Weibull survival distribution (proportional hazards formulation)
Source:R/outcome_surv_weibull_ph.R
outcome_surv_weibull_ph.Rd
Weibull 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
Prior
class object for the Weibull shape parameter. Default isprior_exponential(beta = 0.0001)
.- baseline_prior
Prior
. Object of classPrior
specifying prior distribution for the baseline outcome. SeeDetails
for 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()
: thebaseline_prior
for Bayesian Dynamic Borrowing refers to the log hazard rate of the external control arm.Full borrowing or No borrowing using
borrowing_full()
orborrowing_none()
: thebaseline_prior
for 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)
)