Statistics Seminar: James Robins

Speaker: James Robins

Title: Estimation of Optimal Testing and Treatment Regimes under No Direct Effect (NDE) of Testing

Abstract: 
This paper provides new, highly efficient estimators of optimal joint testing and treatment regimes under the no direct effect assumption that a given laboratory, diagnostic, or screening test has no effect on a patient's clinical outcomes, except through the effect of the test results on the choice of treatment. The proposed estimators attain high efficiency because they leverage this `no direct effect of testing' (abbreviated as NDE) assumption. 

What is surprising and, indeed, unprecedented in my experience, is that, in a substantive study of HIV infected subjects, our new estimators delivered a 50-fold increase in efficiency (and, thus, a 50 fold reduction in required sample size) compared to estimators that fail to leverage the NDE assumption!   In this talk I review the results of this HIV study, describe the new estimators, and provide guidance as to when such large gains in efficiency are to be expected.

Areas in which our new, more efficient estimators should be particularly important is that of cost-benefit analyses wherein the costs of expensive tests (such as MRIs to screen for lung cancer, mammograms to screen for breast cancer, and urinary cytology to screen for bladder cancer) are weighed against the clinical value of the information supplied by the test results. 

(This is joint work with Lin Liu, Zach Shahn, and Andrea Rotnitzky)

Bio: James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly those in which the treatment varies with time. He is the 2013 recipient of the Nathan Mantel Award for lifetime achievement in statistics and epidemiology.

He graduated in medicine from Washington University in 1976. He is currently Mitchell L. and Robin LaFoley Dong Professor of Epidemiology at Harvard School of Public Health. He has published over 100 papers in academic journals and is an ISI highly cited researcher.