The function get_arrows() prepares a data frame for putting an
arrow on a plot prepared by the ggplot() function from the
‘ggplot2’ package.
get_arrow(model, x_range, rl_index, mtbs = "verified")A data frame with the columns ‘Time.1’, ‘Time.2’, ‘Response.1’, ‘Response.2’, Item, Colour, Line.Type, Arrow.Type, Size, Curvature, Angle and Length is returned, where the column names ‘Time.1’, ‘Time.2’, ‘Response.1’ and ‘Response.2’ are placeholders for the corresponding variable names. The data frame has a single row representing the arrow that is put on the graphical illustration.
An ‘expirest_osle’ or an
‘expirest_Wisle’ object, i.e. a list returned
by the expirest_osle() or by the
expirest_wisle() function.
A numeric vector of the form c(min, max) that
specifies the range of the time variable to be plotted.
A positive integer that specifies which of the release limit
values that have been handed over to expirest_wisle() should
be displayed. The default is NULL.
A character string that specifies the “model to be shown”,
i.e. either verified, which is the default, or one of cics,
dics, dids or dids.pmse. The verified model
is the model that was identified through the poolability check. It is
thus also one of the possible optional models. The dids model
represents the case where a separate model is fitted to the data of each
individual batch while the dids.pmse model is the interaction
model which includes the \(batch\) variable as main effect and in the
interaction term with the \(time\) variable (\(batch \times time\)),
i.e. a model where the mean square error is pooled across batches.
The function get_arrows() expects various pieces
of information that characterises an ‘expirest_osle’ or an
‘expirest_wisle’ model. Based on the information provided,
the function prepares a data frame that that is used by the function
plot_expirest_wisle()) to put an arrow on the graph that
is prepared by this function.