BCIG TUTORIAL:
"Appropriate Use of Statistics for Big-Data Projects"
- view the seminar archive
Clinical
Center (Building 10) Medical Board Room (Room 2C116)
DESCRIPTION: Learn where
big-data projects such as fMRI, proteomics, and
microarray, can go astray from the statistical and study
design assumptions in ways that can impede accurate
interpretation of their resulting data. How can you
ensure the numerical processing of your data does not
hurt the interpretability of its final outcome? Analysis
tools cannot compensate for any and all study
irregularities. Big-data usually costs big money, so
make sure the data you get not only fills drive space
but also can be analyzed to give you real answers to
your real questions!
REGISTRATION: As with all BCIG
events, registration is not required. Just show up
happy.
WEBCASTING: This event will be
web cast live and be made available for post program
viewing on the BCIG web site (www.nih-bcig.org).
To get more information about our webcasting service,
please contact Meeting Master Carl Leonard by e-mail:
cleonard@lired.com
or by calling him on 301-496-0191. NIH CONTACT: Jim
DeLeo, 301-496-3848,
jdeleo@nih.gov
REFRESHMENTS: Bring refreshments
if you would like. There is an open cafeteria near the
meeting room.
BCIG WEB SITE:
www.nih-bcig.org
NIH VISITOR INFORMATION:
http://www.nih.gov/about/visitor/
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3:00 - 4:30 pm May 11, 2006
Laura Lee Johnson, Ph.D.
National Center for Complementary and Alternative
Medicine
INSTRUCTOR: Laura Lee
Johnson graduated with a BA in mathematics from the
University of Virginia and a Ph.D. in biostatistics
from the University of Washington's School of Public
Health and Community Medicine. She was a pre-doctoral
trainee at the Northwest Veterans Affairs Health
Services Research and Development Center of Excellence
in Seattle and a Presidential Fellow in the Department
of Biostatistics at the University of Washington where
she taught biostatistics to clinical fellows. She has
helped lead the biostatistics core in the Cancer
Prevention Studies Branch in the Center for Cancer
Research at the National Cancer Institute. She now
works as a statistician for the NIH National Center
for Complementary and Alternative Medicine. Her
research interests include analysis of biomarker data,
statistical methodology for non-parametric joint
modeling of longitudinal and survival data, and
longitudinal crossover designs.
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