Abstract
Abstract Regression type estimators of a population proportion under a general sampling design and using auxiliary information are obtained. Confidence intervals based on various methods, involving auxiliary information, are also derived. An application of the proposed methods is illustrated by estimating the proportion of lakes at risk of acidification, based on data from the U.S. Environmental Protection Agency. Theoretical properties suggest that the proposed methods can outperform alternative methods, and the results derived from a Monte Carlo simulation study support this view.
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