_pkgdown.yml

url: https://www.shirokuriwaki.com/ccesMRPprep/
destination: docs
template:
  params:
    docsearch:
      api_key: 1a2c0d939f9a70090cf27efbbac5ba52
      index_name: ccesmrpprep
    bootswatch: spacelab
home:
  title: Portable Routines for Preparing CCES and ACS data for MRP
  description: |
    Multilevel Regression and Poststratification (MRP) is a method for analyzing surveys, and can be implemented on public datasets such as the CCES, ACS, and CPS. This package provides data loading, processing, and formatting functions for a particular task: using CCES data for MRP. It uses the dataverse and tidycensus packages to load data and provide some crosswalks. Model fitting and visualization of MRP itself is handled elsewhere.
authors:
  Shiro Kuriwaki:
    href: https://www.shirokuriwaki.com
reference:
- title: Lookup tables and variable metadata
  desc: tibbles that obtain, link, collpase, and describe ACS and CCES values
  contents:
  - ends_with("_key")
  - cces_dv_ids
  - starts_with("acscodes")
  - starts_with("cps")
- title: Reading Data
  desc: Functions that read in CCES and ACS data from an API
  contents: starts_with("get_")
- title: Sample datasets
  desc: Samples of datasets one can get from the data loading functions
  contents:
  - ccc_samp
  - cc18_samp
  - cc18_NY
  - cd_info
  - cd_info_long
  - elec_NY
  - questions_samp
- title: Data recoding and cleaning
  desc: Functions that standardize and clean variable names and formats
  contents:
  - ccc_bin_age
  - ccc_std_demographics
  - to_cd
  - std_acs_cdformat
  - cces_join_slim
  - yesno_to_binary
- title: Data collapsing and reshaping
  desc: Wrangling cleaned data for apporpriate modeling
  contents:
  - build_counts
articles:
- title: Get Started
  navbar: ~
  contents: overview
- title: Derived Variables
  navbar: ~
  contents: derived
- title: ACS Data
  navbar: ~
  contents: acs
- title: CPS Data
  navbar: ~
  contents: cps