1. Experimental and Quasi-Experimental Research
C H A P T E R 18
Experimental and Quasi-Experimental Research
Chapter ??

2. Chapter Outline Sources of invalidity Threats to internal validity
Threats to external validity
Controlling threats to internal validity
Controlling threats to external validity
Types of designs

3. Experimental Research Tries to Establish Cause and Effect
Selection of a good theoretical framework
Application of appropriate experimental design
Use of correct statistical model and analysis
Proper selection and control of independent variables
Appropriate selection and measurement of dependent variables
Correct interpretation of results

4. Three Criteria for Cause and Effect
The cause must precede the effect in time.
The cause and effect must be correlated with each other.
The correlation between cause and effect cannot be explained by another variable. If the condition is necessary and sufficient to produce the effect, then it is the cause.

5. Reviewing Important Terms
Independent variable (IV)
Dependent variable (dv)
Categorical variable
Control variable
Extraneous variable

6. Distinguishing Between Types of Validity
Internal validity: did the treatments (IV) cause the change in the outcome (dv)?
External validity: to what populations, settings, or treatments can the outcome be generalized?
Is there a trade-off between internal and external validity?
Can a series of studies address the trade-off?

7. Threats to Internal Validity
History: events that are not part of treatment
Maturation: events due to passage of time
Testing: effects of more than one test administration
Instrumentation: change in calibration of measurements
Statistical regression: selection based on extreme score
(continued)

8. Threats to Internal Validity (continued)
Selection biases: nonrandom participant selection
Experimental mortality: differential loss of participants
Selection–maturation interaction: passage of time influencing groups differently
Expectancy: influence of experimenters on participants

9. Threats to External Validity
Reactive or interactive effects of testing: Pretest may make participants sensitive to treatment.
Interaction of selection biases and treatment: Treatment may work only on participants selected on specific characteristic.
Reactive effects of experimental arrangements: Setting constraints may influence generalizability.
Multiple-treatment interference: One treatment may influence the next treatment.

10. Controlling Threats to Internal Validity
Randomization
Real randomization
Matched pairs (not matched groups)
Randomizing treatments or counterbalancing
Placebos
Blind setups
(continued)

11. Controlling Threats to Internal Validity (continued)
Double-blind setups
Reactive effects of testing: eliminate pretest.
Instrumentation
Calibration and test reliability
Halo effects
Experimental mortality: keeping participants

12. Controlling Threats to External Validity
Selecting from larger population
Participants
Treatments
Situations
Ecological validity: does the setting capture the essence of the real world?

13. Types of Designs: Pre-Experimental Designs
One-shot studies
One-group pretest-posttest
Static group comparison T O O1 T O2
Statistical analysis? T O1
Statistical analysis? O2

14. Types of Designs: True Experimental Designs
Randomized-groups design
Extending the levels—randomized-groups design R T O1
Statistical analysis? O2 R T1 O1
Statistical analysis? T2 O2 O3
(continued)

15. Types of Designs: True Experimental Designs (continued)

16. Types of Designs: True Experimental Designs (continued)
A factorial design with a categorical factor (B) R A1 O1 B1 A2 O2 A3 O3
Statistical analysis? O4 B2 O5 O6
(continued)

17. Types of Designs: True Experimental Designs (continued)
Pretest—posttest randomized-groups
Extending the design on the RM factor R O1 T O2 O3 O4
Statistical analysis? R O1 T O2 O3
Statistical analysis? O4 O5 O6
(continued)

18. Types of Designs: True Experimental Designs (continued)
Extending the pretest—posttest randomized groups design on both factors
Statistical analysis? R O1 T1 O2 O3 O4 T2 O5 O6 O7 O8 O9
(continued)

19. Types of Designs: True Experimental Designs (continued)
Solomon four-group design—purpose
Statistical analysis (factorial ANOVA) R O1 T O2 O3 O4 O5 O6
No treatment
Treatment
Pretested O4 O2
Unpretested O6 O5

20. Quasi-Experimental Designs: Reversal (Figure 18.1)

21. Quasi-Experimental Designs: Time Series (Figure 18.2)

22. Quasi-Experimental Designs: Ex Post Facto
This is one of the preexperimental designs, but with the treatment not under the control of the experimenter. T O1
Statistical analysis? O2

23. Quasi-Experimental Designs: Switched Replication

24. Quasi-Experimental Designs: Single Participant
Identify participant and follow over time.
Does the treatment produce the same effect each time?
Are treatment effects cumulative, or does participant return to baseline?
Does participant’s response become less variable over treatment times?
(continued)

25. Quasi-Experimental Designs: Single Participant (continued)
Is participant’s magnitude of response sensitive to multiple treatment applications?
Do varying intensities, frequencies, and lengths of treatment produce varying responses?