Weighting adjustments are commonly applied in surveys to compensate for nonresponse and noncoverage, and to make weighted sample estimates conform to external values. Recent years have seen theoretical developments and increased use of methods that take account of substantial amounts of auxiliary information in making these adjustments. The article uses a simple example to describe such methods as cell weighting, raking, generali sed regression estimation, logistic regression weighting, mixtures of methods, and methods for restricting the range of the resultant adjustments. It also discusses how auxiliary variables may be chosen for use in the adjustments and describes some applications.