| RcmdrPlugin.DCE-package | R Documentation |
This package adds menu items for discrete choice experiments (DCEs) to the R Commander. DCE is a question-based survey method that designs various combinations (profiles) of attribute levels using the experimental designs, asks respondents to select the most preferred profile in each choice set, and then measures preferences for the attribute levels by analyzing the responses. For details on DCEs, refer to Louviere et al. (2000).
This package is an R Commander plug-in package for discrete choice experiments (DCEs). It depends on support.CEs (Aizaki 2012), survival (Therneau 2020; Therneau and Grambsch 2000), and Rcmdr (Fox 2005, 2017; Fox and Bouchet-Valat 2020). Refer to Aizaki (2012), Aizaki et al. (2014), and “Non-Market Valuation with R” <http://lab.agr.hokudai.ac.jp/nmvr/> for a brief introduction to DCEs in R.
After successfully installing and loading the RcmdrPlugin.DCE, the R Commander window will appear, and then you will find “DCE” added to the top-level menus in the R Commander window.
Selecting “DCE” displays menu items. When selecting a menu item, the corresponding dialog box opens. The following dialog boxes are provided by RcmdrPlugin.DCE:
The dialog box for “Design choice sets...” designs
choice sets for DCE with the rotation design method or mix-and-match method
using the function rotation.design
in support.CEs.
The dialog box for “Create questions...”
creates DCE questions from the choice sets designed in the first dialog box
using the function questionnaire in support.CEs.
The dialog box for “Create design matrix...” creates
a design matrix from the choice sets designed in the first daialog box
using the function make.design.matrix
in support.CEs. The resultant design matrix can be also
saved as a CSV file with the option “Save as CSV file”.
The dialog box for “Import design matrix...” read a CSV file
containing the design matrix saved in the previous dialog box using
the function read.table in utils.
The dialog box for “Create data set for analysis...”
creates a data set for analysis from the choice sets designed in the first
dialog box and a data set containing responses to DCE questions using
the function make.dataset
in support.CEs.
The dialog box for “Fit model...” implements a conditional
logit model analysis of the data set for analysis generated in the previous
dialog box using the functions clogit
in survival and gofm
in support.CEs. The menu item “Fit model...” is activated
if a data set for analysis created in the previous dialog box is selected as
the active data set.
The dialog box for “Calculate MWTPs...”
calculates marginal willingness to pays (MWTPs) of non-monetary variables
from the model fitted in the previous dialog box using the function
mwtp in support.CEs. The menu item
“Calculate MWTPs...” is activated if the active model is of
class "clogit".
This work was supported by JSPS KAKENHI Grant Number JP20K06251.
Hideo Aizaki
Aizaki H (2012) Basic Functions for Supporting an Implementation of Choice Experiments in R. Journal of Statistical Software, 50(C2): 1–24. https://www.jstatsoft.org/article/view/v050c02.
Aizaki H (2021) support.CEs: Basic Functions for Supporting an Implementation of Choice Experiments. R package version 0.5-0. https://CRAN.R-project.org/package=support.CEs.
Aizaki H, Nakatani T, Sato K (2014) Stated Preference Methods Using R. Chapman and Hall/CRC.
Fox J (2005) The R Commander: A Basic Statistics Graphical User Interface to R. Journal of Statistical Software, 14(9): 1–42. https://www.jstatsoft.org/article/view/v014i09.
Fox J (2017) Using the R Commander: A Point-and-Click Interface for R. Chapman and Hall/CRC. https://socialsciences.mcmaster.ca/jfox/Books/RCommander/
Fox J, Bouchet-Valat M (2020) Rcmdr: R Commander. R package version 2.7-1. https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/.
Louviere JJ, Hensher DA, Swait JD (2000) Stated Choice Methods: Analysis and Application. Cambridge University Press.
Therneau T (2020) survival: Survival Analysis. R package version 3.2-7. https://CRAN.R-project.org/package=survival.
Therneau TM, Grambsch PM (2000) Modeling Survival Data: Extending the Cox Model. Springer.
if(interactive()) {
library(RcmdrPlugin.DCE)
}