RcmdrPlugin.BWS1-package {RcmdrPlugin.BWS1}

R Commander Plug-in for Case 1 Best–Worst Scaling

Description

This package adds menu items to the R Commander for implementing case 1 (object case) best–worst scaling (BWS1) from designing choice sets to measuring preferences for items. BWS1 is a question-based survey method that constructs various combinations of items (choice sets) using the experimental designs, asks respondents to select the best and worst items in each choice set, and then measures preferences for the items by analyzing the responses. For details on BWS1, refer to Louviere et al. (2015).

Details

This package is an R Commander Plug-in package for BWS1. It depends on R packages crossdes (Sailer 2005), support.BWS (Aizaki 2021; Aizaki and Fogarty 2023; Aizaki et al. 2014), support.CEs (Aizaki 2012), and survival (Therneau 2021; Therneau and Grambsch 2000) as well as the Rcmdr package (Fox 2005, 2017ab; Fox and Bouchet-Valat 2021). Refer to Aizaki and Fogarty (2023) and ‘Non-Market Valuation with R’ <http://lab.agr.hokudai.ac.jp/nmvr/> for a brief introduction to BWS1 in R. A manual for this package is available at <https://sites.google.com/view/r4sp/rcmdrplugin>.

After successfully installing and loading RcmdrPlugin.BWS1, the R Commander window will appear, and then you will find ‘BWS1’ added to the top-level menus in the R Commander window.

Selecting ‘BWS1’ displays several menu items. When selecting a menu item, the corresponding dialog box opens. The following dialog boxes are provided by RcmdrPlugin.BWS1:

• The dialog box for ‘Design choice sets...’ designs choice sets for BWS1 with an balanced incomplete block design (BIBD) using functions find.BIB and isGYD in the package crossdes.

• The dialog box for ‘Display questions...’ displays a series of questions for BWS1 according to choice sets designed in the previous dialog box using the function bws.questionnaire in the package support.BWS.

• The dialog box for ‘Create data set for analysis...’ creates a data set for analysis from the BIBD generated in the first dialog box and a data set containing responses to BWS1 questions using the function bws.dataset in support.BWS.

• Selecting the menu item ‘Measure preferences...’ gives options: ‘Counting approach’ and ‘Modeling approach’. Each has additional sub-items (see below).

• The dialog box for ‘Calculate scores...’ calculates various BW scores for each respondent from the data set for BWS1 analysis created in the previous dialog box, and then stores them into a data frame using the function bws.count in support.BWS.

• Selecting ‘Summarize scores’ summarizes the BW scores calculated in the previous dialog box and displays the results in the Output pane of the R Commander window.

• The dialog box for ‘Draw distributions of scores...’ draws distributions (bar plots) of the BW scores by item using an R basic graphic function barplot (S3 method for class ‘bws.count2’: bws.count).

• The dialog box for ‘Draw mean scores...’ draws a bar plot of means of the BW scores by item using the function barplot (S3 method for class ‘bws.count2’: bws.count).

• The dialog box for ‘Draw relationship between means and sds of scores...’ draws a plot of the relationship between means and standard deviations of the BW scores by item using an R basic graphic function plot (S3 method for class ‘bws.count2’: bws.count).

• The dialog box for ‘Fit model...’ implements a modeling analysis using the data set for BWS1 analysis generated in the previous dialog box using the functions clogit in survival and gofm in support.CEs.

• The dialog box for ‘Calculate shares of preferences...’ calculates shares of preferences for items from the model fitted in the previous dialog boxes using the function bws.sp in support.BWS.

• The dialog box for ‘Load saved objects...’ loads an R Data (rda) file saved in the dialog box for ‘Design choice sets...’ or ‘Create data set for analysis...’ using the function load in base.

Acknowledgments

This work was supported by JSPS KAKENHI Grant Number JP20K06251.

Author(s)

Hideo Aizaki

References

Aizaki H (2012) Basic Functions for Supporting an Implementation of Choice Experiments in R. Journal of Statistical Software, Code Snippets, 50(2): 1–24. DOI: 10.18637/jss.v050.c02

Aizaki H (2021) support.BWS: Tools for Case 1 Best-Worst Scaling. R package version 0.4-4. https://CRAN.R-project.org/package=support.BWS.

Aizaki H, Fogarty J (2023) R packages and tutorial for case 1 best-worst scaling. Journal of Choice Modelling, 46: 100394. DOI: 10.1016/j.jocm.2022.100394

Aizaki H, Nakatani T, Sato K (2014) Stated Preference Methods Using R. Chapman and Hall/CRC. DOI: 10.1201/b17292

Fox J (2005) The R Commander: A Basic Statistics Graphical User Interface to R. Journal of Statistical Software, 14(9): 1–42. DOI: 10.18637/jss.v014.i09

Fox J (2017a) Using the R Commander: A Point-and-Click Interface for R. Chapman and Hall/CRC. DOI: 10.1201/9781315380537

Fox J (2017b) Writing R Commander Plug-in Packages. Version 3.4-0. https://socialsciences.mcmaster.ca/jfox/Books/RCommander/plug-ins.html.

Fox J, Bouchet-Valat M (2021) Rcmdr: R Commander. R package version 2.7-1. https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/.

Louviere JJ, Flynn TN, Marley AAJ (2015) Best-Worst Scaling: Theory, Methods and Applications. Cambridge University Press. DOI: 10.1017/CBO9781107337855

Sailer O (2005) crossdes: A package for design and randomization in crossover studies. Rnews, 5/2: 24–27.

Therneau T (2021) survival: Survival Analysis. R package version 3.2-13. https://CRAN.R-project.org/package=survival.

Therneau TM, Grambsch PM (2000) Modeling Survival Data: Extending the Cox Model. Springer. DOI: 10.1007/978-1-4757-3294-8

Examples

if (interactive()) {
  library(RcmdrPlugin.BWS1)
}