{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T01:20:24Z","timestamp":1789953624650,"version":"4.0.1"},"reference-count":29,"publisher":"Wiley","issue":"15","license":[{"start":{"date-parts":[[2001,7,13]],"date-time":"2001-07-13T00:00:00Z","timestamp":994982400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2001,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Meta\u2010analyses are being undertaken in an increasing diversity of diseases and conditions, some of which involve outcomes measured on an ordered categorical scale. We consider methodology for undertaking a meta\u2010analysis on individual patient data for an ordinal response. The approach is based on the proportional odds model, in which the treatment effect is represented by the log\u2010odds ratio. A general framework is proposed for fixed and random effect models. Tests of the validity of the various assumptions made in the meta\u2010analysis models, such as a global test of the assumption of proportional odds between treatments, are presented. The combination of studies with different definitions or numbers of response categories is discussed. The methods are illustrated on two data sets, in a classical framework using SAS and MLn and in a Bayesian framework using BUGS. The relative merits of the three software packages for such meta\u2010analyses are discussed. Copyright \u00a9 2001 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.919","type":"journal-article","created":{"date-parts":[[2002,8,25]],"date-time":"2002-08-25T22:27:40Z","timestamp":1030314460000},"page":"2243-2260","source":"Crossref","is-referenced-by-count":68,"title":["Meta\u2010analysis of ordinal outcomes using individual patient data"],"prefix":"10.1002","volume":"20","author":[{"given":"Anne","family":"Whitehead","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rumana Z.","family":"Omar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian P. T.","family":"Higgins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elly","family":"Savaluny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca M.","family":"Turner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon G.","family":"Thompson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2001,7,13]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780101105"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780132313"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19991030)18:20<2693::AID-SIM235>3.0.CO;2-V"},{"key":"e_1_2_1_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0258(20001230)19:24<3417::AID-SIM614>3.0.CO;2-L"},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.280.20.1777"},{"key":"e_1_2_1_7_2","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1111\/j.2517-6161.1980.tb01109.x","article-title":"Regression models for ordinal data","volume":"42","author":"McCullagh P","year":"1980","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"e_1_2_1_8_2","volume-title":"SAS\/STAT\u00ae User's Guide, Version 6, 4th edn.","author":"SAS Institute Inc.","year":"1990"},{"key":"e_1_2_1_9_2","volume-title":"Stata Statistical Software, Version 6.0","author":"StataCorp","year":"1999"},{"key":"e_1_2_1_10_2","volume-title":"Multilevel Modelling Applications: A Guide for Users of MLn","author":"Woodhouse G","year":"1996"},{"key":"e_1_2_1_11_2","volume-title":"MLn Macros for Advanced Multilevel Modelling, V1.1","author":"Yang M","year":"1996"},{"key":"e_1_2_1_12_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/78.1.45"},{"key":"e_1_2_1_13_2","volume-title":"Multilevel Statistical Models","author":"Goldstein H","year":"1995"},{"key":"e_1_2_1_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0197-2456(97)91201-0"},{"key":"e_1_2_1_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/73.1.13"},{"key":"e_1_2_1_16_2","volume-title":"SAS\/IML\u00ae Software: Usage and Reference, Version 6","author":"SAS Institute Inc.","year":"1990"},{"key":"e_1_2_1_17_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0305004100009580"},{"key":"e_1_2_1_18_2","doi-asserted-by":"publisher","DOI":"10.2307\/2533433"},{"key":"e_1_2_1_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/0169-2607(96)01720-8"},{"key":"e_1_2_1_20_2","doi-asserted-by":"publisher","DOI":"10.2307\/2290687"},{"key":"e_1_2_1_21_2","volume-title":"BUGS: Bayesian inference Using Gibbs Sampling, Version 0.50","author":"Speigelhalter DJ","year":"1995"},{"key":"e_1_2_1_22_2","doi-asserted-by":"publisher","DOI":"10.2307\/2983178"},{"key":"e_1_2_1_23_2","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1111\/j.2517-6161.1995.tb02042.x","article-title":"Bayesian model choice via Markov chain Monte Carlo methods","volume":"57","author":"Carlin BP","year":"1995","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"e_1_2_1_24_2","volume-title":"CODA Convergence Diagnosis and Output Analysis software for Gibbs Sampler output, Version 0.3","author":"Best NG","year":"1995"},{"key":"e_1_2_1_25_2","doi-asserted-by":"publisher","DOI":"10.2307\/1390675"},{"key":"e_1_2_1_26_2","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1093\/oso\/9780198522669.003.0010","volume-title":"Bayesian Statistics 4","author":"Geweke J","year":"1992"},{"key":"e_1_2_1_27_2","first-page":"3","article-title":"Consistent estimators for multilevel generalised linear models using an iterated bootstrap","volume":"8","author":"Goldstein H","year":"1996","journal-title":"Multilevel Modelling Newsletter"},{"key":"e_1_2_1_28_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19961230)15:24<2733::AID-SIM562>3.0.CO;2-0"},{"key":"e_1_2_1_29_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780122404"},{"key":"e_1_2_1_30_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.918"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fsim.919","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.919","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T16:43:55Z","timestamp":1733157835000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.919"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,7,13]]},"references-count":29,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2001,8,15]]}},"alternative-id":["10.1002\/sim.919"],"URL":"https:\/\/doi.org\/10.1002\/sim.919","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"value":"0277-6715","type":"print"},{"value":"1097-0258","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,7,13]]}}}