Censored count data regression with missing censoring information

We investigate estimation in Poisson regression model when the count response is right-censored and censoring indicators are missing at random. propose several estimators based on calibration, multiple imputation augmented inverse probability weighting methods. Under appropriate regularity conditions, we prove consistency of our derive their asymptotic distributions. Simulation experiments carried out to finite sample behaviour relative performance proposed estimates. These estimates illustrated a real data set.