A new version of Design will be posted to CRAN in the next 2 days.
After than, update your system, including an update to the survival
package. Then re-try.
Your formula is wrong as it can't be negative. LR should be the
likelihood ratio chi-square stat : -2 times the difference in the two
loglik values.
Frank
Andrea Weidacher wrote:> Hello All,
>
> as I?m new to R and survival analysis, I?ve got a question about the
> Design::validate function:
>
> My Code:
> cox <- cph(Surv(t,status) ~ var1 + var2 + var3, data=data, x=TRUE,
y=TRUE,
> surv=TRUE)
> cox.val <- validate(cox, B=10, dxy=TRUE, pr=TRUE);
>
> My output (cox.val):
> index.orig training test
> Dxy -0.3639222921368090891 -0.3591157308750822175 -0.3634294047761231106
> R2 1.0000000000000000000 1.0000000000000000000 1.0000000000000000000
> Slope 1.0000000000000000000 1.0000000000000000000 1.0055508323397084336
> D 0.0232804472888947744 0.0226998668193014774 0.0232190381679612834
> U -0.0000607553318187988 -0.0000610134584621832 0.0000254159617147094
> Q 0.0233412026207135703 0.0227608802777636665 0.0231936222062465713
> optimism index.corrected n
> Dxy 0.0043136739010409269 -0.36823596603785002657 10
> R2 0.0000000000000000000 1.00000000000000000000 10
> Slope -0.0055508323397084336 1.00555083233970843359 10
> D -0.0005191713486598047 0.02379961863755457596 10
> U -0.0000864294201768926 0.00002567408835809379 10
> Q -0.0004327419284829055 0.02377394454919647515 10
>
> And my question ist about the R2: Why ist the value always 1.0. That
doesn?t
> seem to me like a realistic value.
>
> And so I tried to calculate R2 with my own formula:
> LR <- -2*cox$loglik[2]
> L0 <- -2*cox$loglik[1]
> n <- length(data[,"ID"])
> R2N <- (1-exp(-LR/n)) / (1-exp(L0/n))
>
> R2N calculated that way is -0.00132314024559236.
>
> Can anybody help me to understand the formula to R2 and why the
> validate-function results in 1.0?
>
> Thanks,
>
> Andrea.
>
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> and provide commented, minimal, self-contained, reproducible code.
>
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University