Process / pipelinedimension-reduction
Factor Analysis
Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data.
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Sources
- Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press. DOI: 10.1037/10366-000 ↗
- Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI: 10.1007/BF02289343 ↗
- Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. DOI: 10.1177/001316446002000116 ↗
Related methods
Referenced by
Analysis of Variance (ANOVA)AutoencoderBayesian Statistical InferenceCanonical Correlation AnalysisHierarchical ClusteringIndependent Component AnalysisLinear Discriminant Analysis (Classification)Multiple Regression AnalysisMultivariate Quantitative Content AnalysisPrincipal Component AnalysisPrincipal Component Risk FactorsQ-MethodologyRobust Factor AnalysisRobust PCASemantic DifferentialStructural Equation ModelingUMAP