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An Analysis and Synthesis of Multiple Correspondence Analysis, Optimal Scaling, Dual Scaling, Homogeneity Analysis and Other Methods for Quantifying Categorical Multivariate Data
Abstract
We discuss a variety of methods for quantifying categorical multivariate data. These methods have been proposed in many different countries, by many different authors, under many different names. In the first major section of the paper we analyze the many different methods and show that they all lead to the same equations for analyzing the same data. In the second major section of the paper we introduce the notion of a duality diagram, and use this diagram to synthesize the many superficially different methods into a single method.
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Cited by
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Carreté, L., Ksiezopolska, E., Pegueroles, C., Gómez-Molero, E., Saus, E., Iraola-Guzmán, S., Loska, D., Bader, O., Fairhead, C., & Gabaldón, T. (2018) · Current Biology · doi:10.1016/j.cub.2017.11.027 · Cited by 118
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Metadata
- Authors
- Tenenhaus, M., & Young, F. W.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1985-03
- Volume
- 50
- Issue
- 1
- Pages
- 91-119
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W1991596242
- Cited by
- 414
- References
- 0
- FWCI
- 15.97
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: An Analysis and Synthesis of Multiple Correspondence Analysis, Optimal Scaling, Dual Scaling, Homogeneity Analysis and Other Methods for Quantifying Categorical Multivariate Data. https://app.cochat.ai/papers/10.1007/bf02294151
- The paper
- Tenenhaus, M., & Young, F. W. (1985). An Analysis and Synthesis of Multiple Correspondence Analysis, Optimal Scaling, Dual Scaling, Homogeneity Analysis and Other Methods for Quantifying Categorical Multivariate Data. Psychometrika. https://doi.org/10.1007/bf02294151
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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.
