In FPRgroup/FPEM: FPEM

knitr::opts_chunk$set(echo = TRUE)
options(warn=-1)

Table of Contents

1. Introduction
2. Run models
3. Post-process
4. Plot model results

Introduction

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.

knitr::opts_chunk$set(echo = TRUE)
library(fpemdata)
library(fpemmodeling)
library(fpemreporting)
library(ggplot2)
library(grid)
library(gridExtra)

Run models

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
)

Process the samples

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())
)

Plot the results

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")

FPRgroup/FPEM documentation built on March 3, 2020, 8:19 a.m.