MetaXL keeps pushing the envelope of innovation in meta-analysis. Version 1 introduced the quality effects (QE) model,
version 2 the inverse variance heterogeneity (IVhet) model, and now version 3 introduces the Doi plot and LFK index for the detection of publication bias.
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.
There are two main issues with meta-analysis:
heterogeneity between studies, and publication bias. Heterogeneity is usually dealt with by employing the random effects (RE) model. However the RE estimator, as explained in the MetaXL User Guide, underestimates the statistical error and has a larger mean squared error (MSE) than even the fixed effects estimator and for
these reasons is seriously flawed and should be abandoned. MetaXL offers two alternatives to the RE model:
1) The IVhet model provides a quasi-likelihood based expansion of the confidence interval
around the inverse variance weighted pooled estimate when studies exhibit heterogeneity (without inappropriate changes to individual study weights, as the random effects model does), thus keeping the MSE
lower than with the random effects estimator.
2) The QE model allows incorporating information on study quality into the analysis, thereby affording the opportunity for further reduction in estimator
MSE 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.
background on these alternatives is in our publications.
Publication bias can
occur, among other reasons, because studies with ‘positive’ results are more likely to get published than ones with ‘negative’ results. Traditionally, the funnel plot is used to
detect possible publication bias, but this plot is often hard to interpret. MetaXL now offers an alternative, the Doi plot, which is much easier to interpret.
Using Excel as a platform makes
MetaXL-based meta-analysis highly accessible. And you still can’t beat the price!