A Compositional Approach to Survey Inference

• Activity Number: 522
• Type: Topic Contributed
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Survey Research Methods Section
• Author(s): J. Brick*
• Companies: Westat
• Keywords: Non-probability sampling ; variance estimation ; raking ; model diagnostics ; survey

Abstract

The ability to conduct surveys using opt-in Web respondents has raised concerns about whether these samples are valid. Probability sampling theory is not applicable because the units are not subject to being sampled with a known and non-zero probability of selection. Frameworks have been proposed for Web opt-in surveys, but these generally have features that are not well suited for general-purpose surveys. This paper proposes a model-based framework for making inferences from non-probability samples that we refer to as a compositional approach. The paper outlines the assumptions required for making inferences from these types of samples, and suggests some evaluation measures for assessing the assumptions.