Package: autoRasch 0.2.2

Feri Wijayanto

autoRasch: Semi-Automated Rasch Analysis

Performs Rasch analysis (semi-)automatically, which has been shown to be comparable with the standard Rasch analysis (Feri Wijayanto et al. (2021) <doi:10.1111/bmsp.12218>, Feri Wijayanto et al. (2022) <doi:10.3758/s13428-022-01947-9>, Feri Wijayanto et al. (2022) <doi:10.1177/01466216221125178>).

Authors:Feri Wijayanto [aut, cre], Ioan Gabriel Bucur [aut], Perry Groot [aut], Tom Heskes [aut], Karlien Mul [ctb], Baziel G.M. van Engelen [ctb]

autoRasch_0.2.2.tar.gz
autoRasch_0.2.2.tar.gz(r-4.5-noble)autoRasch_0.2.2.tar.gz(r-4.4-noble)
autoRasch_0.2.2.tgz(r-4.4-emscripten)autoRasch_0.2.2.tgz(r-4.3-emscripten)
autoRasch.pdf |autoRasch.html✨
autoRasch/json (API)

# Install 'autoRasch' in R:
install.packages('autoRasch', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

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

openblascppopenmp

3.00 score 253 downloads 24 exports 12 dependencies

Last updated 2 years agofrom:b1f02bacef. Checks:1 OK, 2 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-linux-x86_64NOTEApr 01 2025
R-4.4-linux-x86_64NOTEApr 01 2025

Exports:autoRaschOptionsbackward_searchcheck.unidimcheckRelcompute_scorecompute_scorescorResidcreateGroupfitStatsgenerate_datageneric_modelgpcmgpcm_difitemfitpcmpcm_difpersonfitplot_EVCplot_fitStatsplot_ICCplot_PImapplot_searchresidCorstepwise_search

Dependencies:codetoolsdoParallelforeachiteratorslavaanMASSmnormtnumDerivpbivnormquadprogRcppRcppArmadillo

autoRasch: The Semi-automated Rasch Analysis

Rendered fromsearch.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2022-10-19
Started: 2022-02-28

autoRasch: Working with the models

John Doe

Rendered frommodels.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2022-02-28
Started: 2022-02-28

Citation

To cite package ‘autoRasch’ in publications use:

Wijayanto F, Bucur I, Groot P, Heskes T (2022). autoRasch: Semi-Automated Rasch Analysis. R package version 0.2.2, https://CRAN.R-project.org/package=autoRasch.

Corresponding BibTeX entry: 

  @Manual{,
    title = {autoRasch: Semi-Automated Rasch Analysis},
    author = {Feri Wijayanto and Ioan Gabriel Bucur and Perry Groot and
      Tom Heskes},
    year = {2022},
    note = {R package version 0.2.2},
    url = {https://CRAN.R-project.org/package=autoRasch},
  }

Readme and manuals

autoRasch

R package for semi-automated Rasch analysis

Installation

# install.packages("remotes")
remotes::install_github("fwijayanto/autoRasch", build_manual = TRUE, build_vignettes = TRUE)

Usage

Please refers to the vignettes and function manual documentations which have been provided along within the package.

Help Manual

Help pageTopics
autoRasch: A package for semi-automatic Rasch analysisautoRasch
autoRasch Optimization Parameters SettingautoRaschOptions
Unidimensionality Checkcheck.unidim
Compute Reliability and Standard ErrorcheckRel summary.seprel
Compute the In-plus-out-of-questionnaire log likelihood (with DIF) (IPOQ-LL(-DIF))compute_score compute_scores summary.score
Multidimensional polytomous data set with 0.2 correlationcorrel02_multidim
Multidimensional polytomous data set with 0.3 correlationcorrel03_multidim
Multidimensional polytomous data set with 0.4 Correlationcorrel04_multidim
Multidimensional polytomous data set with 0.5 Correlationcorrel05_multidim
Multidimensional polytomous data set with 0.6 Correlationcorrel06_multidim
Create Mapping Matrix of DIF GroupscreateGroup
The Simulated Datasetdataset
Inhomogenous Dichotomous Data Setdicho_inh_dset
Uncorrelated Multidimensional Dichotomous Data Setdicho_md_dset
Fit statisticsfitStats itemfit personfit plot_fitStats summary.fit
Generate the artificial datasetgenerate_data
Estimation of the generic form of the modelsgeneric_model
Estimation of The Generalized Partial Credit Modelgpcm print.gpcm summary.gpcm
Estimation of The Generalized Partial Credit Model with DIFgpcm_dif print.gpcmdif summary.gpcmdif
Estimation of The Partial Credit Model (PCM)fitStats.pcm pcm print.pcm summary.pcm
Estimation of The Partial Credit Model with DIFfitStats.pcmdif pcm_dif print.pcmdif summary.pcmdif
Plot The Expected Value Curvesplot_EVC
Plot The Item Characteristic Curvesplot_ICC
Plot The Person-Item Mapplot_PImap
The Inhomogenous Polytomous Datasetpoly_inh_dset
Uncorrelated Multidimensional Polytomous Data Setpoly_md_dset
The Inhomogenous Polytomous Dataset containing DIF itemspolydif_inh_dset
Residual CorrelationcorResid residCor summary.ld
A Shorter Inhomogenous Polytomous Datasetshort_poly_data
A Shorter Polytomous Dataset with DIFshortDIF
Stepwise Selection Searchbackward_search plot_search print.search stepwise_search summary.search
Multi-testlets Polytomous Data Settestlets_dataset
Within-item Multidimensional Polytomous Data SetwithinItem_multidim