Susan Murphy, Ph.D. | The Methodology Center

Susan Murphy, Ph.D.

Susan Murphy, Ph.D. Principal Investigator, The Methodology Center

H.E. Robbins Professor, Statistics

Research Professor, The Institute for Social Research

Professor, Psychiatry

 

Department of Statistics

439 West Hall, 1085 S. Univ.

University of Michigan

Ann Arbor, MI 48109-1107

 

734-647-3684

Website

CV

 

 

Education

Ph.D., University of North Carolina, 1989 (Statistics) 
B.S., Louisiana State University, 1980 (Mathematics)

 

 

Research Interests

My current primary interest concerns clinical trial design and the development of data analytic methods for informing multi-stage decision making in health. In particular for (1) constructing individualized sequences of treatments (known as adaptive interventions) for use in informing clinical decision making and (2) constructing real-time individualized sequences of treatments (known as just-in-time adaptive interventions) delivered by mobile devices. (See workshop on just in time adaptive interventions.) Adaptive Interventions, also known as dynamic treatment regimes, are composed of a sequence of decision rules that specify when to alter the therapy and specify which intensity or type of subsequent therapy should be offered. The decision rules employ variables such as patient response, risk, burden, adherence, and preference, collected during prior therapy. These regimes hold the promise of maximizing treatment efficacy by avoiding ill effects due to over-treatment and by providing increased treatment levels to those who can benefit.  My work has been funded by National Institute on Drug Abuse and by National Institute of Mental Health.

Current Projects and Collaborators

I am working on multiple related projects all aimed at how best to collect and use data in the development of adaptive interventions. My collaborators on these projects are Daniel Almirall, Linda Collins, and Inbal Nahum-Shani.

 

 

Selected Honors and Awards

2014: Elected a Fellow of the College of Problems of Drug Dependence

2013: MacArthur Fellowship

2011: Elected a Member of the International Statistical Institute.

2007-2008: Invited Fellow at the Center for Advanced Study in the Behavioral Sciences, Stanford University

2007-2009: Editor of The Annals of Statistics (with B. Silverman)

2005: Presented the Clifford C. Clogg Memorial Lecture, Sociology and Statistics Departments, Pennsylvania State University

2004: Awarded a University of Michigan Collegiate Professorship

2002: Elected a Fellow of the American Statistical Association

2000: Elected a Fellow of the Institute of Mathematical Statistics

1999: NSF Mid-Career Methodological Opportunities Fellowship

 

Selected Recent Publications

Peer-Reviewed Articles

Lagoa, C. M., Bekiroglu, K., Lanza, S. T. & Murphy, S. A. (in press). Designing adaptive intensive interventions using methods from engineering. Journal of Consulting and Clinical Psychology. PMC Journal-In Process

Bekiroglu, K., Lagoa, C., Murphy, S., & Lanza, S. T. (in press). A robust MPC approach to the design of treatments. Proceedings of the 52nd IEEE Conference on Decision and Control.

Kumar, S., Nilsen, W.J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., Riley, W. T., Shar, A., Spring, B., Spruijt-Metz, D., Hedeker, D., Honavar, V., Kravitz, R., Craig Lefebvre, R., Mohr, D.C., Murphy, S.A., Quinn, C., Shusterman, V., Swendeman, D. (2013). Mobile health technology evaluation, the mHealth evidence workshop. American Journal of Preventive Medicine, 45(2), 228-236. PMC Journal-In Process

Almirall, D., Griffin, B. A., McCaffrey, D. F., Ramchand, R., Yuen, R. A., & Murphy, S. A. (2013). Time-varying effect moderation using the structural nested mean model: Estimation using inverse-weighted regression with residuals. Statistics in Medicine. Advance online publication. doi: 10.1002/sim.5892

Almirall, D., Compton, S. N., Rynn, M. A., Walkup, J. T., & Murphy, S. A. (2012). SMARTer discontinuation trial designs for developing an adaptive treatment strategy. Journal of Child and Adolescent Psychopharmacology, 22(5), 364-374. PMCID: PMC3482379

