Peer-reviewed Publications

• Yoon, J. and Fan, J.J. (2024). Forecasting the direction of the Fed's monetary policy decisions using random forests. Journal of Forecasting, 1-12. paper


• Liu, C., Fan, J.J., Bailey, B., Mueller, R.-A., and Linke, A., (2023). Assessing Predictive Ability of Dynamic Time Warping Functional Connectivity for ASD Classification. International Journal of Biomedical Imaging, Volume 2023, Article ID 8512461, 1-13. paper


• Thorp, J., Levine, R.A., Li, L., and Fan, J.J. (2023). Random forest of interaction trees for estimating individualized treatment regimes with ordered treatment levels in observational studies. Journal of Data Science, 21(2):391-411.


• Levine, R.A., Rivera, P.E., He, L., Fan, J.J., and Bresciani, M.J. (2022). A Learning Analytics Case Study: On Class Sizes in Undergraduate Writing Courses. Stat, 12(1):e527, 1-15.


• Fan, J.J., Beemer, J., Yan, X., and Levine, R.A. (2022). On machine learning methods for propensity score matching and weighting in educational data mining applications. In Artificial Intellegence in STEM Education, F. Ouyang, P. Jiao, B. McLaren, and A. Alavi (Eds.) Taylor & Francis, pp. 277-288.


• Li, L., Levine, R.A., and Fan, J.J. (2022). Causal effect random forest of interaction trees for learning individualized treatment regimes with multiple treatments in observational studies. Stat, 11:e457, 1-13.


• Shao, L., Ieong, M., Levine, R.A., Stronach, J. and Fan, J.J. (2022). Machine learning methods for course enrollment prediction. Strategic Enrollment Management Quarterly, 10(2):11-29.


• Shao, L, Levine, R.A., Hyman, S., Stronach, J., and Fan, J.J. (2022). A Combinatorial Optimization Framework for Scoring Students in University Admissions. Evaluation Review, 46(3):296-335.


• Shao, L., Levine, R.A., Fan, J.J. (2022). Estimating a Dose-Response Relationship in Quasi-Experimental Student Success Studies. International Journal of Artificial Intelligence in Education, paper


• Calhoun, P,. Su, X.G., Spoon, K., Levine, R.A., and Fan, J.J. (2021). Random Forest. In Wiley StatsRef: Statistics Reference Online. Davidian, M., Kenett, R.S., Longford, N.T., Molenberghs, G., Piegorsch, W.W., and Ruggeri, F., eds. Chichester: John Wiley & Sons.


• Wilke, M.C., Guarcello, M.A., Fan, J.J., and Levine, R.A. (2021). Estimating the Optimal Treatment Regime for Student Success Programs. Behaviormetrika, 48:309-343.


• Hillis, T., Guarcello, M.A., Levine, R.A, Fan, J.J. (2021). Causal inference in the presence of missing data using a random forest based matching algorithm. Stat, 10:e326, 1-8.


• Calhoun, P., Levine, R.A., and Fan, J.J. (2021) Repeated Measures Random Forests (RMRF): Identifying Factors Associated with Nocturnal Hypoglycemia. Biometrics, 77:343-351. Top Cited Article in Biometrics published between 1 Jan 2020-31 Dec 2021.


• Autenrieth, M., Levine, R.A., Fan, J.J., and Guarcello, M.A. (2021). Stacked Ensemble Learning for Propensity Score Methods in Observational Studies. Journal of Educational Data Mining, 13(1), 24-189. paper


• Calhoun, P, Hallett, M.J.,Su, X.G., Cafri, G., Levine, R.A., and Fan, J.J. (2020). Random Forest with Acceptance-Rejection Trees. Computational Statistics, 35(3), 983-999. paper


• Cafri, G., Calhoun, P., Fan, J.J. (2019). High Dimensional Variable Selection with Clustered Data: An Application of Random Multivariate Survival Forests for Detection of Outlier Medical Device Components. Journal of Statistical Computation and Simulation, 89(8):1410-1422. paper


• Pelaez, K., Levine, R.A., Fan, J.J., Guarcello, M., and Laumakis, M. (2019). Latent Class Analysis and Random Forest Ensemble to Identify At-Risk Students in Higher Education. Journal of Educational Data Mining, 11(1), 18-46. .


