Survey sampling and multiple stratifications
Title
Survey sampling and multiple stratifications
Published Date
2013-09
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Thesis or Dissertation
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.
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University of Minnesota Ph.D. dissertation. September 2013. Major: Statistics. Advisor: Glen Meeden. 1 computer file (PDF); vii, 100 pages.
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Zimmerman, Patrick Lennon Kendall. (2013). Survey sampling and multiple stratifications. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/160015.
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