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…

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…

Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…

In the literature of mean and covariance structure analysis, noncentral chi-square distribution is commonly used to describe the behavior of the likelihood ratio (LR) statistic under alternative hypothesis. Due to the inaccessibility of the rather technical literature for the distribution of the LR statistic, it is widely believed that the…

Score limitation at the top of a scale is commonly termed "ceiling effect." Ceiling effects can lead to serious artifactual parameter estimates in most data analysis. This study examines the consequences of ceiling effects in longitudinal data analysis and investigates several methods of dealing with ceiling effects through Monte Carlo simulations…

Psychologists are applying growth mixture models at an increasing rate. This article argues that most of these applications are unlikely to reproduce the underlying taxonic structure of the population. At a more fundamental level, in many cases there is probably no taxonic structure to be found. Latent growth classes then categorically approximate…

Multilevel analysis is an appropriate tool for the analysis of hierarchically structured data. There may, however, be reasons to ignore one of the levels of nesting in the data analysis. In this article a three level model with one predictor variable is used as a reference model and the top or intermediate level is ignored in the data analysis.…

A particular strategy for investigating effects from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The analysis strategy is described in detail and illustrated with real data sets. (Author/JKS)

A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)

This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…

Two major and two minor principles are shown to serve to generate a large number of multivariate models, including canonical analysis, factor analysis, and latent trait test theory. The statistical underpinnings of the theory are discussed. (Author/JKS)

STATGRAPHICS, a statistical package written for the IBM PC/XT/AT, is reviewed. In addition to superb graphics, STATGRAPHICS is unequalled in time series procedures, quality control, linear programming, and other mathematical procedures. The modules for regression analysis, categorical data analysis, and nonparametric analysis are good, but contain…