ordDisp (version 2.1.1)

plotordDisp: 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

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.

See Also

ordDisp

Examples

# NOT RUN {
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"))

# }