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| Factors associated with mortality from tuberculosis in Iran: an application of a generalized estimating equation-based zero-inflated negative binomial model to national registry data |
| Fatemeh Sarvi, Abbas Moghimbeigi, Hossein Mahjub, Mahshid Nasehi, Mahmoud Khodadost |
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Epidemiol Health. 2019;41:e2019032 Published online July 9, 2019 DOI: https://doi.org/10.4178/epih.e2019032 |
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Application of zero-inflated negative binomial mixed model to human microbiota sequence data . 2014;  Application of zero-inflated negative binomial mixed model to human microbiota sequence data . 2014; A bivariate zero-inflated negative binomial regression model for count data with excess zeros Economics Letters. 2003;78(3):373-378 Simulation on the Zero Inflated Negative Binomial (ZINB) to Model Overdispersed, Poisson Distributed Data IOP Conference Series: Materials Science and Engineering. 2019;546:052025 Analysis Death Rate of Age Model with Excess Zeros using Zero Inflated Negative Binomial and Negative Binomial Death Rate: Mortality AIDS Co-Infection Patients, Kelantan Malaysia Procedia Economics and Finance. 2012;2:275-283 Generalized Estimating Equations for Zero-Inflated Spatial Count Data Procedia Environmental Sciences. 2011;7:281-286 Estimation for zero-inflated beta-binomial regression model with missing response data Statistics in Medicine. 2018;37(26):3789-3813 PERFORMA PROPORSI ZERO-INFLATION PADA REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (STUDI KASUS: DATA TETANUS NEONATORUM DI JAWA TIMUR) E-Jurnal Matematika. 2018;7(1):41 Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial Journal of Physics: Conference Series. 2017;943:012051 A generalized Bayesian nonlinear mixed‐effects regression model for zero‐inflated longitudinal count data in tuberculosis trials Pharmaceutical Statistics. 2019; |
