Student Work
Robustifying logistic regression for nonresponse -- an application to obesity
PublicWe predict finite population mean BMI nationally for children and adolescents using NHANES III survey data. There are many nonrespondents and no distributional assumption is made on BMI. As link functions for response indicators, we compare the logistic distribution and student's t mixtures. We use Metropolis samplers to fit our models. Nonrespondents are assigned cells based on propensity scores to impute BMI, and uncertainty about this process is included. Predictive inference is done using least-squares, and we make comparison with a recent method.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- 06D472M
- Advisor
- Year
- 2006
- Date created
- 2006-01-01
- Resource type
- Major
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