A. James O'Malley, PhD

Professor of Biostatistics

A. James O’Malley, PhD



(603) 653-0854


  • PhD, in Statistics, University of Canterbury, 1999
  • MS, Applied Statistics, Purdue University, 1999
  • BSc(Hons), in Statistics, University of Canterbury, 1994

Primary Contact

Joel King

Curriculum Vitae

A. James O'Malley CV

Areas of Expertise

My methodological research interests have centered on the design and analysis of medical device clinical trials, multivariate-hierarchical modeling, causal inference and social network analysis. I have developed novel statistical methods, often involving novel use of Bayesian statistics, to solve important methodological and applied problems in health policy and health services research, including the evaluation of treatments and quality of care in multiple areas of medicine. I am continuing to look at problems from multiple lenses including statistical, health policy, medical, epidemiological, and sociological perspectives. I expect to continue working on methodological problems in causal inference (comparative effectiveness research), hierarchical-multivariate modeling, social network analysis, and Bayesian analysis with specific problems often at the intersection of two or more of these areas.


1992 Page Memorial Prize for Mathematics, University of Canterbury
1993 University of Canterbury Senior Scholarship, University of Canterbury
1993 Cook Memorial Prize for Mathematics, University of Canterbury
1994 University of Canterbury Doctoral Scholarship
1996 Second Place, Students' Paper Competition, New Zealand Statistical Association
1997 Charles Cook, Warwick House Memorial Scholarship, University of Canterbury
1999 L.J. Cote Award for Excellence in Statistics, Purdue University
2002 Young investigator travel award, 4th Scientific Forum on Quality of Care and
Outcomes Research in Cardiovascular Disease and Stroke
2011 Mid-Career Excellence Award, American Statistical Association Health Policy
Statistics Section
2012 Elected Fellow, American Statistical Association for “novel use of Bayesian statistics, multivariate-hierarchical modeling, causal inference and social network analysis to solve problems in health policy and health services research, for improving evaluation of treatments and quality of health care, and for leadership in health policy statistics.”

Professional Achievements:

Published Chapter: O’Malley AJ, Neelon BH. "Using structural equation, latent factor and latent class models to accommodate heterogeneity." In: Anthony J. Culyer (ed.), Encyclopedia of Health Economics, Vol 2. San Diego: Elsevier; 2014. pp. 131-140.

Published Research

Using Retrospective Sampling to Estimate Models of Relationship Status in Large Longitudinal Social Networks.
Computational Statistics and Data Analysis, 2014;
Results from using a new dyadic-dependence model to analyze sociocentric physician networks.
Social Science & Medicine, 2014;(published online 19 July): 67-75doi: 10.1016/j.socscimed.2014.07.01 The Effect of Part D Coverage Restrictions for Antidepressants, Antipsychotics, and Cholinesterase Inhibitors on Related Nursing Home Resident Outcomes.
Journal of General Internal Medicine, 2014; DOI: 10.1111/jgs.12988 Fatty acids increase neuronal hypertrophy of Pten knockdown neurons
Frontiers in Molecular Neuroscience, April 23, 2014;doi: 10.3389/fnmol.2014.00030 :
Increased Use of the Emergency Department After Health Care Reform in Massachusetts
Annals of Emergency Medicine, March 19, 2014;DOI: http://dx.doi.org/10.1016/j.annemergmed.2014.02.011:
Linear mixed models for multiple outcomes using extended multivariate skew-t distributions
Statistics and Its Interface, 2014;7: 101–111 Estimating Peer Effects in Longitudinal Dyadic Data Using Instrumental Variables
Biometrics, April 29, 2014;DOI: 10.1111/biom.12179:

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