Statistical literature is being more and more concerned with debates about hypothesis testing and p-values supporting the significance of a given variable specification. Specifically, if on one hand statistical foundations about significance are not arguable, scholars should be able to distinguish between significance and variable importance. This is a matter of serious concern in questionnaire analysis to derive respondents’ profiles and develop targeted marketing strategies, for instance. To this aim, this contribution proposes a hypothesis system that considers the normalized dissimilarity measure to assess the importance of explanatory variables in the setting of mixture models for ordinal data to account for uncertainty of choice.

A Test for Variable Importance / Simone, Rosaria. - (2018), pp. 1367-1372.

A Test for Variable Importance

Rosaria Simone
2018

Abstract

Statistical literature is being more and more concerned with debates about hypothesis testing and p-values supporting the significance of a given variable specification. Specifically, if on one hand statistical foundations about significance are not arguable, scholars should be able to distinguish between significance and variable importance. This is a matter of serious concern in questionnaire analysis to derive respondents’ profiles and develop targeted marketing strategies, for instance. To this aim, this contribution proposes a hypothesis system that considers the normalized dissimilarity measure to assess the importance of explanatory variables in the setting of mixture models for ordinal data to account for uncertainty of choice.
2018
9788891910233
A Test for Variable Importance / Simone, Rosaria. - (2018), pp. 1367-1372.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/751514
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