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-Thank you James, well the problem of my type of data is that there can be many possible subsets and therefore plots, and I want to automatically generate them, and facet_wrap does not give me all the possible cases On Saturday, April 16, 2016 6:01 AM, James C. Whanger <james.whanger at gmail.com> wrote: Would facet_wrap or facet_grid give you what you want? On Sat, Apr 16, 2016 at 8:45 AM, ch.elahe via R-help <r-help at r-project.org> wrote: Hi, >I have a data set (mydata), which a part of this is like the following: > > >'data....

...gt; R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. -- *James C. Whanger* [[alternative HTML version deleted]]

Hi, I have a data set (mydata), which a part of this is like the following: 'data.frame': 36190 obs. of 16 variables: $ RE : int 38 41 11 67 30 18 38 41 41 30 ... $ LU : int 4200 3330 530 4500 3000 1790 4700 3400 3640 4000 ... $ COUNTRY : Factor w/ 4 levels "DE","FR","JP", "FR"? $Light

Since I read the list in digest form (and was out ill yesterday) I'm late to the discussion. There are 3 steps for predicting survival, using a Cox model: 1. Fit the data fit <- coxph(Surv(time, status) ~ age + ph.ecog, data=lung) The biggest question to answer here is what covariates you wish to base the prediction on. There is the usual tradeoff between too few (leave out something

>If you are looking at radioactive decay maybe but how often do >you actually see exponential KM curves in real life? Exponential curves are rare. But proportional hazards does not imply exponential. > A trial design could in fact try to get all the control sample to "event" at the same time if enough was known about prognostic factors and natural trajectory You are a

Hi: Apologies for asking the following question. As?this may sound very basic and stupid for this forum?, I honestly do not know how to solve it and I do not have a teacher who can help me understand. ? I have list of genes (200)?that are involved in a particular process and I call this as a?ProcSet.?? From an independent experiment I found that out of 10,000 genes, 1500 are significant and I

Dear all, I'm struggling with predicting "expected time until death" for a coxph and survreg model. I have two datasets. Dataset 1 includes a certain number of people for which I know a vector of covariates (age, gender, etc.) and their event times (i.e., I know whether they have died and when if death occurred prior to the end of the observation period). Dataset 2 includes another