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Bruno Arpino; Silvia Bacci; Leonardo Grilli; Raffaele Guetto; Carla Rampichini – Evaluation Review, 2025
We consider estimating the effect of a treatment on a given outcome measured on subjects tested both before and after treatment assignment in observational studies. A vast literature compares the competing approaches of modelling the post-test score conditionally on the pre-test score versus modelling the difference, namely, the gain score. Our…
Descriptors: Scores, Pretesting, Conditioning, Achievement Gains
Oliver Lüdtke; Alexander Robitzsch – Journal of Experimental Education, 2025
There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…
Descriptors: Statistical Analysis, Longitudinal Studies, Error of Measurement, Hierarchical Linear Modeling
A Multi-Level Analysis of the Effects of Statistics Anxiety/Attitudes on Trajectories of Exam Scores
MacArthur, Kelly Rhea; Santo, Jonathan B. – Journal of Statistics and Data Science Education, 2023
This study explores three understudied facets--quadratic effects, change over time, and gender as a moderator--of the otherwise well-documented relationships between statistics anxiety and academic performance. Using pre- and post- course survey data among a sample of 111 undergraduate students in Social Statistics courses at a U.S. Midwestern…
Descriptors: Hierarchical Linear Modeling, Mathematics Anxiety, Statistics Education, Student Attitudes
Stephen M. Leach; Jason C. Immekus; Jeffrey C. Valentine; Prathiba Batley; Dena Dossett; Tamara Lewis; Thomas Reece – Assessment for Effective Intervention, 2025
Educators commonly use school climate survey scores to inform and evaluate interventions for equitably improving learning and reducing educational disparities. Unfortunately, validity evidence to support these (and other) score uses often falls short. In response, Whitehouse et al. proposed a collaborative, two-part validity testing framework for…
Descriptors: School Surveys, Measurement, Hierarchical Linear Modeling, Educational Environment
DeMars, Christine E. – Journal of Experimental Education, 2020
Multilevel Rasch models are increasingly used to estimate the relationships between test scores and student and school factors. Response data were generated to follow one-, two-, and three-parameter logistic (1PL, 2PL, 3PL) models, but the Rasch model was used to estimate the latent regression parameters. When the response functions followed 2PL…
Descriptors: Hierarchical Linear Modeling, Regression (Statistics), Simulation, Predictor Variables
F. Sehkar Fayda-Kinik; Munevver Cetin – Journal of Computer Assisted Learning, 2025
Background: The unprecedented access to information in the 21st century entails a deep understanding of information and communication technology (ICT)-related factors in education and their impacts on learning and teaching. The role of attitudes towards ICT is a proven factor in student achievement. However, there is no consensus about the…
Descriptors: Information Technology, Technology Uses in Education, Academic Achievement, Secondary Education
Gary Rempe; Michelle N. Saltis; David W. Matheson; Sydney Cople – Journal of Youth Development, 2023
The purpose of this study was to explore potential effects of a 12-week therapeutic mentoring program targeting social, emotional, and behavioral concerns in 52 children and adolescents between 11 and 17 years of age. Self-reported scores on a norm-referenced behavioral questionnaire were tracked across the span of a mentoring program, and then…
Descriptors: Norm Referenced Tests, Mentors, Therapy, Hierarchical Linear Modeling
Xiao, ZhiMin; Higgins, Steve; Kasim, Adetayo – Journal of Experimental Education, 2019
Lord's Paradox occurs when a continuous covariate is statistically controlled for and the relationship between a continuous outcome and group status indicator changes in both magnitude and direction. This phenomenon poses a challenge to the notion of evidence-based policy, where data are supposed to be self-evident. We examined 50 effect size…
Descriptors: Statistical Analysis, Decision Making, Research Methodology, Scores
Palermo, Corey; Bunch, Michael B.; Ridge, Kirk – Journal of Educational Measurement, 2019
Although much attention has been given to rater effects in rater-mediated assessment contexts, little research has examined the overall stability of leniency and severity effects over time. This study examined longitudinal scoring data collected during three consecutive administrations of a large-scale, multi-state summative assessment program.…
Descriptors: Scoring, Interrater Reliability, Measurement, Summative Evaluation
Campione-Barr, Nicole; Lindell, Anna K.; Giron, Sonia E. – Developmental Psychology, 2020
The use of differences scores to assess agreement/disagreement has a long and contentious history. Laird (2020) notes, however, that developmentalists have been particularly resistant to discontinue the use of difference scores. One area of developmental science where difference scores are still in regular use is that of parental differential…
Descriptors: Educational Research, Hypothesis Testing, Differences, Scores
Stallasch, Sophie E.; Lüdtke, Oliver; Artelt, Cordula; Brunner, Martin – Journal of Research on Educational Effectiveness, 2021
To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous…
Descriptors: Foreign Countries, Randomized Controlled Trials, Intervention, Educational Research
Chan, Wendy – Journal of Educational and Behavioral Statistics, 2018
Policymakers have grown increasingly interested in how experimental results may generalize to a larger population. However, recently developed propensity score-based methods are limited by small sample sizes, where the experimental study is generalized to a population that is at least 20 times larger. This is particularly problematic for methods…
Descriptors: Computation, Generalization, Probability, Sample Size
Quesen, Sarah; Lane, Suzanne – Applied Measurement in Education, 2019
This study examined the effect of similar vs. dissimilar proficiency distributions on uniform DIF detection on a statewide eighth grade mathematics assessment. Results from the similar- and dissimilar-ability reference groups with an SWD focal group were compared for four models: logistic regression, hierarchical generalized linear model (HGLM),…
Descriptors: Test Items, Mathematics Tests, Grade 8, Item Response Theory
Harel, Daphna; McAllister, Tara – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Research in communication sciences and disorders frequently involves the collection of clusters of observations, such as a series of scores for each individual receiving treatment over the course of an intervention study. However, little discipline-specific guidance is currently available on the subject of building and interpreting…
Descriptors: Communication Disorders, Intervention, Scores, Guidance
Lee, HyeSun – Applied Measurement in Education, 2018
The current simulation study examined the effects of Item Parameter Drift (IPD) occurring in a short scale on parameter estimates in multilevel models where scores from a scale were employed as a time-varying predictor to account for outcome scores. Five factors, including three decisions about IPD, were considered for simulation conditions. It…
Descriptors: Test Items, Hierarchical Linear Modeling, Predictor Variables, Scores