Alternative Meta-Analysis Methods
Description
Provides alternative statistical methods for meta-analysis, including:
- bivariate generalized linear mixed models for synthesizing odds ratios, relative risks,
and risk differences
(Chu et al., 2012 )
- heterogeneity tests and measures and penalization methods that are robust to outliers
(Lin et al., 2017 ;
Wang et al., 2022 );
- measures, tests, and visualization tools for publication bias or small-study effects
(Lin and Chu, 2018 ;
Lin, 2019 ;
Lin, 2020 ;
Shi et al., 2020 );
- meta-analysis of diagnostic tests for synthesizing sensitivities, specificities, etc.
(Reitsma et al., 2005 ;
Chu and Cole, 2006 );
- meta-analysis methods for synthesizing proportions
(Lin and Chu, 2020 );
- models for multivariate meta-analysis, measures of inconsistency degrees of freedom
in Bayesian network meta-analysis, and predictive P-score
(Lin and Chu, 2018 ;
Lin, 2020 ;
Rosenberger et al., 2021 ).