JSM Activity #260

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Activity ID:  260
* Incomplete Data in Longitudinal Studies
Date / Time / Room Sponsor Type
2:00 PM - 3:50 PM
Room: H-Morgan Suite
Biometrics Section*, Biopharmaceutical Section*, ENAR Contributed
Organizer: n/a
Chair: Mimi Kim, New York University

Many studies of chronic disease collect data at intervals over extended periods of time. Dropout, possibly nonignorable, is the Achilles heel of such studies. These talks will describe what one can do to extract valid inferences from such data.
  301406  By:  Christina  Korkontzelou 2:05 PM 08/13/2002
Accounting for Informative Dropout in Longitudinal Clinical Trials of Smoking Cessation: Application of Inverse Probability Weighting and Sensitivity Analysis

  301810  By:  Louis  Grothaus 2:20 PM 08/13/2002
Current Issues in Missing Data Analysis in Randomized Trials of Smoking Cessation Interventions

  300588  By:  Jason  Roy 2:35 PM 08/13/2002
Analysis of Multivariate Longitudinal Outcomes With Nonignorable Dropouts and Missing Covariates

  300495  By:  Steven  Shoptaw 2:50 PM 08/13/2002
Multiple Partial Imputation for Incomplete Longitudinal Data

  301111  By:  Yunrong  Ye 3:05 PM 08/13/2002
Extension of a Shared Parameter Model Applied to a QOL Analysis

  301488  By:  J. Lynn  Palmer 3:20 PM 08/13/2002
Analysis of Data Not Missing at Random in Palliative Care Studies

  301852  By:  Juwon  Song 3:35 PM 08/13/2002
Alternative Strategies for Dimension Reduction with Multivariate Incomplete Data

JSM 2002

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Revised March 2002