Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

Causal inference regarding a hypothesized mediation mechanism relies on the assumptions that there are no omitted pretreatment confounders (i.e., confounders preceding the treatment) of the treatment-mediator, treatment-outcome, and mediator-outcome relationships, and there are no posttreatment confounders (i.e., confounders affected by the…

Children's media is replete with human-like portrayals of animals and objects that wear clothing, speak, drive cars, and experience human emotions. Recent research has shown that anthropomorphic portrayals of animals in books lead children to think anthropomorphically about real animals. Here we asked whether this is also the case for an inanimate…

In causal mediation analysis, the definitions of the natural direct and indirect effects involve potential outcomes that can never be observed, so-called a priori counterfactuals. This conceptual challenge translates into issues in identification, which requires strong and often unverifiable assumptions, including sequential ignorability.…

This study's purpose was to investigate effects of 3 intervention approaches for building working memory (WM) and improving word-problem solving (WPS). Children with mathematics difficulties (n = 240; 7.51 years [SD = 0.33]) were randomized to 4 conditions: a control group, general WM training with contiguous math practice, WPS intervention…

Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same units under different treatment conditions. Because for each unit at most one of the potential…

Prerequisite skill structures have been closely studied in past years leading to many data-intensive methods aimed at refining such structures. While many of these proposed methods have yielded success, defining and refining hierarchies of skill relationships are often difficult tasks. The relationship between skills in a graph could either be…

Causal inference in observational studies typically requires making comparisons between groups that are dissimilar. For instance, researchers investigating the role of a prolonged duration of breastfeeding on child outcomes may be forced to make comparisons between women with substantially different characteristics on average. In the extreme there…