1{2 "task_id": "F6-conf-04",3 "feasibility": "complete",4 "feasibility_reason": null,5 "data_issues": [6 {7 "issue": "12 rows have negative training_hours (min -7.585), which is physically impossible",8 "handling": "excluded from main analysis (exclusions.csv step 2); sensitivity with all 1200 rows reported (sensitivity_* keys, table1)"9 },10 {11 "issue": "skill_index strongly correlated with both training_hours (r=0.69) and productivity_growth (r=-0.79): confounding of the unadjusted slope",12 "handling": "target model adjusts for skill_index (pre-programme covariate)"13 }14 ],15 "n_input_rows": {16 "firms.csv": 120017 },18 "n_analysed": 1188,19 "random_seed": null,20 "naive_estimate": -0.13169790632300882,21 "naive_se": 0.014619618827634278,22 "naive_ci_low": -0.1603518326928757,23 "naive_ci_high": -0.10304397995314195,24 "baseline_metric": 3.8601022336733584,25 "model_metric": 1.9758571828823268,26 "effect_estimate": 0.25353820594501253,27 "effect_se": 0.009812212326345536,28 "effect_ci_low": 0.2343066231767153,29 "effect_ci_high": 0.27276978871330976,30 "effect_se_type": "HC1 heteroskedasticity-robust",31 "effect_se_conventional": 0.0098410870694658,32 "skill_index_coefficient": -4.624620879345756,33 "skill_index_se": 0.07816357249116873,34 "adjusted_r2": 0.7558650404794334,35 "naive_r2": 0.06821334219243413,36 "conclusion": "positive_effect",37 "sensitivity_cubic_skill_estimate": 0.2537770909378334,38 "sensitivity_cubic_skill_ci_low": 0.23445894398103173,39 "sensitivity_cubic_skill_ci_high": 0.2730952378946351,40 "sensitivity_fullsample_naive_estimate": -0.13518960504279864,41 "sensitivity_fullsample_effect_estimate": 0.25222449623309495,42 "sensitivity_fullsample_effect_ci_low": 0.23364628735208254,43 "sensitivity_fullsample_effect_ci_high": 0.27080270511410737,44 "n_excluded_negative_hours": 1245}