outcome_cont_normal {psborrow2} | R Documentation |
Normal Outcome Distribution
Description
Normal Outcome Distribution
Usage
outcome_cont_normal(
continuous_var,
baseline_prior,
std_dev_prior,
weight_var = ""
)
Arguments
continuous_var |
character. Name of continuous outcome variable in the model matrix |
baseline_prior |
|
std_dev_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
intercept of the linear model. 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 intercept of the external control arm. -
Full borrowing or No borrowing using
borrowing_full()
orborrowing_none()
: thebaseline_prior
for these borrowing methods refers to the intercept for the internal control arm.
Value
Object of class OutcomeContinuousNormal
.
See Also
Other outcome models:
outcome_bin_logistic()
,
outcome_surv_exponential()
,
outcome_surv_weibull_ph()
Examples
norm <- outcome_cont_normal(
continuous_var = "tumor_size",
baseline_prior = prior_normal(0, 100),
std_dev_prior = prior_half_cauchy(1, 5)
)