diff --git a/DESCRIPTION b/DESCRIPTION index beb4e11..6f63a86 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: ndi Title: Neighborhood Deprivation Indices -Version: 0.1.6.9015 -Date: 2025-05-30 +Version: 0.2.0 +Date: 2025-08-29 Authors@R: c(person(given = "Ian D.", family = "Buller", @@ -38,6 +38,7 @@ Depends: Imports: car, dplyr, + Hmisc, MASS, Matrix, psych, diff --git a/NAMESPACE b/NAMESPACE index fca523d..7c9c88f 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -26,6 +26,7 @@ export(theil) export(white) export(white_blau) import(dplyr) +importFrom(Hmisc,wtd.quantile) importFrom(MASS,ginv) importFrom(Matrix,sparseMatrix) importFrom(car,logit) diff --git a/NEWS.md b/NEWS.md index 4f1df9e..d71bc70 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,6 +1,6 @@ # ndi (development version) -## ndi v0.1.6.9015 +## ndi v0.2.0 ### New Features @@ -31,7 +31,8 @@ ### Updates #### Bug Fixes -* Fixed NOTE in CRAN checks to provide package anchors for Rd \link{} targets not in the package itself and the base packages within 'ndi-package.Rd' +* Fixed NOTE in CRAN checks to provide package anchors for Rd `\link{}` targets not in the package itself and the base packages within 'ndi-package.Rd' +* Updated population-weighted quantile method from `stats::quantile` to `Hmisc::wtd.quantile` in `powell_wiley()` thanks to a contribution (#32) by [Hunter Miller](https://github.com/huntermills707) * `bell()` function computes the Interaction Index (Bell) not the Isolation Index as previously documented. Updated documentation throughout. * Fixed bug in `bell()`, `bemanian_beyer()`, `duncan()`, `sudano()`, and `white()` functions when a smaller geography contains n=0 total population, will assign a value of zero (0) in the internal calculation instead of NA * Fixed bug in `atkinson()` function to properly compute the income Atkinson Index @@ -40,7 +41,7 @@ * Output of racial or ethnic residential segregation indices is now rounded to four significant digits #### New Dependencies -* `tigris` and `units` are now Imports +* `Hmisc`, `tigris`, and `units` are now Imports #### Updated Documentation * Split up vignette into three separate vignettes: 'ndi1', 'ndi2', and 'ndi3' for the *NDI*, racial or ethnic residential segregation, and additional socioeconomic disparity indices, respectively diff --git a/R/ndi-package.R b/R/ndi-package.R index 5a55dea..9c24c76 100644 --- a/R/ndi-package.R +++ b/R/ndi-package.R @@ -83,17 +83,18 @@ #' @name ndi-package #' @aliases ndi-package ndi #' -#' @section Dependencies: The 'ndi' package relies heavily upon \code{\link[tidycensus]{tidycensus}} to retrieve data from the U.S. Census Bureau American Community Survey five-year estimates and the \code{\link[psych]{psych}} for computing the neighborhood deprivation indices. The \code{\link{messer}} function builds upon code developed by Hruska et al. (2022) \doi{10.17605/OSF.IO/M2SAV} by fictionalizing, adding the percent of households earning <$30,000 per year to the \emph{NDI} computation, and providing the option for computing the ACS-5 2006-2010 \emph{NDI} values. There is no code companion to compute \emph{NDI} included in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} or Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002}, but the package author worked directly with the Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} authors to replicate their SAS code in \strong{R}. The indices of racial or ethnic residential segregation rely heavily on the \code{\link[sf]{sf}} and \code{\link[tigris]{tigris}} packages to assign the smaller geographical units within larger geographical units and, occasionally, perform geospatial projection for distance-based metrics. The computation of \emph{RI} and \emph{EI} also relies on the \code{\link[Matrix]{Matrix}} package to compute the geospatial adjacency matrix between census geographies. Internal function to calculate \emph{AI} using the Hölder mean is based on \code{\link[DescTools]{Atkinson}} function. +#' @section Dependencies: The 'ndi' package relies heavily upon \code{\link[tidycensus]{tidycensus-package}} to retrieve data from the U.S. Census Bureau American Community Survey five-year estimates and the \code{\link[psych]{psych-package}} for computing the neighborhood deprivation indices. The \code{\link{messer}} function builds upon code developed by Hruska et al. (2022) \doi{10.17605/OSF.IO/M2SAV} by fictionalizing, adding the percent of households earning <$30,000 per year to the \emph{NDI} computation, and providing the option for computing the ACS-5 2006-2010 \emph{NDI} values. There is no code companion to compute \emph{NDI} included in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} or Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002}, but the package author worked directly with the Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} authors to replicate their SAS code in \strong{R}. The indices of racial or ethnic residential segregation rely heavily on the \code{\link[sf]{sf-package}} and \code{\link[tigris]{tigris-package}} packages to assign the smaller geographical units within larger geographical units and, occasionally, perform geospatial projection for distance-based metrics. The computation of \emph{RI} and \emph{EI} also relies on the \code{\link[Matrix]{sparseMatrix}} function to compute the geospatial adjacency matrix between census geographies. Internal function to calculate \emph{AI} using the Hölder mean is based on \code{\link[DescTools]{Atkinson}} function. #' #' @author Ian D. Buller\cr \emph{DLH, LLC (formerly DLH Corporation and Social & Scientific Systems, Inc.), Bethesda, Maryland, USA (current); Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA (original).} \cr #' #' Maintainer: I.D.B. \email{ian.buller@@alumni.emory.edu} #' #' @keywords internal -'_PACKAGE' +"_PACKAGE" #' @import dplyr #' @importFrom car logit +#' @importFrom Hmisc wtd.quantile #' @importFrom MASS ginv #' @importFrom Matrix sparseMatrix #' @importFrom psych alpha principal diff --git a/R/powell_wiley.R b/R/powell_wiley.R index d0af3f1..5dc5769 100644 --- a/R/powell_wiley.R +++ b/R/powell_wiley.R @@ -31,7 +31,7 @@ #' #' Use the internal \code{state} and \code{county} arguments within the \code{\link[tidycensus]{get_acs}} function to specify the referent for standardizing the \emph{NDI} (Powell-Wiley) values. For example, if all U.S. states are specified for the \code{state} argument, then the output would be a U.S.-standardized index. Please note: the \emph{NDI} (Powell-Wiley) values will not exactly match (but will highly correlate with) those found in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} and Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} because the two studies used a different statistical platform (i.e., SPSS and SAS, respectively) that intrinsically calculate the principal component analysis differently from R. #' -#' The categorical \emph{NDI} (Powell-Wiley) values are population-weighted quintiles of the continuous \emph{NDI} (Powell-Wiley) values. +#' The categorical \emph{NDI} (Powell-Wiley) values are population-weighted quintiles of the continuous \emph{NDI} (Powell-Wiley) values. NOTE: As of version 0.2.0, population-weighted quintiles are computed using a weighted quantile function \code{\link[Hmisc]{wtd.quantile}} where values are calculated NDI and weights are Total Population instead of previously using \code{\link[stats]{quantile}} of the product of the calculated NDI and natural logarithm transformed total population. #' #' Check if the proportion of variance explained by the first principal component is high (more than 0.5). #' @@ -53,9 +53,10 @@ #' @references Slotman, BA, Stinchcomb, DG, Powell-Wiley, TM, Ostendorf, DM, Saelens, BE, Gorin, AA, Zenk, SN, & Berrigan, D (2022) Environmental Data and Methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Environmental Working Group. \emph{Data in Brief}, 41:108002. \doi{10.1016/j.dib.2022.108002} #' #' @import dplyr +#' @importFrom Hmisc wtd.quantile #' @importFrom MASS ginv #' @importFrom psych alpha principal -#' @importFrom stats complete.cases cor cov2cor loadings median promax quantile sd +#' @importFrom stats complete.cases cor cov2cor loadings median promax sd #' @importFrom stringr str_trim #' @importFrom tidycensus get_acs #' @importFrom tidyr pivot_longer separate @@ -350,9 +351,10 @@ powell_wiley <- function(geo = 'tract', NDIQuint <- ndi_data_NDI %>% dplyr::mutate( NDIQuint = cut( - NDI * log(TotalPop), - breaks = stats::quantile( - NDI * log(TotalPop), + NDI, + breaks = Hmisc::wtd.quantile( + NDI, + weights = TotalPop, probs = c(0, 0.2, 0.4, 0.6, 0.8, 1), na.rm = TRUE ), diff --git a/README.md b/README.md index 5ce71cf..6884493 100644 --- a/README.md +++ b/README.md @@ -9,10 +9,10 @@ [![CRAN RStudio mirror downloads monthly](https://cranlogs.r-pkg.org/badges/ndi)](https://r-pkg.org:443/pkg/ndi) [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/license/apache-2-0) ![GitHub last commit](https://img.shields.io/github/last-commit/idblr/ndi) -[![DOI](https://zenodo.org/badge/521439746.svg)](https://zenodo.org/badge/latestdoi/521439746) +[![](https://img.shields.io/badge/DOI-10.32614/CRAN.package.ndi-1f57b6?style=flat&link=https://doi.org/10.32614/CRAN.package.ndi)](https://doi.org/10.32614/CRAN.package.ndi) -**Date repository last updated**: 2025-05-30 +**Date repository last updated**: 2025-08-29 ### Overview @@ -182,6 +182,8 @@ See also the list of [contributors](https://github.com/idblr/ndi/graphs/contribu * **Jessica Gleason** - *Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland* - [ORCID](https://orcid.org/0000-0001-9877-7931) +* **Hunter Mills** - [GitHub](https://github.com/huntermills707) + * **Chris Prener** - *Real World Evidence Center of Excellence, Pfizer, Inc.