title: In defense of causal-formative indicators: A minority report.
abstract: Causal-formative indicators directly affect their corresponding latent variable. They run counter to the predominant view that indicators depend on latent variables and are thus often controversial. If present, such indicators have serious implications for factor analysis, reliability theory, item response theory, structural equation models, and most measurement approaches that are based on reflective or effect indicators. Psychological Methods has published a number of influential articles on causal and formative indicators as well as launching the first major backlash against them. This article examines 7 common criticisms of these indicators distilled from the literature: (a) A construct measured with "formative" indicators does not exist independently of its indicators; (b) Such indicators are causes rather than measures; (c) They imply multiple dimensions to a construct and this is a liability; (d) They are assumed to be error-free, which is unrealistic; (e) They are inherently subject to interpretational confounding; (f) They fail proportionality constraints; and (g) Their coefficients should be set in advance and not estimated. We summarize each of these criticisms and point out the flaws in the logic and evidence marshaled in their support. The most common problems are not distinguishing between what we call causal-formative and composite-formative indicators, tautological fallacies, and highlighting issues that are common to all indicators, but presenting them as special problems of causal-formative indicators. We conclude that measurement theory needs (a) to incorporate these types of indicators, and (b) to better understand their similarities to and differences from traditional indicators. (PsycINFO Database Record
authors.affiliation: Departments of Psychology and Neuroscience and Sociology, University of North Carolina, Chapel Hill.
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Bollen
authors.affiliation: Department of Business Administration, University of Vienna.
authors.forename: Adamantios
authors.initials: A
authors.lastname: Diamantopoulos
mesh_terms: D015984:Causality; D005163:Factor Analysis, Statistical; D006801:Humans; D015233:Models, Statistical; D011584:Psychology / Q000379:methods*; D015203:Reproducibility of Results