Health Research Methods, Evidence, and Impact


Jemila Hamid

Jemila Hamid

BSc (Addis Ababa), MSc (Uppsala), PhD (Uppsala)

Assistant Professor (Part-time), Department of Health Research Methods, Evidence, and Impact

jhamid@mcmaster.ca

 

 

 

 

Academic Interests

Research focus

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.

Research Interests

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

  1. 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
  2. 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.
  3. 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.
  4. 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
  5. 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
  6. 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 .
  7. 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
  8. 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
  9. 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.
  10. 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.

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