In multilevel models,why can centring be useful?
A)To combat multicollinearity between predictor variables
B)To reject the null hypothesis early on
C)To improve the strength of the analysis
D)To hide errors

Question

Quizplus · Accepted Answer

Centring can be useful in multilevel models to combat multicollinearity between predictor variables. It involves adjusting the scale of the variables to have a mean of zero, which can help in reducing multicollinearity, a common issue where predictor variables are highly correlated with each other, potentially distorting the results and making coefficients difficult to interpret.

In Multilevel Models,why Can Centring Be Useful