* - [GitHub](https://github.com/chris-prener) - [ORCID](https://orcid.org/0000-0002-4310-9888) * **Davis Vaughan** - *Posit* - [GitHub](https://github.com/DavisVaughan) - [ORCID](https://orcid.org/0000-0003-4777-038X) diff --git a/cran-comments.md b/cran-comments.md index ca6f1d1..388ba35 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,6 +1,8 @@ ## This is the seventh resubmission * Actions taken since previous submission: + +#### New Functions * Added `denton()` function to compute the aspatial racial or ethnic Relative Clustering (*RCL*) based on [Massey & Denton (1988)](https://doi.org/10.1093/sf/67.2.281) * Added `denton_cuzzort()` function to compute the aspatial racial or ethnic Relative Concentration (*RCO*) based on [Massey & Denton (1988)](https://doi.org/10.1093/sf/67.2.281) and Duncan, Cuzzort, & Duncan (1961; LC:60007089) * Added `duncan_cuzzort()` function to compute the aspatial racial or ethnic Absolute Centralization (*ACE*) based on Duncan, Cuzzort, & Duncan (1961; LC:60007089) and [Massey & Denton (1988)](https://doi.org/10.1093/sf/67.2.281) @@ -14,19 +16,28 @@ * Added `morgan_massey()` function to compute the aspatial racial or ethnic Distance-Decay Isolation Index (_DPxx\*_) based on [Morgan (1983)](https://www.jstor.org/stable/20001935) and [Massey & Denton (1988)](https://doi.org/10.1093/sf/67.2.281) * Added `theil()` function the aspatial racial or ethnic Entropy (*H*) based on Theil (1972; ISBN:978-0-444-10378-9) and [Theil & Finizza (1971)](https://doi.org/110.1080/0022250X.1971.9989795) * Added `white_blau()` function to compute an index of spatial proximity (*SP*) based on [White (1986)](https://doi.org/10.2307/3644339) and Blau (1977; ISBN-13:978-0-029-03660-0) + +#### New Function Capabilities * Added `geo_large = 'place'` for census-designated places, `geo_large = 'cbsa'` for core-based statistical areas, `geo_large = 'csa'` for combined statistical areas, and `geo_large = 'metro'` for metropolitan divisions as the larger geographical unit in `atkinson()`, `bell()`, `bemanian_beyer()`, `denton()`, `denton_cuzzort()`, `duncan()`, `duncan_cuzzort()`, `duncan_duncan()`, `hoover()`, `james_taeuber()`, `lieberson()`, `massey()`, `massey_duncan()`, `morgan_denton()`, `morgan_massey()`, `sudano()`, `theil()`, and `white()`, `white_blau()` functions. * Added census block group computation for `anthopolos()` by specifying `geo == 'cbg'` or `geo == 'block group'` * Added `holder` argument to `atkinson()` function to toggle the computation with or without the Hölder mean. The function can now compute *A* without the Hölder mean. The default is `holder = FALSE`. * Added `crs` argument to `anthopolos()`, `bravo()`, and `white_blau()` functions to provide spatial projection of the distance-based metrics * The `gini()` function now computes the aspatial racial or ethnic Gini Index (*G*) based on [Gini (1921)](https://doi.org/10.2307/2223319) as the main outcome. Arguments `geo_large`, `geo_small`, `subgroup`, and `omit_NAs` were added and argument `geo` was deprecated. The `gini()` function still retrieves the original output of the aspatial income Gini Index (*G*) at each smaller geography and is moved from the `g` output to `g_data` output. * Specifying census block groups in `geo` or `geo_small` arguments is now `'block group'` or `'cbg'` to match internal `get_acs()` function from the [tidycensus](https://CRAN.R-project.org/package=tidycensus) package - * Fixed NOTE in CRAN checks to provide package anchors for Rd \link{} targets not in the package itself and the base packages within 'ndi-package.Rd' + +#### Bug Fixes + * Fixed NOTE in CRAN checks to provide package anchors for Rd `\link{}` targets not in the package itself and the base packages within 'ndi-package.Rd' + * Updated population-weighted quantile method from `stats::quantile` to `Hmisc::wtd.quantile` in `powell_wiley()` * `bell()` function computes the Interaction Index (Bell) not the Isolation Index as previously documented. Updated documentation throughout. * Fixed bug in `bell()`, `bemanian_beyer()`, `duncan()`, `sudano()`, and `white()` functions when a smaller geography contains n=0 total population, will assign a value of zero (0) in the internal calculation instead of NA * Fixed bug in `atkinson()` function to properly compute the income Atkinson Index * Renamed *AI* as *A*, *DI* as *D*, *Gini* as *G*, and *II* as _xPy\*_ to align with the definitions from [Massey & Denton (1988)](https://doi.org/10.1093/sf/67.2.281). The output for `atkinson()` now produces `a` instead of `ai`. The output for `duncan()` now produces `d` instead of `ai`. The output for `gini()` now produces `g` instead of `gini`. The output for `bell()` now produces `xPy_star` instead of `II`. The internal functions `ai_fun()`, `di_fun()` and `ii_fun()` were renamed `a_fun()`, `ddd_fun()` and `xpy_star_fun()`, respectively. * Output of racial or ethnic residential segregation indices is now rounded to four significant digits - * `tigris` and `units` are now Imports + +#### New Dependencies + * `Hmisc`, `tigris`, and `units` are now Imports + +#### Updated Documentation * Reformatted functions for consistent internal structure * 'package.R' deprecated. Replaced with 'ndi-package.R' and reordered the contents * Consolidated DESCRIPTION @@ -52,19 +63,25 @@ * * * +* The win-builder oldrelease throws a NOTE that "Author field differs from that derived from Authors@R". The behavior is OK because ORCID has different formatting but same information * Some tests and examples for `anthopolos()`, `atkinson()`, `bell()`, `bemanian_beyer()`, `bravo()`, `denton()`, `denton_cuzzort()`, `duncan()`, `duncan_cuzzort()`, `duncan_duncan()`, `gini()`, `hoover()`, `james_taeuber()`, `krieger()`, `lieberson()`, `massey()`, `massey_duncan()`, `messer()`, `powell_wiley()`, `sudano()`, `theil()`, `white()`, and `white_blau()` functions require a Census API key so they are skipped if NULL or not run ## Test environments -* local Windows install, R 4.4.1 +* local Windows install, R 4.5.1 * win-builder, (devel, release, oldrelease) -* Rhub - * Fedora Linux, R-devel, clang, gfortran - * Ubuntu Linux 20.04.1 LTS, R-release, GCC - * Windows Server 2022, R-devel, 64 bit - * Windows Server 2008 R2 SP1, R-release, 32⁄64 bit - * Oracle Solaris 10, x86, 32 bit, R-release - * macOS 10.13.6 High Sierra, R-release, CRAN's setup +* R-CMD-check on GitHub + * macos-latest (release) + * windows-latest (release) + * ubuntu-latest (devel) + * ubuntu-latest (release) + * ubuntu-latest (oldrel-1) +* Rhub v2 + * macos-15 on GitHub, ASAN + UBSAN on macOS (`m1-san`) + * macos-13 on GitHub(`macos`) + * Fedora Linux 40 (Container Image) (`gcc-asan`) + * Ubuntu 22.04.5 LTS (`ubuntu-clang`) + * Ubuntu 22.04.5 LTS (`ubuntu-gcc12`) ## R CMD check results 0 errors | 0 warnings | 0 notes diff --git a/inst/CITATION b/inst/CITATION index 2c6d77a..e2c9789 100755 --- a/inst/CITATION +++ b/inst/CITATION @@ -3,7 +3,7 @@ bibentry(bibtype = 'manual', author = as.person('Ian D. Buller'), publisher = 'The Comprehensive R Archive Network', year = '2025', - number = '0.1.6.9015.', + number = '0.2.0.', doi = '10.32614/CRAN.package.ndi', url = 'https://cran.r-project.org/package=ndi', @@ -11,7 +11,7 @@ bibentry(bibtype = 'manual', paste('Ian D. Buller (2025)', 'ndi: Neighborhood Deprivation Indices.', 'The Comprehensive R Archive Network.', - 'v0.1.6.9015.', + 'v0.2.0.', 'DOI:10.32614/CRAN.package.ndi', 'Accessed by: https://cran.r-project.org/package=ndi'), diff --git