R/MultOrd-package.R

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

#' Model Multivariate Ordinal Responses Including Response Styles
#' 
#' A model for multivariate ordinal responses. The response is modelled 
#' using a mixed model approach that is also capable of the inclusion 
#' of response style effects of the respondents.
#' 
#' 
#' @name MultOrd-package
#' @docType package
#' @author Gunther Schauberger\cr \email{gunther.schauberger@@tum.de}\cr
#' \url{https://www.researchgate.net/profile/Gunther_Schauberger2}
#' @seealso \code{\link{multord}}  \code{\link{ctrl.multord}}  \code{\link{plot.MultOrd}}
#' @keywords multivariate ordinal response style adjacent categories cumulative 
#' @examples
#' \dontrun{
#' 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)
#'}
NULL


#' Tenseness data from the Freiburg Complaint Checklist (tenseness)
#' 
#' Data from the Freiburg Complaint Checklist. The data contain all 8 items corresponding to the scale 
#' \emph{Tenseness} for 1847 participants of the standardization sample of the Freiburg Complaint Checklist. 
#' Additionally, several person characteristics are available. 
#' 
#' @name tenseness
#' @docType data
#' @format A data frame containing data from the Freiburg Complaint Checklist with 1847 observations. 
#' All items refer to the scale \emph{Tenseness} and are measured on a 5-point Likert scale where low numbers 
#' correspond to low frequencies or low intensitites of the respective complaint and vice versa. 
#' \describe{ 
#' \item{Clammy hands}{Do you have clammy hands?}
#' \item{Sweat attacks}{Do you have sudden attacks of sweating?}
#' \item{Clumsiness}{Do you notice that you behave clumsy?}
#' \item{Wavering hands}{Are your hands wavering frequently, e.g. when lightning a cigarette or when holding a cup?}
#' \item{Restless hands}{Do you notice that your hands are restless?}
#' \item{Restless feet}{Do you notice that your feet are restless?}
#' \item{Twitching eyes}{Do you notice unvoluntary twitching of your eyes?}
#' \item{Twitching mouth}{Do you notice unvoluntary twitching of your mouth?}
#' \item{Gender}{Gender of the participant}
#' \item{Household}{Does participant live alone in a houshold or together with others?}
#' \item{WestEast}{is the participant from East Germany (former GDR) or West Germany?}
#' \item{Age}{Age in 15 categories, treated as continuous variable}
#' \item{Abitur}{Does the participant have Abitur (a-levels)?}
#' \item{Income}{Income in 11 categories, treated as continuous variable}
#'  }
#' @source 
#' ZPID (2013). PsychData of the Leibniz Institute for Psychology Information ZPID. Trier: Center for Research Data in Psychology.
#' 
#' Fahrenberg, J. (2010). Freiburg Complaint Checklist [Freiburger Beschwerdenliste (FBL)]. Goettingen, Hogrefe.
#' @keywords datasets
#' @examples
#' \dontrun{
#' 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)
#'}
NULL