AustinRochford · November 23, 2025 21:45
diff --git a/mrp2.ipynb b/mrp2.ipynb
 {
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ca4581d4-c4cc-45fe-893c-556611fee0d8",
   "metadata": {},
   "source": [
    "A little over eight years ago, I published a [post](https://austinrochford.com/posts/2017-07-09-mrpymc3.html) entitled _MRPyMC3 - Multilevel Regression and Poststratification with PyMC3_, showing how to perform [multilevel regression with poststratification](https://en.wikipedia.org/wiki/Multilevel_regression_with_poststratification) (MRP) in Python with PyMC. I periodically enjoy [revisiting](https://austinrochford.com/posts/revisit-survival-pymc.html) old posts after both technology and my understanding of the problem advances.  This post revisits MRP with a few notable changes:\n",
    "\n",
    "* [PyMC](http://pymc.io/) is now on major version 5 instead of version 3,\n",
    "* we use [nutpie](https://pymc-devs.github.io/nutpie/) for sampling from the model instead of PyMC's built in sampler, and\n",
    "* we use [Polars](http://pymc.io/) instead of [pandas](https://pandas.pydata.org/).\n",
    "\n",
    "We will not repeat the previous post's full exposition of MRP and will rather focus on the mechanics of its implementation.\n",
    "\n",
    "First we import the necessary packages and do a bit of light configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "edcdf70a-c255-4be0-b937-bce507e14487",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = \"retina\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5bb22b68-0a11-4759-8534-f2aed0cc0dcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import zip_longest\n",
    "import os\n",
    "from urllib import request\n",
    "import us\n",
    "from zipfile import ZipFile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1fb32e07-91f8-4391-a09c-b49cc349900e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import arviz as az\n",
    "from matplotlib import cm, pyplot as plt, ticker\n",
    "from matplotlib.colorbar import ColorbarBase\n",
    "from matplotlib.colors import Normalize\n",
    "import numpy as np\n",
    "import nutpie\n",
    "import polars as pl\n",
    "import pymc as pm\n",
    "from pyreadstat import read_dta\n",
    "from pytensor import tensor as pt\n",
    "import seaborn as sns\n",
    "from seaborn import objects as so\n",
    "from scipy.special import logit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8c061dbe-097c-4f1a-a6d7-b76c24d545c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"darkgrid\", {\"axes.linewidth\": 1, \"axes.edgecolor\": \"black\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b5e21b-6c6f-416a-b222-935bb3e1f033",
   "metadata": {},
   "source": [
    "## Load and transform the data\n",
    "\n",
    "As in the previous post, we follow [Jonathan Kastellec](https://jkastellec.scholar.princeton.edu/)'s excellent [MRP Primer](https://jkastellec.scholar.princeton.edu/publications/mrp_primer), which focuses on estimating state-level opinions of gay marriage in 2005/2006 from polling data.\n",
    "\n",
    "First we download and decompress the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4ea540e1-ab76-430c-8a9a-788ad6edd517",
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_PATH = \"./data\"\n",
    "DATA_URI = \"https://jkastellec.scholar.princeton.edu/sites/g/files/toruqf3871/files/jkastellec/files/mrp_primer_replication_files.zip\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "67c2f68e-be22-46ab-bd3c-8a82e1aa45d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "USER_AGENT = \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "21facc6d-c899-464f-8c3c-d1204c4f8aeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.isdir(DATA_PATH):\n",
    "    os.mkdir(DATA_PATH)\n",
    "\n",
    "dest_path = os.path.join(DATA_PATH, os.path.basename(DATA_URI))\n",
    "\n",
    "if not os.path.exists(dest_path):\n",
    "    opener = request.build_opener()\n",
    "    opener.addheaders = [(\"User-agent\", USER_AGENT)]\n",
    "    request.install_opener(opener)\n",
    "    request.urlretrieve(DATA_URI, dest_path)\n",
    "\n",
    "    with ZipFile(dest_path) as src:\n",
    "        src.extractall(DATA_PATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d3a2887-7e29-4bf6-bbf6-54690aa5af28",
   "metadata": {},
   "source": [
    "### Poll data\n",
    "\n",
    "Next we load and do some light feature engineering on the polling data necessary to build the multilevel model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c94c9aba-cfc9-49d1-8419-ffd1b3ac0ae8",
   "metadata": {},
   "outputs": [],
   "source": [
    "UNZIPPED_DIR = \"MRP_Primer_Replication_Files\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d68ae868-6eba-4ae3-b911-826f21813ef0",
   "metadata": {},
   "outputs": [],
   "source": [
    "POLL_PATH = os.path.join(DATA_PATH, UNZIPPED_DIR, \"gay_marriage_megapoll.dta\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fc65705e-7437-4343-8011-51ad97696821",
   "metadata": {},
   "outputs": [],
   "source": [
    "POLL_COLS = [\n",
    "    \"race_wbh\",\n",
    "    \"age_cat\",\n",
    "    \"edu_cat\",\n",
    "    \"female\",\n",
    "    \"region\",\n",
    "    \"state\",\n",
    "    \"poll\",\n",
    "    \"yes_of_all\",\n",
    "]\n",
    "\n",
    "NN_COLS = [\"race_wbh\", \"age_cat\", \"edu_cat\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f8c9dbfc-80e3-4fa7-9e74-16b72ca90864",
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_zero_indexed(name):\n",
    "    col = pl.col(name)\n",
    "\n",
    "    return col - col.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a67ad88d-a553-46f5-8135-89fa8ab8eae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "CAT_COLS = [\"age_cat\", \"edu_cat\", \"race_wbh\"]\n",
    "\n",
    "cat_col_transforms = [to_zero_indexed(name) for name in CAT_COLS]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78f1d8ef-640e-4a9b-b25e-a0ec11a21b54",
   "metadata": {},
   "outputs": [],
   "source": [
    "GENDER = pl.Enum([\"Male\", \"Female\"])\n",
    "POLL = pl.Enum(\n",
    "    [\n",
    "        \"ABC 2004Jan15\",\n",
    "        \"Gall2004Mar05\",\n",
    "        \"Gall2005Aug22\",\n",
    "        \"Pew 2004Dec01\",\n",
    "        \"Pew 2004Feb11\",\n",
    "    ]\n",
    ")\n",
    "RACE = pl.Enum([\"White\", \"Black\", \"Hispanic\"])\n",
