irtQ
Unidimensional Item Response Theory Modeling
Fit unidimensional item response theory (IRT) models to a mixture of dichotomous and polytomous data, calibrate online item parameters (i.e., pretest and operational items), 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).
- Version0.2.1
- R version≥ 4.1
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release08/25/2024
Documentation
Team
Hwanggyu Lim
James Howard
Show author detailsRolesContributorDavid Magis
Show author detailsRolesContributorJoshua Pritikin
Show author detailsRolesContributorCraig S. Wells
Show author detailsRolesContributorJonathan P Weeks
Show author detailsRolesContributorJorge González
Show author detailsRolesContributor
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- Imports13 packages