diff --git a/docs/notebooks/rd_pymc_drinking.ipynb b/docs/notebooks/rd_pymc_drinking.ipynb
index 3350b90d..5758531c 100644
--- a/docs/notebooks/rd_pymc_drinking.ipynb
+++ b/docs/notebooks/rd_pymc_drinking.ipynb
@@ -1,417 +1,817 @@
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-    "cells": [
-        {
-            "cell_type": "markdown",
-            "metadata": {},
-            "source": [
-                "# Drinking age - Bayesian analysis\n",
-                "\n",
-                "Run the 'drinking example' from the RDD chapter of [Causal Inference for the Brave and True](https://matheusfacure.github.io/python-causality-handbook/16-Regression-Discontinuity-Design.html).\n",
-                "\n",
-                "Use `pymc` models"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 1,
-            "metadata": {},
-            "outputs": [],
-            "source": [
-                "import arviz as az\n",
-                "import pandas as pd\n",
-                "import pathlib"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 2,
-            "metadata": {},
-            "outputs": [],
-            "source": [
-                "# %config InlineBackend.figure_format = 'svg'\n",
-                "az.style.use(\"arviz-darkgrid\")"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 3,
-            "metadata": {},
-            "outputs": [],
-            "source": [
-                "%load_ext autoreload\n",
-                "%autoreload 2"
-            ]
-        },
-        {
-            "cell_type": "markdown",
-            "metadata": {},
-            "source": [
-                "## Load data"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 4,
-            "metadata": {},
-            "outputs": [],
-            "source": [
-                "rd_data_path = pathlib.Path.cwd().parents[1] / \"causalpy\" / \"data\" / \"drinking.csv\"\n",
-                "df = (\n",
-                "    pd.read_csv(rd_data_path)[[\"agecell\", \"all\", \"mva\", \"suicide\"]]\n",
-                "    .rename(columns={\"agecell\": \"age\"})\n",
-                "    .assign(treated=lambda df_: df_.age > 21)\n",
-                "    .dropna(axis=0)\n",
-                ")"
-            ]
-        },
-        {
-            "cell_type": "markdown",
-            "metadata": {},
-            "source": [
-                "## Run the analysis"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 5,
-            "metadata": {},
-            "outputs": [
-                {
-                    "name": "stderr",
-                    "output_type": "stream",
-                    "text": [
-                        "Auto-assigning NUTS sampler...\n",
-                        "Initializing NUTS using jitter+adapt_diag...\n",
-                        "Multiprocess sampling (4 chains in 4 jobs)\n",
-                        "NUTS: [beta, sigma]\n"
-                    ]
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-                            "\n",
-                            "    <div>\n",
-                            "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-                            "      100.00% [8000/8000 00:16&lt;00:00 Sampling 4 chains, 9 divergences]\n",
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-                        ],
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-                    "name": "stderr",
-                    "output_type": "stream",
-                    "text": [
-                        "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 17 seconds.\n",
-                        "Sampling: [beta, sigma, y_hat]\n",
-                        "Sampling: [y_hat]\n"
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-                    "name": "stderr",
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-                    "text": [
-                        "Sampling: [y_hat]\n"
-                    ]
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-                {
-                    "name": "stderr",
-                    "output_type": "stream",
-                    "text": [
-                        "Sampling: [y_hat]\n"
-                    ]
-                },
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-                    "data": {
-                        "text/html": [
-                            "\n",
-                            "<style>\n",
-                            "    /* Turns off some styling */\n",
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-                            "        border: none;\n",
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-                        ]
-                    },
-                    "metadata": {},
-                    "output_type": "display_data"
-                },
-                {
-                    "name": "stderr",
-                    "output_type": "stream",
-                    "text": [
-                        "Sampling: [y_hat]\n"
-                    ]
-                },
-                {
-                    "data": {
-                        "text/html": [
-                            "\n",
-                            "<style>\n",
-                            "    /* Turns off some styling */\n",
-                            "    progress {\n",
-                            "        /* gets rid of default border in Firefox and Opera. */\n",
-                            "        border: none;\n",
-                            "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-                            "        background-size: auto;\n",
-                            "    }\n",
