diff --git a/book/ate/propensity_score_and_dml.ipynb b/book/ate/propensity_score_and_dml.ipynb
index c2e7639..417b71e 100644
--- a/book/ate/propensity_score_and_dml.ipynb
+++ b/book/ate/propensity_score_and_dml.ipynb
@@ -11,9 +11,1149 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "- Matching\n",
-    "- IPW, AIPW, Doubly Robust Estimator\n",
-    "- Double Machine Learning (비모수 버전의 Regression 처럼 활용 가능)"
+    "## Propensity Score Matching - Binary Treatment"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "미국 공립 고등학교에서 수행된 성장 마인드셋(Growth Mindset) 무작위 연구를 기반으로 생성된 시뮬레이션 데이터입니다.\n",
+    "\n",
+    "- **처치(intervention)**: 성장 마인드 교육 세미나 참여 여부\n",
+    "- **결과(achievement_score)**: 학업 성취도 점수\n",
+    "\n",
+    "그 외 공변량들은 학생과 학교의 배경 특성을 반영합니다.\n",
+    "\n",
+    "**참고**: [Athey & Wager (2019)](https://arxiv.org/pdf/1902.07409)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>schoolid</th>\n",
+       "      <th>intervention</th>\n",
+       "      <th>achievement_score</th>\n",
+       "      <th>success_expect</th>\n",
+       "      <th>ethnicity</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>frst_in_family</th>\n",
+       "      <th>school_urbanicity</th>\n",
+       "      <th>school_mindset</th>\n",
+       "      <th>school_achievement</th>\n",
+       "      <th>school_ethnic_minority</th>\n",
+       "      <th>school_poverty</th>\n",
+       "      <th>school_size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>76</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.277359</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.334544</td>\n",
+       "      <td>0.648586</td>\n",
+       "      <td>-1.310927</td>\n",
+       "      <td>0.224077</td>\n",
+       "      <td>-0.426757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>76</td>\n",
+       "      <td>1</td>\n",
+       "      <td>-0.449646</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.334544</td>\n",
+       "      <td>0.648586</td>\n",
+       "      <td>-1.310927</td>\n",
+       "      <td>0.224077</td>\n",
+       "      <td>-0.426757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>76</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.769703</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.334544</td>\n",
+       "      <td>0.648586</td>\n",
+       "      <td>-1.310927</td>\n",
+       "      <td>0.224077</td>\n",
+       "      <td>-0.426757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>76</td>\n",
+       "      <td>1</td>\n",
+       "      <td>-0.121763</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.334544</td>\n",
+       "      <td>0.648586</td>\n",
+       "      <td>-1.310927</td>\n",
+       "      <td>0.224077</td>\n",
+       "      <td>-0.426757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>76</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.526147</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.334544</td>\n",
+       "      <td>0.648586</td>\n",
+       "      <td>-1.310927</td>\n",
+       "      <td>0.224077</td>\n",
+       "      <td>-0.426757</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   schoolid  intervention  achievement_score  success_expect  ethnicity  \\\n",
+       "0        76             1           0.277359               6          4   \n",
+       "1        76             1          -0.449646               4         12   \n",
+       "2        76             1           0.769703               6          4   \n",
+       "3        76             1          -0.121763               6          4   \n",
+       "4        76             1           1.526147               6          4   \n",
+       "\n",
+       "   gender  frst_in_family  school_urbanicity  school_mindset  \\\n",
+       "0       2               1                  4        0.334544   \n",
+       "1       2               1                  4        0.334544   \n",
+       "2       2               0                  4        0.334544   \n",
+       "3       2               0                  4        0.334544   \n",
+       "4       1               0                  4        0.334544   \n",
+       "\n",
+       "   school_achievement  school_ethnic_minority  school_poverty  school_size  \n",
+       "0            0.648586               -1.310927        0.224077    -0.426757  \n",
