17. Quasi-experimental research designs

1. 17. Quasi-experimental research designs Pelham & Blanton Ch. 8

2. Results from last week: Psych 217:

3. Maybe not enough power, so I took the leftover chocolate to work:

4. BiM chose in the opposite direction, made overall results worse!

5. My co-workers . . .

6. What is a quasi-experiment? Research design in which researcher only has partial control over the independent variables Participants are not randomly assigned to different conditions When do we do quasi-experiments?

7. Examples of Quasi-Experimental Independent Variable�s Demographic categories (e.g., gender, culture, race) Individual differences (e.g., high & low self-esteem)

8. Types of Quasi-experiments Person by treatment quasi-experiments Natural experiments

9. Person by Treatment Quasi-Experiments Measures at least one IV e.g., men vs. women, low vs. high self-esteem, patient vs. control, class section in yesterday�s demo Manipulates (and randomly assigns) at least one other IV e.g., drug vs. placebo, success vs. failure feedback, high fat vs. low fat

10. Culture & the Effect of Talking on Cognitive Performance To examine cultural difference in how thinking aloud and silently affects cognitive performance IV Culture (European American vs. East Asian American) Talking (Talking vs. Silence) DV Cognitive Performance

11. Median Split A way to convert a continuous variable into a categorical variable Determine the median of a sample and divide the group into two groups (e.g., high vs. low SE) Problem � people near the cut-off point

12. Therefore, rather than doing median split take people with extreme scores What do you know about people in the middle of the distribution? �assume that people who possess a medium amount of an attitude or trait will respond to treatments in medium amounts when compared to people who scored at the extreme� Use extreme scores to increase test sensitivity

13. Inductive Problem Because we are not manipulating the IV it is possible that there are confounds e.g., self-esteem correlated with gender. SES, depression, anxiety, etc Inductive problem � we never know if we have ruled out all possible confounds

14. Natural Experiments Experimenter does not manipulate anything Naturally occurring events expose some people to a condition and other people to other condition e.g., effect of job loss on marital satisfaction; effect of natural disasters on anxiety levels Usually rely on archival data

15. Again we have issue of confounds!!! Because naturally occurring events are not completely random Measures all the possible confounds (again problem of induction)

16. Comparison (Control) Group? It is difficult to determine what an adequate control group would be in natural experiments. Patching: adding new conditions to help establish the size of the effect, to test for the influence of conceivable confounds, or both i.e., many control groups

17. True vs Quasi-Experiments Internal validity � true wins External validity � quasi wins Ethical sensitive topics � quasi wins

18. Examples The effect of poor housing on health. The effect of learning a second language on cognitive ability.