Adjusted jackknife for imputation under unequal probability sampling without replacement
Berger, Yves 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), 531-547. (doi:10.1111/j.1467-9868.2006.00555.x).
Full text not available from this repository.
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
|Digital Object Identifier (DOI):||doi:10.1111/j.1467-9868.2006.00555.x|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions :||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
|Accepted Date and Publication Date:||
|Date Deposited:||16 May 2006|
|Last Modified:||31 Mar 2016 12:01|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)