+       "1            0.648586               -1.310927        0.224077    -0.426757  \n",
+       "2            0.648586               -1.310927        0.224077    -0.426757  \n",
+       "3            0.648586               -1.310927        0.224077    -0.426757  \n",
+       "4            0.648586               -1.310927        0.224077    -0.426757  "
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.read_csv(\"../data/matheus_data/learning_mindset.csv\")\n",
+    "\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Propensity Score Estimation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install causalml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.special import logit\n",
+    "import numpy as np\n",
+    "from causalml.propensity import ElasticNetPropensityModel\n",
+    "\n",
+    "categ = [\"ethnicity\",\"gender\",\"school_urbanicity\"]\n",
+    "cont  = [\"school_mindset\",\"school_achievement\",\"school_ethnic_minority\",\"school_poverty\",\"school_size\"]\n",
+    "X = pd.get_dummies(data[categ + cont], columns=categ, drop_first=True)\n",
+    "\n",
+    "pm = ElasticNetPropensityModel(\n",
+    "    random_state=42,\n",
+    "    max_iter=5000\n",
+    ")\n",
+    "\n",
+    "ps = pm.fit_predict(X.values, data[\"intervention\"].values)\n",
+    "logit_ps  = logit(np.clip(ps, 1e-6, 1-1e-6))\n",
+    "zlogit_ps = (logit_ps - logit_ps.mean()) / logit_ps.std(ddof=1)\n",
+    "\n",
+    "df = data.copy()\n",
+    "df[\"ps\"] = ps\n",
+    "df[\"ps_logit_z\"] = zlogit_ps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- **logit(PS) 표준화**: caliper 기준으로 사용 (Rosenbaum & Rubin, 1985)\n",
+    "- **clip(ε=1e-6)**: PS가 0 또는 1 근처일 때 수치 불안정 방지"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Matching - ATT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ATT: 0.4418 | match rate: 0.948\n"
+     ]
+    }
+   ],
+   "source": [
+    "from causalml.match import NearestNeighborMatch\n",
+    "\n",
+    "df_match = pd.concat([df[[\"intervention\", 'achievement_score', \"ps_logit_z\"]], X], axis=1)\n",
+    "\n",
+    "matcher_att = NearestNeighborMatch(\n",
+    "    caliper=0.2,\n",
+    "    replace=False,\n",
+    "    ratio=2,\n",
+    "    shuffle=False,\n",
+    "    random_state=42,\n",
+    "    treatment_to_control=True\n",
+    ")\n",
+    "\n",
+    "matched_att = matcher_att.match(\n",
+    "    data=df_match, treatment_col=\"intervention\", score_cols=[\"ps_logit_z\"]\n",
+    ")\n",
+    "\n",
+    "n_t = (df_match[\"intervention\"]==1).sum()\n",
+    "n_t_matched = (matched_att[\"intervention\"]==1).sum()\n",
+    "match_rate = n_t_matched / n_t if n_t else float(\"nan\")\n",
+    "\n",
+    "ATT = (\n",
+    "    matched_att.loc[matched_att[\"intervention\"]==1, 'achievement_score'].mean() \n",
+    "    - matched_att.loc[matched_att[\"intervention\"]==0, 'achievement_score'].mean()\n",
+    ")\n",
+    "\n",
+    "print(f\"ATT: {ATT:.4f} | match rate: {match_rate:.3f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- **caliper**: logit(PS) 표준편차의 0.2배를 기본값으로 사용 (Rosenbaum & Rubin, 1985)\n",
+    "  \n",
+    "  공통지지가 부족하거나 매칭률이 낮을 경우 0.25, 0.30 등으로 완화 가능\n",
+    "- **replace**: 기본은 비복원(False). 매칭률 확보를 위해 필요 시 복원(True) 허용\n",
+    "- **ratio**: 1:1에서 시작해 필요 시 1:K로 확장. 조정 기준은 `|SMD|<0.1`과 매칭률\n",
+    "\n",
+    "> 세 가지 조정은 분산 감소에 도움되지만, 멀리 있거나 중복된 대조군을 포함해 **bias–variance trade-off**를 동반할 수 있음을 고려해야 합니다.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Balance Check - ATT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def _mark_smd(val, thresh=0.1):\n",
+    "    try:\n",
+    "        f = float(val)\n",
+    "        return f\"{f:.4f}\" + (\"*\" if abs(f) >= thresh else \"\")\n",
+    "    except Exception:\n",
+    "        return val\n",
+    "\n",
+    "def combine_table_one(table_pre, table_post, smd_star_thresh=0.1):\n",
+    "    table_post = table_post.reindex(table_pre.index)\n",
+    "\n",
+    "    out = pd.DataFrame({\n",
+    "        \"Control (pre)\":   table_pre[\"Control\"],\n",
+    "        \"Treatment (pre)\": table_pre[\"Treatment\"],\n",
+    "        \"SMD (pre)\":       table_pre[\"SMD\"].astype(str),\n",
+    "        \"Control (post)\":  table_post[\"Control\"],\n",
+    "        \"Treatment (post)\":table_post[\"Treatment\"],\n",
+    "        \"SMD (post)\":      table_post[\"SMD\"].astype(str),\n",
+    "    }, index=table_pre.index)\n",
