Abstract
Although there are many suggested measures of explained variation for single-event survival data, there has been little attention to explained variation for recurrent event data. We describe an existing rank-based measure and we investigate a new statistic based on observed and expected event count processes. Both methods can be used for all models. Adjustments for missing data are proposed and demonstrated through simulation to be effective. We compare the population values of the two statistics and illustrate their use in comparing an array of non-nested models for data on recurrent episodes of infant diarrhoea.