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Exposure-Response Modeling
book

Exposure-Response Modeling

by Jixian Wang
July 2015
Intermediate to advanced content levelIntermediate to advanced
351 pages
10h 2m
English
Chapman and Hall/CRC
Content preview from Exposure-Response Modeling
Confounding bias and caus al inference in exposure–response modeling 243
to adjust the confounding bias. But u
i
may not be entirely confounded. It is
the component correlated to v
i
that causes bias and has to be adjusted for.
The CF method uses the IV mo de l to predict this component, then includes
its prediction to adjust the y-part model. To this end, we need to assume that
u
i
can be written as
u
i
= av
i
+ ε
i
(8.49)
where ε
i
is a ra ndom term independent of v
i
. Therefore, u
i
has two compo-
nents; av
i
is the source of confounding and the error term ε
i
is independent
of c
i
. The re lationship (8.49) holds when u
i
and v
i
are jointly normally dis-
tributed. But it
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Publisher Resources

ISBN: 9781466573215