The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Improper analysis of trials randomised using stratified blocks or minimisation
Abstract
Many clinical trials restrict randomisation using stratified blocks or minimisation to balance prognostic factors across treatment groups. It is widely acknowledged in the statistical literature that the subsequent analysis should reflect the design of the study, and any stratification or minimisation variables should be adjusted for in the analysis. However, a review of recent general medical literature showed only 14 of 41 eligible studies reported adjusting their primary analysis for stratification or minimisation variables. We show that balancing treatment groups using stratification leads to correlation between the treatment groups. If this correlation is ignored and an unadjusted analysis is performed, standard errors for the treatment effect will be biased upwards, resulting in 95% confidence intervals that are too wide, type I error rates that are too low and a reduction in power. Conversely, an adjusted analysis will give valid inference. We explore the extent of this issue using simulation for continuous, binary and time‐to‐event outcomes where treatment is allocated using stratified block randomisation or minimisation. Copyright © 2011 John Wiley & Sons, Ltd.
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Cites
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The method of minimization for allocation to clinical trials
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“A majority of the statistical literature suggests any baseline variable involved in randomisation should also be included in the analysis[9, 12, 13, 14, 15, 16, 17, 18] though some argue this is not always sensible[19].”
BackgroundStratified Randomization for Clinical Trials
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Holst, L. B., Haase, N., Wetterslev, J., Wernerman, J., Guttormsen, A. B., Karlsson, S., Johansson, P. I., Åneman, A., Vang, M. L., Winding, R., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1406617 · Cited by 899
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Randomized trial of four financial-incentive programs for smoking cessation
Halpern, S. D., French, B., Small, D. S., Saulsgiver, K., Harhay, M. O., Audrain-McGovern, J., Loewenstein, G., Brennan, T. A., Asch, D. A., & Volpp, K. G. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1414293 · Cited by 379
Pantoprazole in Patients at Risk for Gastrointestinal Bleeding in the ICU
Krag, M., Marker, S., Perner, A., Wetterslev, J., Wise, M. P., Schefold, J. C., Keus, F., Guttormsen, A. B., Bendel, S., Borthwick, M., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1714919 · Cited by 344
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Self-citationKangovi, S., Mitra, N., Norton, L., Harte, R., Zhao, X., Carter, T., Grande, D., & Long, J. A. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.4630 · Cited by 272
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“We used multiple imputation for analysis of the primary outcome, pain-related disability [34].”
Meyhoff, T. S., Hjortrup, P. B., Møller, M. H., Wetterslev, J., Lange, T., Kjær, M. N., Jonsson, A. B., Hjortsø, C. J. S., Cronhjort, M., Laake, J. H., et al. (2019) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.13434 · Cited by 47
Taylor, S. J., Carnes, D., Homer, K., Pincus, T., Kahan, B. C., Hounsome, N., Eldridge, S., Spencer, A., Diaz-Ordaz, K., Rahman, A., et al. (2016) · Programme Grants for Applied Research · doi:10.3310/pgfar04140 · Cited by 44
Self-citationAmonoo, H. L., Newcomb, R., Lorenz, K. A., Psenka, R., Holmbeck, K., Farnam, E. J., Tse, A., Desai, S., Vassev, N., Waldman, L. P., et al. (2024) · Contemporary Clinical Trials · doi:10.1016/j.cct.2024.107550 · Cited by 2
Metadata
- Authors
- Kahan, B. C., & Morris, T. P.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2011-12-04
- Volume
- 31
- Issue
- 4
- Pages
- 328-340
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2131593307
- Cited by
- 332
- References
- 8
- FWCI
- 9.18
- Type
- journal article
- Language
- en
- Open access
- closed
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