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

Test True or False (Circle T or F)

T F 1. In a category-matched 2-to-1 case-control study,

each case is matched to two controls who are in

the same category as the case for each of the

matching factors.

T F 2. An advantage of matching over not matching is

that information may be lost when not matching.

T F 3. If we do not match on an important risk factor

for the disease, it is still possible to obtain an

unbiased estimate of the odds ratio by doing an

appropriate analysis that controls for the

important risk factor.

T F 4. McNemar’s test statistic is not appropriate when

there isR-to-1 matching andRis at least 2.

T F 5. In a matched case-control study, logistic regres-

sion can be used when it is desired to control for

variables involved in the matching as well as

variables not involved in the matching.

6. Consider the following McNemar’s table from the
   study analyzed by Donovan et al. (1984). This is a
   pair-matched case-control study, where the cases are
   babies born with genetic anomalies and controls are
   babies born without such anomalies. The matching
   variables are hospital, time period of birth, mother’s
   age, and health insurance status. The exposure
   factor is status of father (Vietnam veteran¼1 or non-
   veteran¼0):

Case

E notE

Control E 2 121

notE 125 8254

For the above data, carry out McNemar’s test for the sig-

nificance of exposure and compute the estimated odds

ratio. What are your conclusions?

7. State the logit form of the logistic model that can be
   used to analyze the study data.


8. The following printout results from using conditional
   ML estimation of an appropriate logistic model for
   analyzing the data:

95% CI for OR

Variable b sb P-value OR LU

E 0.032 0.128 0.901 1.033 0.804 1.326

424 11. Analysis of Matched Data Using Logistic Regression