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• Exploratory_factor_analysis abstract "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. 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. It should be used when the researcher has no a priori hypothesis about factors or patterns of measured variables. Measured variables are any one of several attributes of people that may be observed and measured. An example of a measured variable would be the physical height of a human being. Researchers must carefully consider the number of measured variables to include in the analysis. 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. Within the common factor model, a function of common factors, unique factors, and errors of measurements expresses measured variables. Common factors influence two or more measured variables, while each unique factor influences only one measured variable and does not explain correlations among measured 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). EFA requires the researcher to make a number of important decisions about how to conduct the analysis because there is no one set method.".
• Exploratory_factor_analysis wikiPageExternalLink Exploratory_factor_analysis.
• Exploratory_factor_analysis wikiPageExternalLink v10n7.pdf.
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• Exploratory_factor_analysis wikiPageWikiLink Angle.
• Exploratory_factor_analysis wikiPageWikiLink Category:Factor_analysis.
• Exploratory_factor_analysis wikiPageWikiLink Confidence_interval.
• Exploratory_factor_analysis wikiPageWikiLink Confirmatory_factor_analysis.
• Exploratory_factor_analysis wikiPageWikiLink Factor_analysis.
• Exploratory_factor_analysis wikiPageWikiLink Goodness_of_fit.
• Exploratory_factor_analysis wikiPageWikiLink Latent_variable.
• Exploratory_factor_analysis wikiPageWikiLink Maximum_likelihood.
• Exploratory_factor_analysis wikiPageWikiLink Multivariate_statistics.
• Exploratory_factor_analysis wikiPageWikiLink Occams_razor.
• Exploratory_factor_analysis wikiPageWikiLink Orthogonality.
• Exploratory_factor_analysis wikiPageWikiLink Statistical_significance.
• Exploratory_factor_analysis wikiPageWikiLink V:Exploratory_factor_analysis.
• Exploratory_factor_analysis wikiPageWikiLink Variable_and_attribute_(research).
• Exploratory_factor_analysis wikiPageWikiLinkText "Exploratory factor analysis".
• Exploratory_factor_analysis wikiPageWikiLinkText "exploratory factor analysis".
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• Exploratory_factor_analysis subject Category:Factor_analysis.
• Exploratory_factor_analysis hypernym Method.
• Exploratory_factor_analysis type Model.
• Exploratory_factor_analysis type Software.
• Exploratory_factor_analysis type Model.
• Exploratory_factor_analysis type Page.
• Exploratory_factor_analysis comment "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.".
• Exploratory_factor_analysis label "Exploratory factor analysis".
• Exploratory_factor_analysis sameAs Q5421350.
• Exploratory_factor_analysis sameAs Feltáró_faktorelemzés.
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