    "REGION = pl.Enum([\"dc\", \"midwest\", \"northeast\", \"south\", \"west\"])\n",
    "STATE = pl.Enum(sorted([state.abbr for state in us.states.STATES] + [\"DC\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c61728c1-9761-4519-ae76-02791fffbe53",
   "metadata": {},
   "outputs": [],
   "source": [
    "ENUM_CASTS = {\n",
    "    \"female\": (GENDER, \"gender\"),\n",
    "    \"poll\": (POLL, None),\n",
    "    \"race_wbh\": (RACE, \"race\"),\n",
    "    \"region\": (REGION, None),\n",
    "    \"state\": (STATE, None),\n",
    "}\n",
    "\n",
    "\n",
    "def cast_enum_cols(df):\n",
    "    for name, (enum, new_name) in ENUM_CASTS.items():\n",
    "        if name in df.columns:\n",
    "            df = df.with_columns(pl.col(name).cast(enum).alias(new_name or name))\n",
    "\n",
    "            if new_name is not None:\n",
    "                df = df.drop(name)\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "877e89c1-f101-43c2-be00-1888c42d6b99",
   "metadata": {},
   "outputs": [],
   "source": [
    "poll_df = (\n",
    "    pl.from_pandas(read_dta(POLL_PATH)[0])\n",
    "    .select(POLL_COLS)\n",
    "    .drop_nulls(NN_COLS)\n",
    "    .with_columns(*cat_col_transforms)\n",
    "    .group_by(POLL_COLS[:-1])\n",
    "    .agg(pl.sum(\"yes_of_all\"), poll_pop=pl.len().cast(pl.Int32))\n",
    "    .filter(pl.col(\"state\") != \"\")\n",
    "    .pipe(cast_enum_cols)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e4366cd6-e8b6-4094-84f1-d57b54fa02b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (3_693, 9)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>age_cat</th><th>edu_cat</th><th>region</th><th>state</th><th>poll</th><th>yes_of_all</th><th>poll_pop</th><th>gender</th><th>race</th></tr><tr><td>i64</td><td>i64</td><td>enum</td><td>enum</td><td>enum</td><td>i64</td><td>i32</td><td>enum</td><td>enum</td></tr></thead><tbody><tr><td>1</td><td>1</td><td>&quot;south&quot;</td><td>&quot;DE&quot;</td><td>&quot;Gall2005Aug22&quot;</td><td>0</td><td>1</td><td>&quot;Male&quot;</td><td>&quot;Black&quot;</td></tr><tr><td>3</td><td>3</td><td>&quot;south&quot;</td><td>&quot;FL&quot;</td><td>&quot;Pew&nbsp;2004Dec01&quot;</td><td>3</td><td>5</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>0</td><td>3</td><td>&quot;south&quot;</td><td>&quot;VA&quot;</td><td>&quot;Pew&nbsp;2004Feb11&quot;</td><td>1</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;White&quot;</td></tr><tr><td>0</td><td>1</td><td>&quot;midwest&quot;</td><td>&quot;OH&quot;</td><td>&quot;Gall2004Mar05&quot;</td><td>0</td><td>1</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>3</td><td>1</td><td>&quot;south&quot;</td><td>&quot;TN&quot;</td><td>&quot;ABC&nbsp;2004Jan15&quot;</td><td>0</td><td>1</td><td>&quot;Male&quot;</td><td>&quot;Black&quot;</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>3</td><td>1</td><td>&quot;west&quot;</td><td>&quot;CA&quot;</td><td>&quot;Pew&nbsp;2004Feb11&quot;</td><td>0</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;Black&quot;</td></tr><tr><td>1</td><td>3</td><td>&quot;midwest&quot;</td><td>&quot;IA&quot;</td><td>&quot;ABC&nbsp;2004Jan15&quot;</td><td>1</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;White&quot;</td></tr><tr><td>0</td><td>3</td><td>&quot;south&quot;</td><td>&quot;TN&quot;</td><td>&quot;Pew&nbsp;2004Feb11&quot;</td><td>1</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;White&quot;</td></tr><tr><td>0</td><td>2</td><td>&quot;northeast&quot;</td><td>&quot;NY&quot;</td><td>&quot;Gall2004Mar05&quot;</td><td>0</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;White&quot;</td></tr><tr><td>3</td><td>1</td><td>&quot;midwest&quot;</td><td>&quot;WI&quot;</td><td>&quot;Gall2005Aug22&quot;</td><td>0</td><td>1</td><td>&quot;Female&quot;</td><td>&quot;White&quot;</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (3_693, 9)\n",
       "┌─────────┬─────────┬───────────┬───────┬───┬────────────┬──────────┬────────┬───────┐\n",
       "│ age_cat ┆ edu_cat ┆ region    ┆ state ┆ … ┆ yes_of_all ┆ poll_pop ┆ gender ┆ race  │\n",
       "│ ---     ┆ ---     ┆ ---       ┆ ---   ┆   ┆ ---        ┆ ---      ┆ ---    ┆ ---   │\n",
       "│ i64     ┆ i64     ┆ enum      ┆ enum  ┆   ┆ i64        ┆ i32      ┆ enum   ┆ enum  │\n",
       "╞═════════╪═════════╪═══════════╪═══════╪═══╪════════════╪══════════╪════════╪═══════╡\n",
       "│ 1       ┆ 1       ┆ south     ┆ DE    ┆ … ┆ 0          ┆ 1        ┆ Male   ┆ Black │\n",
       "│ 3       ┆ 3       ┆ south     ┆ FL    ┆ … ┆ 3          ┆ 5        ┆ Male   ┆ White │\n",
       "│ 0       ┆ 3       ┆ south     ┆ VA    ┆ … ┆ 1          ┆ 1        ┆ Female ┆ White │\n",
       "│ 0       ┆ 1       ┆ midwest   ┆ OH    ┆ … ┆ 0          ┆ 1        ┆ Male   ┆ White │\n",
       "│ 3       ┆ 1       ┆ south     ┆ TN    ┆ … ┆ 0          ┆ 1        ┆ Male   ┆ Black │\n",
       "│ …       ┆ …       ┆ …         ┆ …     ┆ … ┆ …          ┆ …        ┆ …      ┆ …     │\n",
       "│ 3       ┆ 1       ┆ west      ┆ CA    ┆ … ┆ 0          ┆ 1        ┆ Female ┆ Black │\n",
       "│ 1       ┆ 3       ┆ midwest   ┆ IA    ┆ … ┆ 1          ┆ 1        ┆ Female ┆ White │\n",
       "│ 0       ┆ 3       ┆ south     ┆ TN    ┆ … ┆ 1          ┆ 1        ┆ Female ┆ White │\n",
       "│ 0       ┆ 2       ┆ northeast ┆ NY    ┆ … ┆ 0          ┆ 1        ┆ Female ┆ White │\n",
       "│ 3       ┆ 1       ┆ midwest   ┆ WI    ┆ … ┆ 0          ┆ 1        ┆ Female ┆ White │\n",
       "└─────────┴─────────┴───────────┴───────┴───┴────────────┴──────────┴────────┴───────┘"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poll_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8ed605b-fda2-47ca-b648-ca3316dffe08",
   "metadata": {},
   "source": [
    "Each row represents a group of people polled:\n",
    "\n",
    "* `age_cat` represents the age category of that group,\n",
    "* `edu_cat` represents the education category of that group,\n",
    "* `region` represents the region of the state in which that group resides,\n",
    "* `state` represents the state in which that group resides,\n",
    "* `poll` represents which poll surveyed that group,\n",
    "* `yes_of_all` represents the number of respondents that indicated support for gay marriage,\n",
    "* `poll_pop` represents the number of respondents,\n",
    "* `gender` represents the gender of that group, and\n",
    "* `race` represents the race of that group."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05fc463d-ae4f-4ede-ae9e-7b9d6477192a",
