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Keselman, H. J.; And Others – Journal of Educational Statistics, 1993
This article shows how a multivariate approximate degrees of freedom procedure based on the Welch-James procedure as simplified by S. Johansen (1980) can be applied to the analysis of repeated measures designs without assuming covariance homogeneity. A Monte Carlo study illustrates the approach. (SLD)
Descriptors: Analysis of Covariance, Equations (Mathematics), Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Wu, Yow-wu B. – Educational and Psychological Measurement, 1984
The present study compares the robustness of two different one way fixed-effects analysis of covariance (ANCOVA) models to investigate whether the model which uses a test statistic incorporating estimates of separate unequal regression slopes is more robust than the conventional model which assumes the slopes are equal. (Author/BW)
Descriptors: Analysis of Covariance, Comparative Analysis, Computer Simulation, Hypothesis Testing
Peer reviewed Peer reviewed
Chou, Chih-Ping; Bentler, P. M. – Multivariate Behavioral Research, 1990
The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Mathematical Models
Corder-Bolz, Charles R. – 1978
A Monte Carlo Study was conducted to evaluate six models commonly used to evaluate change. The results revealed specific problems with each. Analysis of covariance and analysis of variance of residualized gain scores appeared to substantially and consistently overestimate the change effects. Multiple factor analysis of variance models utilizing…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Hypothesis Testing
Peer reviewed Peer reviewed
Sherman, Charles R. – Psychometrika, 1972
Results provide a first step toward the establishment of guidelines for the experimenter who wishes to use nonmetric multidimensional scaling effectively, especially when an underlying configuration is hypothesized. (Author)
Descriptors: Analysis of Covariance, Analysis of Variance, Evaluation, Goodness of Fit
Peer reviewed Peer reviewed
Gallini, Joan K., Mandeville, Garrett K. – Journal of Experimental Education, 1984
This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)
Descriptors: Analysis of Covariance, Error of Measurement, Goodness of Fit, Mathematical Models
Peer reviewed Peer reviewed
Brown, R. L. – Educational and Psychological Measurement, 1989
Three correlation matrices (PEARSON, POLYCHORIC, and TOBIT) were used to obtain reliability estimates on ordered polytomous variable models. A Monte Carlo study with different levels of variable asymmetry and 400 sample correlation matrices demonstrated that the PEARSON matrix did not perform as well as did the other 2 matrices. (SLD)
Descriptors: Analysis of Covariance, Comparative Analysis, 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
Peer reviewed Peer reviewed
Cappelleri, Joseph C.; And Others – Evaluation Review, 1991
A conceptual approach and a set of computer simulations are presented to demonstrate that random measurement error in the pretest does not bias the estimate of the treatment effect in the regression-discontinuity design. Focus is on the case of no interaction between pretest and treatment on posttest. (SLD)
Descriptors: Analysis of Covariance, Computer Simulation, Equations (Mathematics), Error of Measurement
Edwards, Lynne K. – 1990
One of the most frequently used research methods in education and psychology involves repeated observations on the same individuals. When sample sizes are relatively small and a multivariate analysis lacks power, there are currently two analytical options in testing time effects. One is to assume a time series structure to these observations, and…
Descriptors: Analysis of Covariance, Comparative Analysis, Correlation, Educational Research