R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Beauducel, André (2024) R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates. Open Journal of Statistics, 14 (01). pp. 38-54. ISSN 2161-718X

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Abstract

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Item Type: Article
Subjects: Science Global Plos > Multidisciplinary
Depositing User: Unnamed user with email support@science.globalplos.com
Date Deposited: 09 Feb 2024 07:14
Last Modified: 09 Feb 2024 07:14
URI: http://ebooks.manu2sent.com/id/eprint/2487

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