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

• Learning analytics and educational data mining: My research team is currently developing data mining methods and algorithms to parse massive student information system and learning management system data to study student success in courses/programs, provide early alert systems for at-risk students, and assess pedagogical intervention strategies. This work is in collaboration with
  • SDSU Analytic Studies and Institutional Research (in which I serve as Faculty Advisor)
  • SDSU Instructional Technology Services
  • CRMSE collegues, Computational Statistics PhD students, and Statistics Masters students
  I serve on the SDSU Learning Analytics task force and and am a member of the Center for Research in Mathematics and Science Education and Joint Doctoral Program in Mathematics and Science Education. I am co-organizer of the SDSU Data Champions program, offered 2017-2018.

• Biostatistics: I am/have been involved in a number of projects as a
  • collaborator with UCSD Professor Wes Thompson developing Bayesian bioinformatics methods for GWAS;

  • statistical collaborator with the Creighton University School of Dentistry for studies in periodontal disease and tooth loss;

  • statistical collaborator on the Perimetry and Psychophysics in Glaucoma (PPIG) study at Devers Eye Institute through 2014;

  • collaborator with the Division of Biostatistics at the UCSD School of Medicine through 2013;

  • statistical consultant and collaborator at the SDSU Quality Assurance Project;

  • statistical consultant and collaborator with the UCDMC Department of Ophthalmology as part of the Visual Field Reading Center (VFRC) and the ocular hypertension treatment study (OHTS) from 2001-2008;

• Markov chain Monte Carlo methods: my main interest in this area is the development of new MCMC methodologies and the study of MCMC implementation strategies in terms of computational efficiency and statistical precision, including convergence issues.

• Environmental statistics: In a previous research life, I developed statistical methodologies for the study of environmental data towards understanding the Earth and the impacts of those nasty homo sapiens. My main focus was on detection of climate change and attribution of potential changes to anthropogenic and/or natural forcings. I was additionally interested in weather forecast verification and analysis of high dimensional climatological and geological images. My work was in collaboration with
  • Energy and Environment group at Lawrence Livermore National Laboratory;

  • Professor N. Saito, University of California, Davis, and Professor D. Layton, Evans School of Public Affairs, U of Washington, funded by an environmental statistics grant from NSF/EPA.

  • the SDSU/UC Davis Joint Doctoral Program in Ecology, in which I was a member.

  • Geophysical Statistics Project at the National Center for Atmospheric Research in Boulder, Colorado;

• Bayesian decision theory: I have a soft spot in my heart for decision theory. I enjoy dabbling in decision problems with Bayesian twists and neat computational nuances.

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:

• Acting on Actionable Intelligence: A Learning Analytics Methodlogy for Student Success Efficacy Studies, NSF 1633130 BIGDATA: IA, 2016-2019.

• Sustatining Success for Course Redesign, Learning Analytics, CSU Chancellor's Office, 2016-2017.

• co-PI, Action Research Project: Improving Time-to-Degree for STEM students changing majors, CSU Chancellor's Office, (PI Stronach, co-PI Bohonak), 2015-2016.

• Reducing Bottlenecks and Improving Student Success in Large Enrollment Statistics Courses, CSU Chancellor's Office, (PI with K. Duncan and J. Frazee), 2014-2015.

• Promising Course Redesign of Bottleneck Math/Stat Courses, CSU Chancellor's Office (PI with J. Bowers and J. Frazee), 2013-2014

• "Multivariate CART for Survival with Dental Applications", NIH NIDCR R01DE019656, 2011-2014 (with J. Fan, M. Nunn, X. Su)

