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Kyle T. Turner; George Engelhard Jr. – Journal of Experimental Education, 2024
The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…
Descriptors: Data Analysis, Multivariate Analysis, Individual Characteristics, Behavior
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Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
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Kadengye, Damazo T.; Ceulemans, Eva; Van Den Noortgate, Wim – Journal of Experimental Education, 2015
In educational environments, monitoring persons' progress over time may help teachers to evaluate the effectiveness of their teaching procedures. Electronic learning environments are increasingly being used as part of formal education and resulting datasets can be used to understand and to improve the environment. This study presents…
Descriptors: Electronic Learning, Educational Environment, Longitudinal Studies, Item Response Theory
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Ferron, John; Jones, Peggy K. – Journal of Experimental Education, 2006
The authors present a method that ensures control over the Type I error rate for those who visually analyze the data from response-guided multiple-baseline designs. The method can be seen as a modification of visual analysis methods to incorporate a mechanism to control Type I errors or as a modification of randomization test methods to allow…
Descriptors: Multivariate Analysis, Data Analysis, Inferences, Monte Carlo Methods
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Williamson, Gary L. – Journal of Experimental Education, 1990
A growth curve approach to longitudinal profile analysis is presented by which univariate and multivariate descriptions of achievement and rate of growth are provided, and intraindividual strengths and weaknesses are computed for profiles of achievement and progress. Analyses are reported for simulated data conforming to a straight-line growth…
Descriptors: Academic Achievement, Achievement Gains, Data Analysis, Individual Characteristics