Meta-analysis is a statistical method to combine the results of epidemiological studies in order to increase power.
Basically, it produces a weighted average of the included studies results.
The goal of MetaXL is twofold. The first is to make high quality meta-analysis methods easily accessible for people without
access to statistical packages such as Stata or SAS, or to commercial specialized software such as MIX or Comprehensive Meta-analysis. The second is to make available
and promote the use of alternatives to the random effects model. The random effects model, as explained in the MetaXL User Guide, is seriously flawed and should be abandoned. MetaXL therefore implements
the inverse variance heterogeneity (IVhet) and quality effects models as alternatives to the random effects model. The first provides a quasi-likelihood based expansion of the confidence interval around the inverse variance weighted pooled estimate when studies exhibit heterogeneity, without messing with individual study weights (as the random effects model does). The second allows incorporating information on study quality into the analysis, thereby affording the opportunity for reduction in estimator variance beyond that of the IVhet model. Much of the heterogeneity between study results is explained by differences in study quality, and it is preferable to make use of this information explicitly.
Using Excel as a platform makes MetaXL-based meta-analysis highly accessible. And you can’t beat the price!