a/man/ndi-package.Rd b/man/ndi-package.Rd index db3d027..1620169 100644 --- a/man/ndi-package.Rd +++ b/man/ndi-package.Rd @@ -88,7 +88,7 @@ Key content of the 'ndi' package include:\cr \code{\link{DCtracts2020}} A sample dataset containing information about U.S. Census American Community Survey 5-year estimate data for the District of Columbia census tracts (2020). The data are obtained from the \code{\link[tidycensus]{get_acs}} function and formatted for the \code{\link{messer}} and \code{\link{powell_wiley}} functions input. } \section{Dependencies}{ - The 'ndi' package relies heavily upon \code{\link[tidycensus]{tidycensus}} to retrieve data from the U.S. Census Bureau American Community Survey five-year estimates and the \code{\link[psych]{psych}} for computing the neighborhood deprivation indices. The \code{\link{messer}} function builds upon code developed by Hruska et al. (2022) \doi{10.17605/OSF.IO/M2SAV} by fictionalizing, adding the percent of households earning <$30,000 per year to the \emph{NDI} computation, and providing the option for computing the ACS-5 2006-2010 \emph{NDI} values. There is no code companion to compute \emph{NDI} included in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} or Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002}, but the package author worked directly with the Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} authors to replicate their SAS code in \strong{R}. The indices of racial or ethnic residential segregation rely heavily on the \code{\link[sf]{sf}} and \code{\link[tigris]{tigris}} packages to assign the smaller geographical units within larger geographical units and, occasionally, perform geospatial projection for distance-based metrics. The computation of \emph{RI} and \emph{EI} also relies on the \code{\link[Matrix]{Matrix}} package to compute the geospatial adjacency matrix between census geographies. Internal function to calculate \emph{AI} using the Hölder mean is based on \code{\link[DescTools]{Atkinson}} function. + The 'ndi' package relies heavily upon \code{\link[tidycensus]{tidycensus-package}} to retrieve data from the U.S. Census Bureau American Community Survey five-year estimates and the \code{\link[psych]{psych-package}} for computing the neighborhood deprivation indices. The \code{\link{messer}} function builds upon code developed by Hruska et al. (2022) \doi{10.17605/OSF.IO/M2SAV} by fictionalizing, adding the percent of households earning <$30,000 per year to the \emph{NDI} computation, and providing the option for computing the ACS-5 2006-2010 \emph{NDI} values. There is no code companion to compute \emph{NDI} included in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} or Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002}, but the package author worked directly with the Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} authors to replicate their SAS code in \strong{R}. The indices of racial or ethnic residential segregation rely heavily on the \code{\link[sf]{sf-package}} and \code{\link[tigris]{tigris-package}} packages to assign the smaller geographical units within larger geographical units and, occasionally, perform geospatial projection for distance-based metrics. The computation of \emph{RI} and \emph{EI} also relies on the \code{\link[Matrix]{sparseMatrix}} function to compute the geospatial adjacency matrix between census geographies. Internal function to calculate \emph{AI} using the Hölder mean is based on \code{\link[DescTools]{Atkinson}} function. } \seealso{ diff --git a/man/powell_wiley.Rd b/man/powell_wiley.Rd index 7393a21..55eaee7 100644 --- a/man/powell_wiley.Rd +++ b/man/powell_wiley.Rd @@ -64,7 +64,7 @@ The function uses the \code{\link[tidycensus]{get_acs}} function to obtain U.S. Use the internal \code{state} and \code{county} arguments within the \code{\link[tidycensus]{get_acs}} function to specify the referent for standardizing the \emph{NDI} (Powell-Wiley) values. For example, if all U.S. states are specified for the \code{state} argument, then the output would be a U.S.-standardized index. Please note: the \emph{NDI} (Powell-Wiley) values will not exactly match (but will highly correlate with) those found in Andrews et al. (2020) \doi{10.1080/17445647.2020.1750066} and Slotman et al. (2022) \doi{10.1016/j.dib.2022.108002} because the two studies used a different statistical platform (i.e., SPSS and SAS, respectively) that intrinsically calculate the principal component analysis differently from R. -The categorical \emph{NDI} (Powell-Wiley) values are population-weighted quintiles of the continuous \emph{NDI} (Powell-Wiley) values. +The categorical \emph{NDI} (Powell-Wiley) values are population-weighted quintiles of the continuous \emph{NDI} (Powell-Wiley) values. NOTE: As of version 0.2.0, population-weighted quintiles are computed using a weighted quantile function \code{\link[Hmisc]{wtd.quantile}} where values are calculated NDI and weights are Total Population instead of previously using \code{\link[stats]{quantile}} of the product of the calculated NDI and natural logarithm transformed total population. Check if the proportion of variance explained by the first principal component is high (more than 0.5). diff --git a/vignettes/ndi1.Rmd b/vignettes/ndi1.Rmd index 7a04c8d..ee6264a 100644 --- a/vignettes/ndi1.Rmd +++ b/vignettes/ndi1.Rmd @@ -70,7 +70,7 @@ A third output from the `messer()` function is a tibble containing a breakdown o messer2010GA$missing ``` -We can visualize the *NDI* (Messer) values geographically by linking them to spatial information from the [*tigris*]([*tidycensus*](https://CRAN.R-project.org/package=tigris) package and plotting with the [*ggplot2*]([*tidycensus*](https://CRAN.R-project.org/package=ggplot2) package suite. +We can visualize the *NDI* (Messer) values geographically by linking them to spatial information from the [*tigris*](https://CRAN.R-project.org/package=tigris) package and plotting with the [*ggplot2*](https://CRAN.R-project.org/package=ggplot2) package suite. ```{r messer_prep, results = 'hide'} # Obtain the 2010 counties from the 'tigris' package @@ -102,7 +102,7 @@ ggplot() + data = county2010GA, fill = 'transparent', color = 'white', - size = 0.2 + size = 0.10 ) + theme_minimal() + scale_fill_viridis_c() + @@ -135,7 +135,7 @@ ggplot() + data = county2010GA, fill = 'transparent', color = 'white', - size = 0.2 + size = 0.10 ) + theme_minimal() + scale_fill_viridis_d(guide = guide_legend(reverse = TRUE), na.value = 'grey80') + @@ -163,7 +163,7 @@ ggplot() + geom_sf( data = GA2010messer_county, aes(fill = NDI), - size = 0.20, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -190,7 +190,7 @@ ggplot() + geom_sf( data = GA2010messer_county, aes(fill = NDIQuartNA), - size = 0.20, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -256,7 +256,7 @@ A fourth output from the `powell_wiley()` function is a character string or nume powell_wiley2020DMVW$cronbach ``` -We can visualize the *NDI* (Powell-Wiley) values geographically by linking them to spatial information from the [*tigris*]([*tidycensus*](https://CRAN.R-project.org/package=tigris) package and plotting with the [*ggplot2*]([*tidycensus*](https://CRAN.R-project.org/package=ggplot2) package suite. +We can visualize the *NDI* (Powell-Wiley) values geographically by linking them to spatial information from the [*tigris*](https://CRAN.R-project.org/package=tigris) package and plotting with the [*ggplot2*](https://CRAN.R-project.org/package=ggplot2) package suite. ```{r powell_wiley_prep, results = 'hide'} # Obtain the 2020 counties from the 'tigris' package @@ -346,7 +346,7 @@ ggplot() + geom_sf( data = DMVW2020pw_county, aes(fill = NDI), - size = 0.20, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -373,7 +373,7 @@ ggplot() + geom_sf( data = DMVW2020pw_county, aes(fill = NDIQuint), - size = 0.20, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -416,7 +416,7 @@ ggplot() + geom_sf( data = DC2020pw, aes(fill = NDI_nonimp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -431,7 +431,7 @@ ggplot() + geom_sf( data = DC2020pw, aes(fill = NDI_imp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -458,7 +458,7 @@ ggplot() + geom_sf( data = DC2020pw, aes(fill = NDIQuintNA_nonimp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -484,7 +484,7 @@ ggplot() + geom_sf( data = DC2020pw, aes(fill = NDIQuintNA_imp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + diff --git a/vignettes/ndi1.html b/vignettes/ndi1.html index 231e72f..874413d 100644 --- a/vignettes/ndi1.html +++ b/vignettes/ndi1.html @@ -12,7 +12,7 @@ - + 1. Neighborhood Deprivation Indices @@ -340,7 +340,7 @@

