Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships. Nevertheless, to simplify empirical evaluation, researchers typically…

In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different…

Individual religiosity measures are used by researchers to describe and compare individuals and societies. However, the cross-cultural comparability of the measures has often been questioned but rarely empirically tested. In the current study, we examined the cross-national measurement invariance properties of generalized individual religiosity in…

Complex social scientific theories are conventionally tested using linear structural equation modeling (SEM). However, the underlying assumptions of linear SEM often prove unrealistic, making the decomposition of direct and indirect effects problematic. Recent advancements in causal mediation analysis can help to address these shortcomings,…

The Stranger Face Trust scale (SFT) and Imaginary Stranger Trust scale (IST) are two new self-report measures of generalized trust that assess trust in strangers--both real and imaginary--across four trust domains. Prior research has established the reliability and validity of SFT and IST, but a number of measurement validation tests remain.…

The item wording (or keying) effect is respondents' differential response style to positively and negatively worded items. Despite decades of research, the nature of the effect is still unclear. This article proposes a potential reason; namely, that the item wording effect is scale-specific, and thus findings are applicable only to a particular…

Development and refinement of self-report measures generally involves selecting a subset of indicators from a larger set. Despite the importance of this task, methods applied to accomplish this are often idiosyncratic and ad hoc, or based on incomplete statistical criteria. We describe a structural equation modeling (SEM)-based technique, based on…

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display nonequivalence. Several researchers have suggested that nonequivalence may be used as a useful source of information as to…

Measuring values in sociological research sometimes involves the use of ranking data. A disadvantage of a ranking assignment is that the order in which the items are presented might influence the choice preferences of respondents regardless of the content being measured. The standard procedure to rule out such effects is to randomize the order of…

Most studies of the early origins of adult health rely on summing dichotomously measured negative exposures to measure childhood misfortune (CM), neglect, adversity, or trauma. There are several limitations to this approach, including that it assumes each exposure carries the same level of risk for a particular outcome. Further, it often leads…

Given that the root mean square error of approximation (RMSEA) is currently one of the most popular measures of goodness-of-model fit within structural equation modeling (SEM), it is important to know how well the RMSEA performs in models with small degrees of freedom ("df"). Unfortunately, most previous work on the RMSEA and its…