We address the problem of describing several categorical variables with a prediction purpose. We focus on methods in the multiblock modelling framework, each block being formed of the indicator matrix associated with each qualitative variable.We propose a method, called categorical multiblock Redundancy Analysis, based on a well-identified global optimization criterion which leads to an eigensolution. In comparison with usual procedures, such as logistic regression, the method is well- Adapted to the case of a large number of redundant explanatory variables. Practical uses of the proposed method are illustrated using an empirical example in the field of epidemiology. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Bougeard, S., Qannari, E. M., & Chauvin, C. (2010). Multiblock method for categorical variables. Application to the study of antibiotic resistance. In Proceedings of COMPSTAT 2010 - 19th International Conference on Computational Statistics, Keynote, Invited and Contributed Papers (pp. 389–396). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-7908-2604-3_36
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