Which type of regression is typically preferred when dealing with multicollinearity among independent variables?
Understand the Problem
The question is asking which regression technique is favored when there is multicollinearity among independent variables. It implies an understanding of different types of regression and their suitability in the presence of multicollinearity.
Answer
Ridge and LASSO regression
The final answer is Ridge and LASSO regression.
Answer for screen readers
The final answer is Ridge and LASSO regression.
More Information
Ridge and LASSO regression are both effective in situations with multicollinearity because they apply a penalty to the coefficients of the linear regression model, which can help to minimize overfitting caused by multicollinearity.
Tips
A common mistake is to continue using ordinary least squares regression without checking for multicollinearity among independent variables. It's important to detect and address multicollinearity to ensure reliable model estimation.
Sources
- Addressing Multicollinearity: Definition, Types, Examples, and More - sawtoothsoftware.com
- 5 Types of Regression Analysis And When To Use Them - Appier - appier.com
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