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It is well established in the survey sampling literature that the commonly used estimators for population parameters may be biased when based only on the sample respondents. Since the early days of the development of sampling theory various methods for compensating for this bias has been derived and implemented. These methods have ranged from ad hoc techniques to complex modeling procedures which sought to capture functional relationships between sample respondents and nonrespondents. While considerable attention has been devoted to this problem, nonresponse-related error remains one of the most prominent sources of nonsampling error affecting the quality of survey estimates. Moreover, general concern regarding the effects of nonresponse is growing as a result of a trend toward decling response rates.
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