arainboldt / bwstools

Tools for Case 1 Best-Worst Scaling (MaxDiff) Designs

bwsTools

Tools for Case 1 Best-Worst Scaling (MaxDiff) Designs

Installation

install.packages("bwsTools")

Tutorial

A paper introducing the package and showing basic usage information can be found at the Open Science Framework: https://osf.io/xftvq/

Citation

To cite bwsTools in publications, please use:

White, M. H., II. (2021). bwsTools: An R package for case 1 best-worst scaling. Journal of Choice Modelling, 39. doi: 10.1016/j.jocm.2021.100289

Contents

• Aggregate estimates, based on: analytical estimation of the multinomial logit model using ae_mnl() and Elo scores using elo()

• Individual estimates, based on: difference scores (best minus worst) using diffscoring(), random walks in directed networks using walkscoring(), empirical Bayes using e_bayescoring(), Elo scores using eloscoring(), and page rank scores using prscoring()

• A data.frame of balanced incomplete block designs for creating these studies, bibds, and a function to generate a balanced incomplete block design from this, make_bibd()