Adjusted jackknife for imputation under unequal probability sampling without replacementBerger, Y. G. and Rao, J. N. K. (2006) Adjusted jackknife for imputation under unequal probability sampling without replacement. Journal of the Royal Statistical Society Series B-Statistical Methodology, 68 (3). pp. 531-547. ISSN 1369-7412 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1111/j.1467-9868.2006.00555.x Abstract/SummaryImputation is commonly used to compensate for item non-response in sample surveys. If we treat the imputed values as if they are true values, and then compute the variance estimates by using standard methods, such as the jackknife, we can seriously underestimate the true variances. We propose a modified jackknife variance estimator which is defined for any without-replacement unequal probability sampling design in the presence of imputation and non-negligible sampling fraction. Mean, ratio and random-imputation methods will be considered. The practical advantage of the method proposed is its breadth of applicability.
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