   "metadata": {},
   "source": [
    "### Census data\n",
    "\n",
    "Next we load and do some light feature engineering on the census data necessary for postratification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "80ab3330-79c0-41ca-b2fc-94fb6474f587",
   "metadata": {},
   "outputs": [],
   "source": [
    "CENSUS_PATH = os.path.join(DATA_PATH, UNZIPPED_DIR, \"poststratification 2000.dta\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "76f5e41f-612e-41e6-9d98-a587a9e621b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "CENSUS_COLS = [\n",
    "    \"race_wbh\",\n",
    "    \"age_cat\",\n",
    "    \"edu_cat\",\n",
    "    \"female\",\n",
    "    \"state\",\n",
    "    \"_freq\",\n",
    "    \"region\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "198c458f-f0e1-444d-91b7-1c569bc7e545",
   "metadata": {},
   "outputs": [],
   "source": [
    "census_df = (\n",
    "    pl.from_pandas(read_dta(CENSUS_PATH)[0])\n",
    "    .rename(lambda s: s.lstrip(\"c\").lower())\n",
    "    .select(CENSUS_COLS)\n",
    "    .rename({\"_freq\": \"pop\"})\n",
    "    .with_columns(*cat_col_transforms)\n",
    "    .pipe(cast_enum_cols)\n",
    "    .sort(\"state\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1a25585d-9c40-40ee-8d6f-47334bc359fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (4_896, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>age_cat</th><th>edu_cat</th><th>state</th><th>pop</th><th>region</th><th>gender</th><th>race</th></tr><tr><td>i64</td><td>i64</td><td>enum</td><td>i64</td><td>enum</td><td>enum</td><td>enum</td></tr></thead><tbody><tr><td>0</td><td>0</td><td>&quot;AK&quot;</td><td>467</td><td>&quot;west&quot;</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>1</td><td>0</td><td>&quot;AK&quot;</td><td>377</td><td>&quot;west&quot;</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>2</td><td>0</td><td>&quot;AK&quot;</td><td>419</td><td>&quot;west&quot;</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>3</td><td>0</td><td>&quot;AK&quot;</td><td>343</td><td>&quot;west&quot;</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>0</td><td>1</td><td>&quot;AK&quot;</td><td>958</td><td>&quot;west&quot;</td><td>&quot;Male&quot;</td><td>&quot;White&quot;</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>3</td><td>2</td><td>&quot;WY&quot;</td><td>4</td><td>&quot;west&quot;</td><td>&quot;Female&quot;</td><td>&quot;Hispanic&quot;</td></tr><tr><td>0</td><td>3</td><td>&quot;WY&quot;</td><td>8</td><td>&quot;west&quot;</td><td>&quot;Female&quot;</td><td>&quot;Hispanic&quot;</td></tr><tr><td>1</td><td>3</td><td>&quot;WY&quot;</td><td>16</td><td>&quot;west&quot;</td><td>&quot;Female&quot;</td><td>&quot;Hispanic&quot;</td></tr><tr><td>2</td><td>3</td><td>&quot;WY&quot;</td><td>10</td><td>&quot;west&quot;</td><td>&quot;Female&quot;</td><td>&quot;Hispanic&quot;</td></tr><tr><td>3</td><td>3</td><td>&quot;WY&quot;</td><td>1</td><td>&quot;west&quot;</td><td>&quot;Female&quot;</td><td>&quot;Hispanic&quot;</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (4_896, 7)\n",
       "┌─────────┬─────────┬───────┬─────┬────────┬────────┬──────────┐\n",
       "│ age_cat ┆ edu_cat ┆ state ┆ pop ┆ region ┆ gender ┆ race     │\n",
       "│ ---     ┆ ---     ┆ ---   ┆ --- ┆ ---    ┆ ---    ┆ ---      │\n",
       "│ i64     ┆ i64     ┆ enum  ┆ i64 ┆ enum   ┆ enum   ┆ enum     │\n",
       "╞═════════╪═════════╪═══════╪═════╪════════╪════════╪══════════╡\n",
       "│ 0       ┆ 0       ┆ AK    ┆ 467 ┆ west   ┆ Male   ┆ White    │\n",
       "│ 1       ┆ 0       ┆ AK    ┆ 377 ┆ west   ┆ Male   ┆ White    │\n",
       "│ 2       ┆ 0       ┆ AK    ┆ 419 ┆ west   ┆ Male   ┆ White    │\n",
       "│ 3       ┆ 0       ┆ AK    ┆ 343 ┆ west   ┆ Male   ┆ White    │\n",
       "│ 0       ┆ 1       ┆ AK    ┆ 958 ┆ west   ┆ Male   ┆ White    │\n",
       "│ …       ┆ …       ┆ …     ┆ …   ┆ …      ┆ …      ┆ …        │\n",
       "│ 3       ┆ 2       ┆ WY    ┆ 4   ┆ west   ┆ Female ┆ Hispanic │\n",
       "│ 0       ┆ 3       ┆ WY    ┆ 8   ┆ west   ┆ Female ┆ Hispanic │\n",
       "│ 1       ┆ 3       ┆ WY    ┆ 16  ┆ west   ┆ Female ┆ Hispanic │\n",
       "│ 2       ┆ 3       ┆ WY    ┆ 10  ┆ west   ┆ Female ┆ Hispanic │\n",
       "│ 3       ┆ 3       ┆ WY    ┆ 1   ┆ west   ┆ Female ┆ Hispanic │\n",
       "└─────────┴─────────┴───────┴─────┴────────┴────────┴──────────┘"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "282b4ad1-91a8-4b42-b583-a8b5a2e3d848",
   "metadata": {},
   "source": [
    "Each row represents a group of people with the given age, education, state, gender, and race combination.  All columns have the same meaning as in the poll data.  The `pop` column contains the census population of that group."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0469f894-dc55-4947-a624-5c8f3b46c837",
   "metadata": {},
   "source": [
    "### State data\n",
    "\n",
    "Finally, we load and do some light feature engineering on data about each state, which we will use, in addition to the poll data, to build our multilevel model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "469b443f-647a-4827-a8a6-b453479494f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "STATE_PATH = os.path.join(DATA_PATH, UNZIPPED_DIR, \"state_level_update.dta\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "277fa268-ac88-4e46-9c34-ece7c843d52d",
   "metadata": {},
   "outputs": [],
   "source": [
    "STATE_COLS = [\"sstate\", \"p_evang\", \"p_mormon\", \"kerry_04\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "649d6401-30f4-4878-a918-29dbbf99a921",
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_percentage(name):\n",
    "    return pl.col(name) / 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5653de9d-290c-4339-919c-2913e7d83ece",
   "metadata": {},
   "outputs": [],
   "source": [
    "state_df = (\n",
    "    pl.from_pandas(read_dta(STATE_PATH)[0])\n",
    "    .select(STATE_COLS)\n",
    "    .rename(lambda name: name.replace(\"ss\", \"s\"))\n",
    "    .with_columns(\n",
    "        to_percentage(\"p_evang\"), to_percentage(\"p_mormon\"), to_percentage(\"kerry_04\")\n",
    "    )\n",
    "    .with_columns(p_relig=pl.col(\"p_evang\") + pl.col(\"p_mormon\"))\n",
    "    .drop(\"p_evang\", \"p_mormon\")\n",
    "    .pipe(cast_enum_cols)\n",
