Thnx a lot, It was quite helpful. Dimitris 2011/6/30 James W. MacDonald <jmacdon@med.umich.edu> > Hi Dimitris, > > > On 6/30/2011 3:24 PM, Dimitris Kampas wrote: > >> Hello everyone, >> >> I would like to perfom a linear model like the following on my data using >> limma but i am not familiar with that. >> >> Y~ a + b*TYPE + c*TIME + d * TYPE * TIME >> I have 2 types of mice, CSB and WT, and 3 time points. >> I would like to model the time as a continous covariate. >> Unfortunately, the limma examples i found contain only categrical >> covariates. >> Can anybody provide me any help? Or does anybody know where to find an >> example of limma model with >> continous covariate. >> > > You don't say what kind of data you are analyzing, so I will keep this > pretty general. What you need to understand is that the design matrix set up > by R is dependent on the class of the input data. So if you pass numerical > data to model.matrix(), then R will assume you want to model those data as a > continuous variable. For example, > > > z <- 1:4 > > Fit z as a continuous variable: > > > model.matrix(~z) > (Intercept) z > 1 1 1 > 2 1 2 > 3 1 3 > 4 1 4 > attr(,"assign") > [1] 0 1 > > Fit z as factor levels: > > > model.matrix(~factor(z)) > (Intercept) factor(z)2 factor(z)3 factor(z)4 > 1 1 0 0 0 > 2 1 1 0 0 > 3 1 0 1 0 > 4 1 0 0 1 > attr(,"assign") > [1] 0 1 1 1 > attr(,"contrasts") > attr(,"contrasts")$`factor(z)` > [1] "contr.treatment" > > > Does that help? > > Best, > > Jim > > > >> Dimitris Kampas >> >> [[alternative HTML version deleted]] >> >> ______________________________**_________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/**listinfo/bioconductor<https: stat.e="" thz.ch="" mailman="" listinfo="" bioconductor=""> >> Search the archives: http://news.gmane.org/gmane.** >> science.biology.informatics.**conductor<http: news.gmane.org="" gmane="" .science.biology.informatics.conductor=""> >> > > -- > James W. MacDonald, M.S. > Biostatistician > Douglas Lab > University of Michigan > Department of Human Genetics > 5912 Buhl > 1241 E. Catherine St. > Ann Arbor MI 48109-5618 > 734-615-7826 > ************************************************************ > Electronic Mail is not secure, may not be read every day, and should not be > used for urgent or sensitive issues > [[alternative HTML version deleted]]