-                            "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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-                        ],
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-                    },
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-                },
-                {
-                    "data": {
-                        "text/html": [
-                            "\n",
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-                        ]
-                    },
-                    "metadata": {},
-                    "output_type": "display_data"
-                }
-            ],
-            "source": [
-                "from causalpy.pymc_experiments import RegressionDiscontinuity\n",
-                "from causalpy.pymc_models import LinearRegression\n",
-                "\n",
-                "result = RegressionDiscontinuity(\n",
-                "    df,\n",
-                "    formula=\"all ~ 1 + age + treated + age:treated\",\n",
-                "    running_variable_name=\"age\",\n",
-                "    outcome_variable_name=\"all\",\n",
-                "    prediction_model=LinearRegression(),\n",
-                "    treatment_threshold=21,\n",
-                ")"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": 6,
-            "metadata": {},
-            "outputs": [
-                {
-                    "name": "stderr",
-                    "output_type": "stream",
-                    "text": [
-                        "/Users/benjamv/opt/mambaforge/envs/CausalPy/lib/python3.10/site-packages/arviz/plots/hdiplot.py:156: FutureWarning: hdi currently interprets 2d data as (draw, shape) but this will change in a future release to (chain, draw) for coherence with other functions\n",
-                        "  hdi_data = hdi(y, hdi_prob=hdi_prob, circular=circular, multimodal=False, **hdi_kwargs)\n"
-                    ]
-                },
-                {
-                    "data": {
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",
-                        "text/plain": [
-                            "<Figure size 720x480 with 1 Axes>"
-                        ]
-                    },
-                    "metadata": {},
-                    "output_type": "display_data"
-                }
-            ],
-            "source": [
-                "fig, ax = result.plot()"
-            ]
-        },
-        {
-            "cell_type": "code",
-            "execution_count": null,
-            "metadata": {},
-            "outputs": [],
-            "source": []
-        }
-    ],
-    "metadata": {
-        "kernelspec": {
-            "display_name": "Python 3.10.6 ('CausalPy')",
-            "language": "python",
-            "name": "python3"
-        },
-        "language_info": {
-            "codemirror_mode": {
-                "name": "ipython",
-                "version": 3
-            },
-            "file_extension": ".py",
-            "mimetype": "text/x-python",
-            "name": "python",
-            "nbconvert_exporter": "python",
-            "pygments_lexer": "ipython3",
-            "version": "3.10.6"
-        },
-        "orig_nbformat": 4,
-        "vscode": {
-            "interpreter": {
-                "hash": "02f5385db19eab57520277c5168790c7855381ee953bdbb5c89c321e1f17586e"
-            }
-        }
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Drinking age - Bayesian analysis\n",
+    "\n",
+    "This example uses the regression discontinuity design to make claims about the causal effects of the minimum legal drinking age (21 in the USA) upon all cause mortality rates. The dataset is from a study by [Carpenter & Dobkin, (2009)](https://www.aeaweb.org/articles?id=10.1257/app.1.1.164)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for use when developing the code\n",
+    "# %load_ext autoreload\n",
+    "# %autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plot formatting\n",
+    "import arviz as az\n",
+    "\n",
+    "# %config InlineBackend.figure_format = 'svg'\n",
+    "az.style.use(\"arviz-darkgrid\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load and process data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import pathlib\n",
+    "\n",
+    "rd_data_path = pathlib.Path.cwd().parents[1] / \"causalpy\" / \"data\" / \"drinking.csv\"\n",
+    "df = (\n",
+    "    pd.read_csv(rd_data_path)[[\"agecell\", \"all\", \"mva\", \"suicide\"]]\n",
+    "    .rename(columns={\"agecell\": \"age\"})\n",
+    "    .assign(treated=lambda df_: df_.age > 21)\n",
+    "    .dropna(axis=0)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Main effects model\n",
+    "\n",
+    "First we will examine a simple 'main effects' model. Here, the expected death rate (in units of deaths/1000 people/year) for a given age $a$ (with monthly resolution), is modelled with an intercept term $\\beta_0$, a treatment effect $\\beta_1$ and an effect of age $\\beta_2$.\n",
+    "\n",
+    "$$\n",
+    "\\mu(a) = \\beta_0 + \\beta_1 t(a) + \\beta_2  a\n",
+    "$$\n",
+    "\n",
+    "The term $t(a)$ describes whether 'treatment' has been applied. In this example it simply describes whether a give age $a$ is over the minimum legal drinking age of 21:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "t(a) = \n",
+    "    \\begin{cases} \n",
+    "        1 & \\text{if $a \\ge 21$} \\\\\n",
+    "        0 & \\text{if $a < 21$} \n",
+    "    \\end{cases}\n",
+    "\\end{align}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [beta, sigma]\n"
+     ]
     },
-    "nbformat": 4,
-    "nbformat_minor": 2
