Application of categorical principal component analysis in the study of ovine production systems in Ciego de Ávila province - Torres, Verena; Serrano, J. O.; Martínez Melo, J.; Fonseca, N.; Borroto, Angela; Mazorra, C. A. (Cuban Journal of Agricultural Science, 2021)
The application of categorical principal component analysis is presented, with 22 qualitative variables measured in the study of ovine production systems in Ciego de Ávila province. The mathematical description of the method is stated using the loss function that is minimized by applying alternating least squares, which contemplate the transformation of any qualitative variable into variables of quantitative nature through optimal scaling. Cronback coefficient was used to measure the reliability of the questionnaire. Crossover tables were determined to verify the association among variables using the contingency coefficient, which is based on χ2 and its significance. All the processes were carried out using the IBM-SPSS program, version 22. The application of the categorical principal components analysis allowed to identify categorical variables that explained the greatest variance in ovine production system in Ciego de Ávila province. Key words: Qualitative variation, production systems, multivariable analysis