Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26029
Title: The value of using test responses data for content validity: An application of the bifactor-MIRT to a nursing knowledge test
Authors: Cai, Y
Keywords: Bifactor multidimensional item response theory (bifactor-MIRT)
Content validity
Subject-matter experts (SME)
Test response data
Issue Date: 2015
Publisher: Churchill Livingstone
Source: Nurse education today, 2015 How to cite?
Journal: Nurse Education Today 
Abstract: Aim: This paper aimed 1) to argue for the values of using test response data for content validation, and b) to demonstrate this practice using bifactor-multidimensional item response theory (bifactor-MIRT) for nurse education. Method: The Nursing Knowledge Test (NKT) response data by 1491 nurse students from China were used for demonstration. Based on the content structure assumed by subject-matter experts (SME), a bifactor-MIRT model was constructed and tested. This involved five steps: dimensionality assessment, local dependence detection, model specification, calibrating and unit weighting. Results: Dimensionality assessment results confirmed the content structure assumed by SME. Through local dependence detection and calibrating (i.e., item parameter check), items suspected of contaminating content were detected and those producing substantive harm were removed or constrained. Finally, content contributions by items to the overall scale and to their subscales were obtained through unit weighting. Conclusion: Deficiencies residing in SME for content validation must raise attention. The study suggests the value of modeling test response data to compensate these deficiencies. The theoretical implication is discussed.
URI: http://hdl.handle.net/10397/26029
ISSN: 0260-6917
DOI: 10.1016/j.nedt.2015.05.014
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

20
Last Week
0
Last month
Checked on Mar 26, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.