Social desirability bias (SDB) is a common threat to the validity of conclusions from responses to a scale or survey. There is a wide range of person-fit statistics in the literature that can be employed to detect SDB. In addition, machine learning classifiers, such as logistic regression and random forest, have the potential to distinguish…

Attributional processes about why outcomes occur constitute an important mediating mechanism that can explain different reactions of both the targets of harassment and their peers. The present study aimed to evaluate the psychometric properties of a measure of attributions for victimization among adolescents, using Confirmatory Factor Analyses,…

Information can be conveyed via multiple channels such as verbal and gestural (visual) channels during communication. Sometimes the information from different channels does not match (e.g., saying right while pointing to the left). How do addressees choose which information to act upon in such cases? In two experiments, we investigated this issue…

We empirically examined the effectiveness of how the Analysis of Competing Hypotheses (ACH) technique structures task information to help reduce confirmation bias (Study 1) and the portrayal of intelligence analysts as suffering from such bias (Study 2). Study 1 (N = 161) showed that individuals presented with hypotheses in rows and evidence items…

The presence of face masks can significantly impact processes related to trait impressions from faces. In the present research, we focused on trait impressions from faces either wearing a mask or not by addressing how contextual factors may shape such inferences. In Study 1, we compared trait impressions from faces in a phase of the COVID-19…

In network meta-analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized clinical trials (RCT) or non-randomized studies (NRS) as individual participant data (IPD) or as aggregate data (AD). We present a suite of Bayesian NMA and network meta-regression (NMR) models…

Accumulating evidence suggests that there is a spontaneous preference for numerical, compared to non-numerical (e.g., cumulative surface area), information. However, given a paucity of research on the perception of non-numerical magnitudes, it is unclear whether this preference reflects a specific bias towards number, or a general bias towards the…

Risk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule-based algorithm for RoB assessment of seroprevalence studies. We developed the SeroTracker-RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the…

Is self-assessment enough to keep physicians' cognitive skills--such as diagnosis, treatment, basic biological knowledge, and communicative skills--current? We review the cognitive strengths and weaknesses of self-assessment in the context of maintaining medical expertise. Cognitive science supports the importance of accurately self-assessing…

This paper introduces a simple, quotient effect size, termed (for 'quotient'), suitable for reporting on the effectiveness of educational interventions. The quotient effect size for a pre-test-post-test design is defined as the gain score (i.e. post-test minus pre-test) for the intervention group, divided by the gain score for the control group.…

Meta-analysis of diagnostic test accuracy (DTA) is a powerful statistical method for synthesizing and evaluating the diagnostic capacity of medical tests and has been extensively used by clinical physicians and healthcare decision-makers. However, publication bias (PB) threatens the validity of meta-analysis of DTA. Some statistical methods have…

Teaching about climate change should be a top priority for all education sectors. However, research to date suggests that climate change education is sparse and ad hoc across school contexts, is not mandated, and relies on the efforts of an impassioned few. Here, we present educators' experiences of teaching climate change in Australian…

Discipline disparities are driven by classroom teachers' decisions to refer a student for disciplinary action "and" by school administrators' decisions in response to those referrals (Amos, 2021). In this qualitative study, the researcher will explore educators' perceptions on the disparity in discipline referrals and evaluate…

We study the returns to experience in teaching, estimated using supervisor ratings from classroom observations. We describe the assumptions required to interpret changes in observation ratings over time as the causal effect of experience on performance. We compare two difference-in-differences strategies: the two-way fixed effects estimator common…

To mitigate the deleterious effects of rapid guessing (RG) on ability estimates, several rescoring procedures have been proposed. Underlying many of these procedures is the assumption that RG is accurately identified. At present, there have been minimal investigations examining the utility of rescoring approaches when RG is misclassified, and…