Abstract
Scientic hypotheses of interest often involve variables that are not available in a single survey. This is a common problem for researchers working with survey data. We propose a model-based approach to provide information about the missing variable. We use a spatial extension of the BART (Bayesian additive regression tree) model. The imputation of the missing variables and infer-ence about the relationship between two variables are obtained simultaneously as posterior inference under the proposed model. The uncertainty due to imputation is automatically accounted for. A simulation analysis and an application to data on self-perceived health status and income are presented.
Original language | English (US) |
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Pages (from-to) | 611-634 |
Number of pages | 24 |
Journal | Bayesian Analysis |
Volume | 2 |
Issue number | 3 |
DOIs | |
State | Published - 2007 |
Keywords
- Bart
- Cart
- Missing variables
- Spatial model
- Survey
ASJC Scopus subject areas
- Statistics and Probability
- Applied Mathematics