`R/aggregate_model_internal.R`

`aggregate_model_internal.Rd`

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 )

df | A dataframe of Model Output. |
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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 |

summary_var | A logical (defaults to |

An aggregated dataframe.

aggregate_model aggregate_model_internal combine_to_age_model combine_strat_model_output summarise_var_by_strat

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)#>#> #>#> 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