The quality of products from the causal mapping process and the effect of factors related to causal map quality are unlikely to be the same for students at different educational levels. However, there is a lack of studies that provide insights into causal maps constructed by primary school students to reveal appropriate strategies. This study…

Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…

Given the developmental benefits associated with higher sense of purpose, past work has aimed to understand how experiences of adversity relate to sense of purpose. With a specific focus on experiences of adversity that may impact individuals from marginalized groups, past work has found that discrimination is related to lower sense of purpose in…

Talent identification and development systems (TIDS) adopt a deterministic perspective (i.e. athletes' future state/performances can be predicted by observations of their initial state/performance), which encourages early identification and specialisation in sport. In this framework, the main aim of sport systems is to enhance predictability and…

In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…

The p-factor is a construct that is thought to explain and maybe even cause variation in all forms of psychopathology. Since its 'discovery' in 2012, hundreds of studies have been dedicated to the extraction and validation of statistical instantiations of the p-factor, called general factors of psychopathology. In this Perspective, we outline five…

Evaluators are often called upon to assess the effects of programs. To assess a program effect, evaluators need a clear understanding of how a program effect is defined. Arguably, the most widely used definition of a program effect is the counterfactual one. According to the counterfactual definition, a program effect is the difference between…

Alarmed by his students' random use of causal language in their essays, James Edward Carroll resolved to help his students improve their understanding of causal processes. Carroll decided to introduce his students to the metaphors that historians use to describe causation in the historiography of the Salem witch trials. By modelling how historians…

From an early age, children show a keen interest in discovering the causal structure of the world around them. Given how fundamental causal information is to scientific inquiry and knowledge, this early emerging "causal stance" might be important in propelling the development of scientific literacy. However, currently little is known…

The view that empirical strategies in economics should be transparent and credible now goes almost without saying. The local average treatment effects (LATE) framework for causal inference helped make this so. The LATE theorem tells us for whom particular instrumental variables (IV) and regression discontinuity estimates are valid. This lecture…

For misguided reasons, social scientists have long been reluctant to use gain scores for estimating causal effects. This article develops graphical models and graph-based arguments to show that gain score methods are a viable strategy for identifying causal treatment effects in observational studies. The proposed graphical models reveal that gain…

Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical…

Pretend play is often hypothesized in a global sense to be an effective context for young children's learning, but there is much still to learn about whether all types of information can be learned equally and whether all types of pretend play are equally beneficial. The present study tests whether preschoolers can learn a simple, novel causal…

Although cross-sectional studies depict (negative) emotions as both antecedents and consequences of trait procrastination, longitudinal studies examining reciprocal relationships between procrastination and emotions are scant. Yet, investigating reciprocal relationships between procrastination and emotions within long-term frameworks can shed…

Causal mechanistic reasoning is a thinking strategy that can help students explain complex phenomena using core ideas commonly emphasized in separate undergraduate courses, as it requires students to identify underlying entities, unpack their relevant properties and interactions, and link them to construct mechanistic explanations. As a…