caa a22 4500 606241760 CHVBK 20210128101314.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s11336-013-9372-y doi (NATIONALLICENCE)springer-10.1007/s11336-013-9372-y Consistency of Nonparametric Classification in Cognitive Diagnosis [Elektronische Daten] [Shiyu Wang, Jeff Douglas] Latent class models for cognitive diagnosis have been developed to classify examinees into one of the 2 K attribute profiles arising from a K-dimensional vector of binary skill indicators. These models recognize that response patterns tend to deviate from the ideal responses that would arise if skills and items generated item responses through a purely deterministic conjunctive process. An alternative to employing these latent class models is to minimize the distance between observed item response patterns and ideal response patterns, in a nonparametric fashion that utilizes no stochastic terms for these deviations. Theorems are presented that show the consistency of this approach, when the true model is one of several common latent class models for cognitive diagnosis. Consistency of classification is independent of sample size, because no model parameters need to be estimated. Simultaneous consistency for a large group of subjects can also be shown given some conditions on how sample size and test length grow with one another. The Psychometric Society, 2013 cognitive diagnosis nationallicence nonparametric classification nationallicence large sample theory nationallicence Wang Shiyu University of Illinois at Urbana-Champaign, Champaign, IL, USA aut Douglas Jeff University of Illinois at Urbana-Champaign, Champaign, IL, USA aut Psychometrika Springer US; http://www.springer-ny.com 80/1(2015-03-01), 85-100 0033-3123 80:1<85 2015 80 11336 https://doi.org/10.1007/s11336-013-9372-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11336-013-9372-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Shiyu University of Illinois at Urbana-Champaign, Champaign, IL, USA aut NATIONALLICENCE 700 1- Douglas Jeff University of Illinois at Urbana-Champaign, Champaign, IL, USA aut NATIONALLICENCE 773 0- Psychometrika Springer US; http://www.springer-ny.com 80/1(2015-03-01), 85-100 0033-3123 80:1<85 2015 80 11336