Statistical analysis of heaped duration data

Abstract

This paper shows how heaping of duration data eg caused by rounding due to memory eects can be analyzed If the data are heaped Coxs partial likelihood approach which is often used in survival analysis is no longer appropriate We show how this problem can be overcome by considering the problem as a missing data problem A variant of Coxs Proportional Hazard Model is constructed that takes heaping into account and is estimated by maximum likelihood using the EM algorithm with many nuisance parameters simultaneously for all parameters Ingredients of our method are application of the EM algorithm Cox regression and nonparametric maximumlikelihood calculation with predicted data in each M step An example from practice where jackknife is used to estimate the variances illustrates the power of the new methodology