Analiza Componentelor Principale pentru date Categoriale (CATPCA)

Cristian Opariuc-Dan


In many cases, the basic assumptions of parametric exploratory factor analysis are not met and yet even in these cases, the technique is used. There is the risk of inducing significant errors that could invalidate the factor analysis model. To avoid such situations, we can use another technique, available for ordinal or even nominal variables, less known and used, called "Principal Components Analysis for Categorical Data". This article aims at an introduction to these methods of data analysis. The article begins with a fictional example illustrating the configuration and analysis of results provided by SPSS for Windows for CATPCA (Categorical Principal Components Analysis).


non-parametric analysis;nonparametric factor analysis;principal components


Meulman, J., Heiser, W., & SPSS, Inc. (2007). PASW Categories 18. Illinois: SPSS Inc.

Opariuc-Dan, C. (2009). Statistică aplicată în științele socio-umane. Noțiuni de bază. Statistici univariate. Cluj-Napoca: ASCR.


  • There are currently no refbacks.

Copyright (c) 2015 Cristian Opariuc-Dan

Asociatia de Psihologie Industriala si Organizationala
Strada Grigore Moisil, nr. 42, sector 2, București, cod poștal 023796

Creative Commons License
This work by Psihologia Resurselor Umane is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at