Modelling Responses in Multi-Item Measurements with R and Shiny (Pre-Conference event of EAM 2025 - XI European Congress of Methodology)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00639244" target="_blank" >RIV/67985807:_____/25:00639244 - isvavai.cz</a>

Výsledek na webu

<a href="https://eam2025.eu/workshops/" target="_blank" >https://eam2025.eu/workshops/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Modelling Responses in Multi-Item Measurements with R and Shiny (Pre-Conference event of EAM 2025 - XI European Congress of Methodology)

Popis výsledku v původním jazyce

Item response analysis is crucial for developing high-quality educational and psychological assessments. It not only provides valuable insight into respondent behaviors or student performance but also informs evidence-based policies. Over the years, various methods have been proposed for modeling item responses based on respondent data. Recently, more complex data, such as item text wording, have also been harnessed with numerous analytical methods. This workshop equips participants with a deeper understanding of item response analysis and practical skills for performing it using traditional methods, regression models, item response theory (IRT), and machine learning techniques. We will start with a step-by-step development of IRT models, illustrating their relationships with traditional item characteristics and simpler regression models. Next, we will explore differential item functioning and measurement invariance – key concepts for detecting potentially biased items and a detailed understanding of student performance and respondent behavior across different social groups. The final part will be devoted to item text analysis using machine learning methods. The workshop follows selected chapters from “Computational Aspects of Psychometric Methods: With R”, authored by the instructors and published by CRC Press/Chapman C Hall in 2023. The course lectures will be complemented by practical exercises, allowing participants to apply the presented techniques using R, a free and open-source statistical software. We will utilize the ShinyItemAnalysis and difNLR packages, along with other R packages. Moreover, an interactive ShinyItemAnalysis application and its add-on modules will be used for hands-on training, enabling the participants to perform all necessary analyses in a user-friendly environment. Before the course, the participants will receive detailed instructions on how to install the necessary software. Previous experience with R is a plus, but the course is designed to be accessible even for R novices. References: Martinková, P., C Hladká, A. (2023). Computational Aspects of Psychometric Methods: With R. Chapman and Hall/CRC.

Název v anglickém jazyce

Modelling Responses in Multi-Item Measurements with R and Shiny (Pre-Conference event of EAM 2025 - XI European Congress of Methodology)

Popis výsledku anglicky

Item response analysis is crucial for developing high-quality educational and psychological assessments. It not only provides valuable insight into respondent behaviors or student performance but also informs evidence-based policies. Over the years, various methods have been proposed for modeling item responses based on respondent data. Recently, more complex data, such as item text wording, have also been harnessed with numerous analytical methods. This workshop equips participants with a deeper understanding of item response analysis and practical skills for performing it using traditional methods, regression models, item response theory (IRT), and machine learning techniques. We will start with a step-by-step development of IRT models, illustrating their relationships with traditional item characteristics and simpler regression models. Next, we will explore differential item functioning and measurement invariance – key concepts for detecting potentially biased items and a detailed understanding of student performance and respondent behavior across different social groups. The final part will be devoted to item text analysis using machine learning methods. The workshop follows selected chapters from “Computational Aspects of Psychometric Methods: With R”, authored by the instructors and published by CRC Press/Chapman C Hall in 2023. The course lectures will be complemented by practical exercises, allowing participants to apply the presented techniques using R, a free and open-source statistical software. We will utilize the ShinyItemAnalysis and difNLR packages, along with other R packages. Moreover, an interactive ShinyItemAnalysis application and its add-on modules will be used for hands-on training, enabling the participants to perform all necessary analyses in a user-friendly environment. Before the course, the participants will receive detailed instructions on how to install the necessary software. Previous experience with R is a plus, but the course is designed to be accessible even for R novices. References: Martinková, P., C Hladká, A. (2023). Computational Aspects of Psychometric Methods: With R. Chapman and Hall/CRC.

Druh

W - Uspořádání workshopu

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/EH22_008%2F0004583" target="_blank" >EH22_008/0004583: Excelentní výzkum v oblasti digitálních technologií a wellbeingu</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Místo konání akce

San Cristobal de La Laguna

Stát konání akce

ES - Španělské království

Datum zahájení akce

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Datum ukončení akce

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Celkový počet účastníků

5

Počet zahraničních účastníků

5

Typ akce podle státní přísl. účastníků

EUR - Evropská akce