Michael McDermott, PhD

Associate Chair
Professor of Biostatistics
Professor of Neurology
Professor, Center for Human Experimental Therapeutics
Director, Statistics PhD program

Ph.D. (1989) University of Rochester


 

Contact Information:

University of Rochester
Dept of Biostatistics and Computational Biology
265 Crittenden Blvd., CU 420630
Rochester, New York 14642-0630
 
Office: Saunders Research Building 4105
Phone: (585) 275-6685
Fax: (585) 273-1031
E-mail: MikeM@bst.rochester.edu
Michael P. McDermott, PhD

 

Research Interests

Much of my statistical research has been in the area of order-restricted inference, specifically with regard to developing novel approaches to hypothesis testing problems involving order-constrained parameters.  This methodology is useful in many applications, including dose-response studies and clinical trials with multiple endpoints.  I am also interested in problems of inference concerning receiver operating characteristic (ROC) curves and surfaces, including the problem of correcting verification bias that sometimes arises in studies of the performance of diagnostic tests.  Other areas of interest include methods for combining p-values, reliability of measurement, meta-analysis, missing data problems, and clinical trials methodology.

I hold a joint appointment with the Department of Neurology and much of my collaborative work stems from this relationship.  I have been a member of several national and international collaborative groups conducting basic and clinical research in Parkinson’s disease, Huntington’s disease, Tourette’s syndrome, epilepsy, various muscular dystrophies and other muscle diseases, HIV-associated dementia, multiple sclerosis, attention deficit-hyperactivity disorder, idiopathic intracranial hypertension, and pain.  I was the primary statistician for the University’s NIH-funded General Clinical Research Center from 1994-2007.

I am currently an Editor for Chance magazine and have served on the editorial board for the journal Movement Disorders since 2010.  I was Associate Editor of the journal Neurology from 1997-2003 and served on the Medical Advisory Committee of the Muscular Dystrophy Association from 1998-2008.  I was named the Andrew W. Mellon Dean’s Teaching Scholar in 1997 in recognition of excellence in teaching.  I am a member of the American Statistical Association, the Biometric Society, the Institute of Mathematical Statistics, and the Society for Clinical Trials.



Selected References

  • Mudholkar, G. S. and McDermott, M. P. (1989).  A class of tests for equality of ordered means.  Biometrika 76:161-168.
  • McDermott, M. P. and Mudholkar, G. S. (1993).  A simple approach to testing homogeneity of order constrained means.  Journal of the American Statistical Association 88:1371-1379.
  • Mudholkar, G. S., McDermott, M. P., and Aumont, J. (1993).  Testing homogeneity of ordered variances.  Metrika 40:271-281.
  • Mudholkar, G. S., McDermott, M. P., and Mudholkar, A. (1995).  Robust finite-intersection tests for homogeneity of ordered variances.  Journal of Statistical Planning and Inference 43:185-195.
  • Wang, Y. and McDermott, M. P. (1998).  Conditional likelihood ratio test for a nonnegative normal mean vector.  Journal of the American Statistical Association 93:380-386.
  • Wang, Y. and McDermott, M. P. (1998).  A conditional test for a nonnegative mean vector based on a Hotelling’s T 2-type statistic.  Journal of Multivariate Analysis 66:64-70.
  • Zou, K. H. and McDermott, M. P. (1999).  Higher-moment approaches to approximate interval estimation for a certain intraclass correlation coefficient.  Statistics in Medicine 18:2051-2061.
  • McDermott, M. P. (1999).  Generalized orthogonal contrast tests for homogeneity of ordered means.  Canadian Journal of Statistics 27:457-470.
  • McDermott, M. P. and Wang, Y. (1999).  Comment on “The Emperor’s new tests” by M. D. Perlman and L. Wu.  Statistical Science 14:374-377.
  • Wang, Y. and McDermott, M. P. (2001).  Uniformly more powerful tests for hypotheses about linear inequalities when the variance is unknown.  Proceedings of the American Mathematical Society 129:3091-3100.
  • McDermott, M. P. and Wang, Y. (2002).  Construction of uniformly more powerful tests for hypotheses about linear inequalities.  Journal of Statistical Planning and Inference 107:207-217.
  • McDermott, M. P., Hall, W. J., Oakes, D., and Eberly, S. (2002).  Design and analysis of two-period studies of potentially disease-modifying treatments.  Controlled Clinical Trials 23:635-649.
  • Kost, J. T. and McDermott, M. P. (2002).  Combining dependent p-values.  Statistics and Probability Letters 60:183-190.
  • Natarajan, R., Mudhoklar, G. S., and McDermott, M. P. (2005).  Order-restricted inference for the scale-like inverse Gaussian parameters.  Journal of Statistical Planning and Inference 127:229-236.
  • Kost, J. T. and McDermott, M. P. (2008).  Testing equality of means under order restrictions using multiple contrasts.  Communications in Statistics, Part A – Theory and Methods 37:3029-3039.
  • He, H., Lyness, J. M., and McDermott, M. P. (2009).  Direct estimation of the area under the receiver operating characteristic curve in the presence of verification bias.  Statistics in Medicine 28:361-376.
  • He, H. and McDermott, M. P. (2012).  A robust method using propensity score stratification for correcting verification bias for binary tests.  Biostatistics 13:32-47.
  • Ravina, B., Cummings, J., McDermott, M. P., Poole, R.M., eds. (2012).  Clinical Trials in Neurology: Design, Conduct, Analysis.  Cambridge: Cambridge University Press.
  • Morrissette, J. L. and McDermott, M. P. (2013).  Estimation and inference concerning ordered means in analysis of covariance models with interactions.  Journal of the American Statistical Association 108:832-839.
  • Dworkin, R. H., McDermott, M. P., Farrar, J. T., O’Connor, A. B., and Senn, S (2014).  Interpreting patient treatment response in analgesic clinical trials: implications for genotyping, phenotyping, and personalized pain treatment.  Pain 155:457-460.