What is it about?

In regression, a basic goal is understanding the association between some outcome measure of interest and a set p predictor variables. The paper deals with the issue of determining the relative importance of the predictors. For example, is the first predictor more important than the second? Are the first two predictors more important than the third predictor?

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Why is it important?

There are various ways of estimating which independent variables in a regression model are most important. But generally it is unclear how compelling the evidence is that the most important predictors have been identified. The paper describes a robust method for dealing with this issue.

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This page is a summary of: Robust regression: an inferential method for determining which independent variables are most important, Journal of Applied Statistics, December 2016, Taylor & Francis,
DOI: 10.1080/02664763.2016.1268105.
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