On Jul 15, 2011, at 23:05 , Data Analytics Corp. wrote: > Hi, > > I have a consultants nightmare -- I was given a project that another > consultant did and I was told to do the same calculations, but there's no > documentation on what he did. Basically, I have yes/no answers to survey > questions about the effectiveness of product attributes by brands. There are > 44 attributes and 13 brands. The other guy scaled the proportion of > respondents who said Yes to be mean 0 and variance 1.0, apparently doing this > by brand within each attribute. He then created a matrix of 44 rows for the > attributes and 13 columns for the brands. No problem with this; I can always > replicate this much. But then he apparently rescaled this 44x13 matrix so > that the rows all sum to zero and the columns all sum to zero. None of the > row and column standard deviations are 1.0. This I can't see how to do. How > can I rescale the rows and columns so that they all sum to zero? Any > suggestions? >
If the _sum_ is zero, there must be both negative and positive elements, so it can't be a pure scaling. sweep()'ing out the row and column means would be the first thing to come to my mind. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
