Staff profile
Overview
Dr Emmanuel Ogundimu
Co-Director of Durham Biostatistics Unit, Associate Professor, Statistics
Affiliation | Telephone |
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Co-Director of Durham Biostatistics Unit, Associate Professor, Statistics in the Department of Mathematical Sciences | +44 (0) 191 33 43488 |
Fellow of the Wolfson Research Institute for Health and Wellbeing |
Research interests
- Applied Statistics
- Biostatistics
- Machine Learning and Causal Inference
- Missing Data Methodology
- Models for Rare Events
Publications
Journal Article
- Ogundimu, E. O. (online). On Lasso and adaptive Lasso for non-random sample in credit scoring. Statistical Modelling, https://doi.org/10.1177/1471082x221092181
- Rodgers, J., Cassidy, S., Pelton, M., Goodwin, J., Wagnild, J., Bhattarai, N., Gordon, I., Wilson, C., Heslop, P., Ogundimu, E., O'Connor, R. C., Ramsay, S. E., Townsend, E., & Vale, L. (2024). Feasibility and acceptability of autism adapted safety plans: an external pilot randomised controlled trial. EClinicalMedicine, 73, Article 102662. https://doi.org/10.1016/j.eclinm.2024.102662
- Catlow, J., Sharp, L., Wagnild, J., Lu, L., Bhardwaj-Gosling, R., Ogundimu, E., Kasim, A., Brookes, M., Lee, T., McCarthy, S., Gray, J., Sniehotta, F., Valori, R., Westwood, C., McNally, R., Ruwende, J., Sinclair, S., Deane, J., & Rutter, M. (2024). Nationally Automated Colonoscopy Performance Feedback Increases Polyp Detection: the NED APRIQOT Randomised Controlled Trial. Clinical Gastroenterology and Hepatology, 22(9), 1926-1936. https://doi.org/10.1016/j.cgh.2024.03.048
- Dudley, R., Dodgson, G., Common, S., Ogundimu, E., Liley, J., O’Grady, L., Watson, F., Gibbs, C., Arnott, B., Fernyhough, C., Alderson-Day, B., & Aynsworth, C. (2024). Effects of a novel, brief psychological therapy (Managing Unusual Sensory Experiences) for hallucinations in first episode psychosis (MUSE FEP): findings from an exploratory randomised controlled trial. Journal of Psychiatric Research, 174, 289-296. https://doi.org/10.1016/j.jpsychires.2024.04.031
- Akowuah, E., Mathias, A., Bardgett, M., Harrison, S., Kasim, A. S., Loughran, K., Ogundimu, E., Trevis, J., Wagnild, J., Witharana, P., Hancock, H. C., & Maier, R. H. (2023). Prehabilitation in elective patients undergoing cardiac surgery: a randomised control trial (THE PrEPS TRIAL) – a study protocol. BMJ Open, 13(1), Article e065992. https://doi.org/10.1136/+bmjopen-2022-065992
- Dudley, R., Dodgson, G., Common, S., O'Grady, L., Watson, F., Gibbs, C., Arnott, B., Fernyhough, C., Alderson-Day, B., Ogundimu, E., Kharatikoopaei, E., Patton, V., & Aynsworth, C. (2022). Managing Unusual Sensory Experiences in People with First-Episode Psychosis (MUSE FEP): a study protocol for a single-blind parallel-group randomised controlled feasibility trial. BMJ Open, 12(5), Article e061827. https://doi.org/10.1136/bmjopen-2022-061827
- Ogundimu, E. O. (2022). Regularization and variable selection in Heckman selection model. Statistical Papers, 63(2), 421-439. https://doi.org/10.1007/s00362-021-01246-z
- Ogundimu, E. O. (2019). Prediction of default probability by using statistical models for rare events. Journal of the Royal Statistical Society: Series A, 182(4), 1143-1162. https://doi.org/10.1111/rssa.12467
- Ogundimu, E. O., & Collins, G. S. (2019). A robust imputation method for missing responses and covariates in sample selection models. Statistical Methods in Medical Research, 28(1), 102-116. https://doi.org/10.1177/0962280217715663
- Ogundimu, E. O., & Collins, G. S. (2018). Predictive performance of penalized beta regression model for continuous bounded outcomes. Journal of Applied Statistics, 45(6), 1030-1040. https://doi.org/10.1080/02664763.2017.1339024
- Collins, G. S., Ogundimu, E. O., Cook, J. A., Manach, Y. L., & Altman, D. G. (2016). Quantifying the impact of different approaches for handling continuous predictors on the performance of a prognostic model. Statistics in Medicine, 35(23), 4124-4135. https://doi.org/10.1002/sim.6986
- Ogundimu, E. O., & Hutton, J. L. (2016). A Sample Selection Model with Skew-normal Distribution. Scandinavian Journal of Statistics, 43(1), 172-190. https://doi.org/10.1111/sjos.12171
- Collins, G. S., Ogundimu, E. O., & Altman, D. G. (2016). Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Statistics in Medicine, 35(2), 214-226. https://doi.org/10.1002/sim.6787
- Ogundimu, E. O., & Hutton, J. L. (2016). A unified approach to multilevel sample selection models. Communications in Statistics - Theory and Methods, 45(9), 2592-2611. https://doi.org/10.1080/03610926.2014.887108
- Rubio, F., Ogundimu, E., & Hutton, J. (2016). On modelling asymmetric data using two-piece sinh–arcsinh distributions. Brazilian Journal of Probability and Statistics (Impresso), 30(3), https://doi.org/10.1214/15-bjps290
- Akacha, M., & Ogundimu, E. O. (2016). Sensitivity analyses for partially observed recurrent event data. Pharmaceutical Statistics, 15(1), https://doi.org/10.1002/pst.1720
- Ogundimu, E. O., Altman, D. G., & Collins, G. S. (2016). Adequate sample size for developing prediction models is not simply related to events per variable. Journal of Clinical Epidemiology, 76, https://doi.org/10.1016/j.jclinepi.2016.02.031
- Ogundimu, E. O., & Hutton, J. L. (2015). On the extended two-parameter generalized skew-normal distribution. Statistics and Probability Letters, 100, 142-148. https://doi.org/10.1016/j.spl.2015.02.016