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Kang, Yoonjeong; Harring, Jeffrey R.; Li, Ming – Journal of Experimental Education, 2015
The authors performed a Monte Carlo simulation to empirically investigate the robustness and power of 4 methods in testing mean differences for 2 independent groups under conditions in which 2 populations may not demonstrate the same pattern of nonnormality. The approaches considered were the t test, Wilcoxon rank-sum test, Welch-James test with…
Descriptors: Comparative Analysis, Monte Carlo Methods, Statistical Analysis, Robustness (Statistics)
Bai, Haiyan – Journal of Experimental Education, 2013
Propensity score estimation plays a fundamental role in propensity score matching for reducing group selection bias in observational data. To increase the accuracy of propensity score estimation, the author developed a bootstrap propensity score. The commonly used propensity score matching methods: nearest neighbor matching, caliper matching, and…
Descriptors: Statistical Inference, Sampling, Probability, Computation

Serlin, Ronald C. – Journal of Experimental Education, 1993
Several new multiple comparison procedures are discussed in terms of their applicability to the problem of generating confidence intervals based on range null hypotheses to control the familywise Type 1 error in multiple sample experiments. These procedures seem fairly robust to violations of normality and homogeneity assumptions. (SLD)
Descriptors: Comparative Analysis, Hypothesis Testing, Robustness (Statistics), Sampling

Levy, Kenneth J. – Journal of Experimental Education, 1979
Dunnett's procedure for comparing K-1 treatments with a control is discussed within the context of three nonparametric models: those of Kruskal-Wallis, Friedman, and Cochran. (Author/MH)
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Nonparametric Statistics

Penfield, Douglas A.; Koffler, Stephen L. – Journal of Experimental Education, 1978
Three nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two-sample Siegel-Tukey test, Mood test, and Klotz test are extended to the multisample situation by Puri's methods. These K-sample scale tests are illustrated and compared. (Author/GDC)
Descriptors: Comparative Analysis, Guessing (Tests), Higher Education, Mathematical Models

Abrams, Allan S.; And Others – Journal of Experimental Education, 1979
Evaluation of large-scale programs is problematical because of inherent bias in assignment of treatment and control groups, resulting in serious regression artifacts even with the use of analysis of covariance designs. Nonuniformity of program implementation across sites and classrooms is also a problem. (Author/GSK)
Descriptors: Analysis of Covariance, Comparative Analysis, Compensatory Education, Educational Assessment

Marascuilo, Leonard A. – Journal of Experimental Education, 1979
The utility of the biomedical model of adjusted statistics is demonstrated. The model is recommended for use by educational researchers to randomize subjects for a more accurate estimate of school programs' success or failure when compared across classrooms or other units. (Author/MH)
Descriptors: Academic Achievement, Analysis of Variance, Comparative Analysis, Criterion Referenced Tests