Two way analysis using covarites1
Author:
Jean baptiste Denis a
| Affiliation: | a Laboratoire de Biometrie, Versailles, France |
DOI:
10.1080/02331888808802080
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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(English)
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Abstract
Interpreting two factor interaction is often difficult, but may sometimes be eased by making use of eovariates associated to each factor. Some linear and non-linear models are considered to this end. In the orthogonal case, the model structure is given by tensor products of vector subspaces. Such a structure naturally applies to main effects. The estimators and their variances'and covariances are given (asymptotic variances in the non-linear case). The choice of a submodel is discussed in the linear case. Finally some remarks are made to generalize these models to models with more than two factors
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| Keywords: Covariate; factor regression; multiplicative model; bilinear model; estimation; two-way analysis; interaction; fixed models |
| view references (12) : view citations |

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