{
  "task_id": "F6-conf-04",
  "feasibility": "complete",
  "feasibility_reason": null,
  "data_issues": [
    {
      "issue": "12 rows have negative training_hours (min -7.585), which is physically impossible",
      "handling": "excluded from the main analysis; sensitivity analysis re-estimates both models on all 1200 rows (keys sens_all_rows_*)"
    },
    {
      "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",
      "handling": "skill_index (measured before the programme) is included as a control in the model that targets the estimand"
    }
  ],
  "n_input_rows": {
    "firms.csv": 1200
  },
  "n_analysed": 1188,
  "random_seed": null,
  "naive_estimate": -0.13169790632300882,
  "naive_se": 0.014619618827634278,
  "naive_ci_low": -0.1603518326928757,
  "naive_ci_high": -0.10304397995314195,
  "baseline_metric": 3.8601022336733584,
  "model_metric": 1.9758571828823268,
  "effect_estimate": 0.25353820594501253,
  "effect_se": 0.009812212326345536,
  "effect_ci_low": 0.2343066231767153,
  "effect_ci_high": 0.27276978871330976,
  "skill_index_coefficient": -4.624620879345756,
  "skill_index_se": 0.07816357249116873,
  "se_type": "HC1 heteroskedasticity-robust; 95% CI = estimate +/- 1.96*SE (normal)",
  "conclusion": "positive_effect",
  "corr_skill_training": 0.677572028059802,
  "robust_quadratic_skill_effect": 0.25383792381516485,
  "robust_quadratic_skill_sq_pvalue": 0.5689381094023501,
  "robust_interaction_coef": -0.00032835690944043455,
  "robust_interaction_pvalue": 0.9564572077696775,
  "sens_all_rows_naive_estimate": -0.13518960504279864,
  "sens_all_rows_effect_estimate": 0.25222449623309495,
  "sens_all_rows_effect_se": 0.00947885217664965,
  "n_excluded_negative_hours": 12
}