Factor Analysis

S. P. Mukherjee (), Bikas K. Sinha and Asis Kumar Chattopadhyay ()
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S. P. Mukherjee: University of Calcutta, Department of Statistics
Bikas K. Sinha: Indian Statistical Institute
Asis Kumar Chattopadhyay: University of Calcutta, Department of Statistics

Chapter Chapter 10 in Statistical Methods in Social Science Research, 2018, pp 103-111 from Springer

Abstract: Abstract Factor Analysis is a method for modeling observed variables and their covariance structure, in terms of a smaller number of underlying unobservable factors. The factors are considered as broad concepts or ideas that may describe an observed phenomenon. Factor analysis may be considered to be a generalization of principal component method since here also we replace the large number of variables by a smaller number of unknown factors. However, the aim of principal component analysis is to explain the variance while factor analysis explains the covariance among the variables. Hence, factor analysis is a way to understand how the patterns of relationship between several variables are caused by a smaller number of latent variables, according to their common aspects. These hidden variables are called factors.

Keywords: Factor; Latent variable; Communality; Factor score; Rotation; Varimax (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/978-981-13-2146-7_10

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