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www.mattiheino.com
@heinonmatti
The Assumptions Which
Must Be Named
Social science in the post-replication crisis era
Slides: mattiheino.com/naming-assumptions
www.mattiheino.com
@heinonmatti
Models and simplification
Link
www.mattiheino.com
@heinonmatti
Models and simplification
“All social science research must do some violence
to reality in order to reveal simple truths.”
- (Lazer & Friedman, 2007)
Link
www.mattiheino.com
@heinonmatti
Complex adaptive systems
Great intro here!
www.mattiheino.com
@heinonmatti
Complex adaptive systems
Source
Great intro here!
www.mattiheino.com
@heinonmatti Great intro here!
Complex adaptive systems
• Emergent phenomena
• Interconnectedness
• Path dependence
• Context specificity
• Cascades
• Self-organisation
• Non-linear interactions
• Feedback loops
• Interaction-dominant causal
dynamics…
Source
Link
www.mattiheino.com
@heinonmatti
Perceiving the world
Raw reality
Simplifying assumptions
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
Raw reality
Simplifying assumptions
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
Source
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
Source
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
Source
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
www.mattiheino.com
@heinonmatti
Ergodicity
• Time average and ensemble average are equal
• Measuring a single person 1000 times = measuring 1000 people 1 time
• When a process is ergodic, generalising from group-level data to
individuals is ok!
• When non-ergodic, groups and people have different properties
 Ecological fallacy
Link for economists
Link for (social) psychologists
www.mattiheino.com
@heinonmatti
Empirical study:
• Six samples, compare within- and between individual characteristics
• Positive/negative affect
• Heart rate
• Depressive symptoms
• Means were quite close
• Individuals varied wildly in time Link
www.mattiheino.com
@heinonmatti
Stationarity
Between-individual relationships
www.mattiheino.com
@heinonmatti
Stationarity
Between
Observed average within-
individual relationships
www.mattiheino.com
@heinonmatti
Stationarity
?!Between
Observed average within-
individual relationships
www.mattiheino.com
@heinonmatti
Stationarity: Observed time-varying
relationships
BetweenWithin
www.mattiheino.com
@heinonmatti
Stationarity: Observed time-varying
relationships
Week 1
BetweenWithin
www.mattiheino.com
@heinonmatti
Stationarity: Observed time-varying
relationships
Week 1 Week 10
BetweenWithin
www.mattiheino.com
@heinonmatti
Stationarity: Observed time-varying
relationships
Week 1 Week 10 Week 17
BetweenWithin
www.mattiheino.com
@heinonmatti
Stationarity: Observed time-varying
relationships
Week 1 Week 10 Week 17
Haslbeck, J. M. B., & Waldorp, L. J. (2015).
MGM: Estimating Time-Varying Mixed
Graphical Models in High-Dimensional Data.
Link
BetweenWithin
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
”What does it mean for my
conclusions, if this assumption
is far from reality?”
www.mattiheino.com
@heinonmatti
Perceiving the world
• Draw boundaries between things
• Classify elements into types
• Constructs are different from each other
• Consider structures as unchanging
• All possible events can happen: markov
processes (no memory or hysterisis)
• Only most probable events can happen:
equilibria
• Consider processes as unchanging
• Consider components (people) as
identical and unchanging
Raw reality
Simplifying assumptions
”What does it mean for my
conclusions, if this assumption
is far from reality?”
Link
www.mattiheino.com
@heinonmatti
Thanks! Summary:
• Find out (and explicate!) the assumptions you’re making
• Investigate the extent to which they violate reality
• Triangulate with other models and methods when possible
• Always ask: “What does it mean if I’m wrong about this?”
• Next step: Learn about interaction-dominant causality
Slides: mattiheino.com/naming-assumptions
www.mattiheino.com
@heinonmatti
Link
Link

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The assumptions which must be named