Fonteneau, R., Murphy S. A., Wehenkel, L., & Ernst, D. (2012). Batch mode reinforcement learning based on the synthesis of artificial trajectories. Annals of Operations Research. Advance online publication. doi: 10.1007/s10479-012-1248-5 PMCID: PMC3773886

Lizotte, D. J., Bowling, M., & Murphy, S. A. (2012). Linear fitted Q-iteration with multiple reward functions. Journal of Machine Learning Research, 13, 3253-3295. PMCID: PMC3670261

Little, R. J., D’Agostino, R., Cohen, M. L., Dickersin, K., Emerson, S. S., Farrar, J. T., Frangakis, C., Hogan, J. W., Molenberghs, G., Murphy, S. A., … Stern, H. (2012). The prevention and treatment of missing data in clinical trials. New England Journal of Medicine 367, 1355-1360. PMCID: PMC3771340

Almirall, D., Lizotte, D., & Murphy, S. A. (2012). Comment: SMART design issues and the consideration of opposing outcomes: Discussion of “Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer” by Wang, Rotnitzky, Lin, Millikan, and Thall. Journal of the American Statistical Association, 107, 509-512. PMCID: PMC3607391

Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W., Gnagy, B., Fabiano, G., … Murphy, S. A. (2012). Experimental design and primary data analysis methods for comparing adaptive interventions. Psychological Methods, 17, 457-77. NIHMSID: NIHMS422560

Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W., Gnagy, B., Fabiano, G., … Murphy, S. A. (2012). Q-learning: A data analysis method for constructing adaptive interventions. Psychological Methods, 17, 478-494. PMCID: PMC3747013

Almirall, D., Compton, S. N., Gunlicks-Stoessel, M., Duan, N., & Murphy, S. A. (2012). Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy. Statistics in Medicine, 31(17), 1887-1902. PMCID: PMC3399974

Lei, H., Nahum-Shani, I., Lynch, K., Oslin, D., & Murphy, S. A. (2012). A "SMART" design for building individualized treatment sequences. The Annual Review of Clinical Psychology, 8, 21-48. PMC Journal- In process

Gunter, L., Zhu, J., & Murphy, S. A. (2011). Variable selection for qualitative interactions in personalized medicine while controlling the family-wise error rate. Journal of Biopharmaceutical Statistics, 21, 1063-1078. PMCID: PMC3003934

Shortreed, S. M., Laber, E., Lizotte, D. L., Stroup S., Pineau, J., & Murphy, S. A. (2011). Informing sequential clinical decision-making through reinforcement learning: An empirical study. Machine Learning, 84(1), 109-136. PMCID: PMC3143507

Gunter, L., Zhu, J., & Murphy, S. A. (2011). Variable selection for qualitative interactions. Statistical Methodology, 1(8), 42-55. PMCID: PMC3003934

Qian, M., & Murphy, S. A. (2011). Performance guarantees for individualized treatment rules. Annals of Statistics, 39(2), 1180-1210. PMCID: PMC3110016

Li, Z., & Murphy, S. A. (2011). Sample size formulae for two-stage randomized trials with survival outcomes. Biometrika 98(3): 503-518. PMCID:PMC3254237

Almirall, D., McCaffrey, D. F., Ramchand, R., & Murphy, S. A. (2011). Subgroups analysis when treatment and moderators are time-varying. Prevention Science. Advance online publication. doi: 10.1007/s11121-011-0208-7 PMCID: PMC3135740

Deng, K., Pineau, J., & Murphy, S. A. (2011). Active learning for personalizing treatment. Proceedings of the ADPRL - 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (pp. 32-39). Piscataway, NJ: IEEE. doi: 10.1109/ADPRL.2011.5967348

Deng, K., Pineau, J., & Murphy, S. A. (2011). Active learning for developing personalized treatment. Proceedings of the Twenty-seventh Conference on Uncertainty in Artificial Intelligence 2011 (pp. 161-168). Corvallis, OR: AUAI Press.

