Estimation of population mean using imputation techniques in sample surveys

G. N. Singh; Kumari Priyanka; Jong Min Kim; Sarjinder Singh

doi:10.1016/j.jkss.2009.04.002

Estimation of population mean using imputation techniques in sample surveys

G. N. Singh, Kumari Priyanka, Jong Min Kim, Sarjinder Singh

Statistics (Morris)

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

22 Scopus citations

Abstract

To deal with the problems of non-response, one-parameter classes of imputation techniques have been suggested and their corresponding point estimators have been proposed. The proposed classes of estimators include several other estimators as a particular case for different values of the parameter. A design based approach is used to compare the proposed strategy with the existing strategies. Theoretical results have been verified through simulation studies handling real data examples.

Original language	English (US)
Pages (from-to)	67-74
Number of pages	8
Journal	Journal of the Korean Statistical Society
Volume	39
Issue number	1
DOIs	https://doi.org/10.1016/j.jkss.2009.04.002
State	Published - Mar 2010

Bibliographical note

Funding Information:
The authors appreciate the free access and acknowledge the use of data from the Statistical Abstract of the United States, 1999, 2001 that are available on the internet. The authors are also grateful to the Indian School of Mines University, Dhanbad for providing the financial assistance to carry out the present work.

Keywords

Bias
Design based approach
Imputation
Mean square error
Missing data
Non-response

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10.1016/j.jkss.2009.04.002

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title = "Estimation of population mean using imputation techniques in sample surveys",

abstract = "To deal with the problems of non-response, one-parameter classes of imputation techniques have been suggested and their corresponding point estimators have been proposed. The proposed classes of estimators include several other estimators as a particular case for different values of the parameter. A design based approach is used to compare the proposed strategy with the existing strategies. Theoretical results have been verified through simulation studies handling real data examples.",

keywords = "Bias, Design based approach, Imputation, Mean square error, Missing data, Non-response",

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note = "Funding Information: The authors appreciate the free access and acknowledge the use of data from the Statistical Abstract of the United States, 1999, 2001 that are available on the internet. The authors are also grateful to the Indian School of Mines University, Dhanbad for providing the financial assistance to carry out the present work. ",

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T1 - Estimation of population mean using imputation techniques in sample surveys

AU - Singh, G. N.

AU - Priyanka, Kumari

AU - Kim, Jong Min

AU - Singh, Sarjinder

N1 - Funding Information: The authors appreciate the free access and acknowledge the use of data from the Statistical Abstract of the United States, 1999, 2001 that are available on the internet. The authors are also grateful to the Indian School of Mines University, Dhanbad for providing the financial assistance to carry out the present work.

PY - 2010/3

Y1 - 2010/3

N2 - To deal with the problems of non-response, one-parameter classes of imputation techniques have been suggested and their corresponding point estimators have been proposed. The proposed classes of estimators include several other estimators as a particular case for different values of the parameter. A design based approach is used to compare the proposed strategy with the existing strategies. Theoretical results have been verified through simulation studies handling real data examples.

AB - To deal with the problems of non-response, one-parameter classes of imputation techniques have been suggested and their corresponding point estimators have been proposed. The proposed classes of estimators include several other estimators as a particular case for different values of the parameter. A design based approach is used to compare the proposed strategy with the existing strategies. Theoretical results have been verified through simulation studies handling real data examples.

KW - Bias

KW - Design based approach

KW - Imputation

KW - Mean square error

KW - Missing data

KW - Non-response

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JO - Journal of the Korean Statistical Society

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ER -

Estimation of population mean using imputation techniques in sample surveys

Abstract

Bibliographical note

Keywords

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