Online Causal Inference Seminar

Free and open to the public

Tuesday, May 3, 2022 [Link to join] (ID: 996 2837 2037, Password: 386638)

• Speaker: Tyler VanderWeele (Harvard University)
• Title: Causal Inference and Measure Construction: Towards a New Model of Measurement

• Abstract: Psychosocial constructs can only be assessed indirectly, and measures are typically formed by a combination of indicators that are thought to relate to the construct. Reflective and formative measurement models offer different conceptualizations of the relation between the indicators and what is sometimes conceived of as a univariate latent variable supposedly corresponding to the construct. I argue that the empirical implications of these models will often be violated by data since the causally relevant constituents will generally be multivariate, not univariate. In fact, the assumption of an underlying univariate structural latent variable is so strong that it has empirically testable implications, even though the latent is unobserved. Formal statistical tests can be developed to reject this assumption, but factor analysis, as typically practiced, is not adequate to do so. Factor analysis also suffers from the inability to distinguish associations arising from causal versus conceptual relations. I put forward an outline for a new model of the process of measure construction and propose a causal interpretation of associations between constructed measures and subsequent outcomes that is applicable even if the usual assumptions of reflective and formative models fail. I discuss the practical implications of these observations and proposals for the provision of definitions, the selection of items, item-by-item analyses, the construction of measures, and the causal interpretation of regression analyses.