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Harrop, John W.; Velicer, Wayne F. – Multivariate Behavioral Research, 1985
Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)
Descriptors: Computer Simulation, Data Analysis, Mathematical Models, Matrices
Peer reviewed Peer reviewed
Williams, John D. – Multiple Linear Regression Viewpoints, 1977
The problems of two way analysis of variance designs with unequal and disproportionate cell sizes are discussed. A variety of solutions are discussed and a new solution is presented. (JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Matrices
Carlson, James E.; Timm, Neil H. – 1980
This paper presents two extensions of the full-rank multivariate linear model that are particularly useful in multivariate analysis of covariance (MANCOVA) and repeated measurements designs. After a review of the basic full-rank model, an extension is described which allows restrictions of a more general nature. This model is useful in the…
Descriptors: Analysis of Covariance, Data Analysis, Hypothesis Testing, Mathematical Formulas
Peer reviewed Peer reviewed
Sirotnik, Kenneth; Wellington, Roger – Journal of Educational Measurement, 1977
A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)
Descriptors: Analysis of Variance, Data Analysis, Item Sampling, Mathematical Models
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Williams, John D.; Wali, Mohan K.
A solution is proposed for analysis of variance procedures with missing cells, such as may occur when a control group is not assigned to any of the rows or columns of the various experimental groups. Mathematical models for two-way design are presented which define several variables; as well as row effect, column effect, and row and column…
Descriptors: Analysis of Variance, Control Groups, Experimental Groups, Hypothesis Testing