Always reply to the list. I do not do private consulting.

(I have cc'ed this to the list).

I still think this belongs on stackexchange, not r-help. I think you need

to read up on the mathematics of spline bases.

On Thu, Nov 2, 2017 at 3:43 AM, Kosta S. <

> Hi Bert,

>

> Maybe I should make this more clear.

> I get following output when I use the pspline function inside the coxph

> statement:

>

> * library(survival)*

>

>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>>

>> *> Option.test2<-coxph(Surv(START,STOP,ZEROBAL==1)~pspline(OPTION),

>> data=FNMA)coxph(formula = Surv(START, STOP, ZEROBAL == 1) ~

>> pspline(OPTION), data = FNMA)> > Option.test2> Call:> coxph(formula =

>> Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION),> data = FNMA)>

>> coef se(coef) se2 Chisq DF

>> p> pspline(OPTION), linear -0.1334 0.0131 0.0131 104.4325

>> 1.00 <0.0000000000000002> pspline(OPTION), nonlin

>> 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19

>> Newton-Raphson> Theta= 0.991> Degrees of freedom for terms= 4>

>> Likelihood ratio test=2136 on 4.05 df, p=0 n= 3390429*

>

>

>

> What I do not understand, and what I have not found either in the package

> documentation nor somewhere else is how to interpret the output result:

>

>

>

>

>

>

>

> *> coef se(coef) se2 Chisq DF

> p> pspline(OPTION), linear -0.1334 0.0131 0.0131

> 104.4325 1.00 <0.0000000000000002> pspline(OPTION), nonlin

> 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19

> Newton-Raphson> Theta= 0.991> Degrees of freedom for terms= 4>

> Likelihood ratio test=2136 on 4.05 df, p=0 n= 3390429*

>

>

> What does it actually tell me? What does the "linear" and "nonlinear"

> mean? It differs from the usual coxph output. Is this a proof of

> non-linearity?

>

> This topic was also alreday asked on the cross validated board, but

> unfortunately without any answer, see

https://stats.

> stackexchange.com/questions/280168/interpretation-of-coxph-pspline-terms

>

>

> Thanks,

>

> KS

>

>

>

>

>

>

>

>

> 2017-11-01 23:11 GMT+01:00 Bert Gunter <

[hidden email]>:

>

>> ??

>>

>> It is unclear to me what "How to interpret the result" means. Note that

>> the survival package is very well documented and there is a vignette

>> specifically on the topic of the use of "Spline terms in a Cox model." Have

>> you studied it?

>>

>> If you want to discuss the statistical issues, e.g. of survival modeling

>> or the technical details of penalized smoothing splines, that is mostly OT

>> here: stats.stackexchange.com would probably be a better place to post

>> for that. This list is mostly about R programming rather than statistics,

>> although they do sometimes intersect.

>>

>> If I have misunderstood your question, you might wish to clarify exactly

>> what it is that you are seeking in another post.

>>

>> Finally, as you can see from the below, post in PLAIN TEXT ONLY, as html

>> can get mangled by the server on this plain text mailing list.

>>

>> Cheers,

>> Bert

>>

>>

>>

>> Bert Gunter

>>

>> "The trouble with having an open mind is that people keep coming along

>> and sticking things into it."

>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

>>

>> On Wed, Nov 1, 2017 at 1:12 PM, Kosta S. <

[hidden email]> wrote:

>>

>>> Hi,

>>>

>>> I'm using a Cox-Regression to estimate hazard rates on prepayments.

>>>

>>> I'm using the "pspline" function to face non-linearity, but I have no

>>> clue

>>> how to interpret the result.

>>> Unfortunately I did not find enough information on the "pspline" function

>>> wether in the survival package nor using google..

>>>

>>> I got following output:

>>>

>>> * library(survival)*

>>>

>>>

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> >

>>> > *> Option.test2<-coxph(Surv(START,STOP,ZEROBAL==1)~pspline(OPTION),

>>> > data=FNMA)coxph(formula = Surv(START, STOP, ZEROBAL == 1) ~

>>> > pspline(OPTION), data = FNMA)> > Option.test2> Call:>

>>> coxph(formula =

>>> > Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION), > data = FNMA)>

>>> > coef se(coef) se2 Chisq DF

>>> > p> pspline(OPTION), linear -0.1334 0.0131 0.0131

>>> 104.4325

>>> > 1.00 <0.0000000000000002> pspline(OPTION), nonlin

>>> > 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19

>>> > Newton-Raphson> Theta= 0.991 > Degrees of freedom for terms= 4 >

>>> > Likelihood ratio test=2136 on 4.05 df, p=0 n= 3390429 > *

>>>

>>>

>>> Thanks,

>>>

>>> KS

>>>

>>> [[alternative HTML version deleted]]

>>>

>>> ______________________________________________

>>>

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>>>

https://stat.ethz.ch/mailman/listinfo/r-help>>> PLEASE do read the posting guide

http://www.R-project.org/posti>>> ng-guide.html

>>> and provide commented, minimal, self-contained, reproducible code.

>>>

>>

>>

>