Advanced methods in meta-analysis: multivariate approach and meta-regression
This tutorial on advanced statistical methods for meta‐analysis can be seen as a sequel to the recent Tutorial in Biostatistics on meta‐analysis by Normand, which focused on elementary methods. Within the framework of the general linear mixed model using approximate likelihood, we discuss methods to...
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| Veröffentlicht in: | Statistics in medicine 2002-02, Vol.21 (4), p.589-624 |
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| container_title | Statistics in medicine |
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| creator | van Houwelingen, Hans C. Arends, Lidia R. Stijnen, Theo |
| description | This tutorial on advanced statistical methods for meta‐analysis can be seen as a sequel to the recent Tutorial in Biostatistics on meta‐analysis by Normand, which focused on elementary methods. Within the framework of the general linear mixed model using approximate likelihood, we discuss methods to analyse univariate as well as bivariate treatment effects in meta‐analyses as well as meta‐regression methods. Several extensions of the models are discussed, like exact likelihood, non‐normal mixtures and multiple endpoints. We end with a discussion about the use of Bayesian methods in meta‐analysis. All methods are illustrated by a meta‐analysis concerning the efficacy of BCG vaccine against tuberculosis. All analyses that use approximate likelihood can be carried out by standard software. We demonstrate how the models can be fitted using SAS Proc Mixed. Copyright © 2002 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/sim.1040 |
| format | Article |
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Copyright © 2002 John Wiley & Sons, Ltd.</description><subject>Bayes Theorem</subject><subject>BCG Vaccine - immunology</subject><subject>BCG Vaccine - standards</subject><subject>Biological and medical sciences</subject><subject>Computerized, statistical medical data processing and models in biomedicine</subject><subject>Humans</subject><subject>Medical sciences</subject><subject>Medical statistics</subject><subject>meta-analysis</subject><subject>Meta-Analysis as Topic</subject><subject>meta-regression</subject><subject>Multivariate Analysis</subject><subject>multivariate random effects models</subject><subject>Statistics as Topic - methods</subject><subject>Tuberculosis - prevention & control</subject><issn>0277-6715</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp10E1P3DAQBmALFcEWKvUXoFyKegl44jiOewNUKOrypVK1N2vW9oLbfCyeLGX_fb3aqJx6mjk8mnf0MvYe-BFwXhxTaNNS8i02Aa5VzgtZv2ETXiiVVwrkLntL9ItzAFmoHbYLUItKiXrCpifuGTvrXdb64bF3lIVuvWKOHTYrCvQpa5fNEJ4xBhx8hotF7NE-Zti5DYz-IXqi0Hf7bHuODfl349xj388_3599yac3F5dnJ9PclhJ4brWoKoCZsHUNWhS6LLx23mqFyJ1FUdROipn2lQapuLSutnzuqlJJQAUg9tjh5m565WnpaTBtIOubBjvfL8koKKVIIQl-3EAbe6Lo52YRQ4txZYCbdXMmNWfWzSV6MN5czlrvXuFYVQIfRoBksZnHVFugVydKWUixfi7fuD-h8av_Bppvl1dj8OgDDf7ln8f426RcJc2P6wuj736ey9uvp-Ze_AVwPZLc</recordid><startdate>20020228</startdate><enddate>20020228</enddate><creator>van Houwelingen, Hans C.</creator><creator>Arends, Lidia R.</creator><creator>Stijnen, Theo</creator><general>John Wiley & Sons, Ltd</general><general>Wiley</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20020228</creationdate><title>Advanced methods in meta-analysis: multivariate approach and meta-regression</title><author>van Houwelingen, Hans C. ; Arends, Lidia R. ; Stijnen, Theo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4510-c936611b3c881932942e9dec97aa0dca328d53b9e6915705cd8c0fd64751a7113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Bayes Theorem</topic><topic>BCG Vaccine - immunology</topic><topic>BCG Vaccine - standards</topic><topic>Biological and medical sciences</topic><topic>Computerized, statistical medical data processing and models in biomedicine</topic><topic>Humans</topic><topic>Medical sciences</topic><topic>Medical statistics</topic><topic>meta-analysis</topic><topic>Meta-Analysis as Topic</topic><topic>meta-regression</topic><topic>Multivariate Analysis</topic><topic>multivariate random effects models</topic><topic>Statistics as Topic - methods</topic><topic>Tuberculosis - prevention & control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>van Houwelingen, Hans C.</creatorcontrib><creatorcontrib>Arends, Lidia R.</creatorcontrib><creatorcontrib>Stijnen, Theo</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Statistics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>van Houwelingen, Hans C.</au><au>Arends, Lidia R.</au><au>Stijnen, Theo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Advanced methods in meta-analysis: multivariate approach and meta-regression</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Statist. 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| ispartof | Statistics in medicine, 2002-02, Vol.21 (4), p.589-624 |
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| language | eng |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Bayes Theorem BCG Vaccine - immunology BCG Vaccine - standards Biological and medical sciences Computerized, statistical medical data processing and models in biomedicine Humans Medical sciences Medical statistics meta-analysis Meta-Analysis as Topic meta-regression Multivariate Analysis multivariate random effects models Statistics as Topic - methods Tuberculosis - prevention & control |
| title | Advanced methods in meta-analysis: multivariate approach and meta-regression |
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