1. Experimental and Quasi- Experimental Designs Chapters 9 & 10

2. Research Design It is the outline, plan, or strategy for the procedures you will use to address your research question.

3. Research Designs – What are some limitations of these? 1. One-group after design TreatmentResponse measure 2. One-group before-after design Response Measure 1 Treatment Compare Response Measure 2

4. Research Designs – What are some limitation of these?

5. What are the requirements of true research designs?

6. Requirements of True Research Design Design is adequate to answer the research question (i.e., test the hypothesis). Control for extraneous variables Results are generalizable.

7. Why Pre-testing Your Participants Increased sensitivity of the study Ceiling effect Initial position Initial comparability Evidence of change

8. What are the limitations of this design?

9. Factorial Design Two or more independent variables are studied in order to determine their independent and interactive effects on the dependent variable.

10. Interaction Effect The effect of one factor (independent variable) depends on the level of the other factor (other independent variable).

11. Main Effects & Interactions Sadness Lightness Seasonal Affect Disorder Non-Seasonal Affect Disorder High Low

12. Advantages of Factorial Designs More than one hypothesis can be tested. Potentially confounding variables can be built into the design as factors. Enables interaction effects to be tested.

13. Within Participant After-Only Design Same research participants in all experimental treatment conditions. Repeated measures design. Overcomes concerns about creating equivalence between groups. Requires fewer participants. Most serious limitation is the confounding influence of a sequence effect.

14. Combining Within and Between Participant Designs Factorial design based on a mixed model. Can include as many independent variables as is necessary.

15. Combining Within and Between Participant Designs Repeated Measure Between-Subject Factor May want to match before randomizing

16. Factorial Design Main effect for beta blocker Main effect for stress management Interaction effect for drug and stress management

17. Main & Interaction Effects Main Effect Interaction Effect

18. Selecting the Appropriate Design The design must be one that addresses your research question. What control techniques can and should you apply to help you arrive at an unambiguous answer. Between or within-in design or mixed model.

19. Quasi-Experimental Design

20. Quasi-Experimental Does not meet all of the requirements necessary for controlling the influence of extraneous variables. Most common criteria not met is random assignment. While you cannot infer cause and effect, well designed quasi-experiments enable you to demonstrate that rival interpretations are implausible.

21. Non -Equivalent Control Group Design: Typical Rival Hypotheses Increasing treatment effect I outcome A selection-maturation effect

22. Increasing Treatment Effect I Outcome Pre-test Post-test Control Group Experimental Group

23. Increasing Treatment and Control Group Outcomes Both groups’ scores increase over time but one group changes to a greater extent than the other group. Effect could be due to a treatment effect or to a selection-maturation interaction.

24. HADS Depression ANOVA – time and time by group effect, depression decreased in both groups but levelled off in control Group at follow-up while continuing to decrease in experimental.

25. Increasing Treatment Effect II Outcome Pre-test Post-test Control Group Experimental Group

26. Cross-Over Effects Pre-test Post-test Control Group Experimental Group

27. Time Series Analyses Useful when you cannot randomize participants and where it is possible to obtain a series of assessments of the dependent variable at pre-treatment and post-treatment.

28. Time Series Analysis Treatment Applied     

29. Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut In 1955 there were a record number of traffic accidents ( n = 324) so the Governor (Abraham Ribicoff) introduced a law to reduce the speed limit. In 1956 there were 284 traffic accidents, a reduction of 12.3%. Governor concluded that his intervention worked but the effects could just as easily been due to regression to the mean.

30. Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut Campbell and Ross (1968) used interrupted time series design to test if the reduced trend in traffic accidents was plausible. Compared traffic accident trend in Connecticut with control States.

31. Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut ‘51‘52‘53‘54‘55‘56‘57‘58‘59 9 10 11 12 13 14 15 Control State Connecticut        

32. Class Exercise Specify your research question Your scientific hypothesis Specify your design Break into groups of 5