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Adjusted jackknife for imputation under unequal probability sampling without replacement

Berger, 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

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To link to this item DOI: 10.1111/j.1467-9868.2006.00555.x

Abstract/Summary

Imputation 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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Biological Sciences
ID Code:10127
Uncontrolled Keywords:adjusted imputed values, consistency, finite population, inclusion, probabilities, item non-response, pseudovalues, HOT DECK IMPUTATION, VARIANCE-ESTIMATION, ESTIMATOR

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