The Polynomial Model in the Multivariate Analysis of Variance
Copyright policy )The Polynomial Model in the Multivariate Analysis of Variance
AbstractAssuming that the independent variables (factors) are quantitative, there exist besides the coding schemes generally used for the multivariate analysis of variance (dummy‐coded or effect‐coded design matrices) the so‐called polynomial models. The advantage of these polynomial models are the full rank design matrices, which allow a more comprehensible analysis, i.e. the unambiguous interpretation of tested hypotheses and simultaneous confidence intervals.
- University of Passau Germany
simultaneous confidence intervals, quantitative factors, Analysis of variance and covariance (ANOVA), polynomial models, Hypothesis testing in multivariate analysis, MANOVA, full rank design matrices, orthonormal polynomials
simultaneous confidence intervals, quantitative factors, Analysis of variance and covariance (ANOVA), polynomial models, Hypothesis testing in multivariate analysis, MANOVA, full rank design matrices, orthonormal polynomials
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