A note on the analysis of covariance: efficiency of concomitant variables

The paper gives an explicit formula for expressing the efficiency of the analysis of covariance, that is for measuring the improvement of a least squares estimator when concomitant variables are taken into account. In the derivation of it, a general Gauss-Markov multivariate linear model with the no...

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Bibliographic Details
Published inJournal of statistical planning and inference Vol. 21; no. 3; pp. 315 - 326
Main Authors Caliński, Tadeusz, Caussinus, Henri
Format Journal Article
LanguageEnglish
Published Lausanne Elsevier B.V 01.03.1989
New York,NY Elsevier Science
Amsterdam
Subjects
Analysis of covariance
efficiency
Exact sciences and technology
experimental designs
growth curves
least squares estimation
Linear inference, regression
Mathematics
Probability and statistics
Sciences and techniques of general use
Statistics
efficiency
experimental designs
Analysis of covariance
growth curves
62J10
62H12
62K10
least squares estimation
Covariance analysis
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Summary:The paper gives an explicit formula for expressing the efficiency of the analysis of covariance, that is for measuring the improvement of a least squares estimator when concomitant variables are taken into account. In the derivation of it, a general Gauss-Markov multivariate linear model with the normality assumption for all variables is considered.Suggestions on application in the analysis of a designed experiment and of a growth curves model are given.
ISSN:0378-3758
1873-1171
DOI:10.1016/0378-3758(89)90050-5