Abstract
Group randomized trials (GRTs) in public health research typically use a small number of randomized groups with a relatively large number of participants per group. Two fundamental features characterize GRTs: A positive correlation of outcomes within a group, and the small number of groups. Appropriate consideration of these fundamental features is essential for design and analysis. This paper presents the fundamental features of GRTs and the importance of considering these features in design and analysis. It also reviews and contrasts the main analytic methods proposed for GRTs, emphasizing the assumptions required to make these methods valid and efficient. Also discussed are various design issues, along with guidelines for choosing among them. A real data example illustrates these issues and methods.
Original language | English (US) |
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Pages (from-to) | 167-187 |
Number of pages | 21 |
Journal | Annual Review of Public Health |
Volume | 22 |
DOIs | |
State | Published - 2001 |
Keywords
- Correlated data
- Generalized estimating equations (GEE)
- Generalized linear mixed models (GLMM)
- Matched design
- Permutation tests
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health