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In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social science research. [1] It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor). As such, the objective of confirmatory factor analysis is to ...
The multitrait-multimethod (MTMM) matrix is an approach to examining construct validity developed by Campbell and Fiske (1959). [1] It organizes convergent and discriminant validity evidence for comparison of how a measure relates to other measures.
Using simulated data sets, Richardson et al. (2009) investigate three ex post techniques to test for common method variance: the correlational marker technique, the confirmatory factor analysis (CFA) marker technique, and the unmeasured latent method construct (ULMC) technique.
Factor analysis can be only as good as the data allows. In psychology, where researchers often have to rely on less valid and reliable measures such as self-reports, this can be problematic. Interpreting factor analysis is based on using a "heuristic", which is a solution that is "convenient even if not absolutely true". [49]
where the weights of each composite are appropriately normalized (see Confirmatory composite analysis#Model identification). In the following, it is assumed that the weights are scaled in such a way that each composite has a variance of one, i.e., ′. Moreover, it is assumed that the observable random variables are standardized having a mean ...
Moreover, while Mokken scaling analysis is a confirmatory method, meant to test whether a number of items form a coherent scale (like confirmatory factor analysis), an Automatic Item Selection Procedure has been developed to explore which latent dimensions structure responses on a number of observable items (like factor analysis). [17]
A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models. New York: Springer. ISBN 0-387-96972-1. Kelderman, Henk (1987). "LISREL models for inequality constraints in factor and regression analysis". In Cuttance, Peter; Ecob, Russell (eds.). Structural Modelling by Example.
Confirmatory Factor Analysis (CFA) is a factor analytic technique that begins with a theory and test the theory by carrying out factor analysis. The CFA is also called as latent structure analysis, which considers factor as latent variables causing actual observable variables. The basic equation of the CFA is X = Λξ + δ