Latent variable models build causal links that definitional frameworks reject

Evidence

In the appendix to the next chapter I contrast this ontological-semantic approach to conceptualization and measurement with latent variable models. These present a radically different approach, focused much more on indicators and measurement and much less on ontology and semantics. Latent variables are cause indicators. The ontological–semantic approach does not have causal relationships within the basic framework. The core criteria of completeness and nonredundancy for concepts make no sense in the latent variable framework. In the basic framework the focus is first and above all on the definitions and concept structure and then secondarily on the empirical indicators; for latent variables the focus is on “measurement models.” — Gary Goertz, Social Science Concepts and Measurement, 47

Categorization

• XREF: Connects to latent-variable/reflective-vs-formative measurement debates in psychometrics and structural equation modeling.