Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of…

"Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

The detection of outliers and influential observations is routine practice in linear regression. Despite ongoing extensions and development of case diagnostics in structural equation models (SEM), their application has received limited attention and understanding in practice. The use of case diagnostics informs analysts of the uncertainty of model…

In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…

Maxwell, Cole, and Mitchell (2011) extended the work of Maxwell and Cole (2007), which raised important questions about whether mediation analyses based on cross-sectional data can shed light on longitudinal mediation process. The latest article considers longitudinal processes that can only be partially explained by an intervening variable, and…

A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…

Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…

The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…

Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread,…

DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data…

A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

Common source bias has been the focus of much attention. To minimize the problem, researchers have sometimes been advised to take measurements of predictors from one observer and measurements of outcomes from another observer or to use separate occasions of measurement. We propose that these efforts to eliminate biases due to common source…