Missing Data in Longitudinal Studies

16-17 July 2011

University of Queensland

Brisbane, Australia

 

 

Missing Data in Longitudinal Studies - Strategies for Bayesian Modeling, Sensitivity Analysis and Causal Inference

About this course:

This course provides a survey of primarily Bayesian approaches to handling missing data in longitudinal studies, and illustrates the use of newly-developed methods for model selection, sensitivity analysis, incorporation of prior information, and causal inference. 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 five parts: Part 1 course will include a brief review of models for longitudinal data and the basics of Bayesian inference; Part 2 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 and model selection and Bayesian proper  imputation; Part 3 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; Part 4 will focus on causal inference in the context of incomplete longitudinal data; Part 5 will discuss approaches for handling missing time-varying and baseline covariates. Integrated into the course will be six 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).

 

About the Instructor

Michael Daniels is Professor and Chair in the Department of Statistics at the University of Florida. Mike has published extensively in the statistical literature on methods for (incomplete) longitudinal data with articles appearing in Biometrics, Biometrika, Biostatistics, Journal of the American Statistical Association, and Statistics in Medicine and has had continuous research funding from the U.S. National Institutes of Health (NIH) since 2001. He recently completed a book, coauthored with Joe Hogan, titled "Missing Data in Longitudinal Studies: Strategies for Bayesian modeling and Sensitivity Analysis" published by Chapman & Hall/CRC Press. He has taught a graduate-level course on incomplete longitudinal data at the University of Florida several times and has given several short courses on missing data and dropout at national and international conferences and government agencies.

  

Target Audience 

• Professional statisticians working in applied environments where missing data is a key issue  and where formal, well justified approaches are needed for making informed inferences; e.g. academic centers running large clinical trials, statisticians work ing in the pharmaceutical industry,     statisticians working for regulatory agencies
• Researchers and students from statistics and related fields who are interested in the topic as an area of research. The necessary background is a working knowledge of linear and generalized linear models and basics of likelihood-based inference. This would include individuals with graduate degrees in statistics, biostatistics,  econometrics and related fields, and advanced students in programs offering these degrees.

Cost

There are separate regression costs depending upon whether the delegate is a full-time student, and a member of the Statistical Society of Australia. Registration includes a complete set of course notes, and full catering (lunch, morning and afternoon tea) throughout the workshop.

 

	Student members	Student non-members	SSAI Members	Non-members
Early Bird (before 16th June)	$AUD320	$AUD425	$AUD625	$AUD850
Regular (after 15th June)	$AUD370	$AUD475	$AUD675	$AUD900

  

 

Places are limited, so please book early to avoid disappointment!

Online registration is available here. To download a registration form, please click here.
Non-member students wishing to take advantage of the student rate need to use the hard-copy registration form and fax it together with their student id to SSAI, Fax No. 02 6251 0204.

Members need to be logged in with their username and password to take advantage of the member rates!

 

Program

To download the flyer with the program, please click here.

 

Venue

The workshop will be held at room 142, building 67 (Priestley Building) at the University of Queensland. A map of the venue can be downloaded here.

 

Accommodation

Anyone wanting to stay in student accommodation for the duration of the workshop can do so for $80 per night for bed, breakfast and dinner. To book your room, please contact John Nightingale at St John’s College at john.nightingale@stjohns.uq.edu.au.

 

Travel Expenses

Occasionally workshops have to be cancelled due to a lack of subscription. Please contact the SSAI Office before making any travel arrangements to confirm that the workshop will go ahead, because the SSAI will not be held responsible for any travel or accommodation expenses incurred due to a workshop cancellation.

 

Cancellation Policy

Cancellations received prior to 9 July 2011 will be refunded in full. Cancellations need to be accompanied by a valid credit card number and expiry date which will be used to put the refund through. After 9 July 2011 no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au.

   

Proudly organised by the
SSAI Biostatistics Section and the
ASA Friends of Australasia