Recoverability and Testability of Missing Data: Introduction and Summary of Results

23 Pages Posted: 26 Oct 2013

See all articles by Judea Pearl

Judea Pearl

University of California, Los Angeles (UCLA) - Computer Science Department

Karthika Mohan

University of California, Los Angeles (UCLA)

Date Written: September 25, 2013

Abstract

Managing missing data is a problem in every experimental science. Sensors do not always work reliably, respondents do not ll out every question in the questionnaire, and medical patients are often unable to recall episodes, treatments or outcomes. The literature on this problem is huge and has resulted in a powerful software industry that makes missing data packages available through computer programs such as LISREL, M-plus and EQS. The availability of such software has engendered a culture that shares vocabulary, beliefs and expectations and uses common theoretical framework and default assumptions. Most practices are based on the seminal theoretical work of Rubin (Rubin, 1976; Little & Rubin, 2002) who have formulated procedures and conditions under which the damage of missingness can be minimized. This theory has also resulted in a number of performance guarantees when data obey certain statistical conditions. However, the theoretical guarantees provided by this theory are rather coarse, as will be shown in the discussion that follows.

Suggested Citation

Pearl, Judea and Mohan, Karthika, Recoverability and Testability of Missing Data: Introduction and Summary of Results (September 25, 2013). Available at SSRN: https://ssrn.com/abstract=2343873 or http://dx.doi.org/10.2139/ssrn.2343873

Judea Pearl (Contact Author)

University of California, Los Angeles (UCLA) - Computer Science Department ( email )

4732 Boelter Hall
Los Angeles, CA 90095
United States

HOME PAGE: http://www.cs.ucla.edu/~judea/

Karthika Mohan

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

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