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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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Handbook of Regression Analysis With Applications in R, 2020
Filmore E. Bender +2 more
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Filmore E. Bender +2 more
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Analysis of covariance under neutrosophic statistics
Journal of Statistical Computation and Simulation, 2022Analysis of covariance (ANCOVA) is a widely used statistical analysis technique in numerous experimental studies. The existing ANCOVA test cannot be applied when the sample is taken from a population with imprecise and uncertain data.
Abdulrahman AlAita +1 more
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The New Statistics with R, 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.
A. Hector
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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.
A. Hector
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An Analysis of Variance of the Pantheon+ Dataset: Systematics in the Covariance Matrix?
Universe, 2022We investigate the statistics of the available Pantheon+ dataset. Noticing that the χ2 value for the best-fit ΛCDM model to the real data is small, we quantify how significant its smallness is by calculating the distribution of χ2 values for the best-fit
R. Keeley, A. Shafieloo, B. L’Huillier
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Biometrics, 1982
The simple analysis of covariance situation with two groups and one concomitant variable is considered. The parameters of this model with outliers present are estimated by the methods of at least squares and M-estimation. By use of simulation, several forms of M-estimators are compared with the least squares method.
Birch, Jeffrey B., Myers, Raymond H.
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The simple analysis of covariance situation with two groups and one concomitant variable is considered. The parameters of this model with outliers present are estimated by the methods of at least squares and M-estimation. By use of simulation, several forms of M-estimators are compared with the least squares method.
Birch, Jeffrey B., Myers, Raymond H.
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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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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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Using analysis of covariance (ANCOVA) with fallible covariates.
Psychological methods, 2011Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses ...
S. Culpepper, Herman Aguinis
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