Applying the Rasch sampler to identify aberrant responding through person fit statistics under fixed nominal α-level.
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In: Journal of applied measurement, Vol. 15, No. 3, 2014, p. 276-291.
Research output: Journal contributions › Journal articles › Research › peer-review
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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
Y1 - 2014
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.
AB - 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.
KW - Psychology
UR - http://www.scopus.com/inward/record.url?scp=84907249556&partnerID=8YFLogxK
M3 - Journal articles
C2 - 24992251
AN - SCOPUS:84907249556
VL - 15
SP - 276
EP - 291
JO - Journal of applied measurement
JF - Journal of applied measurement
SN - 1529-7713
IS - 3
ER -