A deflated indicators approach for estimating second-order reflective models through PLS-PM: an empirical illustration

The paper provides a procedure aimed at obtaining more interpretable second-order models estimated with the partial least squares-path modeling. Advantages in interpretation stem from the separation of the two sources of influence on the data. As a matter of fact, in hierarchical models effects on m...

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Bibliographic Details
Published in:Journal of applied statistics 2014-10, Vol.41 (10), p.2222-2239
Main Authors: Nitti, M., Ciavolino, E.
Format: Article
Language:English
Subjects:
Applied statistics
Assignment problem
deflated indicators
Empirical analysis
Estimating
Estimating techniques
high-order construct model
Illustrations
Indicators
Least squares method
Mathematical models
OQ-45
PLS-PM
psychological assessment
Separation
Studies
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Summary:The paper provides a procedure aimed at obtaining more interpretable second-order models estimated with the partial least squares-path modeling. Advantages in interpretation stem from the separation of the two sources of influence on the data. As a matter of fact, in hierarchical models effects on manifest variables (MVs) are assigned to both first-order (specific) factors and second-order (general) factors. In order to separate these overlapping contributions, MVs are deflated from the effect of the specific latent variables (LVs) and used as indicators of the second-order LV. A case study is presented in order to illustrate the application of the proposed method.
ISSN:0266-4763
1360-0532
DOI:10.1080/02664763.2014.909786