logit form of the logistic model that can be used to
analyze these data. (Note: Other than the variables
matched, there are no other control variables to be
considered here.)- Consider again the pair-matched case-control data
described in Exercise 10 (W¼50,X¼40, Y¼20,
Z¼100). Using conditional ML estimation, a logistic
model fitted to these data resulted in an estimated
coefficient of exposure equal to 0.693, with standard
error equal to 0.274. Using this information, compute
an estimate of the odds ratio of interest and compare
its value with the estimate obtained using the MOR
formulaX/Y. - For the same situation as in Exercise 12, compute the
Wald test for the significance of the exposure variable
and compare its squared value and test conclusion
with that obtained using McNemar’s test. - Use the information provided in Exercise 12 to com-
pute a 95% confidence interval for the odds ratio, and
interpret your result. - If unconditional ML estimation had been used instead
of conditional ML estimation, what estimate would
have been obtained for the odds ratio of interest?
Which estimation method is correct, conditional or
unconditional, for this data set?
Consider a 2-to-1 matched case-control study involving 300
bisexual males, 100 of whom are cases with positive HIV
status, with the remaining 200 being HIV negative. The
matching variables are AGE and RACE. Also, the following
additional variables are to be controlled but are not
involved in the matching: NP, the number of sexual part-
ners within the past 3 years; ASCM, the average number of
sexual contacts per month over the past 3 years, and PAR, a
(0, 1) variable indicating whether or not any sexual part-
ners in the past 5 years were in high-risk groups for HIV
infection. The exposure variable is CON, a (0, 1) variable
indicating whether the subject used consistent and correct
condom use during the past 5 years.
- Based on the above scenario, state the logit form of a
logistic model for assessing the effect of CON on HIV
acquisition, controlling for NP, ASCM, and PAR as
potential confounders and PAR as the only effect
modifier. - Using the model given in Exercise 16, give an expres-
sion for the odds ratio for the effect of CON on HIV
status, controlling for the confounding effects of AGE,
Practice Exercises 421