APO Models

APO Pointwise Coverage

The simulations are based on the the make_irm_data_discrete_treatments-DGP with 500 observations. Due to the linearity of the DGP, Lasso and Logit Regression are nearly optimal choices for the nuisance estimation.

DoubleML Version                   0.10.dev0
Script                   irm_apo_coverage.py
Date                     2025-01-08 15:02:49
Total Runtime (seconds)         10054.695461
Python Version                        3.12.8
Table 1: Coverage for 95.0%-Confidence Interval over 1000 Repetitions
Table 2: Coverage for 90.0%-Confidence Interval over 1000 Repetitions

APOS Coverage

The simulations are based on the the make_irm_data_discrete_treatments-DGP with 500 observations. Due to the linearity of the DGP, Lasso and Logit Regression are nearly optimal choices for the nuisance estimation.

The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).

DoubleML Version                   0.10.dev0
Script                   irm_apo_coverage.py
Date                     2025-01-08 15:02:49
Total Runtime (seconds)         10054.695461
Python Version                        3.12.8
Table 3: Coverage for 95.0%-Confidence Interval over 1000 Repetitions
Table 4: Coverage for 90.0%-Confidence Interval over 1000 Repetitions

Causal Contrast Coverage

The simulations are based on the the make_irm_data_discrete_treatments-DGP with 500 observations. Due to the linearity of the DGP, Lasso and Logit Regression are nearly optimal choices for the nuisance estimation.

The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).

DoubleML Version                   0.10.dev0
Script                   irm_apo_coverage.py
Date                     2025-01-08 15:02:49
Total Runtime (seconds)         10054.695461
Python Version                        3.12.8
Table 5: Coverage for 95.0%-Confidence Interval over 1000 Repetitions
Table 6: Coverage for 90.0%-Confidence Interval over 1000 Repetitions