circacompare_mixed: circacompare_mixed

In circacompare: Analyses of Circadian Data

circacompare_mixed

Description

circacompare_mixed is similar to circacompare but allows for some simple, user-specified random-effects on the rhythmic parameters of choice.

Usage

circacompare_mixed(
  x,
  col_time,
  col_group,
  col_outcome,
  col_id,
  randomeffects = c(),
  period = 24,
  alpha_threshold = 0.05,
  nlme_control = list(),
  nlme_method = "REML",
  weights = NULL,
  suppress_all = FALSE,
  timeout_n = 10000,
  control = list()
)

Arguments

x	data.frame. This is the data.frame which contains the rhythmic data for two groups in a tidy format.
col_time	The name of the column within the data.frame, x, which contains time in hours at which the data were collected.
col_group	The name of the column within the data.frame, x, which contains the grouping variable. This should only have two levels.
col_outcome	The name of the column within the data.frame, x, which contains outcome measure of interest.
col_id	The name of the column within the data.frame, x, which contains the identifying values for the random effect, such as subject_id.
randomeffects	which rhythmic parameters to allow random effects. The default is to include no rhythmic parameters.
period	The period of the rhythm. For circadian rhythms, leave this as the default value, 24.
alpha_threshold	The level of alpha for which the presence of rhythmicity is considered. Default is to 0.05.
nlme_control	A list of control values for the estimation algorithm to replace the default values returned by the function nlme::nlmeControl. Defaults to an empty list.
nlme_method	A character string. If "REML" the model is fit by maximizing the restricted log-likelihood. If "ML" the log-likelihood is maximized. Defaults to "REML".
weights	An optional numeric vector of (fixed) weights internally passed to nlme::nlme() via nlme::varPower(). When present, the objective function is weighted least squares.
suppress_all	Logical. Set to TRUE to avoid seeing errors or messages during model fitting procedure. Default is FALSE. If FALSE, also runs nlme() with verbose = TRUE.
timeout_n	The upper limit for the model fitting attempts. Default is 10000.
control	list. Used to control the parameterization of the model.

Value

list

Examples

# Generate some data with within-id correlation for phase-shift (phi1)

set.seed(99)
phi1_in <- 3.15

mixed_data <- function(n) {
  counter <- 1
  for (i in 1:n) {
    x <- make_data(k1 = 0, alpha1 = 0, phi1 = rnorm(1, phi1_in, 0.5), hours = 72, noise_sd = 1)
    x$id <- counter
    counter <- counter + 1
    if (i == 1) {
      res <- x
    } else {
      res <- rbind(res, x)
    }
  }
  return(res)
}
df <- mixed_data(20)
out <- circacompare_mixed(
  x = df,
  col_time = "time",
  col_group = "group",
  col_outcome = "measure",
  col_id = "id",
  control = list(grouped_params = c("phi"), random_params = c("phi1"))
)

# with sample weights (arbitrary weights for demonstration)
sw <- runif(n = nrow(df))
out2 <- circacompare_mixed(
  x = df,
  col_time = "time",
  col_group = "group",
  col_outcome = "measure",
  col_id = "id",
  control = list(grouped_params = c("phi"), random_params = c("phi1")),
  weights = sw
)

circacompare documentation built on May 29, 2024, 6:22 a.m.