The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Multivariate Random-effects Meta-analysis
Open accessAbstract
Multivariate meta-analysis combines estimates of several related parameters over several studies. These parameters can, for example, refer to multiple outcomes or comparisons between more than two groups. A new Stata command, mvmeta, performs maximum likelihood, restricted maximum likelihood, or method-of-moments estimation of random-effects multivariate meta-analysis models. A utility command, mvmeta_make, facilitates the preparation of summary datasets from more detailed data. The commands are illustrated with data from the Fibrinogen Studies Collaboration, a meta-analysis of observational studies; I estimate the shape of the association between a quantitative exposure and disease events by grouping the quantitative exposure into several categories.
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Cites
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Heinze, G., & Schemper, M. (2002) · Statistics in Medicine · doi:10.1002/sim.1047 · Cited by 2,711
Improved tests for a random effects meta‐regression with a single covariate
Knapp, G., & Hartung, J. (2003) · Statistics in Medicine · doi:10.1002/sim.1482 · Cited by 2,075
Systematic Review: Why sources of heterogeneity in meta-analysis should be investigated
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“In such work, it is important to allow for heterogeneity between studies, usually by fitting a random-effects model (Thompson 1994).”
Harbord, R. M., & Higgins, J. P. T. (2008) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0800800403 · Cited by 897
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Cited by
Hutton, B., Salanti, G., Caldwell, D. M., Chaimani, A., Schmid, C. H., Cameron, C., Ioannidis, J. P. A., Straus, S., Thorlund, K., Jansen, J. P., et al. (2015) · Annals of Internal Medicine · doi:10.7326/m14-2385 · Cited by 8,269
Ekelund, U., Tarp, J., Steene-Johannessen, J., Hansen, B. H., Jefferis, B., Fagerland, M. W., Whincup, P., Diaz, K. M., Hooker, S. P., Chernofsky, A., et al. (2019) · BMJ · doi:10.1136/bmj.l4570 · Cited by 1,769
Salanti, G. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.1037 · Cited by 1,729
Methods to estimate the between‐study variance and its uncertainty in meta‐analysis
Veroniki, A. A., Jackson, D., Viechtbauer, W., Bender, R., Bowden, J., Knapp, G., Kuss, O., Higgins, J. P., Langan, D., & Salanti, G. (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1164 · Cited by 1,685
White, I. R., Barrett, J. K., Jackson, D., & Higgins, J. P. T. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.1045 · Cited by 1,114
Self-citation
Metadata
- Authors
- White, I. R.
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2009-03
- Volume
- 9
- Issue
- 1
- Pages
- 40-56
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W1509852289
- Cited by
- 286
- References
- 5
- FWCI
- 11.94
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
