| Integrating the evidence from evidence factors in observational studies B Karmakar, B French, DS Small Biometrika 106 (2), 353-367, 2019 | 34 | 2019 |
| Using approximation algorithms to build evidence factors and related designs for observational studies B Karmakar, DS Small, PR Rosenbaum Journal of Computational and Graphical Statistics 28 (3), 698-709, 2019 | 26 | 2019 |
| How to make a neural network say “don’t know” B Karmakar, NR Pal Information Sciences 430, 444-466, 2018 | 19 | 2018 |
| Tight clustering for large datasets with an application to gene expression data B Karmakar, S Das, S Bhattacharya, R Sarkar, I Mukhopadhyay Scientific reports 9 (1), 3053, 2019 | 18 | 2019 |
| Improved retention analysis in freemium role-playing games by jointly modelling players’ motivation, progression and churn B Karmakar, P Liu, G Mukherjee, H Che, S Dutta Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022 | 13 | 2022 |
| Reinforced designs: Multiple instruments plus control groups as evidence factors in an observational study of the effectiveness of Catholic schools B Karmakar, DS Small, PR Rosenbaum Journal of the American Statistical Association 116 (533), 82-92, 2021 | 12 | 2021 |
| Assessment of the extent of corroboration of an elaborate theory of a causal hypothesis using partial conjunctions of evidence factors B Karmakar, DS Small | 12 | 2020 |
| Using evidence factors to clarify exposure biomarkers B Karmakar, DS Small, PR Rosenbaum American Journal of Epidemiology 189 (3), 243-249, 2020 | 11 | 2020 |
| Evidence factors from multiple, possibly invalid, instrumental variables A Zhao, Y Lee, DS Small, B Karmakar The Annals of Statistics 50 (3), 1266-1296, 2022 | 7 | 2022 |
| Risk efficient estimation of fully dependent random coefficient autoregressive models of general order B Karmakar, I Mukhopadhyay Communications in Statistics-Theory and Methods 47 (17), 4242-4253, 2018 | 7 | 2018 |
| False discovery rate control for effect modification in observational studies B Karmakar, R Heller, DS Small | 7 | 2018 |
| An approximation algorithm for blocking of an experimental design B Karmakar Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 5 | 2022 |
| Evidence factors in a case-control study with application to the effect of flexible sigmoidoscopy screening on colorectal cancer B Karmakar, CA Doubeni, DS Small The annals of applied statistics 14 (2), 829, 2020 | 4 | 2020 |
| Risk-efficient sequential estimation of multivariate random coefficient autoregressive process B Karmakar, I Mukhopadhyay Sequential Analysis 38 (1), 26-45, 2019 | 4 | 2019 |
| Degree of interference: A general framework for causal inference under interference Y Ohnishi, B Karmakar, A Sabbaghi arXiv preprint arXiv:2210.17516, 2022 | 3 | 2022 |
| Statistical validity and consistency of big data analytics: a general framework B Karmakar, I Mukhopadhyay arXiv preprint arXiv:1803.10901, 2018 | 3 | 2018 |
| The Effect of Demonetization on Digital Payments in India B Karmakar, B Pareek, D Small, P Ghosh Working paper, University of Pennsylvania, Philadelphia, PA, 2018 | 3 | 2018 |
| An efficient partition-repetition approach in clustering of big data B Karmakar, I Mukhopadhayay Big Data Analytics: Methods and Applications, 75-93, 2016 | 2 | 2016 |
| Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening B Karmakar, AG Zauber, AI Hahn, YK Lau, CA Doubeni, MM Joffe International Journal of Epidemiology 53 (4), dyae096, 2024 | 1 | 2024 |
| Constructing independent evidence from regression and instrumental variables with an application to the effect of violent conflict on altruism and risk preference B Karmakar, DS Small Biostatistics & Epidemiology 7 (1), e2109910, 2023 | 1 | 2023 |
Dylan SmallProfessor of Statistics, University of PennsylvaniaVerified email at wharton.upenn.edu
