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Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study

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  1. Das, Ujjwal & Das, Kalyan, 2018. "Inference on zero inflated ordinal models with semiparametric link," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 104-115.
  2. Loni Philip Tabb & Eric J. Tchetgen Tchetgen & Greg A. Wellenius & Brent A. Coull, 2016. "Marginalized Zero-Altered Models for Longitudinal Count Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 181-203, October.
  3. Chénangnon Frédéric Tovissodé & Aliou Diop & Romain Glèlè Kakaï, 2021. "Inference in skew generalized t-link models for clustered binary outcome via a parameter-expanded EM algorithm," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-31, April.
  4. Damgaard, Christian, 2008. "Modelling pin-point plant cover data along an environmental gradient," Ecological Modelling, Elsevier, vol. 214(2), pages 404-410.
  5. Yang, Yan & Simpson, Douglas, 2010. "Unified computational methods for regression analysis of zero-inflated and bound-inflated data," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1525-1534, June.
  6. Lijuan Wang, 2010. "IRT–ZIP Modeling for Multivariate Zero-Inflated Count Data," Journal of Educational and Behavioral Statistics, , vol. 35(6), pages 671-692, December.
  7. Chiara Mazzetta & Steve Brooks & Stephen N. Freeman, 2007. "On Smoothing Trends in Population Index Modeling," Biometrics, The International Biometric Society, vol. 63(4), pages 1007-1014, December.
  8. Becky Tang & Henry A. Frye & Alan E. Gelfand & John A. Silander, 2023. "Zero-Inflated Beta Distribution Regression Modeling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 117-137, March.
  9. J Paul Dunne & Nan Tian, 2016. "Determinants of Civil War and Excess Zeroes," SALDRU Working Papers 191, Southern Africa Labour and Development Research Unit, University of Cape Town.
  10. Channouf, Nabil & Fredette, Marc & MacGibbon, Brenda, 2014. "Power and sample size calculations for Poisson and zero-inflated Poisson regression models," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 241-251.
  11. H. He & W. Wang & J. Hu & R. Gallop & P. Crits-Christoph & Y. Xia, 2015. "Distribution-free inference of zero-inflated binomial data for longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2203-2219, October.
  12. Sileshi, Gudeta & Hailu, Girma & Nyadzi, Gerson I., 2009. "Traditional occupancy–abundance models are inadequate for zero-inflated ecological count data," Ecological Modelling, Elsevier, vol. 220(15), pages 1764-1775.
  13. Ren, Haiying & Zhao, Yuhui, 2021. "Technology opportunity discovery based on constructing, evaluating, and searching knowledge networks," Technovation, Elsevier, vol. 101(C).
  14. Sehee Kim & Fan Wu & Claudia Dahlerus & Deanna Chyn & Yi Li & Joseph M Messana, 2019. "Comparative effectiveness analysis of Medicare dialysis facility survey processes," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-11, April.
  15. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
  16. Kathryn M. Irvine & T. J. Rodhouse & Ilai N. Keren, 2016. "Extending Ordinal Regression with a Latent Zero-Augmented Beta Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(4), pages 619-640, December.
  17. J. Christopher Westland, 2017. "An empirical investigation of analytical procedures using mixture distributions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(4), pages 111-124, October.
  18. Yanling Li & Zita Oravecz & Shuai Zhou & Yosef Bodovski & Ian J. Barnett & Guangqing Chi & Yuan Zhou & Naomi P. Friedman & Scott I. Vrieze & Sy-Miin Chow, 2022. "Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 376-402, June.
  19. Yang, Zhiwei & Chen, Xiaohong & Pan, Ruixu & Yuan, Quan, 2022. "Exploring location factors of logistics facilities from a spatiotemporal perspective: A case study from Shanghai," Journal of Transport Geography, Elsevier, vol. 100(C).
  20. Li, Yan & Jiao, Yan, 2013. "Modeling seabird bycatch in the U.S. Atlantic pelagic longline fishery: Fixed year effect versus random year effect," Ecological Modelling, Elsevier, vol. 260(C), pages 36-41.
  21. Buu-Chau Truong & Nguyen Van Thuan & Nguyen Huu Hau & Michael McAleer, 2019. "Applications of the Newton-Raphson Method in Decision Sciences and Education," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 52-80, December.
  22. Dylan Molenaar & Paul Boeck, 2018. "Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 279-297, June.
  23. Qiang Fu & Tian‐Yi Zhou & Xin Guo, 2021. "Modified Poisson regression analysis of grouped and right‐censored counts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1347-1367, October.
  24. John Haslett & Andrew C. Parnell & John Hinde & Rafael de Andrade Moral, 2022. "Modelling Excess Zeros in Count Data: A New Perspective on Modelling Approaches," International Statistical Review, International Statistical Institute, vol. 90(2), pages 216-236, August.
  25. Niklas Elert, 2014. "What determines entry? Evidence from Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 55-92, August.
