Paper #539

Título:

Analysis of matched matrices

Autor:

Michael Greenacre

Fecha:

Marzo 2001

Resumen:

We consider the joint visualization of two matrices which have common rows and columns, for example multivariate data observed at two time points or split accord-ing to a dichotomous variable. Methods of interest include principal components analysis for interval-scaled data, or correspondence analysis for frequency data or ratio-scaled variables on commensurate scales. A simple result in matrix algebra shows that by setting up the matrices in a particular block format, matrix sum and difference components can be visualized. The case when we have more than two matrices is also discussed and the methodology is applied to data from the International Social Survey Program.

Palabras clave:

Correspondence analysis, International Social Survey Program (ISSP), matched matrices, principal component analysis, singular-value decomposition

Códigos JEL:

C19, C88

Área de investigación:

Estadística, Econometría y Métodos Cuantitativos

Publicado en:

Journal of Applied Statistics, 30, 10, (2004), pp. 1101-1113

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