Calculate mean difference between glucose values obtained at the same time of day (MODD)

The function modd produces MODD values in a tibble object.

Usage

modd(data, lag = 1, tz = "")

Arguments

data: DataFrame object with column names "id", "time", and "gl".
lag: Integer indicating which lag (# days) to use. Default is 1.
tz: A character string specifying the time zone to be used. System-specific (see as.POSIXct), but " " is the current time zone, and "GMT" is UTC (Universal Time, Coordinated). Invalid values are most commonly treated as UTC, on some platforms with a warning.

Value

A tibble object with two columns: subject id and corresponding MODD value.

Details

A tibble object with 1 row for each subject, a column for subject id and a column for the MODD values is returned.

Missing values will be linearly interpolated when close enough to non-missing values.

MODD is calculated by taking the mean of absolute differences between measurements at the same time 1 day away, or more if lag parameter is set to an integer > 1.

References

Service, F. J. & Nelson, R. L. (1980) Characteristics of glycemic stability. Diabetes care 3 .58-62, doi:10.2337/diacare.3.1.58 .

Examples


data(example_data_1_subject)
modd(example_data_1_subject)
#> # A tibble: 1 × 2
#>   id         MODD
#>   <fct>     <dbl>
#> 1 Subject 1  27.8
modd(example_data_1_subject, lag = 2)
#> # A tibble: 1 × 2
#>   id         MODD
#>   <fct>     <dbl>
#> 1 Subject 1  27.7

data(example_data_5_subject)
modd(example_data_5_subject, lag = 2)
#> # A tibble: 5 × 2
#>   id         MODD
#>   <fct>     <dbl>
#> 1 Subject 1  27.7
#> 2 Subject 2  46.0
#> 3 Subject 3  47.1
#> 4 Subject 4  24.9
#> 5 Subject 5  56.0