Several of my papers have involved the development of causal inference methodology.
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.
R Herbert, J Kasza, K Bo. Analysis of randomised trials with long-term follow up. BMC Medical Research Methodology. 2018; 18(48)
J Kasza, R Wolfe, T Schuster. Assessing the impact of unmeasured confounding for binary outcomes using confounding functions. International Journal of Epidemiology. Accepted 26 January 2017.
- Winner of the 2018 Monash University John McNeil Early Career Researcher Publication Prize for Public Health Research
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.
- Winner of the 2016 Monash University John McNeil Early Career Researcher Publication Prize for Public Health Research
- Winner of the 2016 AMREP Public Health Research Mid-Career Researcher Best Paper Award
