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

PSC In The News

RSS Feed icon

Kusunoki, Hall, and Barber find obese teen girls less likely to use birth control

Prescott finds reported sex offenses lower in neighborhoods with resident sex offenders

Geronimus says poor Detroiters face greater health risks given adverse social conditions

Highlights

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Elizabeth Bruch wins ASA award for paper in mathematical sociology

Next Brown Bag

PSC Brown Bags will be back fall 2015


Data Quality in HIV/AIDS Web-Based Surveys: Handling Invalid and Suspicious Data

Publication Abstract

Bauermeister, J., E. Pingel, Martin B. Zimmerman, Mick P. Couper, A. Carballo-Dieguez, and V. Strecher. 2012. "Data Quality in HIV/AIDS Web-Based Surveys: Handling Invalid and Suspicious Data." Field Methods, 24(3): 272-291.

Invalid data may compromise data quality. We examined how decisions made to handle these data may affect the relationship between Internet use and HIV risk behaviors in a sample of young men who have sex with men (YMSM). We recorded 548 entries during the 3-month period and created six analytic groups (i.e., full sample, entries initially tagged as valid, suspicious entries, valid cases mislabeled as suspicious, fraudulent data, and total valid cases) using data quality decisions. We compared these groups on the sample's composition and their bivariate relationships. Forty-one cases were marked as invalid, affecting the statistical precision of our estimates but not the relationships between variables. Sixty-two additional cases were flagged as suspicious entries and found to contribute to the sample's diversity and observed relationships. Using our final analytic sample, we found that very conservative criteria regarding data exclusion may prevent researchers from observing true associations. We discuss the implications of data quality decisions and its implications for the design of future HIV/AIDS web surveys.

DOI:10.1177/1525822x12443097 (Full Text)

PMCID: PMC3505140. (Pub Med Central)

Browse | Search : All Pubs | Next