Precision Medicine - 2014

Chanta, S., Mayorga, M. E., & McLay, L. A. (2014). Improving emergency service in rural areas: a bi-objective covering location model for EMS systems. Annals of Operations Research, 221(1), 133–159. https://doi.org/10.1007/s10479-011-0972-6

Toro-Díaz, H., Mayorga, M. E., Barritt, A. S., Orman, E. S., & Wheeler, S. B. (2014). Predicting Liver Transplant Capacity Using Discrete Event Simulation. Medical Decision Making, 35(6), 784–796. https://doi.org/10.1177/0272989x14559055

Song, R., Kosorok, M. R., & Fine, J. P. (2014). Comment on ”Multiscale change point inference” by Frick, Munk and Sieling [Review of Multiscale change point inference, by K. Frick, A. Munk, & H. Sieling]. Journal of the Royal Statistical Society, Series B, 76(3), 564.

Beheshti, B., Özalt?n, O. Y., Zare, M. H., & Prokopyev, O. A. (2014). Exact solution approach for a class of nonlinear bilevel knapsack problems. Journal of Global Optimization, 61(2), 291–310. https://doi.org/10.1007/s10898-014-0189-8

Tsiatis, A. A., & Davidian, M. (2014). Missing data methods: A semiparametric perspective. In G. Fitzmaurice, M. Kenward, G. Molenberghs, A. A. Tsiatis, & G. Verbeke (Eds.), Handbook of Missing Data. Boca Raton: Chapman & Hall/CRC Press.

Vock, D. M., Davidian, M., & Tsiatis, A. A. (2014). SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models. Journal of Statistical Software, 56(Code Snippet 2). https://doi.org/10.18637/jss.v056.c02

Ren, Z., Davidian, M., George, S. L., Goldberg, R. M., Wright, F. A., Tsiatis, A. A., & Kosorok, M. R. (2014). Research Methods for Clinical Trials in Personalized Medicine: A Systematic Review. In Lost in Translation (pp. 659–684). https://doi.org/10.1142/9789814489072_0025

Zhao, Y. Q., Zeng, D., Laber, E. B., Song, R., Yuan, M., & Kosorok, M. R. (2014). Doubly robust learning for estimating individualized treatment with censored data. Biometrika, 102(1), 151–168. https://doi.org/10.1093/biomet/asu050

Davidian, M. (2014). Publishing without perishing and other career advice. Past, Present, and Future of Statistical Science, 581–591.

Davidian, M., Lin, X., Morris, J. S., & Stefanski, L. A. (Eds.). (2014). The Work of Raymond J. Carroll. https://doi.org/10.1007/978-3-319-05801-6

Baraldi, R., Cross, K., McChesney, C., Poag, L., Thorpe, E., Flores, K. B., & Banks, H. T. (2014). Uncertainty quantification for a model of HIV-1 patient response to antiretroviral therapy interruptions. 2014 american control conference (acc), 2753–2758.

Schulte, P. J., Tsiatis, A. A., Laber, E. B., & Davidian, M. (2014). Q- and A-Learning Methods for Estimating Optimal Dynamic Treatment Regimes. STATISTICAL SCIENCE, 29(4), 640–661. https://doi.org/10.1214/13-sts450

Song, R., Lu, W., Ma, S., & Jeng, X. (J. (2014). Censored rank independence screening for high-dimensional survival data. Biometrika, 101(4), 799–814. https://doi.org/10.1093/biomet/asu047

Song, R., Yi, F., & Zou, H. (2014). On varying-coefficient independence screening for high-dimensional varying-coefficient models. Statistica Sinica, 24(4), 1735–1752.

Goldberg, Y., Song, R., Zeng, D. L., & Kosorok, M. R. (2014). Comment on "Dynamic treatment regimes: Technical challenges and applications". Electronic Journal of Statistics, 8, 1290–1300.

Chanta, S., Mayorga, M. E., & McLay, L. A. (2014). The minimum p-envy location problem with requirement on minimum survival rate. COMPUTERS & INDUSTRIAL ENGINEERING, 74, 228–239. https://doi.org/10.1016/j.cie.2014.06.001

Laber, E. B., Tsiatis, A. A., Davidian, M., & Holloway, S. T. (2014, September). Combining Biomarkers to Optimize Patient Treatment Recommendations Discussions. BIOMETRICS, Vol. 70, pp. 707–710. https://doi.org/10.1111/biom.12187

Bandara, D., Mayorga, M. E., & McLay, L. A. (2014). Priority dispatching strategies for EMS systems. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 65(4), 572–587. https://doi.org/10.1057/jors.2013.95

Sudtachat, K., Mayorga, M. E., & McLay, L. A. (2014). Recommendations for dispatching emergency vehicles under multitiered response via simulation. INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 21(4), 581–617. https://doi.org/10.1111/itor.12083

Verbeke, G., Fieuws, S., Molenberghs, G., & Davidian, M. (2014). The analysis of multivariate longitudinal data: A review. STATISTICAL METHODS IN MEDICAL RESEARCH, 23(1), 42–59. https://doi.org/10.1177/0962280212445834

Molenberghs, G., Kenward, M. G., Aerts, M., Verbeke, G., Tsiatis, A. A., Davidian, M., & Rizopoulos, D. (2014). On random sample size, ignorability, ancillarity, completeness, separability, and degeneracy: Sequential trials, random sample sizes, and missing data. STATISTICAL METHODS IN MEDICAL RESEARCH, 23(1), 11–41. https://doi.org/10.1177/0962280212445801

Davidian, M., & Kutal, C. (2014, January). Collaboration To Meet the Statistical Needs in the Chemistry Curriculum. https://doi.org/10.1021/ed400516y