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Yongseok Lee; Walter L. Leite; Audrey J. Leroux – Journal of Experimental Education, 2024
In the current study, we compare propensity score (PS) matching methods for data with a cross-classified structure, where each individual is clustered within more than one group, but the groups are not hierarchically organized. Through a Monte Carlo simulation study, we compared sequential cluster matching (SCM), preferential within cluster…
Descriptors: Comparative Analysis, Data Analysis, Groups, Classification
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Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
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Vaughn, Brandon K.; Wang, Qui – Journal of Experimental Education, 2008
The authors consider the problem of classifying an unknown observation into 1 of several populations by using tree-structured allocation rules. Although many parametric classification procedures are robust to certain assumption violations, there is need for classification procedures that can be used regardless of the group-conditional…
Descriptors: Classification, Regression (Statistics), Discriminant Analysis, Monte Carlo Methods
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Katz, Barry M.; McSweeney, Maryellen – Journal of Experimental Education, 1979
Errors of misclassification and their effects on categorical data analysis are discussed. The chi-square test for equality of two proportions is examined in the context of errorful categorical data. The effects of such errors are illustrated. A correction procedure is developed and discussed. (Author/MH)
Descriptors: Classification, Data Analysis, Data Collection, Error Patterns