Title
Evaluating effect, composite, and causal indicators in structural equation models
Abstract
Although the literature on alternatives to effect indicators is growing, there has been little attention given to evaluating causal and composite (formative) indicators. This paper provides an overview of this topic by contrasting ways of assessing the validity of effect and causal indicators in structural equation models (SEMs). It also draws a distinction between composite (formative) indicators and causal indicators and argues that validity is most relevant to the latter. Sound validity assessment of indicators is dependent on having an adequate overall model fit and on the relative stability of the parameter estimates for the latent variable and indicators as they appear in different models. If the overall fit and stability of estimates are adequate, then a researcher can assess validity using the unstandardized and standardized validity coefficients and the unique validity variance estimate. With multiple causal indicators or with effect indicators influenced by multiple latent variables, collinearity diagnostics are useful. These results are illustrated with a number of correctly and incorrectly specified hypothetical models.
Year
DOI
Venue
2011
10.2307/23044047
MIS Quarterly
Keywords
Field
DocType
multiple causal indicator,unique validity variance estimate,effect indicator,adequate overall model fit,multiple latent variable,latent variable,sound validity assessment,causal indicator,overall fit,standardized validity coefficient,structural equation model,validity,measurement,structural equation models,composites
Econometrics,Collinearity,Relative stability,Structural equation modeling,Computer science,Scale construction,Latent variable,Statistics,Formative assessment
Journal
Volume
Issue
ISSN
35
2
0276-7783
Citations 
PageRank 
References 
28
1.46
1
Authors
1
Name
Order
Citations
PageRank
Kenneth Bollen1895.46