Chapter 12: Quasi-Experimental
Designs
• When researchers can not manipulate the
independent variable, rather it is a grouping
variable (gender, age, disability) and equivalence
between the groups can not ensured
• Researchers can not randomly assign
participants to groups thus lack control over
extraneous variables
• Quasi-independent variable: is not a true
independent variable but usually occurs naturally
or can not be manipulated.
• Researchers still look for effect of the quasiindependent variable.
• Quasi-experimental designs usually have lower
internal validity than true experiments.
Types of Quasi-Experimental Designs
Pretest-Postest designs
• Test participants before an after the quasiindependent variable
One group: measure participants before and after
the quasi-independent variable. Only have one
group of participants (those that experienced the
quasi-independent variable)
• Test reading before children at school X start
reading program and then test their reading after
they finish the reading program.
• O1 X O2
Threats to internal validity
• Maturation: students may have matured over the
reading program. They may be better at reading
just because of time and not due to the program.
• History Effects: something other than the
independent variable may have occurred between
the pretest and posttest.
• Pretest sensitization: taking the pretest may
change the participants reaction to the posttest.
• Regression to the mean: Tendency for extreme
scores on pretest to regress (move towards) the
mean on a subsequent test (posttest).
• If participants are selected because they have
extreme scores on the pretest (e.g. select a school
with very poor reading ability) there may be other
factors due to measurement error that resulted in
such low scores at the pretest (tired, bad day etc.)
that may have slightly deflated their scores.
• Measurement error causes extreme scores to be
biased in the extreme direction (away form the
mean).
• So when you test them a second time it is unlikely
that you will have those same factors that may
have deflated their scores and their scores will
increase a bit and make it look like the program is
have an effect.
Reading Skills Before and After New Reading
Program
Mean Reading Score
60
50
40
30
20
10
0
Before
After
Nonequivalent Control Group Design:
• We cannot randomly assign participants to control
and study group, so we select a control group that
is similar to the group that gets the quasiindependent variable.
Posttest-only: measure both groups after one group
has received the treatment.
• Measure reading in School A and School B after
School A has participated in the reading program.
Quasi-experimental group
X O
Nonequivalent control group
-- O
• Selection bias: we do not know whether the two
groups were similar before the intervention
Pretest-Posttest design: Test both groups before
one group gets the intervention, then test both
groups again after one group gets the
intervention (quasi-independent variable)
Quasi-experimental group
O1 X O2
Nonequivalent control group O1 -- O2
• Allows researchers to see if the two groups
scored similarly on the dependent variable
before the introduction of the treatment.
• To determine if the quasi-independent variable
had an effect you want scores to change
between pretest and posttest ONLY for the
Quasi-experimental group and NOT for the
Nonequivalent control group.
Time Series Designs
• Measure the dependent variable many times
before and after the quasi-independent variable is
introduced.
Simple interrupted time series design
• Researchers make a series of observations of the
dependent variable before and after the treatment
is introduced.
O1 O2 O3 O4 X O5 O6 O7 O8
• Evidence for a treatment effect occurs when there
are abrupt changes in the time-series data at the
time the treatment was implemented.
Percentage of cavities after the introduction of
fluoride into toothpaste in 1970
30
25
20
15
10
5
0
1970
1971
Percentage of cavities after the introduction of
fluoride into toothpaste in 1970
35
30
25
20
15
10
5
0
1967
1968
1969
1970
1971
1972
1973
Percentage of cavities after the introduction of
fluoride into toothpaste in 1970
35
30
25
20
15
10
5
0
1967
1968
1969
1970
1971
1972
1973
• This design helps to distinguish changes due to
maturation from the quasi-independent variable
• Contemporary History: Observed effect could still
be due to another event that occurred at the
same time as the quasi-independent variable
• Perhaps the electric toothbrush was introduced in
1970, or there was a major TV add campaign that
promoted brushing teeth.
Interrupted time series with a reversal
• Researchers measures the dependent variable
before and after the treatment is introduced and
then again after the treatment is removed
O1 O2 O3 O4 X O5 O6 O7 O8 -X O9 O10 O11
• We can see what happens to the dependent
variable after the quasi independent variable is
introduced and then again after it is removed.
• If the quasi-independent variable was really having
an effect we would expect performance to change
back to normal after it is removed
Percentage of cavities after the introduction of
fluoride into toothpaste in 1970
35
30
25
20
15
10
5
0
1968
1969
1970
1971
1972
1973
Limitations:
• Researchers may not have the ability to remove
the quasi-independent variable
• remove fluoride from toothpaste, remove a seatbelt
law
• Some effects of the quasi-independent variable
may remain even after it is removed
• If you did a time series study before and after
introduction of reading program, and then removed
program, reading may not decrease, the children may
not regress because they did learn to read.
