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Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable
Abstract
We consider a model in which one observes multiple indicators and multiple causes of a single latent variable. In terms of the multivariate regression of the indicators on the causes, the model implies restrictions of two types: (i) the regression coefficient matrix has rank one, (ii) the residual variance-covariance matrix satisfies a factor analysis model with one common factor. The first type of restriction is familiar to econometricians and the second to psychometricians. We derive the maximum-likelihood estimators and their asymptotic variance-covariance matrix. Two alternative “limited information” estimators are also considered and compared with the maximum-likelihood estimators in terms of efficiency.
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Cited by
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Specification, evaluation, and interpretation of structural equation models
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Diamantopoulos, A., & Siguaw, J. A. (2006) · British Journal of Management · doi:10.1111/j.1467-8551.2006.00500.x · Cited by 3,410
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
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Metadata
- Authors
- Jöreskog, K. G., & Goldberger, A. S.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1975-09
- Volume
- 70
- Issue
- 351a
- Pages
- 631-639
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2021641691
- Cited by
- 1,595
- References
- 0
- FWCI
- 11.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jöreskog, K. G., & Goldberger, A. S. (1975). Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1975.10482485
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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