Chapter 6
Experiments in the Real World
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Thought Question 1
Suppose you are interested in determining if drinking a glass
of red wine each day helps prevent heartburn. You recruit
40 adults age 50 and older to participate in an experiment.
You want half of them to drink a glass of red wine each day
and the other half to not do so. You ask them which they
would prefer, and 20 say they would like to drink the red
wine and the other 20 say they would not. You ask each of
them to record how many cases of heartburn they have in
the next six months. At the end of that time period, you
compare the results reported from the two groups. Give
three reasons why this is not a good experiment.
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Experiments: Some Techniques
 Double-blinding
– to control experimenter/respondent bias
 Pairing
or blocking
– to reduce a source of variability in responses
– the same or similar subjects receive each
treatment
 different
from a completely randomized design,
where all subjects are allocated at random
among all treatments
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(not) Double-Blinded:
Case Study
Mozart, Relaxation and Performance on
Spatial Tasks
(Nature, Oct. 14, 1993, p. 611)
 Variables:
– Explanatory: Relaxation condition assignment
– Response: Stanford-Binet IQ measure
 Not
double-blinded
– Participants know their treatment group
 Single-blinded
– Those measuring the IQ
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Double-Blinded:
Case Study
Quitting Smoking with Nicotine Patches
(JAMA, Feb. 23, 1994, pp. 595-600)
 Variables:
– Explanatory: Treatment assignment
– Response: Cessation of smoking (yes/no)
 Double-blinded
– Participants do not know which patch they
received
– Nor do those measuring smoking behavior
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Pairing or Blocking:
Case Study
Mozart, Relaxation and Performance on
Spatial Tasks
(Nature, Oct. 14, 1993, p. 611)
 Variables:
– Explanatory: Relaxation condition assignment
– Response: Stanford-Binet IQ measure
 Blocking
– Participants practiced all three relaxation
conditions. Each participant is a block.
– IQ’s re-measured after each relaxation period
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Pairing or Blocking:
Case Study
Quitting Smoking with Nicotine Patches
(JAMA, Feb. 23, 1994, pp. 595-600)
 Variables:
– Explanatory: Treatment assignment
– Response: Cessation of smoking (yes/no)
 Pairing?
– Cannot block: participants can only take
one treatment
– Could use a matched-pairs design
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Experiments:
Difficulties and Disasters
 Extraneous
variables
– Confounding variables (in chapter 5)
– Interacting variables
 Hawthorne,
placebo and experimenter
effects
 Refusals, nonadherers, dropouts
 Extending the results (generalizing)
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Interacting Variables

The problem:
– effect of explanatory variable on response variable
may vary over levels of other variables.

The solution:
– measure and study potential interacting variables.
does the relationship between explanatory and response
variables change for different levels of these interacting
variables?
 if so, report results for different groups defined by the levels of
the interacting variables.

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Interacting Variables:
Case Study
Quitting Smoking with Nicotine Patches
(JAMA, Feb. 23, 1994, pp. 595-600)

Researchers considered:
– smoker at home
 found
this to be an interacting variable:
Percent quitting
Nicotine
Placebo
Smoker at home
31%
20%
No smoker at home
58%
20%
– other variables: age, weight, depression
 no
interactions found
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Hawthorne, Placebo and
Experimenter Effects
 The
problem:
– people may respond differently when they
know they are part of an experiment.
 The
solution:
– use placebos, control groups, and doubleblind studies when possible.
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Hawthorne, Placebo and
Experimenter Effects :
Case Study I
1920’s Experiment by Hawthorne Works
of the Western Electric Company
 What changes in working conditions
improve productivity of workers?
– More lighting?
– Less lighting?
– Other changes?
 All
changes improved productivity!
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Hawthorne, Placebo and
Experimenter Effects :
Case Study II
Experimenter Effects in Behavioral Research
(Rosenthal, 1976, Irvington Pub., p. 410)
 Teachers
given a list of student names
– told these were students “who would show unusual
academic development.”
 IQ
was measured at end of year
– first graders on list: 15 points higher
– second graders on list: 9.5 points higher
– older: no striking difference
 Great
expectations = self-fulfilling prophecy
– students were randomly selected (did not have high IQ)
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Extending the Results
( Can We Generalize? )
 The
problem:
– lack of generalizability due to:
 unrealistic
treatments
 unnatural settings
 sample that is not representative of population
 The
solution:
– Researchers should use natural settings
with a properly chosen sample.
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Extending the Results :
Case Study
Does Aspirin Prevent Heart Attacks?
(NEJM, Jan. 28, 1988, pp. 262-264)
 Participants
were measured in their
natural setting (at home)
 Only healthy male physicians were
participants
– Results may not apply to:
 male
physical laborers
 women
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Key Concepts
 Double-Blind
Experiment
 Difficulties and Disasters
 Experimental Designs
– Completely Randomized Design
– Matched Pairs Design
– Block Design
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