search for: isvik

Dear R fans, I have got a difficult sounding problem. For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used. library(MASS) model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus) dropterm(model, test = "F") But I am not sure whether any similar functions is

Hi friends, I have a matrix with following format. group var1 var2 .......varN c1 group1 1.2399 1.4990....-1.4829 c2 group4 0.8989 0.7849.....1.8933 ... ... c100 group10 ..... I want to draw a profile plot of each condition c1 to c100, which rows in above matrix and each line representing a row should be uniquely colored according to the group(1 to 10). I think this is simple task

Hi naive question. It is possible to get R command for omitting rows or cols with missing values present. But if i want to omit rows or cols with i.e . >20% missing values, I could´t find any package-based command, probably because it is too simple for anyone to do that manually, though not for me. Can anyone please help me ? - vickie [[alternative HTML version

Hi Friends, I am new to R. On R utility class pages, creating "named.list" is described with this command : new("named.list",a=1,b=2) For large matrix having two columns, such as : "row1" 2334 "row2" 347 "row3" 379 ... I want to create a named.list like : $row1 [1] 2334 $row2 [1] 347 ... Can anyone explain how "named.list"

Hi guys, Can anyone tell me what is the meaning of following command ? paste(execDir,paste(short,"myfile",sep="_"),sep="\") R gives me an error : Error: object 'short' not found I tried to find help about 'short' in R, but could not find any such function/ object. Viki [[alternative HTML version deleted]]

Hi, I have two unequal patient groups belonging to different geographic locations, treated by different drug regimens and their survival data. N1=150 and N2=60 In each group of data there are three strata for one independent variable- treatment status (2=two drugs administered, 1=only one conventionally used drug administered, 0=no drug administered), dead or not and months to death. In order to

Hi, I have a question about filterMicroRna in AgiMicroRna package function for filtering probes in Agilent microRNA dataset. >ddPROC = filterMicroRna(ddNORM.micro, dd, control = TRUE, IsGeneDetected = TRUE, wellaboveNEG = FALSE, limIsGeneDetected = 75, limNEG = 25, makePLOT = TRUE, target.micro, verbose = TRUE) If in a dataset there are two or more sample replicates and in the step of

Hi all, I've got the following matrix : ? mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f", c(1:140), sep="_"), c("A", "B", "C", "D", "E"))) I can see that currently most of the multivariate Hotelling T2 tests are limited for application on two groups/samples. I wud appreciate if someone can provide me a

Hi guys, I have been testing the hypothesis for difference of survival between four different classes. The p-values provided in coxph output are confusing for me to interpret. Here is the output : sur<-coxph(Surv(SURVIV, status == 1)~factor(A)+cluster(rownames(d)), data = d, model=TRUE) Call: coxph(formula = Surv(SURVIV, status == 1) ~ factor(A) + cluster(rownames(d)), data = d, model = TRUE)

Hi friends, I have got a list where each element might have variable number of members. $`4213` [1] "214077_x_at" $`164832` [1] "225996_at" "235977_at" $`339010` [1] NA $`23410` [1] "221562_s_at" "221913_at" "49327_at" $`285386` [1] "229764_at" $`2099` [1] "205225_at" "211233_x_at"