Composite Size Measures in Surveys of Rare or Hard-to-Reach Populations

• Activity Number: 241
• Type: Contributed
• Date/Time: Monday, August 1, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Section on Survey Research Methods
• Author(s): Frank Potter*+ and Eric Grau and John Hall
• Companies: Mathematica Policy Research, Inc. and Mathematica Policy Research, Inc. and Mathematica Policy Research, Inc.
• Keywords: hard-to-reach populations ; rare populations ; composite size measure ; complex survey design

Abstract

Rare and hard-to-reach populations pose significant challenges to the design and implementation of cost-efficient sample surveys. To find and enumerate these populations, multi-stage surveys are often used to avoid the construction of a sampling frame for the entire target population, and primary sampling units (PSUs) are selected with probability proportional to a size measure related to the population sizes in the PSUs. When multiple populations are of interest, composite size measures are used that are based on the population counts in the PSUs. Some composite size measures were described by Folsom, Potter and Williams (1987) and by Fahimi and Judkins (1991). The purpose of this paper is to discuss the advantages and disadvantages of these methods for various study populations and when to use these algorithms. We will demonstrate these size measures in surveys of students with disabilities, of persons receiving unemployment insurance compensation, and of persons in households receiving Supplemental Nutrition Assistance Program (SNAP, formerly called the Food Stamps program) payments and low income households not receiving SNAP payments.