+    "\n",
+    "    mask_vars = out.index != \"n\"\n",
+    "    out.loc[mask_vars, \"SMD (pre)\"]  = out.loc[mask_vars, \"SMD (pre)\"].apply(_mark_smd, thresh=smd_star_thresh)\n",
+    "    out.loc[mask_vars, \"SMD (post)\"] = out.loc[mask_vars, \"SMD (post)\"].apply(_mark_smd, thresh=smd_star_thresh)\n",
+    "    out.index.name = \"Variable\"\n",
+    "    return out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Control (pre)</th>\n",
+       "      <th>Treatment (pre)</th>\n",
+       "      <th>SMD (pre)</th>\n",
+       "      <th>Control (post)</th>\n",
+       "      <th>Treatment (post)</th>\n",
+       "      <th>SMD (post)</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Variable</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>n</th>\n",
+       "      <td>7007</td>\n",
+       "      <td>3384</td>\n",
+       "      <td></td>\n",
+       "      <td>6414</td>\n",
+       "      <td>3209</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_10</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.0124</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.0094</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_11</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.12)</td>\n",
+       "      <td>-0.0117</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>-0.0050</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_12</th>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.03 (0.17)</td>\n",
+       "      <td>-0.0123</td>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.03 (0.17)</td>\n",
+       "      <td>-0.0109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_13</th>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>-0.0492</td>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>0.01 (0.12)</td>\n",
+       "      <td>0.0192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_14</th>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>-0.0170</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>-0.0093</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_15</th>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.0081</td>\n",
+       "      <td>0.04 (0.19)</td>\n",
+       "      <td>0.04 (0.19)</td>\n",
+       "      <td>-0.0001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_2</th>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>-0.0011</td>\n",
+       "      <td>0.15 (0.35)</td>\n",
+       "      <td>0.15 (0.35)</td>\n",
+       "      <td>0.0020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_3</th>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>-0.0163</td>\n",
+       "      <td>0.01 (0.09)</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>0.0127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_4</th>\n",
+       "      <td>0.48 (0.50)</td>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>0.0367</td>\n",
+       "      <td>0.51 (0.50)</td>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>-0.0137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_5</th>\n",
+       "      <td>0.04 (0.19)</td>\n",
+       "      <td>0.04 (0.20)</td>\n",
+       "      <td>0.0138</td>\n",
+       "      <td>0.04 (0.20)</td>\n",
+       "      <td>0.04 (0.20)</td>\n",
+       "      <td>-0.0056</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_6</th>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.01 (0.07)</td>\n",
+       "      <td>0.0336</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.0102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_7</th>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.01 (0.07)</td>\n",
+       "      <td>0.0199</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>-0.0102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_8</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>0.0238</td>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>-0.0001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_9</th>\n",
+       "      <td>0.01 (0.12)</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>-0.0316</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>0.0014</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender_2</th>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>0.47 (0.50)</td>\n",
+       "      <td>-0.0543</td>\n",
+       "      <td>0.48 (0.50)</td>\n",
+       "      <td>0.48 (0.50)</td>\n",
