Brian Neelon, PhD
Associate Professor
Department of Public Health Sciences
Medical University of South Carolina
Contact Information:
Room CS305K
Department of Public Health Sciences
Medical University of South Carolina
135 Cannon Street, Suite 303
Charleston, SC 29425-8350 USA
E-mail: neelon@musc.edu
Research Interests: Bayesian inference; longitudinal data analysis; latent growth models; zero-inflated and semicontinuous models; spatial data analysis; health services research
Somewhat Current CV
Selected Publications
- Neelon B, Shoaibi A, Benjamin-Neelon SE (2018). A multivariate discrete failure time model for the analysis of infant motor development. Statistics in Medicine. Early view.
- Neelon B (2018). Bayesian zero-inflated negative binomial regression based on Pólya-Gamma mixtures. Bayesian Analysis. Advance publication.
- 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.
- Davis ML, Neelon B, Nietert PJ, Hunt KJ, Burgette LF, Lawson AB, Egede LE (2017). Addressing geographic confounding through spatial propensity scores: a study of racial disparities in diabetes. Statistical Methods in Medical Research.
In press.
- 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.
- 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.
- 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.
- Neelon B and Chung D (2017). The LZIP: A Bayesian latent factor model for correlated zero-inflated counts. Biometrics, 73, 185-196.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Smith VA, Preisser JS, Neelon B, Maciejewski ML (2014).
A marginalized two-part model for semicontinuous data. Statistics in Medicine, 33, 4891-4903.
- 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.
- 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.
- 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.
- Montagna S, Tokdar ST, Neelon B, Dunson DB (2012). Bayesian latent factor regression for functional and longitudinal data. Biometrics, 68, 1064-1073.
- 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.
- 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.
- 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.
- 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
- 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.
- Neelon B and Dunson DB (2004).
Bayesian isotonic regression and trend analysis.
Biometrics, 60, 177-191.
- 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.
Books and Book Chapters
- 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.
- Kupper L, Neelon B, O'Brien S. (2013). Exercises and Solutions in Statistical Theory. CRC Press.
- Kupper L, Neelon B, O'Brien S. (2010). Exercises and Solutions in Biostatistical Theory. CRC Press.