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The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions.

MacKenzie, Scott B., Podsakoff, Philip M., Jarvis, Cheryl Burke·2005·Journal of Applied Psychology

Abstract

The purpose of this study was to review the distinction between formative- and reflective-indicator measurement models, articulate a set of criteria for deciding whether measures are formative or reflective, illustrate some commonly researched constructs that have formative indicators, empirically test the effects of measurement model misspecification using a Monte Carlo simulation, and recommend new scale development procedures for latent constructs with formative indicators. Results of the Monte Carlo simulation indicated that measurement model misspecification can inflate unstandardized structural parameter estimates by as much as 400% or deflate them by as much as 80% and lead to Type I or Type II errors of inference, depending on whether the exogenous or the endogenous latent construct is misspecified. Implications of this research are discussed.

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Metadata

Authors
MacKenzie, S. B., Podsakoff, P. M., & Jarvis, C. B.
Venue
Journal of Applied Psychology
Published
2005-07
Volume
90
Issue
4
Pages
710-730
ISSN
  • 0021-9010 (ISSN-L)
  • 1939-1854
OpenAlex
W1988897250
Cited by
1,669
References
11
FWCI
39.76
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions. https://app.cochat.ai/papers/10.1037/0021-9010.90.4.710
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MacKenzie, S. B., Podsakoff, P. M., & Jarvis, C. B. (2005). The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions. Journal of Applied Psychology. https://doi.org/10.1037/0021-9010.90.4.710

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.