Implications of Survey Sampling Design for Missing Data Imputation Reportar como inadecuado




Implications of Survey Sampling Design for Missing Data Imputation - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

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: Multiple Imputation ; Sampling Based Estimation ; Missing Data

Subject(s): Research Methods/ Statistical Methods

Issue Date: 2013-05

Publication Type: Conference Paper/ Presentation

PURL Identifier: http://purl.umn.edu/149679

Total Pages: 16

Series Statement: Paper

1870

Record appears in: Agricultural and Applied Economics Association (AAEA) > 2013 Annual Meeting, August 4-6, 2013, Washington, D.C.





Autor: Gedikoglu, Haluk ; Parcell, Joseph L.

Fuente: http://ageconsearch.umn.edu/record/149679?ln=en







Documentos relacionados