DisMod II



Risk factor






Version 3.1

V 3.0: Doi plot for the detection of publication bias
V 3.1: Indirect comparisons

MetaXL’s forest plot output.


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.
More background on these alternatives is in our

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!


Supports fixed effects (inverse variance, Mantel Haenszel, Peto), random effects (DerSimonian & Laird), inverse variance heterogeneity (Doi et al) and quality effects (Doi & Thalib) models.

Both binary (relative risk, odds ratio, risk difference, prevalence) and continuous (weighted mean mean difference, Cohen’s d, Hedges’ g, Glasss’s Δ, correlations) methods, as well as rates, rate-ratio’s and rate difference effect sizes.

Heterogeneity statistics: Cochran’s Q, I2.

Subgroup analysis

Detection of publication bias using Doi and funnel plots

Quantitative measure of publication bias: LFK index

Multiple category pooled prevalence

Indirect comparisons

Output in table and graphical formats.

Supports both 32 and 64 bit Excel.

Product Summary

MetaXL is an add-in for meta-analysis in Microsoft Excel for Windows. It supports all  major meta-analysis methods, plus, uniquely, the inverse variance heterogeneity and quality effects models. Output is in table and graphical formats.

Price: Free


MetaXL Setup

MetaXL User Guide

The User Guide is included in the installation download.

MetaXL publications

Workshop on Health Economic Evaluation

The School of Public Health,  University of Queensland, conducts an annual five-day workshop on Health Economic Evaluation, featuring MetaXL for meta-analysis.

For details download the workshop flyer

[Home] [Products] [Publications] [Consultancy] [Contact] [About EpiGear]

© Copyright 2015 EpiGear International Pty Ltd.  All rights reserved.