Jackknife variance estimator with reimputation for randomly imputed survey data

H. Saigo; R. R. Sitter

doi:10.1016/j.spl.2005.04.006

Jackknife variance estimator with reimputation for randomly imputed survey data

H. Saigo, R. R. Sitter^*

^*Corresponding author for this work

School of Political Science and Economics

Research output: Contribution to journal › Article › peer-review

Abstract

Reimputing after each deletion of a unit in the jackknife is known to lead to inconsistent variance estimators in the presence of random imputation in complex surveys. We use rescaling to adjust the reimputation and show that the resulting variance estimator performs somewhat better than the adjusted jackknife variance estimator.

Original language	English
Pages (from-to)	321-331
Number of pages	11
Journal	Statistics and Probability Letters
Volume	73
Issue number	3
DOIs	https://doi.org/10.1016/j.spl.2005.04.006
Publication status	Published - 2005 Jul 1

Keywords

Hotdeck
Ratio imputation
Regression imputation
Resampling

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2005.04.006

Cite this

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abstract = "Reimputing after each deletion of a unit in the jackknife is known to lead to inconsistent variance estimators in the presence of random imputation in complex surveys. We use rescaling to adjust the reimputation and show that the resulting variance estimator performs somewhat better than the adjusted jackknife variance estimator.",

keywords = "Hotdeck, Ratio imputation, Regression imputation, Resampling",

author = "H. Saigo and Sitter, {R. R.}",

note = "Funding Information: The first author (H.S) was supported by grants from the Japan Statistical Association. The second author (R.R.S) was supported by a grant from the Natural Sciences and Engineering Council of Canada. The authors thank Jun Shao and a referee for their helpful suggestions. ",

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AU - Sitter, R. R.

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PY - 2005/7/1

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N2 - Reimputing after each deletion of a unit in the jackknife is known to lead to inconsistent variance estimators in the presence of random imputation in complex surveys. We use rescaling to adjust the reimputation and show that the resulting variance estimator performs somewhat better than the adjusted jackknife variance estimator.

AB - Reimputing after each deletion of a unit in the jackknife is known to lead to inconsistent variance estimators in the presence of random imputation in complex surveys. We use rescaling to adjust the reimputation and show that the resulting variance estimator performs somewhat better than the adjusted jackknife variance estimator.

KW - Hotdeck

KW - Ratio imputation

KW - Regression imputation

KW - Resampling

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JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

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ER -

Jackknife variance estimator with reimputation for randomly imputed survey data

Abstract

Keywords

ASJC Scopus subject areas

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