1. Neighborhood Deprivation Indices

Ian D. Buller (GitHub: @idblr)

-

2024-08-29

+

2025-08-29

@@ -495,8 +495,8 @@

Compute NDI (Messer)

## 7 PUB 1969 14 0.71 % ## 8 U30 1969 14 0.71 %

We can visualize the NDI (Messer) values geographically by -linking them to spatial information from the [tigris](tidycensus -package and plotting with the [ggplot2](tidycensus +linking them to spatial information from the tigris +package and plotting with the ggplot2 package suite.

# Obtain the 2010 counties from the 'tigris' package
 county2010GA <- counties(state = 'GA', year = 2010, cb = TRUE)
@@ -524,7 +524,7 @@ 
Compute NDI (Messer)

     data = county2010GA,
     fill = 'transparent',
     color = 'white',
-    size = 0.2
+    size = 0.10
   ) +
   theme_minimal() +
   scale_fill_viridis_c() +
@@ -557,7 +557,7 @@ 
Compute NDI (Messer)

     data = county2010GA,
     fill = 'transparent',
     color = 'white',
-    size = 0.2
+    size = 0.10
   ) +
   theme_minimal() +
   scale_fill_viridis_d(guide = guide_legend(reverse = TRUE), na.value = 'grey80') +
@@ -566,7 +566,7 @@ 
Compute NDI (Messer)

     'Neighborhood Deprivation Index (Messer) Quartiles',
     subtitle = 'GA census tracts as the referent'
   )
-

+

The results above are at the tract level. The NDI (Messer) values can also be calculated at the county level.

messer2010GA_county <- messer(geo = 'county', state = 'GA', year = 2010)
@@ -580,7 +580,7 @@ 
Compute NDI (Messer)

   geom_sf(
     data = GA2010messer_county,
     aes(fill = NDI),
-    size = 0.20,
+    size = 0.10,
     color = 'white'
   ) +
   theme_minimal() +
@@ -607,7 +607,7 @@ 
Compute NDI (Messer)

   geom_sf(
     data = GA2010messer_county,
     aes(fill = NDIQuartNA),
-    size = 0.20,
+    size = 0.10,
     color = 'white'
   ) +
   theme_minimal() +
@@ -617,7 +617,7 @@ 
Compute NDI (Messer)

     'Neighborhood Deprivation Index (Messer) Quartiles',
     subtitle = 'GA counties as the referent'
   )
-

+

Compute NDI (Powell-Wiley)

@@ -863,9 +863,8 @@

Compute NDI (Powell-Wiley)

powell_wiley2020DMVW$cronbach
## [1] 0.9321693

We can visualize the NDI (Powell-Wiley) values -geographically by linking them to spatial information from the -[tigris](tidycensus -package and plotting with the [ggplot2](tidycensus +geographically by linking them to spatial information from the tigris +package and plotting with the ggplot2 package suite.

