fix_caw_wrapper: A wrapper for 'fix_caw' so that I can use SQUAREM.
In dcgerard/vicar: Various Ideas for Confounder Adjustment in Regression

A wrapper for fix_caw so that I can use SQUAREM.

fix_caw_wrapper(
  wzs_vec,
  rotate_out,
  weight_func = ash_wrap,
  weight_args = list(),
  min_scale = 0.8
)

`wzs_vec`	A vector of numerics. The first p of which are the `w_current`, the next `length(cov_of_interest) * k` of which are `Z2hat`, the last of which is `scale_val`.
`rotate_out`	The output from `rotate_model` with `degrees_freedom` added to the list.
`weight_func`	The function that calculates the weights given `w_current`. So far, this only supports functions that take as input three quantities: `betahat`, `sebetahat`, and `degrees_freedom`
`weight_args`	Additional arguments to pass to `weight_func`.
`min_scale`	A scalar. The minimum value that `scale_val` is allowed to take. In practice, you wouldn't think that shrinking the variance is a good idea. But a value of 1 seems to stringent. So I set this to 0.8 to give you some wiggle room. Most of the time `scale_val` is usually estimated greater than 1.