InversePropensityWeighting.make_raw_adjustments#
- InversePropensityWeighting.make_raw_adjustments(ps)[source]#
Compute inverse-propensity-weighted outcomes using the raw (basic) scheme.
This is the simplest form of inverse propensity weighting, as discussed in Aronow and Miller’s Foundations of Agnostic Statistics. Each observation is weighted by the reciprocal of its propensity score (or
1 - psfor the control group).- Parameters:
ps (
ndarray) – Propensity scores for each observation.- Returns:
A tuple of
(weighted_outcome0, weighted_outcome1, n_ntrt, n_trt)where the weighted outcomes are the IPW-adjusted outcome values for the control and treated groups.n_ntrtandn_trtare both equal to the total number of observations (the raw scheme normalises by the full sample size).- Return type: