A semiparametric proportional odds regression model for the analysis of current status data

An approach to covariate analysis of current status data is described. The method is applicable when the logit of the conditional probability of survival given the covariates is some increasing function of time plus a linear combination of the covariates. The approach is based on approximating the infinite-dimensional nuisance parameter, the baseline log-odds of failure, with a step function, and carrying out a maximum likelihood procedure. The resulting finite dimensional parameter estimates for the regression parameters are shown to be asymptotically normal and semiparametric efficient. Numerical studies with small and moderate samples are discussed.