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:: Volume 16, Issue 2 (3-2020) ::
JSRI 2020, 16(2): 397-407 Back to browse issues page
Joint Modeling for Zero-Inflated Beta-Binomial and Normal Responses
Sedigheh Azimi 1, Ehsan Bahrami Samani , Mojtaba Ganjali  
1- , sazimi04@gmail.com
Abstract:   (1104 Views)
We present a new joint model with random effects for the correlated count with extra zero and continuous responses. In this model, we assume a Zero-Inflated Beta-Binomial distribution for the analysis of over dispersed binomial variable and a normal distribution for the analysis of continuous response. Furthermore, a full model likelihood function approach is used to obtain maximum likelihood estimates of the model parameters. We also evaluate the proposed model using the Monte Carlo simulation method. Finally, we fit the model to real data to find effective factors on mixed responses.
Keywords: Random effects, mixed response, the EM algorithm, population survey data.
Full-Text [PDF 337 kb]   (1384 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/06/9 | Accepted: 2021/01/12 | Published: 2021/09/19
References
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3. Casella, G., and Berger, R.L. (2001). Statistical Inference, 2nd Edition. Duxbury Press, Pacific Grove.
4. Hu, T., Gallins, P., and Zhou, Y-H. (2018). A Zero-inflated Beta-binomial Model for Microbiome Data Analysis. Stat., 7, e185. DOI:10.1002/sta4.185. [DOI:10.1002/sta4.185]
5. Kassahun, W., Neyens, T., Molenberghs, G., Faes, C., and Verbeke G. (2012). Modeling Overdispersed Longitudinal Binary Data Using a Combined Beta and Normal Random-Effects Model. Archives of Public Health, 70. DOI: 10.1186/0778-7367-70-7. [DOI:10.1186/0778-7367-70-7]
6. Kim, J., and Lee, J.H. (2015). The Validation of a Beta-binomial Model for Overdispersed Binomial Data. Communications in Statistics - Simulation and Computation, 46, 807-814. DOI: 10.1080/03610918.2014.96009. [DOI:10.1080/03610918.2014.960091]
7. Lambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34, 1-14. [DOI:10.2307/1269547]
8. Skellam, J.G. (1948). A Probability Distribution Derived from the Binomial Distribution by Regarding the Probability of a Success as Variable Between the Sets of Trials. Journal of the Royal Statistical Society, Series B, 10, 25-261. [DOI:10.1111/j.2517-6161.1948.tb00014.x]
9. Wang, W. (2013). Identifiability of Linear Mixed Effects Models. Electron. J. Stat., 7, 244-263. [DOI:10.1214/13-EJS770]
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Azimi S, Bahrami Samani E, Ganjali   M. Joint Modeling for Zero-Inflated Beta-Binomial and Normal Responses. JSRI 2020; 16 (2) :397-407
URL: http://jsri.srtc.ac.ir/article-1-382-en.html


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Volume 16, Issue 2 (3-2020) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران Journal of Statistical Research of Iran JSRI
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