Transcript Chapter 6 - cloudfront.net

Experiments
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Observational Studies- passive data collection.
We observe, record, or measure, but we don’t
interfere.
Experiments– involve active data production.
Actively intervene by imposing some treatment in
order to see what happens.
Subjects- individuals studied in an experiment.
Treatment- any specific experimental condition
applied to the subjects. If an experiment has
several explanatory variables, a treatment is a
combination of specific values of these variables.
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Do students who take a course on the Web
learn well as those who take the same course
in a traditional classroom?
The best way to find out is to assign some
students to the classroom and others the
Web. That’s an experiment.
If students choose for themselves whether to
enroll in a classroom or in an online version
of a course. This is not an experiment.
This study simply measured their learning.
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Let’s say the students who chose the online
course had an average score on a pretest of
40.70, where as the students who chose the
classroom setting had a pretest score of
27.64.
It’s hard to compare the two when the online
students already have a head start.
The effect of the online versus the classroom
is mixed up with influences lurking in the
background.
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Lurking Variable- A variable that has an
important effect on the relationship in a study
but is not one of the explanatory variables
studied.
Confounding—two variables are confounded
when their effects on a response variable
cannot be distinguished from each other. The
confounding variable may be either
explanatory variable or lurking variables.
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In the 1990s, researchers measured the
number television sets per person x and the
life expectancy y for the world’s nations.
There was a high positive correlation: nations
with many TV sets had higher life
expectancies.
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What causes obesity in children? Inheritance from
parents, overeating, lack of physical activity, and
too much television have all been named as
explanatory variables.
The results of a study of Mexican American girls aged 9 to 12
years are typical. Measure BMI, a measure of weight relative to
height, for both the girls and their mothers. Also measure hours
of television, minutes of physical activity and intake of several
kinds of food.
Results: the girls’ BMIs were weakly correlated (r=.18) with physical activity and also with diet and
television. The strongest correlation(r=.506) was
between the BMI of the daughters and the BMI of
their mothers.
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Clinical trials- Experiments that study the
effectiveness of medical treatments on actual
patients.
Placebo- dummy treatment with no active
ingredients.
Placebo effect- many patients respond
favorably to any treatment, even a placebo.
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Ulcers seem to accompany the stress of
modern life. “Gastric freezing” is a clever
treatment for stomach ulcers. The patient
swallows a deflated balloon with tubes
attached: then a refrigerated solution is
pumped through the balloon for an hour. The
idea is that cooling the stomach will reduce
its production of acid and so relieve ulcers.
A report claimed that gastric freezing did
relieve ulcer pain.
Imposed treatment
measure response
Gastric Freezing
Reduced Pain?
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A second clinical trail was done several years
later, divided ulcer patients into two groups.
One group was treated by gastric freezing as
before, the other group received a placebo
treatment in which the solution in the balloon
was at body temperature.
Results: 34% of the 82 patients in the
treatment group improved. But so did 38% of
the 78 patients in the placebo group.
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A standard experiment on “avoidance conditioning” in rats is
as follows. The apparatus is a cage with two compartments
separated by a door. One compartment is painted white and
is lighted, while the other is black and unlighted. A rat is
placed in the black compartment, the door is opened, and a
bell rings. If the rat is still in the black compartment after 5
seconds, it is shocked through the metal door until it moves
to the white compartment. Since the rat prefers the dark, it
will not move to the white compartment until it has been
conditioned to avoid the shock. This process is repeated to
observe how many trials are required to condition the rat.
What are the subjects?
What is the treatment?
What is the response variable?
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Sickle-cell anemia is an inherited disorder of the
red blood cells. It can cause severe pain and
many complications. The National Institute of
Health carried out a clinical trial of the drug
hydroxyurea for treatment of sickle-cell anemia.
The subjects were 299 adult patients who had
had at least three episodes of pain in the
previous year. Half of the subjects received
hydroxyurea and the other half received a
placebo that looked and tasted the same. All
subjects were treated the same, therefore any
lurking variables affected both groups equally
and should not have caused any differences
between their average responses.
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The two groups must be similar in all
respects before they start taking the
medication.
Best way to avoid bias, you should draw a SRS
of the subjects. One way is to use Table B.
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Randomized comparative experiment– one
that compares just two treatments.
