Although the use of simulation to teach the sampling distribution of the mean is meant to provide students with sound conceptual understanding, it may lead them astray. We discuss a misunderstanding that can be introduced or reinforced when students who intuitively understand that "bigger samples are better" conduct a simulation to…

Through an examination of measurement invariance, this study investigated whether attachment-related dimensions (i.e., secure base, safe haven, and negative interactions as measured with the Network of Relationships Inventory-Behavioral Systems Version) have the same psychological meaning for early adolescents in their relationships with parents…

Every measurement in science, every experimental decision, result and information drawn from it has to cope with something that has long been named by the term "error". In fact, errors describe our limitations when it comes to experimental science and science looks back on a long tradition to cope with them. The widely known way to cope…

Remediation is one of the largest single interventions intended to improve outcomes for underprepared college students, yet little is known about the remedial screening process. Using administrative data and a rich predictive model, we find that severe mis-assignments are common using current test-score-cutoff-based policies, with…

This study examined the measurement structure, cross-year stability of achievement goals, and mediating effects of achievement goals between self-efficacy and math grades in a national sample of Taiwan middle school students. The measurement model with factorial structure showed good fit to the data. In the panel data (N?=?343), four achievement…

This article provides an overview of the available evidence on psychological misconceptions, including key findings, current directions and emerging issues for investigation. We begin by defining misconceptions and then examine their prevalence and persistence, discuss their implications for student learning and highlight potential strategies to…

Developmental score scales represent the performance of students along a continuum, where as students learn more they move higher along that continuum. Unidimensional item response theory (UIRT) vertical scaling has become a commonly used method to create developmental score scales. Research has shown that UIRT vertical scaling methods can be…

In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…

Goodness-of-fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square, but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's (1984) asymptotically distribution-free method and Satorra Bentler's…

The DIF-free-then-DIF (DFTD) strategy consists of two steps: (a) select a set of items that are the most likely to be DIF-free and (b) assess the other items for DIF (differential item functioning) using the designated items as anchors. The rank-based method together with the computer software IRTLRDIF can select a set of DIF-free polytomous items…

This article introduces new statistics for evaluating score consistency. Psychologists usually use correlations to measure the degree of linear relationship between 2 sets of scores, ignoring differences in means and standard deviations. In medicine, biology, chemistry, and physics, a more stringent criterion is often used: the extent to which…

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…

Undergraduate students who have just completed an introductory statistics course often lack deep understanding of variability and enthusiasm for the field of statistics. This paper argues that by introducing the commonly underemphasized concept of measurement error, students will have a better chance of attaining both. We further present lecture…

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…

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…