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TomeHirata merged 1 commit into from
Aug 30, 2026
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docs(tutorials): fix broken Oregon tutorial code #139

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20 changes: 10 additions & 10 deletions docs/docs/tutorials/oregon.md
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Original file line number Diff line number Diff line change
Expand Up @@ -215,7 +215,7 @@ lpte_ml, lpte_lower_ml, lpte_upper_ml = ml_local_estimator.predict_lpte(
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))

# Simple local estimator
plot(outcome_ed_costs_locations[1:], lpte_simple, lpte_lower_simple, lpte_upper_simple,
plot(outcome_ed_costs_locations, lpte_simple, lpte_lower_simple, lpte_upper_simple,
chart_type="bar",
title="Effects of Emergency Department Costs (Simple Local Estimator)",
xlabel="Emergency Department Costs",
Expand All @@ -224,7 +224,7 @@ plot(outcome_ed_costs_locations[1:], lpte_simple, lpte_lower_simple, lpte_upper_
ax=ax1)

# ML-adjusted local estimator
plot(outcome_ed_costs_locations[1:], lpte_ml, lpte_lower_ml, lpte_upper_ml,
plot(outcome_ed_costs_locations, lpte_ml, lpte_lower_ml, lpte_upper_ml,
chart_type="bar",
title="Effects of Emergency Department Costs (ML-Adjusted Local Estimator)",
xlabel="Emergency Department Costs",
Expand Down Expand Up @@ -275,13 +275,13 @@ Let's compare the results from both simple and machine learning-adjusted local e

```python
# Compute LDTE: Treatment vs Control
ldte_simple, lower_simple, upper_simple = simple_local_estimator.predict_ldte(
ldte_visits_simple, lower_visits_simple, upper_visits_simple = simple_local_estimator.predict_ldte(
target_treatment_arm=1, # Z=1 Selected for treatment (Enrolled)
control_treatment_arm=0, # Z=0 Not selected for treatment (Not enrolled)
locations=outcome_ed_visits_locations
)

ldte_ml, lower_ml, upper_ml = ml_local_estimator.predict_ldte(
ldte_visits_ml, lower_visits_ml, upper_visits_ml = ml_local_estimator.predict_ldte(
target_treatment_arm=1, # Selected for treatment (Enrolled)
control_treatment_arm=0, # Not selected for treatment (Not enrolled)
locations=outcome_ed_visits_locations
Expand All @@ -291,14 +291,14 @@ ldte_ml, lower_ml, upper_ml = ml_local_estimator.predict_ldte(
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))

# Visualize Treatment vs Control using dte_adj's plot function
plot(outcome_ed_visits_locations, ldte_simple, lower_simple, upper_simple,
plot(outcome_ed_visits_locations, ldte_visits_simple, lower_visits_simple, upper_visits_simple,
title="ED Visits: Treatment vs Control (Simple Local Estimator)",
xlabel="Emergency Department Visits",
ylabel="Local Distribution Treatment Effect",
color="purple",
ax=ax1)

plot(outcome_ed_visits_locations, ldte_ml, lower_ml, upper_ml,
plot(outcome_ed_visits_locations, ldte_visits_ml, lower_visits_ml, upper_visits_ml,
title="ED Visits: Treatment vs Control (ML-Adjusted Local Estimator)",
xlabel="Emergency Department Visits",
ylabel="Local Distribution Treatment Effect",
Expand All @@ -324,13 +324,13 @@ The confidence intervals are not substantially narrower with ML adjustment. Both

```python
# Compute Local Probability Treatment Effects
lpte_simple, lpte_lower_simple, lpte_upper_simple = simple_local_estimator.predict_lpte(
lpte_visits_simple, lpte_visits_lower_simple, lpte_visits_upper_simple = simple_local_estimator.predict_lpte(
target_treatment_arm=1, # Z=1 Selected for treatment (Enrolled)
control_treatment_arm=0, # Z=0 Not selected for treatment (Not enrolled)
locations=np.insert(outcome_ed_visits_locations, 0, -1)
)

lpte_ml, lpte_lower_ml, lpte_upper_ml = ml_local_estimator.predict_lpte(
lpte_visits_ml, lpte_visits_lower_ml, lpte_visits_upper_ml = ml_local_estimator.predict_lpte(
target_treatment_arm=1, # Z=1 Selected for treatment (Enrolled)
control_treatment_arm=0, # Z=0 Not selected for treatment (Not enrolled)
locations=np.insert(outcome_ed_visits_locations, 0, -1)
Expand All @@ -339,7 +339,7 @@ lpte_ml, lpte_lower_ml, lpte_upper_ml = ml_local_estimator.predict_lpte(
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))

# Simple local estimator
plot(outcome_ed_visits_locations[1:], lpte_simple, lpte_lower_simple, lpte_upper_simple,
plot(outcome_ed_visits_locations, lpte_visits_simple, lpte_visits_lower_simple, lpte_visits_upper_simple,
chart_type="bar",
title="Effects of Emergency Department Visits (Simple Local Estimator)",
xlabel="Emergency Department Visits",
Expand All @@ -348,7 +348,7 @@ plot(outcome_ed_visits_locations[1:], lpte_simple, lpte_lower_simple, lpte_upper
ax=ax1)

# ML-adjusted local estimator
plot(outcome_ed_visits_locations[1:], lpte_ml, lpte_lower_ml, lpte_upper_ml,
plot(outcome_ed_visits_locations, lpte_visits_ml, lpte_visits_lower_ml, lpte_visits_upper_ml,
chart_type="bar",
title="Effects of Emergency Department Visits (ML-Adjusted Local Estimator)",
xlabel="Emergency Department Visits",
Expand Down