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Jamshidi, Laleh; Declercq, Lies; Fernández-Castilla, Belén; Ferron, John M.; Moeyaert, Mariola; Beretvas, S. Natasha; Van den Noortgate, Wim – Journal of Experimental Education, 2021
Previous research found bias in the estimate of the overall fixed effects and variance components using multilevel meta-analyses of standardized single-case data. Therefore, we evaluate two adjustments in an attempt to reduce the bias and improve the statistical properties of the parameter estimates. The results confirm the existence of bias when…
Descriptors: Statistical Bias, Multivariate Analysis, Meta Analysis, Research Design
Chang, Wanchen; Pituch, Keenan A. – Journal of Experimental Education, 2019
When data for multiple outcomes are collected in a multilevel design, researchers can select a univariate or multivariate analysis to examine group-mean differences. When correlated outcomes are incomplete, a multivariate multilevel model (MVMM) may provide greater power than univariate multilevel models (MLMs). For a two-group multilevel design…
Descriptors: Hierarchical Linear Modeling, Multivariate Analysis, Research Problems, Error of Measurement
Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
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
Huang, Francis L. – Journal of Experimental Education, 2016
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Sample Size, Error of Measurement

Games, Paul A.; Hedges, Larry V. – Journal of Experimental Education, 1987
Variance stabilizing transformations yield statistics whose standard errors are only influenced by the number of observations on which they are based. A solution that can be extended to inference on all of these parameters is presented and illustrated via three examples. (TJH)
Descriptors: Correlation, Error of Measurement, Least Squares Statistics, Multivariate Analysis
Lei, Pui-Wa; Koehly, Laura M. – Journal of Experimental Education, 2003
Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…
Descriptors: Monte Carlo Methods, Classification, Discriminant Analysis, Regression (Statistics)