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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/

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()

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Install

install.packages('bwsTools')

Monthly Downloads

223

Version

1.1.0

License

MIT + file LICENSE

Issues

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Maintainer

Mark White

Last Published

March 19th, 2020

Functions in bwsTools (1.1.0)

vdata

Example Data Used in Vignettes
elo

Elo Method to Calculate Aggregate Best-Worst Scores
walkscoring

Walkscoring Method to Calculate Individual Best-Worst Scores
ae_mnl

Analytical Estimation of a Multinomial Logit Model for Best-Worst Scaling
indiv

Example Data for Individual-Level Best-Worst Scaling
e_bayescoring

Empirical Bayes Method to Calculate Individual Best-Worst Scores
diffscoring

Difference Method to Calculate Individual Best-Worst Scores
eloscoring

Elo Method to Calculate Individual Best-Worst Scores
make_bibd

Make Balanced Incomplete Block Designs from bibds Designs
prscoring

Page Rank Method to Calculate Individual Best-Worst Scores
agg

Example Data for Non-BIBD Aggregate-Level Best-Worst Scaling
bibds

Balanced Incomplete Block Designs for use in Best-Worst Scaling