# Specify Borrowing Model

`borrowing_details.Rd`

Specify type of borrowing and, for Bayesian Dynamic Borrowing, set hyperprior for commensurability parameter tau.

## Arguments

- method
character. The type of borrowing to perform. It must be one of:

`'BDB'`

,`'Full borrowing'`

, or`'No borrowing'`

. See*Details*for more information.- ext_flag_col
character. The name of the column in the data matrix that corresponds to the external control flag (

`1`

/`0`

or`TRUE`

/`FALSE`

). This identifies a patient as belonging to the external control cohort.- tau_prior
Object of class

`Prior`

defining the hyperprior on the "commensurability parameter". See`Details`

for more information.

## Value

Object of class `Borrowing`

.

## Details

### Method

The `method`

argument specifies the type of borrowing that will be
implemented. There are currently three types of borrowing that are supported:

*'BDB'*for Bayesian Dynamic Borrowing. In Bayesian Dynamic Borrowing, external control information is borrowed to the extent that the outcomes (i.e., log hazard rates or log odds) are similar between external and internal control populations. See Viele et. al. 2014.*'Full borrowing'*for pooling of historical and concurrent controls. There is no distinction between patients in the internal and external control arms. While the`ext_flag_col`

must still be specified, it is not used.*'No borrowing'*for evaluating only the internal comparison, ignoring historical controls. Note that this method will filter the model matrix based on values in`ext_flag_col`

.

Though the ultimate model specification is the same for 'Full borrowing' and 'No borrowing', both are available as options to facilitate comparison between methods.

### External Control

The `ext_flag_col`

argument refers to the column in the data matrix that
contains the flag indicating a patient is from the external control cohort.
While this column is not used in 'Full borrowing', it must still be
specified.

### Tau Prior

The `tau_prior`

argument specifies the hyperprior on the precision parameter
commonly referred to as the commensurability parameter.
See Viele et. al. 2014 for more
details.
This hyperprior determines (along with the comparability of the outcomes
between internal and external controls) how much borrowing of the external
control group will be performed.
Example hyperpriors include largely uninformative inverse gamma distributions
[e.g., `gamma_prior(alpha = .001, beta = .001)`

] as well as more
informative distributions [e.g., `gamma_prior(alpha = 1, beta = .001`

)],
though any distribution \(x \in (0, \infty)\) can be used. Distributions
with more density at higher values of \(x\) (i.e., higher precision)
will lead to more borrowing.

## References

Viele, K., Berry, S., Neuenschwander, B., Amzal, B., Chen, F.,
Enas, N., Hobbs, B., Ibrahim, J.G., Kinnersley, N., Lindborg, S., Micallef,
S., Roychoudhury, S. and Thompson, L. (2014),
Use of historical control data for assessing treatment effects in clinical trials.
**Pharmaceut. Statist., 13: 41--54**. doi:10.1002/pst.1589

## Examples

```
sb <- borrowing_details(
method = "BDB",
ext_flag_col = "ext",
tau_prior = gamma_prior(0.001, 0.001)
)
```