CHAPTER 11
KEY TERMS
Across-subjects counterbalancing - A technique
for controlling progressive error that pools all
subjects' data together to equalize the effects of
progressive error for each condition.
Balanced Latin square - A partial counterbalancing
technique for constructing a matrix, or square, of
sequences in which each treatment condition (1)
appears only once in each position in a sequence
and (2) precedes and follows every other condition
an equal number of times.
Block randomization - A process of randomization
that first creates treatment blocks containing one
random order of the conditions in the experiment;
subjects are then assigned to fill each successive
treatment block.
Carryover effect - The persistence of the effect of a
treatment condition after the condition ends.
Complete counterbalancing A technique for
controlling progressive error using all possible
sequences that can be formed out of the treatment
conditions and using each sequence the same
number of times.
Counterbalancing - A technique for controlling
order effects by distributing progressive error
across the different treatment conditions of the
experiment; may also control carryover effects.
Fatigue effects - Changes in performance caused by
fatigue, boredom, or irritation.
Latin square counterbalancing - A partial
counterbalancing technique in which a matrix, or
square, of sequences is constructed so that each
treatment appears only once in any order
position.
Mixed design - A factorial design that combines
within-subjects and between subjects factors. Order
effects Change in subjects' performance that occurs
when a condition falls in different positions in a
sequence of treatments.
Partial counterbalancing - A technique for
controlling progressive error by using some subset of
the available sequences of treatment conditions.
Power - The chance of detecting a genuine effect of
the independent variable.
Practice effect - Change in subjects' performance
resulting from practice.
Progressive error - Changes in subjects' responses
that are caused by testing in multiple treatment
conditions; includes order effects, such as the effects
of practice or fatigue.
Randomized partial counterbalancing - The
simplest partial counterbalancing procedure in which
the experimenter randomly selects as many
sequences of treatment conditions as there are
subjects for the experiment.
Reverse counterbalancing - A technique for
controlling progressive error for each individual
subject by presenting all treatment conditions twice,
first in one order, then in the reverse order.
Subject-by-subject counterbalancing - A technique
for controlling progressive error for each individual
subject by presenting all treatment conditions more
than once.
Within-subjects design - A design in which each
subject takes part in more than one condition of the
experiment; also called a repeated-measures design.
Within-subjects factorial design - A factorial
design in which subjects receive all conditions in the
experiment.
CHAPTER 12
AB design - A design in which a baseline condition
(A) is measured first, followed by measurements
during the experimental intervention (B); there is no
return to the baseline condition.
ABA design - A design in which a baseline condition
(A) is measured first, followed by measurements
during the experimental condition (B), followed by a
return to the baseline condition (A) to verify that the
change in behavior is linked to the experimental
condition; also called a reversal design.
ABAB design - A design in which a baseline
condition (A) is measured first, followed by
measurements during a treatment condition (B),
followed by a return to the baseline condition (A) to
verify that the change in behavior is linked to the
experimental condition, followed by a return to the
treatment condition (B).
ABBA design - A design in which a baseline
condition (A) is measured first, followed by
measurements during a treatment condition (B),
followed by a return to the baseline measurement
condition (A), followed by a return to the treatment
condition (B) and a final baseline measurement
condition (A) to verify that the change in behavior is
linked to the experimental condition.
Baseline - A measure of behavior as it normally
occurs without the experimental manipulation; a
control condition used to assess the impact of the
experimental condition.
Changing criterion design - A design used to
modify behavior when the behavior cannot be
changed all at once; instead, the behavior is modified
in increments, and the criterion for success changes
as the behavior is modified.
Discrete trials design - A design that relies on
presenting and averaging across many, many
experimental trials; repeated applications result in a
reliable picture of the effects of the independent
variable.
Large N design - A design in which the behavior of
groups of subjects is compared.
Multiple baseline design - A small N design in
which a series of baselines and treatments are
compared; once established, however, a treatment is
not withdrawn.
Small N design - A design in which just one or a few
subjects are used; typically, the experimenter collects
baseline data during an initial control condition,
applies the experimental treatment, then reinstates
the original control condition to verify that changes
observed in behavior were caused by the
experimental intervention.