| Thursday August 5 held
at the Fields Institute Room 230 |
| |
Session Chair: McLeish/Cook |
| 8:45 |
Little, R. J. A.
Robust likelihood-based
analysis of multivariate data with missing values
|
| 9:30 |
Discussion |
| 9:45
|
Coffee |
| |
Session Chair: Wild |
| 10:00 |
Scott, A.
Fitting family-specific models
to retrospective family data
|
| 10:30 |
Chatterjee, N.
Missing Data Problems in
Statistical Genetics
|
| 11:00 |
Bull, S. (co-presenting with Juan Pablo Lewinger)
Missing Data in Family-Based
Genetic Association Studies
|
| 11:30 |
Cook, R. and Yi, G.
Weighted Generalized Estimating
Equations for Incomplete Clustered Longitudinal Data
|
| 12:00 |
Discussion |
|
12:15 |
Lunch |
| |
Session Chair: R. Cook
|
| 1:15 |
Stafford, J.
ICE: Iterated Conditional
Expectations
|
| 1:45 |
Thompson, M. E.
Interval censoring of event
times in the National Population Health Survey
|
| 2:15 |
Scharfstein, D.
Sensitivity Analysis for
Informatively Interval-Censored Discrete Time-to-Event Data
|
| 2:45 |
Yi, G. Y.
Median Regression Models for Longitudinal
Data with Missing Observations
|
| 3:15
|
Coffee |
| 3:30 |
Session Chair:Alan Lee
Wild, C.
Some issues of efficiency and
robustness
|
| 4:00 |
McLeish, D. L. & Struthers, C.A.
Regression with Missing Covariates:
Importance Sampling and Imputation
|
| 4:30 |
Rotnitzky, A.
Doubly-robust estimation of the area under the operating characteristic
curve in the presence of non-ignorable verification bias
|
| 5:15 |
Discussion |
|
5:30
|
Wine and Cheese at Fields
|
|
Friday August 6
|
held at the Bahen Centre, Room 1180 |
| 8:45 |
Session Chair: R.J.A. Little
Rubin, D. B.
Multiple Imputation for Item Nonresponse:
Some Current Theory and
Application to Anthrax Vaccine Experiments at CDC
|
| 9:30 |
Discussion |
| 9:45
|
Coffee |
|
Session Chair:A. Scott
|
| 10:00 |
Lawless, J.F.
Some Problems Concerning
Missing Data in Survival and Event History Analysis
|
| 10:30 |
Lee, A.
Asymptotic Efficiency Bounds in
Semi-Parametric Regression Models
|
| 11:00 |
Chen, Jinbo (NIH)
Semiparametric efficiency and
optimal estimation for missing data problems, with application
to auxiliary outcomes
|
| 11:30 |
Nan, B.
A new look at some efficiency
results for semiparametric models with missing data
|
| 12:00 |
Discussion |
| 12:15
|
Lunch |
| |
Session Chair:Grace Yi
|
| 1:30 |
Reilly, J.
Multiple Imputation and Complex
Survey Data
|
| 1:55 |
DiCesare, J.
Estimating Diffusions with
Missing Data
|
| 2:20 |
Koru-Sengul, T.
The Time-Varying Autoregressive
Model With Covariates For Analyzing Longitudinal Data With Missing
Values
|
| 2:45 |
Zhao, Y.
Maximum likelihood Methods for Regression Problems with Missing
Data
|
| 3:10 |
Karakoulas, G.
Mixture-of-Experts Classification
under Different Missing Label Mechanisms
|
| 3:35 |
Coffee |
|
Session Chair:Cook/McLeish
|
| 4:00 |
Robins, J.
Application of a Unified
Theory of Parametric, Semi , and Nonparametric Statistics Based
On Higher Dimensional Influence Functions to Coarsened at Random
Missing Data Models
|
| 4:45 |
Discussion |
| 5:30 |
Mixer and Dinner |
