RLMResults does not have bse = sqrt(diag(cov_params))
bse = sqrt(diag(cov_params))
generic results based on cov_params (e.g. t_test) are not the same as those by the specific methods.
generic tvalues uses bse which is correctly based on bcov_scaled
cov_params should return the default covariance which is bcov_scaled
found while testing that t_test(eye(..)) returns the same as tvalues, pvalues across models (after adjusting for normal/t distribution.
In my robustcov branch I can just set it in __init__ with
self.cov_params_default = self.bcov_scaled
REF: use robustcov in RLM as default, see #1164
Note: the above commit 6117549 broke bcov_unscaled, (and RLM tests were failing)
fixed in 87684b7 by replacing with normalized_cov_params
Currently there is no cov option unscaled, the only available options are H1, H2, H3
Should there be a "non-robust" option?
Looks like this is fixed in master with the two commits.
missing unit tests for this?
Closing. Create a separate issue to add tests, if desired.