Confidentiality is among the main themes of SAE 2017. On the other hand, the subject field is relatively new in the context of SAE, especially from a research point of view. The main purpose of this invited session is to engage this field of increasing importance and encourage research in confidentiality and related topics in the context of SAE. In particular, we will discuss approaches from fields other traditional statistics, such as economics and computer science, and potential applications of statistical methodology research to confidentiality and related topics in SAE. The session has three speakers, including an economist, a computer scientist, and a mathematical statistician.
Small area statistics provide an important source of information used to study local trends related to social, health, and economic phenomena. However, most large-scale sample surveys, for which rigorous measures of these phenomena are collected, are not designed for purposes of producing reliable small area estimates. A further complication is that data disseminators are typically […]
Given a medical database, how does one allow access by medical researchers while preserving patient privacy? How about a similar dilemma in analysis in an employment discrimination legal case? Data privacy has been an area of active research from the 1980s to the present, in both the statistics and computer science communities. As in the machine learning case, computer scientists […]
For the last several decades, area level models have played a critical role in the theory and practice of small area estimation. The implementation of an area level model does not require confidential micro data. Aggregate statistics are modeled and thus the chance of disclosing information about a given individual is minimal. Relatively easier accessibility of aggregate statistics […]