| A comparison of two methods of estimating propensity scores after multiple imputation R Mitra, JP Reiter Statistical methods in medical research 25 (1), 188-204, 2016 | 250 | 2016 |
| On the use of Cauchy prior distributions for Bayesian logistic regression J Ghosh, Y Li, R Mitra Bayesian Analysis 13 (2), 359-383, 2018 | 123 | 2018 |
| Estimating risks of identification disclosure in partially synthetic data JP Reiter, R Mitra Journal of Privacy and Confidentiality 1 (1), 2009 | 110 | 2009 |
| Estimating propensity scores with missing covariate data using general location mixture models R Mitra, JP Reiter Statistics in medicine 30 (6), 627-641, 2011 | 47 | 2011 |
| Adjusting survey weights when altering identifying design variables via synthetic data R Mitra, JP Reiter International Conference on Privacy in Statistical Databases, 177-188, 2006 | 41 | 2006 |
| Multiply imputing missing values in data sets with mixed measurement scales using a sequence of generalised linear models MC Lee, R Mitra Computational statistics & data analysis 95, 24-38, 2016 | 20 | 2016 |
| Two-level stochastic search variable selection in GLMs with missing predictors R Mitra, D Dunson The international journal of biostatistics 6 (1), 2010 | 16 | 2010 |
| Optimal design for experiments with possibly incomplete observations KM Lee, S Biedermann, R Mitra Statistica Sinica 28 (3), 1611-1632, 2018 | 7 | 2018 |
| Optimal design when outcome values are not missing at random KM Lee, R Mitra, S Biedermann Statistica Sinica 28 (4), 1821-1838, 2018 | 7 | 2018 |
| On the equivalence of posterior inference based on retrospective and prospective likelihoods: application to a case‐control study of colorectal cancer M Ghosh, J Song, JJ Forster, R Mitra, B Mukherjee Statistics in medicine 31 (20), 2196-2208, 2012 | 7 | 2012 |
| Data privacy preserving scheme using generalised linear models MC Lee, R Mitra, E Lazaridis, AC Lai, YK Goh, WS Yap Computers & Security 69, 142-154, 2017 | 6 | 2017 |
| Are independent parameter draws necessary for multiple imputation? J Hu, R Mitra, J Reiter The American Statistician 67 (3), 143-149, 2013 | 5 | 2013 |
| Confidentiality challenges in releasing longitudinally linked data R Mitra, S Blanchard, I Dove, C Tudor, K Spicer Transactions on Data Privacy 13 (2), 151-170, 2020 | 4 | 2020 |
| Using mixtures of t densities to make inferences in the presence of missing data with a small number of multiply imputed data sets S Rashid, R Mitra, RJ Steele Computational Statistics & Data Analysis 92, 84-96, 2015 | 4 | 2015 |
| Bayesian model-based clustering for multiple network data A Mantziou, S Lunagomez, R Mitra arXiv preprint arXiv:2107.03431, 2021 | 3 | 2021 |
| Multiply imputing missing values arising by design in transplant survival data L Pankhurst, R Mitra, A Kimber, D Collett Biometrical Journal 62 (5), 1192-1207, 2020 | 2 | 2020 |
| Statistical Disclosure Control for Data Privacy Using Sequence of Generalised Linear Models MC Lee, R Mitra, E Lazaridis, AC Lai, YK Goh, WS Yap Australasian Conference on Information Security and Privacy, 77-93, 2016 | 2 | 2016 |
| Propensity score matching with missing covariates via iterated, sequential multiple imputation R Mitra, JP Reiter Southampton Statistical Sciences Research Institute, University of Southampton, 2011 | 2 | 2011 |
| Bayesian Methods to Impute Missing Covariates for Causal Inference and Model Selection R Mitra Duke University, 2008 | 1 | 2008 |
| An overview on synthetic administrative data for research T Kokosi, B De Stavola, R Mitra, L Frayling, A Doherty, I Dove, ... International Journal of Population Data Science 7 (1), 2022 | | 2022 |
Jerome ReiterDuke UniversityVerifierad e-postadress på duke.edu
