factor analysis


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Words related to factor analysis

any of several methods for reducing correlational data to a smaller number of dimensions or factors

References in periodicals archive ?
Keywords: PANAS, Positive affect, Negative affect, exploratory factor analysis, Confirmatory factor analysis.
In order to define new convergence criteria for cluster analysis, we applied factor analysis to cross-sectional data of 28 EU members from 2014.
The introduction describes the purpose of the book as, "to provide clinicians and researchers practical understanding of the complex statistical procedures involved in factor analysis.
Factor analysis criteria make the content variance of the objects between partitions as high as possible and the style variance of the objects within a partition as low as possible.
Doloi (2009) applied factor analysis to identify the prominent factors that influence contractors' performance in construction projects.
The principal factor analysis method explained by Harman [6] was followed in the extraction of the factor loadings.
Similarly, although the exploratory factor analysis has provided a seven-factor structure, studies that have evaluated the psychometric properties of the MBI with other populations show a greater number of factors than the original version (13,14,15) by this same method.
There are various types of factor analysis and principal components analysis (PCA) has been mostly used by the researchers.
One of the most effective methods to remove the problem is to use factor analysis scores for multiple regression analysis in different species as reported by many authors (Keskin et al.
Analyze the construct validity obtained from confirmatory factor analysis, comparing it to the validity obtained from the initial exploratory factor analysis.
To summarize data, factor analysis desires dimension that, when interpreted and understood, describes data in terms of a much smaller number of items than do the individual variables.
To analyze such information of different regions, regarding multivariate nature of data, it is appropriate to use statistical multivariate techniques such as Principal Component Analysis (PCA), Factor Analysis (FA), Cluster Analysis (CA), etc.
The PAS was then analyzed using Cronbach's alpha reliability coefficient and Comrey's minimum residual factor analysis with tandem criteria rotation (Comrey, 1962, Comrey, 1967, Comrey & Lee, 1992).
Factor analysis is a mathematical model which attempts to reduce a large number of inter-correlated variables to a smaller number of unobserved and uncorrelated latent factors or dimensions.