search for: danardonos

To Danardonos concern of splitting time for records with delayed entry: This can fairly easily be accomodated, by simply splitting time in small intervals of time since entry into the study, and then compute the value of the other timescales for each of these e.g.: current.age <- time.from.entry + age.at.en...

Danardono <daodao99 at student.umu.se> wrote: > > While waiting for 2.1, for those who need function[s] for this > survival-splitting business, as I do, this 'survcut' function below > might be helpful. > It is not an elegant nor efficient function but it works, at least for > some examples below. > Ditto the following, for the case where there are multiple

Alternatively, use the concat() function from the gregmisc library: > library(gregmisc) Attaching package `gregmisc': [warnings omitted]] > concat(x[[1]],x[[2]],names=names(x)) age.day state source 1 81 0 772307 2 141 0 772307 3 234 0 772307 4 321 0 772307 5 437 0 772307 6 499 0 772307 7 601 1 772307 8 689

Hi all, This is a potentially very stupid question about MySQL <-> R interaction, but I have not been able to solve it. I'm just trying to connect R to my MySQL databse, and gets this: > library(RMySQL) Loading required package: methods > m <- dbDriver("MySQL") > con <- dbConnect(m,group="testdb") Process R segmentation fault at Wed Oct 16 07:04:30

Hello everyone, I am searching for a covariate selection procedure in a cox model formulated as a counting process. I use intervals, my formula looks like coxph(Surv(start,stop,status)~ x1+x2+...+cluster(id),robust=T) where id is a country code (I study occurence of civil wars from 1962 to 1997). I'd like something not based on p-values, since they have several flaws for this purpose. I turned