Observational versus experimental studies Observational study: record data on individuals without attempting to influence the responses. Experimental study: Deliberately impose a treatment on individuals and record their responses. Influential factors can be controlled. In 1992, several major medical organizations said that women should take hormones such as estrogen after menopause, because women who took hormones seemed to reduce their risk of a heart attack by 35% to 50%. By 2002, several studies concluded that hormone replacement does not reduce the risk of heart attacks. These studies had assigned women to either hormone replacement or to dummy pills. The assignment was done by a coin toss.
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Observational versus experimental studies - web.pdx.edujong/S243LSW17/Lectures/ch07.pdfrandom sample of 1,535 national adults. Using random assignment, 719 heard the question in Form
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Observational versus experimental studies
Observational study: record data on individuals without attempting to
influence the responses.
Experimental study: Deliberately impose a treatment on individuals
and record their responses. Influential factors can be controlled.
In 1992, several major medical organizations said that women should take
hormones such as estrogen after menopause, because women who took
hormones seemed to reduce their risk of a heart attack by 35% to 50%.
By 2002, several studies concluded that hormone replacement does not reduce
the risk of heart attacks. These studies had assigned women to either hormone
replacement or to dummy pills. The assignment was done by a coin toss.
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Access to medical care, lifestyle, socioeconomic status, are possible confounding variables.
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Random assignment of subjects to treatments
A 2013 Gallup study investigated how phrasing affects the opinions of Americans
regarding physician-assisted suicide. Telephone interviews were conducted with a
random sample of 1,535 national adults. Using random assignment, 719 heard the
question in Form A and 816 the one in Form B.
Form A: When a person has a disease that cannot be cured, do you think
doctors should be allowed by law to end the patient’s life by some painless
means if the patient and his or her family request it?
Form B: When a person has a disease that cannot be cured and is living in
severe pain, do you think doctors should or should not be allowed by law to
assist the patient to commit suicide if the patient requests it?
70% of those given Form A answered “should be allowed”, compared with only 51%
of those given Form B. What type of study is this?
A. Observational study.
B. Randomized experiment.
C. Neither. This is just anecdotal evidence.
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The individuals surveyed did not choose which question they heard. This was done by Gallup, using random assignment.Therefore this is a comparative randomized experiment.
Confounding
Two variables are confounded when their effects on a response
variable cannot be distinguished.
Observational studies often fail to yield clear causal conclusions,
because the explanatory variable is confounded with lurking variables.
CONFOUNDING?
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Experiments provide an opportunity for manipulating the environment and confounding variables.
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An observational study. Higher education and higher access to health care are confounded.
Population versus sample
Sample: The part of the
population we actually examine
and for which we do have data
A statistic is a number
summarizing a characteristic of
a sample.
Population: The entire group
of individuals in which we are
interested but can’t usually
assess directly
A parameter is a number
summarizing a characteristic
of the population.
Population
Sample
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Parameters are often referred to by a Greek letter, but statistics are typically labeled using English letters.
The role of randomness in sampling
How do you select the individuals/units in a sample?
Voluntary response sampling: individuals choose to be involved
Convenience sampling: ask whoever is around (mall, street) or take
the next 10 units
Probability sampling: individuals or units are randomly selected;
the sampling process is unbiased
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Biased
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Biased
Ann Landers summarizing responses of readers: 70% of
(~10,000) parents wrote in to say that having kids was not
worth it—if they had to do it over again, they wouldn’t.
But a random sample showed that 91% of parents WOULD have kids again.
What do you think explains such drastically different responses?
Would you expect very different responses on the
potential legalizing of marijuana if you asked the first
people you saw on the parking lot of a university or the
first people you saw on the parking lot of a church?
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Most letters to newspapers are written by disgruntled people. They are not representative of the population of interest (all parents).
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People you find in one location may be very different from the people you would find at a different location.
The simple random sample
A Simple Random Sample (SRS) is made of randomly selected
individuals. Each individual in the population has the same probability of
being in the sample. All possible samples of size n have the same
chance of being drawn.
How to choose an SRS?
Draw from a hat (lottery style)
Flip a coin
Use a table of published random numbers (Table A)
Use software that generates random numbers
Choosing a simple random sample with Table A
We need to select a random sample of 5 from a class of 20 students.
1) List and number all members of the population, which is the class of 20.
2) The number 20 is two digits long.
3) Parse the list of random digits into numbers that are two digits long. Here
we chose to start with line 103, for no particular reason.