psychotree (version 0.13-0)

node_effects: Panel-Generating Function for Visualizing Rating Scale and Partial Credit Tree Models

Description

Panel-generating function for visualizing the threshold parameters from the nodes in rating scale and partial credit tree models.

Usage

node_effects(mobobj, names = NULL, type = c("mode", "median", "mean"),
  ref = NULL, ylab = "Latent trait", ylim = NULL, off = 0.1, col_fun = gray.colors,
  uo_show = TRUE, uo_col = "red", uo_lty = 2, uo_lwd = 1.25)

Arguments

mobobj

an object of class "mob" based on rating scale models fitted by RSModel or partial credit models fitted by PCModel.

names

character vector containing x-axis labels for the threshold parameters. If set to NULL (the default), these are generated.

type

character, specifying which type of threshold parameters are to be used to mark the category regions per item in the plot (see plot.PCModel for details).

ref

a vector of labels or position indices of item parameters which should be used as restriction/for normalization. If NULL (the default), all items are used (sum zero restriction).

ylim

y axis limits

ylab

label for the y axis.

off

the distance (in scale units) between two item rectangles.

col_fun

function. Function to use for creating the color palettes for the rectangles. Per default gray.colors is used. Be aware that col_fun should accept as first argument an integer specifying the number of colors to create.

uo_show

logical. If set to TRUE (the default), disordered threshold parameters are indicated by a horizontal line (if cut is set to "modus").

uo_col

character, color of indication lines (if uo_show).

uo_lty

numeric, line typ of indication lines (if uo_show).

uo_lwd

numeric, line width of indication lines (if uo_show).

Value

• A panel function which can be supplied to the plot method for "mob" objects.

Details

The panel-generating function node_effects is called by the plot method for "rstree" and "pctree" objects by default and does not have to be called by the user directly.

See plot.PCModel for details and references of the drawn effect plots and possible values and their meaning for argument cut (taken by node_effects).

See Also

rstree, pctree, plot.PCModel