Hepner Hall on SDSU campus

The research life and times of Richard A. Levine

"Is mathematical analysis...only a vain play of the mind? It can give to the physicist only a convenient language; is this not a mediocre service, which, strictly speaking could be done without; and even is it not to be feared that this artificial language may be a veil interposed between reality and the eye of the physicist? Far from it; without this language most of the intimate analogies of things would have remained forever unknown to us; and we should forever have been ignorant of the internal harmony of the world, which is...the only true objective reality."

                                                                                                                                            - Henri Poincare

I like the label 'data scientist': I am all in on the big data analytics wave, developing and applying statistical methods to summarize, visualize, and analyze potentially massive data sets to solve and communicate results about scientific problems of the day.
My research interests focus on development and application of Monte Carlo techniques and machine learning tools in statistical inference and Bayesian decision theory. In particular, I enjoy statistical applications in education and medicine.
My current research program may be divided into five areas:

Here is the complete bibliographical list in chronological order within each of these areas. First are funded grants for which I am principal investigator. Second are articles in print, followed by manuscripts submitted for publication, and then conference proceedings.

Extramural Funding serving as PI:

Intramural Funding:


  1. Predictive Analytics Pipeline for Student Success Efficacy Studies. Submitted to Applied Artificial Intelligence. (with He, Bohonak, Fan, and Stronach)

  2. Analytics Approach to Selecting Students for a Competitive Program with Unobserved Student Success Outcome. Submitted to Journal of Research on Educational Effectiveness. (with He, Beemer, and Stronach)

  3. Random Forest Implementations with an Eye on Variable Selection Bias and Prediction Accuracy. Submitted to Data Mining and Knowledge Discovery. (with Calhoun, Hallet, Su, Cafri, and Fan)

  4. Assessing Instructional Modalities: Individualized Treatment Effects for Personalized Learning. (2018). Journal of Statistics Education. DOI 10.1080/10691898.2018.1426400

  5. Random Forests of Interaction Trees for Estimating Individualized Treatment Effects in Randomized Trials. To appear in Statistics in Medicine. (with Su, Pena, Liu)

  6. A Semi-Parametric Covariate-Modulated Local Falso Discovery Rate for Genome-Wide Association Studies. To appear in Annals of Applied Statistics. (with Zablocki, Schork, Xu, Wang, and Fan)

  7. Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research. (2018). Practical Assessment, Research, and Evaluation 23(1). Available online: http://pareonline.net/getvn.asp?v=23&n=1. (with He, Fan, and Stronach)

  8. Examining the Recruitment, Placement, and Career Trajectories of Secondary Mathematics Teachers Prepared for High Need Schools. To appear in Teachers College Record. (with Zahner, Chapin, He, and Afonso)

  9. Ensemble Learning for Estimating Individualized Treatment Effects in Student Success Studies. (2017). International Journal of Artificial Intelligence in Education/ https://doi.org/10.1007/s40593- 017-0148-x (with Beemer, Spoon, He, and Fan)

  10. Balancing Student Success: Assessing Supplemental Instructions through Coarsened Exact Matching. (2017). Technology, Knowledge, and Learning 22, 335-351. (with Guarcello, Beemer, Frazee, Laumakis, and Schellenberg)

  11. Sparse Estimation of Generalized Linear Models (GLM) via Approximated Information Criterion. To appear in Statistica Sinica. (with Su, Fan, Nunn, and Tsai)

  12. Shrinkage Estimation for NFL Field Goal Success Probabilities. (2017). Journal of Sports Analytics. 3, 129-146. (with J. Osborne)

  13. Random Forests for Evaluating Pedagogy and Informing Personalized Learning. (2016). Journal of Educational Data Mining 8, 20-50. (with Spoon, Beemer, Whitmer, Fan, Frazee, Stronach, Bohonak)

  14. How Reliable is your Multi-Rater Inter-Rater Reliability Index? (2016). The American Statistician 70, 373-384. (with D. Quarfoot)

  15. Covariate-Modulated Local False Discovery Rate for GWAS. (2014). Bioinformatics doi:10.1093/bioinformatics/btu145. (with Zablocki, Thompson, Schork, Andreassen, and Dale)

  16. Topic Models: A Tutorial with R. (2014). International Journal of Semantic Computing 8, 85-98. (with Richardson, Bowers, Woodill, Barr, and Gawron)

  17. Journal of Computational and Graphical Statistics. (2014). WIREs Computational Statistics 06/2014 DOI: 10.1002/wics.1307. (with Sampson and Lee)

  18. Bayesian Multivariate Survival Trees for Tooth Prognosis. (2014). Statistical Analysis and Data Mining 7, 111-124. (with Fan, Su, and Nunn)

  19. On Variable Importance Rankings for Correlated Survival Datat, with Applications to Tooth Loss. (2014). Statistical Modeling 14, 523-547. (with Hallett, Fan, Su, and Nunn)

  20. Predicting Glaucoma Progression using Decision Trees for Clustered Data by Goodness of Split. (2013). International Journal of Semantic Computing 7, 157-172. (with Sharpsten, Fan, Barr, Su, and Demirel)