# Obtain the 2020 counties from the 'tigris' package
 county2020 <- counties(cb = TRUE)
@@ -923,7 +922,7 @@ 
Compute NDI (Powell-Wiley)

     'Neighborhood Deprivation Index (Powell-Wiley) Population-weighted Quintiles',
     subtitle = 'DC, MD, VA, and WV tracts as the referent'
   )
-

+

Like the NDI (Messer), we also compute county-level NDI (Powell-Wiley).

# Obtain the 2020 counties from the 'tigris' package
@@ -946,7 +945,7 @@ 
Compute NDI (Powell-Wiley)

   geom_sf(
     data = DMVW2020pw_county,
     aes(fill = NDI),
-    size = 0.20,
+    size = 0.10,
     color = 'white'
   ) +
   theme_minimal() +
@@ -973,7 +972,7 @@ 
Compute NDI (Powell-Wiley)

   geom_sf(
     data = DMVW2020pw_county,
     aes(fill = NDIQuint),
-    size = 0.20,
+    size = 0.10,
     color = 'white'
   ) +
   theme_minimal() +
@@ -983,7 +982,7 @@ 
Compute NDI (Powell-Wiley)

     'Neighborhood Deprivation Index (Powell-Wiley) Population-weighted Quintiles',
     subtitle = 'DC, MD, VA, and WV counties as the referent'
   )
-

+

Advanced Features

@@ -1018,7 +1017,7 @@

Imputing missing census variables

geom_sf( data = DC2020pw, aes(fill = NDI_nonimp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -1033,7 +1032,7 @@

Imputing missing census variables

geom_sf( data = DC2020pw, aes(fill = NDI_imp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -1060,7 +1059,7 @@

Imputing missing census variables

geom_sf( data = DC2020pw, aes(fill = NDIQuintNA_nonimp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -1086,7 +1085,7 @@

Imputing missing census variables

geom_sf( data = DC2020pw, aes(fill = NDIQuintNA_imp), - size = 0.2, + size = 0.10, color = 'white' ) + theme_minimal() + @@ -1096,7 +1095,7 @@

Imputing missing census variables

'Neighborhood Deprivation Index (Powell-Wiley) Quintiles, Imputed', subtitle = 'DC census tracts as the referent' )
-

+

Assign the referent (U.S.-Standardized Metric)

@@ -1130,17 +1129,17 @@

Assign the referent (U.S.-Standardized Metric)

'Histogram of US-standardized NDI (Powell-Wiley) values (2013-2017)', subtitle = 'U.S. census tracts as the referent (including AK, HI, and DC)' )
-

+

The process to compute a US-standardized NDI (Powell-Wiley) -took about 4.5 minutes to run on a machine with the features listed at +took about 12.7 minutes to run on a machine with the features listed at the end of the vignette.

sessionInfo()
-
## R version 4.4.1 (2024-06-14 ucrt)
+
## R version 4.5.1 (2025-06-13 ucrt)
 ## Platform: x86_64-w64-mingw32/x64
-## Running under: Windows 10 x64 (build 19045)
+## Running under: Windows 11 x64 (build 26100)
 ## 
 ## Matrix products: default
-## 
+##   LAPACK version 3.12.1
 ## 
 ## locale:
 ## [1] LC_COLLATE=English_United States.utf8 
@@ -1156,28 +1155,31 @@ 
Assign the referent (U.S.-Standardized Metric)

 ## [1] stats     graphics  grDevices utils     datasets  methods   base     
 ## 
 ## other attached packages:
-## [1] tigris_2.1       tidycensus_1.6.5 sf_1.0-16        ndi_0.1.6.9007  
-## [5] ggplot2_3.5.1    dplyr_1.1.4      knitr_1.48      
+## [1] tigris_2.2.1     tidycensus_1.7.3 sf_1.0-21        ndi_0.2.0       
+## [5] ggplot2_3.5.2    dplyr_1.1.4      knitr_1.50      
 ## 
 ## loaded via a namespace (and not attached):
-##  [1] gtable_0.3.5       xfun_0.47          bslib_0.8.0        psych_2.4.6.26    
-##  [5] lattice_0.22-6     tzdb_0.4.0         Cairo_1.6-2        vctrs_0.6.5       
-##  [9] tools_4.4.1        generics_0.1.3     curl_5.2.2         parallel_4.4.1    
-## [13] tibble_3.2.1       proxy_0.4-27       fansi_1.0.6        highr_0.11        
-## [17] pkgconfig_2.0.3    Matrix_1.7-0       KernSmooth_2.23-24 uuid_1.2-1        
-## [21] lifecycle_1.0.4    farver_2.1.2       compiler_4.4.1     stringr_1.5.1     
-## [25] munsell_0.5.1      mnormt_2.1.1       carData_3.0-5      htmltools_0.5.8.1 
-## [29] class_7.3-22       sass_0.4.9         yaml_2.3.10        pillar_1.9.0      
-## [33] car_3.1-2          crayon_1.5.3       jquerylib_0.1.4    tidyr_1.3.1       
-## [37] MASS_7.3-61        classInt_0.4-10    cachem_1.1.0       abind_1.4-5       
-## [41] nlme_3.1-166       tidyselect_1.2.1   rvest_1.0.4        digest_0.6.36     
-## [45] stringi_1.8.4      purrr_1.0.2        labeling_0.4.3     fastmap_1.2.0     
-## [49] grid_4.4.1         colorspace_2.1-1   cli_3.6.3          magrittr_2.0.3    
-## [53] utf8_1.2.4         e1071_1.7-14       readr_2.1.5        withr_3.0.1       
-## [57] scales_1.3.0       rappdirs_0.3.3     rmarkdown_2.28     httr_1.4.7        
-## [61] hms_1.1.3          evaluate_0.24.0    viridisLite_0.4.2  rlang_1.1.4       
-## [65] Rcpp_1.0.13        glue_1.7.0         DBI_1.2.3          xml2_1.3.6        
-## [69] rstudioapi_0.16.0  jsonlite_1.8.8     R6_2.5.1           units_0.8-5