+       "      <td>0.0044</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_achievement</th>\n",
+       "      <td>0.04 (0.94)</td>\n",
+       "      <td>0.09 (0.93)</td>\n",
+       "      <td>0.0597</td>\n",
+       "      <td>0.08 (0.92)</td>\n",
+       "      <td>0.04 (0.89)</td>\n",
+       "      <td>-0.0431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_ethnic_minority</th>\n",
+       "      <td>-0.09 (0.97)</td>\n",
+       "      <td>-0.09 (0.96)</td>\n",
+       "      <td>-0.0048</td>\n",
+       "      <td>-0.14 (0.92)</td>\n",
+       "      <td>-0.11 (0.96)</td>\n",
+       "      <td>0.0314</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_mindset</th>\n",
+       "      <td>-0.01 (0.97)</td>\n",
+       "      <td>-0.10 (0.97)</td>\n",
+       "      <td>-0.0984</td>\n",
+       "      <td>-0.07 (0.95)</td>\n",
+       "      <td>-0.03 (0.91)</td>\n",
+       "      <td>0.0440</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_poverty</th>\n",
+       "      <td>-0.04 (0.97)</td>\n",
+       "      <td>-0.06 (0.96)</td>\n",
+       "      <td>-0.0249</td>\n",
+       "      <td>-0.03 (0.95)</td>\n",
+       "      <td>-0.03 (0.98)</td>\n",
+       "      <td>-0.0085</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_size</th>\n",
+       "      <td>-0.05 (1.00)</td>\n",
+       "      <td>0.02 (1.02)</td>\n",
+       "      <td>0.0729</td>\n",
+       "      <td>-0.02 (1.02)</td>\n",
+       "      <td>-0.01 (1.03)</td>\n",
+       "      <td>0.0071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_1</th>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>0.23 (0.42)</td>\n",
+       "      <td>-0.0288</td>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>-0.0135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_2</th>\n",
+       "      <td>0.19 (0.39)</td>\n",
+       "      <td>0.20 (0.40)</td>\n",
+       "      <td>0.0350</td>\n",
+       "      <td>0.19 (0.39)</td>\n",
+       "      <td>0.18 (0.39)</td>\n",
+       "      <td>-0.0163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_3</th>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.13 (0.34)</td>\n",
+       "      <td>-0.0472</td>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.14 (0.35)</td>\n",
+       "      <td>-0.0359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_4</th>\n",
+       "      <td>0.34 (0.48)</td>\n",
+       "      <td>0.36 (0.48)</td>\n",
+       "      <td>0.0267</td>\n",
+       "      <td>0.34 (0.47)</td>\n",
+       "      <td>0.37 (0.48)</td>\n",
+       "      <td>0.0540</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       Control (pre) Treatment (pre) SMD (pre) Control (post)  \\\n",
+       "Variable                                                                        \n",
+       "n                               7007            3384                     6414   \n",
+       "ethnicity_10             0.02 (0.13)     0.02 (0.13)    0.0124    0.02 (0.13)   \n",
+       "ethnicity_11             0.02 (0.13)     0.02 (0.12)   -0.0117    0.02 (0.13)   \n",
+       "ethnicity_12             0.03 (0.18)     0.03 (0.17)   -0.0123    0.03 (0.18)   \n",
+       "ethnicity_13             0.02 (0.14)     0.01 (0.11)   -0.0492    0.01 (0.11)   \n",
+       "ethnicity_14             0.06 (0.24)     0.06 (0.24)   -0.0170    0.06 (0.24)   \n",
+       "ethnicity_15             0.03 (0.18)     0.03 (0.18)    0.0081    0.04 (0.19)   \n",
+       "ethnicity_2              0.15 (0.36)     0.15 (0.36)   -0.0011    0.15 (0.35)   \n",
+       "ethnicity_3              0.01 (0.11)     0.01 (0.10)   -0.0163    0.01 (0.09)   \n",
+       "ethnicity_4              0.48 (0.50)     0.50 (0.50)    0.0367    0.51 (0.50)   \n",
+       "ethnicity_5              0.04 (0.19)     0.04 (0.20)    0.0138    0.04 (0.20)   \n",
+       "ethnicity_6              0.00 (0.06)     0.01 (0.07)    0.0336    0.00 (0.06)   \n",
+       "ethnicity_7              0.00 (0.06)     0.01 (0.07)    0.0199    0.00 (0.06)   \n",
+       "ethnicity_8              0.02 (0.13)     0.02 (0.14)    0.0238    0.02 (0.14)   \n",
+       "ethnicity_9              0.01 (0.12)     0.01 (0.10)   -0.0316    0.01 (0.10)   \n",
+       "gender_2                 0.50 (0.50)     0.47 (0.50)   -0.0543    0.48 (0.50)   \n",
