  We propose a new method for the analysis of competing risks data with long
term survivors. The proposed method enables us to estimate the overall survival
probability and cure fraction simultaneously. We formulate the effect of
covariates on cumulative incidence functions using linear transformation
models. Estimating equations based on counting process are developed to
estimate regression coefficients. The asymptotic properties of the estimators
are studied using martingale theory. An extensive Monte Carlo simulation study
is carried out to assess the finite sample performance of the proposed
estimators. Finally, we illustrate our method using a real data set.
