Title
Survey sampling and multiple stratifications
Abstract
In survey sampling, stratied random sampling and post-stratification can increase the precision of estimation. In some cases, however, there may be multiple ways to stratify a population. We present a method, based on a non-informative Bayesian approach, that uses a finite mixture model to incorporate information from each stratification into estimation. This approach works well when the response variable is categorical or discrete,and for some non-response types of problems. We provide the theoretical basis for our method, present some simulation results, discuss various extensions, and define some software that implements the method.
Description
University of Minnesota Ph.D. dissertation. September 2013. Major: Statistics. Advisor: Glen Meeden. 1 computer file (PDF); vii, 100 pages.
Suggested Citation
Zimmerman, Patrick Lennon Kendall.
(2013).
Survey sampling and multiple stratifications.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/160015.