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Applying the Rasch sampler to identify aberrant responding through person fit statistics under fixed nominal α-level.
J Appl Meas. 2014; 15(3):276-91.JA

Abstract

Testing hypotheses on a respondent's individual fit under the Rasch model requires knowledge of the distributional properties of a person fit statistic. We argue that the Rasch Sampler (Verhelst, 2008), a Markov chain Monte Carlo algorithm for sampling binary data matrices from a uniform distribution, can be applied for simulating the distribution of person fit statistics with the Rasch model in the same way as it used to test for other forms of misfit. Results from two simulation studies are presented which compare the approach to the original person fit statistics based on normalization formulas. Simulation 1 shows the new approach to hold the expected Type I error rates while the normalized statistics deviate from the nominal alpha-level. In Simulation 2 the power of the new approach was found to be approximately the same or higher than for the normalized statistics under most conditions.

Authors+Show Affiliations

Department of Research Methods in Education, Friedrich Schiller University Jena, 07737 Jena, Germany, christian.spoden@uni-jena.de.No affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

24992251

Citation

Spoden, Christian, et al. "Applying the Rasch Sampler to Identify Aberrant Responding Through Person Fit Statistics Under Fixed Nominal Α-level." Journal of Applied Measurement, vol. 15, no. 3, 2014, pp. 276-91.
Spoden C, Fleischer J, Leutner D. Applying the Rasch sampler to identify aberrant responding through person fit statistics under fixed nominal α-level. J Appl Meas. 2014;15(3):276-91.
Spoden, C., Fleischer, J., & Leutner, D. (2014). Applying the Rasch sampler to identify aberrant responding through person fit statistics under fixed nominal α-level. Journal of Applied Measurement, 15(3), 276-91.
Spoden C, Fleischer J, Leutner D. Applying the Rasch Sampler to Identify Aberrant Responding Through Person Fit Statistics Under Fixed Nominal Α-level. J Appl Meas. 2014;15(3):276-91. PubMed PMID: 24992251.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Applying the Rasch sampler to identify aberrant responding through person fit statistics under fixed nominal α-level. AU - Spoden,Christian, AU - Fleischer,Jens, AU - Leutner,Detlev, PY - 2014/7/4/entrez PY - 2014/7/6/pubmed PY - 2014/9/26/medline SP - 276 EP - 91 JF - Journal of applied measurement JO - J Appl Meas VL - 15 IS - 3 N2 - Testing hypotheses on a respondent's individual fit under the Rasch model requires knowledge of the distributional properties of a person fit statistic. We argue that the Rasch Sampler (Verhelst, 2008), a Markov chain Monte Carlo algorithm for sampling binary data matrices from a uniform distribution, can be applied for simulating the distribution of person fit statistics with the Rasch model in the same way as it used to test for other forms of misfit. Results from two simulation studies are presented which compare the approach to the original person fit statistics based on normalization formulas. Simulation 1 shows the new approach to hold the expected Type I error rates while the normalized statistics deviate from the nominal alpha-level. In Simulation 2 the power of the new approach was found to be approximately the same or higher than for the normalized statistics under most conditions. SN - 1529-7713 UR - https://www.unboundmedicine.com/medline/citation/24992251/Applying_the_Rasch_sampler_to_identify_aberrant_responding_through_person_fit_statistics_under_fixed_nominal_α_level_ DB - PRIME DP - Unbound Medicine ER -