Although ownership is acknowledged to exert a potent influence on various aspects of information processing, the origin of these effects remains largely unknown. Based on the demonstration that self-relevance facilitates perceptual judgments (i.e., the self-prioritization effect), here we explored the possibility that ownership enhances object…

Maori and Pacific students generally do not attain the same levels of tertiary success as New Zealanders of European descent, particularly in science, technology, engineering, and mathematics (STEM) subjects. Te Ropu Awhina (Awhina), an equity initiative at Victoria University of Wellington in New Zealand between 1999 and 2015, aimed to produce…

The aim of this study is to investigate interrelationships between overexcitability and learning patterns from the perspective of personality development according to Dabrowski's theory of positive disintegration. To this end, Bayesian structural equation modeling (BSEM) is applied which allows for the simultaneous inclusion in the measurement…

Competition judges are often selected for their expertise, under the belief that a high level of performance expertise should enable accurate judgments of the competitors. Contrary to this assumption, we find evidence that expertise can reduce judgment accuracy. Adaptation level theory proposes that discriminatory capacity decreases with greater…

Synthesizing results from multiple studies is a daunting task during which researchers must tackle a variety of challenges. The task is even more demanding when studying developmental processes longitudinally and when different instruments are used to measure constructs. Data integration methodology is an emerging field that enables researchers to…

Previous studies on discourse have employed a self-paced sentence-by-sentence paradigm to present text and record reading times. However, presenting discourse this way does not mirror real-world reading conditions; for example, this paradigm prevents regressions to earlier portions of the text. The purpose of the present study is to investigate…

Many important real-world decision-making problems involve group interactions among individuals with purely informational interactions. Such situations arise for example in jury deliberations, expert committees, medical diagnoses, etc. We model the purely informational interactions of group members, where they receive private information and act…

High dimensional multivariate data, where the number of variables approaches or exceeds the sample size, is an increasingly common occurrence for social scientists. Several tools exist for dealing with such data in the context of univariate regression, including regularization methods such as Lasso, Elastic net, Ridge Regression, as well as the…

Baeysian Network Meta-Analysis represents a rather unique challenge in assessing the quality of included studies. Prior efforts to synthesize computer based scaffolding are in need of a closer examination of research quality. This study examines two quality metrics for meta-analysis, study design, and risk of bias (Higgins et al., 2011). Lower…

Policymakers usually leave decisions about scaling the scores used for accountability to their appointed technical advisory committees and the testing contractors. However, scaling decisions can have an appreciable impact on school ratings. Using middle-school data from New York State, we examined the consistency of school ratings based on two…

Interest in using Bayesian methods for estimating item response theory models has grown at a remarkable rate in recent years. This attentiveness to Bayesian estimation has also inspired a growth in available software such as WinBUGS, R packages, BMIRT, MPLUS, and SAS PROC MCMC. This article intends to provide an accessible overview of Bayesian…

Syntactic structures are unobserved theoretical constructs which are useful in explaining a wide range of linguistic and psychological phenomena. Language acquisition studies how such latent structures are acquired by human learners through many hypothesized learning mechanisms and apparatuses, which can be genetically endowed or of general…

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…

A key assumption of dual process theory is that reasoning is an explicit, effortful, deliberative process. The present study offers evidence for an implicit, possibly intuitive component of reasoning. Participants were shown sentences embedded in logically valid or invalid arguments. Participants were not asked to reason but instead rated the…

Posterior Predictive Model Checking (PPMC) is a Bayesian model checking method that compares the observed data to (plausible) future observations from the posterior predictive distribution. We propose an alternative to PPMC in the context of structural equation modeling, which we term the Poor Persons PPMC (PP-PPMC), for the situation wherein one…