Contents
When did the METAFOR package become available in R?
•several meta-analysis packages •all lacked meta-regression capabilities •wrote my own function (mima) in 2006 •turned into full package (metafor) in 2009 •Viechtbauer, W. (2010). Conducting meta- analyses in R with the metafor package.
How to do a meta-analysis with R?
Random-Effects Model (k = 13; tau^2 estimator: REML) • tau^2 (estimated amount of total heterogeneity): 0.3132 tau (square root of estimated tau^2 value): 0.5597 I^2 (total heterogeneity / total variability): 92.22% H^2 (total variability / sampling variability): 12.86 Test for Heterogeneity: predict(res, transf=<>, digits=2)
What are the functions of the METAFOR package?
The package consists of a collection of functions that allow the user to calculate various effect size or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots. On this website, you can find:
How is the RMA function used in METAFOR?
Function to fit the meta-analytic fixed- and random/mixed-effects models with or without moderators via linear (mixed-effects) models. See the documentation of the metafor-package for more details on these models.
Which is the meta analysis package in R?
R comes with a lot of built -in the form of packages. Metafor, a package that conducts meta-analyses was written statistics programmes such as SPSS and Minitab.
When to do a meta-analysis with METAFOR?
Doing the meta-analysis with metafor The next thing is to decide what kind of meta- ana lysis you are doing. odds/risks to start with. When you have decided that you need to tell R two main analysis you want to do. standard deviations, and numbers in each group. “SMD” for standardised mean difference.
How to reconstruct data for a meta-analysis?
Given only this information, it is possible to reconstruct the full dataset for the meta-analysis (after each step, I would recommend examining the contents of the dat2 object to better appreciate what the code is doing).
How to do a meta-analysis using RVE?
The current “state-of-the-art” [@polanin2017review] way to model these dependencies and avoid underestimating standard errors is to use robust variance estimates [RVE; @hedges2010robust; @tanner2016handling]. I performed my meta-analysis using RVE for correlated effects in the robumeta R package [@fisher2015robumeta].
Is the linear regression model the same as the mixed effect model?
Models of this sort can be fitted with the function rma () from the metafor package. Consequently, if one were to set vi = 0 v i = 0 for all outcomes, then the standard linear regression model and the mixed-effects meta-regression model are actually identical (with σ2 σ 2 denoting the same parameter as τ 2 τ 2 ).
Which is the best method for meta analysis?
Advanced methods in meta-analysis: Multivariate approach and meta-regression. Statistics in Medicine, 21 (4), 589-624. The conditional logistic model (also called hypergeometric-normal model) can be used to meta-analyze odds ratios (obtained from 2×2 table data).
What do you need to know about a meta-analysis?
Quick Meta-Analysis Intro •a set of statistical methods and techniques for combining and contrasting the findings from studies examining a common phenomenon •key idea:•quantify the outcome (usually some measure of effect or association) and its variance in each study and use this data in further analyses (averaging, modeling, meta- regression, …)
What can I find on the METAFOR website?
On this website, you can find: some news concerning the package and/or its development, a log of the package updates that have been made over the years, a to-do list and a description of planned features to be implemented in the future,
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.