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Qian, Jiahe – ETS Research Report Series, 2020
The finite population correction (FPC) factor is often used to adjust variance estimators for survey data sampled from a finite population without replacement. As a replicated resampling approach, the jackknife approach is usually implemented without the FPC factor incorporated in its variance estimates. A paradigm is proposed to compare the…
Descriptors: Computation, Sampling, Data, Statistical Analysis
Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
Suk, Youmi; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2021
There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…
Descriptors: Artificial Intelligence, Statistical Analysis, Statistical Inference, Classification
Ilhan, Mustafa – International Journal of Assessment Tools in Education, 2019
This study investigated the effectiveness of statistical adjustments applied to rater bias in many-facet Rasch analysis. Some changes were first made in the dataset that did not include "rater × examinee" bias to cause to have "rater × examinee" bias. Later, bias adjustment was applied to rater bias included in the data file,…
Descriptors: Statistical Analysis, Item Response Theory, Evaluators, Bias
Alonzo, Julie; Anderson, Daniel – Behavioral Research and Teaching, 2018
In response to a request for additional analyses, in particular reporting confidence intervals around the results, we re-analyzed the data from prior studies. This supplementary report presents the results of the additional analyses addressing classification accuracy, reliability, and criterion-related validity evidence. For ease of reference, we…
Descriptors: Curriculum Based Assessment, Computation, Statistical Analysis, Accuracy
Alonzo, Julie; Anderson, Daniel – Behavioral Research and Teaching, 2018
In response to a request for additional analyses, in particular reporting confidence intervals around the results, we re-analyzed the data from prior studies. This supplementary report presents the results of the additional analyses addressing classification accuracy, reliability, and criterion-related validity evidence. For ease of reference, we…
Descriptors: Curriculum Based Assessment, Computation, Statistical Analysis, Classification
Tindal, Gerald; Nese, Joseph F. T.; Stevens, Joseph J. – Educational Assessment, 2017
For the past decade, the accountability model associated with No Child Left Behind (NCLB) emphasized proficiency on end of year tests; with Every Student Succeeds Act (ESSA) the emphasis on proficiency within statewide testing programs, though now integrated with other measures of student learning, nevertheless remains a primary metric for…
Descriptors: Testing Programs, Middle School Students, Models, State Standards
Ost, Ben; Gangopadhyaya, Anuj; Schiman, Jeffrey C. – Education Economics, 2017
Studies using tests scores as the dependent variable often report point estimates in student standard deviation units. We note that a standard deviation is not a standard unit of measurement since the distribution of test scores can vary across contexts. As such, researchers should be cautious when interpreting differences in the numerical size of…
Descriptors: Scores, Statistical Analysis, Measurement, Computation
Yarbrough, Jamie L.; Cannon, Laura; Bergman, Shawn; Kidder-Ashley, Pamela; McCane-Bowling, Sara – Journal of Psychoeducational Assessment, 2017
Numerous studies have identified differences between males and females in academic performance across the areas of reading, writing, and mathematics. The current study examined whether or not gender differences exist when math curriculum-based measures (M-CBMs) are used to assess basic math computation skills in a sample of third- through…
Descriptors: Gender Differences, Curriculum Based Assessment, Mathematics Achievement, Grade 3
Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo – Journal of Educational Psychology, 2017
The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects, and domain-specific effects were indexed by prior grade…
Descriptors: Longitudinal Studies, Mathematics Achievement, Knowledge Level, Developmental Stages
Westine, Carl D. – Society for Research on Educational Effectiveness, 2015
A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…
Descriptors: Correlation, Randomized Controlled Trials, Science Achievement, Cluster Grouping
Brandon, Paul R.; Harrison, George M.; Lawton, Brian E. – American Journal of Evaluation, 2013
When evaluators plan site-randomized experiments, they must conduct the appropriate statistical power analyses. These analyses are most likely to be valid when they are based on data from the jurisdictions in which the studies are to be conducted. In this method note, we provide software code, in the form of a SAS macro, for producing statistical…
Descriptors: Statistical Analysis, Correlation, Effect Size, Benchmarking
Bohrnstedt, G.; Kitmitto, S.; Ogut, B.; Sherman, D.; Chan, D. – National Center for Education Statistics, 2015
The School Composition and the Black-White Achievement Gap study was undertaken by the National Center for Education Statistics to present both descriptive and associative information on the relationships among the percentage of students in a school who were Black (referred to as "Black student density" or "density"), the…
Descriptors: School Demography, Racial Composition, Achievement Gap, African American Students
Tong, Xin; Zhang, Zhiyong – Multivariate Behavioral Research, 2012
Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…
Descriptors: Models, Robustness (Statistics), Statistical Analysis, Error of Measurement
Yeo, Seungsoo; Fearrington, Jamie Y.; Christ, Theodore J. – Assessment for Effective Intervention, 2012
Oral reading tasks and Maze reading tasks are often used interchangeably to assess the level and rate of reading skill development. This study examined the concurrent validity of growth estimates derived from "Curriculum-Based Measurement of Oral Reading" (CBM-R) and "Maze Reading" (CBM-mR). Participants were 1,528 students…
Descriptors: Curriculum Based Assessment, Oral Reading, Reading Tests, Cloze Procedure
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