# \donttest{
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 <- multordRS(f.tense0, data = tenseness, control = ctrl.multordRS(RS = FALSE))
m.tense0
## Multivariate adjacent categories model, with response style as a random effect,
## without explanatory variables
m.tense1 <- multordRS(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 <- multordRS(f.tense1, data = tenseness, control = ctrl.multordRS(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 <- multordRS(f.tense1, data = tenseness)
m.tense3
plot(m.tense3)
####
## Cumulative Models
####
## Multivariate cumulative model, without response style, without explanatory variables
m.tense0.cumul <- multordRS(f.tense0, data = tenseness, control =
ctrl.multordRS(RS = FALSE), model = "cumulative")
m.tense0.cumul
## Multivariate cumulative model, with response style as a random effect,
## without explanatory variables
m.tense1.cumul <- multordRS(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 <- multordRS(f.tense1, data = tenseness,
control = ctrl.multordRS(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 <- multordRS(f.tense1, data = tenseness, model = "cumulative")
m.tense3.cumul
plot(m.tense3.cumul)
# }
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