Sebastien Haneuse, PhD
Assistant Investigator
Research Interests:
Dr. Haneuse is a biostatistician whose primary methodological interests are
in methods for biased sampling schemes; combining ecological- and
individual-level data; Bayesian nonparametric survival and longitudinal data
analysis; and methods relating to cancer screening. His applied work covers
areas such as breast cancer screening and Alzheimer's disease.
Contact Dr. Haneuse
Voice Mail: 206-287-2005
E-Mail:haneuse.s@ghc.org
Curriculum Vitae (CV)
View Dr.
Haneuse's CV. You'll need Adobe Reader to view the CV.
Recent Publications:
Haneuse S, Wakefield J. The combination of ecological and case-control data.
J R Stat Soc Ser B. 2008;70:73-93.
Haneuse SJ, Rudser KD, Gillen DL. The separation of timescales in
Bayesian survival modeling of the time-varying effect of a time-dependent
exposure. Biostatistics. 2007; [Epub ahead of print].
Abstract
Sonnen JA, Larson EB, Crane PK, Haneuse S, Li G, Schellenberg GD, Craft
S, Leverenz JB, Montine TJ. Pathological correlates of dementia in a
longitudinal, population-based sample of aging. Ann Neurol.
2007;62(4):406-13. Epub 2007 Aug 20.
Abstract
Haneuse S, Wakefield J. Geographic-based ecological correlation studies
using supplemental case-control data. Stat Med. 2008;27(6):864-87.
Epub 2007 Jul 11.
Abstract
Haneuse SJ, Wakefield JC. Hierarchical models for combining ecological
and case-control data. Biometrics. 2007;63(1):128-36.
Abstract
Haneuse S, Wakefield J, Sheppard L. The interpretation of exposure effect
estimates in chronic air pollution studies. Stat Med.
2007;26(16):3172-87. Epub 2007 Jan 15.
Abstract
Gordian ME, Haneuse S, Wakefield J. An investigation of the association
between traffic exposure and the diagnosis of asthma in children. J Expo
Anal Environ Epidemiol. 2006;16(1):49-55.
Abstract
Haneuse S, Wakefield J. Ecological inference incorporating spatial
dependence. In: King G, Rosen O, Tanner M, editors. Ecological Inference:
New Methodological Strategies. Cambridge: Cambridge University Press; 2004.
p 266-302.
Brumback B, Hernan M, Haneuse S, Robins J. Sensitivity analysis for
unmeasured confounding assuming a marginal structural model for repeated
measures. Stat Med. 2004;23:749-67.
Abstract
Top |
search 
