Logistic Regression: A Self-learning Text, Third Edition (Statistics in the Health Sciences)

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F is a common effect ofEandD:

E

D


F


Conditioning on F creates a spur-
ious association betweenEandD

E

D


F


E


D


F


Backdoor pathE–F–Dis blocked by
common effect. No spurious asso-
ciation unless we condition on F.

Berkson’s bias:
Selecting only hospital patients
could lead to bias of A–B
association.

A

B


Hospital

Selecting volunteers could lead to
bias of X–Y association.

X

Y


Volunteers

Conditioning on a common cause can
 Remove bias
Conditioning on a common effect can
 Induce bias

This spurious association produced by condi-
tioning on a common effect can be expressed
with causal diagrams. Let F be a common
effect of the exposure (E) and disease (D) with
exposure unrelated to disease.

The second causal diagram, with the box
around F (the common effect), indicates con-
ditioning, or adjusting, on F. The dotted lines
betweenEandDwithout a causal arrow indi-
cate that a spurious association betweenEand
Dwas produced because of the conditioning on
F (i.e., within strata of F).

If we do not condition on a common effect
we may still wonder if there is a spurious asso-
ciation betweenEandDbecause of the back-
door path E–F–D. However, a backdoor path
through a common effect willnotcreate a spu-
rious association, unless we condition on that
common effect.

Joseph Berkson illustrated this bias in studies
in which selected subjects were hospitalized
patients (Berkson, 1946). If condition A and
condition B can lead to hospitalization, then
selecting only hospitalized patients can yield a
biased estimated association between A and B.

Similarly, if factors X and Y influenced volun-
teerism, then restricting the study population
to volunteers could lead to a selection bias of
the X–Y association.

We have seen that conditioning on a common
cause (a confounder) can remove bias and con-
ditioning on a common effect can induce bias.

178 6. Modeling Strategy Guidelines
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