Package: SNSequate 1.3-5

SNSequate: Standard and Nonstandard Statistical Models and Methods for Test Equating

Contains functions to perform various models and methods for test equating (Kolen and Brennan, 2014 <doi:10.1007/978-1-4939-0317-7> ; Gonzalez and Wiberg, 2017 <doi:10.1007/978-3-319-51824-4> ; von Davier et. al, 2004 <doi:10.1007/b97446>). It currently implements the traditional mean, linear and equipercentile equating methods. Both IRT observed-score and true-score equating are also supported, as well as the mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods. It also supports newest methods such that local equating, kernel equating (using Gaussian, logistic, Epanechnikov, uniform and adaptive kernels) with presmoothing, and IRT parameter linking methods based on asymmetric item characteristic functions. Functions to obtain both standard error of equating (SEE) and standard error of equating differences between two equating functions (SEED) are also implemented for the kernel method of equating.

Authors:Jorge Gonzalez [cre, aut], Daniel Leon Acuna [ctb]

SNSequate_1.3-5.tar.gz
SNSequate_1.3-5.zip(r-4.5)SNSequate_1.3-5.zip(r-4.4)SNSequate_1.3-5.zip(r-4.3)
SNSequate_1.3-5.tgz(r-4.4-any)SNSequate_1.3-5.tgz(r-4.3-any)
SNSequate_1.3-5.tar.gz(r-4.5-noble)SNSequate_1.3-5.tar.gz(r-4.4-noble)
SNSequate_1.3-5.tgz(r-4.4-emscripten)SNSequate_1.3-5.tgz(r-4.3-emscripten)
SNSequate.pdf |SNSequate.html
SNSequate/json (API)

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

Peer review:

Datasets:
  • ACTmKB - Scores on two 40-items ACT mathematics test forms
  • CBdata - Observed (raw) score values for two different tests
  • KB36 - Data on two 36-items test forms
  • KB36.1PL - Difficulty parameter estimates for KB36 data under a 1PL model
  • KB36_t - Data on two 36-items test forms
  • Math20EG - Scores on two 20-items mathematics tests.
  • Math20SG - Bivariate score frequencies on two 20-items mathematics tests.
  • SEPA - A sample of observed score values for two different forms of the SEPA test.

On CRAN:

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

1.41 score 26 scripts 677 downloads 30 exports 33 dependencies

Last updated 7 months agofrom:c575dca92b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 23 2024
R-4.5-winOKOct 23 2024
R-4.5-linuxOKOct 23 2024
R-4.4-winOKOct 23 2024
R-4.4-macOKOct 23 2024
R-4.3-winOKOct 23 2024
R-4.3-macOKOct 23 2024

Exports:bandwidthbandwidth.defaultBB.smoothBB.smooth.defaultBNP.eqBNP.eq.predictdiscrete.smoothdiscrete.smooth.defaulteqp.eqeqp.eq.defaultgofirt.eqirt.eq.defaultirt.linkirt.link.defaultker.eqker.eq.defaultle.eqle.eq.defaultlin.eqlin.eq.defaultloglin.smoothloglin.smooth.defaultmea.eqmea.eq.defaultPREpPREp.defaultSEEDSEED.defaultsim_unimodal

Dependencies:abindAkebbmlebdsmatrixclicodacrayonemdbookequateevaluategluehighrhmsknitrlatticelifecyclemagicMASSMatrixmomentsmvtnormnumDerivpkgconfigplyrprettyunitsprogressR6Rcpprlangstatmodvctrsxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Standard and Nonstandard Statistical Models and Methods for Test EquatingSNSequate-package SNSequate
Scores on two 40-items ACT mathematics test formsACTmKB
Automatic selection of the bandwidth parameter 'h'bandwidth bandwidth.default
Pre-smoothing using beta4 models.BB.smooth BB.smooth.default
Bayesian non-parametric model for test equatingBNP.eq
Prediction step for Bayesian non-parametric model for test equatingBNP.eq.predict
Observed (raw) score values for two different testsCBdata
Pre-smoothing using discrete kernels.discrete.smooth discrete.smooth.default
The equipercentile method of equatingeqp.eq eqp.eq.default
Functions to assess model fitting.gof
IRT methods for Test Equatingirt.eq irt.eq.default
IRT parameter linking methodsirt.link irt.link.default
Data on two 36-items test formsKB36
Data on two 36-items test formsKB36_t
Difficulty parameter estimates for KB36 data under a 1PL modelKB36.1PL
The Kernel method of test equatingker.eq ker.eq.default
Local equating methodsle.eq le.eq.default
The linear method of equatinglin.eq lin.eq.default
Pre-smoothing using log-linear models.loglin.smooth loglin.smooth.default
Scores on two 20-items mathematics tests.Math20EG
Bivariate score frequencies on two 20-items mathematics tests.Math20SG
The mean method of equatingmea.eq mea.eq.default
Percent relative errorPREp PREp.default
Take a matrix and sum blocks of rowsrowBlockSum
Standard error of equating differenceSEED SEED.default
A sample of observed score values for two different forms of the SEPA test.SEPA
Simulate test scores.sim_unimodal