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Analysis of Covariance Structures
Psychometrika, 1966A general method is presented for estimating variance components when the experimental design has one random way of classification and a possibly unbalanced fixed classification. The procedure operates on a sample covariance matrix in which the fixed classes play the role of variables and the random classes correspond to observations.
R D, Bock, R E, Bargmann
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Biometrics, 1948
THE WHOLE OF this discussion is based on the data of a single experiment, the details of which have been published under the title "The Effect of Atropine and Quinidine Sulphate on Atrophy and Fibrillation in Deniervated Skeletal Muscle." [1] For the present, we may adopt the view that the experiment was conducted to compare the effects of four ...
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THE WHOLE OF this discussion is based on the data of a single experiment, the details of which have been published under the title "The Effect of Atropine and Quinidine Sulphate on Atrophy and Fibrillation in Deniervated Skeletal Muscle." [1] For the present, we may adopt the view that the experiment was conducted to compare the effects of four ...
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Analysis of Covariance Algorithms
Biometrics, 1982Computational algorithms specific to the analysis of covariance are discussed for the treatment of both balanced and unbalanced data. The use of covariance algorithms in the solution of missing data problems is also considered.
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Randomization in the Analysis of Covariance
Biometrika, 1986When examining any linear contrast of adjusted treatment means in the analysis of covariance it is shown that balancing on the covariates is desirable in that it minimizes the model variance of the treatment contrast averaged over the randomization distribution.
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Analysis of Variance and Covariance
1983This chapter concerns linear models of the form $$ y = X\beta + e $$ with e ~ N(0, σ 2 Iwhere y and e are random vectors of length N, X is an N × p matrix of constants, s is a vector of p parameters and I is the unit matrix. These models differ from the regression models of the previous chapter in that X, called the design matrix, consists ...
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Nonparametric Analysis of Covariance by Matching
Biometrics, 1982The basic problem under consideration is the comparison of treatments with respect to a response Y when a covariable X is taken into account. Various methods involving matching may be regarded as compromises between the standard analysis of covariance and the standard analysis of independent matched pairs.
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2021
ANCOVA of designed experiments combines one categorical and one continuous explanatory variable. Panel plots are usually the best way to graphically display ANCOVA designs, with a separate linear regression within each level of the factor. ANCOVA can test for effects of both variables and interactions between them.
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ANCOVA of designed experiments combines one categorical and one continuous explanatory variable. Panel plots are usually the best way to graphically display ANCOVA designs, with a separate linear regression within each level of the factor. ANCOVA can test for effects of both variables and interactions between them.
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Analysis of Covariance with Interaction
Infection Control, 1981Donald L. Kaiser, James E. Veney
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