![]() ![]() It yields R-squared values that are badly biased to be high. The following is a list of problems with automated stepwise model selection procedures (attributed to Frank Harrell, and copied from here): Unfortunately however, they are not, and the pairing of this situation and goal are quite difficult to successfully navigate. In addition, many textbooks (and courses) on regression cover stepwise selection methods, which implies that they must be legitimate. Moreover, it is a situation in which people seem to find themselves regularly. Wanting to know the best model given some information about a large number of variables is quite understandable. Stumbled on to an interesting comment on crossvalidated which I think is a nice way to warn against using techniques such as best subset regression, forward step regression, backward step regression etc.
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