June 14, 2024

Workshop on Missing Data Problems
August 5-6, 2004

to be held at the Fields Institute, Toronto, Canada

Organizers: Richard Cook and Don McLeish (University of Waterloo)

Supported by The National Program on
Complex Data Structures

On line registration is now closed , please register on site.
Registration Fee is $100CDN. However, for students, postdoctoral fellows and invited speakers there is no fee.

Two days of invited lectures and contributed papers prior to the Joint Statistical Meetings

Modern data often includes some form of censorship or missing data. Data imputation is a critical component of the analysis of such data and crude methods for data imputation can lead to substantial bias in the results and the conclusions. Missing data problems are common in health research (e.g. retrospective and prospective studies), sample surveys (e.g. nonresponse), and less obvious parts of any study in which the data available is influenced by what is easy or feasible to collect. Longitudinal studies which collect data on a set of subjects repeatedly over time are subject to attrition, Subjects drop out because they move, suffer side effects from drugs, or for other often unknown reasons. Similarly in sampling, survey “nonrespondents” are often ignored, although factors related to the objectives of the study such as income may influence the completeness of a subjects response.

Problems which involved missing data have historically been dealt with using a “complete-case analysis'' which ignores the missing data and therefore biases conclusions. There have been many new computationally intensive tools developed in recent years which can be applied to these problems: likelihood and estimating function methodology, cross-validation, the bootstrap and other simulation techniques, Bayes' and multiple imputation, and the EM algorithm.

The primary goal of the workshop is to provide impetus to the development of mathematical and statistical tools for the analysis of data under various patterns of censorship and mechanisms governing missingness and data imputation. The workshop will be of interest to researchers and graduate students in many different disciplines, including biostatistics and sampling theory.

Preliminary list of Speakers

N. Breslow (Washington)
S. Bull (Toronto)
N. Chatterjee (NIH)
Jinbo Chen (NIH)
R. J. Cook (Waterloo)
J.D. Kalbfleisch (Michigan)
J.F. Lawless (Waterloo)
R.J.A. Little (Michigan)
D. L. McLeish (Waterloo)
A. Rotnitzky (Harvard)
D.B. Rubin (Harvard)
D. Sharfstein (Johns Hopkins)
A. Scott (Auckland)
C. A. Struthers (Waterloo)
M. E. Thompson (Waterloo)
C. Wild (Auckland)
G. Y. Yi (Waterloo)

Plus contributed sessions -
To submit an abstract for invited or contributed talks (deadline June 15, 2004)

Travel support

Funding support is available to cover part of the travel expenses of graduate students. If you would like to apply for a travel funds please:

1) Register for the workshop
2) Submit an abstract before June 15, 04 if you would like to give a talk
3) Copy the text below, provide responses, and send the following information to the organizers to Funding Request with "Missing Data Workshop" in the subject line.
(or and

a) Name, Institution and Graduate Program
b) Email
c) Reason for attending the workshop
d) Anticipated costs for travel and accomodation.
e) Are you planning on giving a talk?
f) Supervisor, Graduate Advisor, or other reference: Name, Telephone Number or E-mail Address
(Please have your reference send an email in support of this application to the workshop organizers by email indicating your research topic.)

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