+       "school_achievement       0.04 (0.94)     0.09 (0.93)    0.0597    0.08 (0.92)   \n",
+       "school_ethnic_minority  -0.09 (0.97)    -0.09 (0.96)   -0.0048   -0.14 (0.92)   \n",
+       "school_mindset          -0.01 (0.97)    -0.10 (0.97)   -0.0984   -0.07 (0.95)   \n",
+       "school_poverty          -0.04 (0.97)    -0.06 (0.96)   -0.0249   -0.03 (0.95)   \n",
+       "school_size             -0.05 (1.00)     0.02 (1.02)    0.0729   -0.02 (1.02)   \n",
+       "school_urbanicity_1      0.24 (0.43)     0.23 (0.42)   -0.0288    0.24 (0.43)   \n",
+       "school_urbanicity_2      0.19 (0.39)     0.20 (0.40)    0.0350    0.19 (0.39)   \n",
+       "school_urbanicity_3      0.15 (0.36)     0.13 (0.34)   -0.0472    0.15 (0.36)   \n",
+       "school_urbanicity_4      0.34 (0.48)     0.36 (0.48)    0.0267    0.34 (0.47)   \n",
+       "\n",
+       "                       Treatment (post) SMD (post)  \n",
+       "Variable                                            \n",
+       "n                                  3209             \n",
+       "ethnicity_10                0.02 (0.13)     0.0094  \n",
+       "ethnicity_11                0.02 (0.13)    -0.0050  \n",
+       "ethnicity_12                0.03 (0.17)    -0.0109  \n",
+       "ethnicity_13                0.01 (0.12)     0.0192  \n",
+       "ethnicity_14                0.06 (0.24)    -0.0093  \n",
+       "ethnicity_15                0.04 (0.19)    -0.0001  \n",
+       "ethnicity_2                 0.15 (0.35)     0.0020  \n",
+       "ethnicity_3                 0.01 (0.10)     0.0127  \n",
+       "ethnicity_4                 0.50 (0.50)    -0.0137  \n",
+       "ethnicity_5                 0.04 (0.20)    -0.0056  \n",
+       "ethnicity_6                 0.00 (0.06)     0.0102  \n",
+       "ethnicity_7                 0.00 (0.06)    -0.0102  \n",
+       "ethnicity_8                 0.02 (0.14)    -0.0001  \n",
+       "ethnicity_9                 0.01 (0.11)     0.0014  \n",
+       "gender_2                    0.48 (0.50)     0.0044  \n",
+       "school_achievement          0.04 (0.89)    -0.0431  \n",
+       "school_ethnic_minority     -0.11 (0.96)     0.0314  \n",
+       "school_mindset             -0.03 (0.91)     0.0440  \n",
+       "school_poverty             -0.03 (0.98)    -0.0085  \n",
+       "school_size                -0.01 (1.03)     0.0071  \n",
+       "school_urbanicity_1         0.24 (0.43)    -0.0135  \n",
+       "school_urbanicity_2         0.18 (0.39)    -0.0163  \n",
+       "school_urbanicity_3         0.14 (0.35)    -0.0359  \n",
+       "school_urbanicity_4         0.37 (0.48)     0.0540  "
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from causalml.match import create_table_one\n",
+    "\n",
+    "features_cov = list(X.columns)\n",
+    "\n",
+    "table_pre_att = create_table_one(\n",
+    "    data=df_match,\n",
+    "    treatment_col=\"intervention\",\n",
+    "    features=features_cov,\n",
+    "    with_std=True,\n",
+    "    with_counts=True\n",
+    ")\n",
+    "\n",
+    "table_post_att = create_table_one(\n",
+    "    data=matched_att,\n",
+    "    treatment_col=\"intervention\",\n",
+    "    features=features_cov,\n",
+    "    with_std=True,\n",
+    "    with_counts=True\n",
+    ")\n",
+    "\n",
+    "balance_att = combine_table_one(table_pre_att, table_post_att, smd_star_thresh=0.1)\n",
+    "balance_att"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Matching - ATC"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ATC: 0.3843 | control match rate: 0.999\n"
+     ]
+    }
+   ],
+   "source": [
+    "from causalml.match import NearestNeighborMatch\n",
+    "\n",
+    "matcher_atc = NearestNeighborMatch(\n",
+    "    caliper=0.3,\n",
+    "    replace=True,\n",
+    "    ratio=1,\n",
+    "    shuffle=False,\n",
+    "    random_state=42,\n",
+    "    treatment_to_control=False\n",
+    ")\n",
+    "\n",
+    "matched_atc = matcher_atc.match(\n",
+    "    data=df_match, treatment_col=\"intervention\", score_cols=[\"ps_logit_z\"]\n",
+    ")\n",
+    "\n",
+    "n_c = (df_match[\"intervention\"]==0).sum()\n",
+    "n_c_matched = (matched_atc[\"intervention\"]==0).sum()\n",
+    "match_rate = n_c_matched / n_c if n_c else float(\"nan\")\n",
+    "\n",
+    "ATC = (\n",
+    "    matched_atc.loc[matched_atc[\"intervention\"]==1, \"achievement_score\"].mean()\n",
