Functions for simple fixed and random effects meta-analysis
for two-sample comparison of binary outcomes. Draws standard summary
plots and computes odds ratios and tests for association and
heterogeneity

Functions for simple fixed and random effects meta-analysis
for two-sample comparisons. Draws standard summary
plots, funnel plots, and computes odds ratios and tests for
association and heterogeneity

Functions for simple fixed and random effects meta-analysis
for two-sample comparisons and cumulative meta-analyses. Draws standard
summary plots, funnel plots, and computes odds ratios and tests for
association and heterogeneity

Functions for simple fixed and random effects meta-analysis
for two-sample comparisons and cumulative meta-analyses. Draws standard
summary plots, funnel plots, and computes summaries and tests for
association and heterogeneity

Functions for simple fixed and random effects
meta-analysis for two-sample comparisons and cumulative
meta-analyses. Draws standard summary plots, funnel plots, and
computes summaries and tests for association and heterogeneity

Functions for simple fixed and random effects meta-analysis
for two-sample comparisons.  Draws standard summary
plots, funnel plots, and computes odds ratios and tests for
association and heterogeneity

Functions for simple fixed and random effects meta-analysis
for two-sample comparisons and cumulative meta-analyses of binary
data. Draws standard summary plots, funnel plots, and computes odds
ratios and tests for association and heterogeneity

Functions for simple fixed and random effects
meta-analysis for two-sample comparisons and cumulative
meta-analyses. Draws standard summary plots, funnel plots, and
computes summaries and tests for association and heterogeneity.

R Implementation of the Metalog Distribution
c(
person("Isaac", "Faber", email = "isaacfab@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4478-9598")),
person("Jongbin", "Jung", email = "me@jongbin.com", role = c("aut")))
Implementation of the metalog distribution in R.
The metalog distribution is a modern, highly flexible, data-driven distribution.
Metalogs are developed by Keelin (2016) <doi:10.1287/deca.2016.0338>.
This package provides functions to build these distributions from raw data.
Resulting metalog objects are then useful for exploratory and probabilistic analysis.
Isaac Faber [aut, cre] (<https://orcid.org/0000-0002-4478-9598>),
Jongbin Jung [aut]