Staff profile
Dr Reza Drikvandi
Associate Professor, Statistics
Affiliation | Telephone |
---|---|
Associate Professor, Statistics in the Department of Mathematical Sciences | +44 (0) 191 33 40846 |
Fellow of the Wolfson Research Institute for Health and Wellbeing |
Biography
About me:
I am an Associate Professor of Statistics at Durham University. Previously, I had academic positions at Imperial College, Manchester and KU Leuven. My research mainly focuses on high dimensional statistics, change point analysis for high dimensional data, longitudinal data analysis, linear and nonlinear mixed models, survival analysis, nonparametric methods, joint modelling and model diagnostics. A major focus of my research has been on developing novel statistical methods and models for the analysis of complex data such as high dimensional data and multilevel/longitudinal data, especially from medical and health research as well as finance and social science.
I serve as Associate Editor for "Statistics & Probability Letters" journal.
I achieved Fellowship of the Higher Education Academy in 2020. This year I am teaching the course "High Dimensional Statistics" for final year maths and statistics students. Last year I taught the MSc course "Models and Methods for Health Data Science".
If you are interested to do a PhD in Statistics or Data Science, please get in touch.
Research interests
- High dimensional statistics
- Longitudinal data analysis
- Change point analysis for high dimensional data
- Statistical modelling and inference
- Biostatistics
- Survival analysis
Publications
Conference Paper
- Zhang, L., & Drikvandi, R. (2023). High dimensional change points: challenges and some proposals. . https://doi.org/10.11159/icsta23.142
- Zhang, Y., Einbeck, J., & Drikvandi, R. (2023). A multilevel multivariate response model for data with latent structures.
- Drikvandi, R. (2021). Diagnostic tools for random effects in general mixed models.
- Drikvandi, R. (2020). Invited session "Recent advances in biostatistics".
- Drikvandi, R. (2019). A novel method for analysis of high dimensional data.
- Drikvandi, R. (2019). Joint modelling of longitudinal data involving time-varying covariates.
- Drikvandi, R. (2017). A joint mixed model for longitudinal data involving time-varying covariates.
- Drikvandi, R. (2016). A joint semiparametric mixed model for longitudinal data involving time-varying covariates.
- Drikvandi, R. (2015). Assessing the random effects part of mixed models.
- Drikvandi, R. (2014). Diagnosing misspecication of the random-effects distribution in mixed models.
Journal Article
- Al-Zubaidy, N., Crespo, R., Jones, S., Drikvandi, R., Gould, L., Leis, M., …Darzi, A. Using big data analytics to explore the relationship between government stringency and preventative social behaviour during the COVID-19 pandemic in the United Kingdom [Preprint]
- Drikvandi, R., & Modarres, R. (2024). A distribution-free method for change point detection in non-sparse high dimensional data. Journal of Computational and Graphical Statistics, https://doi.org/10.1080/10618600.2024.2365733
- Drikvandi, R., Verbeke, G., & Molenberghs, G. (2024). A framework for analysing longitudinal data involving time-varying covariates. Annals of Applied Statistics, 18(2), 1618-1641. https://doi.org/10.1214/23-AOAS1851
- Al-Zubaidy, N., Fernandez Crespo, R., Jones, S., Gould, L., Leis, M., Maheswaran, H., …Drikvandi, R. (2023). Exploring the relationship between government stringency and preventative social behaviours during the COVID-19 pandemic in the United Kingdom. Health Informatics Journal, 29(4), Article 14604582231215867. https://doi.org/10.1177/14604582231215867
- Drikvandi, R., & Lawal, O. (2023). Sparse principal component analysis for natural language processing. Annals of Data Science, 10(1), 25-41. https://doi.org/10.1007/s40745-020-00277-x
- Rubio, J., & Drikvandi, R. (2022). MEGH: A parametric class of general hazard models for clustered survival data. Statistical Methods in Medical Research, 31(8), 1603-1616. https://doi.org/10.1177/09622802221102620
- Drikvandi, R. (2020). Nonlinear mixed-effects models with misspecified random-effects distribution. Pharmaceutical Statistics, 19(3), 187-201. https://doi.org/10.1002/pst.1981
- Sirimongkolkasem, T., & Drikvandi, R. (2019). On regularisation methods for analysis of high dimensional data. Annals of Data Science, 6(4), 737-763. https://doi.org/10.1007/s40745-019-00209-4
- Rao, K., Drikvandi, R., & Saville, B. (2019). Permutation and Bayesian tests for testing random effects in linear mixed-effects models. Statistics in Medicine, 38(25), 5034-5047. https://doi.org/10.1002/sim.8350
- Drikvandi, R., & Noorian, S. (2019). Testing random effects in linear mixed-effects models with serially correlated errors. Biometrical Journal, 61(4), 802-812. https://doi.org/10.1002/bimj.201700203
- Drikvandi, R. (2017). Nonlinear mixed-effects models for pharmacokinetic data analysis: assessment of the random-effects distribution. Journal of Pharmacokinetics and Pharmacodynamics, 44(3), 223-232. https://doi.org/10.1007/s10928-017-9510-8
- Efendi, A., Drikvandi, R., Verbeke, G., & Molenberghs, G. (2017). A goodness-of-fit test for the random-effects distribution in mixed models. Statistical Methods in Medical Research, 26(2), 970-983. https://doi.org/10.1177/0962280214564721
- Drikvandi, R., Verbeke, G., & Molenberghs, G. (2017). Diagnosing misspecification of the random-effects distribution in mixed models. Biometrics, 73(1), 63-71. https://doi.org/10.1111/biom.12551
- Drikvandi, R., Verbeke, G., & Molenberghs, G. (2017). Supplementary materials for: Diagnosing misspecification of the random-effects distribution in mixed models. Biometrics, https://doi.org/10.1111/biom.12551
- Drikvandi, R., Verbeke, G., Khodadadi, A., & Partovi Nia, V. (2013). Testing multiple variance components in linear mixed-effects models. Biostatistics, 14(1), 144-159. https://doi.org/10.1093/biostatistics/kxs028
- Drikvandi, R., Khodadadi, A., & Verbeke, G. (2012). Testing variance components in balanced linear growth curve models. Journal of Applied Statistics, 39(3), 563-572. https://doi.org/10.1080/02664763.2011.603294
- Drikvandi, R., Modarres, R., & Jalilian, A. H. (2011). A bootstrap test for symmetry based on ranked set samples. Computational Statistics & Data Analysis, 55(4), 1807-1814. https://doi.org/10.1016/j.csda.2010.11.012
Report