Significance of Factor analysis
Factor analysis is a statistical method instrumental in identifying underlying factors and assessing relationships within a dataset, particularly useful for questionnaire items. It aids in determining construct validity through exploratory and confirmatory approaches while simplifying complex data by reducing multiple variables into fewer factors. This method is commonly applied across various research fields, examining constructs and relationships among variables, ultimately supporting the refinement and development of assessment tools.
Synonyms: Exploratory factor analysis, Confirmatory factor analysis, Structural equation modeling, Principal component analysis, Data reduction
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
The concept of Factor analysis in scientific sources
Factor analysis is a statistical method that uncovers underlying relationships among variables, streamlining data for analysis and commonly used in areas like personality assessments to reveal latent factors influencing behaviors and traits.
(1) Factor analysis is a statistical method used to identify underlying factors or components within a set of variables, such as questionnaire items, to assess their relationships.[1] (2) This is a statistical method used to identify the underlying factors that explain the patterns of correlations within a set of observed variables, and it was used to validate the CHAOS-6.[2] (3) This is a statistical method employed to analyze the dimensionality of the work-family conflict construct, utilizing techniques such as exploratory and confirmatory factor analysis, as described.[3] (4) This is a statistical method used to examine the structure of the scale and identify the underlying factors or dimensions measured by the instrument.[4] (5) This is a statistical method used to analyze the relationships between variables and identify underlying factors.[5]
(1) This is a statistical method used to identify underlying factors or components within a set of variables, such as those found in a questionnaire or assessment tool.[6] (2) Factor analysis of obsessive-compulsive spectrum disorders in patients with obsessive-compulsive disorder: clinical and genetic correlates.[7]