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

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.