In FPRgroup/FPEMcountry: fpemlocal

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())
# knitr::opts_knit$get("root.dir")  # alternative to the previous line
# the default autosave location will depend on this being setup
options(warn=-1)

1. Fit one country models for populations of interest

library(fpemlocal)
fit_botswana <- fit_fp_c(
  surveydata_filepath = "data-raw/manuscript_example_data/Botswana_72_married_example.csv",
  division_numeric_code = 72,
  is_in_union = "Y",
  first_year = 1970,
  last_year = 2030
)
fit_lesotho <- fit_fp_c(
  surveydata_filepath = "data-raw/manuscript_example_data/Lesotho_426_married_example.csv",
  division_numeric_code = 426,
  is_in_union = "Y",
  first_year = 1970,
  last_year = 2030
)

2. Read in population data for the populations of interest. Create a single dataset with the function rbind.

popdata_botswana <- read.csv("data-raw/manuscript_example_data/Botswana_72_married_popdata_example.csv")
popdata_lesotho <- read.csv("data-raw/manuscript_example_data/Lesotho_426_married_popdata_example.csv")
popdata <- rbind(popdata_botswana, popdata_lesotho)

3. Supply the fits in a list and the population dataset to the function calc_fp_aggregate. The resulting object is a list of long format tibbles with family planning estimates.

results <- calc_fp_aggregate(fits = list(fit_botswana, fit_lesotho),
                   population_data = popdata)
results[["contraceptive_use_modern"]] %>% head()

FPRgroup/FPEMcountry documentation built on April 24, 2023, 4:32 p.m.