Random effect exponentiated-exponential geometric model for clustered/longitudinal zero-inflated count data
© 2019 Informa UK Limited, trading as Taylor & Francis Group.
| Veröffentlicht in: | Journal of applied statistics. - 1991. - 47(2020), 12 vom: 30., Seite 2272-2288 |
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| Weitere Verfasser: | , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | Journal of applied statistics |
| Schlagworte: | Journal Article Count model mixture model under- and over-dispersion zero-inflated poisson model zero-inflation |
| Zusammenfassung: | © 2019 Informa UK Limited, trading as Taylor & Francis Group. For count responses, there are situations in biomedical and sociological applications in which extra zeroes occur. Modeling correlated (e.g. repeated measures and clustered) zero-inflated count data includes special challenges because the correlation between measurements for a subject or a cluster needs to be taken into account. Moreover, zero-inflated count data are often faced with over/under dispersion problem. In this paper, we propose a random effect model for repeated measurements or clustered data with over/under dispersed response called random effect zero-inflated exponentiated-exponential geometric regression model. The proposed method was illustrated through real examples. The performance of the model and asymptotical properties of the estimations were investigated using simulation studies |
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| Beschreibung: | Date Revised 16.07.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2019.1706726 |