Interoception, the body's perception of its own internal states, is thought to be altered in autism, though results of empirical studies have been inconsistent. The current study systematically reviewed and meta-analyzed the extant literature comparing interoceptive outcomes between autistic (AUT) and neurotypical (NT) individuals, determining…

A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate…

In order to detect a wide range of aberrant behaviors, it can be useful to incorporate information beyond the dichotomous item scores. In this paper, we extend the l[subscript z] and l*[subscript z] person-fit statistics so that unusual behavior in item scores and unusual behavior in item distractors can be used as indicators of aberrance. Through…

According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to…

Social desirability bias (SDB) has been a major concern in educational and psychological assessments when measuring latent variables because it has the potential to introduce measurement error and bias in assessments. Person-fit indices can detect bias in the form of misfitted response vectors. The objective of this study was to compare the…

In this report, we analyze students' learning of compound probability by describing connections they generated while engaged with tasks involving two independent events. Several of their connections were compatible with the development of expertise, such as recognizing the need to determine sample spaces across a variety of situations and noting…

Percentage of uncontaminated correlations (PUC), explained common variance (ECV), and omega hierarchical ([omega]H) have been used to assess the degree to which a scale is essentially unidimensional and to predict structural coefficient bias when a unidimensional measurement model is fit to multidimensional data. The usefulness of these indices…

This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…

Providing a rich context has become a sine qua non of principled teaching of applied statistical thinking. With increasing opportunities to access secondary data, there should be increasing opportunity to work with rich context. We review the contextual information provided in 41 data sets suitable for introductory tertiary statistics teaching,…

There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…

This study proposed Gibbs sampling algorithms for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model. Three types of shrinkage priors were employed to obtain shrinkage estimates: double-exponential (i.e., Laplace), horseshoe, and horseshoe+ priors. These shrinkage priors were…

The latest edition highlights information about schools, enrollment, and staffing patterns for Catholic elementary and secondary schools for the 2022-2023 school year. [For the 2021-2022 edition, see ED620428.]

We consider the statistical inference for noisy incomplete binary (or 1-bit) matrix. Despite the importance of uncertainty quantification to matrix completion, most of the categorical matrix completion literature focuses on point estimation and prediction. This paper moves one step further toward the statistical inference for binary matrix…

While calculus remains the gold standard of academic rigor in most college admissions offices, educators and employers increasingly champion advanced statistics as critical for navigating today's data-driven workforce. So which math pathway actually shapes long-term success? To find out, we asked UT Austin Associate Professor Matt Giani, graduate…

This article discusses and contrasts the measures of association introduced by Pearson, Spearman, and Kendall, as these are the three most commonly used in practice and also the ones primarily covered in introductory statistics courses. Emphasis is placed on concepts pertaining to the measurement of the level of association between two variables,…