Brian Neelon, PhD
Professor and Graduate Training Director for Biostatistics
Department of Public Health Sciences
Medical University of South Carolina

1. Mutiso F, Li H, Pearce JL, Benjamin-Neelon SE, Mueller NT, Neelon B (2024). A marginalized zero-inflated negative binomial model for spatial data: Modeling COVID-19 deaths in Georgia. Biometrical Journal. In press.
   
   
2. Seal S, Neelon B, Angel P, O'Quinn ED, Hill E, Vu T, Ghosh D, Mehta A, Wallace W, Alekseyenko AV (2024). SpaceANOVA: Spatial Co-occurrence Analysis of Cell Types in Multiplex Imaging Data Using Point Process and Functional ANOVA. Journal of Proteome Research. Online ahead of print.
   
   
3. Mutiso F, Li H, Pearce JL, Benjamin-Neelon SE, Mueller NT, Neelon B (2024). Bayesian kernel machine regression for count data: modeling the association between social vulnerability and COVID-19 deaths in South Carolina. Journal of the Royal Statistical Society: Series C, 73, 257-274.
   
   
4. Wen CC, Baker N, Paul R, Hill E, Hunt KJ, Li H, Gray K, Neelon B (2023). A Bayesian zero-inflated beta-binomial model for longitudinal data with group-specific changepoints. Statistics in Medicine, 43, 125-140.
   
   
5. Sun Z, Chung D, Neelon B, Millar-Wilson A, Ethier S, Xiao F, Zheng Y, Wallace K, Hardiman G (2023). A Bayesian framework for pathway-guided identification of cancer subgroups by integrating multiple types of genomic data. Statistics in Medicine, 42, 5266-5284.
   
   
6. Neelon B, Wen C-C, Benjamin-Neelon SE (2023). A multivariate spatiotemporal model for tracking COVID-19 incidence and death rates in socially vulnerable populations. Journal of Applied Statistics, 50, 1812-1835.
   
   
   • Here's R code for fitting simulated data.
     
   • Here's the Georgia adjacency matrix needed to generate the simulated data.
     
     
7. Mutiso F, Pearce JL, Benjamin-Neelon SE, Mueller NT, Li H, Neelon B (2022). Bayesian negative binomial regression with spatially varying dispersion: Modeling COVID-19 incidence in Georgia. Spatial Statistics. 52, 100703.
   
   
8. Allen CA, Chang Y, Neelon B, Chang W, Kim HJ, Li Z, Ma Q, Chung D (2022). A Bayesian multivariate mixture model for high throughput spatial transcriptomics, Biometrics, 79, 1775-1787.
   
   
9. White AA, Neelon B, Martin RH, Roberts JR, Korte JE, Williams EM, Cartmell KB (2022). Predicting HPV vaccination among Tdap vaccinated adolescents in Georgia at the county level. Annals of Epidemiology, 70, 74-78.
   
   
10. Neelon B, Mutiso F, Mueller NT, Pearce JL, Benjamin-Neelon SE (2021). Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States. PLOS ONE, 16(3): e0248702.
    
    
11. Davis ML, Neelon B, Nietert PJ, Hunt KJ, Burgette LF, Lawson AB, Egede LE (2021). Propensity score matching for multilevel spatial data: accounting for geographic confounding in health disparity studies. International Journal of Health Geographics, 20, 10.
    
    
12. Neelon B, Mutiso F, Mueller NT, Pearce JL, Benjamin-Neelon SE (2021). Associations between governor political affiliation and COVID-19 cases and deaths in the United States. American Journal of Preventive Medicine, 61, 115-119.
    
    
    • Recipient of the AJPM 2021 Paper of the Year award. See this link for more information.
      
    • Here's a video that AJPM put out in support of the article.
      
      
13. Allen CA, Benjamin-Neelon SE, Neelon B (2021). A Bayesian multivariate mixture model for skewed longitudinal data with intermittent missing observations: An application to infant motor development. Biometrics, 77, 675-688.
    
    
    • Here's example R code written and maintained by Carter Allen.
      
