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Van Norman, Ethan R.; Klingbeil, David A.; McLendon, Katherine E. – Remedial and Special Education, 2019
Researchers and practitioners frequently use curriculum-based measures of reading (CBM-R) within single-case design (SCD) frameworks to evaluate the effects of reading interventions with individual students. Effect sizes (ESs) developed specifically for SCDs are often used as a supplement to visual analysis to gauge treatment effects. The degree…
Descriptors: Oral Reading, Error of Measurement, Progress Monitoring, Effect Size
Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun – Grantee Submission, 2017
The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…
Descriptors: Statistical Analysis, Evaluation Methods, Structural Equation Models, Reliability
Nugent, William Robert; Moore, Matthew; Story, Erin – Educational and Psychological Measurement, 2015
The standardized mean difference (SMD) is perhaps the most important meta-analytic effect size. It is typically used to represent the difference between treatment and control population means in treatment efficacy research. It is also used to represent differences between populations with different characteristics, such as persons who are…
Descriptors: Error of Measurement, Error Correction, Predictor Variables, Monte Carlo Methods
Sapp, Marty – Multicultural Learning and Teaching, 2012
Like many journals within education, for "Multicultural Learning and Teaching," this writer found little written on measurement, effect sizes, and confidence intervals; therefore, the purpose of this article is to address these factors. The effect of not addressing these issues is that a basic foundation of science cannot be established…
Descriptors: Multicultural Education, Educational Research, Scholarship, Reliability
Gagnon, Robert; Lubarsky, Stuart; Lambert, Carole; Charlin, Bernard – Advances in Health Sciences Education, 2011
The Script Concordance Test (SCT) uses a panel-based, aggregate scoring method that aims to capture the variability of responses of experienced practitioners to particular clinical situations. The use of this type of scoring method is a key determinant of the tool's discriminatory power, but deviant answers could potentially diminish the…
Descriptors: Expertise, Oncology, Scoring, Error of Measurement
Wilson, Celia M. – ProQuest LLC, 2010
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Descriptors: Monte Carlo Methods, Measurement, Multivariate Analysis, Error of Measurement

Cornwell, John M.; Ladd, Robert T. – Educational and Psychological Measurement, 1993
Simulated data typical of those from meta analyses are used to evaluate the reliability, Type I and Type II errors, bias, and standard error of the meta-analytic procedures of Schmidt and Hunter (1977). Concerns about power, reliability, and Type I errors are presented. (SLD)
Descriptors: Bias, Computer Simulation, Correlation, Effect Size
Thompson, Bruce – 1987
This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…
Descriptors: Analysis of Variance, Data Interpretation, Editors, Effect Size