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 equations.

In this paper after introducing generalized regression estimator, we explain general form of calibration estimators. Then special cases of calibration estimators due to using different distance functions, practical aspects and results of comparing the methods are ... [To continue please click here]