flag_low_counts: Flag low counts and set them to NAs

In reconverse/i2extras: Functions to Work with 'incidence2' Objects

Flag low counts and set them to NAs

Description

Low counts may be genuine, but they can also reflect actually missing data or strong under-reporting. This function aims to detect the latter by flagging any count below a certain threshold, expressed as a fraction of the median count. Setting low values to NAs can be useful to help fitting temporal trends to the data, as zeros / low counts can throw off some models (e.g. Negative Binomial GLMs).

Usage

flag_low_counts(x, counts = NULL, threshold = 0.001, set_missing = TRUE)

Arguments

x	An incidence2::incidence object.
counts	A tidyselect compliant indication of the counts to be used.
threshold	A numeric multiplier of the median count to be used as threshold. Defaults to 0.001, in which case any count strictly lower than 0.1% of the mean count is flagged as low count.
set_missing	A logical indicating if the low counts identified should be replaced with NAs (TRUE, default). If FALSE, new logical columns with the flag_low suffix will be added, indicating which entries are below the threshold.

Value

An incidence2::incidence object.

Author(s)

Tim Taylor and Thibaut Jombart

Examples

if (requireNamespace("outbreaks", quietly = TRUE) &&
    requireNamespace("incidence2", quietly = TRUE)) {
  data(covid19_england_nhscalls_2020, package = "outbreaks")
  dat <- covid19_england_nhscalls_2020
  i <- incidence(dat, "date", interval = "isoweek", counts = "count")
  plot(i)
  plot(flag_low_counts(i, threshold = 0.1))
  plot(flag_low_counts(i, threshold = 1), title = "removing counts below the median")
}

reconverse/i2extras documentation built on Aug. 10, 2024, 8:03 a.m.