407 publications from this institution
Causal theories of measurement view test items as effects of a common cause. Behavior domain theories view test item responses as behaviors sampled from a common domain. A domain score is a composite score over this domain. The question arises whether latent variables can simultaneously constitute domain scores and common causes of item scores. One argument to the contrary holds that behavior domain theory offers more effective guidance for item construction than a causal theory of measurement. A second argument appeals to the apparent circularity of taking a domain score, which is defined in terms of a domain of behaviors, as a cause of those behaviors. Both arguments require qualification and behavior domain theory seems to rely on implicit causal relationships in two respects. Three strategies permit reconciliation of the two theories: One can take a causal structure as providing the basis for a homogeneous domain. One can construct a homogeneous domain and then investigate whether a causal structure explains the homogeneity. Or, one can take the domain score as linked to an existing attribute constrained by indirect measurement.
As the majority of the global population resides in cities, it is imperative to understand urban well-being. While cities offer concentrated social and economic opportunities, the question arises whether these benefits translate to equitable levels of satisfaction in these domains. Using a robust and objective measure of urbanicity on a sample of 156,000 U.K. residents aged 40 and up, we find that urban living is associated with lower scores across seven dimensions of well-being, social satisfaction, and economic satisfaction. In addition, these scores exhibit greater variability within urban areas, revealing increased inequality. Last, we identify optimal distances in the hinterlands of cities with the highest satisfaction and the least variation. Our findings raise concern for the psychological well-being of urban residents and show the importance of nonlinear methods in urban research.
