Summary Course GW4003MV Advanced Research Methods

Summary Course GW4003MV Advanced Research Methods


Workgroup session 1: DAGs

1. Re-visit the DAG language from lecture 1, the literature and the knowledge video on
DAGS. Describe the meaning of the following terms: path, backdoor path, causal
path, confounding, collider, blocking and unblocking?

Knowledge video 1: Directed Acyclic Graphs
DAG theory (I)
Directed Acyclic Graphs (DAGs) are graphical representations of the
causal structure underlying a research question:




DAG theory (II)
 DAGs help to visualize the causal structure underlying a research
question
 You need a priori theoretical/subject knowledge about the causal
structure to draw a DAG (e.g., from previous studies, literature,
common sense, ...)
 Collect data on all relevant variables
 ‘Simple’ rules can be applied to determine for which variables to
adjust in regression analysis and how to interpret the results

DAG terminology
1. Paths
2. Causal paths and backdoor paths
 avoid opening backdoor paths. Backdoor paths always need to be closed to answer your
research question in an unbiased manner. In that way you will remove the association that
runs through these paths from the association between the exposure and outcome and isolate
the association between the exposure and outcome that you are interested in. If you are
successful in that, you can draw cause and conclusions.
3. Open and closed paths, and colliders
4. Blocking open paths
5. Opening blocked path

1. Paths (I)
RQ: Influence of X on Y?

, A path is any route between exposure X and outcome Y
 Paths do not have to follow the direction of the arrows
Q: How many paths between X and Y?
A: 4 paths from X to Y
XY
XVY
XLY
XWY

1. Paths (II)
RQ: Influence of X on Y?




Answer: having data on all four paths is essential for answering the research question in an
unbiased manner.

2. Causal paths and backdoor paths (I)
RQ: Influence of X on Y?




 A causal path follows the direction of the arrows
 A backdoor path does not
Q: Which are causal or backdoor paths?
A: 2 causal paths
XY
XVY
A: 2 backdoor paths
XLY
XWY

2. Causal paths and backdoor paths (II)
RQ: Influence of X on Y?

,Answer:

3. Open and closed paths (I)
RQ: Influence of X on Y?




 All paths are open, unless they collide somewhere on a path
 A path is closed if arrows collide in one variable on that path
Q: How many paths are open and closed?
A: 3 open paths
XY
XVY
XLY
A: 1 closed path
XWY

3. Open and closed paths (II)
RQ: Influence of X on Y?




Answer:

4. Blocking open paths (I)
RQ: Influence of X on Y?

,  Open (causal or backdoor) paths transmit association
 The association between X and Y consists of
the combination of all open paths between them
 Here: all paths except X  W  Y

4. Blocking open paths (II)
RQ: Influence of X on Y?




 An open path is blocked when we adjust for a variable (L) along the
path
 This means that we remove the disruptive influence of L from the
association between X and Y
 How? By including variable L in the regression analysis
 Backdoor paths always need to be closed
 Causal paths need to be open/closed depending on RQ

5. Open blocked paths
RQ: Influence of X on Y?




 Including a collider (W) in the analysis means you open the blocked
backdoor path
 This introduces bias in the association between X and Y

Correlation does not imply causation
Correlation implies association (not causation):
- A statistical relationship between the treatment and outcome
- Knowing the value of one variable may provide information on the value of another
variable, but that does not mean that one caused the other
- Knowing that Zeus died 5 days after a heart transplant does not mean the transplant
caused Zeus’ death (Hernàn and Robins, 2020)
Causation:
- Difference between potential (i.e., counterfactual) outcomes

A statistical association equals the difference in potential outcomes if, and only if, the
identifiability conditions are met. For this, we need:
- Theory and subject knowledge (e.g., previous studies in literature)