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About Sickkids
About SickKids

Eleanor Pullenayegum , PhD

Research Institute
Senior Scientist
Child Health Evaluative Sciences

Other Positions
McMaster University
Associate Professor


Phone: 416-813-7654 x301352
Email: eleanor.pullenayegum@sickkids.ca

For more information, visit:

McMaster Profile

Brief Biography

I am a biostatistician, and did my undergraduate and master's level training in mathematics at the University of Cambridge in England. After graduating, I worked for two years at the Centre for Applied Medical Statistics in the Department of Public Health and Primary Care at the University of Cambridge. This was my first experience working with real researchers on real data, and I enjoyed it so much I decided I wanted to be a researcher myself. I did my PhD in biostatistics at the University of Toronto, then a post-doctoral fellowship at the University of Waterloo, before moving to McMaster University. There, I set up a research program on statistical methods for longitudinal data and economic evaluations, and I also taught and collaborated on  clinical projects. I now work at SickKids in the Child Health Evaluative Sciences program.

Research Interests

My research falls into two broad categories: statistical methods in health economics and methods for longitudinal data.

In health economics I am interested in the measurement and analysis of cost and health utility data, and focus particularly on semi-parametric models that avoid the need to model the unusual distributions of these outcomes.

My work on longitudinal data focuses particularly on the case where the measurement times are stochastic (i.e. not fixed by a protocol). This often happens with retrospective chart reviews. Ignoring the informative nature of the visit times will lead to misleading inferences. My current work is investigating inverse-intensity weighting and doubly robust inferences.

In these areas I have several projects that are suitable for students considering Master's or Doctoral work, and would be happy to hear from you.

External Funding

Natural Sciences and Engineering Research Council (NSERC)

Achievements

CIHR New Investigator Award

Publications

Pullenayegum EM, Wong HS, Childs A. Generalized additive models for the analysis of EQ-5D utility data. Med Decis Making. 2013 Feb;33(2):244-51. doi:
10.1177/0272989X12465354. Epub 2012 Nov 6. PubMed PMID: 23132902.

Pullenayegum EM, Feldman BM. Doubly robust estimation, optimally truncated inverse-intensity weighting and increment-based methods for the analysis of irregularly observed longitudinal data. Stat Med. 2013 Mar 15;32(6):1054-72. doi:
10.1002/sim.5640. Epub 2012 Oct 10. PubMed PMID: 23047604.

Pullenayegum EM. Adaptive Bayesian randomized trials: realizing their potential. J Bone Joint Surg Am. 2012 Jul 18;94 Suppl 1:29-33. doi:10.2106/JBJS.L.00094. PubMed PMID: 22810444.

Pullenayegum EM, Tarride JE, Xie F, O'Reilly D. Calculating utility decrements associated with an adverse event: marginal Tobit and CLAD coefficients should be used with caution. Med Decis Making. 2011 Nov-Dec;31(6):790-9. doi:10.1177/0272989X11393284. PubMed PMID: 22067429

2.Guo Q*, Hall G, McKinnon M, Thabane L, Pullenayegum EM. Setting Sample Size Using Cost-Efficiency in fMRI Studies. Journal of Open Access Medical Statistics 2012: 2:33-41.

Pullenayegum EM. An informed reference prior for between-study heterogeneity in meta-analyses of binary outcomes. Stat Med. 2011 Nov 20;30(26):3082-94. doi:
10.1002/sim.4326. Epub 2011 Aug 25. PubMed PMID: 22020726.

Pullenayegum EM, Cook RJ. The analysis of treatment effects for recurring episodic conditions. Stat Med. 2010 Jun 30;29(14):1539-58. doi: 10.1002/sim.3882.
PubMed PMID: 20535764.

Pullenayegum EM, Tarride JE, Xie F, Goeree R, Gerstein HC, O'Reilly D. Analysis of health utility data when some subjects attain the upper bound of 1: are Tobit and CLAD models appropriate? Value Health. 2010 Jun-Jul;13(4):487-94.doi: 10.1111/j.1524-4733.2010.00695.x. Epub 2010 Mar 10. PubMed PMID: 20230549.

Pullenayegum EM, Lam C, Manlhiot C, Feldman BM. Fitting marginal structural models: estimating covariate-treatment associations in the reweighted data set can guide model fitting. J Clin Epidemiol. 2008 Sep;61(9):875-81. doi:10.1016/j.jclinepi.2007.10.024. Epub 2008 May 16. PubMed PMID: 18486447

Pullenayegum EM, Willan AR. Semi-parametric models for cost-effectiveness analysis: improving the efficiency of estimation from censored data. Statistics in Medicine 2007; 26(17): 3274-3299.