+    "    - matched_atc.loc[matched_atc[\"intervention\"]==0, \"achievement_score\"].mean() \n",
+    ")\n",
+    "\n",
+    "print(f\"ATC: {ATC:.4f} | control match rate: {match_rate:.3f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Balance Check - ATC"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Control (pre)</th>\n",
+       "      <th>Treatment (pre)</th>\n",
+       "      <th>SMD (pre)</th>\n",
+       "      <th>Control (post)</th>\n",
+       "      <th>Treatment (post)</th>\n",
+       "      <th>SMD (post)</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Variable</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>n</th>\n",
+       "      <td>7007</td>\n",
+       "      <td>3384</td>\n",
+       "      <td></td>\n",
+       "      <td>6999</td>\n",
+       "      <td>6999</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_10</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.0124</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.08 (0.28)</td>\n",
+       "      <td>0.3132*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_11</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.12)</td>\n",
+       "      <td>-0.0117</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.00 (0.00)</td>\n",
+       "      <td>-0.1852*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_12</th>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.03 (0.17)</td>\n",
+       "      <td>-0.0123</td>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.00 (0.00)</td>\n",
+       "      <td>-0.2571*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_13</th>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>-0.0492</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>-0.1465*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_14</th>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>-0.0170</td>\n",
+       "      <td>0.06 (0.25)</td>\n",
+       "      <td>0.00 (0.00)</td>\n",
+       "      <td>-0.3702*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_15</th>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.0081</td>\n",
+       "      <td>0.03 (0.18)</td>\n",
+       "      <td>0.07 (0.26)</td>\n",
+       "      <td>0.1748*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_2</th>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>-0.0011</td>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.18 (0.39)</td>\n",
+       "      <td>0.0875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_3</th>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>-0.0163</td>\n",
+       "      <td>0.01 (0.11)</td>\n",
+       "      <td>0.00 (0.00)</td>\n",
+       "      <td>-0.1521*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_4</th>\n",
+       "      <td>0.48 (0.50)</td>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>0.0367</td>\n",
+       "      <td>0.48 (0.50)</td>\n",
+       "      <td>0.52 (0.50)</td>\n",
+       "      <td>0.0852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_5</th>\n",
+       "      <td>0.04 (0.19)</td>\n",
+       "      <td>0.04 (0.20)</td>\n",
+       "      <td>0.0138</td>\n",
+       "      <td>0.04 (0.19)</td>\n",
+       "      <td>0.05 (0.21)</td>\n",
+       "      <td>0.0352</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_6</th>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.01 (0.07)</td>\n",
+       "      <td>0.0336</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.0098</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_7</th>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.01 (0.07)</td>\n",
+       "      <td>0.0199</td>\n",
+       "      <td>0.00 (0.06)</td>\n",
+       "      <td>0.00 (0.00)</td>\n",
+       "      <td>-0.0863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_8</th>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.14)</td>\n",
+       "      <td>0.0238</td>\n",
+       "      <td>0.02 (0.13)</td>\n",
+       "      <td>0.02 (0.15)</td>\n",
+       "      <td>0.0458</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ethnicity_9</th>\n",
+       "      <td>0.01 (0.12)</td>\n",
+       "      <td>0.01 (0.10)</td>\n",
+       "      <td>-0.0316</td>\n",
+       "      <td>0.01 (0.12)</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>0.2440*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender_2</th>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>0.47 (0.50)</td>\n",
