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Mekuanint Simeneh Workie on Muck Rack

Mekuanint Simeneh Workie

As seen in: Wiley Online Library, Taylor & Francis Online
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Articles

Bayesian hierarchical joint model for analyzing zero-inflated count and binary data

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By Mekuanint Simeneh Workie, Xu Yi
| Taylor & Francis Online
Count and binary outcomes frequently occur in public health, economics, and social sciences, but joint modeling is difficult due to heterogeneous data, random effects, over-dispersion, and excess zeros. Traditional approaches that model these outcomes separately often fail to capture dependencies, resulting in biased estimates.
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Robust Bayesian Inference in the Multilevel Zero‐Inflated Generalized Poisson Model

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By Xu Yi, Mekuanint Simeneh Workie
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. Supporting Information Filename Description sim70173-sup-0001-supinfo.zipZip archive, 1.3 MB Data S1. Supporting Information. References 1 and , Regression Analysis of Count Data. No. 53 in Econometric Society Monographs (Cambridge University Press, 2013), https://doi.org/10.1017/CBO9781139013567. 2, “Zero-Inflated Poisson Regression, With an Application to Defects in Manufacturing,” Technometrics 34, no.
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