Statistical issues in survival analysis (Part XI)
July 19, 2023 The authors, Ning et al, have proposed what they refer to as a “broad class” of “so called” CoxAalen transformation models which have elements of both multiplicative and additive covariate effects on the baseline hazard function contained within the transformation. Originally, the Cox proporiotnal hazards regression model and the Aalen additive model were separate, but over the years, an attempt to incorporate the models has been studied, hence the Cox-Aalen model. In terms of the transformation models, the authors refer speciically to Zeng and Lin’s model (2006) to avoid confusion which they used a non-parametric maximum likelihood estimator in presence of right censoring and developed a system of equations for jumps of the baseline cumulative hazard function at exact failure times through an EM algorithm. Their approach though assumed the covariate effects were multiplicative. In addition, though EM-type algorithms existed for finding the NPMLE of semiparamtric transformation models, Elashoff ad Ryan (2004) propsed an expectation-solving (ES) algorithm to handle missing data for general estimating equations.