We examine the accuracy of p values obtained using the asymptotic mean and variance (MV) correction to the distribution of the sample standardized root mean squared residual (SRMR) proposed by Maydeu-Olivares to assess the exact fit of SEM models. In a simulation study, we found that under normality, the MV-corrected SRMR statistic provides…

As the international large-scale assessments (ILSAs) become more popular, policy makers and education practitioners are interested in collecting as much student background information as possible to better understand the learning context of their students. To collect such abundant information, administrators need to develop a lot of questions.…

Access to authentic research is limited at the 7-12 science education level. At the same time, many local restoration projects would benefit from, but don't have access to a long-term system of monitoring. This project seeks to unite those two needs by developing a protocol for 7-12 classrooms to be able to participate in authentic research…

This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…

Because of the high cost, venue-based probability sampling of young men who have sex with men (YMSM) is largely inaccessible to social researchers. The aim of this study is to compare the feasibility of implementing geosocial networking application-based (GSNA) and venue-based probability sampling of young men who have sex with men. A…

In science education, there has been a sustained focus on supporting the emergence of science practices in K-12 and field-based settings. Recent work has elevated the integral role of emotion in sparking and sustaining such disciplinary practices, deepening the field's understanding of what is entailed in "doing" science. Yet even as we…

Purpose: Language sample analysis (LSA) represents an ecologically valid method for diagnosing, identifying goals, and measuring progress in children with developmental language disorder (DLD). LSA is, however, time consuming. The purpose of this study was to determine the length of sample needed to obtain reliable LSA measures for children in…

We investigated the potential impact of differential item functioning (DIF) on group-level mean and standard deviation estimates using empirical and simulated data in the context of large-scale assessment. For the empirical investigation, PISA 2018 cognitive domains (Reading, Mathematics, and Science) data were analyzed using Jackknife sampling to…

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…

Online platforms offer new opportunities to study human behavior. However, while social scientists are often interested in using behavioral trace data--data created by a user over the course of their everyday life--to draw inferences about users, many online platforms only allow data to be sampled based on user activities (leading to data sets…

As the integration of digital technologies continues to shape academic landscapes, assessing digital literacy in the context of academic writing becomes paramount. Several instruments and frameworks are available for measuring digital literacy and examining it from different perspectives; however, none are suitable for measuring the digital…

Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework…

This study addresses measurement issues around a standards-based content analysis of mathematics textbooks' coverage of standards for use in large-scale monitoring of standards implementation as proposed in a 2013 report by the National Research Council. An earlier study produced an exhaustive content analysis of textbooks using the 2012 Common…

Variability is common in language sample analysis (LSA), arising from personal factors such as age or level of education, or from factors within the text such as its length and purpose. Variability can affect interpretation of results in clinical practice and research studies, as well as the ability to detect change in individuals over time. This…