Timeline for Time-dependent coxph output and making predictions in R
Current License: CC BY-SA 3.0
11 events
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| Jun 29, 2021 at 1:53 | comment | added | Vardaan Khanted | @Fist Pump Cat: Were you able to figure out how to predict the future for the right-censored observations without knowing the values of the time-varying co-variates. Sorry I am unable to make this a comment | |
| Jul 30, 2019 at 16:02 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Mar 30, 2019 at 23:03 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Feb 26, 2019 at 19:29 | answer | added | zhanxw | timeline score: 1 | |
| Aug 6, 2015 at 16:33 | comment | added | Fist Pump Cat | Fair enough...the code link, the model training data link, and the data for the employee of interest link. The first 6 rows of data for the employee of interest are intended to be the employee's history up to the current day. After this the data is forward looking and is simply forecast with everything staying constant except for age, which is predictable | |
| Aug 5, 2015 at 17:50 | comment | added | DWin | I don't understand why I should be expected to create an example when you have not yet provided one. | |
| Aug 5, 2015 at 16:33 | comment | added | Fist Pump Cat |
I actually did nest Surv() inside coxph() in my original code. I changed it in my post for aesthetics, but you're right, I should've been more careful. My mistake. Also, after reading ?predict.coxph several times, I still don't understand exactly what the newdata argument should look like when making a new prediction. I'm also not sure what you mean by "a set of covariates that match the original set as well as covering the time intervals of interest for the prediction". Can you provide an example table? Thanks for your responses...I've been struggling with this for days!
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| Aug 4, 2015 at 4:22 | comment | added | DWin |
You may also need ?survfit.coxph. Unless you have attach-ed the dataset, your creation of the Surv() object will not have succeeded. Therneau specifically warns against creating Surv-objects outside of the 'coxph' function because of later difficulties with the environments not being correctly accessible.
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| Aug 4, 2015 at 4:15 | comment | added | DWin |
Yes, you should be using that sort of call. You need to provide a set of covariates that match both the original set as well as covering the time intervals of interest for the prediction. See ?predict.coxph and you may also need ?survfit.coxph
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| Jul 30, 2015 at 18:18 | review | First posts | |||
| Jul 30, 2015 at 18:19 | |||||
| Jul 30, 2015 at 18:17 | history | asked | Fist Pump Cat | CC BY-SA 3.0 |