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https://doi.org/10.21256/zhaw-20487| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Item fit statistics for Rasch analysis : can we trust them? |
| Autor/-in: | Müller, Marianne |
| et. al: | No |
| DOI: | 10.1186/s40488-020-00108-7 10.21256/zhaw-20487 |
| Erschienen in: | Journal of Statistical Distributions and Applications |
| Band(Heft): | 7 |
| Heft: | 5 |
| Erscheinungsdatum: | 28-Aug-2020 |
| Verlag / Hrsg. Institution: | Springer |
| ISSN: | 2195-5832 |
| Sprache: | Englisch |
| Schlagwörter: | Rasch model; Chi-square test statistics; Outfit and infit statistics; Conditional probability |
| Fachgebiet (DDC): | 510: Mathematik |
| Zusammenfassung: | Aim: To compare fit statistics for the Rasch model based on estimates of unconditional or conditional response probabilities. Background: Using person estimates to calculate fit statistics can lead to problems because the person estimates are biased. Conditional response probabilities given the total person score could be used instead. Methods: Data sets are simulated which fit the Rasch model. Type I error rates are calculated and the distributions of the fit statistics are compared with the assumed normal or chi-square distribution. Parametric bootstrap is used to further study the distributions of the fit statistics. Results: Type I error rates for unconditional chi-square statistics are larger than expected even for moderate sample sizes. The conditional chi-square statistics maintain the significance level. Unconditional outfit and infit statistics have asymmetric distributions with means slighly below 1. Conditional outfit and infit statistics have reduced Type I error rates. Conclusions: Conditional residuals should be used. If only unconditional residuals are available parametric bootstrapping is recommended to calculate valid p-values. Bootstrapping is also necessary for conditional outfit statistics. For conditional infit statistics the adjusted rule-of-thumb critical values look useful. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/20487 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2020_Mueller_Item-fit-statistics-for-Rasch-analysis.pdf | 713.55 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Müller, M. (2020). Item fit statistics for Rasch analysis : can we trust them? Journal of Statistical Distributions and Applications, 7(5). https://doi.org/10.1186/s40488-020-00108-7
Müller, M. (2020) ‘Item fit statistics for Rasch analysis : can we trust them?’, Journal of Statistical Distributions and Applications, 7(5). Available at: https://doi.org/10.1186/s40488-020-00108-7.
M. Müller, “Item fit statistics for Rasch analysis : can we trust them?,” Journal of Statistical Distributions and Applications, vol. 7, no. 5, Aug. 2020, doi: 10.1186/s40488-020-00108-7.
MÜLLER, Marianne, 2020. Item fit statistics for Rasch analysis : can we trust them? Journal of Statistical Distributions and Applications. 28 August 2020. Bd. 7, Nr. 5. DOI 10.1186/s40488-020-00108-7
Müller, Marianne. 2020. “Item Fit Statistics for Rasch Analysis : Can We Trust Them?” Journal of Statistical Distributions and Applications 7 (5). https://doi.org/10.1186/s40488-020-00108-7.
Müller, Marianne. “Item Fit Statistics for Rasch Analysis : Can We Trust Them?” Journal of Statistical Distributions and Applications, vol. 7, no. 5, Aug. 2020, https://doi.org/10.1186/s40488-020-00108-7.
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