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:09&lt;00:00 Sampling 4 chains, 11 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 10 seconds.\n",
+      "Sampling: [beta, sigma, y_hat]\n",
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from causalpy.pymc_experiments import RegressionDiscontinuity\n",
+    "from causalpy.pymc_models import LinearRegression\n",
+    "\n",
+    "result = RegressionDiscontinuity(\n",
+    "    df,\n",
+    "    formula=\"all ~ 1 + age + treated\",\n",
+    "    running_variable_name=\"age\",\n",
+    "    outcome_variable_name=\"all\",\n",
+    "    prediction_model=LinearRegression(),\n",
+    "    treatment_threshold=21,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/benjamv/mambaforge/envs/CausalPy/lib/python3.10/site-packages/arviz/plots/hdiplot.py:156: FutureWarning: hdi currently interprets 2d data as (draw, shape) but this will change in a future release to (chain, draw) for coherence with other functions\n",
+      "  hdi_data = hdi(y, hdi_prob=hdi_prob, circular=circular, multimodal=False, **hdi_kwargs)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = result.plot();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this main effects model, the size of the causal effect is equal to our posterior estimate of $\\beta_1$. Let's plot the parameter estimates (left) and zoom in on the posterior distribution for the main effect of treatment (right)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
+    "\n",
+    "az.plot_forest(result.prediction_model.idata.posterior, var_names=\"beta\", ax=ax[0])\n",
+    "az.plot_posterior(\n",
+    "    result.prediction_model.idata.posterior.beta.sel(coeffs=\"treated[T.True]\"),\n",
+    "    round_to=3,\n",
+    "    ax=ax[1],\n",
+    ")\n",
+    "\n",
+    "ax[1].set(title=\"treated[T.True]\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see that this matches up (nearly exactly) with the \"discontinuity at threshold\" figures in the first results figure.\n",
+    "\n",
+    "It is not exactly the same because we actually manually calculate the discontinuity at threshold. The reason for this is because in anything but the simplest model, the discontinuity at threshold is not simply equal to this parameter. In order to understand this, let's look at the marginally more complex model where we incorporate an interaction term."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Interaction model\n",
+    "\n",
+    "We add an interaction term by changing our formula to `all ~ 1 + age + treated + age:treated`. This now changes the statistical model to :\n",
+    "\n",
+    "$$\n",
+    "\\mu(a) = \\beta_0 + \\beta_1 t(a) + \\beta_2  a + \\beta_3 t(a) \\cdot a\n",
+    "$$\n",
+    "\n",
+    "This model is now more complex in that it can _allow_ for the trend in mortality rate to vary before versus after the age of 21 _if the data suggest it_. If it is not clear already, it will be clear from the next results figure that the discrepancy at threshold is no longer equal to the $\\beta_1$ coefficient. Let's run the model and see."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [beta, sigma]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:15&lt;00:00 Sampling 4 chains, 1 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 16 seconds.\n",
+      "Sampling: [beta, sigma, y_hat]\n",
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
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+       "    progress {\n",
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+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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+       "    }\n",
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+      ]
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+     "data": {
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+       "\n",
+       "    <div>\n",
+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
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+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling: [y_hat]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
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+       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [4000/4000 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "result2 = RegressionDiscontinuity(\n",
+    "    df,\n",
+    "    formula=\"all ~ 1 + age + treated + age:treated\",\n",
+    "    running_variable_name=\"age\",\n",
+    "    outcome_variable_name=\"all\",\n",
+    "    prediction_model=LinearRegression(),\n",
+    "    treatment_threshold=21,\n",
+    ")\n",
+    "\n",
+    "fig, ax = result2.plot();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now see that by adding an interaction term, the parameter estimates are now much changed, and the estimated discontinuity at threshold is no longer simply given by the $\\beta_1$ parameter. To confirm this, we can check the estimate of $\\beta_1$ (which corresponds to the `treated[T.True]` coefficient)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "az.plot_forest(\n",
+    "    result2.prediction_model.idata.posterior, var_names=\"beta\", figsize=(10, 3)\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see that this estimate is now wildly off the desired \"discontinuity at threshold\" value. It is for this reason that `CausalPy` manually calculates the \"discontinuity at threshold\" by evaluating the difference in predicted outcome values slightly above versus slightly below the treatment threshold."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.6 ('CausalPy')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "46d31859cc45aa26a1223a391e7cf3023d69984b498bed11e66c690302b7e251"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
 }