Hi All,

I have conducted the following survival analysis which appears to be OK 

(acknow. to AZ & PR for solving my earlier issues). 

 

surv.mod1 <- survreg( Surv(timep1, relall6)~randgrpc, data=Dataset,
dist="weibull", scale = 1)
 summary(surv.mod1)
 Call:
 survreg(formula = Surv(timep1, relall6) ~ randgrpc, data = Dataset,
dist = "weibull", scale = 1)
            Value Std. Error     z         p
 (Intercept)  7.36      0.259 28.42 1.27e-177
 randgrpc    -0.59      0.156 -3.80  1.47e-04
 Scale fixed at 1
 Weibull distribution
 Loglik(model)= -1268.6   Loglik(intercept only)= -1276
        Chisq= 14.72 on 1 degrees of freedom, p= 0.00012
 Number of Newton-Raphson Iterations: 5
 n= 400



My question is how does one fits a weibull survival function to the
model, 

such that the output would be an alfa and beta (weibull parameters)?

 

Thanks

 

S.

 


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