UA cloudflare authentication

 

Evaluating the Fit of Sequential G-DINA Model Using Limited-Information Measures

Simple item page
dc.contributor.authorMa, Wenchao
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-09-28T19:34:01Z
dc.date.available2023-09-28T19:34:01Z
dc.date.issued2020
dc.description.abstractLimited-information fit measures appear to be promising in assessing the goodness-of-fit of dichotomous response cognitive diagnosis models (CDMs), but their performance has not been examined for polytomous response CDMs. This study investigates the performance of the M-ord statistic and standardized root mean square residual (SRMSR) for an ordinal response CDM-the sequential generalized deterministic inputs, noisy "and" gate model. Simulation studies showed that the M-ord statistic had well-calibrated Type I error rates, but the correct detection rates were influenced by various factors such as item quality, sample size, and the number of response categories. In addition, the SRMSR was also influenced by many factors and the common practice of comparing the SRMSR against a prespecified cut-off (e.g., .05) may not be appropriate. A set of real data was analyzed as well to illustrate the use of M-ord statistic and SRMSR in practice.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationMa, W. (2019). Evaluating the Fit of Sequential G-DINA Model Using Limited-Information Measures. In Applied Psychological Measurement (Vol. 44, Issue 3, pp. 167–181). SAGE Publications. https://doi.org/10.1177/0146621619843829
dc.identifier.doi10.1177/0146621619843829
dc.identifier.orcidhttps://orcid.org/0000-0002-6763-0707
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11444
dc.languageEnglish
dc.language.isoen_US
dc.publisherSage
dc.subjectcognitive diagnosis
dc.subjectordinal response
dc.subjectmodel-data fit
dc.subjectgoodness-of-fit
dc.subjectlimited information
dc.subjectsequential G-DINA
dc.subjectDIAGNOSTIC CLASSIFICATION MODELS
dc.subjectSELECTION
dc.subjectSocial Sciences, Mathematical Methods
dc.subjectPsychology, Mathematical
dc.titleEvaluating the Fit of Sequential G-DINA Model Using Limited-Information Measuresen_US
dc.typeArticle
dc.typetext

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
10.11770146621619843829.pdf
Size:
299.73 KB
Format:
Adobe Portable Document Format
Download

Collections

Research and Publications - Department of Gender and Race Studies