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Analyzing coarsened categorical data with or without probabilistic information

Vach, Werner and Alder, Cornelia and Pichler, Sandra. (2022) Analyzing coarsened categorical data with or without probabilistic information. The Stata Journal, 22 (1). pp. 158-194.

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Official URL: https://edoc.unibas.ch/88153/

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Abstract

In some applications, only a coarsened version of a categorical outcome variable can be observed. Parametric inference based on the maximum likelihood approach is feasible in principle, but it cannot be covered computationally by standard software tools. In this article, we present two commands facilitating maximum likelihood estimation in this situation for a wide range of parametric models for categorical outcomes-in the cases both of a nominal and an ordinal scale. In particular, the case of probabilistic information about the possible values of the outcome variable is also covered. Two examples motivating this scenario are presented and analyzed.
Faculties and Departments:05 Faculty of Science > Departement Umweltwissenschaften > Integrative Biologie > Integrative Prähistorische und Naturwissenschaftliche Archäologie (IPNA)
UniBasel Contributors:Pichler, Sandra L and Vach, Werner and Alder, Cornelia
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:SAGE Publications
ISSN:1536-867X
e-ISSN:1536-8734
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Identification Number:
edoc DOI:
Last Modified:11 Apr 2022 11:45
Deposited On:11 Apr 2022 11:45

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