Frame imperfection, non-response and unequal selection probabilities always affect survey results. In order to compensate for the effects of these problems, Devill and Särndal (1992) introduced a family of estimators called calibration estimators. In these estimators we look for weights that have minimum distance with design weights based on a distance function and satisfy calibration equa...

in many statistical systems, a type of survey called “sampling over time” is common, which repeats continuously over time. one method of sampling over time is panel survey. panel survey is a method in which a “fixed sample” is contacted during different waves. the most important challenge in a panel survey is debility in providing response from some sample units and having non-response that usu...

Survey calibration (or generalized raking) estimators are a standard approach to the use of auxiliary information in survey sampling, improving on the simple Horvitz-Thompson estimator. In this paper we relate the survey calibration estimators to the semiparametric incomplete-data estimators of Robins and coworkers, and to adjustment for baseline variables in a randomized trial. The development...

We show that the model-calibration estimator for the finite population mean, which was proposed by Wu & Sitter (2001) through an intuitive argument, is optimal among a class of calibration estimators. We also present optimal calibration estimators for the finite population distribution function, the population variance, the variance of a linear estimator and other quadratic finite population fu...

In this paper, we propose the calibration procedure for the variance reduction of the stratified Warner’s randomized response estimators, which suggested by Hong et al. (1994) and Kim and Warde (2004), using auxiliary information at the population level. It is shown that the proposed calibration estimators are more efficient than the ordinary Warner’s estimators.

Calibration is commonly used in survey sampling to include auxiliary information to increase the precision of the estimates of population parameter. In this paper, we newly propose various calibration approach ratio estimators and derive the estimator of the variance of the calibration approach ratio estimators in stratified sampling. r 2006 Elsevier B.V. All rights reserved.

This paper considers the problem of linear calibration and presents two estimators arising from a synthesis of classical and inverse calibration approaches Their performance properties are analyzed employing the small error asymptotic theory Using the criteria of bias and mean squared error the proposed estimators along with the traditional classical and inverse calibration are compared Finally...

Calibration estimation, where the sampling weights are adjusted to make certain estimators match known population totals, is commonly used in survey sampling. The generalized regression estimator is an example of a calibration estimator. Given the functional form of the calibration adjustment term, we establish the asymptotic equivalence between the functional-form calibration estimator and an ...

Suppose that the Ž nite population consists of N identiŽ able units. Associated with the ith unit are the study variable, yi , and a vector of auxiliary variables, xi . The values x11 x21 : : : 1xN are known for the entire population (i.e., complete) but yi is known only if the ith unit is selected in the sample. One of the fundamental questions is how to effectively use the complete auxiliary ...