Factor analysis and categorial principal component analysis: comparative analysis and practical application for processing of questionnaire survey results

Authors: Fomina E.E. Published: 13.09.2017
Published in issue: #10(60)/2017  
DOI: 10.18698/2306-8477-2017-10-473  
Category: The Humanities in Technical University | Chapter: Social sciences  
Keywords: factor analysis, CatPCA algorithm, principal component analysis, questionnaire survey

The questionnaire survey is one of the main tools of studying the state of public opinion in the work of the sociologist. The primary result of the survey is usually a database that requires further in-depth analysis and search for relationships among variables being studied. To solve this problem a factor analysis and categorial principal component analysis can be applied. It allows making obtained results meaningful. Despite the fact that using these methods one problem is solved, they include different algorithms for determining integral characteristics, so the problem of selecting the appropriate method is relevant. The article compares factor analysis and categorial principal component analysis both from a theoretical position and from the point of view of practical application. An example ofprocessing of questionnaire survey results is considered, and methodological recommendations are offered.

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