Object

Title: A polytomous item response theory models using R

Title in english:

Politomiczne modele teorii odpowiedzi na pozycje testowe w programie R

Creator:

Brzezińska, Justyna

Description:

Ekonometria = Econometrics, 2016, Nr 2 (52), s. 43-52

Abstrakt:

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

Publisher:

Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu

Place of publication:

Wrocław

Date:

2016

Resource Type:

artykuł

Resource Identifier:

doi:10.15611/ekt.2016.2.04 ; oai:dbc.wroc.pl:36059

Language:

eng

Relation:

Ekonometria = Econometrics, 2016, Nr 2 (52)

Rights:

Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy

Access Rights:

Dla wszystkich zgodnie z licencją

License:

CC BY-NC-ND 3.0 PL

Location:

Uniwersytet Ekonomiczny we Wrocławiu

Group publication title:

Ekonometria = Econometrics

Format:

application/pdf

Edition name Date
A polytomous item response theory models using R Jun 11, 2022
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