Statistics Seminar
| Date/Time: | Monday, 01 Apr 2013 from 4:10 pm to 5:00 pm |
|---|---|
| Location: | Snedecor 3105 |
| Cost: | Free |
| URL: | www.stat.iastate.edu |
| Contact: | Jeanette La Grange |
| Phone: | 515-294-3440 |
| Channel: | College of Liberal Arts and Sciences |
| Actions: | Download iCal/vCal | Email Reminder |
Most sample surveys are designed to provide reliable direct estimates of totals or means for the population as a whole and for subpopulations or domains with large enough sample sizes. However, direct or domain-specific estimates for domains with small sample sizes (called small areas) do not lead to acceptable precision and yet demand for small area statistics has greatly increased in recent years. As a result, it is necessary to use indirect estimates that borrow strength across related small areas through implicit or explicit linking models based on auxiliary population information such as census and administrative data. In this talk, I will focus on explicit model-based methods for constructing small area estimates and associated mean squared error estimates and confidence intervals. In particular, simple area level and unit level models with random small area effects will be used to explain estimation methods based on empirical best linear unbiased prediction, empirical Bayes and hierarchical Bayes methods. Various extensions that address the violation of underlying assumptions will be presented. Practical issues such as benchmarking will be discussed. Some recent applications will also be presented. Wayne Fuller's seminal contributions to small area estimation will be highlighted.