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Campbell, Harlan; de Jong, Valentijn M. T.; Maxwell, Lauren; Jaenisch, Thomas; Debray, Thomas P. A.; Gustafson, Paul – Research Synthesis Methods, 2021
Ideally, a meta-analysis will summarize data from several unbiased studies. Here we look into the less than ideal situation in which contributing studies may be compromised by non-differential measurement error in the exposure variable. Specifically, we consider a meta-analysis for the association between a continuous outcome variable and one or…
Descriptors: Error of Measurement, Meta Analysis, Bayesian Statistics, Statistical Analysis
Li, Lanrong; Becker, Betsy Jane – Journal of Educational Measurement, 2021
Differential bundle functioning (DBF) has been proposed to quantify the accumulated amount of differential item functioning (DIF) in an item cluster/bundle (Douglas, Roussos, and Stout). The simultaneous item bias test (SIBTEST, Shealy and Stout) has been used to test for DBF (e.g., Walker, Zhang, and Surber). Research on DBF may have the…
Descriptors: Test Bias, Test Items, Meta Analysis, Effect Size
Yuxiang Gao; Lauren Kennedy; Daniel Simpson; Andrew Gelman – Grantee Submission, 2021
A central theme in the field of survey statistics is estimating population-level quantities through data coming from potentially non-representative samples of the population. Multilevel regression and poststratification (MRP), a model-based approach, is gaining traction against the traditional weighted approach for survey estimates. MRP estimates…
Descriptors: Regression (Statistics), Statistical Analysis, Surveys, Computation
Demirkaya, Onur; Bezirhan, Ummugul; Zhang, Jinming – Journal of Educational and Behavioral Statistics, 2023
Examinees with item preknowledge tend to obtain inflated test scores that undermine test score validity. With the availability of process data collected in computer-based assessments, the research on detecting item preknowledge has progressed on using both item scores and response times. Item revisit patterns of examinees can also be utilized as…
Descriptors: Test Items, Prior Learning, Knowledge Level, Reaction Time
Bradley, Holly; Smith, Beth A.; Wilson, Rujuta B. – Infant and Child Development, 2023
Joint attention (JA) is the purposeful coordination of an individual's focus of attention with that of another and begins to develop within the first year of life. Delayed, or atypically developing, JA is an early behavioural sign of many developmental disabilities and so assessing JA in infancy can improve our understanding of trajectories of…
Descriptors: Attention, Infants, Child Development, Qualitative Research
Resolving Dimensionality in a Child Assessment Tool: An Application of the Multilevel Bifactor Model
Akaeze, Hope O.; Lawrence, Frank R.; Wu, Jamie Heng-Chieh – Educational and Psychological Measurement, 2023
Multidimensionality and hierarchical data structure are common in assessment data. These design features, if not accounted for, can threaten the validity of the results and inferences generated from factor analysis, a method frequently employed to assess test dimensionality. In this article, we describe and demonstrate the application of the…
Descriptors: Measures (Individuals), Multidimensional Scaling, Tests, Hierarchical Linear Modeling
Kenneth Tyler Wilcox; Ross Jacobucci; Zhiyong Zhang; Brooke A. Ammerman – Grantee Submission, 2023
Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…
Descriptors: Bayesian Statistics, Content Analysis, Undergraduate Students, Self Destructive Behavior
Eric C. Hedberg – Grantee Submission, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
E. C. Hedberg – American Journal of Evaluation, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
Russell, Michael; Oddleifson, Carly; Russell Kish, Micayla; Kaplan, Larry – Practical Assessment, Research & Evaluation, 2022
The deficit narrative is a critical component of the white racial frame and attributes disparate outcomes to the racialized groups themselves rather than the policies and actions that create conditions that produce these disparities. Educational research that employs racialized groups as a variable in quantitative research holds potential to…
Descriptors: Educational Research, Statistical Analysis, Racism, Racial Differences
Marie-Andrée Somers; Michael J. Weiss; Colin Hill – Grantee Submission, 2022
The last two decades have seen a dramatic increase in randomized controlled trials (RCTs) conducted in community colleges. Yet, there is limited empirical information on the design parameters necessary to plan the sample size for RCTs in this context. We provide empirical estimates of key design parameters, discussing lessons based on the pattern…
Descriptors: Randomized Controlled Trials, Research Design, Sample Size, Statistical Analysis
Pedro San Martin Soares – Journal of Psychoeducational Assessment, 2024
Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, International Assessment
Leili Tapak; Yadollah Hamidi; Zahra Toosi – Learning Organization, 2024
Purpose: Learning organization (LO) concept has received much attention in the last decades. The purpose of an LO is to proactively shape its future by fostering a culture of continuous learning among its members. This approach empowers the organization to adapt, evolve and innovate, aligning with the needs and aspirations of both internal and…
Descriptors: Organizational Learning, Questionnaires, Organizational Culture, Organizational Change
Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size
Thomas Mgonja; Francisco Robles – Journal of College Student Retention: Research, Theory & Practice, 2024
Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…
Descriptors: Predictor Variables, Remedial Mathematics, Mathematics Achievement, Graduation Rate