bravo {ndi}

Educational Isolation Index based on Bravo et al. (2021)

Description

Compute the spatial Educational Isolation Index (Bravo) of selected educational attainment category(ies).

Usage

bravo(geo = "tract", year = 2020, subgroup, 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.

subgroup

Character string specifying the educational attainment category(ies). See Details for available choices.

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 the spatial Educational Isolation Index (EI) of U.S. census tracts or counties for a specified geographical extent (e.g., the entire U.S. or a single state) based on Bravo et al. (2021) doi:10.3390/ijerph18179384 who originally designed the metric for the educational isolation of individual without a college degree. This function provides the computation of EI for any of the U.S. Census Bureau educational attainment levels.

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 five educational attainment levels (U.S. Census Bureau definitions) are:

• B06009_002: Less than high school graduate "LtHS"

• B06009_003: High school graduate (includes equivalency) "HSGiE"

• B06009_004: Some college or associate's degree "SCoAD"

• B06009_005: Bachelor's degree "BD"

• B06009_006: Graduate or professional degree "GoPD"

Note: If year = 2009, then the ACS-5 data (2005-2009) are from the B15002 question.

Use the internal state and county arguments within the get_acs function to specify geographic extent of the data output. NOTE: Current version does not correct for edge effects (e.g., census geographies along the specified spatial extent border, coastline, or U.S.-Mexico / U.S.-Canada border) may have few neighboring census geographies, and EI values in these census geographies may be unstable. A stop-gap solution for the former source of edge effect is to compute the EI for neighboring census geographies (i.e., the states bordering a study area of interest) and then use the estimates of the study area of interest.

A census geography (and its neighbors) that has nearly all of its population with the specified educational attainment category (e.g., a Bachelor's degree or more) will have an EI value close to 1. In contrast, a census geography (and its neighbors) that is nearly none of its population with the specified educational attainment category (e.g., less than a Bachelor's degree) will have an EI value close to 0.

Value

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

ei

An object of class 'tbl' for the GEOID, name, EI, 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 EI.

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)
  bravo(geo = "tract", state = "GA", 
        year = 2020, subgroup = c("LtHS", "HSGiE"))
  
  # County-level metric (2020)
  bravo(geo = "county", state = "GA",
        year = 2020, subgroup = c("LtHS", "HSGiE"))
  

## End(Not run)