crtrest: A command for ratio estimators of intervention effects on event rates in cluster randomized trials

Xiangmei Ma () and Yin Bun Cheung ()
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Xiangmei Ma: Duke–NUS Medical School
Yin Bun Cheung: Duke–NUS Medical School

Stata Journal, 2022, vol. 22, issue 4, 908-923

Abstract: We describe five asymptotically unbiased estimators of intervention effects on event rates in nonmatched and matched-pair cluster randomized trials, and we present a bias-corrected version of the estimators for use when the number of clusters is small. The estimators are the ratio of mean counts (r1), ratio of mean cluster-level event rates (r2), ratio of event rates (r3), double ratio of counts (r4), and double ratio of event rates (r5). r1, r2, and r3 estimate the total effect, which comprises the direct and indirect effects; r4 and r5 estimate the direct effect. We describe a new command, crtrest, that provides these ratio estimators and their standard errors in nonmatched and matched-pair cluster randomized trials.

Keywords: crtrest; ratio estimator; intervention effects; event rate; cluster randomized trial (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1177/1536867X221141012

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