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HON 180 2010
Assignment 1 Brief Answers
1. Do Review Exercises Chapter 2 pp. 24 -26
1, 2, 4, 7, 8, 9, 11
2. Read the attached article and answer the following questions:
a. Was the study described in the article an observational or a randomized
controlled study? Briefly explain.
b. Carefully describe the treatment group and the control group in the main
study reported in this article.
c. The article mentions “previous research based on self-reporting of physical
activity has produced similar results.” Why did researchers have concerns
about research studies involving self-reporting? How did the researchers
address the concern in this study?
d. Briefly explain why Amy Zlot, a genetics researcher, said that more research
is needed to see if the results hold in other ethnic groups.
e. Describe at least one source of potential confounding in this study and
explain why it is a source of potential confounding.
Remember the definition of a confounding variable: a factor that is relevant to the
outcome of the study that the treatment and control groups differ by, other than the
treatment itself. For example, consider the true fact that “smokers have shorter life
expectancies than non-smokers.” A confounding variable is gender. Here is why.
Gender is relevant to the outcome of the study (longevity), because men in general have
shorter life-spans than women. Furthermore, the treatment and control groups (smokers
and non-smokers) differ in their gender makeup: More smokers are male than female.
Note on explanations relating to confounding variables. When the authors of our
textbook and I ask questions such as “Why did the investigators adjust for age?
education? marital status?” it is incomplete to say “Because age, education, and marital
status are potential confounding variables.” It is completely obvious that they are
potential confounding variables; to just say that they are potential confounding variable is
superficial. To receive full credit, you must explain how each variable could affect the
outcome of the study.
37 points total
1. (a) (2 points) The investigator is wrong. He is not taking into account the size of the
population of the state. Michigan in fact has twice the population of Minnesota. So in
fact Michigan has lower crime rate than Minnesota!
(b) (2 points) This statement is definitely true; the population of the US increased during
this time period, so the crime rate in fact did go down. People in the US abided the law
more. Note as in 1(a), it would be better to take the population into account by calculating
a rate from the start. Because of the increase in population the decrease is even more
dramatic than the comparison between 28000 and 22000 suggests.
2. (a) (2 points) No, we cannot conclude that American thieves prefer American cars.
What is missing from the equation is that there are far more Corvettes on the road then
Q45’s. For example in 2002, there were 33586 Corvettes sold compared to 8065 Q45’s.
Other confounding variables could be the ease with which one can steal the cars can
differ, but that is most likely a smaller effect than the availability. Both cars are rather
expensive so the difference in the value of the cars cannot account for the difference
either.
(b) (2 points) Similar to (a), there are far more 3-series BMW’s on the road than 7-series.
(c) (2 points) This statement is false. For example, a rate could be high even with a large
denominator. The rate is low because of the relationship between the numerator and the
denominator: the numerator is small compared to the denominator. However with a fixed
numerator, the number with a larger denominator will be smaller.
4. (a) (2 points) They were controlling for age and gender as possible confounders. Men
and women differ in their overall health levels and may have different responses to
smoking and stopping smoking. Similarly different age groups differ in health and could
have different responses to smoking (e.g. smoking may not affect young people as much
older people).
(b) (2 points) Many smokers give up smoking because they are sick. So recent exsmokers include a lot of sick people! A number of you mentioned the fact that exsmokers sometimes suffer from withdrawal symptoms, so they might be less healthy
because of these withdrawal symptoms. This fact may also play a role, but the dominant
one is the first one mentioned.
7. (a) (1 point) It is an observational study.
(b) (2 points) You should address all three. 1) Age. Rates of cervical cancer go up with
age while younger women use the pill more. 2) Education. Women of different education
levels have different patterns of sexual activity (frequency, number of partners,
protection, use of contraceptives) 3) Marital status. Women of different marital status
also have different patterns of sexual activity (married women have fewer partners and
have a lower rate of contraceptive use among other things).
(c) (2 points) Pill users are more active sexually than non-users and have more partners.
(d) (1 point) No, the conclusions of the study were not justified because of the
confounding discussed in part (c).
8. (2 points) There is a little over a quarter of the year between Memorial Day and Labor
Day, so if burglars were continuously active at the same level, more than 25% of the
burglaries would occur during this period. Some of you pointed out that the 25% figure
makes no direct connection between people going on vacations and burglaries (e.g.,
people go on vacations other times of the year as well). This is true, but the authors of
the book wanted you to note the fact that there is a little over a quarter of the year
between Memorial Day and Labor Day.
9. (a) (1 point) False. They failed to confirm the observational studies.
(b) (2 points) True. People who eat lots of fruits and vegetables can differ in many ways
other than the food they eat. They can have different lifestyles (e.g. different levels of
exercise) and even live in different areas (areas with cleaner air and water, better health
care).
(c) (1 point) False. Well-design randomized control studies should produce sound results
by eliminating the possibility of confounding.
11. (a) (2 points) The treatment group consists of those who finished boot camp. The
control group consists of other prisoners—including those who do not volunteer, or those
who volunteer but do not complete the program.
(b) (1 point) This is observational. The prisoners decide whether to volunteer for boot
camp and whether to stay in the program or drop out. That is the problem: those who
volunteer and stay the course might be quite different from those who volunteer but drop
out. They might differ in motivation, types of crimes committed, quality of the network
of friends and family outside of prison…
(c) (1 point) False because it is an observational study and there is the possibility for
confounding as described in part b.
2. (a) (1 point) This is observational study. The subjects themselves determined who
was in the treatment group or the control group by leading an active lifestyle or not.
(b) (2 points) The treatment group was Amish people with the gene who had very
physically active lifestyles. The control group was Amish people with the gene who did
not have very physically active lifestyles. The treatment group was not Amish who have
the gene.
(c) (1 point) They were concerned that self-reporters might overreport or underreport the
amount of physical activity they do. It is also somewhat difficult to keep track of one’s
physical activity. Researchers in this study addressed their concern by asking
participants to wear electronic monitors.
(d) (1 point) All the participants in the study (treatment and control) were Amish, so the
study is only valid (in so far as it is valid) for Amish only. There may other genes
involved which may occur with higher prevalence in the Amish community.
(e) (2 points) Note that in this case, a confounding variable will be a factor that is relevant
to begin overweight that the treatment group (high activity persons with the gene) and the
control (low activity persons with the gene) differ in. Some possibilities are age, gender,
diet. For example, the treatment and the control groups may differ in their average age.
For example there might be more young people in the physically active group (the
treatment). Young people tend by less overweight than people in their 40’s and 50’s. So
age could be a confounding factor. There might be more males on one of the groups, and
males might respond to the gene differently and have different patterns of overweight.