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Peer reviewedToothaker, Larry E.; And Others – Journal of Educational Statistics, 1983
Several methods have been proposed for the analysis of data from single-subject research settings. This research focuses on two methods which have been proposed in previous articles. Criticisms of the methods are presented along with recommendations for practice. (Author/JKS)
Descriptors: Analysis of Variance, Case Studies, Correlation, Hypothesis Testing
Download full textWu, Yi-Cheng; McLean, James E. – 1994
The most widely used procedures to harness the power of a concomitant (nuisance) variable are block designs and analysis of covariance (ANCOVA). This study attempted to provide a scientific foundation on which to base decisions on whether to block or covary and how many blocks to be used if blocking is selected. Monte Carlo generated data were…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Decision Making
Peer reviewedKromrey, Jeffrey D.; Dickinson, Wendy B. – Educational and Psychological Measurement, 1996
Empirical estimates of the power and Type I error rate of the test of the classrooms-within-treatments effect in the nested analysis of variance approach are provided for a variety of nominal alpha levels and a range of classroom effect sizes and research designs. (SLD)
Descriptors: Analysis of Variance, Correlation, Educational Research, Effect Size
Noe, Michael J. – 1976
This study compared three approaches to the two-factor experiment with repeated measures on one factor: (1) the conventional mixed model analysis of variance, (2) the Greenhouse-Geisser conservative analysis of variance, and (3) multivariate extensions of analysis of variance. Computer simulated data were used in a total of 96 sets of covariance…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Correlation
Wu, Yi-Cheng; McLean, James E. – 1993
By employing a concomitant variable, researchers can reduce the error, increase the precision, and maximize the power of an experimental design. Blocking and analysis of covariance (ANCOVA) are most often used to harness the power of a concomitant variable. Whether to block or covary and how many blocks to be used if a block design is chosen…
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Correlation
Dickinson, Terry L. – 1985
The general linear model was described, and the influence that measurement errors have on model parameters was discussed. In particular, the assumptions of classical true-score theory were used to develop algebraic relationships between the squared multiple correlations coefficient and the regression coefficients in the infallible and fallible…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Error of Measurement
Hummel, Thomas J.; Johnston, Charles B. – 1986
This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Differences
