Robust tests for treatment effects based on censored recurrent event data observed over multiple periods.
We derive semiparametric methods for estimating and testing treatment effects when censored recurrent event data are available over multiple periods. These methods are based on estimating functions motivated by a working "mixed-Poisson" assumption under which conditioning can eliminate subject-specific random effects. Robust pseudoscore test statistics are obtained via "sandwich" variance estimation. The relative efficiency of conditional versus marginal analyses is assessed analytically under a mixed time-homogeneous Poisson model. The robustness and empirical power of the semiparametric approach are assessed through simulation. Adaptations to handle recurrent events arising in crossover trials are described and these methods are applied to data from a two-period crossover trial of patients with bronchial asthma.
Cook
Richard J
RJ
Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada. rjcook@uwaterloo.ca
Wei
Wei
W
Yi
Grace Y
GY
D001249:Asthma / Q000188:drug therapy; D001993:Bronchodilator Agents / Q000627:therapeutic use; D003198:Computer Simulation; D003371:Cough / Q000188:drug therapy; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D005260:Female; D005280:Fenoterol / Q000627:therapeutic use; D006801:Humans; D008297:Male; D010366:Peak Expiratory Flow Rate / Q000187:drug effects; D016012:Poisson Distribution; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D013183:Sputum / Q000187:drug effects; D016896:Treatment Outcome
D001993:Bronchodilator Agents; D005280:Fenoterol