      
14. Li H, Benitez A, Neelon B (2020). A Bayesian hierarchical change point model with parameter constraints. Statistical Methods in Medical Research, 30, 316-330.
    
    
15. Shoaibi A, Neelon B, Lenert L (2020). Shared decision making: From decision science to data science. Medical Decision Making, 40, 254-265.
    
    
16. Davis ML, Neelon B, Nietert PJ, Hunt KJ, Burgette LF, Lawson AB, Egede LE (2019). Analysis of racial differences in hospital stays in the presence of geographic confounding. Spatial and Spatio-temporal Epidemiology, 30, 100284.
    
    
17. Neelon B, Shoaibi A, Benjamin-Neelon SE (2019). A multivariate discrete failure time model for the analysis of infant motor development. Statistics in Medicine, 38, 1543-1557.
    
    
18. Davis ML, Neelon B, Nietert PJ, Hunt KJ, Burgette LF, Lawson AB, Egede LE (2019). Addressing geographic confounding through spatial propensity scores: a study of racial disparities in diabetes. Statistical Methods in Medical Research, 28, 734-748.
    
    
19. Neelon B (2019). Bayesian zero-inflated negative binomial regression based on Pólya-Gamma mixtures. Bayesian Analysis, 14, 829-855.
    
    
    • Here's example R code.
      
      
20. Walker RJ, Neelon B, Davis ML, Egede LE (2018). Racial differences in spatial patterns for poor glycemic control in the southeastern United States. Annals of Epidemiology, 28, 153-159.
    
    
21. Smith VA, Neelon B, Maciejewski ML, Preisser JS (2017). Two parts are better than one: Modeling marginal means of semicontinuous data. Health Services and Outcomes Research Methodology, 17, 198-218.
    
    
22. Benecha H, Neelon B, Divaris K, Preisser JS (2017). Marginalized mixture models for count data from multiple source populations. Journal of Statistical Distributions and Applications, 4, 3.
    
    
23. Smith VA, Neelon B, Preisser JS, Maciejewski ML (2017). A marginalized two-part model for longitudinal semicontinuous data. Statistical Methods in Medical Research, 26, 1949-1968.
    
    
24. Neelon B and Chung D (2017). The LZIP: A Bayesian latent factor model for correlated zero-inflated counts. Biometrics, 73, 185-196.
    
    
    • Here's the web supplement.
      
    • Here's R code for fitting various models presented in the paper.
      
      
25. Neelon B, O'Malley AJ, Smith VA (2016). Modeling zero-modified count and semicontinuous data in health services research, part 1: Background and overview. Statistics in Medicine, 35, 5070-5093.
    
    
26. Neelon B, O'Malley AJ, Smith VA (2016). Modeling zero-modified count and semicontinuous data in health services research, part 2: Case studies. Statistics in Medicine, 35, 5094-511.
    
    
    • Here's SAS and WinBUGS code used to the fit the models in the case studies.
      
      
27. Neelon B, Li F, Burgette LF, Benjamin Neelon SE (2015). A spatiotemporal quantile regression model for emergency department expenditures. Statistics in Medicine, 34, 2559-2575.
    
    
    • Here's the web supplement.
      
    • Here's R code for fitting a simulated example.
      
      
28. Zhao L, Feng D, Buyse M, Neelon B (2015). Evaluation of treatment efficacy using a Bayesian mixture piecewise linear model of longitudinal biomarkers. Statistics in Medicine, 34, 1733-1746.
    
    
29. Neelon B, Zhu L, Benjamin Neelon SE (2015). Bayesian two-part spatial models for semicontinuous data with application to emergency department expenditures. Biostatistics, 16, 465-479.
    
    
    • Here's the web supplement.
      
    • Here's R code for fitting a simulated example.
      
      
30. Neelon B, Chang HC, Ling Q, Hastings SN (2014). Spatiotemporal hurdle models for zero-inflated count data: exploring trends in emergency department visits. Statistical Methods in Medical Research. In press.
    
    
    • Here's R2WinBUGS code for fitting the various models presented in the paper.
      
