Comments (2)
Hi @mizumot, thanks for your question! I think this question is beyond my expertise but I will try my best to answer. In an ideal situation where predictors are not correlated, there should be no difference between interpreting the correlations of the predictors and the outcomes for how important they are. When there is multi-collinearity, methods such as Shapley or Relative Weights are more appropriate. I do not know if there is a point where it becomes 'correct' to use a method rather than another; in practical terms, I would always opt to apply multiple methods (e.g. methods from random forest, correlations, dominance analysis, or from the package vip) to explore the implications.
This paper is also a pretty helpful guide for me:
https://www.researchgate.net/profile/Jeff_Johnson/publication/40455316_Determining_the_Statistical_Significance_of_Relative_Weights/links/09e4150cb66c7c099a000000/Determining-the-Statistical-Significance-of-Relative-Weights.pdf
from rwa.
Thanks a lot for your answer and suggestions! Now it is all clear to me. I'll look into the paper.
from rwa.
Related Issues (11)
- Confidence Intervals for Weights HOT 1
- Negative eigenvalues - do not get results HOT 5
- rwa for logistic regression HOT 2
- weights and missings HOT 4
- X not numeric HOT 3
- RWA Export Result HOT 1
- variable scaling? HOT 1
- 95%CI of rescaled weights HOT 1
- Data file problem HOT 2
- Categorical variables HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from rwa.