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Analyse des leviers : effets de colinéarité et hiérarchisation des impacts dans les études de marché et sociales

Abstract : AbstractLinear regression is used in Market Research but faces difficulties due to multicollinearity. Other methods have been considered.A demonstration of the equality between lmg-Shapley and and Johnson methods for Variance Decomposition has been proposed. Also this research has shown that the decomposition proposed by Fabbris is not identical to those proposed by Genizi and Johnson, and that the CAR scores of two predictors do not equalize when their correlation tends towards 1. A new method, weifila (weighted first last) has been proposed and published in 2015.Also we have shown that permutation importance using Random Forest enables to take into account non linear relationships and deserves broader usage in Marketing Research.Regarding Bayesian Networks, there are multiple solutions available and expert driven restrictions and decisions support the recommendation to be careful in their usage and presentation, even if they allow to explore possible structures and make simulations.In the end, weifila or random forests are recommended instead of lmg-Shapley knowing that the benefit of structural and conceptual models should not be underestimated.Keywords :Linear regression, Variable Importance, Shapley Value, Random Forests, Bayesian Networks
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Submitted on : Wednesday, June 8, 2016 - 6:02:09 PM
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Henri Wallard. Analyse des leviers : effets de colinéarité et hiérarchisation des impacts dans les études de marché et sociales. Génie logiciel [cs.SE]. Conservatoire national des arts et metiers - CNAM, 2015. Français. ⟨NNT : 2015CNAM1019⟩. ⟨tel-01329190⟩

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