+       "      <td>-0.0543</td>\n",
+       "      <td>0.50 (0.50)</td>\n",
+       "      <td>0.53 (0.50)</td>\n",
+       "      <td>0.0646</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_achievement</th>\n",
+       "      <td>0.04 (0.94)</td>\n",
+       "      <td>0.09 (0.93)</td>\n",
+       "      <td>0.0597</td>\n",
+       "      <td>0.04 (0.94)</td>\n",
+       "      <td>0.05 (1.00)</td>\n",
+       "      <td>0.0132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_ethnic_minority</th>\n",
+       "      <td>-0.09 (0.97)</td>\n",
+       "      <td>-0.09 (0.96)</td>\n",
+       "      <td>-0.0048</td>\n",
+       "      <td>-0.09 (0.97)</td>\n",
+       "      <td>-0.14 (1.30)</td>\n",
+       "      <td>-0.0445</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_mindset</th>\n",
+       "      <td>-0.01 (0.97)</td>\n",
+       "      <td>-0.10 (0.97)</td>\n",
+       "      <td>-0.0984</td>\n",
+       "      <td>-0.01 (0.97)</td>\n",
+       "      <td>0.26 (0.65)</td>\n",
+       "      <td>0.3264*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_poverty</th>\n",
+       "      <td>-0.04 (0.97)</td>\n",
+       "      <td>-0.06 (0.96)</td>\n",
+       "      <td>-0.0249</td>\n",
+       "      <td>-0.04 (0.97)</td>\n",
+       "      <td>0.12 (0.57)</td>\n",
+       "      <td>0.1968*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_size</th>\n",
+       "      <td>-0.05 (1.00)</td>\n",
+       "      <td>0.02 (1.02)</td>\n",
+       "      <td>0.0729</td>\n",
+       "      <td>-0.05 (1.00)</td>\n",
+       "      <td>-0.19 (1.06)</td>\n",
+       "      <td>-0.1365*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_1</th>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>0.23 (0.42)</td>\n",
+       "      <td>-0.0288</td>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>0.06 (0.24)</td>\n",
+       "      <td>-0.5145*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_2</th>\n",
+       "      <td>0.19 (0.39)</td>\n",
+       "      <td>0.20 (0.40)</td>\n",
+       "      <td>0.0350</td>\n",
+       "      <td>0.19 (0.39)</td>\n",
+       "      <td>0.05 (0.21)</td>\n",
+       "      <td>-0.4412*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_3</th>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.13 (0.34)</td>\n",
+       "      <td>-0.0472</td>\n",
+       "      <td>0.15 (0.36)</td>\n",
+       "      <td>0.24 (0.43)</td>\n",
+       "      <td>0.2238*</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>school_urbanicity_4</th>\n",
+       "      <td>0.34 (0.48)</td>\n",
+       "      <td>0.36 (0.48)</td>\n",
+       "      <td>0.0267</td>\n",
+       "      <td>0.35 (0.48)</td>\n",
+       "      <td>0.65 (0.48)</td>\n",
+       "      <td>0.6475*</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       Control (pre) Treatment (pre) SMD (pre) Control (post)  \\\n",
+       "Variable                                                                        \n",
+       "n                               7007            3384                     6999   \n",
+       "ethnicity_10             0.02 (0.13)     0.02 (0.13)    0.0124    0.02 (0.13)   \n",
+       "ethnicity_11             0.02 (0.13)     0.02 (0.12)   -0.0117    0.02 (0.13)   \n",
+       "ethnicity_12             0.03 (0.18)     0.03 (0.17)   -0.0123    0.03 (0.18)   \n",
+       "ethnicity_13             0.02 (0.14)     0.01 (0.11)   -0.0492    0.02 (0.13)   \n",
+       "ethnicity_14             0.06 (0.24)     0.06 (0.24)   -0.0170    0.06 (0.25)   \n",
+       "ethnicity_15             0.03 (0.18)     0.03 (0.18)    0.0081    0.03 (0.18)   \n",
+       "ethnicity_2              0.15 (0.36)     0.15 (0.36)   -0.0011    0.15 (0.36)   \n",
+       "ethnicity_3              0.01 (0.11)     0.01 (0.10)   -0.0163    0.01 (0.11)   \n",
+       "ethnicity_4              0.48 (0.50)     0.50 (0.50)    0.0367    0.48 (0.50)   \n",
+       "ethnicity_5              0.04 (0.19)     0.04 (0.20)    0.0138    0.04 (0.19)   \n",
+       "ethnicity_6              0.00 (0.06)     0.01 (0.07)    0.0336    0.00 (0.06)   \n",
+       "ethnicity_7              0.00 (0.06)     0.01 (0.07)    0.0199    0.00 (0.06)   \n",
+       "ethnicity_8              0.02 (0.13)     0.02 (0.14)    0.0238    0.02 (0.13)   \n",
