Re: [R] glht() used with coxph()

[array chip]

In case anyone is interested, I figure it out that when strata is used, I have 
to specify the comparison matrix manually:

> (fit<-coxph(Surv(stop, status>0)~treatment+strata(enum),bladder1))
> coef(fit)
treatmentpyridoxine   treatmentthiotepa 
  0.1877925  -0.2097894
> glht(fit,linfct=mcp(treatment='Tukey'))
Error in glht.matrix(model = list(coefficients = c(0.187792527684977,  : 
  ‘ncol(linfct)’ is not equal to ‘length(coef(model))’

> K<-rbind('pyridoxine - placebo'= c(1,0),'thiotepa - placebo' = 
> c(0,1),'thiotepa 
>- pyridoxine'= c(-1,1))
> glht(fit,linfct=K)
 General Linear Hypotheses

Linear Hypotheses:
   Estimate
pyridoxine - placebo == 00.1878
thiotepa - placebo == 0 -0.2098
thiotepa - pyridoxine == 0  -0.3976

John






To: r-help@r-project.org
Sent: Tue, March 1, 2011 11:38:22 AM
Subject: [R] glht() used with coxph()

Hi, I am experimenting with using glht() from multcomp package together with 
coxph(), and glad to find that glht() can work on coph object, for example:

> (fit<-coxph(Surv(stop, status>0)~treatment,bladder1))
coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1)


  coef exp(coef) se(coef)  zp
treatmentpyridoxine -0.063 0.9390.161 -0.391 0.70
treatmentthiotepa   -0.159 0.8530.168 -0.947 0.34

Likelihood ratio test=0.91  on 2 df, p=0.635  n= 294 

> glht(fit,linfct=mcp(treatment='Tukey'))

 General Linear Hypotheses

Multiple Comparisons of Means: Tukey Contrasts


Linear Hypotheses:
   Estimate
pyridoxine - placebo == 0  -0.06303
thiotepa - placebo == 0-0.15885
thiotepa - pyridoxine == 0 -0.09582

However, once I added a strata term in the formula of coxph(), then glht() 
can't 

work anymore:

> (fit<-coxph(Surv(stop, status>0)~treatment+strata(enum),bladder1))
coxph(formula = Surv(stop, status > 0) ~ treatment + strata(enum), 
data = bladder1)


  coef exp(coef) se(coef) zp
treatmentpyridoxine  0.188  1.210.170  1.11 0.27
treatmentthiotepa   -0.210  0.810.172 -1.22 0.22

Likelihood ratio test=4.39  on 2 df, p=0.111  n= 294 

> glht(fit,linfct=mcp(treatment='Tukey'))
Error in glht.matrix(model = list(coefficients = c(0.187792527684977,  : 
  ‘ncol(linfct)’ is not equal to ‘length(coef(model))’

Can anyone suggest why strata would make coxph object ineligible for glht()? Or 
how to make it work?

Thanks

John


  
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[R] glht() used with coxph()

[array chip]

Hi, I am experimenting with using glht() from multcomp package together with 
coxph(), and glad to find that glht() can work on coph object, for example:

> (fit<-coxph(Surv(stop, status>0)~treatment,bladder1))
coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1)


  coef exp(coef) se(coef)  zp
treatmentpyridoxine -0.063 0.9390.161 -0.391 0.70
treatmentthiotepa   -0.159 0.8530.168 -0.947 0.34

Likelihood ratio test=0.91  on 2 df, p=0.635  n= 294 

> glht(fit,linfct=mcp(treatment='Tukey'))

 General Linear Hypotheses

Multiple Comparisons of Means: Tukey Contrasts


Linear Hypotheses:
   Estimate
pyridoxine - placebo == 0  -0.06303
thiotepa - placebo == 0-0.15885
thiotepa - pyridoxine == 0 -0.09582

However, once I added a strata term in the formula of coxph(), then glht() 
can't 
work anymore:

> (fit<-coxph(Surv(stop, status>0)~treatment+strata(enum),bladder1))
coxph(formula = Surv(stop, status > 0) ~ treatment + strata(enum), 
data = bladder1)


  coef exp(coef) se(coef) zp
treatmentpyridoxine  0.188  1.210.170  1.11 0.27
treatmentthiotepa   -0.210  0.810.172 -1.22 0.22

Likelihood ratio test=4.39  on 2 df, p=0.111  n= 294 

> glht(fit,linfct=mcp(treatment='Tukey'))
Error in glht.matrix(model = list(coefficients = c(0.187792527684977,  : 
  ‘ncol(linfct)’ is not equal to ‘length(coef(model))’

Can anyone suggest why strata would make coxph object ineligible for glht()? Or 
how to make it work?

Thanks

John


  
[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.