My research interests pertain to innovative application of statistical methods in health research; these include application of an existing statistical method or development of (new) analytical (statistical) tools as warranted by the health research topic. My research finds their appreciation and application in various disciplines of applied science. Specifically, my research topics include:
- Incomplete or missing data
- Model selection
- Longitudinal models
- Computational statistics
- Signal saturation rates
The above topics have been used extensively in dissertations (21+) and papers (16+) authored by students who I have mentored as a committee member or supervisor. Since joining the School of Public Health Sciences in September 2015, these topics have been used to address pressing questions in the areas of nutrition, epidemiology, cancer care, pediatrics, nephrology, workers health, aging, maternal and child health, and more. A list of my citations can be found on my Google Scholar page.
Graduate supervision and student opportunities
I am currently accepting applications from graduate students with research interests related to:
- Applied statistics and computational statistics to models open problems in health research
- Statistics and probability
- Linear algebra
- Linear and non-linear models
- Longitudinal and hierarchical models
- Missing data and data imputation
- Structural equation models
BSc Statistics (with Honours), University of Texas at San Antonio
BSc Mathematics (with Honours), University of Texas at San Antonio
MSc Statistics, University of Texas at San Antonio
PhD Statistics, University of Connecticut
Postdoctoral Fellow in Biostatistics and Bioinformatics Branch of National Institute of Child Health and Human Development, National Institutes of Health, United States
See Google Scholar for full list publications.
*Designates students in joint paper
- *Hammami, N., Chaurasia, A., Bigelow, P., & Leatherdale, S. T. (2019). A gender-stratified, multilevel latent class assessment of chronic disease risk behaviours' association with Body Mass Index among youth in the COMPASS study. Preventive medicine, 126, 105758.
- *Aboueid, S., Liu, R. H., Desta, B. N., Chaurasia, A., & Ebrahim, S. (2019). The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review. JMIR medical informatics, 7(2), e13445.
- Gilfoyle, M., Garcia, J., Chaurasia, A., & Oremus, M. (2019). Perceived susceptibility to developing cancer and mammography screening behaviour: a cross-sectional analysis of Alberta's Tomorrow Project. Public Health, 177, 135-142.
- Chaurasia, A., Liu, D., & Albert, P. S. (2018). Pattern–mixture models with incomplete informative cluster size: application to a repeated pregnancy study. Journal of the Royal Statistical Society: Series C (Applied Statistics), 67(1), 255-273.
- Sapra, K. J., Chaurasia, A. K., Hutcheon, J. A., & Ahrens, K. A. (2017). Reconstructing a pregnancy cohort to examine potential selection bias in studies on racial disparities in preterm delivery. Paediatric and perinatal epidemiology, 31(1), 55-63.
- Chaurasia, A. and Harel, O. (2013). Model selection rates of information-based criteria. The Electronic Journal of Statistics 7, 2762–2793.