• Cafri, G., Graves, S.E., Sedrakyan, A., Fan, J.J., Calhoun, P., de Steiger, R.N., Cuthbert, A., Lorimer, M., and Paxton, E.W. (2019). Post-Market Surveillance of Arthroplasty Device Components Using Machine Learning Methods. Pharmacoepidemiology and Drug Safety, 28(11), 1440-1447. paper


• Calhoun, P., Su, X.G., Nunn, M.E., and Fan, J.J. (2018). Consturcting Multivariate Survival Trees: The MST Package for R. Journal of Statistical Software, 83(12):1-21. paper


• He, L., Levine, R.A., Bohonak, A.J., Fan, J.J., and Stronach, J. (2018). Predictive Analytics Machinery for STEM Student Success Studies. Applied Artificial Intelligence, 32(4):361-387. paper


• Cafri, G., Li, L., Pxaxton, E.W., Fan, J.J. (2018). Predicting Risk for Adverse Health Events Using Random Forest. Journal of Applied Statistics, 45(12):2279-2294. paper


• Beemer, J., Spoon, K., Fan, J.J., Stronach, J., Frazee, J.P., Bohonak, A.J., and Levine, R.A. (2018). Assessing Instructional Modalities: Individualized Treatment Effects for Personalized Learning. Journal of Statistics Education, 26(1):31-39.


• Su, X.G., Fan, J.J., Levine, R.A., Nunn, M.E., and Tsai, C.-L. (2018). Sparse Estimation of Generalized Linear Models (GLM) via Approximated Information Criteria. Statistica Sinica, 28:1561-1581. paper


• Beemer, J., Spoon, K., He, L.J., Fan, J.J., and Levine, R.A. (2018). Ensemble Learning for Estimating Individualized Treatment Effects in Student Success Studies. International Journal of Artificial Intelligence in Education, 28:315-335. paper


• Cafri, G. and Fan, J.J. (2018). Between-Within Effects in Survival Models with Cross-Classified Clustering: Application to the Evaluation of the Effectiveness of Medical Devices. Statistical Methods in Medical Research, 27(1):312-319. paper


• He, L., Levine, R.A., Fan, J.J., Beemer, J., and Stronach, J. (2018). Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research. Practical Assessment, Research & Evaluation, 23(1). paper


• Jahedi, A., Nasamran, C.A., Faires, B., Fan, J.J., Muller, R.-A. (2017). Distributed intrinsic functional connectivity patterns predict diagnostic status in large autism cohort. Brain Connectivity, 7(8):515-525. paper


• Spoon, K., Beemer, J., Whitmer, J.C., Fan, J.J., Frazee, J.P., Stronach, J., Bohonak, A.J., and Levine, R.A. (2016). Random forests for evaluating pedagogy and informing personalized learning. Journal of educational data mining, 8(2):20-50.


• Su, X.G., Wijayasinghe, C.S., Fan, J.J., and Zhang, Y. (2016). Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criteria. Biometrics, 72:751-759.


• Zhao, P., Su, X.G., Ge, T.T., and Fan, J.J. (2016). Propensity Score and Proximity Matching Using Random Forest. Contemporary Clinical Trials, 47:85-92. paper


• Malvar J., Vaida F., Sanders, C.F., Atkinson, J.H., Bohannon, W., Keltner J., Robinson-Papp J., Simpson, D.M., Marra, C.M., Cli.ord, D.B., Gelman, B., Fan, J.J., Grant, I. and Ellis, R.J. (2015). Predictors of New Onset Distal Neuropathic Pain in HIV-infected Individuals in the Era of Combination Antiretroviral Therapy. Pain, 156:731-739.


