Psychologists have long been interested in characterizing individual differences in change over time. It is often plausible to assume that the distribution of these individual differences is continuous in nature, yet theory is seldom so specific as to designate its parametric form (e.g., normal). Semiparametric groups-based trajectory models…

We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…

A mixed effects location scale model was used to model and explain individual differences in within-person variability of negative and positive affect across 7 days (N=178) within a measurement burst design. The data come from undergraduate university students and are pooled from a study that was repeated at two consecutive years. Individual…

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…

The social accuracy model of interpersonal perception (SAM) is a componential model that estimates perceiver and target effects of different components of accuracy across traits simultaneously. For instance, Jane may be generally accurate in her perceptions of others and thus high in "perceptive accuracy"--the extent to which a particular…

Outliers are typically regarded as data anomalies that should be discarded. However, dynamic or "innovative" outliers can be appropriately utilized to capture unusual but substantively meaningful shifts in a system's dynamics. We extend De Jong and Penzer's 1998 approach for representing outliers in single-subject state-space models to a…

Combines procedures for single-level mediational analysis with multilevel modeling techniques to test mediational effects in clustered data appropriately. Compared, through simulation, the performance of these multilevel mediational models with that of single-level models in clustered data with various real-world characteristics. (SLD)

A data analysis model is proposed for studies concerning attribution theory. The model is based on the author's previous work in the area of trait view theory. (JKS)

Demonstrated how individual differences in semantic differential data can be modeled and assessed using three-mode models by studying the characterization of Chopin's "Preludes" by 38 Japanese college students. (SLD)

The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model…

Recently developed multidimensional-scaling methodology was used to explore the underlying structure of moral reasoning responses to 12 moral dilemmas by 111 graduate students in law and social work and to relate that structure to individual differences. Results indicate that moral reasoning must be viewed from multidimensional and interactional…