Bayesian meta-analysis using SAS PROC BGLIMM.
Res Synth Methods
; 12(6): 692-700, 2021 Nov.
Article
in En
| MEDLINE
| ID: mdl-34245227
ABSTRACT
Meta-analysis is commonly used to compare two treatments. Network meta-analysis (NMA) is a powerful extension for comparing and contrasting multiple treatments simultaneously in a systematic review of multiple clinical trials. Although the practical utility of meta-analysis is apparent, it is not always straightforward to implement, especially for those interested in a Bayesian approach. This paper demonstrates that the recently-developed SAS procedure BGLIMM provides an intuitive and computationally efficient means for conducting Bayesian meta-analysis in SAS, using a worked example of a smoking cessation NMA data set. BGLIMM gives practitioners an effective and simple way to implement Bayesian meta-analysis (pairwise and network, either contrast-based or arm-based) without requiring significant background in coding or statistical modeling. Those familiar with generalized linear mixed models, and especially the SAS procedure GLIMMIX, will find this tutorial a useful introduction to Bayesian meta-analysis in SAS.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Meta-Analysis as Topic
/
Models, Statistical
/
Smoking Cessation
Type of study:
Prognostic_studies
/
Risk_factors_studies
/
Systematic_reviews
Language:
En
Journal:
Res Synth Methods
Year:
2021
Document type:
Article
Affiliation country:
Estados Unidos