Cohen's kappa coefficient was originally proposed for two raters only, and it later extended to an arbitrarily large number of raters to become what is known as Fleiss' generalized kappa. Fleiss' generalized kappa and its large-sample variance are still widely used by researchers and were implemented in several software packages, including, among…

Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified,…

In our data-driven society, it is essential for students to become statistically literate. A core domain within Statistical Literacy is Statistical Inference, the ability to draw inferences from sample data. Acquiring and applying inferences is difficult for students and, therefore, usually not included in the pre-10th-grade curriculum. However,…

The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…

As adults, we intuitively understand how others' goals influence their information-seeking preferences. For example, you might recommend a dense book full of mechanistic details to someone trying to learn about a topic in-depth, but a more lighthearted book filled with surprising stories to someone seeking entertainment. Moreover, you might do…

Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…

Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…

This study examined 4- and 5-year-olds' incremental interpretation of size adjectives, focusing on whether contrastive inferences are modulated by speaker behavior. Children (N = 120, 59 females, mostly White, tested between July, 2018 and August, 2019) encountered either a conventional or unconventional speaker who labeled objects in a…

An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results…

Children with developmental language disorder (DLD) regularly use the bare form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which processing difficulties of children with DLD disproportionally affect processing novel inflected verbs in their input. Limited experience with inflection…

Language comprehension requires a complex series of decisions under uncertainty. This is especially obvious when one string may have multiple different interpretations, whether due to lexical ambiguity, or the potential for an inference beyond literal content. This dissertation profiles how the human system for language comprehension times those…

Research Findings: This study used sequential analysis to investigate teachers' use of literal and inferential questions and their relation to children's responses during small-group shared reading in preschool. Participants were 202 dual-language learners (age 3-5 years) and 53 preschool teachers in multiethnic preschool classrooms in Norway.…

Context: A perennial problem in applied statistics is the inability to justify strong claims about cause-and-effect relationships without full knowledge of the mechanism determining selection into treatment. Few research designs other than the well-implemented random assignment study meet this requirement. Researchers have proposed partial…

Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences will not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by…

In this article, examples are shown to demonstrate how open-ended mathematical activities can be used in the classroom. Open-ended activities give students opportunities to apply their understanding in unfamiliar contexts without the pressure of finding one perfect solution.