&amp;nbsp; &amp;nbsp;  &amp;nbsp; Create a function to run your analysis once on a sample of your data&lt;/h3&gt; 

.small[

```r
fit_ipw &lt;- function(split, ...) {
  .df &lt;- analysis(split)
  
* # fit propensity score model
* propensity_model &lt;- glm(
*   exposure ~ confounder_1 + confounder_2 + ...
*   family = binomial(),
*   data = .df
* )
  
  # calculate inverse probability weights
  .df &lt;- propensity_model %&gt;% 
    augment(type.predict = "response", data = .df) %&gt;% 
    mutate(wts = 1 