> > bounds for each group. My question is, is there a function > > in R that can do > > the same thing for more complex and subtle groupings in > > univariate data, and
>> ** provide a statistical basis for the result? ** No. Others have suggested useful ways to **generate** reasonable hypotheses about "subtle groupings" in the data; however, by the nature and logic of hypothesis testing, one cannot then evaluate the statistical "significance" of any groupings that one purports to have found. One **possible** way of overcoming this dilemma is to randomly bifurcate the data into training and test sets, do ALL model development on the training set, and then evaluate statistical "significance" (once and only once) on the test set. However, one may argue that even this blows up type I error, as the random split likely preserves the same structures in both and thus doesn't eliminate the large bias of testing models fit to the random anomalies of the data set at hand. As A.S.C Ehrenberg argued many years ago -- and recent events on the U.S. Cox II regulatory stage have dramatized -- single sets of data cannot be used as the basis for scientific knowledge; multiple sets of data generated under different conditions and with different sources of exogenous variation are required. -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA "The business of the statistician is to catalyze the scientific learning process." - George E. P. Box ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
