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First Short Course on Strengthening Causal Inference in Behavioral Obesity Research

On-line Registration:    Closed    
Held On:    Mon 7/20/2015 - Fri 7/24/2015   
Location:    The University of Alabama at Birmingham
Executive Learning Center (ELC)
6th floor
1705 University Blvd, SPHB 640
Birmingham AL 35233   
Lodging Options:
(within walking distance)
    Doubletree by Hilton Hotel Birmingham
808 South 20th Street
Birmingham, AL  35205
(205) 933-9000

Residence Inn Birmingham
821 20th St S
Birmingham, AL 35205-2713
(205) 731-9595

Course Directors:   
David Allison, PhD

University of Alabama
at Birmingham    Kevin Fontaine, PhD

University of Alabama
at Birmingham     

  • Overview & Agenda
  • Speakers
  • Contact


The identification of causal relations is fundamental to a science of intervention and prevention. Obesity is a major problem for which much progress in understanding, treatment, and prevention remains to be made. Understanding which social and behavioral factors cause variations in adiposity and which other factors cause variations is vital to producing, evaluating, and selecting among intervention and prevention strategies as well as to understanding obesity’s root causes, requiring input from disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and in some cases behavioral or statistical genetics. The application of these techniques, however, does not involve routine well-known ‘cookbook’ approaches but requires understanding of underlying principles, so the investigator can tailor approaches to specific and varying situations. The nine course modules provide rigorous exposure to the key fundamental principles underlying a broad array of techniques and experience in applying those principles and techniques through guided discussion of real examples in obesity research.

Schedule of Events: [ PDF file]

Mon 7/20/2015   
8:00-8:30    Registration   
8:30- 9:00    Welcoming & Introductory remarks – Allison & Fontaine    video    
Module 1: Split Session – Introduction to Obesity OR Introduction to Basic Language, Terms, and Concepts in Statistics and Design.   
Intro to Obesity    Intro to Statistics & Design   
9:00-9:45    Intro to Terms and Measurement – W. T. Garvey    video     Intro to Statistical Inference (mainly frequentist, with a little Bayesian; covariate and propensity score adjustment, etc.) – David Redden    video    
9:45-10:00    BREAK   
10:00-10:45    Intro to Energy Balance and Laws of Thermodynamics – Diana Thomas & Emily Dhurandhar    video     Quantifying Effect and Association Size – Christopher K. Haddock    video    
10:45-11:30    Some Key Answered and Unanswered Questions – Olivia Affuso    video     Study Designs and Causal Inference – Chanelle Howe    video    
11:30-12:30    LUNCH   
Module 2: Conventional Observational Studies: Advantages, Limits, and Best Practices   
12:30-1:15    Advantages    Emily Levitan    video    
1:15-2:00    Limits I – Theory: Bias and Confounding    Dominik D. Alexander PhD, MSPH    video    
2:00- 2:15    BREAK   
2:15-3:00    Limits II – Empirical: Evidence & Cases Studies of Confirmation and Non-Confirmation of Observational Study-Generated Hypotheses    Andrew Brown    video    
3:00-4:00    Best Practices – Ethical Use, Hill’s Guidelines, Negative Controls, Meta-Analysis, Public Data Availability, etc.    Douglas Weed    Audio
4:00-5:00    Moderated Discussion and Wrap-up   

