The function auc produces hourly average AUC for each subject.
Arguments
- data
DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
- tz
String value of time zone.
Value
If a data.frame object is passed, then a tibble object with two columns: subject id and corresponding hourly average AUC value is returned.
AUC is calculated for every hour using the trapezoidal rule, then hourly average AUC is calculated for each 24 hour period, then the mean of hourly average AUC across all 24 hour periods is returned as overall hourly average AUC.
Details
A tibble object with 1 row for each subject, a column for subject id and a column for hourly average AUC values is returned. NA glucose values are omitted from the calculation of the AUC.
AUC is calculated using the formula: (dt0/60) * ((gl[2:length(gl)] + gl[1:(length(gl)-1)])/2), where dt0/60 is the frequency of the cgm measurements in hours and gl are the glucose values.
This formula is based off the Trapezoidal Rule: (time[2]-time[1] * ((glucose[1]+glucose[2])/2)).
References
Danne et al. (2017) International Consensus on Use of Continuous Glucose Monitoring, Diabetes Care 40 .1631-1640, doi:10.2337/dc17-1600 .
Examples
data(example_data_1_subject)
auc(example_data_1_subject)
#> # A tibble: 1 × 2
#> id hourly_auc
#> <fct> <dbl>
#> 1 Subject 1 123.