Modelling Heterogeneity in Paired Comparison Data

Performs 'BTLLasso' (Schauberger and Tutz, 2017: Subject-Specific Modelling of Paired Comparison Data - a Lasso-Type Penalty Approach), a method to include different types of variables in paired comparison models and, therefore, to allow for heterogeneity between subjects. Variables can be subject-specific, object-specific and subject-object-specific and can have an influence on the attractiveness/strength of the objects. Suitable L1 penalty terms are used to cluster certain effects and to reduce the complexity of the models.


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install.packages("BTLLasso")

0.1-7 by Gunther Schauberger, a year ago


Browse source code at https://github.com/cran/BTLLasso


Authors: Gunther Schauberger


Documentation:   PDF Manual  


Task views: Psychometric Models and Methods


GPL (>= 2) license


Imports Rcpp, stringr, psychotools

Depends on Matrix, parallel, TeachingDemos

Linking to Rcpp, RcppArmadillo

System requirements: C++11


See at CRAN