{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T11:51:52Z","timestamp":1787313112912,"version":"build-2736575974"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2013,4,5]],"date-time":"2013-04-05T00:00:00Z","timestamp":1365120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","award":["MRC:U105260557"],"award-info":[{"award-number":["MRC:U105260557"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","award":["MRC:G0902100"],"award-info":[{"award-number":["MRC:G0902100"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","award":["MRC:U105261167"],"award-info":[{"award-number":["MRC:U105261167"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Health Technology Assessment","award":["08\/30\/02"],"award-info":[{"award-number":["08\/30\/02"]}]},{"name":"Health Technology Assessment","award":["MRC:U105200001"],"award-info":[{"award-number":["MRC:U105200001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,8,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>Meta-analysis is often undertaken in two stages, with each study analysed separately in stage 1 and estimates combined across studies in stage 2. The study-specific estimates are assumed to arise from normal distributions with known variances equal to their corresponding estimates. In contrast, a one-stage analysis estimates all parameters simultaneously. A Bayesian one-stage approach offers additional advantages, such as the acknowledgement of uncertainty in all parameters and greater flexibility. However, there are situations when a two-stage strategy is compelling, e.g. when study-specific analyses are complex and\/or time consuming. We present a novel method for fitting the full Bayesian model in two stages, hence benefiting from its advantages while retaining the convenience and flexibility of a two-stage approach. Using Markov chain Monte Carlo methods, posteriors for the parameters of interest are derived separately for each study. These are then used as proposal distributions in a computationally efficient second stage. We illustrate these ideas on a small binomial data set; we also analyse motivating data on the growth and rupture of abdominal aortic aneurysms. The two-stage Bayesian approach closely reproduces a one-stage analysis when it can be undertaken, but can also be easily carried out when a one-stage approach is difficult or impossible.<\/jats:p>","DOI":"10.1111\/rssc.12007","type":"journal-article","created":{"date-parts":[[2013,9,5]],"date-time":"2013-09-05T05:36:34Z","timestamp":1378359394000},"page":"551-572","source":"Crossref","is-referenced-by-count":70,"title":["Fully Bayesian Hierarchical Modelling in Two Stages, with Application to Meta-Analysis"],"prefix":"10.1093","volume":"62","author":[{"given":"David","family":"Lunn","sequence":"first","affiliation":[{"name":"Medical Research Council Biostatistics Unit , Cambridge , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Barrett","sequence":"additional","affiliation":[{"name":"Medical Research Council Biostatistics Unit , Cambridge , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Sweeting","sequence":"additional","affiliation":[{"name":"Medical Research Council Biostatistics Unit , Cambridge , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Thompson","sequence":"additional","affiliation":[{"name":"Medical Research Council Biostatistics Unit , Cambridge , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2013,4,5]]},"reference":[{"key":"2023032107360257700_","first-page":"5","article-title":"Multiparameter evidence synthesis in epidemiology and medical decision-making: current approaches (with discussion)","volume":"169","author":"Ades","year":"2006","journal-title":"J. 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