    "    .join(census_df.group_by(\"state\").agg(pl.first(\"region\")), on=\"state\")\n",
    "    .sort(\"state\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "69d036a4-e726-4d69-b1a6-12025146f7c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (51, 4)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>state</th><th>kerry_04</th><th>p_relig</th><th>region</th></tr><tr><td>enum</td><td>f64</td><td>f64</td><td>enum</td></tr></thead><tbody><tr><td>&quot;AK&quot;</td><td>0.355</td><td>0.154431</td><td>&quot;west&quot;</td></tr><tr><td>&quot;AL&quot;</td><td>0.368</td><td>0.410083</td><td>&quot;south&quot;</td></tr><tr><td>&quot;AR&quot;</td><td>0.446</td><td>0.436301</td><td>&quot;south&quot;</td></tr><tr><td>&quot;AZ&quot;</td><td>0.444</td><td>0.142887</td><td>&quot;west&quot;</td></tr><tr><td>&quot;CA&quot;</td><td>0.543</td><td>0.087176</td><td>&quot;west&quot;</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>&quot;VT&quot;</td><td>0.589</td><td>0.02912</td><td>&quot;northeast&quot;</td></tr><tr><td>&quot;WA&quot;</td><td>0.528</td><td>0.128227</td><td>&quot;west&quot;</td></tr><tr><td>&quot;WI&quot;</td><td>0.497</td><td>0.129527</td><td>&quot;midwest&quot;</td></tr><tr><td>&quot;WV&quot;</td><td>0.432</td><td>0.116178</td><td>&quot;south&quot;</td></tr><tr><td>&quot;WY&quot;</td><td>0.291</td><td>0.208844</td><td>&quot;west&quot;</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (51, 4)\n",
       "┌───────┬──────────┬──────────┬───────────┐\n",
       "│ state ┆ kerry_04 ┆ p_relig  ┆ region    │\n",
       "│ ---   ┆ ---      ┆ ---      ┆ ---       │\n",
       "│ enum  ┆ f64      ┆ f64      ┆ enum      │\n",
       "╞═══════╪══════════╪══════════╪═══════════╡\n",
       "│ AK    ┆ 0.355    ┆ 0.154431 ┆ west      │\n",
       "│ AL    ┆ 0.368    ┆ 0.410083 ┆ south     │\n",
       "│ AR    ┆ 0.446    ┆ 0.436301 ┆ south     │\n",
       "│ AZ    ┆ 0.444    ┆ 0.142887 ┆ west      │\n",
       "│ CA    ┆ 0.543    ┆ 0.087176 ┆ west      │\n",
       "│ …     ┆ …        ┆ …        ┆ …         │\n",
       "│ VT    ┆ 0.589    ┆ 0.02912  ┆ northeast │\n",
       "│ WA    ┆ 0.528    ┆ 0.128227 ┆ west      │\n",
       "│ WI    ┆ 0.497    ┆ 0.129527 ┆ midwest   │\n",
       "│ WV    ┆ 0.432    ┆ 0.116178 ┆ south     │\n",
       "│ WY    ┆ 0.291    ┆ 0.208844 ┆ west      │\n",
       "└───────┴──────────┴──────────┴───────────┘"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d2cc64f-3ed2-4ac1-a46d-ba220487f635",
   "metadata": {},
   "source": [
    "There is a row for each state, plus an additional one for the District of Columbia, with the following columns:\n",
    "* `state` - the state represented by that row,\n",
    "* `kerry_04` - the proportion of the state's voters that voted for John Kerry in the 2004 presidential election,\n",
    "* `p_relig` - the proportion of the state's population that identifies as evangelical Christian or Mormon, and\n",
    "* `region` - the region of the country the state is in."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4314c9d-620f-4f75-8522-8bfe426bd71a",
   "metadata": {},
   "source": [
    "## Exploratory data analysis\n",
    "\n",
    "Now that we have all the necessary data, we visualize it in order to become familiar with it before building the model.\n",
    "\n",
    "First we define a few functions that will facilitate intuitive plotting of state-level statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "da94ffda-5722-433f-9611-b99be558f58f",
   "metadata": {},
   "outputs": [],
   "source": [
    "STATE_GRID = [\n",
    "    [\"AK\", None, None, None, None, None, None, None, None, None, \"ME\"],\n",
    "    [None, None, None, None, None, None, None, None, None, \"VT\", \"NH\"],\n",
    "    [\"WA\", \"ID\", \"MT\", \"ND\", \"MN\", None, \"MI\", None, \"NY\", \"MA\", \"RI\"],\n",
    "    [\"OR\", \"UT\", \"WY\", \"ND\", \"IA\", \"WI\", \"OH\", \"PA\", \"NJ\", \"CT\"],\n",
    "    [\"CA\", \"NV\", \"CO\", \"NE\", \"IL\", \"IN\", \"WV\", \"VA\", \"MD\", \"DE\"],\n",
    "    [None, \"AZ\", \"NM\", \"KS\", \"MO\", \"KY\", \"TN\", \"SC\", \"NC\"],\n",
    "    [None, None, None, \"OK\", \"LA\", \"AR\", \"MS\", \"AL\", \"GA\", None, \"DC\"],\n",
    "    [\"HI\", None, None, None, \"TX\", None, None, None, \"FL\"],\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0fd7f363-1dd9-4999-94f0-ac3bb50f6d73",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_facecolor(df, col, state, *, ax, norm, cmap, default=\"gray\"):\n",
    "    is_state = pl.col(\"state\") == state\n",
    "\n",
    "    if df.select(is_state.any()).item():\n",
    "        color = cmap(norm(df.filter(is_state)[col]))\n",
    "    else:\n",
    "        color = default\n",
    "\n",
    "    ax.set_facecolor(color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "69506e01-faa3-4451-838d-b26875641aef",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_state_grid(\n",
    "    data, *, col, norm, cmap, default=\"gray\", cbar=True, ax_plotter=plot_facecolor\n",
    "):\n",
    "    nrows = len(STATE_GRID)\n",
    "    ncols = max(len(row) for row in STATE_GRID)\n",
    "\n",
    "    fig, axes = plt.subplots(nrows=nrows, ncols=ncols)\n",
    "\n",
    "    for state_row, ax_row in zip(STATE_GRID, axes):\n",
    "        for state, ax in zip_longest(state_row, ax_row):\n",
    "            if state is None:\n",
    "                ax.axis(\"off\")\n",
    "            else:\n",
    "                ax.set_xticks([])\n",
    "                ax.set_yticks([])\n",
    "\n",
    "                ax.annotate(state, xy=(0.1, 0.1), xycoords=\"axes fraction\")\n",
    "\n",
    "                ax_plotter(\n",
    "                    data, col, state, ax=ax, norm=norm, cmap=cmap, default=default\n",
    "                )\n",
    "\n",
    "    if cbar:\n",
    "        cbar_ax = fig.add_axes([0.925, 0.25, 0.02, 0.5])\n",
    "        ColorbarBase(cbar_ax, cmap=cmap, norm=norm)\n",
    "    else:\n",
    "        cbar_ax = None\n",
    "\n",
    "    return fig, axes, cbar_ax"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54d01304-4706-4836-8f9b-f08733fc7db5",
   "metadata": {},
   "source": [
    "### Poll data\n",
    "\n",
    "With the data and these tools in hand, we begin by plotting the number of poll respondents in each state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "90b8ee98-5f24-42b4-af9f-7d9999df3a67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 89 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 437,
