Calculate partial AUC

Calculate partial AUC

auc_partial(idv, dv, range = c(0, Inf))

Arguments

idv	independent variable (such as time)
dv	dependent variable (such as concentration)
range	time range for pauc calculation

Details

default range is 0 to tmax is recommended to be used alongside dplyr for ease of calculation if an individual does not have any value within the specified range a warning will be issued and an NA value will be returned. This is important if some individuals dropped out early and do not have all observations other individuals have.

See also

s_pauc

Examples

library(PKPDmisc)
library(dplyr, quiet = TRUE)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
df <- capitalize_names(sd_oral_richpk)
head(df)
#>   ID TIME  AMT      CONC      AGE   WEIGHT GENDER     RACE DOSE
#> 1  1 0.00 5000  0.000000 56.09591 94.19649   Male Hispanic 5000
#> 2  1 0.25    0  8.612809 56.09591 94.19649   Male Hispanic 5000
#> 3  1 0.50    0 19.436818 56.09591 94.19649   Male Hispanic 5000
#> 4  1 1.00    0 34.006699 56.09591 94.19649   Male Hispanic 5000
#> 5  1 2.00    0 30.228800 56.09591 94.19649   Male Hispanic 5000
#> 6  1 3.00    0 31.299610 56.09591 94.19649   Male Hispanic 5000
df %>% group_by(ID) %>%
summarize(pAUC0_10 = auc_partial(TIME, CONC, c(0,10)))
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 50 x 2
#>       ID pAUC0_10
#>    <int>    <dbl>
#>  1     1     204.
#>  2     2     523.
#>  3     3     316.
#>  4     4     564.
#>  5     5     302.
#>  6     6     154.
#>  7     7     393.
#>  8     8     255.
#>  9     9     286.
#> 10    10     122.
#> # … with 40 more rows

df %>% group_by(ID) %>%
summarize(auc0_tlast = auc_partial(TIME, CONC))
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 50 x 2
#>       ID auc0_tlast
#>    <int>      <dbl>
#>  1     1       386.
#>  2     2      1203.
#>  3     3       466.
#>  4     4      1220.
#>  5     5       488.
#>  6     6       295.
#>  7     7       739.
#>  8     8       454.
#>  9     9       699.
#> 10    10       161.
#> # … with 40 more rows