uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
A Simulation Study of Polychoric Instrumental Variable Estimation in Structural Equation Models
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Tsinghua University .
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2016 (English)In: Structural Equation Modeling: A Multidisciplinary Journal, ISSN ISSN: 1070-5511 (Print) 1532-8007 (Online), Vol. 23, no 5, 680-694 p.Article in journal (Refereed) Published
Abstract [en]

Data collected from questionnaires are often in ordinal scale. Unweighted least squares

(ULS), diagonally weighted least squares (DWLS) and normal-theory maximum likelihood

(ML) are commonly used methods to fit structural equation models. Consistency of these

estimators demands no structural misspecification. In this article, we conduct a simulation

study to compare the equation-by-equation polychoric instrumental variable (PIV) estimation

with ULS, DWLS, and ML. Accuracy of PIV for the correctly specified model and

robustness of PIV for misspecified models are investigated through a confirmatory factor

analysis (CFA) model and a structural equation model with ordinal indicators. The effects of

sample size and nonnormality of the underlying continuous variables are also examined. The

simulation results show that PIV produces robust factor loading estimates in the CFA model

and in structural equation models. PIV also produces robust path coefficient estimates in the

model where valid instruments are used. However, robustness highly depends on the validity

of instruments.

Place, publisher, year, edition, pages
2016. Vol. 23, no 5, 680-694 p.
Keyword [en]
factor analysis, model misspecification, ordinal data, robustness
National Category
Social Sciences
Research subject
Statistics
Identifiers
URN: urn:nbn:se:uu:diva-302736DOI: 10.1080/10705511.2016.1189334OAI: oai:DiVA.org:uu-302736DiVA: diva2:967402
Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2016-09-08

Open Access in DiVA

No full text

Other links

Publisher's full text
By organisation
Department of Statistics
Social Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 55 hits
ReferencesLink to record
Permanent link

Direct link