R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(survey)
Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Attaching package: 'survey'
The following object is masked from 'package:graphics':
dotchart
> library(survival)
> data(nwtco)
>
> ntwco<-subset(nwtco, !is.na(edrel))
>
> load("nwtco-subcohort.rda")
> nwtco$subcohort<-subcohort
>
> d_BorganII <- twophase(id=list(~seqno,~seqno),
+ strata=list(NULL,~interaction(instit,rel)),
+ data=nwtco, subset=~I(rel |subcohort))
>
> ##Coefficient results same as Splus with code from
> ## http://faculty.washington.edu/norm/software.html
> ## SE slightly larger due to using sandwich variance.
>
> svycoxph(Surv(edrel, rel)~factor(stage)+factor(histol)+I(age/12), design=d_BorganII)
Call:
svycoxph(formula = Surv(edrel, rel) ~ factor(stage) + factor(histol) +
I(age/12), design = d_BorganII)
coef exp(coef) se(coef) z p
factor(stage)2 0.4629 1.5886 0.1809 2.56 0.0105
factor(stage)3 0.5831 1.7916 0.1785 3.27 0.0011
factor(stage)4 1.0597 2.8854 0.2052 5.16 2.4e-07
factor(histol)2 1.5974 4.9403 0.1334 11.97 < 2e-16
I(age/12) 0.0299 1.0304 0.0334 0.90 0.3697
Likelihood ratio test= on 5 df, p=
n= 1062, number of events= 571
>
> ##
> ## This gives higher standard errors. calibrate() does not recompute the
> ## finite population correction if a calibration variable happens to predict
> ## sampling perfectly. It probably should.
> ##
> d_BorganIIps<-calibrate(twophase(id=list(~seqno,~seqno),
+ strata=list(NULL,~rel),
+ data=nwtco, subset=~I(rel |subcohort)),
+ phase=2, formula=~interaction(instit,rel),
+ epsilon=1e-10)
>
> svycoxph(Surv(edrel, rel)~factor(stage)+factor(histol)+I(age/12), design=d_BorganIIps)
Call:
svycoxph(formula = Surv(edrel, rel) ~ factor(stage) + factor(histol) +
I(age/12), design = d_BorganIIps)
coef exp(coef) se(coef) z p
factor(stage)2 0.4629 1.5886 0.1808 2.56 0.0104
factor(stage)3 0.5831 1.7916 0.1784 3.27 0.0011
factor(stage)4 1.0597 2.8854 0.2051 5.17 2.4e-07
factor(histol)2 1.5974 4.9403 0.1304 12.25 < 2e-16
I(age/12) 0.0299 1.0304 0.0333 0.90 0.3688
Likelihood ratio test= on 5 df, p=
n= 1062, number of events= 571
>
> proc.time()
user system elapsed
1.823 0.105 1.962
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