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Activity Details

CE_07C Sat, 8/2/2014, 1:00 PM - 5:00 PM CC-160C
Calibration Weighting in Survey Sampling — Professional Development Continuing Education Course
ASA , Survey Research Methods Section
Calibration weighting involves a mild adjustment of probability-sampling weights that forces the weighted totals for a set of calibration (benchmark) variables to equal values determined using more complete information from the frame, the target population, or a larger sample. Its use can increase the efficiency of survey estimates as well as adjust for frame coverage errors and unit nonresponse. This short course is composed of three modules of increasing complexity. The first module provides a broad overview of the topic. It assumes knowledge of survey sampling at the level of Lohr's Sampling Design and Analysis. The second module discusses the roles of the linear prediction models and probability-sampling theory in calibration weighting. A treatment of optimal and pseudo-optimal calibration is followed by a discussion of double protection from potential biases due to unit nonresponse or coverage errors. The potential use of calibration weighting when nonrespondents are not missing at random is introduced. Some familiarity with derivatives and linear algebra is needed. The third module discusses large sample variance estimation for which previous exposure to asymptotics would be helpful, although concepts are stressed over rigorous proofs. A motivating example grounds the theory throughout by displaying the numerical impact of alternative approaches.
Instructor(s): Phillip Kott, RTI International

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