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Psychological Science and Education

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 1814-2052

ISSN (online): 2311-7273


License: CC BY-NC 4.0

Started in 1996

Published 6 times a year

Free of fees
Open Access Journal


Application of an Alternative Method of Canfirmatory Factor Analysis (Based on the Matherials of Phonemic Speech Perception Research of American Schoolchildren) 766


Abramochkina V.I.
Graduate student, Chair of Applied Informatics (in Psychology), Department of Informational Technologies, Moscow State University of Psychology and Education, Moscow, Russia

Kuravsky L.S.
Doctor of Engineering, Dean of the Computer Science Faculty , Moscow State University of Psychology and Education , Moscow, Russia

Petrova E.A.
Graduate student, Chair of Applied Informatics (in Psychology), Department of Informational Technologies, Moscow State University of Psychology and Education, Moscow, Russia

The research of phonemic speech perception of American school children revealed shortcomings of traditional confirmatory factor analysis. An alternative version of this method was developed. The new version of confirmatory factor analysis suggests examination of factor model free (spare) parameters interrelation. It allows finding parameters directly providing for single optimal solution. The essence of this method is to build redefined equations set, which is resolved directly, and testing adequacy of obtained set with statistical fit indices. The adequacy of obtained model is determined by chi-square statistic, which allows checking the hypothesis about presentability of sampling variances and covariances of latent variables that constitute the right-hand part of the overdetermined equations set, and by the components of variances and co-variances of latent variables contained in the analyzing model. The developed alternative method of confirmative factor analysis also allows assessing statistical value of model's components. The results of examination of free parameters by alternative version of factor analysis didn't show significant difference from results of traditional factor analysis. These findings are encouraging and future applications of the new approach are discussed.

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