cvcrand and cptest: Commands for efficient design and analysis of cluster randomized trials using constrained randomization and permutation tests

John A. Gallis (), Fan Li (), Hengshi Yu () and Elizabeth L. Turner ()
Additional contact information
John A. Gallis: Duke University
Fan Li: Duke University
Hengshi Yu: University of Michigan
Elizabeth L. Turner: Duke University

Stata Journal, 2018, vol. 18, issue 2, 357-378

Abstract: Cluster randomized trials (CRTs), where clusters (for example, schools or clinics) are randomized to comparison arms but measurements are taken on in- dividuals, are commonly used to evaluate interventions in public health, education, and the social sciences. Because CRTs typically involve a small number of clusters (for example, fewer than 20), simple randomization frequently leads to baseline im- balance of cluster characteristics across study arms, threatening the internal valid- ity of the trial. In CRTs with a small number of clusters, classic approaches to bal- ancing baseline characteristics—such as matching and stratification—have several drawbacks, especially when the number of baseline characteristics the researcher desires to balance is large (Ivers et al., 2012, Trials 13: 120). An alternative de- sign approach is covariate-constrained randomization, whereby a randomization scheme is randomly selected from a subset of all possible randomization schemes based on the value of a balancing criterion (Raab and Butcher, 2001, Statistics in Medicine 20: 351–365). Subsequently, a clustered permutation test can be used in the analysis, which provides increased power under constrained randomization compared with simple randomization (Li et al., 2016, Statistics in Medicine 35: 1565–1579). In this article, we describe covariate-constrained randomization and the permutation test for the design and analysis of CRTs and provide an example to demonstrate the use of our new commands cvcrand and cptest to implement constrained randomization and the permutation test. Copyright 2018 by StataCorp LP.

Keywords: cvcrand; cptest; covariate-constrained randomization; cluster randomized trials; permutation test (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0526 link to article purchase
http://www.stata-journal.com/software/sj18-2/st0526/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:18:y:2018:i:2:p:357-378

Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html

Access Statistics for this article

Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins

More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().