Cargando…
A Monte Carlo study of IRTree models’ ability to recover item parameters
Item response tree (IRTree) models are theorized to extract response styles from self-report data by utilizing multidimensional item response theory (IRT) models based on theoretical decision processes. Despite the growing popularity of the IRTree framework, there has been little research that has s...
Autores principales: | Alarcon, Gene M., Lee, Michael A., Johnson, Dexter |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025501/ https://www.ncbi.nlm.nih.gov/pubmed/36949921 http://dx.doi.org/10.3389/fpsyg.2023.1003756 |
Ejemplares similares
-
Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
por: Meiser, Thorsten, et al.
Publicado: (2023) -
Sample Size Requirements for Applying Mixed Polytomous Item Response Models: Results of a Monte Carlo Simulation Study
por: Kutscher, Tanja, et al.
Publicado: (2019) -
A Stan tutorial on Bayesian IRTree models: Conventional models and explanatory extension
por: Xue, Mingfeng, et al.
Publicado: (2023) -
Using IRTree Models to Promote Selection Validity in the Presence of Extreme Response Styles
por: Quirk, Victoria L., et al.
Publicado: (2023) -
Investigating the Applicability of Alignment—A Monte Carlo Simulation Study
por: Wen, Congcong, et al.
Publicado: (2022)