Power and sample size for reversible linear mixed models with clustering and longitudinality: GLIMMPSE Version 3

GLIMMPSE Version 3 is a free, web-based, open-source software tool, which calculates power and sample size for general linear mixed models with Gaussian errors. The software permits power calculations for clinical trials, randomized experiments, and observational studies with clustering, repeated measures, and both, and almost any testable hypothesis. The software has been supported by five United States National Institutes of Health (NIH) grants, is used for more than 14,000 power or sample size calculations per year, has been cited in almost 500 peer-reviewed manuscripts, and used to design more than 200 million dollars in NIH-funded studies. This release provides several new features. The back end has been refactored in Python. The interface has been simplified, requiring user decisions about only one topic per screen. A new menu improves specification of both between-participant and within-participant hypotheses. A recursive algorithm permits computing covariances for up to ten levels of clustering. An updated Monte Carlo simulation using five new examples with clustering, longitudinality, or both, shows accuracy of the power approximations to within 0.01. Five new examples demonstrate power or sample size calculations for 1) a cluster-randomized trial, 2) a longitudinal study with repeated measures, 3) a multilevel study with a multivariate outcome, 4) a multilevel and longitudinal study, and 5) a complex study with a subgroup factor, repeated measures, and intervention-by-location interaction.

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Publication Details

Journal
PLoS ONE
Published
2025-09-03
DOI
https://doi.org/10.1371/journal.pone.0329712
Citations
2
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
4.24

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article

Power and sample size for reversible linear mixed models with clustering and longitudinality: GLIMMPSE Version 3

Albert D. Ritzhaupt, Jiang Bian, Deborah H. Glueck, Natercia Valle et al.
2 citations
PLoS ONE
Mental Health Research Topics
4.24
article

Power and sample size for reversible linear mixed models with clustering and longitudinality: GLIMMPSE Version 3

Albert D. Ritzhaupt, Jiang Bian, Deborah H. Glueck, Natercia Valle, Max Sommer, Elizabeth Litkowski, Xi Yang, Jessica R. Shaw, Anne Macleod, Qian Li, Keith E. Muller
article en
2 citations

Abstract

GLIMMPSE Version 3 is a free, web-based, open-source software tool, which calculates power and sample size for general linear mixed models with Gaussian errors. The software permits power calculations for clinical trials, randomized experiments, and observational studies with clustering, repeated measures, and both, and almost any testable hypothesis. The software has been supported by five United States National Institutes of Health (NIH) grants, is used for more than 14,000 power or sample size calculations per year, has been cited in almost 500 peer-reviewed manuscripts, and used to design more than 200 million dollars in NIH-funded studies. This release provides several new features. The back end has been refactored in Python. The interface has been simplified, requiring user decisions about only one topic per screen. A new menu improves specification of both between-participant and within-participant hypotheses. A recursive algorithm permits computing covariances for up to ten levels of clustering. An updated Monte Carlo simulation using five new examples with clustering, longitudinality, or both, shows accuracy of the power approximations to within 0.01. Five new examples demonstrate power or sample size calculations for 1) a cluster-randomized trial, 2) a longitudinal study with repeated measures, 3) a multilevel study with a multivariate outcome, 4) a multilevel and longitudinal study, and 5) a complex study with a subgroup factor, repeated measures, and intervention-by-location interaction.

PLoS ONEVol. 20(9)
Regenstrief Institute (US), Colorado School of Public Health (US), University of Michigan (US), University of Florida Health (US), University of Florida (US), Indiana University – Purdue University Indianapolis (US), University of Colorado Denver (US), University of Edinburgh (GB)
Georgia Clinical and Translational Science Alliance, National Institutes of Health, University of Colorado Denver, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Dental and Craniofacial Research, National Center for Advancing Translational Sciences
Openalex Percentile: Top 6%
Mental Health Research Topics
4.24
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