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Modelling Heterogeneity in Paired Comparison Data
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | BTLLasso |
Modelling Heterogeneity in Paired Comparison Data |
Statements
12 February 2024
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Performs 'BTLLasso' as described by Schauberger and Tutz (2019) <doi:10.18637/jss.v088.i09> and Schauberger and Tutz (2017) <doi:10.1177/1471082X17693086>. BTLLasso is 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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expanded from: GPL (≥ 2) (English)
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