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Distinguishing valid from invalid causal indicator models

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journal contribution
posted on 2016-11-04, 13:54 authored by John Cadogan, Nick Lee
We highlight the difference between valid causal indicator models, that provide useful information on the variance of theoretical latent variables, and invalid causal indicator models, which do not. We suggest that invalid causal indicator models are of the type typically used in the causal indicator literature, and urge for research to reflect on how to advance the use of valid causal indicator models.

History

School

  • Business and Economics

Department

  • Business

Published in

Measurement: Interdisciplinary Research & Perspectives

Volume

14

Citation

CADOGAN, J.W. and LEE, N., 2016. Distinguishing valid from invalid causal indicator models. Measurement: Interdisciplinary Research & Perspectives, 14 (4), pp. 162-166.

Publisher

© Taylor & Francis

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2016-10-14

Publication date

2016

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in Measurement: Interdisciplinary Research & Perspectives on 07 Dec 2016, available online: http://dx.doi.org/10.1080/15366367.2016.1264235

ISSN

1536-6367

eISSN

1536-6359

Language

  • en

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