The R package melig contains information on Medicaid income
eligibility limits, collected by the Kaiser Family
Foundation.
It includes the following datasets:
children.rda:- Medicaid Income Eligibility Limits for Infants Ages 0–1, 2000–2023
- Medicaid Income Eligibility Limits for Children Ages 1–5, 2000–2023
- Medicaid Income Eligibility Limits for Children Ages 6–18, 2000–2023
- Separate Children’s Health Insurance Program (CHIP) Income Eligibility Limits for Children, 2000–2023
- Medicaid/CHIP Upper Income Eligibility Limits for Children, 2000–2023
prenant_wom.rda: Medicaid and CHIP Income Eligibility Limits for Pregnant Women, 2003–2023parents.rda: Medicaid Income Eligibility Limits for Parents, 2002–2023childless_adults.rda: Medicaid Income Eligibility Limits for Other Non-Disabled Adults, 2011–2023
The datasets are stored in long format.
The
/data-raw/
folder contains raw data and R scripts.
You can install melig from Github with:
# install.packages("remotes") # Install the development version remotes::install_github("jjchern/melig") # Install the released version remotes::install_github("jjchern/melig@v0.1.0") # To uninstall the package, use: # remove.packages("melig")
- Medicaid Income Eligibility Limits (Most Recent Data)
- Annual Updates on Eligibility Rules, Enrollment and Renewal Procedures, and Cost-Sharing Practices in Medicaid and CHIP
×ばつ 2 #> Package Item #> <chr> <chr> #> 1 melig childless_adults #> 2 melig children #> 3 melig parents #> 4 melig pregnant_women # The datasets are in long format melig::parents #> # A tibble: 1,092 ×ばつ 6 #> state fips usps month year cutoff #> <chr> <chr> <chr> <chr> <int> <dbl> #> 1 United States <NA> <NA> January 2002 68 #> 2 Alabama 01 AL January 2002 21 #> 3 Alaska 02 AK January 2002 79 #> 4 Arizona 04 AZ January 2002 107 #> 5 Arkansas 05 AR January 2002 21 #> 6 California 06 CA January 2002 107 #> 7 Colorado 08 CO January 2002 42 #> 8 Connecticut 09 CT January 2002 157 #> 9 Delaware 10 DE January 2002 122 #> 10 District of Columbia 11 DC January 2002 200 #> # i 1,082 more rows # But you can always convert them back to the original wide format melig::parents %>% unite_("monyear", c("month", "year"), sep = " ") %>% spread(monyear, cutoff) #> # A tibble: 52 ×ばつ 24 #> state fips usps `April 2003` `December 2009` `January 2002` `January 2008` #> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 Alaba... 01 AL 20 24 21 26 #> 2 Alaska 02 AK 81 81 79 81 #> 3 Arizo... 04 AZ 200 106 107 200 #> 4 Arkan... 05 AR 20 17 21 18 #> 5 Calif... 06 CA 107 106 107 106 #> 6 Color... 08 CO 47 66 42 66 #> 7 Conne... 09 CT 107 191 157 191 #> 8 Delaw... 10 DE 120 121 122 106 #> 9 Distr... 11 DC 200 207 200 207 #> 10 Flori... 12 FL 63 53 66 56 #> # i 42 more rows #> # i 17 more variables: `January 2009` <dbl>, `January 2011` <dbl>, #> # `January 2012` <dbl>, `January 2013` <dbl>, `January 2014` <dbl>, #> # `January 2015` <dbl>, `January 2016` <dbl>, `January 2017` <dbl>, #> # `January 2018` <dbl>, `January 2019` <dbl>, `January 2020` <dbl>, #> # `January 2021` <dbl>, `January 2022` <dbl>, `January 2023` <dbl>, #> # `July 2004` <dbl>, `July 2005` <dbl>, `July 2006` <dbl>">
library(tidyverse) library(formattable) # List all available datasets data(package = "melig") %>% pluck("results") %>% as_tibble() %>% select(Package, Item) #> # A tibble: 4 ×ばつ 2 #> Package Item #> <chr> <chr> #> 1 melig childless_adults #> 2 melig children #> 3 melig parents #> 4 melig pregnant_women # The datasets are in long format melig::parents #> # A tibble: 1,092 ×ばつ 6 #> state fips usps month year cutoff #> <chr> <chr> <chr> <chr> <int> <dbl> #> 1 United States <NA> <NA> January 2002 68 #> 2 Alabama 01 AL January 2002 21 #> 3 Alaska 02 AK January 2002 79 #> 4 Arizona 04 AZ January 2002 107 #> 5 Arkansas 05 AR January 2002 21 #> 6 California 06 CA January 2002 107 #> 7 Colorado 08 CO January 2002 42 #> 8 Connecticut 09 CT January 2002 157 #> 9 Delaware 10 DE January 2002 122 #> 10 District of Columbia 11 DC January 2002 200 #> # i 1,082 more rows # But you can always convert them back to the original wide format melig::parents %>% unite_("monyear", c("month", "year"), sep = " ") %>% spread(monyear, cutoff) #> # A tibble: 52 ×ばつ 24 #> state fips usps `April 2003` `December 2009` `January 2002` `January 2008` #> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 Alaba... 01 AL 20 24 21 26 #> 2 Alaska 02 AK 81 81 79 81 #> 3 Arizo... 04 AZ 200 106 107 200 #> 4 Arkan... 05 AR 20 17 21 18 #> 5 Calif... 06 CA 107 106 107 106 #> 6 Color... 08 CO 47 66 42 66 #> 7 Conne... 09 CT 107 191 157 191 #> 8 Delaw... 10 DE 120 121 122 106 #> 9 Distr... 11 DC 200 207 200 207 #> 10 Flori... 12 FL 63 53 66 56 #> # i 42 more rows #> # i 17 more variables: `January 2009` <dbl>, `January 2011` <dbl>, #> # `January 2012` <dbl>, `January 2013` <dbl>, `January 2014` <dbl>, #> # `January 2015` <dbl>, `January 2016` <dbl>, `January 2017` <dbl>, #> # `January 2018` <dbl>, `January 2019` <dbl>, `January 2020` <dbl>, #> # `January 2021` <dbl>, `January 2022` <dbl>, `January 2023` <dbl>, #> # `July 2004` <dbl>, `July 2005` <dbl>, `July 2006` <dbl>
# save as Stata format haven::write_dta(melig::parents, "pa0218.dta") # or rio::export(melig::parents, "pa0218.dta")
Or download the *.rda file and try the
rioweb made by
@lbraglia.
For a more detailed exploration of the Medicaid income eligibility cutoffs data, check out the vignette. To access the vignette within R, after installing the package, you can view the vignette using the following command in your R console:
vignette("medicaid-income-eligibility-cutoffs-overview")