Weibull survival distribution (proportional hazards formulation)
Source:R/outcome_surv_weibull_ph.R
      outcome_surv_weibull_ph.RdWeibull survival distribution (proportional hazards formulation)
Arguments
- time_var
- character. Name of time variable column in model matrix 
- cens_var
- character. Name of the censorship variable flag in model matrix 
- shape_prior
- Priorclass object for the Weibull shape parameter. Default is- prior_exponential(beta = 0.0001).
- baseline_prior
- Prior. Object of class- Priorspecifying prior distribution for the baseline outcome. See- Detailsfor more information.
- weight_var
- character. Optional name of variable in model matrix for weighting the log likelihood. 
Value
Object of class OutcomeSurvWeibullPH.
Details
Baseline Prior
The baseline_prior argument specifies the prior distribution for the
baseline log hazard rate. The interpretation of the baseline_prior differs
slightly between borrowing methods selected.
- Dynamic borrowing using - borrowing_hierarchical_commensurate(): the- baseline_priorfor Bayesian Dynamic Borrowing refers to the log hazard rate of the external control arm.
- Full borrowing or No borrowing using - borrowing_full()or- borrowing_none(): the- baseline_priorfor these borrowing methods refers to the log hazard rate for the internal control arm.
See also
Other outcome models:
outcome_bin_logistic(),
outcome_cont_normal(),
outcome_surv_exponential(),
outcome_surv_pem()
Examples
ws <- outcome_surv_weibull_ph(
  time_var = "time",
  cens_var = "cens",
  shape_prior = prior_exponential(1),
  baseline_prior = prior_normal(0, 1000)
)