title: Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.
abstract: Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.
authors.affiliation: 1 Department of Pediatric Dentistry, University of Washington, Seattle, Washington, USA.
authors.forename: JoAnna M
authors.initials: JM
authors.lastname: Scott
authors.affiliation: 2 Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.|3 Department of Biostatistics, University of Washington, Seattle, Washington, USA.
authors.forename: Allan
authors.initials: A
authors.lastname: deCamp
authors.affiliation: 2 Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
authors.forename: Michal
authors.initials: M
authors.lastname: Juraska
authors.affiliation: 4 Division of Biostatistics, National Institute of Allergies and Infectious Diseases, Bethesda, USA.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Fay
authors.affiliation: 2 Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.|3 Department of Biostatistics, University of Washington, Seattle, Washington, USA.
authors.forename: Peter B
authors.initials: PB
authors.lastname: Gilbert
mesh_terms: D016915:AIDS Vaccines / Q000494:pharmacology; D056808:Biostatistics / Q000379:methods; D016000:Cluster Analysis; D003198:Computer Simulation; D015658:HIV Infections / Q000517:prevention & control; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D018401:Sample Size
chemical_list: D016915:AIDS Vaccines
keywords: Phase 3; Phase 4; Vaccine efficacy trial; cluster randomization; generalized estimating equations; marginal mean model; small-sample variance correction