{
  "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 main analysis (exclusions.csv step 2); sensitivity with all 1200 rows reported (sensitivity_* keys, table1)"
    },
    {
      "issue": "skill_index strongly correlated with both training_hours (r=0.69) and productivity_growth (r=-0.79): confounding of the unadjusted slope",
      "handling": "target model adjusts for skill_index (pre-programme covariate)"
    }
  ],
  "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,
  "effect_se_type": "HC1 heteroskedasticity-robust",
  "effect_se_conventional": 0.0098410870694658,
  "skill_index_coefficient": -4.624620879345756,
  "skill_index_se": 0.07816357249116873,
  "adjusted_r2": 0.7558650404794334,
  "naive_r2": 0.06821334219243413,
  "conclusion": "positive_effect",
  "sensitivity_cubic_skill_estimate": 0.2537770909378334,
  "sensitivity_cubic_skill_ci_low": 0.23445894398103173,
  "sensitivity_cubic_skill_ci_high": 0.2730952378946351,
  "sensitivity_fullsample_naive_estimate": -0.13518960504279864,
  "sensitivity_fullsample_effect_estimate": 0.25222449623309495,
  "sensitivity_fullsample_effect_ci_low": 0.23364628735208254,
  "sensitivity_fullsample_effect_ci_high": 0.27080270511410737,
  "n_excluded_negative_hours": 12
}