The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The error term in formative measurement models: interpretation and modeling implications
Abstract
Purpose: To clarify the nature of the error term in formative measurement models, as it had been misinterpreted in prior research. Design/methodology/approach: The error term in formative measurement models is analytically contrasted with the measurement errors typically found in reflective measurement models. Findings: It is demonstrated that, unlike in reflective measurement, the error term in formative models is not measurement error but rather a disturbance representing non‐modeled causes. It is also shown that, under certain circumstances, the inclusion of an error term is not necessary/appropriate. Research limitations/implications: Focus is only on first‐order measurement models; higher‐order specifications are not considered. Originality/value: The paper helps researchers in their initial specification of formative measurement models as well as their evaluation of the subsequent model estimates, leading to better specifications for formative constructs.
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Cites
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549
Conventional wisdom on measurement: A structural equation perspective.
Bollen, K., & Lennox, R. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.110.2.305 · Cited by 3,618
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An assessment of the use of partial least squares structural equation modeling in marketing research
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0261-6 · Cited by 8,088
Partial least squares structural equation modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017) · Handbook of Market Research · doi:10.1007/978-3-319-05542-8_15-1 · Cited by 3,285
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
Testing measurement invariance of composites using partial least squares
Henseler, J., Ringle, C. M., & Sarstedt, M. (2016) · International Marketing Review · doi:10.1108/imr-09-2014-0304 · Cited by 2,964
Metadata
- Authors
- Diamantopoulos, A.
- Venue
- Journal of Modelling in Management
- Publisher
- Emerald
- Published
- 2006-01-01
- Volume
- 1
- Issue
- 1
- Pages
- 7-17
- ISSN
- 1746-5664 (ISSN-L)
- OpenAlex
- W2074967591
- Cited by
- 343
- References
- 2
- FWCI
- 19.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- Diamantopoulos, A. (2006). The error term in formative measurement models: interpretation and modeling implications. Journal of Modelling in Management. https://doi.org/10.1108/17465660610667775
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.