plotordDisp: Visualization of Estimated Effects

In ordDisp: Separating Location and Dispersion in Ordinal Regression Models

Visualization of Estimated Effects

Description

A function to visualize the estimated effects of the location-shift model or rating-scale model accounting for response styles (RSRS) obtained by ordDisp. In case of linear effects, the function returns a two-dimensional plot of the tupel (exp{\alpha},exp{\beta}. It is optional to include pointwise 95% confidence intervals represented by stars, where the horizontal and vertical length correspond to the confidence intervals of exp{\alpha} (dispersion or response-style effect) and exp{\beta} (location or content-related effect). In case of smooth effects, the function returns two plots of the fitted (non-linear) functions f(\beta) and f(\alpha).

Usage

plotordDisp(
  x,
  names,
  colorvec,
  reference = NULL,
  labels = NULL,
  cex = 1,
  KI = FALSE,
  KIfactor = 10/11,
  title = NULL,
  ...
)

Arguments

x	Object of class ordDisp
names	Names of the variables that shall be plotted
colorvec	Vector of colors that are used for plotting (same length as names)
reference	Optional name of reference with estimate (\alpha,\beta)=(0,0) (for categorical covariates)
labels	Optional names that are used as labels in the plot (same length as names)
cex	Global argument to set the size of all the labels in the plot
KI	If true, pointwise 95% confidence intervals are included in the plot
KIfactor	Ratio that is used to plot the stars that represent confidence intervals (only if KI=TRUE)
title	Optional title that is added to the plot
...	Further arguments passed to or from other methods

Author(s)

Moritz Berger <[e-mail]>
https://www.imbie.uni-bonn.de/people/dr-moritz-berger/

References

Tutz, Gerhard and Berger, Moritz (2016): Response Styles in Rating Scales - Simultaneous Modelling of Content-Related Effects and the Tendency to Middle or Extreme Categories, Journal of Educational and Behavioral Statistics 41(3), 239-268.

Tutz, Gerhard and Berger, Moritz (2017): Seperating Location and Dispersion in Ordinal Regression Models, Econometrics and Statistics 2, 131-148.

Tutz, Gerhard and Berger, Moritz (2022): Sparser Ordinal Regression Models Based on Parametric and Additive Location-Shift Approaches. International Statistical Review, 90(2), 306-327.

See Also

ordDisp

Examples

data(reti)

mod <- ordDisp(RET~SM+DIAB+GH+BP|SM+DIAB,data=reti,family="cumulative")
plot(mod,names=c("SM","DIAB"),colorvec=c(1,2))
plotvglm(mod)

mod2 <- ordDisp(RET~SM+s(DIAB)+GH+BP|SM+DIAB+GH+BP, data=reti, 
family="cumulative", n_bs=4, scaling=FALSE)
plot(mod2, names=c("DIAB"))

ordDisp documentation built on June 8, 2025, 1:51 p.m.