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Fahle, Erin; Reardon, Sean – Society for Research on Educational Effectiveness, 2016
Describing the variation in test scores between and within school districts is critical for: (1) for policy-related and descriptive work that investigates the sorting of students among districts and the differential effectiveness of those districts; and (2) for methodological work planning future experiments or interventions. Intraclass…
Descriptors: School Districts, Scores, Comparative Analysis, School Effectiveness
Meshbane, Alice; Morris, John D. – 1994
A method for comparing the cross validated classification accuracies of linear and quadratic classification rules is presented under varying data conditions for the k-group classification problem. With this method, separate-group as well as total-group proportions of correct classifications can be compared for the two rules. McNemar's test for…
Descriptors: Classification, Comparative Analysis, Correlation, Discriminant Analysis
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Zimmerman, Donald W.; Zumbo, Bruno D. – Educational and Psychological Measurement, 1993
A computer simulation compared significance tests of correlation coefficients calculated from initial scores, from ranks assigned by the Spearman method, and from three kinds of modified ranks. Implications of findings for the idea that rank correlation is a nonparametric correlation method are discussed. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Nonparametric Statistics
Morris, John D.; Huberty, Carl J. – 1986
Formulas for estimating cross-validated hit-rates, the number of correct classifications into an a priori grouping structure, were examined. The following mathematical formulas were compared: McLachlan's formula estimator, two Snappin and Knoke smoothed formula estimators, and the analytic leave-one-out estimator. The R method was included as a…
Descriptors: Classification, Comparative Analysis, Correlation, Estimation (Mathematics)
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Williams, Richard H.; Zimmerman, Donald W. – Journal of Experimental Education, 1982
The reliability of simple difference scores is greater than, less than, or equal to that of residualized difference scores, depending on whether the correlation between pretest and posttest scores is greater than, less than, or equal to the ratio of the standard deviations of pretest and posttest scores. (Author)
Descriptors: Achievement Gains, Comparative Analysis, Correlation, Pretests Posttests
Chastain, Robert L.; Joe, George W. – 1986
Multivariate methods were used to identify between-set factors relating the criterion set of eleven Wechsler Adult Intelligence Scale Revised subtest variables to the predictor set of demographic variables: age, race, sex, education, occupation, geographic region, and urban versus rural residence. Although factor analysis is usually used to…
Descriptors: Adults, Comparative Analysis, Correlation, Factor Analysis
Hambleton, Ronald K.; Rovinelli, Richard J. – 1986
Four methods for determining the dimensionality of a set of test items were compared: (1) linear factor analysis; (2) residual analysis; (3) nonlinear factor analysis; and (4) Bejar's method. Five artificial test data sets (for 40 items and 1500 examinees) were generated, consistent with the three-parameter logistic model and the assumption of…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Factor Analysis
Burkhalter, Bettye B.; And Others – 1983
To examine and clarify background conditions for understanding variables which affect salary, the salary and compensation programs at two industrial and three educational organizations were subjected to a statistical audit. Data were available on 272 employees. Ten compensation variables were studied as having direct or indirect effects on salary:…
Descriptors: Comparative Analysis, Correlation, Individual Characteristics, Mathematical Models
Muraki, Eiji – 1984
The TESTFACT computer program and full-information factor analysis of test items were used in a computer simulation conducted to correct for the guessing effect. Full-information factor analysis also corrects for omitted items. The present version of TESTFACT handles up to five factors and 150 items. A preliminary smoothing of the tetrachoric…
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Correlation
Thompson, Bruce – 1985
Hypothetical data sets are used to demonstrate how canonical correlation methods subsume other commonly utilized parametric methods. Analysis of variance, analysis of covariance, multiple analysis of variance, and multiple analysis of covariance are heavily used by educational researchers. It is concluded that researchers would do well to consider…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Correlation
Buhr, Dianne C.; Algina, James – 1986
The focus of this study is on the estimation procedures implemented in BILOG, a computer program. One purpose is to compare the item parameter estimates produced by various procedures available in BILOG. Four different models are used: the one, two, and three parameter model and a three parameter model with common guessing parameters. The results…
Descriptors: Ability, Bayesian Statistics, Comparative Analysis, Computer Oriented Programs
Mathis, Harry Ray – 1972
The purpose of this study was to determine the validity of the American College Test (ACT) in predicting academic achievement of students from an area which is culturally, economically, and educationally depressed. The population, chosen from 6 community colleges serving the Appalachian region of Kentucky, consisted of 1,127 full time (12 or more…
Descriptors: Academic Achievement, Achievement Tests, Community Colleges, Comparative Analysis
Hummel, Thomas J.; Johnston, Charles B. – 1986
This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Differences
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Miao, Jing; Haney, Walt – Education Policy Analysis Archives, 2004
The No Child Left Behind Act has brought great attention to the high school graduation rate as one of the mandatory accountability measures for public school systems. However, there is no consensus on how to calculate the high school graduation rate given the lack of longitudinal databases that track individual students. This study reviews…
Descriptors: High Schools, Graduation Rate, Ethnic Groups, Accountability