+##  [1] tidyselect_1.2.1   psych_2.5.6        viridisLite_0.4.2  farver_2.1.2      
+##  [5] fastmap_1.2.0      digest_0.6.37      rpart_4.1.24       lifecycle_1.0.4   
+##  [9] cluster_2.1.8.1    Cairo_1.6-2        magrittr_2.0.3     compiler_4.5.1    
+## [13] rlang_1.1.6        Hmisc_5.2-3        sass_0.4.10        tools_4.5.1       
+## [17] utf8_1.2.6         yaml_2.3.10        data.table_1.17.8  labeling_0.4.3    
+## [21] htmlwidgets_1.6.4  classInt_0.4-11    mnormt_2.1.1       curl_6.4.0        
+## [25] xml2_1.3.8         RColorBrewer_1.1-3 abind_1.4-8        KernSmooth_2.23-26
+## [29] withr_3.0.2        foreign_0.8-90     purrr_1.1.0        nnet_7.3-20       
+## [33] grid_4.5.1         e1071_1.7-16       colorspace_2.1-1   scales_1.4.0      
+## [37] MASS_7.3-65        cli_3.6.5          rmarkdown_2.29     crayon_1.5.3      
+## [41] generics_0.1.4     rstudioapi_0.17.1  httr_1.4.7         tzdb_0.5.0        
+## [45] DBI_1.2.3          cachem_1.1.0       proxy_0.4-27       stringr_1.5.1     
+## [49] rvest_1.0.4        parallel_4.5.1     base64enc_0.1-3    vctrs_0.6.5       
+## [53] Matrix_1.7-3       jsonlite_2.0.0     carData_3.0-5      car_3.1-3         
+## [57] hms_1.1.3          Formula_1.2-5      htmlTable_2.4.3    jquerylib_0.1.4   
+## [61] tidyr_1.3.1        units_0.8-7        glue_1.8.0         stringi_1.8.7     
+## [65] gtable_0.3.6       tibble_3.3.0       pillar_1.11.0      rappdirs_0.3.3    
+## [69] htmltools_0.5.8.1  R6_2.6.1           evaluate_1.0.5     lattice_0.22-7    
+## [73] readr_2.1.5        backports_1.5.0    bslib_0.9.0        class_7.3-23      
+## [77] Rcpp_1.1.0         uuid_1.2-1         gridExtra_2.3      nlme_3.1-168      
+## [81] checkmate_2.3.2    xfun_0.52          pkgconfig_2.0.3
diff --git a/vignettes/ndi2.html b/vignettes/ndi2.html index 7e60f77..6c7905f 100644 --- a/vignettes/ndi2.html +++ b/vignettes/ndi2.html @@ -12,7 +12,7 @@ - + 2. Racial or Ethnic Residential Segregation Indices @@ -341,7 +341,7 @@

2. Racial or Ethnic Residential Segregation Indices

Ian D. Buller (GitHub: @idblr)

-

2025-05-30

+

2025-08-29

@@ -621,7 +621,7 @@

Compute Dissimilarity Index (D)

'Dissimilarity Index (James & Taeuber)\nCensus tracts within counties of Pennsylvania', subtitle = 'Black population' ) -

+

The racial or ethnic Gini Index (G)

@@ -673,7 +673,7 @@

The racial or ethnic Gini Index (G)

'Gini Index (Gini)\nCensus tracts within counties of Massachusetts', subtitle = 'Black population' )
-

+

Compute Entropy (H)

@@ -731,7 +731,7 @@

Compute Entropy (H)

'Entropy (Theil)\nCensus tracts within Metro Divisions of Pennsylvania', subtitle = 'Black population' )
-

+

Compute Atkinson Index (A)

@@ -802,7 +802,7 @@

Compute Atkinson Index (A)

'Atkinson Index (Atkinson)\nCensus block groups within counties of Kentucky', subtitle = expression(paste('Black non-Hispanic (', epsilon, ' = 0.67)')) )
-

+

Compute Dissimilarity Index (D)

@@ -858,7 +858,7 @@

Compute Dissimilarity Index (D)

'Dissimilarity Index (Duncan & Duncan)\nCensus tracts within counties of Pennsylvania', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Location Quotient (LQ)

@@ -912,7 +912,7 @@

Compute Location Quotient (LQ)

'Location Quotient (Sudano)\nCounties within state of Tennessee', subtitle = 'Black non-Hispanic' )
-

+

Compute Interaction Index (xPy*)

@@ -962,7 +962,7 @@

Compute Interaction Index (xPy*)

'Interaction Index (Bell)\nCensus tracts within counties of Ohio', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Isolation Index (xPx*)

@@ -1012,7 +1012,7 @@

Compute Isolation Index (xPx*)

'Isolation Index (Lieberson)\nCensus block groups within census tracts of Delaware', subtitle = 'Black non-Hispanic' )
-

+

Compute Correlation Ratio (V)

@@ -1063,7 +1063,7 @@

Compute Correlation Ratio (V)

'Correlation Ratio (White)\nCensus tracts within counties of South Carolina', subtitle = 'Black non-Hispanic' )
-

+

Compute Local Exposure and Isolation (LEx/Is)

@@ -1131,7 +1131,7 @@

Compute Local Exposure and Isolation (LEx/Is)

'Local Exposure and Isolation (Bemanian & Beyer)\nCounties within state of Mississippi', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

# Visualize the exponentiated LEx/Is values (2017-2021 5-year ACS) for Counties within state of Mississippi
 ggplot() +
   geom_sf(
@@ -1153,7 +1153,7 @@ 
Compute Local Exposure and Isolation (LEx/Is)

     'Odds ratio of Local Exposure and Isolation (Bemanian & Beyer)\nCounties within state of Mississippi',
     subtitle = 'Black non-Hispanic vs. white non-Hispanic'
   )
-

+

Compute Racial Isolation Index (RI)

@@ -1207,7 +1207,7 @@

Compute Racial Isolation Index (RI)

'Racial Isolation Index (Anthopolos)\nCensus tracts of North Carolina', subtitle = 'Black Non-Hispanic populations (not corrected for edge effects)' )
-

+

The current version of the ndi package does not correct for edge effects (e.g., census geographies along the specified spatial extent border, coastline, or U.S.-Mexico / U.S.-Canada @@ -1260,7 +1260,7 @@

Compute Racial Isolation Index (RI)

'Racial Isolation Index (Anthopolos)\nCensus tracts of North Carolina', subtitle = 'Black Non-Hispanic populations (corrected for interstate edge effects)' ) -

+

Compute Delta (DEL)

@@ -1308,7 +1308,7 @@

Compute Delta (DEL)

'Delta (Hoover)\nCensus tracts within counties within Alabama', subtitle = 'Black Non-Hispanic population' )
-

+

Compute Relative Concentration (RCO)

@@ -1372,7 +1372,7 @@

Compute Relative Concentration (RCO)

'Relative Concentration (Massey & Duncan)\nCensus tracts within core-based statistical areas of Wisconsin', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Absolute Concentration (ACO)

@@ -1429,7 +1429,7 @@

Compute Absolute Concentration (ACO)

'Absolute Concentration (Massey & Duncan)\nCensus tracts within core-based statistical areas of Wisconsin', subtitle = 'Black population' )
-

+

Compute Absolute Centralization (ACE)

@@ -1501,7 +1501,7 @@

Compute Absolute Centralization (ACE)

'Absolute Centralization (Duncan & Cuzzort)\nCensus block groups within census-designated places of Connecticut', subtitle = 'Black population' )
-

+

Compute Relative Centralization (RCE)

@@ -1578,7 +1578,7 @@

Compute Relative Centralization (RCE)

'Relative Centralization (Duncan & Duncan)\nCensus block groups within census-designated places of Connecticut', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Absolute Clustering (ACL)

