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Confidence Regions and Approximate p-values for Classical and Non Symmetric Correspondence Analysis

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  • Eric J. Beh
  • Rosaria Lombardo

Abstract

Recently, a procedure was developed for constructing 100(1–α)% confidence ellipses for points in a low-dimensional plot obtained from performing classical correspondence analysis. This article reviews the construction of confidence regions for classical and non symmetric correspondence analysis and proposes a simple procedure for determining p-values of each of the points in this space. Such features enable the researcher to determine the statistical significance of a category to the association structure between the categorical variables being analyzed. They also reflect the information contained in dimensions higher than those that typically allow for a visual inspection of the association structure.

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  • Eric J. Beh & Rosaria Lombardo, 2015. "Confidence Regions and Approximate p-values for Classical and Non Symmetric Correspondence Analysis," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(1), pages 95-114, January.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:1:p:95-114
    DOI: 10.1080/03610926.2013.768665
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    Cited by:

    1. Lombardo, Rosaria & Camminatiello, Ida & D'Ambra, Antonello & Beh, Eric J., 2021. "Assessing the Italian tax courts system by weighted three-way log-ratio analysis," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    2. Rosaria Lombardo & Eric J. Beh & Francesco Prattichizzo & Giuseppe Lucisano & Antonio Nicolucci & Björn Eliasson & Hanne Krage Carlsen & Rosalba La Grotta & Valeria Pellegrini & Antonio Ceriello, 2024. "Testing and Visualization of Associations in Three-Way Contingency Tables: A Study of the Gender Gap in Patients with Type 1 Diabetes and Cardiovascular Complications," Mathematics, MDPI, vol. 12(14), pages 1-13, July.

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