Running a subnational level single-country model with custom data

Load your library

library(mcmsupply)
library(dplyr)
set.seed(1209)

Try to use unsuitable data. The get_data function throws an error indicating that the Method column is missing from the custom user-supplied data.

cleaned_data <- get_data(national=FALSE, local=TRUE, 
                         surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_data_bad.xlsx",
                         mycountry="Ethiopia")

## Error in get_data(national = FALSE, local = TRUE, surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_data_bad.xlsx", : could not find function "get_data"

Load the suitable data

cleaned_data <- get_data(national=FALSE, local=TRUE, 
                         surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_data_good.xlsx",
                         mycountry="Ethiopia")

Get the JAGS model inputs and the cleaned data

pkg_data <- get_modelinputs(startyear=1990, endyear=2025.5,
                            nsegments=12, raw_data = cleaned_data)

Run JAGS model and get posterior point estimates with uncertainty

mod <- run_jags_model(jagsdata = pkg_data, jagsparams = NULL,
                      n_iter = 40000, n_burnin = 10000, n_thin = 15)

Plot posterior point estimates with uncertainty

plots <- plot_estimates(jagsdata = pkg_data, model_output = mod)

Pull out estimates that you are particularly interested in

estimates_2018 <- pull_estimates(model_output = mod, country = 'Ethiopia', year=2018)

head(estimates_2018)