Package: rccme 0.0.1.9002

James Uanhoro

rccme: Regression Calibration for Classical Measurement Error

Contains functions to get calibrated latent trait estimates under assumption of classical measurement error.

Authors:James Uanhoro [aut, cre], Nivedita Bhaktha [ctb]

rccme_0.0.1.9002.tar.gz
rccme_0.0.1.9002.zip(r-4.7-any)rccme_0.0.1.9002.zip(r-4.6-any)rccme_0.0.1.9002.zip(r-4.5-any)
rccme_0.0.1.9002.tgz(r-4.6-any)rccme_0.0.1.9002.tgz(r-4.5-any)
rccme_0.0.1.9002.tar.gz(r-4.7-any)rccme_0.0.1.9002.tar.gz(r-4.6-any)
rccme_0.0.1.9002.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rccme/json (API)

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

Bug tracker:https://github.com/jamesuanhoro/rccme/issues

Pkgdown/docs site:https://jamesuanhoro.github.io

Datasets:

On CRAN:

Conda:

measurement-errorregression-calibrationquarto

3.30 score 5 scripts 1 exports 0 dependencies

Last updated from:c0670a373e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK111
source / vignettesOK176
linux-releaseOK139
macos-releaseOK119
macos-oldrelOK121
windows-develOK80
windows-releaseOK80
windows-oldrelOK96
wasm-releaseOK82

Exports:rccme_calib_me

Dependencies:

estress
Preamble | The model for affect | The model for withdraw | Summarise all models | Original paper for dataset
Rendered fromestress.qmdusingquarto::html

Last update: 2026-03-28
Started: 2026-03-28

global_warming
Preamble | Calibrating the scores | Run the regression | Original paper for dataset
Rendered fromprotest.qmdusingquarto::html

Last update: 2026-03-28
Started: 2026-03-28