General Package for Meta-Analysis
Coerce to a data frame
Produce weighted bar plot of risk of bias assessment
Baujat plot to explore heterogeneity in meta-analysis
Calculate best linear unbiased predictor for meta object
Bubble plot to display the result of a meta-regression
Calculation of confidence intervals (based on normal approximation or ...
Calculate expected proportion of comparable studies with clinically im...
Drapery plot
Extract results from meta-analysis object
Forest plot to display the result of a meta-analysis
Forest plot to display the result of a meta-analysis
Forest plot to display the result of a cumulative meta-analysis
Forest plot to display the result of a leave-one-out meta-analysis
Funnel plot
Get default for a meta-analysis setting.
Create study labels in JAMA layout (deprecated function)
L'Abbé plot for meta-analysis with binary outcomes
Create study labels for forest plot
Transform data from pairwise comparisons to long arm-based format
Description of R object of class "meta"
meta: Brief overview of methods and general hints
Description of summary measures available in R package meta
Auxiliary functions for (back) transformations
Add pooled results from external analysis to meta-analysis
Test for funnel plot asymmetry
Cochrane review: Test for funnel plot asymmetry
Meta-analysis of binary outcome data
Combine and summarize meta-analysis objects
Meta-analysis of continuous outcome data
Meta-analysis of correlations
Meta-analysis of outcome data from Cochrane review
Cumulative meta-analysis
Generic inverse variance meta-analysis
Meta-analysis of incidence rates
Influence analysis in meta-analysis using leave-one-out method
Meta-analysis of single means
Merge results of two meta-analyses on the same data set
Meta-analysis of single proportions
Meta-analysis of single incidence rates
Meta-regression
Calculate the number needed to treat (NNT)
Conversion from log odds ratio to standardised mean difference
Transform meta-analysis data from two arm-based formats into contrast-...
Plot density of prediction distribution highlighting areas of clinical...
Print meta-analysis results
Print results of a cumulative meta-analysis
Print results of a leave-one-out meta-analysis
Cochrane review: summary of meta-analyses
Print detailed meta-analysis results
Radial plot
Import data of Cochrane intervention review
Import RevMan 4 data files (.mtv)
Import RevMan 5 analysis data
Risk of bias assessment
Print and change default meta-analysis settings in R package meta
Conversion from standardised mean difference to log odds ratio
Extract parts of longarm object
Extract parts of pairwise object
Return subset of longarm object
Return subset of pairwise object
Summary of meta-analysis results
Cochrane review: detailed summary of meta-analyses
Produce traffic light plot of risk of bias assessment
Trim-and-fill method to adjust for bias in meta-analysis
Cochrane review: trim-and-fill method
Update a meta-analysis object
Calculate absolute and percentage weights for meta-analysis
User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - common effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - three-level meta-analysis model; - generalised linear mixed model; - logistic regression with penalised likelihood for rare events; - Hartung-Knapp method for random effects model; - Kenward-Roger method for random effects model; - prediction interval; - statistical tests for funnel plot asymmetry; - trim-and-fill method to evaluate bias in meta-analysis; - meta-regression; - cumulative meta-analysis and leave-one-out meta-analysis; - import data from 'RevMan 5'; - produce forest plot summarising several (subgroup) meta-analyses.