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()