For the horseshoe crab data with width, colors, and spine as predictors, suppose you start a backward elimination process with the most complex model possible Denoted by C ∗ S ∗ W, it uses main effects for each term as well as the three two-factor interactions and the three-factor interaction Conduct a likelihood-ratio test comparing this model to the simpler model that removes the three-factor interaction term but has all the two-factor interactions. Does this suggest that the three-factor term can be removed from the model?At the next stage, if we were to drop one term, explain why we would select model C ∗ S + C ∗ W

you start a backward elimination process with the most complex model possible Denoted by C ∗ S ∗ W, it uses main effects for each term as well as the three two-factor interactions and the three-factor interaction Conduct a likelihood-ratio

you start a backward elimination process with the most complex model possible Denoted by C ∗ S ∗ W, it uses main effects for each term as well as the three two-factor interactions and the three-factor interaction Conduct a likelihood-ratio

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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Question

For the horseshoe crab data with width, colors, and spine as predictors, suppose you start a backward elimination process with the most complex model possible Denoted by C ∗ S ∗ W, it uses main effects for each term as well as the three two-factor interactions and the three-factor interaction

Conduct a likelihood-ratio test comparing this model to the simpler model that removes the three-factor interaction term but has all the two-factor interactions. Does this suggest that the three-factor term can be removed from the model?
At the next stage, if we were to drop one term, explain why we would select model C ∗ S + C ∗ W

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