plotordDisp {ordDisp} | R Documentation |
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 |
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 |
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 |
title |
Optional title that is added to the plot |
... |
Further arguments passed to or from other methods |
Author(s)
Moritz Berger <moritz.berger@imbie.uni-bonn.de>
https://www.imbie.uni-bonn.de/personen/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.
See Also
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"))