acfByID: Estimate the autocorrelation by unit (ID)

In multilevelTools: Multilevel and Mixed Effects Model Diagnostics and Effect Sizes

Description

This function estimates the autocorrelation over time in a time series by a higher level unit, given by ID.

Usage

acfByID(
  xvar,
  timevar,
  idvar,
  data,
  lag.max = 10L,
  na.function = c("na.approx", "na.spline", "na.locf"),
  ...
)

Arguments

xvar	A character string giving the variable name of the variable to calculate autocorrelations on.
timevar	A character string giving the variable name of the time variable.
idvar	A character string giving the variable name of the ID variable. Can be missing if only one time series provided, in which case one will be created.
data	A data.table containing the variables used in the formula. This is a required argument. If a data.frame, it will silently coerce to a data.table. If not a data.table or data.frame, it will attempt to coerce, with a message.
lag.max	An integer of the maximum lag to estimate. Must be equal to or greater than the number of observations for all IDs in the dataset.
na.function	A character string giving the name of the function to use to address any missing data. Functions come from the zoo package, and must be one of: “na.approx”, “na.spline”, “na.locf”.
...	Additional arguments passed to zoo.

Value

A data.table of the estimated autocorrelations by ID and lag

Examples

## example 1
dat <- data.table::data.table(
  x = sin(1:30),
  time = 1:30,
  id = 1)
acfByID("x", "time", "id", data = dat)

## example 2
dat2 <- data.table::data.table(
  x = c(sin(1:30), sin((1:30)/10)),
  time = c(1:30, 1:30),
  id = rep(1:2, each = 30))
dat2$x[4] <- NA

res <- acfByID("x", "time", "id", data = dat2, na.function = "na.approx")

ggplot2::ggplot(res, ggplot2::aes(factor(Lag), AutoCorrelation)) +
  ggplot2::geom_boxplot()

## clean up
rm(dat, dat2, res)

multilevelTools documentation built on March 13, 2020, 2:07 a.m.