Premium
Focus on psychometrics. More on mtmm: The role of confirmatory factor analysis
Author(s) -
Figueredo Aurelio J.,
Ferketich Sandra L.,
Knapp Thomas R.
Publication year - 1991
Publication title -
research in nursing and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 85
eISSN - 1098-240X
pISSN - 0160-6891
DOI - 10.1002/nur.4770140510
Subject(s) - confirmatory factor analysis , bivariate analysis , construct (python library) , variance (accounting) , psychometrics , construct validity , statistics , set (abstract data type) , common method variance , mathematics , computer science , econometrics , structural equation modeling , economics , accounting , programming language
This article is the second of two on the use of confirmatory factor analysis (CFA) as a method to assess construct validity. The construct validation criteria required by the conventional MTMM approach are satisfied only by certain ideal data sets, such as those in which the method variance of measures is very low. The CFA approach to multitrait‐multimethod (MTMM) data is more general, in that violations of those stringent criteria can be managed. Another limitation of the conventional MTMM approach is that only a relatively small number of indicators can be examined by bivariate analysis. The economy of the CFA approach permits the analysis of a much larger number of indicators. In this article, a data set is analyzed using the CFA approach. Results are presented that illustrate the application of this statistical method.