Actually, I tried doing data2 = unique(data) mod = lm(y ~ x1 + ... + xn, data2) fitted(mod)
and I still get les fitted values than observations. Federico On 4 Aug 2009, at 12:18, Federico Calboli wrote:
Hi All, I have some data where the dependent variable is a score, low (1:3) or high (8:9), and the independent variables are 21 genotypic markers. I'm fitting a logistic regression on the whole dataset after transforming the score to 0/1 and normal linear regression on the high and low subsets. I all cases I have a numer of cases of data 'duplications', i.e. different individuals with the same score and the same genotype at the 21 markers. When I do: mod$fitted.values I get a number of fitted values corresponding to the umber of unique lines in the dataset. Is there a way to have the fitted values match the observation, even though some are duplicated and so have the same fitted value? I could do it by hand but it's laborious and I'd venture there is a better way. Best, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com
-- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com ______________________________________________ [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 and provide commented, minimal, self-contained, reproducible code.
