1. Chapter 11: Quasi-Experimental and Single Case Experimental Designs

2. Quasi-experimental designs
Emerged from the need to conduct applied research in settings in which the control features of a true experiment cannot be achieved
- Causal inferences much more difficult

3. Program Evaluation
Research on programs that are proposed and implemented to achieve some positive effect on a group of individuals
Donald Campbell (1969) urged a culture of evaluation
- Programs honestly evaluated to determine whether they are effective

4. Program Evaluation (con’t)
Five types of program evaluations (Rossi, Freeman, & Lipsey, 1999)
Needs assessment = asks whether there are problems that need to be addressed in a target population
Assessment of program theory = asks if the program based on valid assumptions and whether the program addresses the needs in appropriate ways

5. Program Evaluation (con’t)
Process evaluation (program monitoring) = monitors the implementation of the program to determine if it is reaching the target population, attracting enough clients, etc.
Outcome evaluation (impact assessment) = asks whether the intended goals are being realized
Efficiency assessment = asks whether the resources used to implement the program was “worth it”

6. Quasi-Experimental Designs
One-group posttest-only design (called a “one-shot case study”
Lacks a crucial element of a true experiment: a control or comparison group

7. Quasi-Experimental Designs (con’t)
One-group pretest-posttest design
- May be used to determine an index of change from the
pretest to the posttest

8. Quasi-Experimental Designs (con’t)
Alternative explanations to studies using the one-group pretest-posttest design
1. History – event is confounded with the manipulation
2. Maturation – changes that occur systematically over
time (fatigue, hunger, intelligence, etc.)
3. Testing – pretest sensitizes people to the purpose of
experiment or make them more adept at a skill being
tested

9. Quasi-Experimental Designs (con’t)
Alternative explanations to studies using the one-group pretest-posttest design (con’t)
Instrument decay – basic characteristics of the measuring instrument change over time
Regression toward the mean – when participants are selected because they score extremely high or low on some variable; scores ten to change in the direction of the mean when tested again

10. Quasi-Experimental Designs (con’t)
Nonequivalent control group design
Problem is that the groups are not equivalent. An alternative explanation is selection differences.

11. Quasi-Experimental Designs (con’t)
Nonequivalent control group pretest-posttest design
Problem is participants are not randomly assigned to
condition.

12. Quasi-Experimental Designs (con’t)
Interrupted time series design
Examines the dependent variable over an extended period of time, both before and after the IV is implemented
Interpretation problems (possible regression to the mean)

13. Single Case Experimental Designs
Traditionally called single-subject designs
Now referred to as single case and single participant designs
Historical tradition – B. F. Skinner
Techniques and logic applied to other research areas
Problem is that there are many explanations for the
change

14. Single Case Experimental Designs
Reversal designs: Simple ABA design
Participant’s behavior is measured over time during a baseline control period

15. Single Case Experimental Designs (con’t)
Improving the ABA design
ABAB design (treatment is tested twice)
ABABAB design (treatment is tested three times)
Why is it necessary to extend the basic ABA design?
Single reversal is not powerful evidence for the effectiveness of the treatment
- Ethics – sequence ends with the treatment rather than the withdrawal of the treatment

16. Single Case Experimental Designs (con’t)
Multiple baseline designs
Effectiveness of the treatment demonstrated when the behavior changes ONLY after the manipulation is introduced
Necessary because reversal of some behaviors is impossible or unethical
Some treatments might produce a long-lasting change that is not reversible

17. Single Case Experimental Designs (con’t)
Multiple baselines (con’t)
Multiple baseline across subjects
Multiple baseline across behaviors
Multiple baseline across situations

18. Single Case Experimental Designs (con’t)
Multiple baseline design

19. Single Case Experimental Designs (con’t)
Replications in single case designs
Present results from each participant individually rather than group data

20. The End