In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables.[1] It is commonly used by researchers when developing a scale (a scale is a collection of questions used to measure a particular research topic) and serves to identify a set of latent constructs underlying a battery of measured variables.[2] It should be used when the researcher has no a priori hypothesis about factors or patterns of measured variables.[3]Measured variables are any one of several attributes of people that may be observed and measured. Examples of measured variables could be the physical height, weight, and pulse rate of a human being. Usually, researchers would have a large number of measured variables, which are assumed to be related to a smaller number of "unobserved" factors. Researchers must carefully consider the number of measured variables to include in the analysis.[2] EFA procedures are more accurate when each factor is represented by multiple measured variables in the analysis.
EFA is based on the common factor model.[1] In this model, manifest variables are expressed as a function of common factors, unique factors, and errors of measurement. Each unique factor influences only one manifest variable, and does not explain correlations between manifest variables. Common factors influence more than one manifest variable and "factor loadings" are measures of the influence of a common factor on a manifest variable.[1] For the EFA procedure, we are more interested in identifying the common factors and the related manifest variables.
EFA assumes that any indicator/measured variable may be associated with any factor. When developing a scale, researchers should use EFA first before moving on to confirmatory factor analysis (CFA).[4] EFA is essential to determine underlying factors/constructs for a set of measured variables; while CFA allows the researcher to test the hypothesis that a relationship between the observed variables and their underlying latent factor(s)/construct(s) exists.[5]
EFA requires the researcher to make a number of important decisions about how to conduct the analysis because there is no one set method.
^ abcNorris, Megan; Lecavalier, Luc (17 July 2009). "Evaluating the Use of Exploratory Factor Analysis in Developmental Disability Psychological Research". Journal of Autism and Developmental Disorders. 40 (1): 8–20. doi:10.1007/s10803-009-0816-2. PMID 19609833. S2CID 45751299.
^ abFabrigar, Leandre R.; Wegener, Duane T.; MacCallum, Robert C.; Strahan, Erin J. (1 January 1999). "Evaluating the use of exploratory factor analysis in psychological research" (PDF). Psychological Methods. 4 (3): 272–299. doi:10.1037/1082-989X.4.3.272.
^Finch, J. F.; West, S. G. (1997). "The investigation of personality structure: Statistical models". Journal of Research in Personality. 31 (4): 439–485. doi:10.1006/jrpe.1997.2194.
^Worthington, Roger L.; Whittaker, Tiffany A J. (1 January 2006). "Scale development research: A content analysis and recommendations for best practices". The Counseling Psychologist. 34 (6): 806–838. doi:10.1177/0011000006288127. S2CID 146284440.
^Suhr, D. D. (2006). Exploratory or confirmatory factor analysis? (pp. 1-17). Cary: SAS Institute.
and 26 Related for: Exploratory factor analysis information
In multivariate statistics, exploratoryfactoranalysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set...
Wikimedia Commons has media related to Factoranalysis. A Beginner's Guide to FactorAnalysisExploratoryFactorAnalysis. A Book Manuscript by Tucker, L. &...
estimation of threshold parameters. Both exploratoryfactoranalysis (EFA) and confirmatory factoranalysis (CFA) are employed to understand shared variance...
In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical...
IRT analysis. Factoranalysis is at the core of psychological statistics. It has two schools: (1) ExploratoryFactoranalysis (2) Confirmatory Factor analysis...
components to keep in a principal component analysis or factors to keep in an exploratoryfactoranalysis. It is named after psychologist John L. Horn...
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...
negatively phrased items. Under exploratoryfactoranalysis the negatively phrased items have been found to load onto a second factor separate from the positively...
10 items that were determined through the highest factor loadings on the exploratoryfactoranalysis reported by Watson et al. (1988) in his original PANAS...
approach to test for discriminant validity on the item level is exploratoryfactoranalysis (EFA). Average variance extracted (AVE) Concurrent validity Construct...
Exploratory research is "the preliminary research to clarify the exact nature of the problem to be solved." It is used to ensure additional research is...
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...
can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features...
In statistics, factoranalysis of mixed data or factorial analysis of mixed data (FAMD, in the French original: AFDM or Analyse Factorielle de Données...
Explained variation Explanatory variable Exploratory data analysis Exploratoryfactoranalysis Exponential dispersion model Exponential distribution Exponential...
exploratory model modification – as when confirmatory factoranalysis (CFA) is applied to a random second-half of data following exploratoryfactor analysis...
An exploratory laparotomy is a general surgical operation where the abdomen is opened and the abdominal organs are examined for injury or disease. It...
Boolean analysis – a method to find deterministic dependencies between variables in a sample, mostly used in exploratory data analysis Cluster analysis – techniques...
multivariate research methods and statistical analysis (especially his many refinements to exploratoryfactor analytic methodology). In his personality research...
determine the constructs assessed by the measure. ExploratoryFactorAnalysis and Confirmatory FactorAnalysis are two of the most common data reduction techniques...
propagation Exploratoryfactoranalysis F1 score FLAME clustering Factoranalysis of mixed data Factor graph Factor regression model Factored language model...
Typhoon Elementary function arithmetic Essential fatty acid Exploratoryfactoranalysis Egyptian Football Association Eton Fives Association, the governing...
analyzed using various statistical methods, such as exploratoryfactoranalysis or principal component analysis. These methods allow researchers to analyze natural...
we measuring with the morningness–eveningness questionnaire? Exploratoryfactoranalysis across four samples from two countries". Chronobiology International...
researchers performed, “an exploratoryfactoranalysis of scale scores using varimax rotation,”: 632 from which five factors emerged. Peterson & Seligman...