Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…

The internal validity of observational study is often subject to debate. In this study, we define the counterfactuals as the unobserved sample and intend to quantify its relationship with the null hypothesis statistical testing (NHST). We propose the probability of a robust inference for internal validity, that is, the PIV, as a robustness index…

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…

This study aimed to investigate the effects of judgment frames, cues, and test criteria on the accuracy of metacomprehension monitoring. The design was a 2 (rating comprehension vs. predicting performance) × 2 (memory cues vs. comprehension cues) × 2 (detailed questions test vs. inferential questions test) mixed design with judgment frames and…

It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…

Sound educational policy recommendations require valid estimates of causal effects, but observational studies in physics education research sometimes have loosely specified causal hypotheses. The connections between the observational data and the explicit or implicit causal conclusions are sometimes misstated. The link between the causal…

Several studies investigated preschoolers' ability to compute scalar and ad-hoc implicatures, but only one compared children's performance with both kinds of implicature with the same task, a picture selection task. In Experiment 1 (N = 58, age: 4;2-6;0), we first show that the truth value judgment task, traditionally employed to investigate…

Music performance requires high levels of motor control. Professional musicians use body movements not only to accomplish and help technical efficiency, but to shape expressive interpretation. Here, we recorded motion and audio data of twenty participants performing four musical fragments varying in the degree of technical difficulty to analyze…

Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method,…

Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…

People often speak indirectly. For example, "It's cold in here" might be intended not only as a comment on the temperature but also as a request to turn on the heater. How are comprehenders' inferences about a speaker's intentions informed by their ability to reason about the speaker's mental states, that is, "mentalizing?" We…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…

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…

Purpose: The aim of this review is to illuminate the connection between inferential skills and spoken language idiom comprehension (SLIC) with a focus on autism. Idioms are frequently occurring figurative expressions, such as feeling blue, on cloud nine, and all tied up, that have literal and nonliteral meanings. Method: In this review article, an…