Multiple correspondence analysis (MCA) is a multivariate method for analyzing multidimensional contingency tables. General software procedures to perform MCA are available. Among them SAS Proc CORRESP, SPAD CORMU procedure and the mca function of the MASS library in S-PLUS are probably the most used. However, CORRESP and CORMU output is different from that of mca function. The aim of this short note is showing how to obtain from mca function results compatible with those achieved with SAS or SPAD. A modified code is proposed in order to obtain the same coordinate system computed by SAS and SPAD. Moreover, the computation of the contributions of the levels of the factors to the inertia explained by each axis, the squared cosine of each factor level and the re-evaluation of the inertia explained by each axis have been added in order to improve the interpretations of the results of the decomposition. (copyright) 2005 Elsevier Ireland Ltd. All rights reserved.

Multiple correspondence analysis in S-PLUS / F. Ambrogi, E. Biganzoli, P. Boracchi. - In: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - ISSN 0169-2607. - 79:2(2005), pp. 161-167.

Multiple correspondence analysis in S-PLUS

F. Ambrogi
Primo
;
E. Biganzoli
Secondo
;
P. Boracchi
Ultimo
2005

Abstract

Multiple correspondence analysis (MCA) is a multivariate method for analyzing multidimensional contingency tables. General software procedures to perform MCA are available. Among them SAS Proc CORRESP, SPAD CORMU procedure and the mca function of the MASS library in S-PLUS are probably the most used. However, CORRESP and CORMU output is different from that of mca function. The aim of this short note is showing how to obtain from mca function results compatible with those achieved with SAS or SPAD. A modified code is proposed in order to obtain the same coordinate system computed by SAS and SPAD. Moreover, the computation of the contributions of the levels of the factors to the inertia explained by each axis, the squared cosine of each factor level and the re-evaluation of the inertia explained by each axis have been added in order to improve the interpretations of the results of the decomposition. (copyright) 2005 Elsevier Ireland Ltd. All rights reserved.
article; computer aided design; computer program; data analysis; decomposition; dystocia; mathematical computing
Settore MED/01 - Statistica Medica
2005
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/11148
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