ridge regression
Hi Frank,
From: Frank E Harrell Jr [mailto:fharrell at virginia.edu]
[snip]
The anova method for ols fits 'works' when you penalize the model but there is some controversy over whether we should be testing biased coefficients. Some believe that hypothesis tests should be done using the unpenalized model. That brings up other ways to handle collinearity: test groups of variables in combination so they don't compete with each other, or collapse them into summary scores (e.g., principal components) before putting them in the model.
I'm not clear about the last point. Suppose three of the variables are nearly collinear. Are you suggesting to replace the variables with the first one or two PCs, and drop the rest? If so, doesn't that also lead to biased estimators? Best, Andy
--- Frank E Harrell Jr Prof. of Biostatistics & Statistics Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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