Aggregate-Data Meta-Analysis with Generalized Linear Mixed Models

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Documentation for package ‘metaGLMM’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

as.data.frame.metaGLMM	Convert a 'metaGLMM' Fit to Aggregate-Row Data
as_metafor_data	Create Study-Level Data for 'metafor' Workflows
chu2020	dataset of Chu et al. (2020)
ci_metaGLMM	Legacy Confidence-Interval Dispatcher
confint.metaGLMM	Confidence Intervals for a 'metaGLMM' Fit
confint_AN	Wald Confidence Intervals
confint_GSBC	Experimental Godambe-Calibrated Bartlett Intervals
confint_PL	Profile-Likelihood Confidence Intervals
confint_SBC	Simple Bartlett-Corrected Confidence Intervals
forest	Forest Plots for 'metaGLMM' Fits
forest.metaGLMM	Draw a Forest Plot
likelihood	Evaluate the aggregate-data GLMM negative log likelihood.
long2020	dataset of Long et al. (2020)
make_ll_fun	Build the quasi-Monte Carlo likelihood function used by 'metaGLMM()'.
make_ll_fun.fast	Build the fast likelihood function using Gaussian closed form or GHQ.
metaGLMM	Fit an Aggregate-Data Generalized Linear Mixed-Effects Meta-Analysis
metaGLMM_family	Create a custom aggregate-data family specification.
mle2_fit	Extract the Internal 'mle2' Fit
predict.metaGLMM	Predict from a 'metaGLMM' Fit
profile_ll	Evaluate a Profile-Likelihood Ratio
profile_ll_sbc	Evaluate a Simple Bartlett-Corrected Profile Ratio
rutter2021	dataset of Rutter et al. (2021)
summary.metaGLMM	Summarize a 'metaGLMM' Fit