       "width": 577
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _, _ = plot_state_grid(\n",
    "    poll_df.group_by(\"state\").agg(pl.sum(\"poll_pop\")),\n",
    "    col=\"poll_pop\",\n",
    "    norm=Normalize(0, 750),\n",
    "    cmap=cm.binary,\n",
    "    default=\"white\",\n",
    ")\n",
    "\n",
    "fig.suptitle(\"Number of responses\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "887b241a-92c9-4271-855f-62c0dabea14a",
   "metadata": {},
   "source": [
    "We see immediately that some states have very few respondents, and indeed that Alaska and Hawaii had no respondents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dd9915c8-a0de-47b6-a060-0e2f3f055a24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>state</th><th>poll_pop</th></tr><tr><td>enum</td><td>i32</td></tr></thead><tbody><tr><td>&quot;AK&quot;</td><td>0</td></tr><tr><td>&quot;HI&quot;</td><td>0</td></tr><tr><td>&quot;DC&quot;</td><td>6</td></tr><tr><td>&quot;WY&quot;</td><td>14</td></tr><tr><td>&quot;DE&quot;</td><td>16</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 2)\n",
       "┌───────┬──────────┐\n",
       "│ state ┆ poll_pop │\n",
       "│ ---   ┆ ---      │\n",
       "│ enum  ┆ i32      │\n",
       "╞═══════╪══════════╡\n",
       "│ AK    ┆ 0        │\n",
       "│ HI    ┆ 0        │\n",
       "│ DC    ┆ 6        │\n",
       "│ WY    ┆ 14       │\n",
       "│ DE    ┆ 16       │\n",
       "└───────┴──────────┘"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    poll_df.group_by(\"state\")\n",
    "    .agg(pl.sum(\"poll_pop\"))\n",
    "    .join(state_df, how=\"right\", on=\"state\")\n",
    "    .with_columns(pl.col(\"poll_pop\").fill_null(0))\n",
    "    .sort(\"poll_pop\")\n",
    "    .select(\"state\", \"poll_pop\")\n",
    "    .head()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "669c9d0b-e9f8-4ce0-ab70-301760e01206",
   "metadata": {},
   "source": [
    "One of the benefits of MRP is the ability to use census data to predict the support for gay marriage in these states with little to no data based on similar respondents in other states.\n",
    "\n",
    "Next we visualize the empirical support for gay marriage in each state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fd6b6c7b-145e-46b4-9f7e-035a0fcda745",
   "metadata": {},
   "outputs": [],
   "source": [
    "PROB_CMAP = sns.diverging_palette(220, 10, as_cmap=True).reversed()\n",
    "PROB_FORMATTER = ticker.StrMethodFormatter(\"{x:.1%}\")\n",
    "PROB_LOCATOR = ticker.MultipleLocator(0.2)\n",
    "PROB_MIN, PROB_MAX = 0.1, 0.70\n",
    "PROB_NORM = Normalize(0, PROB_MAX)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7fe65b59-f252-4138-8df0-522738eede61",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_prob_ax(ax):\n",
    "    cbar_ax.yaxis.set_major_locator(PROB_LOCATOR)\n",
    "    cbar_ax.yaxis.set_major_formatter(PROB_FORMATTER)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d5d2b22b-68b0-4818-8c2c-f345a6322cf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def rate(num, denom):\n",
    "    return pl.sum(num) / pl.sum(denom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "03329313-c043-492e-a394-4b0b8975c842",
   "metadata": {},
   "outputs": [],
   "source": [
    "disagg_df = poll_df.group_by(\"state\").agg(rate(\"yes_of_all\", \"poll_pop\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9388c2ac-c49a-476e-845a-cd688055daf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 89 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 437,
       "width": 593
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _, cbar_ax = plot_state_grid(\n",
    "    disagg_df,\n",
    "    col=\"yes_of_all\",\n",
    "    norm=PROB_NORM,\n",
    "    cmap=PROB_CMAP,\n",
    ")\n",
    "\n",
    "make_prob_ax(cbar_ax)\n",
    "fig.suptitle(\"Disaggregation estimate of\\nsupport for gay marriage\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a27d335-9b4e-4bcf-afe3-8e902f999a1d",
   "metadata": {},
   "source": [
    "Note that the MRP literature, including the Kastellec primer we are following in this post, refer to this quantity as the \"disaggregation estimate.\"  We will use that language throughout the rest of this post for consistency.  At the end of the post we will see how the MRP estimates of support for gay marriage differ from these disaggregation estimates.  The difference between these estimates is largely due to the fact that the polled population is not (and cannot practically be) precisely reflective of the population of each state.\n",
    "\n",
    "This challenge of representative sampling is further illustrated in the following plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "01a39865-aeb5-493b-bdb4-f48afb8def40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<seaborn._core.plot.Plot at 0x1237d3800>"
      ]
     },
     "execution_count": 36,
     "metadata": {
      "image/png": {
       "height": 378.25,
       "width": 606.05
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    so.Plot(\n",
    "        poll_df.join(\n",
    "            census_df, on=set(poll_df.columns) & set(census_df.columns), how=\"right\"\n",
    "        )\n",
    "        .group_by(\"state\", \"gender\", \"race\")\n",
    "        .agg(pl.col(\"poll_pop\").fill_null(0).sum() == 0)\n",
    "        .group_by(\"gender\", \"race\")\n",
    "        .agg(pl.sum(\"poll_pop\").alias(\"state_ct\")),\n",
    "        x=\"race\",\n",
    "        y=\"state_ct\",\n",
    "        color=\"gender\",\n",
    "    )\n",
    "    .add(so.Bar(), so.Dodge())\n",
    "    .scale(y=so.Continuous().tick(every=5))\n",
    "    .label(\n",
    "        x=\"Race\",\n",
    "        y=\"Number of states\",\n",
    "        color=\"Gender\",\n",
    "        title=\"States with no respondents\",\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "502e49f3-5155-4f51-b758-bfd8450437f3",
   "metadata": {},
   "source": [
    "While only two states have zero polled respondents, significantly more states have zero respondents from minority race/gender subpopulations.  As in states with zero respondents, a benefit of MRP is the ability to predict support for gay marriage among unsampled subpopulations in these states based on attitudes from similar respondents in other statse."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8fb6e0c-988a-4d90-96f6-54b9908942d7",
