Wats (version 1.0.1)

county_month_birth_rate: 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

Author

Will Beasley

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.

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.

• Intercensal estimates for 199x

• Intercensal estimates for 200x

• 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")

# \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")
# }