Confidence intervals for a difference between lognormal means in cluster randomization trials. (April 2017)

• Record Type: Journal Article
• Authors: Poirier, Julia; Zou, GY; Koval, John
• Is Part Of: Statistical methods in medical research. Volume 26:Number 2(2017)
• Page Start: 598
• Page End: 614
• Publication Date: 2017-04
• Subjects: lognormal mean -- method of variance estimates recovery -- generalized confidence interval -- asymmetry -- cluster randomization trial; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280214552291
• Languages: English
• ISSNs: 0962-2802

Abstract

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.