Estimating population proportions in the presence of missing data

  • Authors:

  • E. ÁLvarez;A. Arcos;S. GonzáLez;J. F. MuñOz;M. Rueda

  • Affiliations:

  • Department of Statistics & OR, University of Jaen, Spain;Department of Statistics & OR, Faculty of Science, University of Granada, Spain;Department of Quantitative Methods for Economy and Enterprise, Spain;Department of Statistics & OR, University of Jaen, Spain;Department of Statistics & OR, Faculty of Science, University of Granada, Spain

  • Venue:
  • Journal of Computational and Applied Mathematics
  • Year:
  • 2013

Quantified Score

Hi-index 7.29

Visualization

Abstract

This paper discusses the estimation of a population proportion in the presence of missing data and using auxiliary information at the estimation stage. A general class of estimators, which make efficient use of the available information, are proposed. Some theoretical properties of the proposed estimators are analyzed, and they allow us to find the optimal value for the proposed class in the sense of minimal variance. The optimal estimator is thus more efficient than the customary estimator. Results derived from a simulation study indicate that the proposed optimal estimator gives desirable results in comparison to alternative estimators.