irtQ
Unidimensional Item Response Theory Modeling
Fit unidimensional item response theory (IRT) models to test data, which includes both dichotomous and polytomous items, calibrate pretest item parameters, estimate examinees' abilities, and examine the IRT model-data fit on item-level in different ways as well as provide useful functions related to IRT analyses such as IRT model-data fit evaluation and differential item functioning analysis. The bring.flexmirt() and write.flexmirt() functions were written by modifying the read.flexmirt() function (Pritikin & Falk (2022) doi:10.1177/0146621620929431). The bring.bilog() and bring.parscale() functions were written by modifying the read.bilog() and read.parscale() functions, respectively (Weeks (2010) doi:10.18637/jss.v035.i12). The bisection() function was written by modifying the bisection() function (Howard (2017, ISBN:9780367657918)). The code of the inverse test characteristic curve scoring in the est_score() function was written by modifying the irt.eq.tse() function (González (2014) doi:10.18637/jss.v059.i07). In est_score() function, the code of weighted likelihood estimation method was written by referring to the Pi(), Ji(), and Ii() functions of the catR package (Magis & Barrada (2017) doi:10.18637/jss.v076.c01).
- Version1.0.0
- R versionR (≥ 4.3)
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release07/17/2025
Documentation
Team
- Hwanggyu LimMaintainerShow author details
- Jorge GonzálezShow author detailsRolesContributor
- David MagisShow author detailsRolesContributor
- James HowardShow author detailsRolesContributor
- Joshua PritikinShow author detailsRolesContributor
- Jonathan P WeeksShow author detailsRolesContributor
- Craig S. WellsShow author detailsRolesContributor
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Dependencies
- Imports13 packages