Publications

Papers

  • Zhang, Y. Laber, E.B. (2015) Comment on an adaptive resampling test for detecting the presence of significant predictors, Journal of the American Statistical Association, 110 (512), 1451-1454.
  • Linn, K.A., Laber, E.B., Stefanski, L.A. (2016) Interactive Q-learning for probabilities and quantiles, tentatively accepted, Journal of the American Statistical Association.
  • Barberan, A., Dunn, R., Reich, B., Pacifici, K., Laber, E.B., Menninger, H., Morton, J., Henley, J., Leff, J., Miller, S., and Fierer, N. (2014) The ecology of microscopic life in household dust, Preceedings of the Royal Society B, tentatively accepted.
  • Meyer, N.J., Laber. E.B., Pacifici, K., Reich, B., Drake, J. Adaptive Management Strategies for White-Nose Syndrome. Selected for a poster presentation at the NIPS-14 Workshop: “From Bad Models to Good Policies.”
  • Laber, E.B., Zhao, Y.Q., Regh, T., Davidian, M. Tsiatis, A.A., Stanford, J.B., Zeng, D., Song, R., Kosorok, M. Sizing a phase II trial to find a nearly optimal personalized treatment strategy, to appear, Statistics in Medicine.
  • Zhang, Y., Laber, E.B., Davidian, M. Tsiatis, A.A. (2015) Using decision lists to construct interpretable and parsimonious treatment regimes, Biometrics, 71(4), 895-904.
  • Grantham, N., Reich, B., Pacifici, K, Laber, E.B. Menninger, H.L., Henley, J.B., Leff, J.W., Barberan, A., Fierer, N., Dunn, R.R. (2015) Fungi identify the geographic origin of dust samples, PLOS One, to appear.
  • Wu, F. Laber, E.B., Lipkovich, I., Severus, E. (2015) Estimating optimal treatment regimes in STEP-BD using Q-learning, International Journal of Bipolar Disorders, 3(1), 1-11.
  • Zhang, B., Tsiatis, A.A., Laber, E.B., Davidian, M. (2015) Rejoinder: A robust method for estimating optimal treatment regimes, Biometrics, 71(1), 267-273. Zhao, Y., Zeng, D., Laber, E.B., Kosorok, M. (2015) “New statistical learning methods for estimating optimal dynamic treatment regimes,Journal of the American Statistical Association, (2014).
  • Laber, E.B., Davidian, M., Tsiatis, A.A., Holloway, S.T. (2014) Discussion of Biomarkers to Optimize Patient Treatment Recommendations, Biometrics, 70(3), 707-710. Schulte, P., Tsiatis, A., Laber, E.B., Davidian, M. (2014) “A Comparison and Q- and A-Learning,” Statistical Science, 29(4), 640-661.
  • Laber, E.B., Murphy, S.A. Adaptive inference after model selection, Under Review. Huang, Y., Laber, E.B., Janes, H. (2014) Characterizing Expected Benefits of Biomarkers in Treatment Selection, Biostatistics, 16(2), 383-399.
  • Lim, J., Chanoit, A., Smith, D.T., Laber, E.B., Olby, N.J. (2014) Potassium channel antagonists 4-aminopyridine and the t-butyl carbamate derivative of 4-AP improve hind limb function in chronically non-ambulatory dogs, a blinded, placebo-controlled trial, PLOS One, 9(12), 1-19.
  • Linn, K.A., Laber, E.B., and Stefanski, L.A. (2014) iqLearn: interactive Q-learning in R, Journal of Statistical Software, tenatively accepted.
  • Huang, Y., Laber, E.B. (2014) Personalized evaluation of biomarker value: a cost-benefit perspective, Statistics in Biosciences, to appear.
  • Zhao, Y., Zeng, D., Laber, E.B., Kosorok, M. (2014) ” Doubly Robust Learning for Estimating Individualized Treatment with Censored Data, Biometrika, 101(2), 151-168.
  • Laber, E.B., Zhao, Y.Q. (2014) Tree-based methods for individualized treatment regimes, Biometrika, to appear.
  • Zhao, Y.Q.,Laber, E.B. (2014) Estimation of Optimal Dynamic Treatment Regimes, ” Clinical Trials, 11(4), 400-407.
  • Chakraborty, B., Laber, E.B., Zhao, Y. (2014)” Inference about the expected performance of a data-driven dynamic treatment regime, Clinical Trials 11(4), 408-417.
  • Laber, E.B., Lizotte, D.J., Ferguson, B. (2014) “Set-valued dynamic treatment regimes for competing outcomes,” Biometrics, 70(1), 53-61.
  • Shortreed, S.M., Laber, E.B., Stroup, T.S., Pineau, J., Murphy, S.A. (2014) Overcoming missing data in a sequential, multiple assignment, randomized clinical trial of patients with schizophrenia, ” Statistics in Medicine, 43(24), 4202-4214.
  • Zhang, B., Tsiatis, A., Laber, E.B., Davidian, M. “Robust estimation of optimal dynamic treatment regimes for sequential treatment decision,” Biometrika, 100(3) (2013): 681-694.
  • Vock, D., Tsiatis, A., Davidian, M., Laber, E.B., Tsuang, W.M., Finland-Copeland, A., Palmer, S.M. (2013) Estimating the causal effect of organ transplantation on the distribution of residual lifetime,” Biometrics, 69 (4), 820-829.
  • Laber, E.B., Shedden, K., Yang, Y. (2015) An imputation method for estimating the learning curve in classification,” Proceedings of the Abel Symposium, to appear.
  • Chakraborty, B., Laber, E.B., Zhao, Y. “Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap scheme,” Biometrics, 69 (4), 714-723.
  • Zhang, B., Tsiatis, A., Davidian, M., Zhang, M., Laber, E.B. “Estimating Optimal Treatment Regimes from a Classification Perspective,” Stat, 1(1), 103-114.
  • Laber, E.B., Murphy, S.A. (2011) Small Sample Inference for Generalization Error in Classification Using the CUD Bound,” Uncertainty in Artificial Intelligence, Machine Learning, July 2011.
  • Lizotte, D.J., Laber, E.B., Rush, J.A., and Murphy, S.A. “Exploratory Analysis of Practical Trial Data for Informing the Individualization Of Treatment.” Penn. State Methodology Center Technical Report 09-96.

Book Chapters

  • Davidian, M., Laber, E.B., Tsiatis, A.A. (2015), Dynamic treatment regimes. Cancer Clinical Trials: Current and Controversial Issues in Design and Analysis (ed. George, Wang, and Pang), Taylor and Francis.
  • Laber, E.B., Qian, M. Evaluating personalized treatment regimes (2014), Methods in Comparative Effectiveness Research (ed. Morton and Gatsonis), CRC Press.
  • Wu. Fan, Laber, E.B., Severus, E. Introduction to SMARTs. Bipolar Disorders (ed. Yildez et al.)
  • Linn, K.A., Laber, E.B., Stefanski, L.A. Constrained estimation for competing outcomes. Dynamic treatment regimes (ed. Kosorok and Moodie).
  • Davidian, M., Tsiatis, A.A., Laber, E.B. Value search estimators for optimal treatment regimes. Dynamic treatment regimes (ed. Kosorok and Moodie).
  • Shortreed, S. Laber, E.B., Pineau, J., Murphy, S.A. Imputing missing data from sequential multiple assignment randomized trials. Dynamic Treatment Regimes (ed. Kosorok and Moodie).