Planning longitudinal studies can be challenging as various design decisions need to be made. Often, researchers are in search for the optimal design that maximizes statistical power to test certain parameters of the employed model. We provide a user-friendly Shiny app OptDynMo available at https://shiny.psychologie.hu-berlin.de/optdynmo that…

The increased availability of time-related information as a result of computer-based assessment has enabled new ways to measure test-taking engagement. One of these ways is to distinguish between solution and rapid guessing behavior. Prior research has recommended response-level filtering to deal with rapid guessing. Response-level filtering can…

One of the most vexing challenges facing developmental researchers today is the statistical modeling of two or more behaviors as they unfold jointly over time. Although quantitative methodologists have studied these issues for more than half a century, no widely agreed-upon principled strategy exists to empirically analyze codevelopmental…

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…

Examinees with item preknowledge tend to obtain inflated test scores that undermine test score validity. With the availability of process data collected in computer-based assessments, the research on detecting item preknowledge has progressed on using both item scores and response times. Item revisit patterns of examinees can also be utilized as…

The vast majority of research involving active learning pedagogies uses passive lecture methods as a baseline. We propose to move beyond such comparisons to understand the mechanisms that make different active learning styles unique. Here, we use COPUS observations to record student and instructor activities in six known styles of active learning…

Learning analytics needs to pay more attention to the temporal aspect of learning processes, especially in self-regulated learning (SRL) research. In doing so, learning analytics models should incorporate both the duration and frequency of learning activities, the passage of time, and the temporal order of learning activities. However, where this…

Mixture models have been developed to enable detection of within-subject differences in responses and response times to psychometric test items. To enable mixture modeling of both responses and response times, a distributional assumption is needed for the within-state response time distribution. Since violations of the assumed response time…

In this multiyear, statewide investigation, the extent to which enrollment rates of male and female, part-time, first-time-in-college students enrolled in Texas community colleges differed from the 2003-2004 academic year to the 2018-2019 academic year was determined. From the 2003-2004 academic year to the 2011-2012 academic year, statistically…

Transition metrics, which quantify the propensity for one event to follow another, are often utilized to study sequential patterns of behaviors, emotions, actions, and other states. However, little is known about the conditions in which application of transition metrics is appropriate. We report on two experiments in which we simulated sequences…

This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…

Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching…

Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…

Temporal aspects of child and adolescent time allocation in diverse cultural settings have been difficult to model using conventional statistical techniques. A new statistical approach, Egocentric Relational Event Modelling (EREM), allows for the simultaneous modelling of activity frequency, duration, and sequencing. Here, EREM is applied to a…

Background: When RCTs are not feasible and time series data are available, panel data methods can be used to estimate treatment effects on outcomes, by exploiting variation in policies and conditions over time and across locations. A complication with these methods, however, is that treatment timing often varies across the sample, for example, due…