• Removal of the quasi-independent variable may
produce effects that are not due to the quasiindependent variable
Control Group Interrupted time series
• Measure more than one group on several
occasions, but only one group receives the quasiindependent variable.
O1 O2 O3 O4 X O5 O6 O7 O8
O1 O2 O3 O4 -- O5 O6 O7 O8
• Helps to rule out history effects, and we can be
more certain the a change was due to X rather
than an outside influence.
• Could still have a local history effect.
Longitudinal Designs
• Time serves as the quasi-independent variable
• Commonly used in developmental research
• Allows researchers to eliminate generational
effects (when effects differ depending on the era
in which people grew up). In longitudinal
research you are studying people of the same
generation over time.
O1 O2 O3 O4 O5 O6 O7 O8
• Allows researchers to examine how individuals
change with age (not just group differences).
Limitations:
• Difficult to obtain samples who are willing to be
repeatedly tested over time.
• Difficult to keep track of participants over time
(attrition may occur).
• Takes a lot of time and money.
Program Evaluation
• Used to assess effectiveness of interventions (or
programs) and provide feedback to the
administrators
• Assess needs, process, outcome, and efficiency
of social services.
• Considered applied research.
Evaluating Quasi-Experimental Designs
• The presumed cause usually precedes the
presumed effect.
• These designs do allow researchers to determine
if the two variables covary together.
• BUT they can not eliminate effects of extraneous
variables and ensure randomization.
Chapter 13: Single-Case Research
• Examine individual participants rather than a
group of participants.
• Idiographic approach: describe, analyze, and
compare individual behavior
• Nomothetic approach: Describe, analyze, and
compare behavior across individuals and make
broad generalizations to a group.
• Many research areas started in single caseresearch (Ebbinhgaus’s memory research on
himself, Skinner and Pavlov research)
Three main criticisms of group designs
Error variance: error variance in group data does
not always reflect variability in behavior (rather is
due to the design).
• Group designs examine inter-participant variance
which is across or between participants (individual
differences)
• Rather single-case researchers emphasize intraparticipant variance which is variability in an
individual’s behavior.
Generalizability: single case researchers suggest
that group designs have limited generalizability.
• Group designs usually reflect an average of the
participants behavior which may not represent the
response of any particular participant.
• Average number of children adults have 2.1
• Average anxiety score is 10 (but most people may
be at either high or low end 3-4 and 17-18).
Reliability: group designs may test an effect once,
but do not always replicate it to see if the effect
holds up and is reliable.
• Single-case researchers often test an effect in the
same participant a few times (intraparticipant
replication) or determine whether the same effect
is found in a few other participants
(interparticipant replication)
Single-Case Experimental Designs
ABA design: observe participants in absence of
independent variable, baseline (A), then introduce
independent variable, experimental period (B),
then remove independent variable and observe
behavior (A).
• Sometimes called a reversal design
• Difficult to determine if some other event
occurring at the same time as the independent
variable resulted in the effect
• The independent variable may produce
permanent changes in a participants behavior, so
it may not go back to baseline.
Multiple-I Designs
• Present varying nonzero levels of the independent
variable
• ABC design: baseline (A), introduce IV (B), then
remove this IV and introduce another level of the
IV (C).
• ABACA: have baseline condition between each
level of the independent variable
• Multiple Baseline Designs: two or more behaviors
are examined simultaneously.
• After the baseline data, the researcher examines the
effect of the independent variable on both behaviors.
Usually test to see if independent variable affects the
hypothesized behavior.
Data Analysis
• Graphic analysis: display all of a participants data
points (before and after independent variable) on
a graph. Visually examine the graph to determine
whether it looks like the independent variable
produces an effect.
Uses of single-case designs:
• Conditioning research (reinforcement and
punishment effect)
• Behavior modification techniques (phobias)
• Demonstrational purposes.
Critiques of single-case research
• Not necessarily generalizable because the
participant is not usually chosen at random
• Difficult to study interactions among variables
• Ethical issues in ABA designs when the
researcher may remove a very helpful treatment
Case Study Research
• An intensive description and analysis of a single
individual, or sometimes a group
• Usually gather a narrative description of
information about the individual(s).
• Common when describing rare phenomena (rare
brain injuries or disorders, prodigies, assassins)
• Psychobiography: use psychological theories to
understand lived of famous people (study Nixon)
• Used to make anecdotes and to illustrate general
principles.
Limitations of Case Studies
• Very difficult to control extraneous variables.
Usually unable to asses and rule out alternative
explanations.
• Observer Biases