Format AE specific analysis
Arguments
- outdata
An
outdata
object created byprepare_ae_specific()
.- display
A character vector of measurement to be displayed:
n
: Number of subjects with AE.prop
: Proportion of subjects with AE.total
: Total columns.diff
: Risk difference.diff_ci
: 95% confidence interval of risk difference using M&N method.diff_p
: p-value of risk difference using M&N method.dur
: Average of AE duration.events
: Average number of AE per subject.
- digits_prop
A numeric value of number of digits for proportion value.
- digits_ci
A numeric value of number of digits for confidence interval.
- digits_p
A numeric value of number of digits for p-value.
- digits_dur
A numeric value of number of digits for average duration of AE.
- digits_events
A numeric value of number of digits for average of number of AE per subjects.
- mock
A boolean value to display mock table.
Examples
meta <- meta_ae_example()
outdata <- prepare_ae_specific(meta,
population = "apat",
observation = "wk12",
parameter = "rel"
)
# Basic example
tbl <- outdata |>
format_ae_specific()
head(tbl$tbl)
#> name n_1 prop_1 n_2 prop_2 n_3
#> 1 Participants in population 86 <NA> 84 <NA> 84
#> 2 with one or more drug-related adverse events 44 (51.2) 73 (86.9) 70
#> 3 with no drug-related adverse events 42 (48.8) 11 (13.1) 14
#> 4 NA <NA> NA <NA> NA
#> 122 Cardiac disorders 6 (7.0) 7 (8.3) 4
#> 25 Atrial fibrillation 1 (1.2) 0 (0.0) 2
#> prop_3 n_4 prop_4
#> 1 <NA> 254 <NA>
#> 2 (83.3) 187 (73.6)
#> 3 (16.7) 67 (26.4)
#> 4 <NA> NA <NA>
#> 122 (4.8) 17 (6.7)
#> 25 (2.4) 3 (1.2)
# Display different measurements
tbl <- outdata |>
extend_ae_specific_events() |>
format_ae_specific(display = c("n", "prop", "events"))
head(tbl$tbl)
#> name n_1 prop_1 events_1 n_2
#> 1 Participants in population 86 <NA> NA 84
#> 2 with one or more drug-related adverse events 44 (51.2) 0.7 ( 0.1) 73
#> 3 with no drug-related adverse events 42 (48.8) NA 11
#> 4 NA <NA> NA NA
#> 122 Cardiac disorders 6 (7.0) 2.3 ( 0.4) 7
#> 25 Atrial fibrillation 1 (1.2) 1.0 ( 0.0) 0
#> prop_2 events_2 n_3 prop_3 events_3
#> 1 <NA> NA 84 <NA> NA
#> 2 (86.9) 1.6 ( 0.2) 70 (83.3) 1.5 ( 0.2)
#> 3 (13.1) NA 14 (16.7) NA
#> 4 <NA> NA NA <NA> NA
#> 122 (8.3) 2.5 ( 0.3) 4 (4.8) 3.2 ( 0.3)
#> 25 (0.0) 1.7 ( 0.1) 2 (2.4) 1.5 ( 0.1)