Linear mixed model approach to network meta-analysis for continuous outcomes in periodontal research.
Aim Analysing continuous outcomes for network meta-analysis by means of linear mixed models is a great challenge, as it requires statistical software packages to specify special patterns of model error variance and covariance structure. This article demonstrates a non-Bayesian approach to network me...
| Publicado en: | Journal of Clinical Periodontology Vol. 42; no. 2; pp. 204 - 213 |
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| Autor principal: | |
| Formato: | equations & formulas research systematic review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Feb2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103759330&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103759330 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03036979 8E3 jtl: Journal of Clinical Periodontology issn: 03036979 maglogo: Y pubinfo: dt: Feb2015 vid: 42 iid: 2 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103759330 100988335 10.1111/jcpe.12362 NLM25581572 103759330 ppf: 204 ppct: 9 formats: tig: atl: Linear mixed model approach to network meta-analysis for continuous outcomes in periodontal research. aug: au: Tu, Yu-Kang affil: Institute of Epidemiology & Preventive Medicine College of Public Health National Taiwan University sug: subj: Guided Tissue Regeneration Periodontal Diseases Clinical Research Human Systematic Review Meta Analysis Randomized Controlled Trials Funding Source Data Analysis Software ab: Aim Analysing continuous outcomes for network meta-analysis by means of linear mixed models is a great challenge, as it requires statistical software packages to specify special patterns of model error variance and covariance structure. This article demonstrates a non-Bayesian approach to network meta-analysis for continuous outcomes in periodontal research with a special focus on the adjustment of data dependency. Data Seventeen studies on guided tissue regeneration were used to illustrate how the proposed linear mixed models for network meta-analysis of continuous outcomes. Methods & Results Arm-based network meta-analysis use treatment arms from each study as the unit of analysis; when patients are randomly assigned to each arm, data are deemed independent and therefore no adjustment is required for multi-arm trials. Trial-based network meta-analysis use treatment contrasts as the unit of analysis, and therefore treatment contrasts within a multi-arm trial are not independent. This data dependency occurs also in split-mouth studies, and adjustments for data dependency are therefore required. Conclusions Arm-based analysis is the preferred approach to network meta-analysis, when all included studies use the parallel group design and some compare more than two treatment arms. When included studies used designs that yield dependent data, the trial-based analysis is the preferred approach. pubtype: Academic Journal doctype: equations & formulas meta analysis research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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