+       "ethnicity_9              0.01 (0.12)     0.01 (0.10)   -0.0316    0.01 (0.12)   \n",
+       "gender_2                 0.50 (0.50)     0.47 (0.50)   -0.0543    0.50 (0.50)   \n",
+       "school_achievement       0.04 (0.94)     0.09 (0.93)    0.0597    0.04 (0.94)   \n",
+       "school_ethnic_minority  -0.09 (0.97)    -0.09 (0.96)   -0.0048   -0.09 (0.97)   \n",
+       "school_mindset          -0.01 (0.97)    -0.10 (0.97)   -0.0984   -0.01 (0.97)   \n",
+       "school_poverty          -0.04 (0.97)    -0.06 (0.96)   -0.0249   -0.04 (0.97)   \n",
+       "school_size             -0.05 (1.00)     0.02 (1.02)    0.0729   -0.05 (1.00)   \n",
+       "school_urbanicity_1      0.24 (0.43)     0.23 (0.42)   -0.0288    0.24 (0.43)   \n",
+       "school_urbanicity_2      0.19 (0.39)     0.20 (0.40)    0.0350    0.19 (0.39)   \n",
+       "school_urbanicity_3      0.15 (0.36)     0.13 (0.34)   -0.0472    0.15 (0.36)   \n",
+       "school_urbanicity_4      0.34 (0.48)     0.36 (0.48)    0.0267    0.35 (0.48)   \n",
+       "\n",
+       "                       Treatment (post) SMD (post)  \n",
+       "Variable                                            \n",
+       "n                                  6999             \n",
+       "ethnicity_10                0.08 (0.28)    0.3132*  \n",
+       "ethnicity_11                0.00 (0.00)   -0.1852*  \n",
+       "ethnicity_12                0.00 (0.00)   -0.2571*  \n",
+       "ethnicity_13                0.00 (0.06)   -0.1465*  \n",
+       "ethnicity_14                0.00 (0.00)   -0.3702*  \n",
+       "ethnicity_15                0.07 (0.26)    0.1748*  \n",
+       "ethnicity_2                 0.18 (0.39)     0.0875  \n",
+       "ethnicity_3                 0.00 (0.00)   -0.1521*  \n",
+       "ethnicity_4                 0.52 (0.50)     0.0852  \n",
+       "ethnicity_5                 0.05 (0.21)     0.0352  \n",
+       "ethnicity_6                 0.00 (0.06)     0.0098  \n",
+       "ethnicity_7                 0.00 (0.00)    -0.0863  \n",
+       "ethnicity_8                 0.02 (0.15)     0.0458  \n",
+       "ethnicity_9                 0.06 (0.24)    0.2440*  \n",
+       "gender_2                    0.53 (0.50)     0.0646  \n",
+       "school_achievement          0.05 (1.00)     0.0132  \n",
+       "school_ethnic_minority     -0.14 (1.30)    -0.0445  \n",
+       "school_mindset              0.26 (0.65)    0.3264*  \n",
+       "school_poverty              0.12 (0.57)    0.1968*  \n",
+       "school_size                -0.19 (1.06)   -0.1365*  \n",
+       "school_urbanicity_1         0.06 (0.24)   -0.5145*  \n",
+       "school_urbanicity_2         0.05 (0.21)   -0.4412*  \n",
+       "school_urbanicity_3         0.24 (0.43)    0.2238*  \n",
+       "school_urbanicity_4         0.65 (0.48)    0.6475*  "
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from causalml.match import create_table_one\n",
+    "\n",
+    "table_pre_atc = create_table_one(\n",
+    "    data=df_match,\n",
+    "    treatment_col=\"intervention\",\n",
+    "    features=features_cov,\n",
+    "    with_std=True,\n",
+    "    with_counts=True\n",
+    ")\n",
+    "\n",
+    "table_post_atc = create_table_one(\n",
+    "    data=matched_atc,\n",
+    "    treatment_col=\"intervention\",\n",
+    "    features=features_cov,\n",
+    "    with_std=True,\n",
+    "    with_counts=True\n",
+    ")\n",
+    "\n",
+    "balance_atc = combine_table_one(table_pre_atc, table_post_atc, smd_star_thresh=0.1)\n",
+    "balance_atc"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "ATC 매칭은 caliper와 복원 여부에 따라 매칭률과 공변량 균형 사이에 trade-off가 있습니다. \n",
+    "- 조건이 엄격하면 공통지지 부족으로 매칭이 불가능하고, \n",
+    "- 조건을 완화하면 반복 사용과 먼 거리 매칭으로 SMD가 악화됩니다.\n",
+    "\n",
+    "따라서 처치군과 대조군의 표본 불균형이 큰 경우, 매칭만으로는 ATE 추정에 제약이 있습니다. 모집단 평균 효과를 안정적으로 추정하려면 IPW, AIPW 등 가중치 기반 방법이 더 적합합니다."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### ATE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ATE: 0.403\n"
+     ]
+    }
+   ],
+   "source": [
+    "p_t = float(df[\"intervention\"].mean())\n",
+    "ATE = ATT * p_t + ATC * (1 - p_t)\n",
+    "print(\"ATE:\", round(ATE, 4))"
    ]
   },
   {
@@ -33,7 +1173,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -47,7 +1187,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.12.11"
   }
  },
  "nbformat": 4,