@@ -1639,7 +1639,7 @@

Compute Absolute Clustering (ACL)

'Absolute Clustering (Massey & Denton)\nCensus block groups within census tracts of Harris County, TX', subtitle = 'Black population' )
-

+

Compute an index of spatial proximity (SP)

@@ -1704,7 +1704,7 @@

Compute an index of spatial proximity (SP)

'An index of spatial proximity (White)\nCensus tracts within combined statistical areas of Georgia', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Relative Clustering (RCL)

@@ -1765,7 +1765,7 @@

Compute Relative Clustering (RCL)

'Relative Clustering (Massey & Denton)\nCensus block groups within census tracts of Harris County, TX', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Distance-Decay Isolation Index (DPxy*)

@@ -1819,7 +1819,7 @@

Compute Distance-Decay Isolation Index (DPxy*)

'Distance-Decay Interaction Index (Morgan)\nCensus tracts within core-based statistical areas of Louisiana', subtitle = 'Black non-Hispanic vs. white non-Hispanic' )
-

+

Compute Distance-Decay Isolation Index (DPxx*)

@@ -1872,14 +1872,14 @@

Compute Distance-Decay Isolation Index (DPxx*)

'Distance-Decay Isolation Index (Morgan)\nCensus tracts within core-based statistical areas of Louisiana', subtitle = 'Black population' )
-

+

sessionInfo()
-
## R version 4.4.1 (2024-06-14 ucrt)
+
## R version 4.5.1 (2025-06-13 ucrt)
 ## Platform: x86_64-w64-mingw32/x64
-## Running under: Windows 10 x64 (build 19045)
+## Running under: Windows 11 x64 (build 26100)
 ## 
 ## Matrix products: default
-## 
+##   LAPACK version 3.12.1
 ## 
 ## locale:
 ## [1] LC_COLLATE=English_United States.utf8 
@@ -1895,28 +1895,31 @@ 
Compute Distance-Decay Isolation Index (DPxx*)

 ## [1] stats     graphics  grDevices utils     datasets  methods   base     
 ## 
 ## other attached packages:
-## [1] tigris_2.2.1     tidycensus_1.7.1 sf_1.0-21        ndi_0.1.6.9015  
-## [5] ggplot2_3.5.2    dplyr_1.1.4      knitr_1.48      
+## [1] tigris_2.2.1     tidycensus_1.7.3 sf_1.0-21        ndi_0.2.0       
+## [5] ggplot2_3.5.2    dplyr_1.1.4      knitr_1.50      
 ## 
 ## loaded via a namespace (and not attached):
-##  [1] gtable_0.3.6       xfun_0.47          bslib_0.8.0        psych_2.5.3       
-##  [5] lattice_0.22-6     tzdb_0.5.0         Cairo_1.6-2        vctrs_0.6.5       
-##  [9] tools_4.4.1        generics_0.1.4     curl_6.2.3         parallel_4.4.1    
-## [13] tibble_3.2.1       proxy_0.4-27       highr_0.11         pkgconfig_2.0.3   
-## [17] Matrix_1.7-0       KernSmooth_2.23-24 RColorBrewer_1.1-3 uuid_1.2-1        
-## [21] lifecycle_1.0.4    compiler_4.4.1     farver_2.1.2       stringr_1.5.1     
-## [25] mnormt_2.1.1       carData_3.0-5      htmltools_0.5.8.1  class_7.3-22      
-## [29] sass_0.4.9         yaml_2.3.10        Formula_1.2-5      pillar_1.10.2     
-## [33] car_3.1-3          crayon_1.5.3       jquerylib_0.1.4    tidyr_1.3.1       
-## [37] MASS_7.3-61        classInt_0.4-11    cachem_1.1.0       wk_0.9.4          
-## [41] abind_1.4-8        nlme_3.1-166       tidyselect_1.2.1   rvest_1.0.4       
-## [45] digest_0.6.36      stringi_1.8.7      purrr_1.0.4        labeling_0.4.3    
-## [49] fastmap_1.2.0      grid_4.4.1         cli_3.6.5          magrittr_2.0.3    
-## [53] e1071_1.7-16       readr_2.1.5        withr_3.0.2        scales_1.4.0      
-## [57] rappdirs_0.3.3     rmarkdown_2.28     httr_1.4.7         hms_1.1.3         
-## [61] evaluate_0.24.0    viridisLite_0.4.2  s2_1.1.9           rlang_1.1.6       
-## [65] Rcpp_1.0.14        glue_1.8.0         DBI_1.2.3          xml2_1.3.8        
-## [69] rstudioapi_0.16.0  jsonlite_2.0.0     R6_2.6.1           units_0.8-7

+##  [1] tidyselect_1.2.1   psych_2.5.6        viridisLite_0.4.2  farver_2.1.2      
+##  [5] fastmap_1.2.0      digest_0.6.37      rpart_4.1.24       lifecycle_1.0.4   
+##  [9] cluster_2.1.8.1    Cairo_1.6-2        magrittr_2.0.3     compiler_4.5.1    
+## [13] rlang_1.1.6        Hmisc_5.2-3        sass_0.4.10        tools_4.5.1       
+## [17] yaml_2.3.10        data.table_1.17.8  labeling_0.4.3     htmlwidgets_1.6.4 
+## [21] classInt_0.4-11    mnormt_2.1.1       curl_6.4.0         xml2_1.3.8        
+## [25] RColorBrewer_1.1-3 abind_1.4-8        KernSmooth_2.23-26 withr_3.0.2       
+## [29] foreign_0.8-90     purrr_1.1.0        nnet_7.3-20        grid_4.5.1        
+## [33] e1071_1.7-16       colorspace_2.1-1   scales_1.4.0       MASS_7.3-65       
+## [37] cli_3.6.5          rmarkdown_2.29     crayon_1.5.3       generics_0.1.4    
+## [41] rstudioapi_0.17.1  httr_1.4.7         tzdb_0.5.0         DBI_1.2.3         
+## [45] cachem_1.1.0       proxy_0.4-27       stringr_1.5.1      rvest_1.0.4       
+## [49] parallel_4.5.1     s2_1.1.9           base64enc_0.1-3    vctrs_0.6.5       
+## [53] Matrix_1.7-3       jsonlite_2.0.0     carData_3.0-5      car_3.1-3         
+## [57] hms_1.1.3          Formula_1.2-5      htmlTable_2.4.3    jquerylib_0.1.4   
+## [61] tidyr_1.3.1        units_0.8-7        glue_1.8.0         stringi_1.8.7     
+## [65] gtable_0.3.6       tibble_3.3.0       pillar_1.11.0      rappdirs_0.3.3    
+## [69] htmltools_0.5.8.1  R6_2.6.1           wk_0.9.4           evaluate_1.0.5    
+## [73] lattice_0.22-7     readr_2.1.5        backports_1.5.0    bslib_0.9.0       
+## [77] class_7.3-23       Rcpp_1.1.0         uuid_1.2-1         gridExtra_2.3     
+## [81] nlme_3.1-168       checkmate_2.3.2    xfun_0.52          pkgconfig_2.0.3
diff --git a/vignettes/ndi3.html b/vignettes/ndi3.html index 805bf98..611a8c6 100644 --- a/vignettes/ndi3.html +++ b/vignettes/ndi3.html @@ -12,7 +12,7 @@ - + 3. Additional indices of socioeconomic disparity @@ -341,7 +341,7 @@

