The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Meta‐analysis of continuous outcome data from individual patients
Abstract
Meta‐analyses using individual patient data are becoming increasingly common and have several advantages over meta‐analyses of summary statistics. We explore the use of multilevel or hierarchical models for the meta‐analysis of continuous individual patient outcome data from clinical trials. A general framework is developed which encompasses traditional meta‐analysis, as well as meta‐regression and the inclusion of patient‐level covariates for investigation of heterogeneity. Unexplained variation in treatment differences between trials is considered as random. We focus on models with fixed trial effects, although an extension to a random effect for trial is described. The methods are illustrated on an example in Alzheimer's disease in a classical framework using SAS PROC MIXED and MLwiN, and in a Bayesian framework using BUGS. Relative merits of the three software packages for such meta‐analyses are discussed, as are the assessment of model assumptions and extensions to incorporate more than two treatments. Copyright © 2001 John Wiley & Sons, Ltd.
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Cites
Small sample inference for fixed effects from restricted maximum likelihood
Kenward, M. G., & Roger, J. H. (1997) · Biometrics · doi:10.2307/2533558 · Cited by 4,552
Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
QUANTITATIVE METHODS IN THE REVIEW OF EPIDEMIOLOGIC LITERATURE1
GREENLAND, S. (1987) · Epidemiologic Reviews · doi:10.1093/oxfordjournals.epirev.a036298 · Cited by 1,644 · cited 1×
“i i W β + μ = θ , again using the inverse variances as weights.(26) Random effects meta-regression follows similar principles though computations are more intensive.”
MethodSystematic Review: Why sources of heterogeneity in meta-analysis should be investigated
Thompson, S. G. (1994) · BMJ · doi:10.1136/bmj.309.6965.1351 · Cited by 1,017 · cited 1×
“Some of these clinical differences could be investigated to gain insight as to whether they affect the efficacy of a treatment.(3) Others may be of less importance or not identifiable but, combined, may lead to heterogeneity of results across trials.”
BackgroundA Double-Blind, Placebo-Controlled Multicenter Study of Tacrine for Alzheimer's Disease
Davis, K. L., Thal, L. J., Gamzu, E. R., Davis, C. S., Woolson, R. F., Gracon, S. I., Drachman, D. A., Schneider, L. S., Whitehouse, P. J., Hoover, T. M., et al. (1992) · New England Journal of Medicine · doi:10.1056/nejm199210293271801 · Cited by 626
Bayesian approaches to random-effects meta-analysis: a comparative study
Smith, T. C., Spiegelhalter, D. J., & Thomas, A. (1995) · Statistics in Medicine · doi:10.1002/sim.4780142408 · Cited by 568 · cited 2×
“In order to emulate the classical results we used non-informative ( ) 4 10 , 0 N priors for mean parameters and almost noninformative inverse gamma priors, ( ) 3 3 10 , 10 IG − − for variance parameters.(20) Details of programming the first three models are included in an Appendix; further information is available fro…”
MethodMeta‐analysis for 2 × 2 tables: A bayesian approach
Carlin, J. B. (1992) · Statistics in Medicine · doi:10.1002/sim.4780110202 · Cited by 164
Cholinesterase Inhibition for Alzheimer Disease: A Meta-analysis of the Tacrine Trials
Qizilbash, N., Whitehead, A., Higgins, J., Wilcock, G., Schneider, L., Farlow, M., & for the Dementia Trialists' Collaboration (1998) · JAMA · doi:10.1001/jama.280.20.1777 · Cited by 161
Self-citationClarke, M. J., & Stewart, L. A. (1994) · BMJ · doi:10.1136/bmj.309.6960.1007 · Cited by 117
Cited by
How should meta‐regression analyses be undertaken and interpreted?
Thompson, S. G., & Higgins, J. P. T. (2002) · Statistics in Medicine · doi:10.1002/sim.1187 · Cited by 3,026
Self-citationMeta-analysis of individual participant data: rationale, conduct, and reporting
Riley, R. D., Lambert, P. C., & Abo-Zaid, G. (2010) · BMJ · doi:10.1136/bmj.c221 · Cited by 1,701
Three-level meta-analysis of dependent effect sizes
Van den Noortgate, W., López-López, J. A., Marín-Martínez, F., & Sánchez-Meca, J. (2013) · Behavior Research Methods · doi:10.3758/s13428-012-0261-6 · Cited by 1,130
Efficacy and safety of the weight-loss drug rimonabant: a meta-analysis of randomised trials
Christensen, R., Kristensen, P. K., Bartels, E. M., Bliddal, H., & Astrup, A. (2007) · The Lancet · doi:10.1016/s0140-6736(07)61721-8 · Cited by 1,097
Integrative data analysis: The simultaneous analysis of multiple data sets
Curran, P. J., & Hussong, A. M. (2009) · Psychological Methods · doi:10.1037/a0015914 · Cited by 867
Metadata
- Authors
- Higgins, J. P. T., Whitehead, A., Turner, R. M., Omar, R. Z., & Thompson, S. G.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2001-07-13
- Volume
- 20
- Issue
- 15
- Pages
- 2219-2241
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2016832451
- Cited by
- 265
- References
- 9
- FWCI
- 7.48
- Type
- journal article
- Language
- en
- Open access
- closed
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