Package: robumeta 2.0

robumeta: Robust Variance Meta-Regression

Functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.

Authors:Zachary Fisher [aut, cre], Elizabeth Tipton [aut], Hou Zhipeng [aut]

robumeta_2.0.tar.gz
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robumeta_2.0.tgz(r-4.4-any)robumeta_2.0.tgz(r-4.3-any)
robumeta_2.0.tar.gz(r-4.5-noble)robumeta_2.0.tar.gz(r-4.4-noble)
robumeta_2.0.tgz(r-4.4-emscripten)robumeta_2.0.tgz(r-4.3-emscripten)
robumeta.pdf |robumeta.html✨
robumeta/json (API)

# Install 'robumeta' in R:
install.packages('robumeta', repos = c('https://zackfisher.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/zackfisher/robumeta/issues

Datasets:
  • corrdat - Data for Fitting Correlated Effects Model
  • corrdat.sm - Data for Fitting Correlated Effects Model With Small-Sample Corrections
  • hedgesdat - Hedgesdat
  • hierdat - Data for Fitting Hierarchical Effects Model
  • oswald2013 - IAT Criterion-Related Correlations
  • oswald2013.ex1 - IAT Criterion-Related Correlations

On CRAN:

7.91 score 9 stars 4 packages 176 scripts 2.1k downloads 30 mentions 5 exports 0 dependencies

Last updated 4 years agofrom:149634925e. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winNOTENov 19 2024
R-4.5-linuxNOTENov 19 2024
R-4.4-winNOTENov 19 2024
R-4.4-macNOTENov 19 2024
R-4.3-winNOTENov 19 2024
R-4.3-macNOTENov 19 2024

Exports:forest.robugroup.centergroup.meanrobusensitivity

Dependencies:

robumeta Vignette

Rendered fromrobumetaVignette.pdf.asisusingR.rsp::asison Nov 19 2024.

Last update: 2017-05-29
Started: 2017-05-29