title: NONPARAMETRIC INFERENCE PROCEDURE FOR PERCENTILES OF THE RANDOM EFFECTS DISTRIBUTION IN META-ANALYSIS.
abstract: To investigate whether treating cancer patients with erythropoiesis-stimulating agents (ESAs) would increase the mortality risk, Bennett et al. [Journal of the American Medical Association299(2008) 914-924] conducted a meta-analysis with the data from 52 phase III trials comparing ESAs with placebo or standard of care. With a standard parametric random effects modeling approach, the study concluded that ESA administration was significantly associated with increasedaveragemortality risk. In this article we present a simplenonparametricinference procedure for thedistributionof the random effects. We re-analyzed the ESA mortality data with the new method. Our results about the center of the random effects distribution were markedly different from those reported by Bennett et al. Moreover, our procedure, which estimates the distribution of the random effects, as opposed to just a simple population average, suggests that the ESA may be beneficial to mortality for approximately a quarter of the study populations. This new meta-analysis technique can be implemented with study-level summary statistics. In contrast to existing methods for parametric random effects models, the validity of our proposal does not require the number of studies involved to be large. From the results of an extensive numerical study, we find that the new procedure performs well even with moderate individual study sample sizes.
authors: Department of Biostatistics Harvard University School of Public Health Boston, Massachusetts 02115 USA.
authors: Rui
authors: R
authors: Wang
authors: Department of Health Policy and Research Stanford University School of Medicine Stanford, California 94305 USA.
authors: Lu
authors: L
authors: Tian
authors: Department of Biostatistics Harvard University School of Public Health Boston, Massachusetts 02115 USA.
authors: Tianxi
authors: T
authors: Cai
authors: Department of Biostatistics Harvard University School of Public Health Boston, Massachusetts 02115 USA.
authors: L J
authors: LJ
authors: Wei
keywords: Bivariate beta; conditional permutation test; erythropoiesis-stimulating agents; logit-normal; two-level hierachical model