Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Weir's 2009 report on NFL brain injuries got more attention than neurological findings published in 2005

Edin and Shaefer's book a call to action for Americans to deal with poverty

Weir says pain may underlie rise in suicide and substance-related deaths among white middle-aged Americans


MCubed opens for new round of seed funding, November 4-18

PSC News, fall 2015 now available

Barbara Anderson appointed chair of Census Scientific Advisory Committee

John Knodel honored by Thailand's Chulalongkorn University

Next Brown Bag

Monday, Dec 7 at noon, 6050 ISR-Thompson
Daniel Eisenberg, "Healthy Minds Network: Mental Health among College-Age Populations"

A multiple imputation approach to disclosure limitation for high-age individuals in longitudinal studies

Archived Abstract of Former PSC Researcher

An, D., R.J. Little, and James McNally. 2010. "A multiple imputation approach to disclosure limitation for high-age individuals in longitudinal studies." Statistics in Medicine, 29(17): 1769-1778.

Disclosure limitation is an important consideration in the release of public use data sets. It is particularly challenging for longitudinal data sets, since information about an individual accumulates with repeated measures over time. Research on disclosure limitation methods for longitudinal data has been very limited. We consider here problems created by high ages in cohort studies. Because of the risk of disclosure, ages of very old respondents can often not be released; in particular, this is a specific stipulation of the Health Insurance Portability and Accountability Act (HIPAA) for the release of health data for individuals. Top-coding of individuals beyond a certain age is a standard way of dealing with this issue, and it may be adequate for cross-sectional data, when a modest number of cases are affected. However, this approach leads to serious loss of information in longitudinal studies when individuals have been followed for many years. We propose and evaluate an alternative to top-coding for this situation based on multiple imputation (MI). This MI method is applied to a survival analysis of simulated data, and data from the Charleston Heart Study (CHS), and is shown to work well in preserving the relationship between hazard and covariates. Copyright (C) 2010 John Wiley & Sons, Ltd.

DOI:10.1002/sim.3974 (Full Text)

PMCID: PMC2910194. (Pub Med Central)

Country of focus: United States of America.

Browse | Search : All Pubs | Next