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.


Reference manual

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0.1-7 by Gunther Schauberger, a year ago

Browse source code at

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