Département de Mathématiques et de Statistique, Université de Montréal, Montréal, Québec, Canada, H3C 3J7. e-mail: David.Haziza@umontreal.ca
SAMPLING AND ESTIMATION IN THE PRESENCE OF CUT-OFF SAMPLING
Article first published online: 30 AUG 2010
© 2010 Australian Statistical Publishing Association Inc.
Australian & New Zealand Journal of Statistics
Volume 52, Issue 3, pages 303–319, September 2010
How to Cite
Haziza, D., Chauvet, G. and Deville, J.-C. (2010), SAMPLING AND ESTIMATION IN THE PRESENCE OF CUT-OFF SAMPLING. Australian & New Zealand Journal of Statistics, 52: 303–319. doi: 10.1111/j.1467-842X.2010.00584.x
- Issue published online: 29 SEP 2010
- Article first published online: 30 AUG 2010
- auxiliary information;
- balanced sampling;
- cut-off sampling;
- design bias;
- model bias
Cut-off sampling consists of deliberately excluding a set of units from possible selection in a sample, for example if the contribution of the excluded units to the total is small or if the inclusion of these units in the sample involves high costs. If the characteristics of interest of the excluded units differ from those of the rest of the population, the use of naïve estimators may result in highly biased estimates. In this paper, we discuss the use of auxiliary information to reduce the bias by means of calibration and balanced sampling. We show that the use of the available auxiliary information related to both the variable of interest and the probability of being excluded enables us to reduce the potential bias. A short numerical study supports our findings.