Combining Item Purification and Multiple Comparison Adjustment Methods in Detection of Differential Item Functioning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00572469" target="_blank" >RIV/67985807:_____/24:00572469 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/24:10464627 RIV/00216208:11410/24:10464627

Výsledek na webu

<a href="https://dx.doi.org/10.1080/00273171.2023.2205393" target="_blank" >https://dx.doi.org/10.1080/00273171.2023.2205393</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/00273171.2023.2205393" target="_blank" >10.1080/00273171.2023.2205393</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Combining Item Purification and Multiple Comparison Adjustment Methods in Detection of Differential Item Functioning

Popis výsledku v původním jazyce

Many of the differential item functioning (DIF) detection methods rely on a principle of testing for DIF item by item, while considering the rest of the items or at least some of them being DIF-free. Computational algorithms of these DIF detection methods involve the selection of DIF-free items in an iterative procedure called item purification. Another aspect is the need to correct for multiple comparisons, which can be done with a number of existing multiple comparison adjustment methods. In this article, we demonstrate that implementation of these two controlling procedures together may have an impact on which items are detected as DIF items. We propose an iterative algorithm combining item purification and adjustment for multiple comparisons. Pleasant properties of the newly proposed algorithm are shown with a simulation study. The method is demonstrated on a real data example.

Název v anglickém jazyce

Combining Item Purification and Multiple Comparison Adjustment Methods in Detection of Differential Item Functioning

Popis výsledku anglicky

Many of the differential item functioning (DIF) detection methods rely on a principle of testing for DIF item by item, while considering the rest of the items or at least some of them being DIF-free. Computational algorithms of these DIF detection methods involve the selection of DIF-free items in an iterative procedure called item purification. Another aspect is the need to correct for multiple comparisons, which can be done with a number of existing multiple comparison adjustment methods. In this article, we demonstrate that implementation of these two controlling procedures together may have an impact on which items are detected as DIF items. We propose an iterative algorithm combining item purification and adjustment for multiple comparisons. Pleasant properties of the newly proposed algorithm are shown with a simulation study. The method is demonstrated on a real data example.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA21-03658S" target="_blank" >GA21-03658S: Teoretické základy výpočetní psychometrie</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Multivariate Behavioral Research

ISSN

0027-3171

e-ISSN

1532-7906

Svazek periodika

59

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

16

Strana od-do

46-61

Kód UT WoS článku

000993582400001

EID výsledku v databázi Scopus

2-s2.0-85160094540