Quantifying the impact of between‐study heterogeneity in multivariate meta‐analyses
MRC Biostatistics Unit · University of Birmingham
Abstract
Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I(2) statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R(2) statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I(2), which we call I(R)(2). We also provide a…
Citation impact
- FWCI
- 53.78
- Percentile
- 100%
- References
- 25
Authors
3Topics & keywords
- Multivariate statistics
- Univariate
- Statistic
- Statistics
- Covariate
- Multivariate analysis
- Econometrics
- Context (archaeology)
- Peace, Justice and strong institutions