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.
