JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 304
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #311100 View Presentation
Title: The Sample Overlap Problem for Systematic Sampling
Author(s): Robert Fay*+
Companies: Westat
Keywords: Survey redesign ; dependent sampling ; permanent random numbers
Abstract:

Within the context of probability-based sampling from a finite population, a number of schemes have been studied to maximize or minimize the overlap between two sample selections while maintaining the required probabilities of selection for each. For example, in redesigning a personal-visit survey, it may be desirable to overlap the sampling of primary sampling units between the old and new designs. Optimum solutions to many overlap problems require mathematically and computationally complex approaches, but Ohlsson proposed simpler methods involving permanent random numbers applicable in some situations. Although not optimal, the methods are easily implemented and typically realize much of the gain achieved by the optimal solution. Ernst extended Ohlsson's methods for sequential methods such as Durbin/Brewer method, by a probabilistically correct retrospective assignment of permanent random numbers. This paper presents an extension of the Ernst approach when the first sample was selected by drawing more than one unit per stratum systematically and illustrates its efficiency with a simulation study.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.