  21. When Are Two Pieces Better than One, Fitting and Testing OLS and RMA Regressions. (2013). Environmetrics 24, 306-316. (with Friedman and Bohonak)

  22. Multiple-Inflation Poisson Model with L1 Regularization. (2013). Statistica Sinica 23, 1071-1090. (with Su, Fan, Tan, and Tripathi)

  23. Facilitating Score and Causal Inference Trees in Observational Studies. (2012). Journal of Machine Learning Research 13, 2955-2994. (with Su, Kang, Fan and Yan)

  24. Frailty Modeling via the Empirical Bayes Hastings Sampler. (2012). Computational Statistics and Data Analysis 56, 1303-1318. (with J. Fan, S. Demirel, P. Ohman-Strickland)

  25. If We Build It, Will They Compete? (2012). Chance 25, 26-31. (with M. Watnik)

  26. Development of Prognostic Indicators Using Classification and Regression Trees. (2011). Periodontology 2000 58, 1-10. (with M. Nunn, J. Fan, X. Su, et al.)

  27. Measurement Error of Dietary Self-report in Intervention Trials. (2011). American Journal of Epidemiology 172, 819-827. (with L. Natarajan, J. Fan, M. Pu, et al.)

  28. Meso-scale Monte Carlo Sintering with Anisotropic Grain Growth. (2010). Advances in Sintering Science and Technology, 101-111. (with G. Brown, V. Tikare, E. Olevsky)

  29. Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data. (2009). Investigative Ophthalmology and Vision Science 50, 674-680. (with S. Demirel, J. Fan, C. Johnson, and PPIG group)

  30. Three-Dimensional Solar Cell Finite-Element Sintering Simulation. (2009). Journal of the American Ceramic Society 82, 1450-1455. (with G. Brown, A. Shaikh, and E. Olevsky)

  31. Comment: On Random Scan Gibbs Samplers. (2008). Statistical Science 23, 192-195. (with G. Casella)

  32. Lundberg Process Lifetime Distributions with Aging. (2008). Journal of Probability and Statistical Science 6, 13-24. (with J. Fan and S. Ghurye)

  33. To amnio or not to amnio: that is the decision for Bayes. (2007). Chance 20, 26-32. (with J. Fan)

  34. Bayesian Estimation for the AR(1) Model Using Asymmetric Loss Functions. (2007). Journal of Applied Statistical Science 15, 295-304. (with D. Bhattacharya)
  35. Bayesian demand updating in the lost sales newsvendor problem: A two-moment approximation. (2007). European Journal of Operational Research 182, 256-281. (with E. Berk and Ü. Gürler)

  36. Visual Field Quality Control in the Ocular Hypertension Treatment Study (OHTS). (2007). Journal of Glaucoma 16, 665-669. (with J. Keltner and the VFRC)

  37. Effects of abiotic factors on the phylogenetic diversity of bacterial communities in acidic thermal springs. (2007). Applied and Environmental Microbiology, 73: 2612-2623. (with S. Kelly and J. Mathur and collegues)

  38. Optimizing Random Scan Gibbs Samplers. (2006). Journal of Multivariate Analysis 97, 2071-2100. (with G. Casella)

  39. Assigning Tooth Prognosis by Multivariate Survival Trees. (2006). Journal of the American Statistical Association 101, 959-967. (with J. Fan, X-G. Su, M. Nunn, and M. LeBlanc)
  40. Asymmetries and Visual Field Summaries as Predictors of Glaucoma in the Ocular Hypertension Treatment Study (OHTS). (2006). Investigative Ophthalmology and Vision Science 47, 3896-3903. (with J. Keltner and the VFRC)

  41. The Association Between Glaucomatous Visual Fields and Optic Nerve Head Features in the Ocular Hypertension Treatment Study (OHTS) (2006). Ophthalmology 113, 1603-1612. (with J. Keltner and the VFRC)

  42. Normal Visual Field Tests Following Glaucomatous Visual Field Endpoints In the Ocular Hypertension Treatment Study (OHTS). (2005). Archives of Ophthalmology. 123, 1201-1206. (with J. Keltner and the VFRC)

  43. Bayesian Approaches to Modeling Stated Preference Data. (2005). Applications of Simulation Methods in Environmental and Resource Economics, edited by R. Scarpa and A. A. Alberini. Springer, New York, Chapter 10. (with D. Layton)

  44. On Asymptotically Efficient Sequential Tests for First Order Autoregressive Times Series with a Unit Root. (2005). Journal of Probability and Statistical Science 3, 213-228. (with D. Bhattacharya)
  45. A Note on Markov Chain Monte Carlo Sweep Strategies. (2005). Journal of Statistical Computation and Simulation 75, 253-262.

