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Confirmatory Factor Analysis as a Tool in Research Using Questionnaires: A Critique,
Author(s) -
Peter Prudon
Publication year - 2015
Publication title -
comprehensive psychology
Language(s) - English
Resource type - Journals
ISSN - 2165-2228
DOI - 10.2466/03.cp.4.10
Subject(s) - confirmatory factor analysis , construct validity , goodness of fit , test (biology) , psychology , econometrics , construct (python library) , statistics , psychometrics , structural equation modeling , mathematics , computer science , clinical psychology , paleontology , biology , programming language
Predicting the factor structure of a test and comparing this with the factor structure, empirically derived from the item scores, is a powerful test of the content validity of the test items, the theory justifying the prediction, and the test's construct validity. For the last two decades, the preferred method for such testing has often been confirmatory factor analysis (CFA). CFA expresses the degree of discrepancy between predicted and empirical factor structure in X 2 and indices of “goodness of fit” (GOF), while primary factor loadings and modification indices provide some feedback on item level. However, the latter feedback is very limited, while X 2 and the GOF indices appear to be problematic. This will be demonstrated by a selective review of the literature on CFA.

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