Implications of Survey Sampling Design for Missing Data Imputation

Haluk Gedikoglu and Joe Parcell ()

No 149679, 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. from Agricultural and Applied Economics Association

Abstract: Previous studies that analyzed multiple imputation using survey data did not take into account the survey sampling design. The objective of the current study is to analyze the impact of survey sampling design missing data imputation, using multivariate multiple imputation method. The results of the current study show that multiple imputation methods result in lower standard errors for regression analysis than the regression using only complete observation. Furthermore, the standard errors for all regression coefficients are found to be higher for multiple imputation with taking into account the survey sampling design than without taking into account the survey sampling design. Hence, sampling based estimation leads to more realistic standard errors.

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Pages: 16
Date: 2013-05
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea13:149679

DOI: 10.22004/ag.econ.149679

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