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Rasmussen, Jeffrey Lee – Educational and Psychological Measurement, 1993
J. P. Shaffer has presented two tests to improve the power of multiple comparison procedures. This article described an algorithm to carry out the tests. The logic of the algorithm and an application to a data set are given. (SLD)
Descriptors: Algorithms, Analysis of Variance, Comparative Analysis, Logic
Peer reviewed Peer reviewed
Kiers, Henk A. L.; And Others – Psychometrika, 1993
A new procedure is proposed for handling nominal variables in the analysis of variables of mixed measurement levels, and a procedure is developed for handling ordinal variables. Using these procedures, a monotonically convergent algorithm is constructed for the FACTALS method for any mixture of variables. (SLD)
Descriptors: Algorithms, Analysis of Variance, Equations (Mathematics), Least Squares Statistics
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
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