@inproceedings{79fc0d65873a4380b46546908908fd6a,
title = "The comparison of two input statistics for heuristic cognitive diagnosis",
abstract = "Cognitive diagnosis models of educational test performance decompose ability in a domain into a set of specific binary skills called attributes. (Non-)mastery of attributes documents an examinee{\textquoteright}s strengths and weaknesses in the domain as a profile of mental aptitude. Distinct attribute profiles define classes of intellectual proficiency to which examinees can be assigned. Nonparametric, model-free classification methods have been proposed as heuristic or approximate alternatives to maximum likelihood estimation procedures for assigning examinees to proficiency classes. These classification techniques use as input a statistic obtained by aggregating each examinee{\textquoteright}s test item scores into a profile of attribute sum-scores. This study demonstrates that clustering examinees into proficiency classes based on their item scores rather than on their attribute sum-score profiles results in a more accurate classification of examinees.",
author = "K{\"o}hn, {Hans Friedrich} and Chiu, {Chia Yi} and Brusco, {Michael J.}",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media New York 2013.; 77th Annual Meeting of the Psychometric Society, 2012 ; Conference date: 09-07-2012 Through 12-07-2012",
year = "2013",
doi = "10.1007/978-1-4614-9348-8_21",
language = "English (US)",
isbn = "9781461493471",
series = "Springer Proceedings in Mathematics and Statistics",
publisher = "Springer",
pages = "335--343",
editor = "{van der Ark}, {L. Andries} and Millsap, {Roger E.} and Bolt, {Daniel M.} and Woods, {Carol M.}",
booktitle = "New Developments in Quantitative Psychology - Presentations from the 77th Annual Psychometric Society Meeting",
address = "Germany",
}