Package: weightr 2.0.2

Kathleen M. Coburn

weightr: Estimating Weight-Function Models for Publication Bias

Estimates the Vevea and Hedges (1995) weight-function model. By specifying arguments, users can also estimate the modified model described in Vevea and Woods (2005), which may be more practical with small datasets. Users can also specify moderators to estimate a linear model. The package functionality allows users to easily extract the results of these analyses as R objects for other uses. In addition, the package includes a function to launch both models as a Shiny application. Although the Shiny application is also available online, this function allows users to launch it locally if they choose.

Authors:Kathleen M. Coburn [aut, cre], Jack L. Vevea [aut]

weightr_2.0.2.tar.gz
weightr_2.0.2.zip(r-4.7-any)weightr_2.0.2.zip(r-4.6-any)
weightr_2.0.2.tar.gz(r-4.7-any)weightr_2.0.2.tar.gz(r-4.6-any)
weightr_2.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
weightr/json (API)

# Install 'weightr' in R:
install.packages('weightr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • dat.bangertdrowns2004 - Studies on the Effectiveness of Writing-to-Learn Interventions
  • dat.gatb - Studies of the Predictive Validity of the General Ability Subscale of the General Aptitude Test Battery
  • dat.smith - Studies From Smith, Glass, and Miller's (1980) Meta-Analysis of Psychotherapy Outcomes

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.47 score 49 scripts 548 downloads 6 mentions 4 exports 17 dependencies

Last updated from:af3c9bc0df. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK133
source / vignettesOK189
linux-releaseOK124
windows-develOK89
windows-releaseOK62
wasm-releaseOK121

Exports:densityfunnelshiny_weightrweightfunct

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr