Having your cake and eating it too: Multiple dimensions and a composite. (February 2020)
- Record Type:
- Journal Article
- Title:
- Having your cake and eating it too: Multiple dimensions and a composite. (February 2020)
- Main Title:
- Having your cake and eating it too: Multiple dimensions and a composite
- Authors:
- Wilson, Mark
Gochyyev, Perman - Abstract:
- Highlights: Focus is on contexts where both a uni- a multi-dimensional perspective is needed. Review the limitations of the earlier Hierarchical and Bifactor Models. Introduce the Composite Model, which actuates the two perspectives. Show how it 'has certain benefits over the other two models. Illustrate using an empirical example, and discuss further steps. Abstract: This paper first develops a framework for exploring options that one can have in psychometric modeling alternatives for multidimensional measurement situations. In particular, we focus on situations where there is seen to be value in both (i) the individual dimension outcomes (i.e., "having your cake"), and (ii) the summative combination of those multiple dimensions (i.e., 'eating it too"). We review the literature about this issue, mainly from the perspective of latent variable modeling. There have been three main modeling options used, (a) the Unidimensional and the Multidimensional-Covariance models, (b) the Bifactor model, and (c) the Hierarchical model. We describe a fourth model, the composite model, that we see as having certain advantages over the others. Following a specification of this model, we discuss its estimation, the use of a weighting schemes to create the composite, and the calculation of reliability for the composite. This is followed by an empirical example for which we show results from the different solutions for the models in the framework. In conclusion, we review the results, andHighlights: Focus is on contexts where both a uni- a multi-dimensional perspective is needed. Review the limitations of the earlier Hierarchical and Bifactor Models. Introduce the Composite Model, which actuates the two perspectives. Show how it 'has certain benefits over the other two models. Illustrate using an empirical example, and discuss further steps. Abstract: This paper first develops a framework for exploring options that one can have in psychometric modeling alternatives for multidimensional measurement situations. In particular, we focus on situations where there is seen to be value in both (i) the individual dimension outcomes (i.e., "having your cake"), and (ii) the summative combination of those multiple dimensions (i.e., 'eating it too"). We review the literature about this issue, mainly from the perspective of latent variable modeling. There have been three main modeling options used, (a) the Unidimensional and the Multidimensional-Covariance models, (b) the Bifactor model, and (c) the Hierarchical model. We describe a fourth model, the composite model, that we see as having certain advantages over the others. Following a specification of this model, we discuss its estimation, the use of a weighting schemes to create the composite, and the calculation of reliability for the composite. This is followed by an empirical example for which we show results from the different solutions for the models in the framework. In conclusion, we review the results, and issues discussed in the paper, consider the special case of educational and psychological testing, consider future directions for this work, and speculate about the possible uses of the Composite Model. … (more)
- Is Part Of:
- Measurement. Volume 151(2020)
- Journal:
- Measurement
- Issue:
- Volume 151(2020)
- Issue Display:
- Volume 151, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 151
- Issue:
- 2020
- Issue Sort Value:
- 2020-0151-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-02
- Subjects:
- BI-factor model -- Composite model -- Multidimensional model -- Hierarchical model
Weights and measures -- Periodicals
Measurement -- Periodicals
Measurement
Weights and measures
Periodicals
530.8 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02632241 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.measurement.2019.107247 ↗
- Languages:
- English
- ISSNs:
- 0263-2241
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5413.544700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12579.xml