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

PSC In The News

RSS Feed icon

Levy says ACA has helped increase rates of insured, but rates still lowest among poor

Bruch reveals key decision criteria in making first cuts on dating sites

Murphy on extending health support via a smart phone and JITAI

More News

Highlights

U-M ranked #4 in USN&WR's top public universities

Frey's new report explores how the changing US electorate could shape the next 5 presidential elections, 2016 to 2032

U-M's Data Science Initiative offers expanded consulting services via CSCAR

Elizabeth Bruch promoted to Associate Professor

Next Brown Bag

Mon, Sept 19 at noon:
Paradox of Unintended Pregnancy, Jennifer Barber

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