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Paul A. Jewsbury; Matthew S. Johnson – Large-scale Assessments in Education, 2025
The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…
Descriptors: Factor Analysis, Matrices, Regression (Statistics), Educational Assessment
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2018
Wollack, Cohen, and Eckerly suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This article suggests two modifications of the EDI for…
Descriptors: Deception, Identification, Testing Problems, Cheating
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Sinharay, Sandip – Grantee Submission, 2017
Wollack, Cohen, and Eckerly (2015) suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly (2017) extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This paper suggests two modifications of…
Descriptors: Deception, Identification, Testing Problems, Cheating