• "Measuring and Predicting Visual Field Progression with Longitudinal-Survival CART'', NIH NEI 1R21EY018698-01A2, 2009-2011 (with J. Fan, S. Demirel, S. Gardiner, C. Johnson)
• "Computational Environmetrics/Biometrics for Environmental Studies and Public Health Policy," Fulbright scholarship grant, Zhejiang University, Hangzhou, China, 2007
• "Statistical Analysis of Uncertainty in Climate Change," NSF FRG-0139948, 2002-2006 (with L. M. Berliner and C. Wikle)
• "Bayesian Inventory Management under Censored Demand," NSF INT-0114738, 2001-2006 (with Ü. Gürler and E. Berk)
• "Probabilistic Modeling and Computational Methods in Environmental Statistics," NSF/EPA DMS-9978321, 1999-2001 (with D. Layton and N. Saito)
• "Parallel Computing Environment for Research in the Statistical Science," NSF DMS-0079430, 9/1/00 - 8/31/02 (with J. Fan, H. Li, W. Polonkik, and J-L. Wang)

• UCD Faculty Research Grant, ``Optimal Markov Chain Monte Carlo Samplers,'' 2001 - 2002

• UCD Faculty Research Grant, ``Improved Monte Carlo Markov Chain Sampling Schemes,'' Summer 1997

• UCD Junior Faculty Research Fellowship, ``Improved Monte Carlo Markov Chain Sampling Schemes,'' 1996 - 1997

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.)

• Review of the book "Statistical Methods in the Atmospheric Sciences" by D. Wilks. (2000). Journal of the American Statistical Association 95, 344-345.

• Review of the book "Practical Statistics by Example Using Microsoft Excel." American Statistician 54, 151-153. (with J. Fan)

• JCGS MCMC Special Issue: Dedicated to the Memory of George Casella, 1951-2012. JCGS, 22, 515-517.

• Journal of Computational and Graphical Statistics Volume Previews: 2011, 2012, 2013

• JCGS Celebrates the International Year of Statistics. AmStat News, March 2013 issue.

• JCGS turns 20! AmStat News, March 2012 Issue.

• Publishing Animations, 3D visualizations, and movies in JCGS. JCGS 19, 1-2 plus 20 page online supplement.

• NFL Player Rating Systems: An Investigation of the Passer Rating and Proposal for a Rusher Rating. (with J. Wilson)

• The General Manager as a Sabrmetrician: Quantitative Decision-making for Designing a Winning (and Profitable) Team (with C-D. Lin and J. Davis)

• Virtual Reality of Sintering: Implementation of Multiple Scale Models. (2006). In Advances in Powder Metallurgy and Particulate Materials, Volume 1, Part 1. (work by PhD student G. Brown with B. Kushnarev, E. Olevsky, and V. Tikare)

• An Iterative Nonlinear Gaussianization Algorithm for Resampling Dependent Components. (2000). Proc. 2nd International Workshop on Independent Component Analysis and Blind Signal Separation. IEEE, Helsinki, Finland, 245-250. (work by Ph.D. student J. Lin with N. Saito)
• Polya-Lundberg Process Lifetime Distributions. (1999). Proceedings of the Joint Statistical Meetings, Baltimore, MD, Biometrics Section. (with J. Fan and S. G. Ghurye)
• Identifying Risk Factors Under Informative Loss to Follow Up. (1998). Proceedings of the Joint Statistical Meetings, Dallas, TX, American Statistical Association, Biometrics Section. (with C. Drake)
• Comparison of forecasts using the bootstrap. (1998). 14th Conf. on Probability and Statistics in the Atmospheric Sciences, Phoenix, AZ, Amer. Meteor. Soc., 1-4. (with W. M. Briggs)
• Wavelets and image comparison: new approaches to field forecast verification. (1996). 13th Conf. on Probability and Statistics in the Atmospheric Sciences, San Francisco, CA, Amer. Meteor. Soc., 274-277. (with W. M. Briggs)
• Assessing the Effect of Low-Level Lead Exposure. Technical Report, Biometrics Unit, Cornell University. (with Y-L. Tseng and C-H. Tsao)

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

Questions or comments, send me an email at rlevine@mail.sdsu.edu
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