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Dr Menelaos Pavlou

Position

Lecturer in Medical Statistics

Phone (external)+44(0)20 3108 3245
Phone (internal)53245
Email(*)m.pavlou
ThemesBiostatistics, General Theory and Methodology

* @ucl.ac.uk

Biographical Details

Menelaos has been working as a Lecturer in Medical Statistics at the Department of Statistical Science, UCL since April 2019. He also has the role of the Mentor for Postgraduate Teaching Assistants. He collaborates with the National Institute of Cardiovascular Outcomes Research (NICOR) at Barts Health NHS Trust, where he is part-based, and provides statistical oversight of the analytical team. Menelaos completed a degree of Mathematics in 2004 at the Aristotel's University of Thessaloniki, Greece, followed by an MSc in Statistics (2005) in the Department of Statistical Science, UCL.

After having worked for a consulting company, he pursuit a part-time PhD in Medical Statistics in the department of Statistical Science, UCL (2007), while working as a Medical Statistician at the Centre of Sexual Health and HIV Research, UCL. He was awarded with a PhD in 2012, and until 2016 was employed as a post-doctoral research associate in the Department of Statistical Science, UCL. 

Research Interests

Risk Prediction Modelling, Analysis of Clustered Data, Methods for Comparing Institutional Performance and Outlier Detection, Informative Cluster Size, Missing data, Penalised Regression.

Selected publications

- Pavlou M, Qu C, Omar RZ, Seaman SR, Steyerberg EW, White IR, Ambler G. Estimation of required sample size for external validation of risk models for binary outcomes. Statistical Methods in Medical Research. doi:10.1177/09622802211007522.

 

- Pavlou M, Ambler G, Seaman SR, De Iorio M, Omar RZ (2015). Review and evaluation of penalised regression methods for risk prediction in datasets with few events, Statistics in Medicine, doi: 10.1002/sim.6782.

 

- Pavlou M, Ambler G, Seaman SR, Guttman O, Elliott P, Omar RZ (2015). How to develop a more accurate risk prediction model when there are few events, BMJ, 351:h3868.

 

- Pavlou M, Ambler G, Seaman SR, Omar RZ (2015). A note on obtaining correct marginal predictions from a random intercepts model for binary outcomes, BMC, Medical Research Methodology, 15:59, doi: 10.1186/s12874-015-0046-6.

 

- O'Mahony C, Jichi F, Pavlou M, Monserrat L et al. (2013). A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy, European Heart Journal, doi:10.1093/eurheartj /eht439.

 

- Seaman SR, Pavlou M, Copas A (2014). A Review of Methods for Handling Confounding by Cluster and Informative Cluster Size, Statistics in Medicine, doi:10.1002/sim.6277.

 

- Seaman SR, Pavlou M, Copas A (2014). Methods for Observed-Cluster Inference when Cluster Size is Informative: a Review and Clarifications, Biometrics, doi: 10.1111/biom.12151.

 

- Bailey J, Pavlou M, Copas A, McCarthy O, Karswell K (2013). The Sexunzipped pilot trial: optimizing the design of online randomized controlled trials, Journal of Medical Internet Research,15(12):e278.

 

- Pavlou M, Seaman SR, Copas A (2013). An examination of a method for marginal inference when the cluster size is informative, Statistica Sinica, 23, pp. 791-808.