Marginal Structural Models: unbiased estimation for longitudinal studies

Erica Moodie () and D. Stephens

International Journal of Public Health, 2011, vol. 56, issue 1, 117-119

Abstract: When both time-varying confounding and mediation are present in a longitudinal setting data, Marginal Structural Models are a useful tool that provides unbiased estimates. Copyright Swiss School of Public Health 2011

Keywords: Bias; Confounding; Mediation; Longitudinal data; Marginal Structural Models; Inverse probability weighting (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1007/s00038-010-0198-4 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijphth:v:56:y:2011:i:1:p:117-119

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00038

DOI: 10.1007/s00038-010-0198-4

Access Statistics for this article

International Journal of Public Health is currently edited by Thomas Kohlmann, Nino Künzli and Andrea Madarasova Geckova

More articles in International Journal of Public Health from Springer, Swiss School of Public Health (SSPH+)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().