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Rubin, Donald B.; And Others – Journal of Educational Statistics, 1981
A time-saving and space-saving algorithm is presented for computing the sums of squares and estimated cell means under the additive model in a two-way analysis of variance or covariance with unequal numbers of observations in the cells. The procedure is illustrated. (Author/JKS)
Descriptors: Algorithms, Analysis of Covariance, Analysis of Variance, Computer Programs

Kiiveri, H. T. – Psychometrika, 1987
Covariance structures associated with linear structural equation models are discussed. Algorithms for computing maximum likelihood estimates (namely, the EM algorithm) are reviewed. An example of using likelihood ratio tests based on complete and incomplete data to improve the fit of a model is given. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Computer Simulation, Equations (Mathematics)

Cudeck, Robert; And Others – Psychometrika, 1993
An implementation of the Gauss-Newton algorithm for the analysis of covariance structure that is specifically adapted for high-level computer languages is reviewed. This simple method for estimating structural equation models is useful for a variety of standard models, as is illustrated. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Computer Software, Equations (Mathematics)

Noh, Taehee; Scharmann, Lawrence C. – Journal of Research in Science Teaching, 1997
Describes a study that explores the instructional influence of presenting pictures at the molecular level when introducing chemistry concepts and solving chemistry problems. Explores the effect of the pictures on students' conceptions and problem-solving abilities. Contains 59 references. (DDR)
Descriptors: Algorithms, Analysis of Covariance, Chemistry, Cognitive Structures

Frigon, Jean-Yves; Laurencelle, Louis – Educational and Psychological Measurement, 1993
The statistical power of analysis of covariance (ANCOVA) and its advantages over simple analysis of variance are examined in some experimental situations, and an algorithm is proposed for its proper application. In nonrandomized experiments, an ANCOVA is generally not a good approach. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Analysis of Variance, Educational Research

Canino, Casilda; Cicchelli, Terry – Journal of Educational Computing Research, 1988
Describes aptitude treatment interaction study that used the cognitive styles field dependence and independence matched with computerized algorithmic and discovery treatments to determine mathematics achievement on a criterion-referenced test. Posttest mathematics scores and student responses to the computer are analyzed, and mastery learning is…
Descriptors: Algorithms, Analysis of Covariance, Aptitude Treatment Interaction, Computer Assisted Instruction