Reports where the casualties stood when the clock stopped, which is the
quantity the published reference distribution describes. A casualty's end
state is the last board area it had entered by the horizon; one that never
cleared triage counts as "not_seen".
Arguments
- object
A
game_runfromsdt_simulate().- reference
If
TRUE, fold the areas onto the published reporting locations and add the reference proportion beside the observed one, with their difference.- version
Which evaluated version of the exercise to compare against,
"2.0"or"1.0". Only used whenreference = TRUE.- ...
These dots are for future extensions and must be empty.
Value
A tibble::tibble() with columns area, label, n and
proportion; when reference = TRUE, also reference and difference.
Every area is present even at a zero count, so the shape does not depend
on the run.
Details
Two granularities are available. By default the tibble has one row per board
area. With reference = TRUE it is folded onto the eight locations the
source reports, because those are the only ones a published proportion
exists for: the two emergency-department areas become one, and the green
treatment area joins the ward. Both pairings are recorded in
sdt_reference("defaults")$end_state_map rather than being applied here, so
they can be inspected and argued with.
See also
sdt_reference() for the published values and their provenance.
Examples
co <- sdt_synthetic_cohort(n = 40, seed = 1)
run <- sdt_simulate(sdt_scenario(co), replications = 2, seed = 1,
verbose = FALSE)
summary(run)
#> # A tibble: 12 × 4
#> area label n proportion
#> <chr> <chr> <int> <dbl>
#> 1 triage Screening 34 0.425
#> 2 ed_red ED red 6 0.075
#> 3 ed_yellow ED yellow 9 0.112
#> 4 diagnostics Radiology 13 0.162
#> 5 or Operating room 4 0.05
#> 6 recovery Recovery 0 0
#> 7 icu_imc ICU / IMC 1 0.0125
#> 8 ward Ward 5 0.0625
#> 9 green_area Green area 8 0.1
#> 10 morgue Mortuary 0 0
#> 11 external Transferred out 0 0
#> 12 not_seen Not yet seen 0 0
summary(run, reference = TRUE)
#> # A tibble: 8 × 6
#> area label n proportion reference difference
#> <chr> <chr> <int> <dbl> <dbl> <dbl>
#> 1 triage Screening 34 0.425 0.08 0.345
#> 2 ed Emergency department 15 0.188 0.16 0.0275
#> 3 diagnostics Radiology 13 0.162 0.04 0.122
#> 4 or Operating room 4 0.05 0.11 -0.06
#> 5 recovery Recovery 0 0 0.01 -0.01
#> 6 icu_imc ICU / IMC 1 0.0125 0.23 -0.218
#> 7 ward Ward 13 0.162 0.35 -0.187
#> 8 not_seen Not yet seen 0 0 0 0
summary(run, reference = TRUE, version = "1.0")
#> # A tibble: 8 × 6
#> area label n proportion reference difference
#> <chr> <chr> <int> <dbl> <dbl> <dbl>
#> 1 triage Screening 34 0.425 0.15 0.275
#> 2 ed Emergency department 15 0.188 0.17 0.0175
#> 3 diagnostics Radiology 13 0.162 0.06 0.103
#> 4 or Operating room 4 0.05 0.09 -0.04
#> 5 recovery Recovery 0 0 0.01 -0.01
#> 6 icu_imc ICU / IMC 1 0.0125 0.2 -0.188
#> 7 ward Ward 13 0.162 0.31 -0.148
#> 8 not_seen Not yet seen 0 0 0.03 -0.03