I’m a biostatistician in the Department of Epidemiology and Preventive Medicine at Monash University, in Melbourne, Australia, and I’m part of ViCBiostat: the Victorian Centre for Biostatistics, an NHMRC-funded Centre for Research Excellence. I’m the Vice President of the Victorian Branch of the Statistical Society of Australia, and Vice President nationally. The Vic Branch of the Statistical Society holds seminars every month: see our meetup page for details of upcoming events. I’m on the organising committee of the 2020 Women in Mathematical and Statistical Sciences Conference, to be held at Monash University, October 1-2, 2020.
My colleagues and I recently wrote about the importance of fostering biostatistics research for the success of research in health and medicine. Our article is freely available from the Medical Journal of Australia here.
PhD in Statistics, 2010
University of Adelaide
B Sc (Ma & Comp Sc) (Hons), 2005
University of Adelaide
Much of my recent work has focussed on the development of methodology for longitudinal cluster randomised trials, including the stepped wedge design and multi-cross-over cluster trial.
Many of my recent projects have been in the development of theory for causal inference.
I have been involved in several projects comparing the performance of healthcare providers.
M McGuinness, J Kasza, A Karahalios, R Guymer, RP Finger, JA Simpson. A comparison of methods to estimate the survivor average causal effect in the presence of missing data: a simulation study. BMC Medical Research Methodology, (2019) 19:223.
K Grantham, J Kasza, S Heritier, K Hemming, E Litton, A Forbes. How many times should a cluster randomized crossover trial cross over? Statistics in Medicine. 2019:38(25);5021-5033.
J Kasza, M Taljaard, A Forbes. Information content of stepped-wedge designs when treatment effect heterogeneity and/or implementation periods are present. Statistics in Medicine. Accepted 2019.
K Grantham, A Forbes, S Heritier, J Kasza. Time Parameterizations in Cluster Randomized Trial Planning. The American Statistician. Accepted 2019.
K Grantham, J Kasza, S Heritier, K Hemming, A Forbes. Accounting for a decaying correlation structure in cluster randomized trials with continuous recruitment. Statistics in Medicine. 2019:38(11);1918-1934.
J Kasza, A Forbes. Inference for the treatment effect in multiple-period cluster randomised trials when random effect correlation structure is misspecified. Statistical Methods in Medical Research. (2019) 28(10-11):3112-3122.
J Kasza, A Forbes. Information content of cluster-period cells in stepped wedge trials. Biometrics. (2019) 75(1):144-152.
J Kasza, KR Polkinghorne, R Wolfe, SP McDonald, MR Marshall. Comparing dialysis centre mortality outcomes across Australia and New Zealand: identifying unusually performing centres 2008–2013. BMC Health Services Research. (2018) 18:1007.
R Herbert, J Kasza, K Bo. Analysis of randomised trials with long-term follow up. BMC Medical Research Methodology. 2018; 18(48)
J Kasza, K Hemming, R Hooper, JNS Matthews, A Forbes. Impact of non-uniform correlation on sample size and power in multiple period cluster randomised trials. Statistical Methods in Medical Research. (2019) 28(3):703-716.
J Kasza, R Wolfe, T Schuster. Assessing the impact of unmeasured confounding for binary outcomes using confounding functions. International Journal of Epidemiology. (2017) 46(4):1303–1311.
C Oates*, J Kasza*, JA Simpson, A Forbes. (*Joint first authors) Repair of partly misspecified causal diagrams. Epidemiology. 28(4):548–552.
M McGuinness, A Karahalios, J Kasza, R Guymer, RP Finger, JA Simpson. Survival bias when assessing risk factors for age-related macular degeneration: a tutorial with application to the exposure of smoking. Ophthalmic Epidemiology, (2017) 24(4):229-238.
C Oates, J Kasza, S Mukherjee. Discussion of “Causal inference by using invariant prediction: identification and confidence intervals”. Journal of the Royal Statistical Society, Series B, (2016) 78(5):1003.
J Kasza, KR Polkinghorne, SP McDonald, MR Marshall, R Wolfe. Clustering and residual confounding in the application of marginal structural models to registry data: dialysis, vascular access, and mortality. American Journal of Epidemiology, (2015) 182(6):535-543.
JA Flegg, J Kasza, I Darby and CD Weller. Healing of venous ulcers using compression therapy: predictions of a mathematical model. Journal of Theoretical Biology. (2015) 379:1-9.
J Kasza. Stata tip 125: Binned residual plots for assessing the fit of regression models for binary outcomes. The Stata Journal. (2015) 15(2):599-604.
J Kasza, JL Moran and PJ Solomon. Assessing changes over time in health-care provider performance: addressing regression to the mean over multiple time points. Biometrical Journal. (2015) 57(2):271-285.
J Kasza and PJ Solomon. Comparing score-based methods for estimating Bayesian networks using the Kullback-Leibler divergence. Communications in Statistics: Theory and Methods. (2015) 44(1):135-152.
J Kasza, D Wraith, K Lamb and R Wolfe. Survival analysis of time-to-event data in respiratory health studies. Respirology. (2014) 19(4):483-492.
J Kasza and R Wolfe. Interpretation of commonly used statistical regression models. Respirology. (2014) 19(1):14-21.
PJ Solomon, J Kasza and JL Moran. Identifying unusual performance in Australian and New Zealand intensive care units from 2000 to 2010. BMC Medical Research Methodology. (2014) 14:53.
J Kasza, JL Moran and PJ Solomon. Evaluating the performance of Australian and New Zealand intensive care units in 2009 and 2010. Statistics in Medicine. (2013) 32(21):3720-36.
J Kasza, G Glonek, and PJ Solomon. Estimating Bayesian networks for high-dimensional data with complex mean structure and random effects. Australian and New Zealand Journal of Statistics. (2012) 54(2):169-87.