outcome_surv_exponential {psborrow2} | R Documentation |
Exponential survival distribution
Description
Exponential survival distribution
Usage
outcome_surv_exponential(time_var, cens_var, baseline_prior, weight_var = "")
Arguments
time_var |
character. Name of time variable column in model matrix |
cens_var |
character. Name of the censorship variable flag in model matrix |
baseline_prior |
|
weight_var |
character. Optional name of variable in model matrix for weighting the log likelihood. |
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.
Value
Object of class OutcomeSurvExponential
.
See Also
Other outcome models:
outcome_bin_logistic()
,
outcome_cont_normal()
,
outcome_surv_weibull_ph()
Examples
es <- outcome_surv_exponential(
time_var = "time",
cens_var = "cens",
baseline_prior = prior_normal(0, 1000)
)