   "metadata": {},
   "source": [
    "## Modeling\n",
    "\n",
    "With this basic understanding, we now turn to building the multilevel model necessary for MRP.\n",
    "\n",
    "First we define coordinates that will make our model easier to work with."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "54fd585b-67f3-4608-abcb-f8063cb64489",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_age = poll_df[\"age_cat\"].n_unique()\n",
    "n_edu = poll_df[\"edu_cat\"].n_unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5750c299-0924-431a-905c-7cff7a997171",
   "metadata": {},
   "outputs": [],
   "source": [
    "COORDS = {\n",
    "    \"age\": np.arange(n_age),\n",
    "    \"edu\": np.arange(n_edu),\n",
    "    \"gender\": GENDER.categories.to_numpy(),\n",
    "    \"poll\": POLL.categories.to_numpy(),\n",
    "    \"race\": RACE.categories.to_numpy(),\n",
    "    \"region\": REGION.categories.to_numpy(),\n",
    "    \"state\": STATE.categories.to_numpy(),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2628f483-b7fc-4b88-91f2-e0d6bd2a01d1",
   "metadata": {},
   "source": [
    "The model includes an intercept with a normal prior,\n",
    "\n",
    "$$\\beta_0 \\sim N(0, 2.5^2).$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2b583f73-852e-4394-892a-11caccb2e3ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "with pm.Model(coords=COORDS) as model:\n",
    "    β0 = pm.Normal(\"β0\", 0, 2.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd8ca4f3-5943-40cd-9608-51a4db01a42d",
   "metadata": {},
   "source": [
    "Most of the terms of the model will be [hierarchical](https://en.wikipedia.org/wiki/Bayesian_hierarchical_modeling) normal.  For example, the prior for the age effect is\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "    \\sigma_{\\text{age}}\n",
    "        & \\sim \\text{Half-}N(2.5^2), \\\\\n",
    "    \\beta_{\\text{age}}\n",
    "        & \\sim N(0, \\sigma_{\\text{age}}^2).\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "For sampling efficiency, we actually use an equivalent [noncentered parameterization](https://twiecki.io/blog/2017/02/08/bayesian-hierchical-non-centered/) of the above priors.  The priors for the effects of education, poll, age-education interaction, and gender-race interaction are defined similarly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "cabde71a-2ea7-4fed-90ba-478c63d96f10",
   "metadata": {},
   "outputs": [],
   "source": [
    "HALFNORMAL_SCALE = 1 / np.sqrt(1 - 2 / np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ff578a89-b10e-49fb-9d7f-d0743ba82b62",
   "metadata": {},
   "outputs": [],
   "source": [
    "def noncentered_normal(name, *, dims, μ=0):\n",
    "    Δ = pm.Normal(f\"Δ_{name}\", 0, 1, dims=dims)\n",
    "    σ = pm.HalfNormal(f\"σ_{name}\", 2.5 * HALFNORMAL_SCALE)\n",
    "\n",
    "    return pm.Deterministic(name, μ + Δ * σ, dims=dims)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "33c6bd50-482a-4b88-967f-e0fb9db6ddd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    β_age = noncentered_normal(\"β_age\", dims=\"age\")\n",
    "    β_edu = noncentered_normal(\"β_edu\", dims=\"edu\")\n",
    "    β_poll = noncentered_normal(\"β_poll\", dims=\"poll\")\n",
    "\n",
    "    β_age_edu = noncentered_normal(\"β_age_edu\", dims=(\"age\", \"edu\"))\n",
    "    β_gender_race = noncentered_normal(\"β_gender_race\", dims=(\"gender\", \"race\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b9fec5a-ffca-4273-88f0-20fb4e4eec3a",
   "metadata": {},
   "source": [
    "The state-level effects are slightly more complex, combining a hierarchical normal region-level effect with the effect of the proportion of its residents that identify as religious and that of the state's support for John Kerry in 2024, .  We have\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "    \\sigma_{\\text{region}}\n",
    "        & \\sim \\text{Half-}N(2.5^2), \\\\\n",
    "    \\alpha_{\\text{region}}\n",
    "        & \\sim N(0, \\sigma_{\\text{region}}^2) \\\\\n",
    "    \\alpha_{\\text{relig}}, \\alpha_{\\text{kerry}}\n",
    "        & \\sim N(0, 2.5^2), \\\\\n",
    "    \\beta_{\\text{state}}\n",
    "        & = \\alpha_{\\text{region}} + \\alpha_{\\text{relig}} \\cdot x_{\\text{relig}} +  \\alpha_{\\text{kerry}} \\cdot x_{\\text{kerry}}.\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "Here $x_{\\text{relig}}$ is the proportion of the state's residents that identify as religious and $x_{\\text{kerry}}$ is the proportion that voted for John Kerry in 2024."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f875275f-9370-4768-8fff-5f3021588e97",
   "metadata": {},
   "outputs": [],
   "source": [
    "kerry_04 = state_df[\"kerry_04\"].to_numpy()\n",
    "p_relig = state_df[\"p_relig\"].to_numpy()\n",
    "state_region = state_df[\"region\"].cast(pl.Categorical).to_physical().to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c0b2baf9-142b-44b9-a1ae-c159e77f8203",
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    α_region = noncentered_normal(\"α_region\", dims=\"region\")\n",
    "    α_relig = pm.Normal(\"α_relig\", 0, 2.5)\n",
    "    α_kerry = pm.Normal(\"α_kerry\", 0, 2.5)\n",
    "\n",
    "    β_state = (\n",
    "        α_region[state_region] + α_relig * logit(p_relig) + α_kerry * logit(kerry_04)\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31225977-8817-4c22-9f3f-61eaae17a3b2",
   "metadata": {},
   "source": [
    "Before using these effects to define the likelihood of the observed polling data, we build a number of data containers that will facilitate the posterior predictive sampling that will be necessary to perform poststratification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "2d32d2b5-9269-41ab-a5f5-84cb321b21f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    age = pm.Data(\"age\", poll_df[\"age_cat\"].to_numpy())\n",
    "    edu = pm.Data(\"edu\", poll_df[\"edu_cat\"].to_numpy())\n",
    "    gender = pm.Data(\n",
    "        \"gender\", poll_df[\"gender\"].to_physical().to_numpy().astype(np.int_)\n",
    "    )\n",
    "    poll = pm.Data(\"poll\", poll_df[\"poll\"].to_physical().to_numpy().astype(np.int_))\n",
    "    pop = pm.Data(\"pop\", poll_df[\"poll_pop\"].to_numpy())\n",
    "    race = pm.Data(\"race\", poll_df[\"race\"].to_physical().to_numpy().astype(np.int_))\n",
