title: Explained variation for recurrent event data.
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.
authors.affiliation: Princess Norah Bint Abdulrahman University, Riyadh 11635, Saudi Arabia.
authors.forename: Refah
authors.initials: R
authors.lastname: Alotaibi
authors.affiliation: Statistics Department, Federal University of Bahia, Salvador, Bahia 40170-110, Brazil.
authors.forename: Rosemeire
authors.initials: R
authors.lastname: Fiaccone
authors.affiliation: School of Mathematics & Statistics, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
authors.forename: Robin
authors.initials: R
authors.lastname: Henderson
authors.affiliation: Institute for Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana, Ljubljana 1000, Slovenia.
authors.forename: Janez
authors.initials: J
authors.lastname: Stare
mesh_terms: D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D002675:Child, Preschool; D003967:Diarrhea / Q000453:epidemiology / Q000517:prevention & control; D005260:Female; D006801:Humans; D007223:Infant; D016016:Proportional Hazards Models; D012008:Recurrence; D012499:Sanitation; D055815:Young Adult
keywords: C-index; Counting process; Covariates; Event history; Survival data