Daniel Almirall Assistant Professor of Biostatistics Duke University Medical Center Office 11032, Hock Plaza, DUMC Campus daniel (punto) almirall [arroba] duke (punto) edu (919) 668 7225 Mailing Addresses

Welcome to my homepage. I am Assistant Professor of Biostatistics in the School of Medicine at Duke Universtity, and a Biostatistician/Research Scientist in the Center for Health Services Research in Primary Care at the Durham VA Medical Center.

Research Interests

Methodological Interests: My current methodological research interests lie in the broad area of causal inference. I am particularly interested in methods for causal inference using longitudinal data sets in which treatments, covariates, and outcomes are all time-varying. I am also interested in developing statistical methods that can be used to form adaptive treatment strategies, sometimes known as dynamic treatment regimes. A dynamic treatment regime is a sequence of individually tailored decisions rules that specify whether, how, and when to alter the intensity, type, or delivery of treatment at critical decision points in the medical care process. Dynamic treatment regimes are particularly well-suited for management of chronic diseases, but can be used in any clinical setting in which sequential medical decision making is essential for the welfare of the patient. They hold the promise of enhancing clinical practice by flexibly tailoring treatments to patients when they need it most, and in the most appropriate dose, thereby improving the efficacy and effectiveness of treatment.

Substantive Interests: As a VA Health Research Scientist in a primary care research setting, I take part in research in a wide variety of areas of clinical application. I am particularly interested in the substantive areas of mental health (depression, sleep disorders), obesity, and substance abuse.

Key words: causal inference, propensity score methods, marginal and structural nested mean models, methods for longitudinal data analysis, health services research, mental health, substance abuse, obesity, dynamic treatment regimes, adaptive treatment strategies

Publications

In Progress

• Almirall D, Ten Have T, Murphy SA. Structural Nested Mean Models for Assessing Time-Varying Effect Moderation [submitted]

• Almirall D, McCaffrey D, Morral A, Murphy SA. Causal Effect Moderation Using Latent Variables with Application to Patient-Treatment Matching [in progress]

Journal Articles

• Mithas S, Almirall D, Krishnan MS. Do CRM Systems Cause One-to-One Marketing Effectiveness? Statistical Science 2006, Vol. 21, No. 2, 223-233. [software]

• Bray BC, Almirall D, Zimmerman RS, Lynam D, Murphy SA. Assessing the Total Effect of Time-varying Predictors in Prevention Research. Prevention Science, 2006 March; 7(1): 1-17.

• Newburger JW, Wypij D, Bellinger DC, du Plessis AJ, Kuban KC, Rappaport LA, Almirall D, Wessel DL, Jonas RA, Wernovsky G. Length of Stay After Infant Heart Surgery is Associated with Long-Term Cognitive Outcome. Journal of Pediatrics, 2003 July; 143(1): 67-73.

Book Chapters

• Mithas S, Almirall D, Krishnan M.S. A Framework for Causal Enquiry in Information Systems for Observational Studies. In R.J. Kauffman and P.P. Tallon (Eds.) Economics, Information Systems, and Electronic Commerce Research II: Advanced Empirical Methodologies. Armonk, NY: M.E. Sharpe. [in press]

Mailing Addresses