    "    state = pm.Data(\"state\", poll_df[\"state\"].to_physical().to_numpy())\n",
    "    yes_of_all = pm.Data(\"yes_of_all\", poll_df[\"yes_of_all\"].to_numpy())\n",
    "\n",
    "    use_poll = pm.Data(\"use_poll\", True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84202ab5-b65e-40d6-8463-392be28a6965",
   "metadata": {},
   "source": [
    "Finally we define\n",
    "\n",
    "$$\\eta = \\beta_0 + \\beta_{\\text{age}} + \\beta_{\\text{edu}} + \\beta_{\\text{state}} + \\beta_{\\text{age, edu}} + \\beta_{\\text{gender, race}} + \\beta_{\\text{poll}}.$$\n",
    "\n",
    "Note that to support poststratification, we include the ability to turn off the effect of the poll on the model.\n",
    "\n",
    "The likelihood is binomial with log-odds $\\eta$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ef7740c1-2b6a-483e-b996-a348aad87573",
   "metadata": {},
   "outputs": [],
   "source": [
    "def adv_index(tensor, indices, shape):\n",
    "    return tensor.ravel()[pt.ravel_multi_index(indices, shape)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "14693ea8-c7d8-452a-bd6a-b0068c615e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_gender = GENDER.categories.shape[0]\n",
    "n_race = RACE.categories.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "3d228ac9-ba96-446e-9260-3060b01a67ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    η = sum(\n",
    "        [\n",
    "            β0,\n",
    "            β_age[age],\n",
    "            β_edu[edu],\n",
    "            β_state[state],\n",
    "            adv_index(β_age_edu, (age, edu), (n_age, n_edu)),\n",
    "            adv_index(β_gender_race, (gender, race), (n_gender, n_race)),\n",
    "            pt.switch(use_poll, β_poll[poll], 0),\n",
    "        ]\n",
    "    )\n",
    "\n",
    "    pm.Binomial(\"response\", pop, pt.sigmoid(η), observed=yes_of_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "771ef104-fb9f-4602-9334-fe57e2233ca8",
   "metadata": {},
   "source": [
    "We now sample from the posterior distribution of this model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "2d5630f6-2b7e-4b00-873c-6d8490e3caaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "SEED = 123456789  # for reproducibility\n",
    "CHAINS = 8\n",
    "\n",
    "SAMPLER_KWARGS = {\n",
    "    \"seed\": SEED,\n",
    "    \"chains\": CHAINS,\n",
    "    \"cores\": CHAINS,\n",
    "    \"target_accept\": 0.99,\n",
    "}"
   ]
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   "execution_count": 50,
   "id": "0f6be3ff-3fb4-4f61-b034-08fbe28834d2",
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    "The [Gelman-Rubin statistic](https://en.wikipedia.org/wiki/Gelman-Rubin_statistic), $\\hat{R}$, shows no cause for concern."
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   "execution_count": 51,
   "id": "a1a47dd6-c733-476f-9fb7-3d50d3960197",
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       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray ()&gt; Size: 8B\n",
       "array(1.0036893)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bf0ae7c7-ac38-4115-b20c-971d95313dfe' class='xr-array-in' type='checkbox' checked><label for='section-bf0ae7c7-ac38-4115-b20c-971d95313dfe' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.004</span></div><div class='xr-array-data'><pre>array(1.0036893)</pre></div></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray ()> Size: 8B\n",
       "array(1.0036893)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.rhat(trace).max().to_array().max()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2659a78-a427-40d9-aed7-0ced0badcc74",
   "metadata": {},
   "source": [
    "## Poststratification\n",
    "\n",
    "We now sample from the model's posterior predictive distribution in order to perform poststratification.  To do so, we set the data containers we created above to the values from the census.  This step is what allows us to adjust for the non-representativeness of the poll's respondents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ab6c0763-e109-4747-9bbc-8a3507c82321",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_census, _ = census_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "22e5274f-2da0-4b50-a053-f4e1522cb51f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling: [response]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4a938648cde74a70a7043627b3eabc65",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with model:\n",
    "    pm.set_data(\n",
    "        {\n",
    "            \"age\": census_df[\"age_cat\"].to_numpy(),\n",
    "            \"edu\": census_df[\"edu_cat\"].to_numpy(),\n",
    "            \"gender\": census_df[\"gender\"].to_physical().to_numpy().astype(np.int_),\n",
    "            \"poll\": np.zeros(n_census, dtype=np.int_),\n",
    "            \"pop\": census_df[\"pop\"].to_numpy(),\n",
    "            \"race\": census_df[\"race\"].to_physical().to_numpy().astype(np.int_),\n",
    "            \"state\": census_df[\"state\"].to_physical().to_numpy(),\n",
    "            \"yes_of_all\": np.zeros(n_census, dtype=np.int_),\n",
    "            \"use_poll\": False,\n",
    "        }\n",
    "    )\n",
    "\n",
    "    pm.sample_posterior_predictive(trace, extend_inferencedata=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fe9cd6c-d80b-4ef4-b83e-fb6fb6551311",
   "metadata": {},
   "source": [
    "We use these posterior predictive samples to construct the poststratification estimates of each state's support for gay marriagne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "382676a1-ed37-4e98-ad1d-72113163e5f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "poststrat_df = (\n",
    "    census_df.with_columns(\n",
    "        pp_yes_of_all=trace.posterior_predictive[\"response\"]\n",
    "        .mean(dim=(\"chain\", \"draw\"))\n",
    "        .to_numpy()\n",
    "    )\n",
    "    .group_by(\"state\")\n",
    "    .agg(rate(\"pp_yes_of_all\", \"pop\").alias(\"yes_of_all\"))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "543e68fe-111c-47f2-8a6a-c44823e3c120",
   "metadata": {},
   "source": [
    "Now compare the disaggregation and MRP estimates of support for gay marriage.  The disaggregation estimate colors the upper left corner of each state's rectangle, and the MRP estimate colors the lower right corner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "13354f20-0701-468f-aa39-4232e1cdfa2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_split_color(dfs, col, state, *, ax, norm, cmap, default=\"gray\"):\n",