Tue 7/21/2015   
Module 3: Randomized Controlled Experiments – I   
9:00-10:00    Theory: Potential Outcomes    Dylan Small    video    
10:00-10:45    Methods for Randomization (including cluster randomization, stratified, choice of allocation ratios, adaptive, etc.)    Scarlett L. Bellamy    video    
10:45-11:15    Choice of Control Condition based on Hypothesis and Anticipated Claims    Kevin Fontaine    video    
11:15-11:30    BREAK   
11:30-12:00    Controlling for Expectancy and Non-Specific Effects    Bret Rutherford    video    
12:00-1:00    LUNCH   
Module 4: Randomized Controlled Experiments – II   
1:00-1:45    Power & Sample Size Calculation    David Todem    video    
1:45-2:30    Practical Challenges: Measurement Error, Missing Data, Assumption Violations, etc.    Diane J. Catellier    video    
2:30-2:45    BREAK   
2:45-3:45    Ethical Issues in RCEs    Jonathan Kimmelman    video    
3:45-4:15    Procedural Elements: Trial Registration, Reporting Guidelines    Evan Mayo-Wilson    video    
4:15-4:45    Large Simple Trials & Cluster Randomized Trials    J Michael Oakes    video    
4:45-5:30    Moderated Discussion and Wrap-up   
Wed 7/22/2015   
Module 5: Quasi Experiments   
9:00- 9:15    Quasi-experiments – Their Importance in Evaluating Changes That Occur    Brian Elbel    Audio Only
9:15- 10:25    Design & Analysis    William R. Shadish    video    
10:25-10:40    BREAK     
10:40-11:15    Ethical Issues    May Wang    video    
11:15-12:00    Real World Case Studies    Brian Elbel    video    
12:00-1:00    LUNCH     
Module 6: Natural Experiments   
1:00-1:45    Theory & Concepts    Kelli Komro    video    
1:45-2:15    Packet Randomized Experiments    David Allison & Greg Pavela    video    
2:15-3:00    Analysis    Luke J. Keele    video    
3:00-3:15    BREAK     
3:15-4:00    Practical and Ethical Issues in Accessing Natural Randomization    Luke J. Keele    video    
4:00-4:45    Real World Case Studies    Bisakha Sen    video    
4:45-5:30    Moderated Discussion and Wrap-up     
Thu 7/23/2015   
Module 7: Genetically Informed Designs – Unmeasured Genotype Approaches   
9:00-9:30    Adoption as Pseudo-Random Assignment to Homes and a Special Case of Packet Randomization    Kevin Fontaine & Greg Pavela    video    
9:30-10:15    Co-Twin and Sibling Control Designs    Matt McGue    video    
10:15-10:30    BREAK     
10:30-11:30    Structural Equation Modeling of Twin and Family Data to Assess Causal Effects    Michael C. Neale    video    
11:30-12:00    Study of Behavioral Phenotypes of Obesity in Children: Ethical Considerations    Tanja V. Kral    video    
12:00-1:00    LUNCH     
Module 8: Genetically Informed Designs – Measured Genotype Approaches   
1:00-1:30    Linkage and TDT Methods: Special Cases of Packet Randomization and Utility in Testing Fetal Sire Effects    David Allison    video    
1:30-2:30    Mendelian Randomization    James Dai    video    
2:30-3:15    Methodological issues in Testing for Gene by Environment or Gene by Behavior Interaction    Hemant Tiwari    video    
3:15-3:30    BREAK   
3:30-4:15    Social, behavioral, and ethical issues    Susan J. Persky    video    
4:15-4:45    Real World Case Studies - Causal Inference and Counterfactuals in Obesity Research: Obesity and the Gut Microbiome.    Andrew C Heath    video    
4:45-5:30    Moderated Discussion and Wrap-up     
Fri 7/24/2015   
Module 9: Mediating and Moderating Variables   
9:00-9:45    Conceptual Models (the mediator moderator distinction, environmental, behavioral, psychological, physiological, and molecular mediators and moderators)    Francesca Filbey    video    
9:45-10:30    Testing in General Linear Models    Amanda Fairchild    video    
10:30-10:45    BREAK     
10:45-11:30    Testing in Structural Equation Models    Michael C. Neale    video    
11:30-12:00    Real Life Examples & Ethical Issues    Jose R. Fernandez    video    
12:00-1:00    LUNCH     
Module 10: Group Roundtable Preparation, Presentation & Discussion   
1:00 - 3:00    Group Roundtable Preparation     
3:00-5:00    5 Roundtable Groups Presentations (10 minutes each) Followed by Discussion     
5:00-5:10    Closing Remarks    David Allison & Kevin Fontaine     

Contact Information:

Logistics: Richard Sarver
UAB SOPH Dean's office
Office of Energetics & Nutrition Obesity Research Center
1700 University Boulevard, LHL 434
Birmingham AL 35294-0013
Phone: (205) 975-9169

We would like to
thank our sponsors
for their support:


NIH Disclaimer:
This material is based upon work supported by the National Institutes of Health under Grant No. ( R25HL124208). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Institutes of Health.

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