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Quantile regression for count data: jittering versus regression coefficients modelling in the analysis of credits earned by university students after remote teaching
The extension of quantile regression to count data raises several issues. We compare the traditional approach, based on transforming the count variable using jittering, with a recently proposed approach in which the coefficients of quantile regression are modelled by parametric functions. We exploit...
Autores principales: | Carcaiso, Viviana, Grilli, Leonardo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554398/ https://www.ncbi.nlm.nih.gov/pubmed/36245948 http://dx.doi.org/10.1007/s10260-022-00661-2 |
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