interdaily_stability {LightLogR} | R Documentation |
Interdaily stability (IS)
Description
This function calculates the variability of 24h light exposure patterns across multiple days. Calculated as the ratio of the variance of the average daily pattern to the total variance across all days. Calculated with mean hourly light levels. Ranges between 0 (Gaussian noise) and 1 (Perfect Stability).
Usage
interdaily_stability(
Light.vector,
Datetime.vector,
na.rm = FALSE,
as.df = FALSE
)
Arguments
Light.vector |
Numeric vector containing the light data. |
Datetime.vector |
Vector containing the time data. Must be POSIXct. |
na.rm |
Logical. Should missing values be removed? Defaults to |
as.df |
Logical. Should the output be returned as a data frame? If |
Details
Note that this metric will always be 1 if the data contains only one 24 h day.
Value
Numeric value or dataframe with column 'IS'.
References
Van Someren, E. J. W., Swaab, D. F., Colenda, C. C., Cohen, W., McCall, W. V., & Rosenquist, P. B. (1999). Bright Light Therapy: Improved Sensitivity to Its Effects on Rest-Activity Rhythms in Alzheimer Patients by Application of Nonparametric Methods. Chronobiology International, 16(4), 505–518. doi:10.3109/07420529908998724
Hartmeyer, S.L., Andersen, M. (2023). Towards a framework for light-dosimetry studies: Quantification metrics. Lighting Research & Technology. doi:10.1177/14771535231170500
See Also
Other metrics:
bright_dark_period()
,
centroidLE()
,
disparity_index()
,
duration_above_threshold()
,
exponential_moving_average()
,
frequency_crossing_threshold()
,
intradaily_variability()
,
midpointCE()
,
nvRC()
,
nvRD()
,
nvRD_cumulative_response()
,
period_above_threshold()
,
pulses_above_threshold()
,
threshold_for_duration()
,
timing_above_threshold()
Examples
set.seed(1)
N <- 24 * 7
# Calculate metric for seven 24 h days with two measurements per hour
dataset1 <-
tibble::tibble(
Id = rep("A", N * 2),
Datetime = lubridate::as_datetime(0) + c(lubridate::minutes(seq(0, N * 60 - 30, 30))),
MEDI = sample(1:1000, N * 2)
)
dataset1 %>%
dplyr::summarise(
"Interdaily stability" = interdaily_stability(MEDI, Datetime)
)