Abstract
A number of applications, including claims made under Federal social welfare programs, audits conducted to verify corporate financial conditions, and audit inspections of critical medical products, require retrospective sampling over multiple time periods. A key characteristic of such samples may be that population members will appear in multiple time periods. When this occurs, and when the marginal cost of obtaining multiperiod information is minimum for a member appearing in the sample of the period being actually sampled, then a method which is herein called progressive random sampling (PRS) may be applied. Such a method, which uses information from early samples to reduce the sampling variability of later samples, thereby either improving sampling estimates for a given sample size or allowing effective reductions in sample sizes, is developed in this paper. As an illustration, an example application is included to demonstrate the PRS method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
