ASA Philadelphia Spring Course: Missing Data in Longitudinal Studies

Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis

 Presented by: Mike Daniels, Dept of Statistics, University of Florida

Sponsored by: The Philadelphia Chapter of the American Statistical Association, and an award from the American Statistical Association.

Abstract: This course provides a survey of modern model-based approaches to handling dropout in longitudinal studies, and illustrates the use of newly-developed methods for sensitivity analysis and incorporation of prior information. The emphasis is on Bayesian approaches but the models and methods discussed can be implemented in non-Bayesian settings as well. The course will be roughly divided into two parts:

• Part 1 will focus on formal classification of dropout and missing data mechanisms, describe classes of models that can be used to adjust for biases caused by dropout, and the logistics of model fitting;
• Part 2 will deal with specification and fitting of models to handle non-ignorable (informative) dropout, with emphasis on the role of sensitivity analysis and informative prior distributions for encoding key assumptions.

Integrated into the course will be three case studies that illustrate many of the concepts introduced during the course. We will build on each case study to illustrate progressively more complex analyses (e.g. progressing from analysis under MAR, to analysis under MNAR, to use of informative priors and sensitivity analyses). Code for model fitting using WinBUGS software (and the R-to-WinBUGS interface) can be found on the instructor's webpage.

Location: Room 216, University of Pennsylvania School of Nursing, Claire M. Fagin Hall, 418 Curie Blvd, Philadelphia PA 19104

Directions by car/public transport here.

Assigned parking lot (#30) location here. 

Schedule: (all food/drink included in registration fee)

8:00AM to 8:30AM     Breakfast: Coffee/juice/muffins available

8:30AM to 11:30AM    Morning Session (beverages available)

11:30AM to 12:30PM  Box Lunch (select choice during registration)

12:30PM to 4:30PM    Afternoon Session (beverages available)