Experimental Design: Single factor designs

1. Experimental Design: Single factor designs Psych 231: Research Methods in Psychology

2. Announcements • Reminder: your group project experiment method section is due in labs this week • Remember to download, print and READ the class exp articles

3. Methods of Controlling Variability • Comparison • Production • Constancy/Randomization

4. Methods of Controlling Variability • Comparison • An experiment always makes a comparison, so it must have at least two groups • Sometimes there are control groups • This is typically the absence of the treatment • Without control groups if is harder to see what is really happening in the experiment • it is easier to be swayed by plausibility or inappropriate comparisons • Sometimes there are just a range of values of the IV

5. Methods of Controlling Variability • Production • The experimenter selects the specific values of the Independent Variables • Need to do this carefully • Suppose that you don’t find a difference in the DV across your different groups • Is this because the IV and DV aren’t related? • Or is it because your levels of IV weren’t different enough

6. Methods of Controlling Variability • Constancy/Randomization • If there is a variable that may be related to the DV that you can’t (or don’t want to) manipulate • Control variable: hold it constant • Random variable: let it vary randomly across all of the experimental conditions • But beware confounds, variables that are related to both the IV and DV but aren’t controlled

7. Experimental designs • So far we’ve covered a lot of the about details experiments generally • Now let’s consider some specific experimental designs. • 1 Factor, two levels • 1 Factor, multi-levels • Factorial (more than 1 factor) • Between & within factors

8. Poorly designed experiments • Example: Does standing close to somebody cause them to move? • So you stand closely to people and see how long before they move • Problem: no control group to establish the comparison group (this design is sometimes called “one-shot case study design”)

9. Single variable – One Factor designs • 1 Factor (Independent variable), two levels • Basically you want to compare two treatments (conditions) • The statistics are pretty easy, a t-test Observed difference btwn conditions T-test = Difference expected by chance

10. 1 factor - 2 levels • Example • How does anxiety level affect test performance? • Two groups take the same test • Grp1 (moderate anxiety group): 5 min lecture on the importance of good grades for success • Grp2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough

11. Random Assignment Dependent Variable Anxiety Low Test participants Moderate Test 1 factor - 2 levels

12. One factor Use a t-test to see if these points are statistically different low moderate test performance low moderate anxiety Two levels Single variable – one Factor anxiety 60 80

13. Single variable – one Factor • Advantages: • Simple, relatively easy to interpret the results • Is the independent variable worth studying? • If no effect, then usually don’t bother with a more complex design • Sometimes two levels is all you need • One theory predicts one pattern and another predicts a different pattern

14. Single variable – one Factor • Disadvantages: • “True” shape of the function is hard to see • interpolation and extrapolation are not a good idea

15. Interpolation What happens within of the ranges that you test? test performance low moderate anxiety

16. high Extrapolation What happens outside of the ranges that you test? test performance low moderate anxiety

17. Poorly designed experiments • Example 1: • Testing the effectiveness of a stop smoking relaxation program • The subjects choose which group (relaxation or no program) to be in

18. Random Assignment Poorly designed experiments • Non-equivalent control groups Self Assignment Independent Variable Dependent Variable Training group Measure participants No training (Control) group Measure • Problem: selection bias for the two groups, need to do random assignment to groups

19. Poorly designed experiments • Example 2: Does a relaxation program decrease the urge to smoke? • Pretest desire level – give relaxation program – posttest desire to smoke

20. Poorly designed experiments • One group pretest-posttest design Dependent Variable Independent Variable Dependent Variable participants Pre-test Training group Post-test Measure • Problems include: history, maturation, testing, and more

21. 1 Factor - multilevel experiments • For more complex theories you will typically need more complex designs (more than two levels of one IV) • 1 factor - more than two levels • Basically you want to compare more than two conditions • The statistics are a little more difficult, an ANOVA (analysis of variance)

22. 1 Factor - multilevel experiments • Example (same as earlier with one more group) • How does anxiety level affect test performance? • Three groups take the same test • Grp1 (moderate anxiety group): 5 min lecture on the importance of good grades for success • Grp2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough • Grp3 (high anxiety group): 5 min lecture on how the students must pass this test to pass the course

23. Random Assignment Dependent Variable Anxiety Low Test participants Moderate Test High Test 1 factor - 3 levels

24. anxiety mod high low test performance 60 80 low mod high anxiety 1 Factor - multilevel experiments 60

25. 1 Factor - multilevel experiments • Advantages • Gives a better picture of the relationship (function) • Generally, the more levels you have, the less you have to worry about your range of the independent variable

26. 2 levels 3 levels testperformance test performance low mod high low moderate anxiety anxiety Relationship between Anxiety and Performance

27. 1 Factor - multilevel experiments • Disadvantages • Needs more resources (participants and/or stimuli) • Requires more complex statistical analysis (analysis of variance and pair-wise comparisons)

28. Pair-wise comparisons • The ANOVA just tells you that not all of the groups are equal. • If this is your conclusion (you get a “significant ANOVA”) then you should do further tests to see where the differences are • High vs. Low • High vs. Moderate • Low vs. Moderate

29. Next time • Adding a wrinkle: between-groups versus within-groups factors • Read chapter 11