Mediation analyses abound in social and personality psychology. Current recommendations for assessing power and sample size in mediation models include using a Monte Carlo power analysis simulation and testing the indirect effect with a bootstrapped confidence interval. Unfortunately, these methods have rarely been adopted by researchers due to limited software options and the computational time needed. We propose a new method and convenient tools for determining sample size and power in mediation models. We demonstrate our new method through an easy-to-use application that implements the method. These developments will allow researchers to quickly and easily determine power and sample size for simple and complex mediation models.

The use of item parcels has been a matter of debate since the earliest use of factor analysis and structural equation modeling. Here, we review the arguments that have been levied both for and against the use of parcels and discuss the relevance of these arguments in light of the building body of empirical evidence investigating their performance. We discuss the many advantages of parcels that some researchers find attractive and highlight, too, the potential problems that ill-informed use can incur. We argue that no absolute pro or con stance is warranted. Parcels are an analytic tool like any other. There are circumstances in which parceling is useful and those when it is not. We emphasize the precautions that should be taken when creating item parcels and interpreting model results based on parcels. Finally, we review and compare several proposed strategies for parcel building and suggest directions for further research.

The Difficulties in Emotion Regulation Scale (DERS) is commonly used to assess difficulties recognizing and managing negative affect. Scores on the scale are strongly correlated with measures of psychopathology and are inversely correlated with measures of psychological well-being. Evidence supports the use of the DERS with adolescents and adults; to date, however, few studies have investigated the extent to which the psychometric properties of the DERS are consistent across demographic groups. The overarching goal of the present study was to examine the extent to which the factor structure of the DERS and the reliability and validity of DERS scores are consistent across gender and race in a diverse sample of adults. A total of 1,050 students from a medium-sized, urban university were included in the present study. Participants included 75.6% women and 24.4% men; 42.5% of participants identified as Caucasian, 40.4% as African American, and 17.1% as Asian American. Results showed that the DERS exhibits similar psychometric properties across men and women and all 3 racial groups that were included in this study. As such, the overall scale, as well as the original 6-factor solution of the DERS, can be reliably applied to individuals from the demographic groups investigated in the current study, and results can be interpreted in accordance with those from the preliminary DERS validation sample.

Examining interactions among predictors is an important part of a developing research program. Estimating interactions using latent variables provides additional power to detect effects over testing interactions in regression. However, when predictors are modeled as latent variables, estimating and testing interactions requires additional steps beyond the models used for regression. We review methods of estimating and testing latent variable interactions with a focus on product indicator methods. Product indicator methods of examining latent interactions provide an accurate method to estimate and test latent interactions and can be implemented in any latent variable modeling software package. Significant latent interactions require additional steps (plotting and probing) to interpret interaction effects. We demonstrate how these methods can be easily implemented using functions in the semTools package with models fit using the lavaan package in R, and we illustrate how these methods work using an applied example concerning teacher stress and testing.