Answers about Screening (con-
tinued)
Q2. Yes: It depends.
Use Method 0 if severalEs
andCs? No
Use Method 0 if oneEand
severalCs? No
Use Method 0 if onlyEs?
Yes
Questionable when model con-
sidersCs
Q3. No clear-cut rules for
“largek.”
However, need screening if
initial model does not run.
Q4. Other options for (1-at-a-
time) screening?Yes
Variations to assess
confounding or
interaction, e.g., use
stratified analysis instead
of logistic regression
Such options needed if
consideringCs
- Collinearity?
pffiPrior to screening and/or
after screening
Initial model does not run
+
Cannot obtain collinearity diagnostics
+
Start with screening
Screening completed
+
Model may still be unreliable
+
Consider collinearity diagnostics
Q2. Should the use of Method 0 depend on
types of predictors?
Yes, Method 0 makes most sense when the
model only involvesEs, i.e., no potential con-
founders (Cs) and no corresponding changes in
ORs are being considered. However, Method
0 is questionable whenever there are variables
being controlled (Cs).
Q3. How large doeskhave to be relative ton
in order to justify screening?
There are no clear-cut rules, but you will
become aware that screening should be consid-
ered if your initial model does not run (see next
section on collinearity).
Q4. Are there other ways to carry out (one-at-
a-time) screening and when, if at all, should
they be preferred to the typical approach?
There are several reasonable options for
screening, all of which are variations of ways
to assess possible confounding and/or effect
modification involving covariates. Such options
should be preferred whenever there is a mixture
ofEsandCstobeconsidered.
Q5. Where does collincarity assessment fit in
with this problem?
Collinearity may be considered prior to
screening or after screening is performed.
If your initial model does not run, typical col-
linearity diagnostics (e.g., condition indices, to
be described in the next section) cannot be
obtained, so screening must be considered
from the beginning.
Also, once screening has been performed, col-
linearity assessment may determine that
your reduced model (after screening) is still
unreliable.
Presentation: III. Screening Variables 267