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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/23066

Title: Distinguishing valid from invalid causal indicator models
Authors: Cadogan, John W.
Lee, Nick
Issue Date: 2016
Publisher: © Taylor & Francis
Citation: CADOGAN, J.W. and LEE, N., 2016. Distinguishing valid from invalid causal indicator models. Measurement: Interdisciplinary Research & Perspectives, 14 (4), pp. 162-166.
Abstract: 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.
Description: 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
Version: Accepted for publication
DOI: 10.1080/15366367.2016.1264235
URI: https://dspace.lboro.ac.uk/2134/23066
Publisher Link: http://dx.doi.org/10.1080/15366367.2016.1264235
ISSN: 1536-6367
Appears in Collections:Published Articles (Business)

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