Almirall, D., Ten Have, T., & Murphy, S. A. (2010). Structural nested mean models for assessing time-varying effect moderation. Biometrics, 66(1), 131-139. PMCID: PMC2875310

Fonteneau, R., Murphy, S. A., Wehenkel, L., & Ernst, D. (2010). A cautious approach to generalization in reinforcement learning. In J. Filipe, A. Fred, & B. Sharp (Eds.), Proceedings of the 2nd International Conference on Agents and Artificial Intelligence, Vol.1 (pp.64-73).

Fonteneau, R., Murphy, S. A., Wehenkel, L., & Ernst, D. (2010). Model-free Monte Carlo-like policy evaluation. Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 9, 217-224.

Lizotte, D., Bowling, M., & Murphy, S. A. (2010). Efficient reinforcement learning with multiple reward functions for randomized controlled trial analysis. Proceedings of the 27th International Conference on Machine Learning (pp.695-702).

McGowan, H. M., Nix, R. L., Murphy, S. A., Bierman, K. L., & Conduct Problems Prevention Research Group. (2010). Investigating the impact of selection bias in dose-response analyses of preventive interventions. Prevention Science, 11(3), 239-251. PMCID: PMC3044506

Oetting, A. I., Levy, J. A., Weiss, R. D., & Murphy, S. A. (2010). Statistical methodology for a SMART design in the development of adaptive treatment strategies. In P.E. Shrout, (Ed.), Causality and psychopathology: Finding the determinants of disorders and their cures. Arlington, VA: American Psychiatric Publishing.

Chakraborty, B., Murphy, S. A., & Strecher, V. (2010). Inference for non‐regular parameters in optimal dynamic treatment regimes. Stat Methods Med Res, 19(3), 317‐43. PMCID: PMC2891316

 

Book Chapters

Nahum-Shani, I., Xi, L., Henderson, M. M., & Murphy, S. A. (2013). An innovative experimental design for addressing the “assistance dilemma” using interactive learning environments. In S. A. Karabenick & M. Puustinen (Eds), Advances in help-seeking research and applications: The role of emerging technologies. Charlotte, NC: Information Age Publishing.

Qian, M., Nahum-Shani, I., Murphy, S. A. (2013). Dynamic treatment regimes. In X. Tu and W. Tang (Eds.), Modern clinical trial analysis. New York, NY: Springer Science.

Oetting, A. I., Levy, J. A., Weiss, R. D., & Murphy, S. A. (2011). Statistical methodology for a SMART design in the development of adaptive treatment strategies. In P. E. Shrout, K. M. Keyes, & K. Ornstein (Eds.), Causality and psychopathology: Finding the determinants of disorders and their cures (pp. 179-205). Arlington VA: American Psychiatric Publishing.

Almirall D., Coffman C. J., Yancy W. S., & Murphy S. A. (2010). Maximum likelihood estimation of the structural nested mean model using SAS PROC NLP. In D. Faries, A. Leon, J.M. Haro, & B. Obenchain (Eds.), Analysis of Observational Health-Care Data Using SAS

 

Presentations

Murphy, S. A. (2014, January). SMART study designs for developing intervention. Talk presented at the Deptartment for Preventive Medicine, Northwestern University, Evanston, IL.

Murphy, S. A. (2014, January). Machine learning methods for individualizing just-in-time adaptive interventions. Talk presented at the Deptartment of Biostatistics, University of Washington, Seattle, WA. 

Murphy, S. A. (2013, November). SMART Designs for combatting autism. Future of Statiscial Sciences Worskshop, Royal Statistical Society, London, England.

Murphy, S. A. (2013, November). SMART designs to improve health. International Year of Statistics public lecture presented at the University of Toronto, Toronto, Ontario, Canada.

Murphy, S. A. (2013, October). Beyond efficacy: Innovative designs for effectiveness. Keynote speech at the Center for AIDS Research Syposium 2013: Implementation Sciences and the Global Response to HIV/AIDS, San Francisco, CA.

