Weighted proportional mean inactivity time model

Abstract

In this paper, a mean inactivity time frailty model is considered. Examples are given to calculate the mean inactivity time for several reputable survival models. The dependence structure between the population variable and the frailty variable is characterized. The classical weighted proportional mean inactivity time model is considered as a special case. We prove that several well-known stochastic orderings between two frailties are preserved for the response variables under the weighted proportional mean inactivity time model. We apply this model on a real data set and also perform a simulation study to examine the accuracy of the model.

Keywords

• mixture
• likelihood ratio order
• hazard rate order
• reversed hazard rate order
• mean inactivity time order
• increasing concave order