Dr Rheanna Mainzer is a Postdoctoral Research Fellow in Biostatistics and Data Science. She is currently researching multiple imputation for dealing with missing data in large-scale longitudinal studies. She also provides statistical support for the Respiratory group. She has a Bachelor of Science, with honours, in Mathematics and Statistics, a Bachelor of Finance and a PhD in Statistics from La Trobe University.
2014: Australian Postgraduate Award
2014: Department Prize in Fouth Year Statistics
2012: AMSI Vacation Research Scholarship
Dr Mainzer is currently researching multiple imputation for dealing with missing data in large-scale longitudinal studies. She has a background in statistical inference after model selection.
Kabaila, P., Mainzer, R. (2019). Exact model averaged tail area confidence intervals. RSSDS2019 conference proceedings. Mainzer, R., Kabaila, P. (2019). ciuupi: an R package for computing confidence intervals that utilize uncertain prior information. The R Journal. Mainzer, R. (2018). The effect of a preliminary Hausman test on confidence intervals. Bulletin of the Australian Mathematical Soceity. (PhD thesis abstract.) Kabaila, P., Mainzer, R. (2018). Two sources of poor coverage of confidence intervals after model selection. Statistics and Probability Letters. Kabaila, P., Mainzer, R. (2018). Estimation risk for VaR and ES. Journal of Risk. Kabaila, P., Mainzer, R., Farchione, D. (2017). Conditional assessment of the impact of a Hausman pretest on confidence intervals. Statistica Neerlandica. Kabaila, P., Welsh, A.H., Mainzer, R. (2016). The performance of model averaged tail area confidence intervals. Communications in Statistics - Theory and Methods. Kabaila, P., Mainzer, R., Farchione, D. (2015). The impact of a Hausman pretest, applied to panel data, on the coverage probability of confidence intervals. Economics Letters.