Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…

We describe a hands-on project in which students collect data on the impact of distracted driving on driver reaction time. Initially they do this in class via a virtual driving applet, using themselves and fellow students as test subjects. Different applet versions simulate driving with and without distraction and measure the time it takes to…

This systematic review examines the empirical research conducted in the past decade to investigate the application of immersive Virtual Reality (IVR) in geography higher education. Our analysis includes 29 empirical studies published across 25 peer-reviewed articles and delves into IVR applications from four key perspectives: the temporal and…

Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…

Missing data is a common challenge to any researcher in almost any field of research. In particular, human participants in research do not always respond or return for assessments leaving the researcher to rely on missing data methods. The most common methods (i.e., Multiple Imputation and Full Information Maximum Likelihood) assume that the…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

The overall aim was to examine effects of differences in group ability and features of the anchor test form on equating bias and the standard error of equating (SEE) using both real and simulated data. Chained kernel equating, Postratification kernel equating, and Circle-arc equating were studied. A college admissions test with four different…

Commonly used methods to simulate the oxidation-reduction (redox) titration curves include the three-step method and the rigorous method. The simple three-step method simulates the redox titration curve with the assumption that the reaction is complete, which is widely used in undergraduate quantitative analysis courses. For the rigorous…

Psychology originally defined parent-child conflict in terms of interpersonal relationships, where parent-child conflict is a process of inconsistent attitudes between parents and children that occurs in a family setting. For this end, we aims to investigate the influence of parental awareness on preschoolers' perception of parent-child conflict…

A new index of item discrimination power (IDP), dimension-corrected Somers' D (D2) is proposed. Somers' D is one of the superior alternatives for item-total- (Rit) and item-rest correlation (Rir) in reflecting the real IDP with items with scales 0/1 and 0/1/2, that is, up to three categories. D also reaches the extreme value +1 and -1 correctly…

The increased Simon effect with increasing the ratio of congruent trials may be interpreted by both attention modulation and irrelevant stimulus-response (S-R) associations learning accounts, although the reversed Simon effect with increasing the ratio of incongruent trials provides evidence supporting the latter account. To investigate if…

Computer simulation can be used to demonstrate why the unbiased sample variance uses degrees of freedom (n-1). This is first demonstrated for sampling from a normal random variable, and in additional simulations for some selected non-normal random variables, namely, chi-square and binomial.

In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…

Background: Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs)…