title: Sample size and robust marginal methods for cluster-randomized trials with censored event times.
abstract: In cluster-randomized trials, intervention effects are often formulated by specifying marginal models, fitting them under a working independence assumption, and using robust variance estimates to address the association in the responses within clusters. We develop sample size criteria within this framework, with analyses based on semiparametric Cox regression models fitted with event times subject to right censoring. At the design stage, copula models are specified to enable derivation of the asymptotic variance of estimators from a marginal Cox regression model and to compute the number of clusters necessary to satisfy power requirements. Simulation studies demonstrate the validity of the sample size formula in finite samples for a range of cluster sizes, censoring rates, and degrees of within-cluster association among event times. The power and relative efficiency implications of copula misspecification is studied, as well as the effect of within-cluster dependence in the censoring times. Sample size criteria and other design issues are also addressed for the setting where the event status is only ascertained at periodic assessments and times are interval censored.
authors.affiliation: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, N2L 3G1, ON, Canada.
authors.forename: Yujie
authors.initials: Y
authors.lastname: Zhong
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Cook
mesh_terms: D015982:Bias; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D010033:Otitis Media / Q000188:drug therapy / Q000601:surgery; D011241:Prednisone / Q000627:therapeutic use; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018401:Sample Size; D017211:Treatment Failure
chemical_list: D011241:Prednisone
keywords: censored data; cluster-randomized trials; copula models; robust inference; sample size