search for: egfr

Hi, I am trying to do simple linear regression using dates in R but receiving error messages. With the data shown below, I would like to regress x on y. x y 11/12/1999 56.8 11/29/1999 17.9 01/04/2000 27.4 1/14/2000 96.8 1/31/2000 49.5 R gives the following error messages after reading the linear regression command: Error in storage.mode(y) <-

.... I have to scatterplot two vectors, grouped by a third variable, with two different dimensions according to whether each cell line in the plot is sensitive or resistant to a given drug, and with a different color for each of 9 tissues of origin. Here's what I've done: >obj<-xyplot(EGFR~EPHA2,data=Dataset,groups=interaction(Sens,Tissue),cex=c(1,3),pch=19) > update(obj, par.settings = + custom.theme(symbol = brewer.pal(9, "Paired"), + fill = brewer.pal(9, "Paired"))) > Here are the data: Tissue Sens EGFR ITGB1 1 Breast 1...

Dear Rui, >From my understanding of time-dependent covariates (not an expert but have been working on a similar problem), it would appear that the coding of the status column is not correct. Unless you have observed an event at each interval you should only have status=1 for the last interval. In your example I see 3 in total. Also, I think that if "end" is proportional to your

...that are TRUE. I suspect mygenes, as you have it, is a data frame of only one column, so the subsetting won't work.] HTH, Andy > From: S Peri > > Dear group, > Apologies for asking the most chomped FAQ. > > I have a file with list of gene names(genes.txt): > EGF > EGFR > PTPN6 > TIEG2 > MAPK1 > > > I have another object in R, I do not know the data > type for that object that looks like this > ("lidnames"): > "RABGGTA" "MAPK3" "TIE" "CYP2C19" > > > > lidnames[1:10]...

I have an attached data.frame with a binary composite variable (comp) and a predictor (egfr). I am trying to plot a restricted cubic spline using: require (Hmisc) require (Design) rcspline.plot(x=egfr,y=comp,model="logistic",nk=5,knots=NULL, xlab="label1", ylab="Label2", plim=c(0,1), plotcl=TRUE, showknots=TRUE...

Hi all, I have a question and I do not know If I am at the right place to ask this question. But is there someone that has the formula of CKD-Epi in code in R? I have tried a lot of loops, but none of the approaches give me the right answer. Is there someone who has this formula coded? Thank you! [[alternative HTML version deleted]]

Hi, I have been examining large data and need to do simple linear regression with the data which is grouped based on the values of a particular attribute. For instance, consider three columns : ID, x, y, and I need to regress x on y for each distinct value of ID. Specifically, for the set of data corresponding to each of the 4 values of ID (76,111,121,168) in the below data, I should invoke

Hi all, I am trying to detect association between a covariate and a disease outcome using R. This covariate shows time-varying effect, I add a time-covariate interaction item to build Cox model as follows: COX <- coxph(as.formula("Surv(TIME,outcome)~eGFR_BASE+eGFR_BASE:TIME"),ori.data); coef exp(coef) e(coef) z p eGFR_BASE 6.40 603.5133 0.3702 17.3 0 eGFR_BASE:TIME -3.41 0.0329 0.0772 -44.2 0 But the result seems very different from that go...

Dear all, Here is my code which am using to combine 5th column from different data sets. Here is the function to do my job genesymbol.append.file <-NULL gene.column <- NULL readGeneSymbol <- function(files,genesymbol.column=5){ for(i in fnames){ temp <- read.table(fnames,header=T,sep="\t",stringsAsFactors=F,quote="\"")