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We propose a new method for the analysis of competing risks data with longterm survivors. The proposed method enables us to estimate the overall survivalprobability and cure fraction simultaneously. We formulate the effect ofcovariates on cumulative incidence functions using linear transformationmodels. Estimating equations based on counting process are developed toestimate regression coefficients. The asymptotic properties of the estimatorsare studied using martingale theory. An extensive Monte Carlo simulation studyis carried out to assess the finite sample performance of the proposedestimators. Finally, we illustrate our method using a real data set.

Semiparametric transformation model for competing risks data with cure fraction