Hi Gabor, Thanks for your reply. I have it working now. A couple of follow-ups if I may.
I have a shell script parsing the output to find the brain areas where there is a significant effect of diagnosis but its a bit of a hack. I was wondering whether there are R specific tools for parsing/summarizing this kind of output. Can I apply multiple comparison corrections via lm() or do I need to apply something on the model output from lm() after? Thanks again for your time. Cheers, -Morgan Gabor Grothendieck wrote: > Perhaps something like this: > > >> idx <- 1:2 >> lm(as.matrix(iris[idx]) ~., iris[-idx]) >> > > Call: > lm(formula = as.matrix(iris[idx]) ~ ., data = iris[-idx]) > > Coefficients: > Sepal.Length Sepal.Width > (Intercept) 3.682982 3.048497 > Petal.Length 0.905946 0.154676 > Petal.Width -0.005995 0.623446 > Speciesversicolor -1.598362 -1.764104 > Speciesvirginica -2.112647 -2.196357 > > > > On Nov 23, 2007 10:09 AM, Morgan Hough <[EMAIL PROTECTED]> wrote: > >> Hi there, >> >> I am analyzing a table of brain volume measures where each brain area >> (183 of them) is a column with a label and volume values. I have another >> table of explanatory variables (age, gender, diagnosis and >> IntraCranialVol) that I have been using to model the brain volume >> differences. I have been doing this for single volume measures with no >> difficulties but I have been unable to apply this across the whole set >> of brain areas. If I try: >> >> lm(y.df, x.df) >> Error in eval(expr, envir, enclos) : object "Left_Lateral_Ventricle" not >> found >> >> Left_Lateral_Ventricle happens to be the first column label. Does this >> not work with tables? I have been unable to find any examples. >> >> Would you recommend another approach if I was doing this again. The >> number of columns (brain areas) depends on the parcellation strategy we >> use so I will probably be reforming these tables again and again. I >> would like the simplest way to analyze all the brain areas and find >> where there are significant differences driven mainly by the diagnosis >> factor. >> >> Thanks in advance for your time. >> >> Cheers, >> >> -Morgan >> >> --------------------------------------------------------------------------- >> Morgan Hough, >> D.Phil. Student, >> Oxford University FMRIB Centre >> >> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK >> +44 (0) 1865 222466 (fax 222717) >> [EMAIL PROTECTED] http://www.fmrib.ox.ac.uk/~mhough >> >> ______________________________________________ >> 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. >> >> ______________________________________________ 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.
