Home > Research . Search . Country . Browse . Small Grants

PSC In The News

RSS Feed icon

U-M is the only public and non-coastal university on Forbes' top-10 list for billionaire production

Shaefer says the details matter in child tax reform

Prescott says Michigan's restrictive sex offender law hurts social reentry

More News

Highlights

ASA President Bonilla-Silva takes exception with Chief Justice Roberts' 'gobbledygook' jab

Nobel laureate Angus Deaton, David Lam, and colleagues discuss global poverty, 10/5, 4pm

James Jackson named inaugural recipient of U-M Diversity Scholar Career Award

HomeLab grand opening

More Highlights

Next Brown Bag

Mon, Oct 23, 2017, noon: Carol Shiue, "Social Mobility in China, 1300-1800"

Martha J. Bailey photo

How Does Automated Record Linkage Affect Inferences about Population Health?

a PSC Research Project

Investigators:   Martha J. Bailey, Catherine Massey, Eytan Adar

This project compares the performance of automated linking algorithms with the goal of improving their potential. Automated linking methods are required to complete the NSF-funded Longitudinal Intergenerational Family Electronic Micro-dataset (LIFE-M), which will link millions of US vital records to historical decennial census records to create an extensive longitudinal dataset covering individuals born in the US from 1880 to 1930. This analysis emanates from that need.

The project will produce systematic evidence regarding the performance of the most popular automated linking methods in terms of match rates, representativeness of the underlying population, erroneous match rates, and systematic measurement error. It will also examine how phonetic name-cleaning methods affect quality. Significantly, the project will analyze how match quality metrics vary for different underrepresented subgroups - including women, racial/ethnic minorities, and immigrants - to determine how specific linking methods could differentially affect inferences for different populations. Finally, the project will formulate recommended practices for researchers based upon the findings.

Funding Period: 09/15/2017 to 05/31/2019

Search . Browse