LSAT6

A well-known dichotomous response dataset from the Law School Admission Test (LSAT),
Section 6, as used in Thissen (1982).

datasets

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>).

Hwanggyu Lim

irtQ

Unidimensional Item Response Theory Modeling

LSAT6 function

A data frame with 1,000 rows and 5 columns, where each row represents a unique
examinee's response pattern to five dichotomously scored items (0 = incorrect, 1 = correct).

Format

Hwanggyu Lim <a href="/link/hglim83%40gmail.com?package=irtQ&version=1.0.0" data-mini-rdoc="irtQ::hglim83@gmail.com">hglim83@gmail.com</a>

Author

LSAT6 Data — LSAT6

Hwanggyu Lim <a href='mailto:hglim83@gmail.com'>hglim83@gmail.com</a>

LSAT6: LSAT6 Data

Description

Usage

Arguments

Format

Author

References