Murphy, S. A. (2013, October). Machine learning methods for individualizing real-time treatment policies. Talk presented at the 10th International Conference on Health Policy Statistics, Chicago, IL.

Murphy, S. A. (2013, October). SMART study designs for developing interventions. Talk presented at the Center for AIDS Prevention Studies Methods Town Hall, Department of Medicine, University of California, San Francisco, CA.

Murphy, S. A. (2013, October). Getting SMART about adapting interventions! Talk presented at the the National Network of Depression Centers Annual Conference, University of Michigan, Ann Arbor, MI.

Murphy, S. A. (2013, July). Getting SMART about adapting interventions! Talk presented at the NIH Summer Institute on Randomized Behavioral Clinical Trials, Airlie Conference Center, Warrenton, VA.

Murphy, S. A. (2013, June). Getting SMART about adapting interventions! Talk presented at the 9th Annual RSA Pre-Conference Satellite Meeting on Mechanisms of Behavior Change, Orlando, FL.

Murphy, S. A. (2013, June). A clinical trial design for constructing and individualizing real-time treatment policies. Plenary presented at Gordon C. Ashton Memorial Biometrics Lecture, Guelph Biomathematics and Biostatistics Symposium, Guelph, Ontario, Canada.

Murphy, S. A. (2013, June). Getting SMART about adapting interventions! In the Ninth annual mechanisms of behavior change: Expanding boundaries in studying mechanisms of behavior change. Pre-conference satellite meeting at the 36th Annual Research Society on Alcoholism Scientific Meeting, Orlando, FL.

Lei, H., Lynch, K., Oslin, D., & Murphy, S. A. (2013, May). Power analysis and sample size calculation in designing a smart trial for building dynamic treatment regimens. Poster presented at Society for Clinical Trials annual meeting, Boston, MA.

Murphy, S. A. (2013, May). A clinical trial design for constructing and individualizing real-time treatment policies. Invited paper presented at Statistical Genomics and Data Integration for Personalized Medicine, Ascona, Switzerland.

Murphy, S. A. (2013, May). Getting SMART about adapting interventions. Carriage House Lecture. Presented at the Mathematical Association of America, Washington, D.C.

Murphy, S. A. (2013, April). Advances in sequential, multiple assignment, randomized trials and treatment policies. Invited paper presented at the 7th Meeting of the Eastern Mediterranean Region International Biometric Society, Tel Aviv, Israel.

Murphy, S. A. (2013, February). Adaptive confidence intervals for non-regular parameters. Invited seminar presented at the Mathematics Department, University of Alberta, Edmonton, Alberta, Canada.

Almirall, D., Collins, L. M., & Murphy, S. A. (2012, November). Getting SMART about the design of experimental trials for the development of adaptive health interventions. Presented at the second Innovative Methods Program for Advancing Clinical Trials, Raleigh, NC.

Almirall, D., & Murphy, S. A. (2012, October). Piloting and sizing sequential multiple assignment randomized trials and dynamic treatment regime development. Presented at the International Conference on Statistics and Combinatorics, Greensboro, NC.

Almirall, D., McCaffrey, D., Griffin, B. A., Ramchand, R., & Murphy, S. A. (2012, September). Examining moderated eects of additional adolescent substance use treatment: Structural nested mean model estimation using inverse-weighted regression-with-residuals. Presented at George Mason University, Fairfax, VA.

Murphy, S. A. (2012, September). Treatment effect heterogeneity and dynamic treatment regime development. Presented at the University of Alberta, Edmonton, AB, Canada.

Laber, E. B., Lizotte, D. J., Qian, M., Pelham, W. E., & Murphy, S. A. (2012, August). Statistical inference in dynamic treatment regimes. In F. Wei (Chair), New methods for analyzing clinical trials. Symposium conducted at the Joint Statistical Meetings, San Diego, CA.

Murphy, S. A. (2012, August). Taking advantage of treatment effect heterogeneity in dynamic treatment regime development. In K. Imai (Chair), Treatment effect heterogeneity in causal inference. Invited paper presented at the Joint Statistical Meetings, San Diego, CA.

