Compute Weibull model

For a Weibull model with covariates, we can compute the survival curve just as we did for the Weibull model without covariates. The only thing we need to do is specify the covariate values for a given survival curve in the predict() function. This can be done with the argument newdata.

This exercise is part of the course

Survival Analysis in R

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Exercise instructions

Compute a Weibull model for the GBSG2 dataset with covariate horTh to analyze the effect of hormonal therapy on the survival of patients.
Compute the survival curve for patients who receive hormonal therapy.
Take a look at the survival curve with str().

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Weibull model
wbmod <- survreg(Surv(___, ___) ~ ___, data = GBSG2)
coef(wbmod)

# Retrieve survival curve from model
surv <- seq(.99, .01, by = -.01)
t_yes <- predict(___, type = "quantile", p = ___,
  newdata = data.frame(horTh = ___))

# Take a look at survival curve
str(t_yes)

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