From eed4142e2bcbed4cd1873067101795ffbfcd4e77 Mon Sep 17 00:00:00 2001
From: Stiofain Fordham <17852477+sdfordham@users.noreply.github.com>
Date: Sun, 19 Nov 2023 14:50:32 +0000
Subject: [PATCH] Add a method that returns ATT

---
 pysyncon/base.py | 30 +++++++++++++++++++++++++++++-
 1 file changed, 29 insertions(+), 1 deletion(-)

diff --git a/pysyncon/base.py b/pysyncon/base.py
index fd03ed1..944be7d 100644
--- a/pysyncon/base.py
+++ b/pysyncon/base.py
@@ -94,7 +94,7 @@ def path_plot(
 
     def _gaps(self, time_period: Optional[IsinArg_t] = None) -> pd.Series:
         """Calculate the gaps (difference between factual
-        and estimated conterfactual)
+        and estimated counterfactual)
 
         Parameters
         ----------
@@ -238,6 +238,34 @@ def summary(self, round: int = 3) -> pd.DataFrame:
 
         return pd.concat([treated, synthetic, sample_mean], axis=1).round(round)
 
+    def att(self, time_period: IsinArg_t) -> dict[str, float]:
+        """Computes the average treatment effect on the treated unit (ATT) and
+        the standard error to the value over the chosen time-period.
+
+        Parameters
+        ----------
+        time_period : Iterable | pandas.Series | dict, optional
+            Time period to compute the ATT over.
+
+        Returns
+        -------
+        dict
+            A dictionary with the ATT value and the standard error to the ATT.
+
+        Raises
+        ------
+        ValueError
+            If there is no weight matrix available
+        """
+        if self.W is None:
+            raise ValueError("No weight matrix available; fit data first.")
+        gaps = self._gaps(time_period=time_period)
+
+        att = np.mean(gaps)
+        se = np.std(gaps, ddof=1) / np.sqrt(len(time_period))
+
+        return {"att": att.item(), "se": se.item()}
+
 
 class VanillaOptimMixin:
     @staticmethod