Meta-analyze dichotomous data: Do the calculations with Log Odds Ratios and report Risk Ratios or Risk Differences

This paper describes a method to convert meta-analytic results in (log) Odds Ratio to either Risk Ratio or Risk Difference. It has been argued that odds ratios are mathematically superior for meta-analysis, but risk ratios and risk differences are shown to be easier to interpret. Therefore, the proposed method enables the calculation of meta-analytic results in (log) odds ratio and to transform them afterwards in risk ratio and risk difference. This transformation is based on the assumption of equal significance of the results. It is implemented Meta-Essentials: Workbooks for meta-analyses

How to interpret results of meta-analysis (Version 1.3)

Meta-analysis is a systematic method for synthesizing quantitative results of different empirical studies regarding the effect of an independent variable (or determinant, or intervention, or treatment) on a defined outcome (or dependent variable). Mainly developed in medical and psychological research as a tool for synthesizing empirical information about the outcomes of a treatment, meta-analysis is now increasingly used in the social sciences as a tool for hypothesis testing. However, the assumptions underlying meta-analytic hypothesis testing in the social sciences will usually not be met under real-life conditions. This is the reason why meta-analysis is increasingly conducted with a different aim, based on more realistic assumptions. That aim is to explore the dispersion of effect sizes

Introduction, comparison, and validation of Meta-Essentials

We present a new tool for meta‐analysis, _Meta‐Essentials_, which is free of charge and easy to use. In this paper, we introduce the tool and compare its features to other tools for meta‐analysis.We also provide detailed information on the validation of the tool. Although free of charge and simple, _Meta‐Essentials_ automatically calculates effect sizes from a wide range of statistics and can be used for a wide range of meta‐analysis applications, including subgroup analysis, moderator analysis, and publication bias analyses. The confidence interval of the overall effect is automatically based on the Knapp‐Hartung adjustment of the DerSimonian‐Laird estimator. However, more advanced meta‐analysis methods such as meta‐analytical structural equation modelling and meta‐regression with multiple covariates are not available. In summary, _Meta‐Essentials_ may prove a valuable resource for meta‐analysts, including researchers, teachers, and students

User manual for Meta-Essentials: Workbooks for meta-analyses (Version 1.3)

Meta-Essentials is a set of workbooks that facilitate the integration and synthesis of effect sizes from different studies and provide figures, tables, and statistics that might be helpful for interpreting them. Meta-Essentials generates (“overall” or “meta”) statistical information regarding a set of studies of the same phenomenon based on the statistical information from each separate study. The workbooks and a pdf-version of this user manual can be downloaded from [meta-essentials](http://www.erim.eur.nl/research-support/meta-essentials)