Multivariate Analysis of Covariance

  • Charles E. Brown


The objective of multivariate analysis of covariance is to determine if there are statistically reliable mean differences that can be demonstrated among groups after adjusting the newly created variable (dependent variable) for differences on one or more covariates. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates.


Covariance Matrix Likelihood Ratio Test Covariance Matrice Group Regression Multiple Covariates 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Supplemental Reading

  1. Davis JC (1973) Statistics and data analysis in geology. John Wiley, New YorkGoogle Scholar
  2. Tabachnick BG, Fidell LS (1989) Using multivariate statistics. Harper and Row, New YorkGoogle Scholar
  3. Afifi AA, Azen SP (1972) Statistical analysis — a computer oriented approach. Academic Press, New YorkGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Charles E. Brown
    • 1
    • 2
  1. 1.International Geohydroscience and Energy Research (IGER) InstituteCentrevilleUSA
  2. 2.Department of ChemistryGeorge Mason UniversityFairfaxUSA

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