Sponsors:
Connecticut ASA
Bristol Myers Squibs
Call For Papers / Registration
Third Annual ASA Connecticut Chapter Mini-Conference
Statistical Genetics / Missing Data Problems
The Connecticut Chapter of the American Statistical Association is soliciting attendees
and abstracts of presentations related to these two topics of the conference. The time
limit for contributed presentations will be 20 minutes. The attached registration form and
a non-refundable registration fee must be submitted with each abstract.
Conference site: Bristol Myers Squibs, 5 Research Parkway, Wallingford, CT
Conference Date: Saturday, March 5, 2005
Invited Speakers on Statistical Genetics:
Jun Liu, Professor, Harvard University
Hongyu Zhao, Professor, Yale University
Invited Speakers on Missing Data Problems:
Daniel Scharfstein, Associate Professor, Johns Hopkins University
Andrea Troxel, Assistant Professor, University of Pennsylvania
Naitee Ting, Associate Director, Pfizer Inc.
REGISTRATION FEE (Lunch included):
CT ASA members $30; Non-members -$35; Student $10
POSTMARK DEADLINE FOR ABSTRACT SUBMISSIONS: February 15, 2005
POSTMARK DEADLINE FOR EARLY REGISTRATION: February 25, 2005
SUBMIT REGISTRATION FORM AND/OR ABSTRACT TO:
Mingxiu Hu, CT ASA Program Chair
Pfizer Inc.
A4136, 50 Pequot Avenue
New London, Connecticut 06320
Phone: (860) 732-2118 E-Mail: ming.xiu.hu@pfizer.com
Third Annual ASA Connecticut Chapter Mini-Conference
Registration Form
POSTMARK DEADLINE FOR ABSTRACT SUBMISSIONS: February 15, 2005
Attendee’s Name: _______________________________________________________
Affiliation: ____________________________________________________________
Address: ______________________________________________________________
City, State, ZIP: ________________________________________________________
Phone Number: _________________________________________________________
E-Mail: _______________________________________________________________
Non-refundable Registration Fee: (Circle the appropriate registration fee):
REGISTRATION FEE (Lunch Included):
Before February 25: CT ASA members $30; Non-members - $35; Student $10.00
After February 25: CT ASA members $35; Non-members - $40; Student $15.00
Make checks payable to:
Connecticut Chapter: American Statistical Association
Return registration form and fee to:
Mingxiu Hu, CT ASA Program Chair
Pfizer Inc.
A4136, 50 Pequot Avenue
New London, Connecticut 06320
For further information about the conference:
Phone: (860) 732-2118
E-Mail: ming.xiu.hu@pfizer.com
Abstracts of Invited Presentations (more to come):
Statistical Methods to Dissect Biological Pathways through Integrated
Analysis of Diverse Data Sources
Dr. Hongyu Zhao, Yale University
Recent advances in large-scale RNA expression measurements, DNA-protein
interactions, protein-protein interactions and the availability of genome sequences from
many organisms have opened the opportunity for massively parallel biological data
acquisition and integrated understanding of the genetic networks underlying complex
biological phenotypes. Many existing statistical procedures have been proposed to
analyze a single data type, e.g. clustering algorithms for microarray data and motif
finding methods for sequence data. Different data sources offer different perspectives on
the same underlying system, and they can be combined to increase our ability to uncover
underlying biological mechanisms. In this talk, we will describe our attempts to develop a
statistical framework to integrate diverse genomics and proteomics information to dissect
transcriptional regulatory networks and signal transduction pathways. This is joint work
with Ning Sun, Liang Chen, Baolin Wu, Yin Liu, and Nan Lin.
Modeling Quality of Life Data with Missing Values
Dr. Andrea Troxel, University of Pennsylvania
Quality of life (QOL) data are commonly measured longitudinally in clinical trials.
Especially in oncology and other serious diseases, the full set of intended QOL
measurements can be difficult to obtain. This often leads to nonignorable missingness, in
which subjects with particularly extreme QOL values tend to be missed. Several
modeling approaches are possible in this setting; I will discuss direct nonignorable
modeling, sensitivity analysis, and an adapted frailty model for bivariate survival data.
Why do people use LOCF? Or why not?
Dr. Naitee Ting, Pfizer Inc.
Last observation carried forward (LOCF) has been a common statistical tool for handling
missing data. In the past few decades, numerous drugs were approved (by FDA,
European agency or others) based on LOCF data. Newer statistical methods are available
now to help deal with missing data. All of these methods are model based and require
assumptions. In some cases, the models can be somewhat complicated. Are these
assumptions justified? What are the assumptions used in LOCF? Should LOCF continue
to be used?