Factor Analysis of Society’s Moral State Indices in European Countries

1009

Abstract

The paper presents the instrument and the results of factor analysis of developmental and interaction characteristics dynamics that define the index of the moral state of society, developed by the Institute of Psychology, Russian Academy of Sciences. The alternative way of confirmatory factor analysis and Trained Markov Networks revealed a number of developmental patterns of problematic characteristics that indicate usage appropriateness of this index. The advantages of the applied type of factor analysis include: the possibility of finding estimates of free parameters of the model via direct methods (and not by iteration), that guarantee an unambiguous and optimal solution, flexible means of studying the factor interactions and the applicability of covariance and correlation matrices of arbitrary structure for the analysis. Markov Networks, in turn, revealed new types of indicators that are inaccessible to conventional approaches.

General Information

Keywords: morality, the index of the moral state of society, factor analysis, the Markov Networks

Journal rubric: Social Psychology

Article type: scientific article

For citation: Kuravsky L.S., Yurevitch A.V., Marmalyuk P.A., Ivanova E.G. Factor Analysis of Society’s Moral State Indices in European Countries. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education, 2010. Vol. 15, no. 1, pp. 94–110. (In Russ., аbstr. in Engl.)

References

  1. Kramer G. Matematicheskie metody statistiki. M., 1976.
  2. Kuravskii L. S., Kornienko P. A. Primenenie neironnyh setei dlya identifikacii lokusov kolichestvennyh priznakov v psihogenetike. Neirokomp'yutery: razrabotka i primenenie. 2007. № 4.
  3. Kuravskii L. S., Marmalyuk P. A., Baranov S. N., Abramochkina V.I ., Petrova E. A. Faktornyi analiz rezul'tatov veivlet-preobrazovanii longityudnyh dannyh kak novyi metod issledovaniya dinamicheskih harakteristik slozhnyh sistem. Neirokomp'yutery: razrabotka i primenenie. 2009.№ 9.
  4. Yurevich A. V. Nravstvennost' kak psihologicheskaya problema // Voprosy psihologii. 2009. № 4.
  5. Yurevich A. V., Ushakov D. V. Makropsihologiya kak novaya oblast' psihologicheskih issledovanii // Voprosy psihologii. 2007. № 4.
  6. Yurevich A. V., Ushakov D. V., Capenko I. P. Kolichestvennaya ocenka akropsihologicheskogo sostoyaniya sovremennogo rossiiskogo obshestva // Psihologicheskii zhurnal. 2007. № 4.
  7. Bollen K. A. Structural equations with latent variables. New York, 1989.
  8. Jöreskog K. G. Estimation and testing of simplex models. British Journal of Mathematical and Statistical Psychology. Vol. 23.
  9. Kuravsky L. S., Baranov S. N. The concept of multifactor Markov networks and its application to forecasting and diagnostics of technical systems // In: Proc. Condition Monitoring 2005, Cambridge, United Kingdom, 2005.
  10. Kuravsky L. S., Baranov S. N. Development of the wavelet-based confirmatory factor analysis for monitoring of system factors // In: Proc. 5th International Conference on Condition Monitoring & Machinery Failure Prevention Technologies, Edinburgh, United Kingdom, 2008.
  11. Kuravsky L. S., Baranov S. N. Neural networks in fatigue damage recognition: diagnostics and statistical analysis // In: Proc. 11th International Congress on Sound and Vibration, St.-Petersburg, Russia, 2004.
  12. Kuravsky L. S., Kornienko P. A. On the approach to identifying quantitative trait loci in behavior genetics. In: Proc. 2nd World Congress on Engineering Asset Management and 4th International Conference on Condition Monitoring, Harrogate, United Kingdom, 2007.
  13. Neale M. C., Cardon L. R. Methodology for genetic studies of twins and families. Dordrecht, the Netherlands, Kluwer Academic Publishers, 1992.

Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, Dean of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-3375-8446, e-mail: l.s.kuravsky@gmail.com

Andrei V. Yurevitch, Doctor of Psychology, Deputy director of the Institute of Psychology, Corresponding member, Russian Academy of Science, Moscow, Russia, e-mail: yurevich@psychol.ras.ru

Pavel A. Marmalyuk, PhD in Engineering, Head of the Laboratory of Psychology and Applied Software, Moscow State University of Psychology & Education, associate professor, Department of Information Technologies, Moscow State University of Psychology & Education, Moscow, Russia, e-mail: ykk.mail@gmail.com

Evgeniya G. Ivanova, Psychologist, Applied Informatics Chair, Department of Information Technologies, Moscow State University of Psychology and Education, Russia, e-mail: ivanova_jenny@mail.ru

Metrics

Views

Total: 2305
Previous month: 9
Current month: 10

Downloads

Total: 1009
Previous month: 0
Current month: 3