This function regroups an incidence() object across the specified groups.
The resulting incidence() object will contains counts summed over
the groups present in the input.
regroup(x, groups = NULL)
| x | An |
|---|---|
| groups | The groups to sum over. If |
if (requireNamespace("outbreaks", quietly = TRUE)) { withAutoprint({ data(ebola_sim_clean, package = "outbreaks") dat <- ebola_sim_clean$linelist i <- incidence(dat, date_index = date_of_onset, groups = c(gender, hospital)) regroup(i) regroup(i, hospital) }) } #> > data(ebola_sim_clean, package = "outbreaks") #> > dat <- ebola_sim_clean$linelist #> > i <- incidence(dat, date_index = date_of_onset, groups = c(gender, hospital)) #> > regroup(i) #> An incidence object: 367 x 2 #> date range: [2014-04-07] to [2015-04-30] #> cases: 5829 #> interval: 1 day #> cumulative: FALSE #> #> date_index count #> <date> <int> #> 1 2014-04-07 1 #> 2 2014-04-15 1 #> 3 2014-04-21 2 #> 4 2014-04-25 1 #> 5 2014-04-26 1 #> 6 2014-04-27 1 #> 7 2014-05-01 2 #> 8 2014-05-03 1 #> 9 2014-05-04 1 #> 10 2014-05-05 1 #> # … with 357 more rows #> > regroup(i, hospital) #> An incidence object: 1,635 x 3 #> date range: [2014-04-07] to [2015-04-30] #> cases: 5829 #> interval: 1 day #> cumulative: FALSE #> #> date_index hospital count #> <date> <fct> <int> #> 1 2014-04-07 Military Hospital 1 #> 2 2014-04-15 Connaught Hospital 1 #> 3 2014-04-21 other 2 #> 4 2014-04-25 NA 1 #> 5 2014-04-26 other 1 #> 6 2014-04-27 NA 1 #> 7 2014-05-01 Princess Christian Maternity Hospital (PCMH) 1 #> 8 2014-05-01 Rokupa Hospital 1 #> 9 2014-05-03 Connaught Hospital 1 #> 10 2014-05-04 NA 1 #> # … with 1,625 more rows