Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses ( Baron & Kenny, 1986 ; Sobel, 1982 ) have in recent years been supplemented by computationally intensive methods such as bootstrapping, the distribution of the product methods, and hierarchical Bayesian Markov chain Monte Carlo (MCMC) methods. These different approaches for assessing mediation are illustrated using data from Dunn, Biesanz, Human, and Finn (2007). However, little is known about how these methods perform relative to each other, particularly in more challenging situations, such as with data that are incomplete and/or nonnormal. This article presents an extensive Monte Carlo simulation evaluating a host of approaches for assessing mediation. We examine Type I error rates, power, and coverage. We study normal and nonnormal data as well as complete and incomplete data. In addition, we adapt a method, recently proposed in statistical literature, that does not rely on confidence intervals (CIs) to test the null hypothesis of no indirect effect. The results suggest that the new inferential method-the partial posterior p value-slightly outperforms existing ones in terms of maintaining Type I error rates while maximizing power, especially with incomplete data. Among confidence interval approaches, the bias-corrected accelerated (BC a ) bootstrapping approach often has inflated Type I error rates and inconsistent coverage and is not recommended; In contrast, the bootstrapped percentile confidence interval and the hierarchical Bayesian MCMC method perform best overall, maintaining Type I error rates, exhibiting reasonable power, and producing stable and accurate coverage rates.

We present a flexible full-information approach to modeling multiple user-defined response styles across multiple constructs of interest. The model is based on a novel parameterization of the multidimensional nominal response model that separates estimation of overall item slopes from the scoring functions (indicating the order of categories) for each item and latent trait. This feature allows the definition of response styles to vary across items as well as overall item slopes that vary across items for both substantive and response style dimensions. We compared the model with similar approaches using examples from the smoking initiative of the Patient-Reported Outcomes Measurement Information System. A small set of simulations showed that the estimation approach is able to recover model parameters, factor scores, and reasonable estimates of standard errors. Furthermore, these simulations suggest that failing to include response style factors (when present in the data generating model) has adverse consequences for substantive trait factor score recovery. (PsycINFO Database Record

Previous research has revealed differences in how people value and pursue positive affect in individualistic and collectivistic cultural contexts. Whereas Euro-Americans place greater value on high activation positive affect (HAP; e.g., excitement, enthusiasm, elation) than do Asian Americans and Hong Kong Chinese, the opposite is true for low activation positive affect (LAP; e.g., calmness, serenity, tranquility). Although the form of collectivism present in East Asia dictates that individuals control and subdue their emotional expressions so as to maintain harmonious relationships, the opposite norm emerges in Mexico and other Latin American countries, in that the cultural script of simpatía promotes harmony through the open and vibrant expression of positive emotion. Across two studies, we found that Mexicans display a pattern of HAP/LAP preference different from those from East Asian collectivistic cultures, endorsing HAP over LAP.

Much research finds that Westerners self-enhance more than East Asians, with the exception of studies using the implicit associations test for self-esteem (IATSE). We contrasted Japanese and Canadians on a new measure of self-enhancement under lowand high-attentional load to assess whether cultural differences vary across controlled and automatic processes. Participants also completed measures of relational mobility and the IATSE. Results indicated that Japanese and Asian-Canadians were more self-critical than Euro-Canadians, both under high-and low-attentional load. This cultural difference was partially mediated by relational mobility. The IATSE showed no cultural differences, but this measure did not positively correlate with any of the other measures in the study, suggesting that it is not a valid measure of 'true' self-feelings.

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