The metafor package provides functions for conducting meta-analyses in R. The package includes functions for fitting the meta-analytic fixed- and random-effects models and allows for the inclusion of moderators variables (study-level covariates) in these models. Meta-regression analyses with continuous and categorical moderators can be conducted in this way. Functions for the Mantel-Haenszel and Peto's one-step method for meta-analyses of 2 x 2 table data are also available. Finally, the package provides various plot functions (for example, for forest, funnel, and radial plots) and functions for assessing the model fit, for obtaining case diagnostics, and for tests of publication bias.

Conducting Meta-Analyses in R with the metafor Package

This report presents the first global systematic review of scientific data on the prevalence of two forms of violence against women: violence by an intimate partner (intimate partner violence) and sexual violence by someone other than a partner (non-partner sexual violence). It shows for the first time global and regional estimates of the prevalence of these two forms of violence using data from around the world. Previous reporting on violence against women has not differentiated between partner- and nonpartner violence.

Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence.

The handbook of research synthesis and meta-analysis, 2nd ed.

Rationale: Reducing the global burden of sepsis, a recognized global health challenge, requires comprehensive data on the incidence and mortality on a global scale.Objectives: To estimate the worldwide incidence and mortality of sepsis and identify knowledge gaps based on available evidence from observational studies.Methods: We systematically searched 15 international citation databases for population-level estimates of sepsis incidence rates and fatality in adult populations using consensus criteria and published in the last 36 years.Measurements and Main Results: The search yielded 1,553 reports from 1979 to 2015, of which 45 met our criteria. A total of 27 studies from seven high-income countries provided data for metaanalysis. For these countries, the population incidence rate was 288 (95% confidence interval [CI], 215–386; τ = 0.55) for hospital-treated sepsis cases and 148 (95% CI, 98–226; τ = 0.99) for hospital-treated severe sepsis cases per 100,000 person-years. Restricted to the last decade, th...

https://www.atsjournals.org/doi/pdf/10.1164/rccm.201504-0781OC

Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations.

Analysing data and undertaking meta-analyses

The explanation of heterogeneity plays an important role in meta-analysis. The random effects meta-regression model allows the inclusion of trial-specific covariates which may explain a part of the heterogeneity. We examine the commonly used tests on the parameters in the random effects meta-regression with one covariate and propose some new test statistics based on an improved estimator of the variance of the parameter estimates. The approximation of the distribution of the newly proposed tests is based on some theoretical considerations. Moreover, the newly proposed tests can easily be extended to the case of more than one covariate. In a simulation study, we compare the tests with regard to their actual significance level and we consider the log relative risk as the parameter of interest. Our simulation study reflects the meta-analysis of the efficacy of a vaccine for the prevention of tuberculosis originally discussed in Berkey et al. The simulation study shows that the newly proposed tests are superior to the commonly used test in holding the nominal significance level.

Improved tests for a random effects meta-regression with a single covariate

Statistical meta-analysis with applications , Statistical meta-analysis with applications , کتابخانه مرکزی دانشگاه علوم پزشکی تهران

Statistical Meta-Analysis with Applications

For the meta-analysis of controlled clinical trials with binary outcome a test statistic for testing an overall treatment effect is proposed, which is based on a refined estimator for the variance of the treatment effect estimator usually used in the random-effects model of meta-analysis. In simulation studies it is shown that the proposed test keeps the prescribed significance level much better than the commonly used tests in the fixed-effects and random-effects model, respectively. Moreover, when using the test it is not necessary to choose between fixed effects and random effects approaches in advance. The proposed method applies in the same way to the analysis of a controlled multi-centre study with binary outcome, including a possible interaction between drugs and centres.

A refined method for the meta-analysis of controlled clinical trials with binary outcome.

Statistik: Lehr- und Handbuch der angewandten Statistik

For the meta-analysis of controlled clinical trials or epidemiological studies, in which the responses are at least approximately normally distributed, a refined test for the hypothesis of no overall treatment effect is proposed. The test statistic is based on a direct estimation function for the variance of the overall treatment effect estimator. As outcome measures, the absolute and the standardized difference between means are considered. In simulation studies it is shown that the proposed test keeps the prescribed significance level very well in contrast to the commonly used tests in the fixed effects and random effects model, respectively, which can become very liberal. Furthermore, just for using the proposed test it is not necessary to choose between the fixed effects and the random effects approach in advance.

Joachim Hartung

Papers

Improved tests for a random effects meta-regression with a single covariate

Statistical Meta-Analysis with Applications

A refined method for the meta-analysis of controlled clinical trials with binary outcome.

Statistik: Lehr- und Handbuch der angewandten Statistik

On tests of the overall treatment effect in meta-analysis with normally distributed responses.