Calibration-Weighting Methods for Complex Surveys

• Activity Number: 671
• Type: Topic Contributed
• Date/Time: Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Survey Research Methods Section
• Author(s): Changbao Wu*+ and Wilson Wen Lu
• Companies: University of Waterloo and Acadia University
• Keywords: regression weighting; exponential tilting; pseudo empirical likelihood; calibration; raking

Abstract

This paper provides an overview of three popular calibration weighting methods for complex surveys: (i) the regression weighting method; (ii) the exponential tilting method; and (iii) the pseudo empirical likelihood method. Computational algorithms for each of the methods are discussed, and finite sample configurations of the three types of weights are examined through simulation studies. The pseudo empirical likelihood approach to calibration is shown to have several advantages, including stable weights, efficient and reliable computational procedures, and the method can easily be used for generalized raking, a special calibration problem where auxiliary population information is in the form of known marginal totals for a contingency table.