krieger {ndi}

Index of Concentration at the Extremes based on Feldman et al. (2015) and Krieger et al. (2016)

Description

Compute the aspatial Index of Concentration at the Extremes (Krieger).

Usage

krieger(geo = "tract", year = 2020, quiet = FALSE, ...)

Arguments

geo

Character string specifying the geography of the data either census tracts geo = "tract" (the default) or counties geo = "county".

year

Numeric. The year to compute the estimate. The default is 2020, and the years 2009 onward are currently available.

quiet

Logical. If TRUE, will display messages about potential missing census information. The default is FALSE.

...

Arguments passed to get_acs to select state, county, and other arguments for census characteristics

Details

This function will compute three aspatial Index of Concentration at the Extremes (ICE) of U.S. census tracts or counties for a specified geographical extent (e.g., entire U.S. or a single state) based on Feldman et al. (2015) doi:10.1136/jech-2015-205728 and Krieger et al. (2016) doi:10.2105/AJPH.2015.302955. The authors expanded the metric designed by Massey in a chapter of Booth & Crouter (2001) doi:10.4324/9781410600141 who initially designed the metric for residential segregation. This function computes five ICE metrics:

• Income: 80th income percentile vs. 20th income percentile

• Education: less than high school vs. four-year college degree or more

• Race/Ethnicity: white non-Hispanic vs. black non-Hispanic

• Income and race/ethnicity combined: white non-Hispanic in 80th income percentile vs. black alone (including Hispanic) in 20th income percentile

• Income and race/ethnicity combined: white non-Hispanic in 80th income percentile vs. white non-Hispanic in 20th income percentile

The function uses the get_acs function to obtain U.S. Census Bureau 5-year American Community Survey characteristics used for the geospatial computation. The yearly estimates are available for 2009 onward when ACS-5 data are available but are available from other U.S. Census Bureau surveys. The ACS-5 groups used in the computation of the five ICE metrics are:

• B03002: HISPANIC OR LATINO ORIGIN BY RACE

• B15002: SEX BY EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER

• B19001: HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 20XX INFLATION-ADJUSTED DOLLARS)

• B19001B: HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 20XX INFLATION-ADJUSTED DOLLARS) (BLACK OR AFRICAN AMERICAN ALONE HOUSEHOLDER)

• B19001H: HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 20XX INFLATION-ADJUSTED DOLLARS) (WHITE ALONE, NOT HISPANIC OR LATINO HOUSEHOLDER)

Use the internal state and county arguments within the get_acs function to specify geographic extent of the data output.

ICE metrics can range in value from -1 (most deprived) to 1 (most privileged). A value of 0 can thus represent two possibilities: (1) none of the residents are in the most privileged or most deprived categories, or (2) an equal number of persons are in the most privileged and most deprived categories, and in both cases indicates that the area is not dominated by extreme concentrations of either of the two groups.

Value

An object of class 'list'. This is a named list with the following components:

ice

An object of class 'tbl' for the GEOID, name, ICE metrics, and raw census values of specified census geographies.

missing

An object of class 'tbl' of the count and proportion of missingness for each census variable used to compute the ICEs.

See Also

get_acs for additional arguments for geographic extent selection (i.e., state and county).

Examples

## Not run: 
# Wrapped in \dontrun{} because these examples require a Census API key.
  
  # Tract-level metric (2020)
  krieger(geo = "tract", state = "GA", year = 2020)
  
  # County-level metric (2020)
  krieger(geo = "county", state = "GA", year = 2020)
  

## End(Not run)