Effect size calculation

NNT()

Calculate the number needed to treat (NNT)

se.from.p()

Calculate the standard error from the effect size and p-value

pool.groups()

Pool the results of two treatment arms

Small-study effects & Publication bias

eggers.test()

Perform Egger's test of the intercept

find.outliers()

Find Statistical Outliers in a Meta-Analysis

InfluenceAnalysis()

Influence Diagnostics

gosh.diagnostics()

Identify studies contributing to heterogeneity patterns found in GOSH plots

pcurve()

Perform a p-curve analysis

Power analysis

power.analysis()

A priori power calculator

power.analysis.subgroup()

A priori power calculator for subgroup contrasts

Meta-regression & Subgroups

multimodel.inference()

Perform multimodel inference with a meta-regression model

subgroup.analysis.mixed.effects()

Subgroup analysis using a mixed-effects model

Multilevel Meta-Analysis

mlm.variance.distribution()

Calculate \(I\)-squared and the variance distribution for multilevel meta-analysis models

Network Meta-Analysis

direct.evidence.plot()

Plot for direct evidence proportions in a network meta-analysis using netmeta

sucra()

Calculate the Surface Under the Cumulative Ranking score of from a network meta-analysis

Risk of bias

rob.summary()

Create a RevMan-style risk of bias summary chart

Data sets

ThirdWave

'Third-Wave' cognitive behavioral interventions for perceived stress in college students dataset

MVRegressionData

Toy Dataset for Multivariate Meta-Regression

NetDataGemtc

Toy Dataset for Network Meta-Analyses using the gemtc package

NetDataNetmeta

Toy Dataset for Network Meta-Analysis using the netmeta package

m.gosh

GOSH plot dataset

Package

dmetar

dmetar: Companion R package for the guide 'Doing Meta-Analysis in R'