Public Health Sciences

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Michael McIsaac

Dr. Michael McIsaac received his PhD in Statistics from the University of Waterloo. He joined the Department of Public Health Sciences at Queen's University in 2013. His research interests include the development and application of statistical methods for public health studies. Dr McIsaac works collaboratively with physicians in the design and analysis of epidemiological studies of rheumatology and vasculitis, and his specific areas of interest include efficient two-phase study designs and methods for analysis of incomplete data. Dr. McIsaac is also interested in Statistical education and pedagogy, and earned a Certificate in University Teaching from the University of Waterloo's Centre for Teaching Excellence.

Dr. McIsaac is currently co-teaching Introductory Biostatistics (EPID 821) and Advanced Biostatistics (EPID 823) in the Fall term, and co-teaching Intermediate Biostatistics (EPID 822) in the Winter.

Recent Publications

McIsaac MA and Cook RJ (in press). The Kappa Index. In Encyclopedia of Clinical Trials: Methods and Applications of Statistics in Clinical Trials - Planning, Analysis, and Inferential Methods, Vol. 2 [10 pages], N. Balakrishnan (Ed.), John Wiley & Sons, Newark, NJ.

McIsaac MA and Cook RJ (in press). Statistical Models and Methods for Incomplete Data in Randomized Clinical Trials. In Developments in Statistical Evaluation of Clinical Trials (pp. 1-25). K. van Montfort, J. Oud & W. Ghidey (Eds.), Springer

McIsaac MA and Cook RJ (2013). Biomarkers for Disease Progression in Rheumatology: A Review and Empirical Study of Two-Phase Designs. University of Waterloo Research Paper Series.

McIsaac MA and Cook RJ (2013). Response-Dependent Sampling with Clustered and Longitudinal Data. In ISS- 2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers (pp. 157-181). Springer New York.

McIsaac MA, Cook RJ and Pouline-Costello M (2013). Incomplete Data in Randomized Dermatology Trials: Consequences and Statistical Methodology. Dermatology, 226(1), 19-27.