Murphy, S. A. (2012, August). Dynamic treatment regime development. In J. Cheng (Chair), Roundtable discussion: Statistics in epidemiology. Presented at the Joint Statistical Meetings, San Diego, CA.

Murphy, S. A. (2012, August). Sequential, multiple assignment, randomized trials and treatment policies. In S. Saria (Chair), Active collaborative problem brainstorming. Presented at the Meaningful Use of Complex Medical Data meeting, Los Angeles, CA.

Almirall D., McCaffrey D. F., Griffin B. A., Ramchand, R., & Murphy S. A. (2012, July). Examining moderated effects of additional adolescent substance use treatment: Structural nested mean model estimation using inverse-weighted regression-with-residuals. Invited Seminar presented at the Asia Pacific Rim Meeting of the International Mathematical Statistics Society, Tsukubu, Japan.

Deng, K., Pineau, J., & Murphy, S. A. (2012, July). Active learning for developing personalized treatment. In Y. Liu (Chair), Recent advances in statistical machine learning. Invited paper presented at the Joint Statistical Meetings, San Diego, CA.

Laber, E., & Murphy, S. A. (2012, July). Adaptive confidence intervals for regression coefficients in Q-learning. Workshop presented at Statistical Inference in Complex/High-Dimensional Problems, University of Vienna, Austria.

Murphy, S. A. (2012, June). Adaptive confidence intervals for nonregular parameters. Invited plenary talk at the Conference on Statistical Learning and Data Mining, University of Michigan, Ann Arbor, MI.

Almirall D., & Murphy S. A. (2012, June). Getting SMART about developing individualized, adaptive health interventions. Workshop presented for Methods Work, Chicago, IL.

Murphy, S. A. (2012, May). Piloting and sizing sequential, multiple assignment, randomized trials in dynamic treatment regime development. Workshop presented at 2012 Atlantic Causal Inference Conference, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Li, Z., & Murphy, S. A. (2012, April). Sizing sequential, multiple assignment, randomized trials for survival analysis. Presented at the 2012 Spring Meeting of the Eastern North American Region of the International Biometric Society, Washington DC.

Murphy, S. A. (2012, April). Confidence intervals, Q-learning, and dynamic treatment regimes. Invited talk presented at Time for Causality Workshop, University of Bristol, Bristol, United Kingdom.

Murphy, S. A. (2012, April). Getting SMART about adapting interventions. Invited talk presented at Early Childhood Interventions Working Group Inaugural Conference, University of Chicago, Chicago, IL.

Murphy, S. A. (2012, March). SMART clinical trial designs for developing dynamic treatment regimes. Invited talk presented the 10th Annual ASA CT Chapter Mini-Conference: Emerging Statistical Issues in Clinical Trials, Yale University West Campus, Orange, CT.

Murphy, S. A. (2012, March). SMARTs: New data and challenges. Presented at the Oberwolfach meeting on Frontiers in Nonparametric Statistics, Oberwolfach, Germany

Almirall D., Compton S. N., & Murphy S. A. (2012, March). Developing adaptive health interventions: Getting SMART. Invited talk presented at the AIMS Center, University of Washington, Seattle, WA.

Laber, E. & Murphy, S. A. (2012, February). Adaptive confidence intervals for non-regular parameters. Department of Statistical Science, Cornell University.

Murphy, S. A. (2011, December). Adaptive confidence intervals for non-regular parameters. Presented at the Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh.

Murphy, S. A. (2011, December). Getting SMART about adapting interventions. Presented at the HIV Intervention Science Program for Underrepresented New Investigators, Columbia University.

Almirall, D., & Murphy, S. A. (2011, November). Developing dynamic, sequential interventions that optimize mental health outcomes: Novel clinical trial design and data analysis strategies. Seminar presented at the Association of Behavioral and Cognitive Therapies Convention, Toronto, Canada.

