TY - GEN
T1 - Assessing the Dimensionality of the Latent Attribute Space in Cognitive Diagnosis Through Testing for Conditional Independence
AU - Lim, Youn Seon
AU - Drasgow, Fritz
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Cognitive diagnosis seeks to assess an examinee’s mastery of a set of cognitive skills called (latent) attributes. The entire set of attributes characterizing a particular ability domain is often referred to as the latent attribute space. The correct specification of the latent attribute space is essential in cognitive diagnosis because misspecifications of the latent attribute space result in inaccurate parameter estimates, and ultimately, in the incorrect assessment of examinees’ ability. Misspecifications of the latent attribute space typically lead to violations of conditional independence. In this article, the Mantel-Haenszel statistic (Lim & Drasgow in J Classif, 2019) is implemented to detect possible misspecifications of the latent attribute space by checking for conditional independence of the items of a test with parametric cognitive diagnosis models. The performance of the Mantel-Haenszel statistic is evaluated in simulation studies based on its Type-I-error rate and power.
AB - Cognitive diagnosis seeks to assess an examinee’s mastery of a set of cognitive skills called (latent) attributes. The entire set of attributes characterizing a particular ability domain is often referred to as the latent attribute space. The correct specification of the latent attribute space is essential in cognitive diagnosis because misspecifications of the latent attribute space result in inaccurate parameter estimates, and ultimately, in the incorrect assessment of examinees’ ability. Misspecifications of the latent attribute space typically lead to violations of conditional independence. In this article, the Mantel-Haenszel statistic (Lim & Drasgow in J Classif, 2019) is implemented to detect possible misspecifications of the latent attribute space by checking for conditional independence of the items of a test with parametric cognitive diagnosis models. The performance of the Mantel-Haenszel statistic is evaluated in simulation studies based on its Type-I-error rate and power.
KW - Cognitive diagnosis model
KW - Dimensionality
KW - Mantel-haenszel statistic
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U2 - 10.1007/978-3-030-01310-3_17
DO - 10.1007/978-3-030-01310-3_17
M3 - Conference contribution
AN - SCOPUS:85066110760
SN - 9783030013097
T3 - Springer Proceedings in Mathematics and Statistics
SP - 183
EP - 194
BT - Quantitative Psychology - 83rd Annual Meeting of the Psychometric Society, 2018
A2 - Wiberg, Marie
A2 - Culpepper, Steven
A2 - Janssen, Rianne
A2 - Molenaar, Dylan
A2 - González, Jorge
PB - Springer
T2 - 83rd Annual meeting of the Psychometric Society, 2018
Y2 - 9 July 2018 through 13 July 2018
ER -