Tools for Case 1 Best-Worst Scaling (MaxDiff) Designs
install.packages("bwsTools")
A paper introducing the package and showing basic usage information can be found at the Open Science Framework: https://osf.io/xftvq/
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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