plot.MultOrd: Plot function for MultOrd

In Schaubert/MultOrd: Model Multivariate Ordinal Responses Including Response Styles

Description

Plot function for a MultOrd object. Plots show coefficients of the explanatory variables, both with repect to location and response styles. The coefficient pairs are displayed as stars, where the rays represent (1-alpha) confidence intervals.

Usage

## S3 method for class 'MultOrd'
plot(x, alpha = 0.05, CIfactor = 0.9, ...)

Arguments

x	MultOrd object
alpha	Specifies the confidence level 1-alpha of the confidence interval.
...	Further plot arguments.
CI.factor	Argument that helps to control the appearance (the width) of the stars that represent the confidence intervals of both parameters (location and response style) corresponding to one covariate.

Author(s)

Gunther Schauberger
[e-mail]
https://www.researchgate.net/profile/Gunther_Schauberger2

See Also

multord, ctrl.multord

Examples

## Not run: 
data(tenseness)

## create a small subset of the data to speed up calculations
set.seed(1860)
tenseness <- tenseness[sample(1:nrow(tenseness), 300),]

## scale all metric variables to get comparable parameter estimates
tenseness$Age <- scale(tenseness$Age)
tenseness$Income <- scale(tenseness$Income)

## two formulas, one without and one with explanatory variables (gender and age)
f.tense0 <- as.formula(paste("cbind(",paste(names(tenseness)[1:4],collapse=","),") ~ 1"))
f.tense1 <- as.formula(paste("cbind(",paste(names(tenseness)[1:4],collapse=","),") ~ Gender + Age"))



####
## Adjacent Categories Models
####

## Multivariate adjacent categories model, without response style, without explanatory variables
m.tense0 <- multord(f.tense0, data = tenseness, control = ctrl.multord(RS = FALSE))
m.tense0

## Multivariate adjacent categories model, with response style as a random effect, without explanatory variables
m.tense1 <- multord(f.tense0, data = tenseness)
m.tense1

## Multivariate adjacent categories model, with response style as a random effect, 
## without explanatory variables for response style BUT for location
m.tense2 <- multord(f.tense1, data = tenseness, control = ctrl.multord(XforRS = FALSE))
m.tense2

## Multivariate adjacent categories model, with response style as a random effect, with explanatory variables for location AND response style
m.tense3 <- multord(f.tense1, data = tenseness)
m.tense3

plot(m.tense3)



####
## Cumulative Models
####

## Multivariate cumulative model, without response style, without explanatory variables
m.tense0.cumul <- multord(f.tense0, data = tenseness, control = ctrl.multord(RS = FALSE), model = "cumulative")
m.tense0.cumul

## Multivariate cumulative model, with response style as a random effect, without explanatory variables
m.tense1.cumul <- multord(f.tense0, data = tenseness, model = "cumulative")
m.tense1.cumul

## Multivariate cumulative model, with response style as a random effect, 
## without explanatory variables for response style BUT for location
m.tense2.cumul <- multord(f.tense1, data = tenseness, control = ctrl.multord(XforRS = FALSE), model = "cumulative")
m.tense2.cumul

## Multivariate cumulative model, with response style as a random effect, with explanatory variables for location AND response style
m.tense3.cumul <- multord(f.tense1, data = tenseness, model = "cumulative")
m.tense3.cumul

plot(m.tense3.cumul)

## End(Not run)

Schaubert/MultOrd documentation built on June 13, 2019, 7:09 p.m.