    "    ul_df, lr_df = dfs\n",
    "\n",
    "    is_state = pl.col(\"state\") == state\n",
    "\n",
    "    xmin, xmax = ax.get_xlim()\n",
    "    ymin, ymax = ax.get_ylim()\n",
    "\n",
    "    # upper left\n",
    "    if ul_df.select(is_state.any()).item():\n",
    "        ul_color = cmap(norm(ul_df.filter(is_state)[col]))\n",
    "    else:\n",
    "        ul_color = default\n",
    "\n",
    "    ax.add_patch(plt.Polygon([[0, 0], [xmax, ymax], [0, ymax]], color=ul_color))\n",
    "\n",
    "    # lower right\n",
    "    if lr_df.select(is_state.any()).item():\n",
    "        lr_color = cmap(norm(lr_df.filter(is_state)[col]))\n",
    "    else:\n",
    "        lr_color = default\n",
    "\n",
    "    ax.add_patch(plt.Polygon([[0, 0], [xmax, ymax], [xmax, 0]], color=lr_color))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "d9500070-d97d-446b-9b95-1d8b42404c60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 89 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 437,
       "width": 593
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _, cbar_ax = plot_state_grid(\n",
    "    (\n",
    "        poll_df.group_by(\"state\").agg(rate(\"yes_of_all\", \"poll_pop\")),\n",
    "        poststrat_df,\n",
    "    ),\n",
    "    col=\"yes_of_all\",\n",
    "    norm=PROB_NORM,\n",
    "    cmap=PROB_CMAP,\n",
    "    ax_plotter=plot_split_color,\n",
    ")\n",
    "\n",
    "make_prob_ax(cbar_ax)\n",
    "fig.suptitle(\"Disaggregation and MRP estimates\\nof support for gay marriage\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5f61a28-c43c-41c0-8c7c-d7bd6d352c26",
   "metadata": {},
   "source": [
    "We see that most states support has moved towards the average with the MRP estimate.  Also, MRP produces estimates for Alaska and Hawaii based on their census data, whereas disaggregation cannot.\n",
    "\n",
    "Finally, we produce another comparison of the two estimates state-by-state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "3c2e357b-af7a-4b16-8356-39880e077592",
   "metadata": {},
   "outputs": [],
   "source": [
    "state_pop = census_df.group_by(\"state\").agg(pl.sum(\"pop\")).sort(\"state\")\n",
    "state_pop_ = state_pop[\"pop\"].to_numpy().squeeze()\n",
    "\n",
    "poststrat_state_df = (\n",
    "    trace.posterior_predictive[\"response\"]\n",
    "    .rename(response_dim_2=\"state\")\n",
    "    .assign_coords(state=census_df[\"state\"])\n",
    "    .groupby(\"state\")\n",
    "    .sum()\n",
    "    .pipe(lambda x: x / state_pop_)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "4f5f7492-bbc8-49d6-8255-7efd1fc35a52",
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted_states = STATE.categories[\n",
    "    poststrat_state_df.mean(dim=(\"chain\", \"draw\")).argsort().to_numpy()\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f0c70585",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1014,
       "width": 539
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ax,) = az.plot_forest(\n",
    "    poststrat_state_df,\n",
    "    coords={\"state\": sorted_states[::-1]},\n",
    "    combined=True,\n",
    "    labeller=az.labels.NoVarLabeller(),\n",
    "    figsize=(6, 12),\n",
    ")\n",
    "\n",
    "disagg_scatter_df = (\n",
    "    disagg_df.join(\n",
    "        pl.DataFrame(\n",
    "            {\n",
    "                \"state\": sorted_states.cast(STATE),\n",
    "                \"sort_key\": np.arange(sorted_states.shape[0]),\n",
    "                \"y\": ax.get_yticks(),\n",
    "            }\n",
    "        ),\n",
    "        on=\"state\",\n",
    "    )\n",
    "    .join(state_pop, on=\"state\")\n",
    "    .sort(\"sort_key\")\n",
    ")\n",
    "\n",
    "pop_norm = Normalize(0, disagg_scatter_df[\"pop\"].max())\n",
    "\n",
    "ax.scatter(\n",
    "    disagg_scatter_df[\"yes_of_all\"],\n",
    "    disagg_scatter_df[\"y\"],\n",
    "    s=200 * pop_norm(disagg_scatter_df[\"pop\"]),\n",
    "    c=\"k\",\n",
    "    label=\"Disaggregation\\nestimate\",\n",
    "    zorder=5,\n",
    ")\n",
    "\n",
    "ax.axvline(\n",
    "    (poststrat_state_df.mean(dim=(\"chain\", \"draw\")) * state_pop_).sum()\n",
    "    / state_pop_.sum(),\n",
    "    ls=\"--\",\n",
    "    c=\"k\",\n",
    "    label=\"National average\",\n",
    ")\n",
    "\n",
    "ax.xaxis.set_major_formatter(PROB_FORMATTER)\n",
    "ax.set_xlabel(\"MRP estimate of support for gay marriage\")\n",
    "\n",
    "ax.legend(loc=\"upper left\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b1389fe-d4e0-47bc-b2be-e7f045eb7d04",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Here the size of the black circles corresponding to the disaggregation estimate correspond to the state's population.  We see, by and large, that states with higher population have similar disaggregation and MRP estimates, and states with smaller population have MRP estimates closer to the national (disaggregation) mean than their disaggregation estimates.  Notable exceptions to this trend are New York, Florida, and Pennsylvania, among others.  These states's deviation from the trend indicates that the respondent population was particularly unrepresentative of the state's demographics.\n",
    "\n",
    "This post is available as a Jupyter notebook [here](https://nbviewer.org/gist/AustinRochford/e160d9687e97fa287ec3a072f6c9865c)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "0cd102f4-5528-4ab1-a075-3672a094de73",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Sun Nov 23 2025\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.12.5\n",
      "IPython version      : 8.29.0\n",
      "\n",
      "pymc      : 5.25.1\n",
      "nutpie    : 0.15.2\n",
      "us        : 3.2.0\n",
      "seaborn   : 0.13.2\n",
      "pytensor  : 2.31.7\n",
      "arviz     : 0.20.0\n",
      "polars    : 1.14.0\n",
      "numpy     : 2.0.2\n",
      "matplotlib: 3.9.2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.5"
  },
  "nikola": {
   "date": "2025-11-23",
   "slug": "mrp2",
   "title": "Revisiting Multilevel Regression and Poststratification with PyMC"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
 }
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