EM Algorithm and Likelihood Inference for Flexible Cure Rate Models with Weibull Lifetimes

• Activity Number: 309
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistical Computing
• Author(s): Suvra Pal*+ and Narayanaswamy Balakrishnan
• Companies: McMaster University and McMaster University
• Keywords: Cure rate models ; Conway-Maxwell Poisson distribution ; EM algorithm ; Profile likelihood ; Weibull distribution ; Maximum likelihood estimators

Abstract

Rodrigues et al. (2009) developed a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow the Conway-Maxwell Poisson distribution. This model includes some of the well-known cure rate models discussed in the literature as special cases. Data obtained from cancer clinical trials are often right censored and EM algorithm can be used in this case to efficiently estimate the model parameters based on right censored data. In this work, by assuming the time-to-event to follow the Weibull distribution, the necessary steps of the EM algorithm are derived for estimating the parameters of different cure rate survival models . The standard errors of the MLEs are obtained by inverting the observed information matrix. The method of inference developed here is examined by means of an extensive Monte Carlo simulation study. Finally, the proposed methodology is illustrated with a real data on cancer recurrence.