| Big data, official statistics and some initiatives by the Australian Bureau of Statistics SM Tam, F Clarke International Statistical Review 83 (3), 436-448, 2015 | 97 | 2015 |
| On covariances from overlapping samples SM Tam The American Statistician 38 (4), 288-289, 1984 | 60 | 1984 |
| Maximum likelihood inference from sample survey data JU Breckling, RL Chambers, AH Dorfman, SM Tam, AH Welsh International Statistical Review/Revue Internationale de Statistique, 349-363, 1994 | 59 | 1994 |
| Data integration by combining big data and survey sample data for finite population inference JK Kim, SM Tam International Statistical Review 89 (2), 382-401, 2021 | 55 | 2021 |
| Analysis of repeated surveys using a dynamic linear model SM Tam International Statistical Review/Revue Internationale de Statistique, 63-73, 1987 | 55 | 1987 |
| How nearly can model-based prediction and design-based estimation be reconciled? KRW Brewer, M Hanif, SM Tam Journal of the American Statistical Association 83 (401), 128-132, 1988 | 51 | 1988 |
| Big Data ethics and selection-bias: An official statistician's perspective SM Tam, JK Kim Statistical Journal of the IAOS 34 (4), 577-588, 2018 | 38 | 2018 |
| Characterization of best model-based predictors in survey sampling SM Tam Biometrika 73 (1), 232-235, 1986 | 28 | 1986 |
| Measuring discontinuities in time series obtained with repeated sample surveys J van Den Brakel, X Zhang, SM Tam International Statistical Review 88 (1), 155-175, 2020 | 18 | 2020 |
| Some results on robust estimation in finite population sampling SM Tam Journal of the American Statistical Association 83 (401), 242-248, 1988 | 17 | 1988 |
| Optimal estimation in survey sampling under a regression superpopulation model SM Tam Biometrika 71 (3), 645-647, 1984 | 17 | 1984 |
| A quality framework for statistical algorithms W Yung, SM Tam, B Buelens, H Chipman, F Dumpert, G Ascari, F Rocci, ... Statistical Journal of the IAOS 38, 291 - 308, 2022 | 14 | 2022 |
| Supporting research and protecting confidentiality. ABS microdata access: Current strategies and future directions SM Tam, K Farley-Larmour, M Gare Statistical Journal of the IAOS 26 (3-4), 65-74, 2009 | 14 | 2009 |
| Screening of probability samples SM Tam, NN Chan International Statistical Review/Revue Internationale de Statistique, 301-308, 1984 | 14 | 1984 |
| Asymptotically design-unbiased predictors in survey sampling SM Tam Biometrika 75 (1), 175-177, 1988 | 13 | 1988 |
| On covariance in finite population sampling SM Tam The Statistician, 429-433, 1985 | 12 | 1985 |
| The five V's, seven Virtues and ten Rules of Big Data Engagement for Official Statistics SM Tam, G van Halderen Statistical Journal of the IAOS, 2020 | 11 | 2020 |
| A statistical framework for analysing Big Data SM Tam The Survey Statistician 72, 36-51, 2015 | 11 | 2015 |
| Optimality of Royall's predictor under a Gaussian superpopulation model SM Tam Biometrika 74 (3), 659-660, 1987 | 11 | 1987 |
| Big data, statistical inference and official statistics SM Tam, F Clarke Int. Stat. Rev 83, 436-448, 2015 | 10 | 2015 |
J A HarrawayUniversity of OtagoVerified email at maths.otago.ac.nz
