This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Find sources: "Factor analysis" – news · newspapers · books · scholar · JSTOR(August 2023) (Learn how and when to remove this message)
Statistical method
This article is about factor loadings. For factorial design, see Factorial experiment.
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modelled as linear combinations of the potential factors plus "error" terms, hence factor analysis can be thought of as a special case of errors-in-variables models.[1]
Simply put, the factor loading of a variable quantifies the extent to which the variable is related to a given factor.[2]
A common rationale behind factor analytic methods is that the information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Factor analysis is commonly used in psychometrics, personality psychology, biology, marketing, product management, operations research, finance, and machine learning. It may help to deal with data sets where there are large numbers of observed variables that are thought to reflect a smaller number of underlying/latent variables. It is one of the most commonly used inter-dependency techniques and is used when the relevant set of variables shows a systematic inter-dependence and the objective is to find out the latent factors that create a commonality.
^Jöreskog, Karl G. (1983). "Factor Analysis as an Errors-in-Variables Model". Principals of Modern Psychological Measurement. Hillsdale: Erlbaum. pp. 185–196. ISBN 0-89859-277-1.
^Bandalos, Deborah L. (2017). Measurement Theory and Applications for the Social Sciences. The Guilford Press.
Factoranalysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved...
In statistics, confirmatory factoranalysis (CFA) is a special form of factoranalysis, most commonly used in social science research. It is used to test...
suitable for ANOVA analysis is the completely randomized experiment with a single factor. More complex experiments with a single factor involve constraints...
In multivariate statistics, exploratory factoranalysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set...
algebra, factoranalysis (for a discussion of the differences between PCA and factoranalysis see Ch. 7 of Jolliffe's Principal Component Analysis), Eckart–Young...
critical/judgmental) neuroticism (sensitive/nervous vs. resilient/confident) When factoranalysis is applied to personality survey data, semantic associations between...
Research & Education Association. ISBN 978-0-87891-982-6. "Dimensional Analysis or the Factor Label Method". Mr Kent's Chemistry Page. "Identity property of multiplication"...
Multiple factoranalysis (MFA) is a factorial method devoted to the study of tables in which a group of individuals is described by a set of variables...
In statistics, factoranalysis of mixed data or factorial analysis of mixed data (FAMD, in the French original: AFDM or Analyse Factorielle de Données...
several techniques including the new statistical technique of common factoranalysis applied to the English-language trait lexicon to elucidate the major...
method. LDA is also closely related to principal component analysis (PCA) and factoranalysis in that they both look for linear combinations of variables...
modeling psychological data. These methods include psychometrics, factoranalysis, experimental designs, and Bayesian statistics. The article also discusses...
several variables, such as by factoranalysis, regression analysis, or principal component analysis Principal component analysis – transformation of a sample...
English psychologist known for work in statistics, as a pioneer of factoranalysis, and for Spearman's rank correlation coefficient. He also did seminal...
Point factoranalysis (PFA) is a systemic bureaucratic method for determining a relative score for a job. Jobs can then be banded into grades, and the...
those coordinates. The sub-space found with principal component analysis or factoranalysis is expressed as a dense basis with many non-zero weights which...
the latent factors from factoranalysis) within path-analysis-style equations (which sociologists inherited from Wright and Duncan). The factor-structured...
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called...
frequent user of factoranalysis (a statistical procedure for finding underlying factors in data). Cattell also developed new factor analytic techniques...
exposure to specific factors or components in FactorAnalysis or Principal Component Analysis Add-on factor - sometimes called load factor This disambiguation...
describe the central oppositions in the data. As in factoranalysis or principal component analysis, the first axis is the most important dimension, the...
both made important contributions to the theory and application of factoranalysis, a statistical method developed and used extensively in psychometrics...
Factoranalysis of information risk (FAIR) is a taxonomy of the factors that contribute to risk and how they affect each other. It is primarily concerned...
Look up Factor or factor in Wiktionary, the free dictionary. Factor, a Latin word meaning "who/which acts", may refer to: Factor (agent), a person who...
profile analysis and latent class analysis as from a multinomial distribution. The manifest variables in factoranalysis and latent profile analysis are continuous...