Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data
Edmond S.-W. Ng
Department of Health Services Research and Policy
London School of Hygiene and Tropical Medicine
London, UK
[email protected]
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Richard Grieve
Department of Health Services Research and Policy
London School of Hygiene and Tropical Medicine
London, UK
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James R. Carpenter
Department of Medical Statistics
London School of Hygiene and Tropical Medicine
London, UK
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Abstract. This article describes a new Stata command, tsb, for performing a
stratified two-stage nonparametric bootstrap resampling procedure for clustered
data. Estimates for uncertainty around the point estimate, such as standard error
and confidence intervals, are derived from the resultant bootstrap samples. A
shrinkage estimator proposed for correcting possible overestimation due to second-stage
sampling is implemented as default. Although this command is written with
cost effectiveness analyses alongside cluster trials in mind, it is applicable to the
analysis of continuous endpoints in cluster trials more generally. The use of this
command is exemplified with a case study of a cost effectiveness analysis undertaken
alongside a cluster randomized trial. We also report bootstrap confidence
interval coverage by using data from a published simulation study.
View all articles by these authors:
Edmond S.-W. Ng, Richard Grieve, James R. Carpenter
View all articles with these keywords:
tsb, tsbceprob, two-stage nonparametric bootstrap, shrinkage correction, clustered data, cost effectiveness, health economics
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