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Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition

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  • Brownstone, David

Abstract

Modern travel-behavior surveys have become quite complex; they frequently include multiple telephone contacts, travel diaries, and customized stated preference experiments. The complexity and length of these surveys lead to pervasive problems with missing data and non-random response biases. Panel surveys, which are becoming common in transportation research, also suffer from non-random attrition biases. This paper shows how Rubin's (1987a) multiple imputation methodology provides a unified approach to alleviating these problems.

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  • Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt2zd6w6hh
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    Cited by:

    1. Carlos Madeira, 2019. "Computing population weights for the EFH survey," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(1), pages 004-026, April.

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