Kalaycioglu O, Copas A, King M, Omar RZ (2015). A comparison of multiple imputation methods for handling missing data in repeated measurements observational studies. JRSS A, DOI: 10.1111/rssa.12140.
Pavlou M, Ambler G, Seaman S, Elliott PE, King M, Omar RZ, (2015). How to develop a more accurate risk prediction model when there are few events, BMJ 2015;351:h3868.
Pavlou M, Ambler G, Seaman S, De Iorio M and Omar RZ (2015). Review and evaluation of penalised regression methods for risk prediction in low-dimensional data with few events. Statistics in Medicine. DOI: 10.1002/sim.6782.
Osborn, D. P. J., Hardoon, S., Omar RZ, King, M., Marston, L., Morris, R. W., Nazareth, I. and Larsen, J. (2015). Cardiovascular risk prediction models for people with severe mental illness results from the prediction and management of cardiovascular risk in people with severe mental Illnesses (PRIMROSE) research program. JAMA Psychiatry, 72 (2), 143-151. DOi:10.1001/jamapsychiatry.2014.2133.
O'Mahony C, Jichi F, Menelaos P, Monserrat L, Anastasakis A, Rapezzi C, Biagini E, Gimeno JR, Limongelli G, McKenna WJ, Omar RZ and Elliott PM, for the Hypertrophic Cardiomyopathy Outcomes Investigators (2013). A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM-RISK). Eur Heart J (2013) doi: 10.1093/eurheartj/eht439.
Ambler, G., Seaman, S., Omar, R. Z. (2012). An evaluation of penalised survival methods for developing prognostic models with rare events. Statistics in Medicine 31(11-12), 1150-1161 doi:10.1002/sim.4371.
Omar, R. Z., O'Sullivan, C., Petersen, I., Islam, A., Majeed, A. (2008). A model based on age, sex, and morbidity to explain variation in UK general practice prescribing: cohort study. BMJ 337, a238- doi:10.1136/bmj.a238.