Classification accuracy and consistency under Item Response
Theory
Computes classification accuracy and consistency under
Item Response Theory by the approach proposed by Lee, Hanson &
Brennen (2002) and Lee (2010) or the approach proposed by
Rudner (2001, 2005). For dichotomous IRT models.

Computes classification accuracy and consistency under Item Response Theory by the approach proposed by Lee, Hanson & Brennen (2002) and Lee (2010) or the approach proposed by Rudner (2001, 2005). For dichotomous IRT models.

Computes classification accuracy and consistency under Item Response Theory by the approach proposed by Lee, Hanson & Brennen (2002) and Lee (2010) or the approach proposed by Rudner (2001, 2005).

Classification Accuracy and Consistency under Item Response
Theory
Computes classification accuracy and consistency indices under Item Response Theory. Implements the total score IRT-based methods in Lee, Hanson & Brennen (2002) and Lee (2010), the IRT-based methods in Rudner (2001, 2005), and the total score nonparametric methods in Lathrop & Cheng (2014). For dichotomous and polytomous tests.

Conjunctive Analysis of Case Configurations
c(
person(given = "Asier", family = "Moneva", email = "amoneva@nscr.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2156-0213")),
person(given = "Miriam", family = "Esteve", email = "miriam.estevec@umh.es", role = "aut"),
person(given = "Timothy C.", family = "Hart", email = "thart@ut.edu", role = "aut")
)
A set of functions to conduct Conjunctive Analysis of Case Configurations (CACC) as described in Miethe, Hart, and Regoeczi (2008) <doi:10.1007/s10940-008-9044-8>, and identify and quantify situational clustering in dominant case configurations as described in Hart (2019) <doi:10.1177/0011128719866123>. Initially conceived as an exploratory technique for multivariate analysis of categorical data, CACC has developed to include formal statistical tests that can be applied in a wide variety of contexts. This technique allows examining composite profiles of different units of analysis in an alternative way to variable-oriented methods.
dplyr, ggplot2, rlang, stats, tibble, tidyr
Asier Moneva [aut, cre] (<https://orcid.org/0000-0002-2156-0213>),
Miriam Esteve [aut],
Timothy C. Hart [aut]