  46. Implementing the Random Scan Gibbs Sampler. (2005). Computational Statistics 20, 177-196. (with Z. Yu, W. Hanley, and J. Nitao)

  47. Implementing Componentwise Hastings Samplers. (2005). Computational Statistics and Data Analysis 2, 363-389. (with Z. Yu, B. Hanley, and J. Nitao)

  48. Sensitivity, Specificity, and other Diagnostic Measures with Multiple Sites per Unit. (2005). Contemporary Clinical Trials 26, 252-259. (with C. Drake)

  49. Comparing SF-36 scores across three groups of women with different health profiles. (2005). Quality of Life Research 14, 1251-1261. (with K. Yost, M. Haan, and E. Gold)

  50. An Automated (Markov Chain) Monte Carlo EM Algorithm. (2004). Journal of Statistical Computation and Simulation 74, 349-359. (with J. Fan)

  51. Penetrance of the Fragile-X Associated Tremor/ataxia Syndrome (FXTAS) in a Premutation Carrier Population: Initial Results from a California Family-based Study. (2004). Journal of the American Medical Association 291, 460-469. (with S. Jacquemont, R. Hagerman, P. Hagerman, and collaborators)

  52. Alien fishes in California watersheds: characteristics of successful and failed invaders. (2004). Ecological Applications 14, 587-596. (with M. Marchetti and P. Moyle)

  53. Invasive secies profiling? Exploring the Characteristics of Non-native Fishes Across Invastion Stages in California. (2004). Freshwater Biology 49, 646-661. (with M. Marchetti and P. Moyle)

  54. How Much Does the Far Future Matter? A Hierarchical Bayesian Analysis of the Public's Willingness to Mitigate Ecological Impacts of Climate Change. (2003). Journal of the American Statistical Association 98, 533-544. (with D. Layton)

  55. Implementations of Matching Priors for Frequentist Inferences. (2003). Biometrika 90, 127-137. (with G. Casella)
  56. Mega Deal? A Relative Performance Analysis for Major League Baseball Players. (2004). Economics, Management, and Optimization in Sports, 163-184. (with C-D. Lin)

  57. Fragile X Tremor/Ataxia Syndrome: Molecular, Clinical, and Neuroimaging Correlates. (2003). The American Journal of Human Genetics 72 (4), 869-878. (with S. Jacquemont, R. J. Hagerman, P. J. Hagerman, and collaborators)

  58. Implementations of the Monte Carlo EM Algorithm. (2001). Journal of Computational and Graphical Statistics 10, 422-439. (with G. Casella)
  59. Discussion of "The Art of Data Augmentation" by D. A. van Dyk and X. Meng. (2001). Journal of Computational and Graphical Statistics 10, 51-58.
  60. The Newsboy Problem with Bayesian Updating of the Demand Distribution and Censored Observations. (2001). Bayesian Methods with Applications to Science, Policy, and Official Statistics, Selected Papers from ISBA 2000: The Sixth World Meeting of the International Society for Bayesian Analysis, 21-29. (with Ü. Gürler and E. Berk)
  61. NFL Y2K PCA. (2001). Journal of Statistics Education 9(3). (with M. Watnik)

  62. Bayesian Assessment of Climate Change. (2000). Journal of Climate 13, 3805-3820. (with L. M. Berliner and D. Shea)
  63. Multi-component Lifetime Distributions in the Presence of Aging. (2000). Journal of Applied Probability 37, 521-533. (with J. Fan and S. G. Ghurye)
  64. C-Reactive Protein Predicts All-Cause and Cardiovascular Mortality in Hemodialysis Patients. (2000). American Journal of Kidney Diseases 35, 469-476. (with J. Y. Yeun, V. Mantadilok, and G. A. Kaysen)
  65. Statistical Principles for Climate Change Studies. (1999). Journal of Climate 12, 565-574. (with M. Berliner)
  66. Prospective Magnetic Resonance Imaging Assessment of Acute Cervical Spine Injuries in a Level I Trauma Center. (1999). Radiology 213, 203-212. (with R. W. Katzberg, P. Benedetti, C. Drake, M. Ivanovic, C. Beatty, W. Nemzek, R. McFall, F. Ontell, D. Bishop)
  67. Wavelets and Field Forecast Verification. (1997). Monthly Weather Review 125 (6), 1329-1341. (with W. M. Briggs)
  68. Repeated Challenge Studies: A Comparison of Union-Intersection Testing with Linear Modeling. (1997). Psychometrika 62, 435-455. (with P. A. Ohman)
  69. Convergence of Posterior Odds. (1996). Journal of Statistical Planning and Inference 55, 331-344. (with G. Casella)
  70. Carpal Tunnel Syndrome and Occupation in U.S. Navy Enlisted Personnel. (1996). Archives of Environmental Health, 51 (5), 395-407. (with Garland, F C; Garland, C F; Doyle, E J Jr; Balazs, L L; Pugh, W M; Gorham, E D.)
Book Reviews: Conference proceedings plus:

"Colleagues at work" by A. Fenech
On left is Professor Ülkü Gürler of Bilkent University, Turkey

More info to come...

Questions or comments, send me an email at rlevine@mail.sdsu.edu
Go back to my main page.