Since November 2018, I am a Senior Lecturer in Statistics at Manchester Metropolitan University. Previously, I was a Research Associate in Statistics at Imperial College London from October 2015 to October 2018. Prior to that, I was a Postdoctoral Fellow in Statistics at KU Leuven, Belgium, from October 2013 to September 2015.
My main research interests are statistical modelling and statistical inference, as well as big data and data science. My research particularly focuses on high dimensional statistics, mixed-effects models, multilevel models, nonparametric and semiparametric models, joint modelling, model diagnostics and missing data problems. A major focus of my research has been on developing novel statistical methods for the analysis of complex data such as high dimensional data and longitudinal/multilevel data, especially from medical studies.
I teach the undegraduate module "Applied Regression and Multivariate Analysis", and the MSc module "Computational Statistics and Visualisation" for the MSc in Data Analytics. I am also unit leader for the module "Foundation Data Analysis".
T. Sirimongkolkasem, R. Drikvandi (2019). On Regularisation Methods for Analysis of High Dimensional Data. Annals of Data Science.
R. Drikvandi (2019). Nonlinear mixed-effects models with misspecified random-effects distribution. Pharmaceutical Statistics.
K. Rao, R. Drikvandi, B. Saville (2019). Permutation and Bayesian tests for testing random effects in linear mixed-effects models. Statistics in Medicine.
R. Drikvandi, S. Noorian (2019). Testing random effects in linear mixed-effects models with serially correlated errors. Biometrical Journal. 61(4), pp.802-812.
R. Drikvandi, A. Williams, A. Boustati, D. Ezer, D. Arenas, et al. (2018). CodeCheck: How do our food choices affect climate change?. Data Study Groups, The Alan Turing Institute.
R. Drikvandi (2017). Nonlinear mixed-effects models for pharmacokinetic data analysis: assessment of the random-effects distribution. Journal of Pharmacokinetics and Pharmacodynamics. 44(3), pp.223-232.
R. Drikvandi, G. Verbeke, G. Molenberghs (2017). Diagnosing misspecification of the random-effects distribution in mixed models. Biometrics. 73(1), pp.63-71.
A. Efendi, R. Drikvandi, G. Verbeke, G. Molenberghs (2017). A goodness-of-fit test for the random-effects distribution in mixed models. Statistical Methods in Medical Research. 26(2), pp.970-983.
R. Drikvandi, G. Verbeke, A. Khodadadi, V. Partovi Nia (2013). Testing multiple variance components in linear mixed-effects models. Biostatistics. 14(1), pp.144-159.
R. Drikvandi, A. Khodadadi, G. Verbeke (2012). Testing variance components in balanced linear growth curve models. Journal of Applied Statistics. 39(3), pp.563-572.
R. Drikvandi, R. Modarres, AH. Jalilian (2011). A bootstrap test for symmetry based on ranked set samples. Computational Statistics & Data Analysis. 55(4), pp.1807-1814.
R. Drikvandi (2019). Joint modelling of longitudinal data involving time-varying covariates. 'The 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2019)', London, UK,
R. Drikvandi (2019). A novel method for analysis of high dimensional data. 'The Royal Statistical Society International Conference 2019', Belfast, UK,
R. Drikvandi (2017). A joint mixed model for longitudinal data involving time-varying covariates. 'The 17th Conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society', London, UK,
R. Drikvandi (2016). A joint semiparametric mixed model for longitudinal data involving time-varying covariates. 'The Royal Statistical Society International Conference 2016', Manchester, UK,
R. Drikvandi (2015). Assessing the random effects part of mixed models. 'The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015)', London, UK,
R. Drikvandi (2014). Diagnosing misspecication of the random-effects distribution in mixed models. 'The 22nd Conference of the Belgian Statistical Society', Louvain-la-Neuve, Belgium,