Racial/ethnic diversity has become an increasingly important variable in the social sciences. Research from multiple disciplines consistently demonstrates the tremendous impact of ethnic diversity on individuals and organizations. Investigators use a variety of measures, and their choices can affect the conclusions that can be drawn and limit the…

Subtraction can be understood by two basic models--taking away (ta) and determining the difference (dd)--and by its inverse relation to addition. Epistemological analyses and empirical examples show that the two models are not relevant only in single-digit arithmetic. As curricula should be developed in a longitudinal perspective on mathematics…

Letter recognition is the foundation of the human reading system. Despite this, it tends to receive little attention in computational modelling of single word reading. Here we present a model that can be trained to recognise letters in various spatial transformations. When presented with degraded stimuli the model makes letter confusion errors…

A simple benchtop experiment in which a moving cart collides with a fixed spring is described. Force-time and force-distance data recorded during the collision display the transit of compression wave fronts through the spring following impact. These data can be used by students to develop a computational model of the dynamics of this simple…

Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to multiply imputed data sets. However, the presence of multiple random imputations complicates model fit testing, which is an important aspect of mean and covariance structure…

An interval estimation procedure for proportion of explained observed variance in latent curve analysis is discussed, which can be used as an aid in the process of choosing between linear and nonlinear models. The method allows obtaining confidence intervals for the R[squared] indexes associated with repeatedly followed measures in longitudinal…

Muthen and Asparouhov (2012) made a strong case for the advantages of Bayesian methodology in factor analysis and structural equation models. I show additional extensions and adaptations of their methods and show how non-Bayesians can take advantage of many (though not all) of these advantages by using interval restrictions on parameters. By…

In this study, the authors tested alternative factor models of the 12-item General Health Questionnaire (GHQ-12) in a sample of Spanish postpartum women, using confirmatory factor analysis. The authors report the results of modeling three different methods for scoring the GHQ-12 using estimation methods recommended for categorical and binary data.…

The performance of multiple imputation in questionnaire data has been studied in various simulation studies. However, in practice, questionnaire data are usually more complex than simulated data. For example, items may be counterindicative or may have unacceptably low factor loadings on every subscale, or completely missing subscales may…

Does having more knowledge or interest in the topics used in example problems facilitate or hinder learning in statistics? Undergraduates enrolled in Introductory Psychology received a lesson on central tendency. Following the lesson, half of the students completed a worksheet with a baseball cover story while the other half received a weather…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Data from competence tests usually show a number of missing responses on test items due to both omitted and not-reached items. Different approaches for dealing with missing responses exist, and there are no clear guidelines on which of those to use. While classical approaches rely on an ignorable missing data mechanism, the most recently developed…

Extreme response style (ERS) is a systematic tendency for a person to endorse extreme options (e.g., strongly disagree, strongly agree) on Likert-type or rating-scale items. In this study, we develop a new class of item response theory (IRT) models to account for ERS so that the target latent trait is free from the response style and the tendency…

This study explores the effects of counting objects and reciting numbers in preschool on 1st-grade math performance. Data on 3,125 low-income preschoolers' (4-to 5-year-olds) counting abilities (orally reciting numerals in chronological order and counting blocks) were collected during a fall session (between September 15 and December 15) and were…

On August 7th, 2013, the New York State Education Commissioner, John King, announced the initial results of the state's new assessment, which was designed to measure college and career readiness relative to the Common Core Learning Standards. Commissioner King noted that the proficiency rates on these assessments were significantly lower than…