FPEM is composed of the following micro-packages
fpemdata,
fpemmodeling, and
fpemreporting. The
micropackages can be installed by cloning and using
devtools::install(). The source code for vignettes can be found in
/vignettes.
Knitted versions of vignettes can be found in
/docs. The directory
/design contains
technical details about the design of this project for pacakge
maintainers and contibutors. Below is a brief introduction to the FPEM
packages.
fpemmodeling::do_1country_run is a wrapper function to run the family
planning estimation model for a coutnry of interest for either married
or unmarried women. When a survey file is not provided (as in this
example) the function uses default data from
fpemdata::contraceptive_use. The function takes in additional inputs
such as services statistics if desired. See
??fpemdata::service_statsfor required service statistic data format.
See ??fpemmodeling::do_1country_run for all possible inputs to this
wrapper function. If you wish to obtain results for all women
fpemmodeling::posterior_samples_all_women can be used after completing
a run for married women and a run for unmarried women. See
FPEM/vignettes for more
details
run_y <- fpemmodeling::do_1country_run(
is_in_union = "Y",
surveydata_filepath = NULL,
service_stats = FALSE,
division_numeric_code = 400,
first_year = 1989,
last_year = 2030
)
fpemreporting::fpem_calculate_results returns point-estimates for
several indicators in long-format.
population_counts <- fpemdata::population_counts %>%
dplyr::filter(division_numeric_code == run_y$core_data$units$division_numeric_code) %>%
dplyr::filter(is_in_union == "Y")
results_y <- fpemreporting::fpem_calculate_results(
posterior_samples = run_y$posterior_samples,
country_population_counts = population_counts,
first_year = min(run_y$core_data$time_frame$limits())
)
fpemreporting::fpem_plot_country_results plots the results of the
model againts the observations. Choose any indicators returned from
fpemreporting::fpem_calculate_results
indicators <- c(
"unmet_need_any",
"contraceptive_use_modern",
"contraceptive_use_traditional",
"contraceptive_use_any"
)
plots <- fpemreporting::fpem_plot_country_results(
country_results = results_y,
observations = run_y$core_data$observations,
first_year = min(run_y$core_data$time_frame$limits()),
last_year = max(run_y$core_data$time_frame$limits()),
is_in_union = "Y",
indicators = indicators
)
gridExtra::grid.arrange(grobs=plots[1:length(indicators)],
ncol=2,
top="In-union women")

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