An Internal Function to Aggregate Model Output Using other Idmodelr functions.

An Internal Function to Aggregate Model Output Using other Idmodelr functions.

aggregate_model_internal(
  df,
  aggregate_to = NULL,
  compartments = NULL,
  strat = NULL,
  hold_out_var = NULL,
  new_var = "incidence",
  id_col = NULL,
  groups = NULL,
  total_pop = TRUE,
  summary_var = FALSE
)

Arguments

df	A dataframe of Model Output.
aggregate_to	A character vector specifying the aggregation function to apply possible values are; disease, demographic, or incidence.
compartments	A character vector specifying the unique compartments to aggregate.
strat	The number of stratified groups in the model.
hold_out_var	A character vector specifying the unique compartments not to aggregate.
new_var	A character vector specifying the new variable to add when aggregating incidence.
id_col	A character string containing the name of the new id column.
groups	A character vector with length equal to the level of stratification. Used to name the stratified levels.
total_pop	A logical (defaults to TRUE) indicating if the total population should be calculated when summarising the model demographics.
summary_var	A logical (defaults to FALSE), specifying whether to add an additional summary variable across all stratified levels.

Value

An aggregated dataframe.

See also

aggregate_model aggregate_model_internal combine_to_age_model combine_strat_model_output summarise_var_by_strat

Examples

df <- data.frame(time = 1, A1 = 1, B1 = 1, A2 = 1, B2 = 1, A3 = 1, B3 = 1)

## Incidence
aggregate_model_internal(df, aggregate_to = "incidence",
                        compartments = c("A", "B"), strat = 3,
                        summary_var = TRUE)
#> # A tibble: 1 x 11
#>   incidence incidence1 incidence2 incidence3  time    A1    B1    A2    B2    A3
#>       <dbl>      <dbl>      <dbl>      <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1         6          2          2          2     1     1     1     1     1     1
#> # … with 1 more variable: B3 <dbl>

## Demographic
aggregate_model_internal(df, aggregate_to = "demographic",
                        compartments = c("A", "B"), strat = 3,
                        summary_var = TRUE)
#>   time age_group_1 age_group_2 age_group_3 N
#> 1    1           2           2           2 6
## Disease
aggregate_model_internal(df, aggregate_to = "disease",
                        compartments = c("A", "B"), strat = 3,
                        summary_var = TRUE)
#> New names:
#> * value -> value...1
#> * value -> value...2
#>   time A B
#> 1    1 3 3
## Tidy (long)
aggregate_model_internal(df, aggregate_to = "tidy",
                        compartments = c("A", "B"), hold_out_var = "time", strat = 3,
                        summary_var = TRUE, id_col = "Age",
                        groups = c("Children", "Young adults", "Adults"))
#>   time          Age A B
#> 1    1     Children 1 1
#> 2    1 Young adults 1 1
#> 3    1       Adults 1 1