Estimation of proportional odds model based on Stochastic EM algorithm under doubly interval censored data

The incubation period is one of the important indicators of epidemiology and disease progression research, which plays an important role in disease prevention, control and treatment. The incubation period is the gap time between the virus infection and the manifestation of symptoms, and both occurrence times may be censored, resulting in doubly interval censored data. In the study of doubly interval censored data, there are many studies that only consider the occurrence of right censoring or interval censoring in the subsequent time, and there are relatively few studies that consider the simultaneous existence of right censoring and interval censoring. In addition, most of the research methods are based on the Cox model. In this paper, a proportional odds model is established under the doubly interval censored data with both right censored and interval censored in the subsequent time, and the Stochastic EM algorithm is used to process the doubly interval censored data and perform maximum likelihood estimation. The performance of the proposed method under finite samples is evaluated through simulation studies, and then the AIDS data is analyzed by this method.