Being able to notice that a cause-effect relation is getting stronger or weaker is important for adapting to one's environment and deciding how to use the cause in the future. We conducted an experiment in which participants learned about a cause-effect relation that either got stronger or weaker over time. The experiment was conducted with a…

This paper, a conversation between Simon Grennan, Carol Wild, Miranda Matthews and Claire Penketh, explores drawing as cause and consequence, applying Grennan's thinking to three drawings as a means of exploring and exemplifying ideas discussed in his keynote at the iJADE Conference: Time in 2023. Following an initial introduction to key ideas…

Suppose "X" and "Y" are binary exposure and outcome variables, and we have full knowledge of the distribution of "Y," given application of "X." We are interested in assessing whether an outcome in some case is due to the exposure. This "probability of causation" is of interest in comparative…

We present a model of endogenous schooling and earnings to isolate the causal effect of parents' education on children's education and earnings outcomes. The model suggests that parents' education is positively related to children's earnings, but its relationship with children's education is ambiguous. Identification is achieved by comparing the…

Causal mediation analysis has gained increasing attention in recent years. This article guides empirical researchers through the concepts and challenges of causal mediation analysis. I first clarify the difference between traditional and causal mediation analysis and highlight the importance of adjusting for the treatment-by-mediator interaction…

Regression discontinuity (RD) designs are increasingly used for causal evaluations. For example, if a student's need for a literacy intervention is determined by a low score on a past performance indicator and that intervention is provided to all students who fall below a cutoff on that indicator, an RD study can determine the intervention's main…

Regression discontinuity (RD) designs are increasingly used for causal evaluations. However, the literature contains little guidance for conducting a moderation analysis within an RDD context. The current article focuses on moderation with a single binary variable. A simulation study compares: (1) different bandwidth selectors and (2) local…

Meta-analysis is commonly used to combine results from multiple clinical trials, but traditional meta-analysis methods do not refer explicitly to a population of individuals to whom the results apply and it is not clear how to use their results to assess a treatment's effect for a population of interest. We describe recently-introduced causally…

Background: Bradford Hill (BH) viewpoints are widely used to assess causality in systematic reviews, but their application has often lacked reproducibility. We describe an approach for assessing causality within systematic reviews ('causal' reviews), illustrating its application to the topic of income inequality and health. Our approach draws on…

Item difficulty and dimensionality often correlate, implying that unidimensional IRT approximations to multidimensional data (i.e., reference composites) can take a curvilinear form in the multidimensional space. Although this issue has been previously discussed in the context of vertical scaling applications, we illustrate how such a phenomenon…

Given decision-makers often prioritize causal research that identifies the impact of treatments on the people they serve, a key question in education research is, "Does it work?". Today, however, researchers are paying increasing attention to successive questions that are equally important from a practical standpoint--not only does it…

Curiosity has long been extolled as a seed for employee creativity. This causality is plausible when considering curiosity as a stable trait. However, curiosity can also oscillate as a transitory state, thus complicating the causal sequence between such state curiosity and creativity. To clarify the causal ordering and achieve a refined…

The (Random Intercept) Cross-Lagged Panel Model ((RI-)CLPM) is increasingly used in psychology and related fields to assess the longitudinal relationship of two or more variables on each other. Researchers are interested in the question which of the lagged effects is causally dominant receives considerable attention. However, currently used…

This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…

In this article, we discuss the methodological implications of data and theory integration for Theory-Based Evaluation (TBE). TBE is a family of approaches to program evaluation that use program theories as instruments to answer questions about whether, how, and why a program works. Some of the groundwork about TBE has expressed the idea that a…