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#' @name county_month_birth_rate
#' @aliases county_month_birth_rate_2005_version county_month_birth_rate_2014_version
#' @docType data
#' @title Monthly Growth Fertility Rates (GFR) for 12 urban Oklahoma counties
#' @description Monthly Growth Fertility Rates (GFR) for 12 urban counties in Oklahoma
#' between January 1990 and December 1999.
#' The GFR is defined as the number of births divided
#' by the number of females (ages 15-44), multiplied by 1,000.
#'
#' There are two datasets in this package that are almost identical.
#' The 2014 version is better suited for substantive researchers
#' in the areas of fertility and traumatic cultural events.
#' The 2005 version recreates the 2005 article
#' and, therefore is better suited for the graphical aims of the 2014 manuscript.
#'
#' The difference is that the 2005 version uses constant estimate for a county population
#' --specifically the US Census 1990 estimates. The 2014 version uses different estimates
#' for each month --specifically the US intercensal annual estimates, with linear interpolation
#' for February through December of each year.
#'
#' @format A data frame with 1,440 observations on the following 11 variables.
#' \describe{
#' \item{fips}{The county's 5-digit value according to the Federal Information Processing Standards. `integer`}
#' \item{county_name}{The lower case name of the county. `character`}
#' \item{year}{The year of the record, ranging from 1990 to 1999. `integer`}
#' \item{month}{The month of the record, ranging from 1 to 12. `integer`}
#' \item{fecund_population}{The number of females in the county, ages of
#' 15 to 44. `numeric`}
#' \item{birth_count}{The number of births in a county for the given month.
#' `integer`}
#' \item{date}{The year and month of the record, with a date of the 15th.
#' Centering the date within the month makes the value a little more representative
#' and the graphs a little easier. `date`}
#' \item{days_in_month}{The number of days in the specific month. `integer`}
#' \item{days_in_year}{The number of days in the specific years `integer`}
#' \item{stage_id}{The "Stage" of the month. The pre-bombing records are "1"
#' (accounting for 9 months of gestation); the post-bombing months are "2". `integer`}
#' \item{birth_rate}{The Growth Fertility Rate (GFR). `numeric`}
#' }
#' @details
#' <<Joe, can you please finish/edit this sentence?>>
#' The monthly birth counts were copied from county records by Ronnie Coleman during the
#' summer of 2001 from state vital statistics records. It was collected
#' for [Rodgers, St. John, & Coleman (2005)](https://pubmed.ncbi.nlm.nih.gov/16463916/).
#'
#' The US Census' intercensal estimates are used for the January values of
#' `fecund_population`. Values for February-December are interpolated using
#' [approx()].
#'
#' The datasets were manipulated to produce this data frame by the two R files
#' [isolate-census-pops-for-gfr.R](https://github.com/OuhscBbmc/Wats/blob/main/utility/isolate-census-pops-for-gfr.R)
#' and [calculate-gfr.R](https://github.com/OuhscBbmc/Wats/blob/main/utility/calculate-gfr.R).
#'
#' @author Will Beasley
#' @references
#' * Rodgers, J. L., St. John, C. A. & Coleman R. (2005).
#' [Did Fertility Go Up after the Oklahoma City Bombing?
#' An Analysis of Births in Metropolitan Counties in Oklahoma, 1990-1999.](https://pubmed.ncbi.nlm.nih.gov/16463916/)
#' *Demography, 42*, 675-692.
#'
#' * [Intercensal estimates for 199x](https://www.census.gov/data/tables/time-series/demo/popest/intercensal-1990-2000-state-and-county-totals.html)
#'
#' * [Intercensal estimates for 200x](https://www.census.gov/data/datasets/time-series/demo/popest/intercensal-2000-2010-counties.html)
#'
#' * Documentation: [US Census Intercensal Estimates](https://www.census.gov/programs-surveys/popest/technical-documentation/file-layouts.html)
#' for [199x](https://www.census.gov/programs-surveys/popest/technical-documentation/file-layouts/1990-2000-intercensal.html)
#' and [200x](https://www.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2000-2010-intercensal.html).
#'
#' @keywords datasets
#' @examples
#' library(ggplot2)
#'
#' # 2005 Version (see description above)
#' ds2005 <- county_month_birth_rate_2005_version
#' ggplot(ds2005, aes(x = date, y = birth_rate, color = factor(fips))) +
#' geom_line() +
#' labs(title="County Fertility - Longitudinal")
#'
#' ggplot(ds2005, aes(x = birth_rate, color = factor(fips))) +
#' geom_density() +
#' labs(title="Distributions of County Fertility")
#'
#' \donttest{
#' # 2014 Version (see description above)
#' ds2014 <- county_month_birth_rate_2014_version
#' ggplot(ds2014, aes(x = date, y = birth_rate, color = factor(fips))) +
#' geom_line() +
#' labs(title="County Fertility - Longitudinal")
#'
#' ggplot(ds2014, aes(x = birth_rate, color = factor(fips))) +
#' geom_density() +
#' labs(title="Distributions of County Fertility")
#' }
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