Package: irtQ 0.2.1

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>).

Authors:Hwanggyu Lim [aut, cre], Craig S. Wells [ctb], James Howard [ctb], Joshua Pritikin [ctb], Jonathan P Weeks [ctb], Jorge González [ctb], David Magis [ctb]