Design and analysis of trials with a partially nested design and a binary outcome measure.

ABSTRACT: Where treatments are administered to groups of patients or delivered by therapists, outcomes for patients in the same group or treated by the same therapist may be more similar, leading to clustering. Trials of such treatments should take account of this effect. Where such a treatment is compared with an un-clustered treatment, the trial has a partially nested design. This paper compares statistical methods for this design where the outcome is binary. Investigation of consistency reveals that a random coefficient model with a random effect for group or therapist is not consistent with other methods for a null treatment effect, and so this model is not recommended for this design. Small sample performance of a cluster-adjusted test of proportions, a summary measures test and logistic genera

SUBMITTER: Roberts C 

PROVIDER: S-EPMC4949566 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature