrent events data, and the estimation methods of unknown parameter and non-parameter function based on the idea of estimating equation are given.