horseshoe {bonsaiforest} | R Documentation |
Bayesian Shrinkage Model Estimation
Description
Function to fit a bayesian shrinkage model with a regularized horseshoe prior
on the interaction coefficients between the subgrouping covariates and
the treatment.
Usage
horseshoe(
resp,
trt,
subgr,
covars,
data,
resptype = c("survival", "binary"),
status = NULL,
...
)
Arguments
resp |
(string ) the response variable name.
|
trt |
(string ) the treatment variable name.The treatment variable
must be a factor with 2 levels where the first level is the control and the
second one the treatment.
|
subgr |
(character ) vector with the name of the subgroup variables
from which we want to obtain the subgroup treatment effect. They have to be
factor variables with the subgroups as levels.
|
covars |
(character ) vector with the name of the variables that
we want to include in the model. They have to be factor variables with the
subgroups as levels. The subgr variables have to be included here.
|
data |
(data frame ) the data frame with the variables.
|
resptype |
(string ) the type of data used. Can be "survival"
or "binary".
|
status |
(string ) only for "survival" resptype ,
the status variable name in survival data.
|
... |
Additional arguments from the brm function.
|
Value
List with fit
, model
, resptype
, data
, alpha
,
design_matrix
, design_dummy
, y
, subgr_names
.
Examples
horseshoe("ev_pfs", "arm", c("x_1", "x_2"), c("x_1", "x_2", "x_3"),
example_data, "binary",
chains = 1, seed = 0, control = list(adapt_delta = 0.95),
iter = 50 # In practice, you need to omit this or set it much higher!
)
[Package
bonsaiforest version 0.1.0
Index]