• Hallett MJ, Fan JJ, Su XG, Levine RA, and Nunn ME (2014). Random Forest and Variable Importance Rankings for Correlated Survival Data, with Applications to Tooth Loss. Statistical Modelling, 14:523-547. paper


• Maybauer, M.O., Maybauer, D.M., Enkhbaatar, P., Laporte, R., Wisniewska, H., Traber, L.D., Lin, C.D., Fan, J.J., Wisniewski, K., Schteingart, C.D., Landry, D.W., Riviere and P.J.-M., Traber, D. (2014). The Selective Vasopressin Type 1a Receptor Agonist Selepressin (FE 202158) Blocks Vascular Leak in Ovine Severe Sepsis. Critical Care Medicine, 42(7):e525-e533.


• Levine RA, Fan JJ, Su XG, and Nunn ME (2014). Bayesian survival trees for clustered observations, applied to tooth prognosis. Statistical Analysis and Data Mining, 7(2):111-124.


• Sharpsten L, Fan JJ, Barr JR, Su XG, Demirel S, and Levine R A (2013): Predicting Glaucoma Progression Using Decision Trees for Clustered Data by Goodness of Split. International Journal of Semantic Computing, 7(2):157-172.


• Su XG, Fan JJ, Levine RA, Tan XM, and Tripathi A (2013): Multiple-Inflation Poisson Model with L1 Regularization. Statistica Sinica, 23(3):1071-1090.


• Levine, RA, Fan, JJ, Ohman-Strickland, PA, and Demirel, S (2012): Frailty Modeling via the Empirical Bayes Hastings Sampler. Computational Statistics and Data Analysis, 56:1303 - 1318.


• Su XG, Kang J, Fan JJ, Levine RA, and Yan X (2012): Facilitating Score and Causal Inference Trees for Large Observational Studies. Journal of Machine Learning Research, 13:2871-2910.


• Chen, JW, Fan, JJ, and Huang, L-S (2011): Comparing optimal sampling acceptance plans for mixed, Type I and Type II censoring. International Journal of Applied Mathematics & Statistics, in press.


• Nunn, ME, Fan, JJ, Su, XG, Levine, RA, Lee, HJ, and McGuire, MK (2011): Development of prognostic indicators using Classification And Regression Trees (CART) for survival. Periodontology 2000, 58:1-10.


• Natarajan, L, Pu, M, Fan, JJ, Levine, RA, Patterson, RE, Thomson, CA, Rock, CL, and Pierce, JP (2010): Measurement error of dietary self-report in intervention trials. American Journal of Epidemiology, 172:819-827.


• Yang Y, Fan JJ and May SJ (2010): Bimodality of plasma glucose distributions in whites: a bootstrap approach to testing mixture models. Journal of Data Science, 8:483-493.


• Fan, JJ, Nunn ME and Su XG (2009): Multivariate Exponential Survival Trees And Their Application to Tooth Prognosis. Computational Statistics and Data Analysis, 53:1110-1121.


• Demirel S, Fortune B, Fan JJ, Levine RA, Torres R, Nguyen H, Mansberger SL, Gardiner SK, Cioffi GA and Johnson CA (2009): Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data. Investigative Ophthalmology & Visual Science, 50:674-680.


• Su XG, Zhou T, Yan X, Fan JJ and Yang S (2008): Interaction trees with censored survival data. International Journal of Biostatistics, Vol. 4:Iss. 1, Article 2.


• Fan JJ, Ghurye SG and Levine RA (2008): Lundberg Process Lifetime Distributions with Aging. Journal of Probability and Statistical Science, 6:13-24.


• Fan JJ and Levine RA (2007): To amnio or not to amnio: that is the decision for Bayes. Chance, 20:26-32.


• Keltner JL, Johnson CA, Cello KE, Bandermann SE, Fan JJ, Levine RA, Kass MA, and Gordon MO (2007): Visual Field Quality Control in the Ocular Hypertension Treatment Study (OHTS). Journal of Glaucoma, 16:665-669.


