Comparison of predictive mean matching and regression multiple imputation methods using the 2006 Family Income and Expenditure Survey (FIES)

Comparison of predictive mean matching and regression multiple imputation methods using the 2006 Family Income and Expenditure Survey (FIES)

This study used the 2006 Family Income and Expenditure Survey (FIES) data of the National Capital Region (NCR) in comparing the two multiple imputation methods predictive mean matching method and regression method. The effects of varying nonresponse rates were also investigated. The mean deviation,...

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Bibliographic Details
Main Author: Hao, Mason Francis T.
Format: text
Language:English
Published: Animo Repository 2010
Subjects:
Multiple imputation (Statistics)
Statistical matching
Regression analysis
Cost and standard of living > Philippines > Statistics
Physical Sciences and Mathematics
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/2443
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Institution: De La Salle University
Language: English
Description
Summary:This study used the 2006 Family Income and Expenditure Survey (FIES) data of the National Capital Region (NCR) in comparing the two multiple imputation methods predictive mean matching method and regression method. The effects of varying nonresponse rates were also investigated. The mean deviation, mean absolute deviation, bias, and the root mean square deviation were the criteria used in determining the better multiple imputation method. Results showed that the predictive mean matching method is better than the regression method.

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