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

(vip2019) #1

T F 9. Given a fitted logistic model from a follow-up
study, it is not possible to estimate individual
risk as the constant term cannot be estimated.


T F 10. Given a fitted logistic model from a case-
control study, an odds ratio can be estimated.
T F 11. Given a fitted logistic model from a case-
control study, we can estimate a risk ratio if
the rare disease assumption is appropriate.


T F 12. The logit transformation for the logistic model
gives the log odds ratio for the comparison of
two groups.


T F 13. The constant term,a, in the logistic model can
be interpreted as a baseline log odds for getting
the disease.


T F 14. The coefficientbiin the logistic model can be
interpreted as the change in log odds cor-
responding to a one unit change in the variable
Xithat ignores the contribution of other variables.


T F 15. We can compute an odds ratio for a fitted
logistic model by identifying two groups to be
compared in terms of the independent
variables in the fitted model.


T F 16. The product formula for the odds ratio tells us
that the joint contribution of different
independent variables to the odds ratio is
additive.
T F 17. Given a (0, 1) independent variable and a model
containing only main effect terms, the odds
ratio that describes the effect of that variable
controlling for the others in the model is given
by e to thea, whereais the constant parameter
in the model.


T F 18. Given independent variables AGE, SMK
[smoking status (0, 1)], and RACE (0, 1), in a
logistic model, an adjusted odds ratio for the
effect of SMK is given by the natural log of the
coefficient for the SMK variable.


T F 19. Given independent variables AGE, SMK, and
RACE, as before, plus the product terms SMK
RACE and SMKAGE, an adjusted odds
ratio for the effect of SMK is obtained by
exponentiating the coefficient of the SMK
variable.


T F 20. Given the independent variables AGE, SMK,
and RACE as in Question 18, but with SMK
coded as (1,1) instead of (0, 1), then e to the
coefficient of the SMK variable gives the
adjusted odds ratio for the effect of SMK.


Test 35
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