county_month_birth_rate {Wats} | R Documentation |
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.
- fips
The county's 5-digit value according to the Federal Information Processing Standards.
integer
- county_name
The lower case name of the county.
character
- year
The year of the record, ranging from 1990 to 1999.
integer
- month
The month of the record, ranging from 1 to 12.
integer
- fecund_population
The number of females in the county, ages of 15 to 44.
numeric
- birth_count
The number of births in a county for the given month.
integer
- 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
- days_in_month
The number of days in the specific month.
integer
- days_in_year
The number of days in the specific years
integer
- 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
- 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).
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 and calculate-gfr.R.
Author(s)
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. Demography, 42, 675-692.
Documentation: US Census Intercensal Estimates for 199x and 200x.
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")
# 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")