Computational Aspects of Psychometric Methods and Beyond

Authors: Patrícia Martinková
Publication year: 2024
Publication type: Abstrakt
Periodical: IMPS 2024 Abstracts
Projects: Research of Excellence on Digital Technologies and Wellbeing
Bibliographic citation: MARTINKOVÁ, Patrícia. Computational Aspects of Psychometric Methods and Beyond. In: IMPS 2024 Abstracts. Prague: IMPS, 2024, S. 173-173. Dostupné z: https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2024_abstracts.pdf?1720733361#page=211
ID: 601127
Online record: View online record

Abstract

ZÁKLADNÍ ÚDAJE: IMPS 2024 Abstracts. Prague: IMPS, 2024. s. 173-173. [IMPS 2024: Annual Meeting of the Psychometric Society. 16.07.2024-19.07.2024, Prague]. ABSTRAKT: This talk introduces the research expanding upon the topics of the recently published book “Computational Aspects of Psychometric Methods: With R” (Martinková & Hladká, 2023). Focusing first on inter-rater reliability (IRR), we describe a flexible method for assessing heterogeneity in IRR with variance components models (Martinková et al., 2023) and discuss the relationship between the IRR and false positive rate (Bartoš & Martinková, 2024). Furthermore, we introduce innovative approaches for assessing item functioning and detecting heterogeneity in responses to multi-item measurements, proposing new iterative methods (Hladká et al., 2024a, 2024b) and Bayesian estimation algorithms (Pavlech & Martinková, 2024). We also discuss approaches incorporating more complex data, such as item wording (Štěpánek et al., 2023). Finally, we provide an overview of the software implementation, highlighting the ShinyItemAnalysis R package and interactive application (Martinková & Drabinová, 2018) and its new extendability option via add-on modules (Martinková et al., 2024).