Package: RM.weights 2.0

RM.weights: Weighted Rasch Modeling and Extensions using Conditional Maximum Likelihood

Rasch model and extensions for survey data, using Conditional Maximum likelihood (CML). Carlo Cafiero, Sara Viviani, Mark Nord (2018) <doi:10.1016/j.measurement.2017.10.065>.

Authors:Carlo Cafiero, Sara Viviani, Mark Nord

RM.weights_2.0.tar.gz
RM.weights_2.0.zip(r-4.7-any)RM.weights_2.0.zip(r-4.6-any)RM.weights_2.0.zip(r-4.5-any)
RM.weights_2.0.tgz(r-4.6-any)RM.weights_2.0.tgz(r-4.5-any)
RM.weights_2.0.tar.gz(r-4.7-any)RM.weights_2.0.tar.gz(r-4.6-any)
RM.weights_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RM.weights/json (API)

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

On CRAN:

Conda:

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

1.49 score 1 stars 31 scripts 298 downloads 8 exports 56 dependencies

Last updated from:ec3742aef8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK209
linux-release-x86_64OK167
macos-release-arm64OK214
macos-oldrel-arm64OK167
windows-develOK100
windows-releaseOK102
windows-oldrelOK117
wasm-releaseOK145

Exports:equating.funEWaldtestICC.funPC.wprob.assignRM.wRT.threstab.weight

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestevaluatefarverfastmapfontawesomeforeignFormulafsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglifecyclemagrittrmemoisemimennetpsychotoolsR6rappdirsRColorBrewerrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrtinytexvctrsviridisLitewithrxfunyaml