Evidence map›Paper›PMID 36968149›Full record

ArticleThe Stata journal2022

power swgee: GEE-based power calculations in stepped wedge cluster randomized trials.

John A Gallis, Xueqi Wang, Paul J Rathouz, John S Preisser, Fan Li, Elizabeth L Turner

Abstract read
In one paragraph

Article in The Stata journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

John A GallisDepartment of Biostatistics, Duke University, Duke Global Health Institute, Durham, NC.
Xueqi WangDepartment of Biostatistics, Duke University, Duke Global Health Institute, Durham, NC.
Paul J RathouzDepartment of Population Health, University of Texas at Austin, Dell Medical School, Austin, TX.
John S PreisserDepartment of Biosttistics, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, NC.
Fan LiDepartment of Biostatistics, Yale School of Public Health, Center for Methods in Implementation, Prevention Science, New Haven, CT.
Elizabeth L TurnerDepartment of Biostatistics, Duke University, Duke Global Health Institute, Durham, NC.

Funding

RESHAPE Diversity SupplementR01MH120649 · NIMH · GEORGE WASHINGTON UNIVERSITY · PI KOHRT, BRANDON ALAN · 2019 to 2023
$3.5M
NIMH NIH HHS R01 MH120649Patient-Centered Outcomes Research Institute ME-2019C1-16196
6 · The paper itself

Abstract

Stepped wedge cluster randomized trials are increasingly being used to evaluate interventions in medical, public health, educational, and social science contexts. With the longitudinal and crossover nature of a SW-CRT, complex analysis techniques are often needed which makes appropriately powering SW-CRTs challenging. In this paper, we introduce a newly-developed SW-CRT power calculator, embedded within the power command in Stata. The power calculator assumes a marginal model (i.e., generalized estimating equations [GEE]) for the primary analysis of SW-CRTs, for which other currently available SW-CRT power calculators may not be suitable. The program accommodates complete cross-sectional and closed-cohort designs, and includes multilevel correlation structures appropriate for such designs. We discuss the methods and formulae underlying our SW-CRT calculator, and provide illustrative examples of the use of power swgee. We provide suggestions about the choice of parameters in power swgee, and conclude by discussing areas of future research which may improve the program.

Indexed as

generalized estimating equationsgroup randomized trialsmarginal modelspower swgeest0001statistical power

Identifiers

PMID36968149
PMCPMC10035664

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.