|Phone (external)||+44 (0) 20 3108 3227|
|Themes||Biostatistics, General Theory and Methodology|
Federico graduated in Statistics and Computer Science from the University of Florence (Italy), where he then also completed a PhD programme in Applied Statistics. During the PhD programme he spent a period at the Netherlands Forensic Insitute in The Hague as Visiting Research Fellow. After a period at the University of Florence as Post-Doc Research Fellow in causal inference, Federico is now a Research Associate at the Department of Statistical Science, UCL, UK, where he is part of the Biostatistics Group and UCL PRIMENT Clinical Trial Unit. More details can be found on his personal website.
Causal Inference for Observational Studies, Sequential Treatments, Regression Discontinuity Designs, Bayesian Inference and Applications, Medical Statistics, Survival Analysis.
- Statistical Methods in Research (MEDCG001, course Co-Organizer)
- Practical Statistics for Medical Research (short course)
- Ricciardi, F., Mattei, A., Mealli, F. (2019) Bayesian Inference for Sequential Treatments under Latent Sequential Ignorability. JASA, doi:10.1080/01621459.2019.1623039.
- Geneletti, S., Ricciardi, F. et al. (2019) Bayesian modelling for binary outcomes in the Regression Discontinuity Design. J. R. Stat. Soc. A, 182: 983-1002. doi:10.1111/rssa.12440
- Bloom, C., Ricciardi F. et al. (2019) Predicting COPD one year mortality using prognostic predictors routinely measured in primary care. BMC Medicine, 17:73, doi:10.1186/s12916-019-1310-0
- Choi, D., Ricciardi, F. et al. (2018). Prediction Accuracy of Common Prognostic Scoring Systems for Metastatic Spine Disease: Results of a Prospective International Multicentre Study of 1469 Patients. Spine 43(23):1678-1684.
- Ricciardi, F. & Slooten, K. (2014). Mutation Models for DVI analysis. FSI:Genetics, 11, 85-95.
- Corradi, F. & Ricciardi, F. (2013). Evaluation of Kinship Identification Systems Based on STR DNA Profiles. JRSS: Series C, 62(5), 649-668.