  26. Dunne J. Paul & Tian Nan, 2017. "Working Paper 274 - Conflict and Fragile States in Africa," Working Paper Series 2391, African Development Bank.
  27. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.
  28. Jane Osburn, 2011. "A Latent Variable Approach to Examining the Effects of HR Policies on the Inter- and Intra-Establishment Wage and Employment Structure: A Study of Two Precision Manufacturing Industries," Working Papers 451, U.S. Bureau of Labor Statistics.
  29. Xie, Feng-Chang & Wei, Bo-Cheng & Lin, Jin-Guan, 2009. "Score tests for zero-inflated generalized Poisson mixed regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3478-3489, July.
  30. Sarah Brown & Pulak Ghosh & Bhuvanesh Pareek & Karl Taylor, 2017. "Financial Hardship and Saving Behaviour: Bayesian Analysis of British Panel Data," Working Papers 2017011, The University of Sheffield, Department of Economics.
  31. Lee, Keunbaik & Joo, Yongsung & Song, Joon Jin & Harper, Dee Wood, 2011. "Analysis of zero-inflated clustered count data: A marginalized model approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 824-837, January.
  32. Brown, Sarah & Ghosh, Pulak & Pareek, Bhuvanesh & Taylor, Karl, 2021. "The protective role of saving: Bayesian analysis of British panel data," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 57-72.
  33. P. Christopher Zegras & Menghan Li & Talip Kilic & Nancy Lozano-Gracia & Ajinkya Ghorpade & Marco Tiberti & Ana I. Aguilera & Fang Zhao, 2018. "Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam, Tanzania," Transportation, Springer, vol. 45(2), pages 335-363, March.
  34. Jayabrata Biswas & Pulak Ghosh & Kiranmoy Das, 2020. "A semi-parametric quantile regression approach to zero-inflated and incomplete longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 261-283, June.
  35. Soutik Ghosal & Timothy S. Lau & Jeremy Gaskins & Maiying Kong, 2020. "A hierarchical mixed effect hurdle model for spatiotemporal count data and its application to identifying factors impacting health professional shortages," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1121-1144, November.
  36. Payandeh Najafabadi Amir T. & MohammadPour Saeed, 2018. "A k-Inflated Negative Binomial Mixture Regression Model: Application to Rate–Making Systems," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(2), pages 1-31, July.
  37. Robert Richardson, 2022. "Spatial Generalized Linear Models with Non-Gaussian Translation Processes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 4-21, March.
  38. Fatemeh Hassanzadeh & Iraj Kazemi, 2017. "Regression modeling of one-inflated positive count data," Statistical Papers, Springer, vol. 58(3), pages 791-809, September.
  39. Sophia Rabe-Hesketh & Anders Skrondal, 2007. "Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 123-140, June.
  40. Arvind Kumar Yadav & Susanta Nag & Pabitra Kumar Jena & Kirtti Ranjan Paltasingh, 2021. "Determinants of Antenatal Care Utilisation in India: A Count Data Modelling Approach," Journal of Development Policy and Practice, , vol. 6(2), pages 210-230, July.
  41. Abbas Moghimbeigi & Mohammed Reza Eshraghian & Kazem Mohammad & Brian Mcardle, 2008. "Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1193-1202.
  42. Alberto Baccini & Lucio Barabesi & Martina Cioni & Caterina Pisani, 2013. "Crossing the hurdle: the determinants of individual scientific performance," Department of Economics University of Siena 691, Department of Economics, University of Siena.
  43. Stacia M. DeSantis & Christos Lazaridis & Shuang Ji & Francis G. Spinale, 2014. "Analyzing propensity matched zero-inflated count outcomes in observational studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 127-141, January.
  44. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
  45. Yundan Xiao & Xiongqing Zhang & Ping Ji, 2015. "Modeling Forest Fire Occurrences Using Count-Data Mixed Models in Qiannan Autonomous Prefecture of Guizhou Province in China," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-12, March.
  46. Livio Finos & Fortunato Pesarin, 2020. "On zero-inflated permutation testing and some related problems," Statistical Papers, Springer, vol. 61(5), pages 2157-2174, October.
  47. Jonghyun Yun & Tao Wang & Guanghua Xiao, 2014. "Bayesian hidden Markov models to identify RNA–protein interaction sites in PAR-CLIP," Biometrics, The International Biometric Society, vol. 70(2), pages 430-440, June.
  48. Sellers, Kimberly F. & Raim, Andrew, 2016. "A flexible zero-inflated model to address data dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 68-80.
  49. Daniel B. Hall & Jing Shen, 2010. "Robust Estimation for Zero‐Inflated Poisson Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 237-252, June.
  50. Feng, Jiarui & Zhu, Zhongyi, 2011. "Semiparametric analysis of longitudinal zero-inflated count data," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 61-72, January.
