Jemila Hamid

, BSc, MSc, Phd

Assistant Professor
Pathology and Molecular Medicine

Assistant Professor, Clinical Epidemiology and Biostatistics

Young Statistician of the Year, Swedish Statistical Association

McMaster University
2N35B Health Science Centre
905-521-2100 ext 73233
jhamid@mcmaster.ca

Assistant: Michelle Allan ext. 22471

Education and Professional Standing

• Post-doc fellow, Biostatistics, University of Toronto and Hospital for Sick Children, Toronto
• PhD, Mathematical Statistics, SLU, Sweden, 2005
• MSc, Mathematical Statistics, Uppsala University, Sweden, 2001
• BSc, Statistics and Computer Science, Addis Ababa University, Ethiopia, 1995

---

Interests

My main research activity is development, validation, implementation and application of statistical methods with a special focus on multivariate growth curves, statistical methods in diagnostic medicine and biomarkers, methods for genomics including time course genomic data and methods for data integration.

I am in general interested in statistical methods in medicine, epidemiology and public health applications. I am particularly interested in multivariate methods and methods for longitudinal data. I am also interested in methods for high dimensional data including high-throughput time course data.

---

Selected Publications

• Hamid JS, Beyene J, von Rosen D. A novel trace test for the mean parameter in a multivariate growth curve model, Journal of Multivariate Analysis 2011, Vol. 102, Issue 2: 238 - 251
• Hamid JS, Meaney C, Crowcroft NS, et. al. Cluster analysis for identifying sub-groups and selecting potential discriminatory variables in human encephalitis, BMC Infectious Diseases 2010, 10:364.
• Hamid JS, Beyene J. A multivariate growth curve model for ranking genes in replicated time course microarray data. Statistical Applications in Genetics and Molecular Biology 2009. Vol. 8, Iss. 1, Article 1.
• Hamid JS, Hu P, Roslin NM, et al. Data integration in genetics and genomics. Methods and challenges. Human Genomics and Proteomics 2009; doi:10.4061/2009/869093
• Hamid JS, Roslin NM, Paterson AD, et al. Using a latent growth curve model for an integrative assessment of the effects of genetic and environmental factors on multiple phenotypes. BMC Genetics Proceedings 2009; 3(Suppl 7): S44
• Beyene J, Atenafu EG, Hamid JS, et al. Determining relative importance of variables in developing and validating a predictive model. BMC Medical Research Methodology 2009, 9:64 doi:10.1186/1471-2288-9-64 .
• Moinedin F, Moineddin R, Jadad A, Hamid JS, et al. Application of biomedical informatics to chronic pediatric diseases: A systematic review. BMC Medical Informatics and Decision Making 2009 , 9:22
• Roslin NM, Hamid JS, Paterson AD, et al. Genome-wide association analysis of cardiovascular-related traits in the Framingham Heart Study. BMC Genetics proceedings 2009; 3(Suppl 7): S117
• Beyene J, Hu P, Hamid JS, et al. Pathway-based analysis of a genome wide case-control association study of rheumatoid arthritis. BMC Genetics Proceedings 2009; 3(Suppl 7): S128.
• Beyene J, Tritcheler D, Asimit JL, Hamid JS. Gene- or region-based analysis of genome-wide association studies. Genetic Epidemiology 2009; 33(S1): S105 - S110.