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Confirmatory Factor Analysis
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CONFIRMATORY FACTOR ANALYSIS RICK H. HOYLE
Departmentof Psychology, Universityof Kentucky, Lexington, Kentucky
Factor analysis is a family of statistical strategies used to model unmeasured sources of variability in a set of scores. Confirmatory factor analysis (CFA), otherwise referred to as restricted factor analysis (Hattie & Fraser, 1988), structural factor analysis (McArdle, 1996), or the measurement model (Hoyle, 1991), typically is used in a deductive mode to test hypotheses regarding unmeasured sources of variability responsible for the commonality among a set of scores. It can be contrasted with exploratory factor analysis (EFA; see Cudeck, chapter 10, this volume), which addresses the same basic question but in an inductive, or discovery-oriented, mode. Although CFA can be used as the sole statistical strategy for testing hypotheses about the relations among a set of variables, it is best understood as an instance of the general structural equation model (BoUen, 1989; Hoyle, 1995a; see Chapter 15). In that model, a useful distinction is made between the measurement model and the structural model (e.g., Anderson & Gerbing, 1988). The measurement model (i.e., CFA) concerns the relations be~tween measures of constructs, indicators, and the constructs they were Handbook of Applied Multivariate Statistics and Mathematical Modeling Copyright 9 2000 by Academic Press. All rights of reproduction in any form reserved.
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III
I Ill
II iN
II
II
I
II
II
I
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CONFIRMATORY FACTOR ANALYSIS RICK H. HOYLE
Departmentof Psychology, Universityof Kentucky, Lexington, Kentucky
Factor analysis is a family of statistical strategies used to model unmeasured sources of variability in a set of scores. Confirmatory factor analysis (CFA), otherwise referred to as restricted factor analysis (Hattie & Fraser, 1988), structural factor analysis (McArdle, 1996), or the measurement model (Hoyle, 1991), typically is used in a deductive mode to test hypotheses regarding unmeasured sources of variability responsible for the commonality among a set of scores. It can be contrasted with exploratory factor analysis (EFA; see Cudeck, chapter 10, this volume), which addresses the same basic question but in an inductive, or discovery-oriented, mode. Although CFA can be used as the sole statistical strategy for testing hypotheses about the relations among a set of variables, it is best understood as an instance of the general structural equation model (BoUen, 1989; Hoyle, 1995a; see Chapter 15). In that model, a useful distinction is made between the measurement model and the structural model (e.g., Anderson & Gerbing, 1988). The measurement model (i.e., CFA) concerns the relations be~tween measures of constructs, indicators, and the constructs they were Handbook of Applied Multivariate Statistics and Mathematical Modeling Copyright 9 2000 by Academic Press. All rights of reproduction in any form reserved.
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