  51. Garay, Aldo M. & Hashimoto, Elizabeth M. & Ortega, Edwin M.M. & Lachos, Víctor H., 2011. "On estimation and influence diagnostics for zero-inflated negative binomial regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1304-1318, March.
  52. William Greene, 2009. "Models for count data with endogenous participation," Empirical Economics, Springer, vol. 36(1), pages 133-173, February.
  53. Stefania Capecchi & Domenico Piccolo, 2017. "Dealing with heterogeneity in ordinal responses," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2375-2393, September.
  54. Yanlin Tang & Liya Xiang & Zhongyi Zhu, 2014. "Risk Factor Selection in Rate Making: EM Adaptive LASSO for Zero‐Inflated Poisson Regression Models," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1112-1127, June.
  55. Harald Oberhofer & Michael Pfaffermayr, 2014. "Two-Part Models for Fractional Responses Defined as Ratios of Integers," Econometrics, MDPI, vol. 2(3), pages 1-22, September.
  56. Jussiane Nader Gonçalves & Wagner Barreto-Souza, 2020. "Flexible regression models for counts with high-inflation of zeros," METRON, Springer;Sapienza Università di Roma, vol. 78(1), pages 71-95, April.
  57. Moghimbeigi, Abbas & Eshraghian, Mohammad Reza & Mohammad, Kazem & McArdle, Brian, 2009. "A score test for zero-inflation in multilevel count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1239-1248, February.
  58. Elek, P. & Varadi, B. & Varga, M., 2014. "Effects of geographical accessibility on the use of outpatient care services: quasi-experimental evidence from administrative panel data," Health, Econometrics and Data Group (HEDG) Working Papers 14/17, HEDG, c/o Department of Economics, University of York.
  59. Wei-Wen Hsu & David Todem & Kyungmann Kim, 2015. "Adjusted Supremum Score-Type Statistics for Evaluating Non-Standard Hypotheses," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 746-759, September.
  60. Cho, Daegon & Hwang, Youngdeok & Park, Jongwon, 2018. "More buzz, more vibes: Impact of social media on concert distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 103-113.
  61. David Todem & Wei-Wen Hsu & KyungMann Kim, 2012. "On the Efficiency of Score Tests for Homogeneity in Two-Component Parametric Models for Discrete Data," Biometrics, The International Biometric Society, vol. 68(3), pages 975-982, September.
  62. D. Todem & Y. Zhang & A. Ismail & W. Sohn, 2010. "Random effects regression models for count data with excess zeros in caries research," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(10), pages 1661-1679.
  63. Zhang, Yan & Zhao, Guangchuan & Gu, Hai, 2022. "Investing in health capital: Does medical insurance matter?," Research in International Business and Finance, Elsevier, vol. 61(C).
  64. Dalei Yu, 2016. "Conditional Akaike Information Criteria for a Class of Poisson Mixture Models with Random Effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1214-1235, December.
  65. A. Baccini & L. Barabesi & M. Cioni & C. Pisani, 2014. "Crossing the hurdle: the determinants of individual scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 2035-2062, December.
  66. Tousifur Rahman & Partha Jyoti Hazarika & M. Masoom Ali & Manash Pratim Barman, 2022. "Three-Inflated Poisson Distribution and its Application in Suicide Cases of India During Covid-19 Pandemic," Annals of Data Science, Springer, vol. 9(5), pages 1103-1127, October.
  67. Shweta Moorthy & Robert Brathwaite, 2019. "Refugees and rivals: The international dynamics of refugee flows," Conflict Management and Peace Science, Peace Science Society (International), vol. 36(2), pages 131-148, March.
  68. Camila Pareja Yale & Hugo Tsugunobu Yoshida Yoshizaki & Luiz Paulo Fávero, 2022. "A New Zero-Inflated Negative Binomial Multilevel Model for Forecasting the Demand of Disaster Relief Supplies in the State of Sao Paulo, Brazil," Mathematics, MDPI, vol. 10(22), pages 1-11, November.
  69. E. Bahrami Samani & Y. Amirian & M. Ganjali, 2012. "Likelihood estimation for longitudinal zero-inflated power series regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1965-1974, May.
  70. Qiang Fu & Xin Guo & Kenneth C. Land, 2020. "Optimizing Count Responses in Surveys: A Machine-learning Approach," Sociological Methods & Research, , vol. 49(3), pages 637-671, August.
  71. Tanzir Chowdhury & Mohammad Imran, 2010. "Morbidity Costs of Vehicular Air Pollution: Examining Dhaka City in Bangladesh," Working Papers id:2677, eSocialSciences.
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  79. Calama, Rafael & Mutke, Sven & Tomé, José & Gordo, Javier & Montero, Gregorio & Tomé, Margarida, 2011. "Modelling spatial and temporal variability in a zero-inflated variable: The case of stone pine (Pinus pinea L.) cone production," Ecological Modelling, Elsevier, vol. 222(3), pages 606-618.
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