The function quantile_glu is a wrapper for the base function quantile(). Output is a tibble object with columns for subject id and each of the quantiles.
Usage
quantile_glu(data, quantiles = c(0, 25, 50, 75, 100))Arguments
- data
DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
- quantiles
List of quantile values between 0 and 100.
Value
If a data.frame object is passed, then a tibble object with a column for subject id and then a column for each quantile value is returned. If a vector of glucose values is passed, then a tibble object without the subject id is returned. as.numeric() can be wrapped around the latter to output a numeric vector.
Details
A tibble object with 1 row for each subject, a column for subject id and a column for each quantile is returned. NA glucose values are omitted from the calculation of the quantiles.
The values are scaled from 0-1 to 0-100 to be consistent in output with above_percent, below_percent, and in_range_percent.
The command quantile_glu(...) / 100 will scale each element down from 0-100 to 0-1.
Examples
data(example_data_1_subject)
quantile_glu(example_data_1_subject)
#> # A tibble: 1 × 6
#> # Groups: id [1]
#> id `0` `25` `50` `75` `100`
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Subject 1 66 99 112 143 276
quantile_glu(example_data_1_subject, quantiles = c(0, 33, 66, 100))
#> # A tibble: 1 × 5
#> # Groups: id [1]
#> id `0` `33` `66` `100`
#> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 Subject 1 66 104 128 276
data(example_data_5_subject)
quantile_glu(example_data_5_subject)
#> # A tibble: 5 × 6
#> # Groups: id [5]
#> id `0` `25` `50` `75` `100`
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Subject 1 66 99 112 143 276
#> 2 Subject 2 90 179 211 253 400
#> 3 Subject 3 60 125 140 173 304
#> 4 Subject 4 50 109 126 149 232
#> 5 Subject 5 66 134 164 211 398
quantile_glu(example_data_5_subject, quantiles = c(0, 10, 90, 100))
#> # A tibble: 5 × 5
#> # Groups: id [5]
#> id `0` `10` `90` `100`
#> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 Subject 1 66 92 172 276
#> 2 Subject 2 90 160 293 400
#> 3 Subject 3 60 110 226. 304
#> 4 Subject 4 50 94 167 232
#> 5 Subject 5 66 104 259 398