Changes in version 0.2.0.9000                      

                        Changes in version 0.2.0                        

Adds a specification-curve tool for comparing rurality classification
schemes on user-supplied county-level outcomes, plus a companion
spec-curve vignette.

New features

  - rurality_spec(): fits OLS models across four schemes (RUCC, RUCA,
    NCHS, OMB), two functional forms (ordinal / binary metro-nonmetro),
    and three built-in covariate sets, returning a tidy data frame and
    (by default) a specification-curve plot.

Data

  - county_crosswalk: new 3,143-county crosswalk harmonising RUCC 2023,
    RUCA 2020 (modal ZCTA), NCHS 2023, OMB metro/micro/noncore, Census
    2020 percent urban, and ACS 2022 5-year demographics. Used as the
    backbone for rurality_spec().

                 Changes in version 0.1.1 (2026-04-15)                  

Data-correctness patch (2026-04-13).

Bug fixes

  - county_rurality: distances to the nearest large/medium/small metro
    were computed against an incomplete metro list (15 large / 9 medium
    / 5 small). Counties near any large metro outside the top 15 —
    Denver, Minneapolis, Portland, Las Vegas, Charlotte, Indianapolis,
    Cleveland, Cincinnati, Columbus, Kansas City, Austin, San Antonio,
    Nashville, Jacksonville, Oklahoma City, Memphis, Louisville, and
    others — were being measured to New York, Chicago, or Los Angeles
    and classified as "Suburban" rather than "Urban". Example: Denver
    County shipped with dist_large_metro = 591, classified Suburban.
  - Rebuilt with a full metro list shared with the rurality-app web
    project (52 large / 57 medium / 36 small). After this patch the
    major urban-core counties (Denver, Hennepin, Multnomah, Mecklenburg,
    Cuyahoga, Marion-IN, and similar) classify as Urban.

Data

  - county_rurality: 3,235 rows, unchanged schema. Score distribution
    (Urban / Suburban / Mixed / Rural / Very Rural): 184 / 908 / 669
    / 976 / 498.

                 Changes in version 0.1.0 (2026-04-10)                  

Initial CRAN release (2026-04-10).

Core

  - get_rurality() returns the composite rurality score, classification,
    and RUCC code for a U.S. county identified by 5-digit FIPS.
  - get_rucc() and rurality_score() return their respective scalar
    values for one-off lookups.
  - get_ruca() returns the primary RUCA code for a ZIP code tabulation
    area.
  - classify_rurality() converts a numeric rurality score (0-100) into
    an ordered classification: Urban, Suburban, Mixed, Rural, Very
    Rural.
  - add_rurality() joins rurality variables onto an existing data frame
    by FIPS column, with optional selection of the full variable set.

Data

  - county_rurality: all 3,235 U.S. counties with 24 variables,
    including composite score, classification, RUCC 2023, population
    density, distance to nearest large metro, and ACS 2022 demographics.
  - ruca_codes: USDA RUCA 2020 codes for 41,146 ZIP code tabulation
    areas.

Methodology

Composite score is a weighted average of RUCC code (55%), population
density (28%), and distance to nearest large metro (17%), rescaled to
0-100.