RESUMO
Few sociologists treat housing as a key independent variable, despite the emergence of disparate bodies of research analyzing how housing affects outcomes that traditionally interest sociologists. Scholars across the social sciences have proposed and tested mechanisms whereby housing could shape subjective wellbeing, socioeconomic status, demography, and politics. We review the evidence for causal effects across these domains. Next, we make recommendations for research designs to advance this literature. Most studies only test effects of homeownership, and most are focused on the United States and Western Europe. The evidence for causation is often weak, although studies increasingly employ complex techniques for identifying effects. Throughout, we emphasize studies beyond the United States, and we conclude by discussing distinctive insights yielded by comparative research. We advocate for a comparative perspective and more expansive conceptualization of housing status as a means to build theory and evidence regarding the conditions under which housing exerts effects.
RESUMO
Selecting between competing Structural Equation Models (SEMs) is a common problem. Often selection is based on the chi square test statistic or other fit indices. In other areas of statistical research Bayesian information criteria are commonly used, but they are less frequently used with SEMs compared to other fit indices. This article examines several new and old Information Criteria (IC) that approximate Bayes Factors. We compare these IC measures to common fit indices in a simulation that includes the true and false models. In moderate to large samples, the IC measures outperform the fit indices. In a second simulation we only consider the IC measures and do not include the true model. In moderate to large samples the IC measures favor approximate models that only differ from the true model by having extra parameters. Overall, SPBIC, a new IC measure, performs well relative to the other IC measures.