Control Group- the placebo group. This
allows us to control the effects of lurking
variables.
Control group does not necessarily have to
receive a placebo. Clinical trials often
compare new treatments with a treatment
that is already on the market.
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Random assignment produces groups of
subjects that should be similar in all respects
before we apply the treatments.
A proper comparative design ensures that
influences other than the experimental
treatments operate equally on all groups.
Therefore, differences in the response
variable must be due to the effects of the
treatments.
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1. Control – the effects of lurking variables on
the response.
2. Randomize-use impersonal chance to
assign subjects to treatments.
3. Use enough subjects in each group to
reduce chance variation in the results.
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Can aspirin help prevent heart attacks? The
Physicians’ Health Study, a large medical
experiment involving 22,071 male physicians,
attempted to answer this question. One randomly
selected group of 11.037 physicians took an
aspirin every second day, while the rest took a
placebo. After several years the study found that
subjects in the aspirin group had significantly
fewer heart attacks than subjects in the placebo
group.
Identify the subject
Identify the explanatory variable
Identify the response variable
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It is possible to use a computer to make
telephone calls over the internet. How will the
cost affect the behavior of users of this
service? You will offer the service to all 200
rooms in a college dorm. Some rooms will
pay a flat rate. Others will pay higher rates at
peak periods and very low rates off-peak.
You are interested in the amount and time of
use.
Outline the design of an experiment to study
the effect of rate structure.
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An observed effect so large that it would
rarely occur by chance is called Statistically
Significant. A difference so large would
almost never happen just by chance.
A randomized comparative experiment
examines whether a calcium supplement in
the diet reduces the blood pressure of
healthy men. The subjects receive either a
calcium supplement or a placebo for 12
weeks. The researchers conclude that “the
blood pressure of the calcium group was
significantly lower than that of the placebo
group.”
Explain what statistically significant means in
the context of this experiment.
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Does regular church attendance lengthen people’s
lives?
Do doctors discriminate against women in treating
heart disease?
Does talking on a cell phone while driving increase
the risk of having an accident?
We can’t randomly assign people to attend church, or
assign heart disease patients to be men or women, or
require driving while using a cell phone.
The best data we have about these and many other
cause and effect questions come from observational
studies.
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Good studies can be comparative.
We can compare random samples of people
who attend or don’t attend religious service
regularly.
We compare how doctors treat men and
women patients.
We can compare drivers on cell phones with
the same drivers when they are not on the
phone.
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To see the effects of taking a painkiller
during pregnancy, we compare women who
did so with women who did not. From a large
pool of women who did not take the drug, we
select individuals who match the drug group
in age, education, number of children and
other lurking variables. We now have two
groups that are similar in all these ways, so
that these lurking variables should not affect
our comparison of the groups.
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Comparison does not eliminate confounding.
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A good comparative study measures and
adjusts for confounding variables.
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Observational studies suggest that children
who watch many hours of television get lower
grades in school and are more likely to
commit crimes than those who watch less TV.
Explain why these studies do not show that
watching TV causes these harmful effects.
Suggest some lurking variables that may be
confounded with heavy TV viewing.
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Randomized Comparative Experiment- An
experiment that compares just two
treatments.
This also assumes all the subjects are treated
alike except for the treatments that the
experiment is designed to compare.
Any other unequal treatment can cause bias.
Does a new breakfast cereal provide good
nutrition? To find out, compare the weight
gains of young rats fed the new product and
rats fed a standard diet. The rats are
randomly assigned to diets and are housed in
large racks of cages.
 It turns out that rats in upper cages grow a
bit faster than rats in bottom cages. If the
experimenters put rats fed the new product
at the top and those fed the standard diet
below.
Would the experiment be bias?
 What could be a solution?
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Medical studies must take special care to show
that a new treatment is not just a placebo.
Part of EQUAL TREATMENT FOR ALL SUBJECTS
is to be sure that the placebo effect operates
on all subjects.
The placebo effect is so strong, it would be
foolish to tell subjects in a medical
experiment whether they are receiving a new
drug or a placebo. Knowing they are getting
“just a placebo” might weaken the placebo
effect and bias the experiment.
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There are times that even doctors or the medical
personnel should not know which treatment the
subjects are getting.
