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Pohl, Steffi; Steiner, Peter M.; Eisermann, Jens; Soellner, Renate; Cook, Thomas D. – Educational Evaluation and Policy Analysis, 2009
Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…
Descriptors: Statistical Analysis, Social Science Research, Statistical Bias, Statistical Inference
Feir, Betty J.; Toothaker, Larry E. – 1974
Researchers are often in a dilemma as to whether parametric or nonparametric procedures should be cited when assumptions of the parametric methods are thought to be violated. Therefore, the Kruskal-Wallis test and the ANOVA F-test were empirically compared in terms of probability of a Type I error and power under various patterns of mean…
Descriptors: Analysis of Variance, Comparative Analysis, Nonparametric Statistics, Sampling
Brennan, Robert L. – 1993
Not infrequently, investigators assume that reliability for groups is greater than reliability for persons, or that the error variance for groups is less than that for persons. Using generalizability theory, it is shown that this "conventional wisdom" is not necessarily true. Examples are provided from the course-evaluation and the…
Descriptors: Comparative Analysis, Course Evaluation, Generalizability Theory, Measurement Techniques
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Brandenburg, Dale C.; Forsyth, Robert A. – Journal of Educational and Psychological Measurement, 1974
Descriptors: Achievement Tests, Comparative Analysis, Item Sampling, Mathematical Models
Blumstein, Alfred; Cohen, Jacqueline – Evaluation Quarterly, 1979
Evaluations involving nonrandom assignment to treatment or control groups are vulnerable to an accidental or intentional confounding of a selection effect with the treatment effect. Two techniques, discriminant analysis and base expectancy analysis, permit separate estimation of the selection and treatment effects in the final results. (Author/CTM)
Descriptors: Comparative Analysis, Discriminant Analysis, Hypothesis Testing, Research Design
Olejnik, Stephen; Algina, James – 1987
The purpose of this study was to develop a single procedure for comparing population variances which could be used for distribution forms. Bootstrap methodology was used to estimate the variability of the sample variance statistic when the population distribution was normal, platykurtic and leptokurtic. The data for the study were generated and…
Descriptors: Comparative Analysis, Estimation (Mathematics), Measurement Techniques, Monte Carlo Methods
Jones, Douglas H.; And Others – 1983
The discovery of disproportionate minority enrollments in special education classes has been a subject of considerable concern to federal, state, and local education officials alike for the past decade. Because the existence of disproportions is frequently thought to result from discriminatory placement practices on the part of local school…
Descriptors: Comparative Analysis, Elementary Secondary Education, Mental Retardation, Minority Group Children
Bloom, Howard S.; Michalopoulos, Charles; Hill, Carolyn J.; Lei, Ying – 2002
A study explored which nonexperimental comparison group methods provide the most accurate estimates of the impacts of mandatory welfare-to-work programs and whether the best methods work well enough to substitute for random assignment experiments. Findings were compared for nonexperimental comparison groups and statistical adjustment procedures…
Descriptors: Adult Education, Comparative Analysis, Control Groups, Error of Measurement