Neural Network Imputation: an Experience with the National Resources Inventory Survey

• Activity Number: 185
• Type: Topic Contributed
• Date/Time: Monday, August 7, 2006 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Tapabrata Maiti*+
• Companies: Iowa State University

Abstract

Imputation is needed in almost all major surveys. In large-scale national surveys, different groups of people work on different stages of the surveys. Often, the statistical estimation group has little or insufficient communication with the other groups. In such situations, hotdeck type of imputation is difficult to apply. On the other hand, because of the complex nature of the survey, finding a suitable model may not be easy and thus a nonparametric method---such as neural network imputation---seems reasonable. One such national survey is the U.S. Department of Agriculture's National Resources Inventory Survey (NRI). By design, the survey has a lot of missing values, and the missing values are imputed using a donor-based method. This article develops a neural network imputation model and compares it with the results of the existing imputation method. The end result looks promising.