Suppose that the means for the treatment and no-treatment conditions are the
same. If so, which requirement of establishing
causality has not been met?
If the study does not manipulate the treatment, which requirement of
establishing causality will be difficult to meet?
If participants are not randomly assigned to condition, which requirement for
establishing causality will be almost impossible to meet?
4. Compare and
contrast how single-subject experiments and randomized experiments account for
between subject variables by studying a single subject.
Independent random assignment to be sure that irrelevant
variables vary randomly rather than systematically.
relevant environmental factors and demonstrate control of extraneous
variables by establishing a stable baseline.
2. Use tests
of statistical significance to see if it is unlikely that random factors
could account for the differences.
What arguments can you make for generalizing results from the single-subject
They often have strong generalizability, especially when
they study well understood, basic, universal processes such as perception and
reinforcement. In addition, single-n researchers often
repeat their study to establish that the same pattern occurs for several
How do the A-B design and the pretest-posttest design differ in terms of
pretest-posttest design uses more participants, does not attempt to develop a
stable baseline, and usually exerts less control over non-treatment variables.
Because the pretest-posttest researcher has not
established a stable baseline and does not exert as much control over
extraneous variables, the pretest-posttest has less internal validity than the
7. How does the single-n researcher’s A–B–A design differ from the quasi-experimenter’s reversal
time-series design in terms of
quasi-experimenter studied more participants, but did not establish a stable
baseline and did not have as much control over extraneous variables.
b. Internal validity?
The single-n researcher might have more internal
validity because of more control over extraneous variables.
Design a quasi-experiment that looks at the effects of a course on simulating
parenthood, including an assignment that involves taking care of an egg, on
changing the expectations of junior-high school students about parenting. What kind of design would you use? Why?
randomized experiment would probably be the best choice because it is (a)
feasible and (b) would have internal validity. The
next best choice would probably be a time-series design with a control group
because the control group might be able to rule out some of the history effects. A time-series design without a control group would be
better than a pretest-posttest design because it could better estimate the
effects of maturation. However, a pretest-posttest
design would be better than a nonequivalent control group design because the
nonequivalent control group is so vulnerable to selection.
An ad depicts a student who has improved his grade point average from 2.0 to
3.2 after a stint in the military. Consider Campbell
(growing up) and history (other events in the person's life) are also likely
possibilities. Instrumentation (grade inflation,
transferring to an easier school or major) is also a possibility.
According to one study, holding students back a grade harmed students. The evidence: students who had been held back a grade did
much worse in school than students who had not been held back.
a. Does this
evidence prove that holding students back harms their performance? Why or why not?
is a strong possibility that those who were held back differ in certain ways
from those who were not held back.
If you were a researcher hired by the Dept. of Education to test the assertion
that holding students back harms them, which of the designs in this chapter
would you use? Why?
A time series design would be inadequate because
dropping out could reflect some historical force (better employment
opportunities). A nonequivalent control group would
not be adequate because the groups are different to begin with. Therefore, you should use a two-group time series design. To make your “held back” group and “not held back” groups
as equivalent as possible, you might
attempt to match on key variables, such
as IQ and attendance.
hope that you could find a
district where students were held back according to some rule (scored below 50%
on a standardized test). Then, you might compare those
who were just above the cut-off (50-51%) to those who were just below (49-50%).
hope that different districts had
different cut-off points so that you could compare 50% scorers who were held
back against 50% scorers who advanced.