3. Additional indices of socioeconomic disparity

Ian D. Buller (GitHub: @idblr)

-

2024-08-30

+

2025-08-29

@@ -445,7 +445,7 @@

Compute income Atkinson Index (A)

'Atkinson Index (Atkinson)\nCensus block groups within counties of Kentucky', subtitle = expression(paste('Median Household Income (', epsilon, ' = 0.33)')) ) -

+

Compute Educational Isolation Index (EI)

@@ -537,7 +537,7 @@

Compute Educational Isolation Index (EI)

'Educational Isolation Index (Bravo)\nCensus tracts of Oklahoma', subtitle = 'Without a four-year college degree (not corrected for edge effects)' )
-

+

Can correct one source of edge effect in the same manner as shown for the RI metric in vignette 2. Racial or Ethnic Residential Segregation Indices

@@ -604,7 +604,7 @@

The income Gini Index (G)

'Gini Index (Gini)\nCensus tracts within counties of Massachusetts', subtitle = 'Median Household Income' ) -

+

Index of Concentration at the Extremes (ICE)

@@ -789,14 +789,14 @@

Index of Concentration at the Extremes (ICE)

'Index of Concentration at the Extremes (Krieger)\nIncome & race or ethnicity combined', subtitle = 'white non-Hispanic (WNH) in 80th inc pctl vs. WNH in 20th inc pctl' )
-

+

sessionInfo()
-
## R version 4.4.1 (2024-06-14 ucrt)
+
## R version 4.5.1 (2025-06-13 ucrt)
 ## Platform: x86_64-w64-mingw32/x64
-## Running under: Windows 10 x64 (build 19045)
+## Running under: Windows 11 x64 (build 26100)
 ## 
 ## Matrix products: default
-## 
+##   LAPACK version 3.12.1
 ## 
 ## locale:
 ## [1] LC_COLLATE=English_United States.utf8 
@@ -812,28 +812,31 @@ 
Index of Concentration at the Extremes (ICE)

 ## [1] stats     graphics  grDevices utils     datasets  methods   base     
 ## 
 ## other attached packages:
-## [1] tigris_2.1       tidycensus_1.6.5 sf_1.0-16        ndi_0.1.6.9008  
-## [5] ggplot2_3.5.1    dplyr_1.1.4      knitr_1.48      
+## [1] tigris_2.2.1     tidycensus_1.7.3 sf_1.0-21        ndi_0.2.0       
+## [5] ggplot2_3.5.2    dplyr_1.1.4      knitr_1.50      
 ## 
 ## loaded via a namespace (and not attached):
-##  [1] gtable_0.3.5       xfun_0.47          bslib_0.8.0        psych_2.4.6.26    
-##  [5] lattice_0.22-6     tzdb_0.4.0         Cairo_1.6-2        vctrs_0.6.5       
-##  [9] tools_4.4.1        generics_0.1.3     curl_5.2.2         parallel_4.4.1    
-## [13] tibble_3.2.1       proxy_0.4-27       fansi_1.0.6        highr_0.11        
-## [17] pkgconfig_2.0.3    Matrix_1.7-0       KernSmooth_2.23-24 uuid_1.2-1        
-## [21] lifecycle_1.0.4    farver_2.1.2       compiler_4.4.1     stringr_1.5.1     
-## [25] munsell_0.5.1      mnormt_2.1.1       carData_3.0-5      htmltools_0.5.8.1 
-## [29] class_7.3-22       sass_0.4.9         yaml_2.3.10        pillar_1.9.0      
-## [33] car_3.1-2          crayon_1.5.3       jquerylib_0.1.4    tidyr_1.3.1       
-## [37] MASS_7.3-61        classInt_0.4-10    cachem_1.1.0       abind_1.4-5       
-## [41] nlme_3.1-166       tidyselect_1.2.1   rvest_1.0.4        digest_0.6.36     
-## [45] stringi_1.8.4      purrr_1.0.2        labeling_0.4.3     fastmap_1.2.0     
-## [49] grid_4.4.1         colorspace_2.1-1   cli_3.6.3          magrittr_2.0.3    
-## [53] utf8_1.2.4         e1071_1.7-14       readr_2.1.5        withr_3.0.1       
-## [57] scales_1.3.0       rappdirs_0.3.3     rmarkdown_2.28     httr_1.4.7        
-## [61] hms_1.1.3          evaluate_0.24.0    viridisLite_0.4.2  rlang_1.1.4       
-## [65] Rcpp_1.0.13        glue_1.7.0         DBI_1.2.3          xml2_1.3.6        
-## [69] rstudioapi_0.16.0  jsonlite_1.8.8     R6_2.5.1           units_0.8-5

+##  [1] tidyselect_1.2.1   psych_2.5.6        viridisLite_0.4.2  farver_2.1.2      
+##  [5] fastmap_1.2.0      digest_0.6.37      rpart_4.1.24       lifecycle_1.0.4   
+##  [9] cluster_2.1.8.1    Cairo_1.6-2        magrittr_2.0.3     compiler_4.5.1    
+## [13] rlang_1.1.6        Hmisc_5.2-3        sass_0.4.10        tools_4.5.1       
+## [17] yaml_2.3.10        data.table_1.17.8  labeling_0.4.3     htmlwidgets_1.6.4 
+## [21] classInt_0.4-11    mnormt_2.1.1       curl_6.4.0         xml2_1.3.8        
+## [25] RColorBrewer_1.1-3 abind_1.4-8        KernSmooth_2.23-26 withr_3.0.2       
+## [29] foreign_0.8-90     purrr_1.1.0        nnet_7.3-20        grid_4.5.1        
+## [33] e1071_1.7-16       colorspace_2.1-1   scales_1.4.0       MASS_7.3-65       
+## [37] cli_3.6.5          rmarkdown_2.29     crayon_1.5.3       generics_0.1.4    
+## [41] rstudioapi_0.17.1  httr_1.4.7         tzdb_0.5.0         DBI_1.2.3         
+## [45] cachem_1.1.0       proxy_0.4-27       stringr_1.5.1      rvest_1.0.4       
+## [49] parallel_4.5.1     base64enc_0.1-3    vctrs_0.6.5        Matrix_1.7-3      
+## [53] jsonlite_2.0.0     carData_3.0-5      car_3.1-3          hms_1.1.3         
+## [57] Formula_1.2-5      htmlTable_2.4.3    jquerylib_0.1.4    tidyr_1.3.1       
+## [61] units_0.8-7        glue_1.8.0         stringi_1.8.7      gtable_0.3.6      
+## [65] tibble_3.3.0       pillar_1.11.0      rappdirs_0.3.3     htmltools_0.5.8.1 
+## [69] R6_2.6.1           evaluate_1.0.5     lattice_0.22-7     readr_2.1.5       
+## [73] backports_1.5.0    bslib_0.9.0        class_7.3-23       Rcpp_1.1.0        
+## [77] uuid_1.2-1         gridExtra_2.3      nlme_3.1-168       checkmate_2.3.2   
+## [81] xfun_0.52          pkgconfig_2.0.3