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An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart, Ph.D. Rush University Medical Center
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An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Dec 17, 2015

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Page 1: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

An Introduction to Modeling Causality with Repeated Measurement Designs:

Guest Lecture for Experimental Psychology Tulane University

11/21/13James Gerhart, Ph.D.

Rush University Medical Center

Page 2: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Agenda

• Discuss methods for assessing statistical causality1 and mechanisms of change2 in longitudinal designs – Ecological Momentary Assessment (Diary Data)– Treatment Outcome Research

Page 3: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Statistical Causality and Mechanisms of Change

• Psychologists are interested in explaining behavior and promoting socially valid changes in behavior.

• Thus, we are often interested in identifying causes of behavior.

• Philosophers continue to argue about causality.

• Today we’ll focus on a few suggested methods for estimating causality.

Page 4: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

John Stuart Mill’s Criteria

• Establish temporal precedence– Cause precedes effect

• Establish co-variation-– The cause and effect are related

• Rule out alternative explanations

Page 5: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Statistical Causality and Mechanisms of Change

• We can attempt to meet these criteria with Ecological Momentary Assessment (diary data), and treatment outcome data.

• We can attempt behavioral change more efficiently.

Page 6: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Benefits of Diary Data

• Diary studies assess multiple behaviors in the context of day-to-day life (ecologically valid)

• Repeated measurements throughout the day allows us to study changes

• Easy to use with smart phone/tablets• The structure of the data allow us to test for

temporal precedence (1), co-variation (2), and rule out some potential confounds (3).

Page 7: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Structure of Diary DataTime 1 Time 2 Time 3 Time 4 Time 5

Anger Anger Anger Anger Anger…

Pain Pain Pain Pain Pain…

Note. All data are illustrative and not from research subjects

Page 8: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Structure of Diary Data

Between subject varianceWithin subject variance

Page 9: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Structure of Diary Data-Measuring Confounds

Time 1 Time 2 Time 3 Time 4 Time 5

Anger Anger Anger Anger Anger…

Pain Pain Pain Pain Pain…

Depression Depression Depression Depression Depression

Medication Medication Medication Medication Medication

Page 10: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Missing Data

• Missing data used to preclude statistical analysis.

Page 11: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Missing Data

• Data replacement techniques have been developed so that data can be estimated and used

• Mixed Models• Data Imputation• Data should be missingat random• Data could be biased if angrier folks skip more

Page 12: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Variance Components

Between subject varianceWithin subject variance

Who is angriest? How does anger fluctuate?

Page 13: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Setting up the Diary Model

How does change in anger relate to change in later pain?

Pain = Prior Anger+Prior Pain+Time+Covariates

Reverse the Model

Anger =Prior Pain+Prior Anger+Time+Covariates

Page 14: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Mechanisms of Change

• For years psychologists have argued back and forth about theoretical orientations

• Meta-analytic research shows that for many disorders (anxiety, anger, depression, PTSD) treatments intended to work, usually do

• But psychodynamic, cognitive, and behavioral models differ drastically

Page 15: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Mechanisms of Change

• There are many explanations for the similarity of effects. – Behaviors are multiply determined

• Maybe psychodynamic treatment changes one part of distress, and behavioral changes another

– Treatments overlap on key processes• Hope, expectation of change, normalization, behavioral

activation, insight, placebo effects, unconscious learning.

• We need to measure these possibilities regularly throughout treatment.

Page 16: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Revisiting John Stuart Mill’s Criteria

• Establish temporal precedence– The mechanism should change before outcome

changes• Establish co-variation– Change in mechanism should correlate with

change in outcome• Rule out alternative explanations– Measure and analyze other potential mechanisms

of change

Page 17: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Structure of Treatment DataTime 1 Time 2 Time 3 Time 4 Time 5

Anger Anger Anger Anger Anger…

Pain Pain Pain Pain Pain…

Depression Depression Depression Depression Depression

Medication Medication Medication Medication Medication

Pain Attitudes Pain Attitudes Pain Attitudes Pain Attitudes Pain Attitudes

Hope Hope Hope Hope Hope

Mindfulness Mindfulness Mindfulness Mindfulness Mindfulness

Distraction Distraction Distraction Distraction Distraction

Page 18: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

Setting up a Mechanism Models

1. Pain = Prior Pain Attitude+Prior Pain+Time+Covariates

2. Pain = Prior Hope+Prior Pain+Time+Covariates3. Pain = Prior Mindfulness+Prior Pain+Time+Covariates4. …

Page 19: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

• Contact info:James Gerhart, Ph.D.Rush University Medical [email protected]

Page 20: An Introduction to Modeling Causality with Repeated Measurement Designs: Guest Lecture for Experimental Psychology Tulane University 11/21/13 James Gerhart,

References

• 1. Duckworth, A.L., Tsukayama, E. & May, H. (2010). Establishing causality using longitudinal hierarchical linear modeling: An illustration predicting achievement from self-control. Social psychological and personality science, 1, 311-317.

• 2. Kazdin, A.E. (2007). Mediators and mechanisms of change in psychotherapy research. Annual review of clinical psychology, 3, 1-27.