Nonparametric empirical Bayes method for comparison of treatment effects with application to stress urinary incontinence data.
Hierarchical models are widely used in medical research to structure complicated models and produce statistical inferences. In a hierarchical model, observations are sampled conditional on some parameters and these parameters are sampled from a common prior distribution. Bayes and empirical Bayes (EB) methods have been effectively applied in analyzing these models. Despite many successes, parametric Bayes and EB methods may be sensitive to misspecification of prior distributions. In this paper, without specific restriction on the form of the prior distribution, we propose a nonparametric EB method to estimate the treatment effect of each group and develop a testing procedure to compare between-group differences. Simulation studies demonstrate that the proposed EB method was more efficient than some standard procedures. An illustrative example is provided with data from a clinical trial evaluating a new treatment for patients with stress urinary incontinence.
Liu
Chaofeng
C
Biostatistics and Statistical Reporting, Novartis Pharmaceuticals Corp., 405-3001A, One Health Plaza, East Hanover, NJ 07936, USA. chaofeng.liu@novartis.com
Shen
Wei
W
Xie
Jun
J
D001499:Bayes Theorem; D003198:Computer Simulation; D016001:Confidence Intervals; D018849:Controlled Clinical Trials as Topic / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D004311:Double-Blind Method; D000068736:Duloxetine Hydrochloride; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D015337:Multicenter Studies as Topic / Q000706:statistics & numerical data*; D016011:Normal Distribution; D012107:Research Design; D018709:Statistics, Nonparametric; D013876:Thiophenes / Q000627:therapeutic use*; D013997:Time Factors; D016896:Treatment Outcome; D014550:Urinary Incontinence, Stress / Q000188:drug therapy*
D013876:Thiophenes; D000068736:Duloxetine Hydrochloride