• Fan JJ, Su XG, Levine RA, Nunn ME and LeBlanc M (2006): Trees for Correlated Survival Data by Goodness of Split: with Applications to Tooth Prognosis. Journal of the American Statistical Association, 101:959-967.


• Su XG, Fan JJ, Wang A, and Johnson M (2006): On Simulating Multivariate Failure Times. International Journal of Applied Mathematics & Statistics, 5:8-18.


• Levine RA, Demirel S, Fan JJ, Keltner JL, Johnson CA, and Kass MA (2006): Asymmetries and Visual Field Summaries as Predictors of Glaucoma in the Ocular Hypertension Treatment Study (OHTS). Investigative Ophthalmology & Visual Science, 47:3896-3903.


• Keltner JL, Johnson CA, Anderson DR, Levine RA, Fan JJ, Cello KE, Quigley HA, Budenz DL, Parrish RK, Kass MA, and Gordon MO (2006): The Association Between Glaucomatous Visual Fields and Optic Nerve Head Features in the Ocular Hypertension Treatment Study (OHTS). Ophthalmology, 113:1603-1612.


• Fan JJ, May SJ, Zhou Y, and Barrett-Connor E (2005): Bimodality of 2-h plasma glucose distributions in whites: The Rancho Bernardo Study. Diabetes Care, 28:1451-1456.


• Keltner JL, Johnson CA, Levine RA, Fan JJ, Cello KE, Kass MA, and Gordon MO (2005): Normal Visual Field Tests Following Glaucomatous Visual Field Endpoints In the Ocular Hypertension Treatment Study (OHTS). Archives of Ophthalmology, 123:1201-1206.


• Su XG and Fan JJ (2004): Multivariate Survival Trees: A Maximum Likelihood Approach Based on Frailty Models. Biometrics, 60:93-99.


• Su XG, Wang M and Fan JJ (2004): Maximum Likelihood Regression Trees. Journal of Computational and Graphical Statistics, 13:586-598.


• Levine RA and Fan JJ (2004): An Automated (Markov Chain) Monte Carlo EM Algorithm. Journal of Statistical Computation and Simulation, 74:349-360.


• Murphy SA, Johnson LC, Wu L, Fan JJ and Lohan J (2003): Bereaved Parents' Outcomes 4 to 60 Months After Their Children's Deaths by Accident, Suicide, or Homicide: A Comparative Study Demonstrating Differences. Death Studies, 27:39-61.


• Fan JJ and Prentice RL (2002): Covariate-adjusted dependence estimation on a finite bivariate failure time region. Statistica Sinica, 12:689-705.


• Williams SG, Gandour-Edwards R, Deitch AD, Toscano S, Fan JJ, Sternberg CN, Pansadoro V, Calabro F, Rossetti A and White RWD (2001): Differences in gene expression in muscle-invasive bladder cancer: A comparison of Italian and American patients. European Urology, 39:430-437.


• Fan JJ, Prentice RL and Hsu L (2000): A class of weighted dependence measures for bivariate failure time data. Journal of Royal Statistical Society, Series B, 62:181-190.


• Fan JJ, Hsu L and Prentice RL (2000): Dependence estimation over a finite bivariate failure time region. Lifetime Data Analysis, 6:343-355.


• Fan JJ, Ghurye SG and Levine RA (2000): Multicomponent lifetime distributions in the presence of aging. Journal of Applied Probability, 37:521-533.


• Li H and Fan JJ (2000): A General Test of Association for Complex Diseases with Variable Age of Onset. Genetic Epidemiology, 19(Suppl 1):S43-S49.


• Hsu L, Prentice RL, Zhao LP and Fan JJ (1999): On dependence estimation using correlated failure time data from case-control family studies. Biometrika, 86:743-753.


• Murphy SA, Lohan J, Dimond M and Fan JJ (1998): Network and Mutual Support for Parents Bereaved Following the Violent Deaths of Their 12 to 28 Year Old Children: A Longitudinal, Prospective Analysis. Journal of Personal and Interpersonal Loss, 3:303-333.

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