Year: 2010
Type: article
Abstract: Sample survey weights represent a standard part of the survey statistician's repertoire, but they remain a mystery for many of those who work with survey data. They also pose a potential challenge for confidentiality protection. Much has been written about how to use weights in statistical analyses since the basic idea of weighted estimates|weighting units inversely proportional to their probability of selection|emerged from the classic paper by Horvitz and Thompson. Very little has been written about the effect of releasing survey weights on the confidentiality of survey data. The two topics are inextricably intertwined. This paper discusses both, largely from the model-based perspective, and explains what is claimed and/or known about the issue of confidentiality protection. The paper also provides a prescription for ways to deal with weights both for analysis and for disclosure limitation.
Author: Stephen E. Fienberg
Institution: Carnegie Mellon University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
Awards: Digital Government: Data Confidentiality, Data Quality and Data Integration For Federal Databases: Foundations to Software Prototypes, Statistical Disclosure Limitation Methods for Tabular Data, G2527852429, G5704252978, Digital Government: A Web-Based Query System for Disclosure-Limited Statistical Analysis of Confidential Data, G9000109631
OpenAlex ID: W1587894268