Skip to contents

Intradaily variability (IV)

Source: R/metric_intradaily_variability.R
intradaily_variability.Rd

This function calculates the variability of consecutive Light levels within a 24h day. Calculated as the ratio of the variance of the differences between consecutive Light levels to the total variance across the day. Calculated with mean hourly Light levels. Higher values indicate more fragmentation.

Usage

intradaily_variability(
  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 FALSE.

as.df

Logical. Should the output be returned as a data frame? If TRUE, a data frame with a single column named intradaily_variability will be returned. Defaults to FALSE.

Value

Numeric value or dataframe with column 'IV'.

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(), interdaily_stability(), midpointCE(), nvRC(), nvRD(), nvRD_cumulative_response(), period_above_threshold(), pulses_above_threshold(), threshold_for_duration(), timing_above_threshold()

Examples


set.seed(1)
N <- 24 * 2
# Calculate metric for two 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(
    "Intradaily variability" = intradaily_variability(MEDI, Datetime)
  )
#> # A tibble: 1 × 1
#>   `Intradaily variability`
#>                      <dbl>
#> 1                     1.71