Methods proposed to solve the missing data problem in estimation procedures should consider the type of missing data, the missing data mechanism, the sampling design and the availability of auxiliary variables correlated with the process of interest. This article explores the use of geostatistical models with multiple imputation to deal with missing data in environmental surveys. The method is applied to the analysis of data generated from a probability survey to estimate Coho salmon abundance in streams located in western Oregon watersheds.
Munoz, Breda; Lesser, Virginia M.; and Smith, Ruben A.
"Applying Multiple Imputation with Geostatistical Models to Account for Item Nonresponse in Environmental Data,"
Journal of Modern Applied Statistical Methods:
1, Article 27.
Available at: http://digitalcommons.wayne.edu/jmasm/vol9/iss1/27