search for: surival

...to both treatments, and i gave them 60 minutes to perform a certain behaviour. 3 of my subjects performed the behaviour in one treatment but not the other. Therefore, i need to do a survival analysis using paired data. Im little confused about how to go about this in R. Im able to perfrom a normal surival analyses not taking the paired data into account, but im just wondering if there is some way to take the pairing into account. I know there are 3 different ways to deal with grouping in the survival package, strata, cluster and frailty but i struggle to understand the meaning of these arguments and...

On Wed 26-07-17 19:44:23, Wei Wang wrote: [...] > I thought about it more. Probably we can use the callback function with a > little change like this: > > void walk_free_mem(void *opaque1, void (*visit)(void *opaque2, unsigned long > pfn, > unsigned long nr_pages)) > { > ... > for_each_populated_zone(zone) { >

On Wed 26-07-17 19:44:23, Wei Wang wrote: [...] > I thought about it more. Probably we can use the callback function with a > little change like this: > > void walk_free_mem(void *opaque1, void (*visit)(void *opaque2, unsigned long > pfn, > unsigned long nr_pages)) > { > ... > for_each_populated_zone(zone) { >

Hi, I'm new to R and using it for Cox survival analysis. Thanks to this great forum I learned how to compute the HR with its confidence interval. My question would be: Is there any way to get the p-value for a hazard ratio in addition to the confidence interval? Thanks, Thierry -- Thierry Panje Visiting Student Researcher Department of Psychology Stanford

Dear friends Hello I'm a PhD student in Edinburgh University and interested in survival analysis. By chance, I found design library in Splus software. I have some questions about it and it's highly appreciated if you can help me. In its help (Design library help) I found the topics(not the commands), which are available in the main software. for instance, survival analysis is available

Hello, Why the correlation between the random effects is negative? library(coxme) rats1 <- coxme(Surv(time, status) ~ (1|litter), rats) random.effects(rats1)[[1]] #one value for each of the 50 litters print(rats1) rats2 <- lmekin(time ~ (1|litter), rats) fixed.effects(rats2) random.effects(rats2)[[1]] #one value for each of the 50 litters print(rats2)

Hi, I am wondering if there is a package for doing conditional logistic regression for nested case-control study as described in "Estimation of absolute risk from nested case-control data" by Langholz and Borgan (1997) where Horvitz-Thompson sampling weight (log of (number in the risk set divided by the number sampled)) is used with regression. In SAS Proc Phreg, this is implemented

On Wed 26-07-17 10:22:23, Wei Wang wrote: > On 07/25/2017 10:53 PM, Michal Hocko wrote: > >On Tue 25-07-17 14:47:16, Wang, Wei W wrote: > >>On Tuesday, July 25, 2017 8:42 PM, hal Hocko wrote: > >>>On Tue 25-07-17 19:56:24, Wei Wang wrote: > >>>>On 07/25/2017 07:25 PM, Michal Hocko wrote: > >>>>>On Tue 25-07-17 17:32:00, Wei Wang wrote:

On Wed 26-07-17 10:22:23, Wei Wang wrote: > On 07/25/2017 10:53 PM, Michal Hocko wrote: > >On Tue 25-07-17 14:47:16, Wang, Wei W wrote: > >>On Tuesday, July 25, 2017 8:42 PM, hal Hocko wrote: > >>>On Tue 25-07-17 19:56:24, Wei Wang wrote: > >>>>On 07/25/2017 07:25 PM, Michal Hocko wrote: > >>>>>On Tue 25-07-17 17:32:00, Wei Wang wrote:

to clean up some code I would like to make a list of arbitrary length to store?various objects for use in a loop sample code: ############ BEGIN SAMPLE ############## # You can see the need for a loop already linearModel1=lm(modelSource ~ .,mcReg) linearModel2=step(linearModel1) linearModel3=lm(modelSource ~ .-1,mcReg) linearModel4=step(linearModel3) #custom linearModel5=lm(modelSource ~ .