Models and DAGs Flashcards
What is a Model?
Represents our understanding of how the world works.
- Speculations about causal relationships, correlations and sequences of events.
What are the elements of a Model?
- Signature
- Functional Relationships
- Probability Distributions
What are some challenges of Models?
- Uncertainty about the true causal model
- Difficulty writing down assumptions
What is a Signature of the Model?
Describes variables and their ranges.
What are the variables included in the Signature?
Exogenous and Endogenous
What is an Exogenous variable?
Not caused by others, can be randomly assigned (eg, treatment)
What is an Endogenous variable?
Caused by others (eg, outcomes, covariates, mediators, moderators)
What is a Functional Relationship?
How endogenous variables are produced (often the outcome variable).
What are the approaches to identifying a functional relationship?
- Structural causal models (SCMs) with DAGs
- Potential outcomes model
What is Probability Distribution?
A way to describe the likelihood or chance of different outcomes occurring for a particular event or variable. It shows how probable each outcome is, often represented by a mathematical function or a table.
What is a DAG?
Directed Acyclic Graphs represent causal relationships between variables.
What are outcome variables and what is its notation?
(Y): variables we want to understand (dependent variables)
What are treatment variables and what is its notation?
(D): variables of interest that explain outcomes (independent variables)
What are moderator variables and what is its notation?
(X2): additional causes of the outcome unrelated to the treatment
What are confounder variables and what is its notation?
(X): variables that introduce a non-causal relationship between treatment and outcome