Laber, E. & Murphy, S. A. (2011, September). Adaptive confidence intervals for non-regular parameter. Institute for Mathematical Research, High- Dimensional Problems in Statistics Conference, Zurich, Switzerland.

Murphy, S. A., & Almirall, D. (2011, June). Getting SMART about developing individualized, adaptive health interventions. Workshop presented at the University of Minnesota NIMH Prevention Center, Twin Cities, MN.

Murphy, S. A., Almirall, D., Oslin, D., & Jones, H. (2011, June). Getting SMART about developing individualized sequences of health interventions. Workshop presented at the College on Problems of Drug Dependence (CPDD), Hollywood, FL.

Murphy, S. A., McKay, J., Pelham, W., Jones, H., & Kasari, C. (2011, June). Developing dynamic, sequential treatments that optimize mental health outcomes: Experiences with a novel clinical trial design. Workshop presented at the New Clinical Drug Evaluation Unit (NCDEU), Boca Raton, FL.

Almirall, D., Collins, L. M., & Murphy, S. A. (2011, June). Experimental designs for developing adaptive treatment strategies. Presented at the Childhood Obesity Prevention and Treatment Research (COPTR) research program. Teleconference.

Murphy, S. A. (2011, May). Practical application of adaptive treatment strategies in trial design and analysis. Paper presented at the Society for Clinical Trials Annual Meeting, Vancouver, BC, Canada.

Murphy, S. A. (2011, May). Time varying treatments and optimal treatment strategies. Workshop presented at the Causal Inference in Health Workshop, Le Centre de recherché mathematiques (CRM), Montreal, QC, Canada.

Murphy, S. A., Laber, E., Nahum-Shani, I., & Pelham, W. (2011, April). Using data to inform sequential, individualized clinical decision making. In L. M. Collins (Chair), Drawing on ideas from engineering and computer science to build better behavioral interventions. Symposium presented at the Society of Behavioral Medicine Annual Meeting & Scientific Sessions, Washington, DC.

Almirall, D., Compton, S. N., & Murphy, S. A. (2011, April). Experimental designs for developing adaptive treatment strategies. Preconference workshop presented at the Society of Behavioral Medicine Annual Meeting & Scientific Sessions, Washington, DC.

Lizotte, D. J., Bowling, M., & Murphy, S. A. (2010, October). Inverse preference elicitation for dynamic treatment regimes. Poster presented at the Society for Medical Decision Making 2010 Meeting.

Laber, E., & Murphy, S. A. (2010, October). Inference for dynamic treatment regimens. Presented at Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX.Department of Statistics, Colorado State University, Fort Collins, CO. Michigan State University, Lansing, MI.

Almirall, D., McCaffrey, D. F., Griffin, B. A., & Murphy, S. A. (2010, August). Time-varying causal effect moderation in the presence of time-varying confounding using structural nested mean models. Presented at the Joint Statistical Meetings, Vancouver, Canada.

Laber, E., & Murphy, S. A. (2010, July). Adaptive confidence intervals for the test error in classification. Presented at the High-Dimensional Models and Processes Conference, Seattle, WA.

Almirall, D., Compton, S. N., & Murphy, S. A. (2010, June). Experimental designs for developing adaptive treatment strategies: With application to the management of bipolar disorder. Presented at the International College of Neuro-Psychopharmacology (CINP) Congress, Hong Kong, China.

Laber, E. B., Qian, M., Nahum-Shani, I., & Murphy, S. A. (2010, January). Constructing dynamic treatment regimes. Presented at the International Conference on Health Policy and Statistics, Washington, D.C.

 

Software

PROC QLEARN (Version 1.0) [Software] (2012). University Park: The Methodology Center, Penn State. Retrieved from http://methodology.psu.edu

Ertefaie, A., Almirall, D. A., Huang L., Dziak, J. J., Wagner, A. T., & Murphy, S. A. (2012). SAS PROC QLEARN users’ guide (Version 1.0). University Park: The Methodology Center, Penn State. Retrieved from http://methodology.psu.edu

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