Estimation In Generalized Logistic Regression Models For DIF Detection

Result code in IS VaVaI
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Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Estimation In Generalized Logistic Regression Models For DIF Detection
Original language description
ZÁKLADNÍ ÚDAJE: Estimation In Generalized Logistic Regression Models For DIF Detection. [IMPS 2021: The Annual Meeting of the Psychometric Society. Virtual, 20.07.2021-23.07.2021]. ABSTRAKT: Generalized logistic regression models are extensions of logistic regression method for differential item functioning (DIF) detection among binary data which account for possibility of guessing or inattention when responding. In this talk we will discuss several approaches to estimate item parameters including nonlinear least squares, maximum likelihood method and a newly implemented expectation-maximization algorithm. We will further propose a new algorithm based on parametric link function. Differences in estimation procedures will be illustrated with a simulation study and we will also show their implementation in the statistical software R including its package difNLR (Hladká & Martinková, 2020).
Czech name
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Czech description
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Project
<a href="/en/project/GA21-03658S" target="_blank" >GA21-03658S: Theoretical foundations of computational psychometrics</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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