It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…

Background: Meta-analysis is considered to be the gold standard for evidence synthesis. It involves combining data from multiple independent sources to produce a summary estimate with improved precision. Traditionally, meta-analysis methods have been applied to a large collection of studies, and past research efforts have indicated its numerous…

The primary purpose of this study was to systematically review the literature regarding the characteristics, use, and implementation of an emerging assessment methodology, "SRL microanalysis." Forty-two studies across diverse samples, contexts, and research methodologies met inclusion criteria. The majority of studies used microanalysis…

Measurement error affects the quality of population orderings of an index and, hence, increases the misclassification of the poor and the non-poor groups and affects statistical inferences from binary regression models. Hence, the conclusions about the extent, profile, and distribution of poverty are likely to be misleading. However, the size and…

Purpose: The goal of this study was to identify some potential key cognitive and communicative processes underlying narrative discourse ability following traumatic brain injury (TBI). Specifically, this study (a) investigated the contribution of working memory (WM) and inferencing to narrative discourse comprehension and production; (b) tested key…

The purpose of this study was to compare the relative effects of word reading and story component interventions in developing reading comprehension of narrative texts with four students with mild levels of intellectual disability. A multielement design was used in this study. The findings revealed that the story component intervention was more…

Today's world is characterized by the extensive production of data in different scenarios that everyday citizens need to understand for their informed participation in society. With the increase in the availability of data in a society defined by the industrious production of data, the educational system needs to think of possibilities to bring…

Recent research suggests the benefits of supporting a progressive understanding of concepts of inference prior to the teaching of procedures and formal calculations through the study of informal statistical inference (ISI). To contribute to the growing knowledge about the early learning and teaching of statistics, particularly regarding the…

This article pushes forward a critical dialogue about the value of visualization as a method of sociological theorizing. Building on a nascent literature, I argue theory diagrams may operate not only conjunctively but also disjunctively, independent from empirics; that their theoretical value lies not only in capturing sociological problems but…

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…

Given the relevance of graphs of functions, we consider their inclusion in primary education from the functional approach to early algebra. The purpose of this article is to shed some light on the students' production and reading of graphs when they solved generalization problems from a functional thinking approach. We aim to explore how 3rd and…

A modified and improved inductive inferential approach to evaluate item discriminations in a conditional maximum likelihood and Rasch modeling framework is suggested. The new approach involves the derivation of four hypothesis tests. It implies a linear restriction of the assumed set of probability distributions in the classical approach that…

Thinking about knowledge and knowing ("i.e.", epistemic cognition) is an important part of student learning and has implications for how they apply their knowledge in future courses, careers, and other aspects of their lives. Three classes of models have emerged from research on epistemic cognition: developmental models, dimensional…

This Family and Practitioner Brief discusses how deaf children who have not had access to a complete language from birth often encounter unique challenges in developing academic language skills, particularly in the realm of inference-making.

We evaluated the efficacy of Early Language Comprehension Individualized Instruction (ELCII), a supplemental computer-based early language comprehension intervention, in improving kindergarten students' inference making performance. In Study 1, students completed ELCII modules over nine weeks, whereas a business-as-usual control group engaged in…