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, version 3 introduced the Doi plot and LFK index for the detection of publication bias, and now version 4 adds network
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
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
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.
More 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.
Network meta-analysis can make multiple indirect comparisons, thus allowing to assess a range of treatment options against a common
comparator. It is a powerful technique, but it has been held back by complex methods. The MetaXL implementation is powerful, yet very easy to use.
Using Excel as a platform makes MetaXL-based
meta-analysis highly accessible. And you still can’t beat the price!