R help - May 2012 - standard error

Dear all,
?I want to determine the standard error or the mean squared error for the
parameter estimate for beta and eta base on the real data.
?Any help on how to obtain these estimated errors.


library(survival)
d <- data.frame(ob=c(149971, 70808, 133518, 145658, 175701, 50960, 126606,
82329), state=1)
s <- Surv(d$ob,d$state)
sr <- survreg(s~1,dist="weibull")
beta<-1/sr$scale
p1=(beta)
p1
eta<-exp(sr$coefficients[1])
b=(eta)
b


Thank you
Chris Guure
Researcher
Institute for Mathematical Research
UPM

On May 28, 2012, at 5:20 AM, Christopher Kelvin wrote:
> Dear all,
>  I want to determine the standard error or the mean squared error  
> for the parameter estimate for beta and eta base on the real data.
>  Any help on how to obtain these estimated errors.
>
>
> library(survival)
> d <- data.frame(ob=c(149971, 70808, 133518, 145658, 175701, 50960,  
> 126606, 82329), state=1)
> s <- Surv(d$ob,d$state)
> sr <- survreg(s~1,dist="weibull")
> beta<-1/sr$scale
> p1=(beta)
> p1
> eta<-exp(sr$coefficients[1])
> b=(eta)
> b
The usual approach is to rely on the normality of the parameters on  
the "Weibull scale" and then back transform coef +/- 1.96*se(coef)

You get these with

summary(sr)

-- 
David.