      
31. Amatya A, Bhaumik D, Normand S-L, Greenhouse J, Kaizar E, Neelon B, Gibbons RD (2014). Likelihood-based random effect meta-analysis of binary events. Journal of Biopharmaceutical Statistics, 25, 984-1004.
    
    
32. Smith VA, Preisser JS, Neelon B, Maciejewski ML (2014). A marginalized two-part model for semicontinuous data. Statistics in Medicine, 33, 4891-4903.
    
    
33. Neelon B, Gelfand AE, Miranda ML (2014). A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores. Journal of the Royal Statistical Society: Series C, 6, 737-761.
    
    
    • Here's R code for fitting a simulated example.
      
      
34. Neelon B, Anthopolos R, Miranda ML (2014). A spatial bivariate probit model for correlated binary data with application to adverse birth outcomes. Statistical Methods in Medical Research, 23(2), 119-133.
    
    
    • Here's R code for fitting a simulated example.
      
      
35. Neelon B, Ghosh P, Loebs PF (2013). A spatial Poisson hurdle model for exploring geographic variation in emergency department visits. Journal of the Royal Statistical Society: Series A, 176(2), 389-413.
    
    
    • Here's R and WinBUGS code for fitting a simulated example using R2WinBUGS.
      
      
36. Montagna S, Tokdar ST, Neelon B, Dunson DB (2012). Bayesian latent factor regression for functional and longitudinal data. Biometrics, 68, 1064-1073.
    
    
37. Bhaumik DK, Amatya A, Normand S-L, Greenhouse J, Kaizar L, Neelon B, Gibbons RD (2012). Meta-analysis of binary rare adverse event data. Journal of the American Statistical Association, 107, 555-567.
    
    
38. Neelon B, Swamy GK, Burgette LF, and Miranda ML (2011). A Bayesian growth mixture model to examine maternal hypertension and birth outcomes. Statistics in Medicine, 30, 2721-2735.
    
    
    • Here's R code for fitting a simulated example with random intercepts.
      
      
39. Neelon B, O'Malley AJ, and Normand S-L (2011). A Bayesian two-part latent class model for longitudinal medical expenditure data: assessing the impact of mental health and substance abuse parity. Biometrics, 67, 280-289.
    
    
    • Biometrics Showcase selection at JSM 2012.
      
    • Here's the web appendix.
      
    • Here's R code for fitting a simulated example.
      
      
40. Neelon B and O'Malley AJ. (2010). Bayesian analysis using power priors with application to pediatric quality of care. Journal of Biometrics and Biostatistics, 1:103. doi: 10.4172/2155-6180.1000103
    
    
41. Neelon B, O'Malley AJ, and Normand S-L (2010). A Bayesian model for repeated measures zero-inflated count data with application to psychiatric outpatient service use. Statistical Modelling, 10(4):421-439.
    
    
    • Here's WinBUGS code for fitting the zero-inflated Poisson model. Here's code for fitting the zero-altered and hurdle models.
      
      
42. Neelon B and Dunson DB (2004). Bayesian isotonic regression and trend analysis. Biometrics, 60, 177-191.
    
    
43. Dunson DB and Neelon B (2003). Bayesian inference on order constrained parameters in generalized linear models. Biometrics, 59, 286-295.
    
    
    • R code is available here. This ZIP file contains code for the minmax transformation function, along with a linear regression example illustrating the method.
      

1. Neelon B and O'Malley AJ. (2019). Two-part models for zero-modified count and semicontinuous data. In Levy A., Goring S., Gatsonis C., Sobolev B., van Ginneken E., Busse R. (eds.) Health Services Evaluation. Health Services Research Series. Springer, New York, NY.
   
   
2. Neelon B (2016). Spatial data analysis for health services research. In Andrew Lawson, Sudipto Banerjee, Robert Haining and Lola Ugarte (eds.) Handbook of Spatial Epidemiology. Chapter 29, pages 549--562. CRC Press.
   
   
3. Kupper L, Neelon B, O'Brien S. (2013). Exercises and Solutions in Statistical Theory. CRC Press.
   
   
4. Kupper L, Neelon B, O'Brien S. (2010). Exercises and Solutions in Biostatistical Theory. CRC Press.