Causal inference and constructed measures: towards a new model of measurement for psychosocial constructs
share
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 often a univariate latent variable supposed to correspond in some way to the construct. In this paper, a causal interpretation is proposed of associations between constructed measures and various outcomes that is applicable to both reflective and formative models and is moreover applicable even if the usual assumptions of these models are violated such that the indicators have causal efficacy, rather than the supposed underlying latent. The interpretative approach is illustrated using associations between measures of social integration and cardiovascular disease incidence, concerning which neither the formative nor the reflective models seem adequate. It is argued that formative models misconstrue the relationship between the constructed measures and the underlying reality by which causal processes operate, but that reflective models misconstrue the nature of the underlying reality itself by typically presuming that the constituents of it that are causally efficacious are unidimensional. The ensuing problems arising from these misconstruals are discussed. An outline for a new model of the process of measure construction is put forward. Discussion is given to 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 interpretation of the associations of these measures with subsequent outcomes.
READ FULL TEXT
