R******o
发帖数: 83 | 1 用 R function: Survfit(Surv 来 estimate survival function , 给出结果Median =
NA
是什么意思呢？
谢谢 |
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y*****w
发帖数: 1350 | 2 I was running the JM package in R for a joint model for longitudinal and
survival data. I could successfully run the lme() function (for the mixed
model) and the coxph() function (for the Cox model) separately, but when I
ran the JointModel() function, the program returned the following error
message:
Error in fitter(X, Y, strats, offset, init, control, weights = weights, :
Can't fit a Cox model with 0 failures
I double checked my data and there was no any irregular point. What's the
meaning ... 阅读全帖 |
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G***G
发帖数: 16778 | 3 thank you very much.
1)do you know when we choose to use cox ph model and when to use survreg?
2)what does the survfit do?
what is difference between survfit and ph model?
3) what we use ph model for? can we use it for prediction? |
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y*****w
发帖数: 1350 | 4 It seems survreg() in R and PROC LIFEREG in SAS run the same type of
survival analysis. However, when I ran both of them on a survival data, I
got different results. Both were set as exponential distribution, and have
right censored data. See below. Could anybody tell me why the results are
different? Did I miss specifying any important parameters in R? Thanks!
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The R code:
survFit <- survreg(Surv(time, event, type="right") ~... 阅读全帖 |
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s***1
发帖数: 343 | 5 100多个subject，每个subject都有已经给定的survival time和censoring value，同
时每个subject都有相应的gene expression data（大概30000的gene features），我
先用这些fit了一个cox model（就是最常规的model<-coxph(Surv(survival$t.os,
survival$e.os)～expression。。。）
现在需要做的是要用这个model去predict其他给定gene expression和time point的new
subject的survival rate（比如10年的存活率）。
我用的是survfit(model,newdata=data.frame(new_expression),individual=TRUE),
期望出来的是几条对应于这几个individual的曲线，可是却报错说start和stop缺失。
想请问问有经验的前辈们，是不是需要把时间加在predict里面，如何能加（survfit的
help里没找到）。
不好意思问题很菜，但是实在是折腾了一阵子... 阅读全帖 |
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hs
发帖数: 1549 | 6 这个R code当例子成不？
library(survival)
fit <- survfit(Surv(time, status) ~ x, data=aml)
plot(fit[1],conf.int=T) |
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G***G
发帖数: 16778 | 7 no, they are not. I mean the result is not.
most of us say cox is non-parameter.
survfit (proportional progression) is parameter model. |
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R******o
发帖数: 83 | 9 Oh, 谢谢！
通常多到什么程度回出现这种情况？？该怎么办？
就这么把结果报上去行吗？ |
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h******3
发帖数: 190 | 10
就是说最后ｃｕｒｖｅ plateau 在５０％ 以上。所以说至少有50%是最后被censor的？
在这种情况最好要report 75% survival time之类的。SAS的output有。 |
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c********d
发帖数: 253 | 11 I want to get the mean survival time from K-M estimator. The code:
print(survfit(Surv(x,time)~ 1), print.rmean=T) can give the restricted mean.
However, this mean cannot output for future use. Does anyone know how to
output the mean survival time? Thanks a lot. |
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a*******g
发帖数: 80 | 12 Hi, I used Dr. Harrell's rms package to make a nomogram.
Below is my code for nomogram and calculate total points and probability in
original data set used for building the nomogram. My question is how I get
the formula for calculating the survival probability for this nomogram. Then
I can use this formula to do validation by using other data set.
f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+cytcyt+Cyt_PCDK2 ,
data=data11,
surv=T, x=T, y=T, time.inc=5)
surv<- Survival(f1)
surv10 <- ... 阅读全帖 |
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w*******9
发帖数: 1433 | 13 你要每个individual整个的predicted survival curve的话，在newdata里只要加上
covariates就行，去掉individual=TRUE. For example, pred<-survfit(model,
newdata) plot(pred). 要得到10年survival prob., 你得自己从pred$surv里去取。
另外你有3000个features, 你怎么降维的？ |
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Y******Y
发帖数: 8753 | 14 你的covariate不是time-dependent的吧？ 而且survival data的结构是one row per
subject的？如果是，那么survfit里面应该是individual=FALSE而不是TRUE
new
。 |
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Z*******n
发帖数: 694 | 15 Three people suggested survival model.
I am willing to learn and try.
I used the cox proportional hazard model long long time ago, and now I
forgot how to use it.
Some old R code is below (NOT for this problem at hand, but for some
exercise problem). Am I in the right track? Any tips/hint/R code snippets?
library(survival)
?coxph
coxph.m <- coxph(Surv(lifetime,notcensored1) ~ x1+x2, data=mydata)
summary(coxph.m)
plot(survfit(coxph.m),xlab='time',ylab='1-CDF')
predict(coxph.m, newdata=ldkfakdfj... 阅读全帖 |
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w*******9
发帖数: 1433 | 16 自己手动吧，survfit算出每个curve的值和variance,你再手动取差值，variance就是
俩variance的和，不过要注意前面的variance得是estimated survival function的
variance,因为默认不是这样的 |
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