Doctors’ expectations change how they interact
with patients and even the way they diagnose a
condition, if they were to know which treatment
the subjects are receiving.
Double-blind experiment- neither the subjects
nor the people who work with them know which
treatment each subject is receiving.
Only the study’s statistician knows which
treatment the subject is receiving.
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Refusal to participate is a serious problem for
medical experiments on treatments for
serious diseases
Minorities, women, the poor and the elderly
have long been underrepresented in clinical
trials. The law now requires representation of
women and minorities. Refusal still remains a
problem with minorities.
Why do you think there is still refusal?
How can we remedy this problem?
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Non-adherers- subjects who participate but
don’t follow the experimental treatment.
Can this cause bias?
Dropouts-experiments that continue over an
extended period of time suffer from when
subject begin the experiment but do not
complete it.
Can this cause bias?
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Orlistat is a drug that may help reduce obesity by preventing
absorption of fat from the foods we eat. The drug was compared
with a placebo in a double blind randomized trial.
Researchers started with 1187 obese subjects. They gave a placebo
to all the subjects for 4 weeks and dropped the subjects who did not
take the pill regularly. There were 892 subjects left.
Researchers randomized the subjects to orlistat or a placebo, along
with a weight-loss diet. After a year 576 subjects were still
participating.
On the average, the Orlistat group lost 3.15 kg more than the
placebo group.
The study kept going for another year, at the end of the second
year, 403 subjects were left. Orlistat again beat the placebo,
reducing weight on the average of 2.25 kg.
Can we trust the results?
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We must be sure our findings are statistically
significant. They are too strong to often
occur by chance.
We need to make sure the treatment, subjects
or the environment of our experiment be
realistic.
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A psychologist wants to study the effects of
failure and frustration on the relationships
among members of a work team. She forms a
team of students, brings them to the
laboratory, and has them play a game that
requires teamwork. The game is rigged so
that they lose regularly. The psychologist
observes the students through a one-way
window, and notes the changes in their
behavior during an evening of game playing.
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Cars sold in the United States since 1986 have been required
to have a high centered brake light in addition to the usual
two brake lights at the rear of the vehicle.
This safety requirement was justified by randomized
comparative experiments with fleets of rental and business
cars. The experiments showed that the third brake light
reduced rear-end collisions by as much as 50%.
After almost a decade of actual use, The Insurance Institute
found only 5% reduction in rear-end collisions, helpful but
much less than the experiments predicted.
What happened??
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1. Divide the subjects at random into as many
groups as there are treatments.
2. Then apply each treatment to one of the
groups.
This is considered Completely Randomized
Designs.
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A fabrics researchers is studying the durability of a
fabric under repeated washing. Because durability
may depend on the water temperature and the type
of cleansing agent used, the researchers decides to
investigate the effect of these two explanatory
variables.
Variable A: water temperature with three levels: hot
(1450F), warm (1000F) and cold(500F).
Variable B: cleansing agent with three levels:
regular Tide, low-phosphate Tide, and Ivory Liquid.
The treatment consists of washing a piece of fabric
50 times in a home automatic washer.
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Interaction- combination effect between two
explanatory variables.
Ex: Washing agent and water temperature
Ex: Drugs interaction with alcohol.
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Matched Pairs Design
*compares just two treatments.
* choose pairs of subjects that are as closely
matched as possible.
* Randomly assign the two treatments to the
subjects in each pair.
*sometimes each “pair” is just one subject
who gets both treatments one after the other.
*Randomize the order of the treatments that
the subjects receives.
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Pepsi wanted to demonstrate that Coke
drinkers prefer Pepsi when they taste both
colas blind. People who said they were Coke
drinkers, tasted both colas from glasses
without brand markings and said which they
liked better.
This is an example of …
The subjects were…
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Block– a group of experimental subjects that are
know before the experiment to be similar in
some way that is expected to affect the response
to the treatments.
Block Design– the random assignment of
subjects to treatments is carried out separately
within each block.
This is a form of Control. They control the
effects of some outside variables by bringing
those variables into the experiment to form the
blocks.
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Women and men respond differently to
advertising. An experiment to compare the
effectiveness of 3 television commercials for
the same product will want to look separately
at the reactions of men and women, as well
as assess the overall response to the ads.