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Glaman, Ryan; Chen, Qi; Henson, Robin K. – Journal of Experimental Education, 2022
This study compared three approaches for handling a fourth level of nesting when analyzing cluster-randomized trial (CRT) data. Although CRT data analyses may include repeated measures, individual, and cluster levels, there may be an additional fourth level that is typically ignored. This study examined the impact of ignoring this fourth level,…
Descriptors: Randomized Controlled Trials, Hierarchical Linear Modeling, Data Analysis, Simulation
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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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Shen, Ting; Konstantopoulos, Spyros – Journal of Experimental Education, 2022
Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine…
Descriptors: Data Collection, Educational Research, Hierarchical Linear Modeling, Bayesian Statistics
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Lee, Daniel Y.; Harring, Jeffrey R.; Stapleton, Laura M. – Journal of Experimental Education, 2019
Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…
Descriptors: Longitudinal Studies, Research Methodology, Research Problems, Data Analysis
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Huberty, Carl J. – Journal of Experimental Education, 1975
An empirical comparison is made of three proposed indices of relative predictor variable contribution: (1) the scaled weights of the first discriminant function; (2) the total group estimates of the correlations between each predictor variable and the first function; and (3) the within-groups estimates of the correlations between each predictor…
Descriptors: Correlation, Data Analysis, Discriminant Analysis, Educational Research
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Wentworth, Donald R.; Lewis, Darrell R. – Journal of Experimental Education, 1973
This paper describes a study that attempts to measure the influence of a commercially available game, Marketplace, on student achievement is economic understanding and student attitudes toward the instructional process and selected economic concepts. (Author)
Descriptors: Academic Achievement, Course Evaluation, Data Analysis, Economics Education
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Ferron, John; Ware, William – Journal of Experimental Education, 1995
The power of randomization tests was systematically examined through simulation for typical designs that rely on the random assignment of interventions within the observation sequence. A 30-observation AB design, 32-observation AB design, and multiple baseline AB (15 observations on 4 individuals) were studied. Power estimates were generally found…
Descriptors: Data Analysis, Effect Size, Estimation (Mathematics), Power (Statistics)
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Van Sickle, Ronald – Journal of Experimental Education, 1977
Examines the effects of selected educational simulation game design and process variables on participants' comprehension of decision-making criteria, interest in real-life analogue of the decision-making procedure, sense of group integration, and satisfaction with participation. (Editor/RK)
Descriptors: Decision Making, Educational Games, Educational Research, Game Theory
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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
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Baldwin, Lee; And Others – Journal of Experimental Education, 1984
Within-class regression is a method, developed in this paper, of comparing a large number of nonequivalent groups. This study indicated that within-class regression was a less biased method of data analysis and will yield more accurate estimates of treatment effects than analysis of covariance. (PN)
Descriptors: Analysis of Covariance, Data Analysis, Educational Research, Evaluation Methods