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Statistical perspectives on confidentiality and data access in public health
Author(s) -
Fienberg Stephen E.
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.672
Subject(s) - categorical variable , confidentiality , contingency table , computer science , statistical model , relevance (law) , data science , public health , statistical inference , data access , statistical hypothesis testing , table (database) , data mining , statistics , computer security , medicine , political science , artificial intelligence , machine learning , mathematics , database , nursing , law
Confidentiality and disclosure limitation are topics that are inherently statistical but, until recently, they have received limited attention from statistical methodologists. That situation has changed considerably in the present decade. In this paper, we provide an introduction and overview of some statistical disclosure limitation issues that are of special relevance to public health studies and surveys, and the linkages to current research on bounds for multi‐dimensional contingency table entries and ‘simulated’ categorical data. We also describe how these research methods relate to a new data access query system being developed for use by NCHS and other statistical agencies. Copyright © 2001 John Wiley & Sons, Ltd.