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

8. If the study design had been case-control, what kind of
   measure of association could you have legitimately
   computed from the above models?


9. For Model 2, compute and interpret the estimated odds
   ratio for the effect of SOC, controlling for SMK and
   SBP? (Again, if you do not have a calculator, just state
   the computations that are required.)


10. Which of the following general formulae is not
    appropriate for computing the effect of SOC
    controlling for SMK and SBP inModel 1? (Circle one
    choice.) Explain your answer.
    a. exp(bS), wherebSis the coefficient of SOC in model 1.
    b. exp[~bi(X 1 iX 0 i)].
    c. P{exp[bi(X 1 iX 0 i)]}.

Test True or False (Circle T or F)

T F 1. We can use the logistic model provided all the

independent variables in the model are

continuous.

T F 2. Suppose the dependent variable for a certain

multivariable analysis is systolic blood

pressure, treated continuously. Then, a

logistic model should be used to carry out the

analysis.

T F 3. One reason for the popularity of the logistic

model is that the range of the logistic

function, from which the model is derived, lies

between 0 and 1.

T F 4. Another reason for the popularity of the logistic

model is that the shape of the logistic function

is linear.

T F 5. The logistic model describes the probability of

disease development, i.e., risk for the disease,

for a given set of independent variables.

T F 6. The study design framework within which the

logistic model is defined is a follow-up study.

T F 7. Given a fitted logistic model from case-control

data, we can estimate the disease risk for a

specific individual.

T F 8. In follow-up studies, we can use a fitted logistic

model to estimate a risk ratio comparing two

groups whenever all the independent variables

in the model are specified for both groups.

34 1. Introduction to Logistic Regression