Hi all, In Tibshirani's PNAS paper about nearest shrunken centroid analysis of microarrays (PNAS vol 99:6567), they used cross validation to choose the amount of shrinkage used in the model, and then test the performance of the model with the cross-validated shrinkage in separate independent testing set. If I don't have the luxury of having independent testing set, can I just use the cross validation performance as the performance estimate? In other words, can I use the same single cross-validation to both choose the value of the parameter (amount of shrinkage in this case) and estimate the performance which was based on the value of the parameter chosen by the same cross-validation? I kind of feel awkward by getting both on a single cross validation, because it seems like I used the dataset in training set manner. Am I wrong/right?
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