Factor Analysis Revisited – How Many Factors are There?

DOI10.1080/03610918.2010.524332zbMath1205.62074OpenAlexW2063488999MaRDI QIDQ3072420

No author found.

Publication date: 3 February 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2010.524332

zbMATH Keywords

correlationfactor analysisprincipal components

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Measures of association (correlation, canonical correlation, etc.) (62H20)

Related Items (5)

Investigating the role of orthogonal and non – orthogonal rotation in multivariate factor analysis, in regard to the repeatability of the extracted factors: A simulation study ⋮ Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size ⋮ Common Factor Analysis versus Principal Component Analysis: A Comparison of Loadings by Means of Simulations ⋮ Parallel analysis approach for determining dimensionality in canonical correlation analysis ⋮ On the use of Cauchy integral formula for the embedding problem of discrete-time Markov chains

Cites Work

• Unnamed Item
• Influence functions of the Spearman and Kendall correlation measures
• High breakdown estimators for principal components: the projection-pursuit approach revis\-ited
• Determining the number of components from the matrix of partial correlations
• Robust factor analysis.
• A rationale and test for the number of factors in factor analysis
• Some necessary conditions for common-factor analysis
• Least Median of Squares Regression
• Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficiencies
• A Measure Of Association Based On Gin's Mean Difference

This page was built for publication: Factor Analysis Revisited – How Many Factors are There?