time_series_plot: time series plot across different interventions

In jiabei-yang/nof1ins: N-of-1 study general analysis tool

Description

time series plot across different interventions

Usage

time_series_plot(
  result,
  baseline.treat.name = NULL,
  plot.by.treat = T,
  overlay.with.model = F,
  predict.model = F,
  trial.start = NULL,
  trial.end = NULL,
  timestamp.format = NULL,
  ...
)

Arguments

result	Modeling result of class nof1.result produced by nof1.run.
baseline.treat.name	Name for reference treatment. Default is NULL.
plot.by.treat	Whether or not the measurements should be plotted in different panels by treatment. The default is T.
overlay.with.model	Whether or not the model prediction should be plotted. The default is F.
predict.model	Indicator for whether or not a prediction line should be plotted over the study period. Option when overlay.with.model = TRUE.
trial.start	Start time of the trial specified with timestamp.format.
trial.end	End time of the trial specified with timestamp.format.
timestamp.format	Format of the trial.start and trial.end.

Examples

Y <- laughter$Y
Treat <- laughter$Treat
nof1 <- nof1.data(Y, Treat, ncat = 11, baseline = "Usual Routine", response = "ordinal")
timestamp <- seq(as.Date('2015-01-01'),as.Date('2016-01-31'), length.out = length(Y))
time_series_plot(nof1,
                 timestamp = timestamp,
                 timestamp.format = "%m-%d-%Y",
                 Outcome.name = "Stress")

jiabei-yang/nof1ins documentation built on Sept. 7, 2021, 1:10 p.m.