@misc{Brzezińska_Justyna_A_2016,
 author={Brzezińska, Justyna},
 identifier={DOI: 10.15611/ekt.2016.2.04},
 year={2016},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Ekonometria = Econometrics, 2016, Nr 2 (52), s. 43-52},
 language={eng},
 abstract={Item response theory (IRT) is widely used in educational and psychological research to model how participants respond to test items in isolation and in bundles. Item response theory has replaced classical measurement theory as a framework for test development, scale constructions, scree reporting and test evaluation. The most popular of the item response models for multiple choice tests are the one-parameter (i. e. the Rasch model) and threeparameter models. This is the general framework for specifying the functional relationship between a respondent’s underlying latent trait level, commonly known as ability in educational testing, or the factor score in the factor analysis tradition and an item level stimulus. In this paper, arguments are offered for continuing research and applying multidimensional IRT models. The position is also taken that multi-parameter IRT models have potentially important roles to play in the advancement of measurement theory about which models to use should depend on model fit to the test data. All calculations are conducted in R available from CRAN which is a widely-used and well-known environment for statistical computing and graphics},
 title={A polytomous item response theory models using R},
 type={artykuł},
 keywords={IRT models, multidimensional IRT models, measurement theory, R software, modele teorii odpowiedzi na pozycje, IRT, wielowymiarowe modele IRT, teoria pomiaru, program R},
}