# simsalRbim - A package for preference test simulations

Preference tests are a valuable tool to measure the “wants” of individuals and have been proven to be a valid method to rate different commodities. The number of commodities presented at the same time is, however, limited and in classical test settings usually, only two options are presented. In our paper, we evaluate the option of combining multiple binary choices to rank preferences among a larger number of commodities. The simsalRbim package offers the necessary tools to test selections of commodities and to obtain an estimate of new or incompletely tested items and their relative position.

simsalRbim Website

## Data availability

Besides the internal ZickeZacke data, we provide additional experimental data from six different preference tests. These data can be downloaded from a separate GitHub repository and can be used directly in this package (e.g., with the bimload function).

## Dependencies

simsalRbim was developed on R (v4.0.3). It depends on the following packages (in no particular order, excluding R base packages) and may have to be installed manually.

dplyr
ggplot2
gnm
prefmod
reshape2
rlang
stringr
viridis
ggrepel

The following function can be used to install single packages - or just the missing ones from CRAN.

install.packages("paste missing package name here")

### Installation

The development version of the simsalRbim package can be downloaded from GitHub with the following command.

# install.packages("devtools")
devtools::install_github("mytalbot/simsalRbim@main")
library(simsalRbim)

#### Manual installation

The source/binary files are also available here:

## Example

This example uses the internal data (ZickeZacke) to perform a simple randomization on the positioning of the incomplete ‘HoiHoiHoi’ item.

library(simsalRbim)

dat        <- ZickeZacke

simOpt     <- "HoiHoiHoi"
GT         <- c("Zacke", "Huehner", "Kacke",  "Zicke" )

predat     <- bimpre(dat=dat, GT=GT, simOpt=simOpt)
#> simsalRbim: 1 tie(s) marked.

worth      <- bimworth(ydata    = predat,
GT       = GT,
simOpt   = simOpt,
showPlot = "worth")