A flexible cure rate model based on the polylogarithm distribution

Models for dealing with survival data in the presence of a cured fraction of individuals have attracted the attention of many researchers and practitioners in recent years. In this paper, we propose a cure rate model under the competing risks scenario. For the number of causes that can lead to the event of interest, we assume the polylogarithm distribution. The model is flexible in the sense it encompasses some well-known models, which can be tested using large sample test statistics applied to nested models. Maximum-likelihood estimation based on the EM algorithm and hypothesis testing are investigated. Results of simulation studies designed to gauge the performance of the estimation method and of two test statistics are reported. The methodology is applied in the analysis of a data set.