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 the main analysis; sensitivity analysis re-estimates both models on all 1200 rows (keys sens_all_rows_*)"9 },10 {11 "issue": "training_hours is strongly correlated with pre-programme skill_index (r = 0.694 in all 1200 rows), and skill_index is strongly negatively related to productivity_growth: the unadjusted slope is confounded",12 "handling": "skill_index (measured before the programme) is included as a control in the model that targets the estimand"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 "skill_index_coefficient": -4.624620879345756,31 "skill_index_se": 0.07816357249116873,32 "se_type": "HC1 heteroskedasticity-robust; 95% CI = estimate +/- 1.96*SE (normal)",33 "conclusion": "positive_effect",34 "corr_skill_training": 0.677572028059802,35 "robust_quadratic_skill_effect": 0.25383792381516485,36 "robust_quadratic_skill_sq_pvalue": 0.5689381094023501,37 "robust_interaction_coef": -0.00032835690944043455,38 "robust_interaction_pvalue": 0.9564572077696775,39 "sens_all_rows_naive_estimate": -0.13518960504279864,40 "sens_all_rows_effect_estimate": 0.25222449623309495,41 "sens_all_rows_effect_se": 0.00947885217664965,42 "n_excluded_negative_hours": 1243}