Higher-Order Models with Reflective Indicators: A Rejoinder to a Recent Call for their Abandonment

Author(s)
Dirk Temme, Adamantios Diamantopoulos
Abstract

Purpose - Higher-order factor models have recently been dismissed as a ‘misleading’, ‘meaningless’, and ‘needless’ approach for modeling multidimensional constructs (Lee and Cadogan, 2013; L&C, 2013 hereafter). The purpose of this paper is to show that – in contrast to L&C’s (2013) verdict – higher-order factor models are still a legitimate operationalization option for multidimensional constructs.
Design/methodology/approach - Basic conceptual and statistical premises of L&C’s (2013) arguments against higher-order factor models are scrutinized both conceptually and statistically as to their logic and validity.
Findings - A thorough analysis of L&C’s (2013) arguments shows that they are fundamentally flawed both conceptually and statistically, rendering their conclusions invalid.
Research limitations/implications - Researchers should not remove the well-established higher-order factor models from their methodological toolkit. Furthermore, empirical findings should not automatically be considered suspect simply because higher-factor models have been used to model multidimensional constructs.
Originality/value - So far L&C’s (2013) arguments against higher-order factor models have gone unchallenged in the literature. This rejoinder is a first, much needed attempt to protect applied researchers from getting the false impression that by using higher-factor models they rely on a ‘misleading’ or 'meaningless' modeling approach.

Organisation(s)
Department of Accounting, Innovation and Strategy
External organisation(s)
Bergische Universität Wuppertal
Journal
Journal of Modelling in Management
Volume
11
Pages
180-188
No. of pages
9
ISSN
1746-5664
DOI
https://doi.org/10.1108/JM2-05-2014-0037
Publication date
08-2015
Peer reviewed
Yes
Austrian Fields of Science 2012
502052 Business administration
Keywords
ASJC Scopus subject areas
General Decision Sciences, Strategy and Management, Management Science and Operations Research
Portal url
https://ucrisportal.univie.ac.at/en/publications/aa7f20ec-fc10-44a2-8e05-d3b8b9e56073