Dr Robert Clark is an Associate Professor in the Statistical Consulting Unit. He has extensive experience in sample surveys, statistical ecology, and applied statistics, both in research and in significant consulting projects. He has been a statistical consultant, researcher and teacher for over 25 years, including leadership roles in the Australian Bureau of Statistics, the University of Wollongong (UOW) and the ANU.
Robert is an Accredited Statistician, and an Elected Member of the International Statistical Institute. He has been an invited speaker at conferences held by the Australian, Canadian and American Statistical Associations, and he delivered the 2011 Ken Foreman lecture for the Statistical Society of Australia. He has been an associate editor for four journals including the Journal of the Royal Statistical Society Series A. He holds degrees from the University of Queensland, ANU and UOW.
Academic outputs include a major textbook on model-based survey sampling, 21 peer-reviewed journal articles and two book chapters. Robert has attracted substantial research income in major contracts and grants including an ARC linkage grant, a Statistics New Zealand (NZ) official statistics research grant, and research projects for the a variety of Australian and NZ organisations.
Clark, R. G., & Barr, M. (2017). A blended link approach to relative risk regression. Statistical Methods in Medical Research, 0962280217698174. DOI: 10.1177/0962280217698174
Clark, R.G. and Barr, M. (2017). A blended link approach to relative risk regression. Statistical Methods in Medical Research. Accepted for publication 4/2/2017.
Au, J., Youngentob, K.N., Clark, R.G., Phillips, R. and Foley, W.J. (2017). Bark chewing reveals a nutrient limitation of leaves for a specialist folivore. Journal of Mammalogy. Accepted for publication 18/12/2016.
Clark, R.G., Kokic, P. and Smith, P.A. (2017). A comparison of two robust estimation methods for business surveys. International Statistical Review, forthcoming.
Clark, R.G. (2016). Statistical efficiency in distance sampling. PLoS One 11(3): e0149298. doi:10.1371/journal.pone.0149298.
Molefe, W. and Clark, R.G. (2015). Model-assisted optimal allocation for planned domains using composite estimation. Survey Methodology, 41(2), pp. 377-387.
Molefe, W., Shangodoyin, D. and Clark, R.G. (2015). An approximation to the optimal subsample allocation for small areas. Statistics in Transition, 16(2), pp. 163-182.
Lago, L.P. and Clark, R.G. (2015). Imputation of household survey data using linear mixed models. Australian and New Zealand Journal of Statistics 57(2), pp.169-187.
Steel, D.G. and Clark, R.G. (2014). Potential gains from using unit level cost information in a model-assisted framework. Survey Methodology, 40(2), pp.231-242.
Clark, R.G., Templeton, R. and McNicholas, A. (2013). Developing the design of a continuous national health survey for New Zealand. Population Health Metrics, 11:25.
Clark, R.G. (2013). Sample design using imperfect design data. Journal of Survey Statistics and Methodology, 1(1), pp.6-23.
Steel, D. G. & Clark, R.G. (2011). Conditional and unconditional models in model-assisted estimation of finite population totals. Pakistan Journal of Statistics, 27 (4), 529-541.
Clark, R.G. and Allingham, S. (2011). Robust resampling confidence intervals for empirical variograms. Mathematical Geosciences, 43 (2), pp.529-541.
Thomas, A. O., Milham, P. J., Morrison, R. J., Clark, R. G. & Alvarez, R. (2011). Oxygen exchange during the reaction of POCl3 and water. Australian Journal of Chemistry, 64 (10), 1360-1365.
Alzoubi, L., Clark, R.G. and Steel, D.G. (2010). Adaptive Inference for Multi-Stage Survey Data. Communications in Statistics: Simulation and Computation, vol. 39, no. 7, pp. 1334-1350.
Clark, R.G. (2009). Sampling of subpopulations in two stage surveys. Statistics in Medicine, Vol. 28, Issue 29, pp. 3697-3717.
Clark, R.G. and Chambers, R.L. (2008). Adaptive calibration for prediction of finite population totals. Survey Methodology, vol. 34, no. 2, pp. 163-172.
Clark, R.G. and Strevens, T.C. (2008). Design and analysis of clustered, unmatched resource selection studies. Journal of the Royal Statistical Society Series C, vol. 57, no. 5, pp. 535-551.
Steel, D.G. and Clark, R.G. (2007). Person-level and household-level regression estimation in household surveys. Survey Methodology vol. 33, pp.51-60.
Clark, R.G. and Steel, D.G. (2007). Sampling within households in household surveys. Journal of the Royal Statistical Society Series A, vol. 170, part 1, pp. 63-82.
Clark, R.G. and Steel, D.G. (2002). The use of households as sampling units. International Statistical Review vol. 70, no.2, pp. 289-314.
Clark, R.G. and Steel, D.G. (2000). Optimal allocation to strata and stages with simple additional constraints. The Statistician vol. 49, pp.197-207.
Smyth, G.K, Chakraborty, S., Clark, R.G. and Pettit, A.N. (1992). A stochastic model for anthracnose development in stylosanthes scabra. Phytopathology 82: 1267-1272.
Clark, R.G. and Templeton, R.T. (2014). Sampling the Māori Population using Proxy Screening, the Electoral Roll and Disproportionate Sampling in the New Zealand Health Survey. Chapter 22 of Hard to Survey Populations, Cambridge University Press: Cambridge.
Chambers, R.L. and Clark, R.G. (2012). An Introduction to Model-Based Survey Sampling. Oxford University Press: Oxford.