The document outlines various single-factor experimental designs, including independent groups, matched groups, non-equivalent groups, and repeated measures, highlighting their definitions and examples. It discusses the statistical methodologies associated with these designs, such as t-tests and ANOVA, meticulously detailing the assumptions required for analysis. Key studies and their findings are summarized to illustrate the use of these experimental designs in psychological research.

1. Single-Factor Experimental
Designs
Brian J. Piper, Ph.D.

2. Goals
• Single Factor: 2 levels
– Independent groups
– Matched groups
– Non-equivalent groups
– Repeated measures (2)
• Single Factor: 3+ levels
• Control Group Designs

3. Really?
• “Single factor studies using only two levels are
not as common as you might think. Most
researchers prefer to use more complex
designs, which produce more elaborate and
intriguing outcomes.”

4. 2 Independent Groups
• Independent variable (IV) manipulated
• Equivalent groups created by randomization
• Does insecurity increase materialism?
– Participants: undergraduate students (N=60)
– IV:
• Control: write essay about listening to music
• Experimental: write essay about own death
Kasser & Sheldon (2000) Psychological Science, 11, 348-351.

5. t-test
• Student’s (Between Subjects) t-test
t = (Mean1 – Mean2)/Variability12 if SD1 ≈SD2
Degrees of Freedom = N - 2
William S. Gosset
O
1876-1937

6. Assumptions of t-test
1) Data is interval or ratio
2) Data is normally distributed
3) For two-groups, homogeneity of variance

7. Logic
If p > .05 assumption is met
If p < .05 than assumption not met.

8. Overview
t = Signal / Noise
+∞ to - ∞

9. 2 Independent Groups
• Dependent Variable (DV): economic value
Mean (SD)
t (degrees of freedom) = # , p <> .05

10. Matched Groups Example
• Some variable is measured & then group
assignment
• Sleep deprivation & suggestibility example
– Sleep length recorded before assigning to
deprivation (+ or - )
– Long-story presented following by leading questions
(Were assailants armed with gun or knife?)
Blagrove (1996) J Exp Psychol: Applied, 2, 48-59.

11. Matched Groups Example
• Some variable is measured & then group
assignment
• Sleep deprivation & suggestibility example
• Results: 43, but not 21, hour deprivation
increased suggestibility
Blagrove (1996) J Exp Psychol: Applied, 2, 48-59.

12. Non-Equivalent Groups
• He quit because his “body forgot the urge to
smoke”
• Comparison of brain damage to insula (N=19)
versus damage to other areas (N=50)

13. Comparing
Groups
• Smoking following brain
damage was examined in
patients with or without
insula damage.
Naqvi et al. (2007). Science, 315, 531-534.

14. Results
Naqvi et al. (2007). Science, 315, 531-534.

15. Repeated Measures
• If same subjects get both treatments, there is
a concern about order effects (fatigue,
practice, etc.)

16. Repeated Measures
• If same subjects get both treatments, there is
a concern about order effects (fatigue,
practice, etc.)
• Solution: Counterbalance!

17. Mental Effects of Steroids
• Men (N=56) received:
– steroids, placebo
– Placebo, steroids
Pope et al. (2000) Archives General Psychiatry, 57, 133-140.

19. Repeated Measures: Example 2
• Do toddlers use visual feedback for balance or
only mechanical feedback?
Lee & Aronson (1974) Perception & Psychophysics, 15, 529-532.

20. Repeated Measures Design
• Within-Subjects: order alternating
– Forward – Backward – Forward – Backward
– Backward – Forward – Backward - Forward
Lee & Aronson (1974) Perception & Psychophysics, 15, 529-532.

21. Repeated Measures Design
• Within-Subjects: order alternating
– Forward – Backward – Forward – Backward
– Backward – Forward – Backward - Forward
Lee & Aronson (1974) Perception & Psychophysics, 15, 529-532.

22. Paired t-test
• Comparison of Novel Faces & Places Response
Times (msec) for correct versus incorrect
decisions
• Degrees of Freedom = N - 2

23. 2-Level Design Statistic
Independent groups Two-sample t-test
Matched groups Paired t-test
Non-equivalent groups Two-sample t-test
Repeated measures (2) Paired t-test

24. 3+ Levels
• Provide more information than 2 levels

25. 3+ Levels
• Provide more information than 2 levels
Hermann Ebbinghaus
1850-1909

26. Data Presentation
• Whenever possible figures
• If you must …………..tables

27. 3+ Groups Analysis
• Analysis of Variance (ANOVA)
– Signal / noise
– Range: 0 to infinity, ≈3.0+ is statistically significant
1

28. ANOVA
• Step 1: Is there a difference 1915-2000
(somewhere)?
• Degrees of freedom:
– between groups = # groups -1
– Error = total N – dfBG -1
• Step 2: Where is the
difference?
– T-test
– Post-hoc tests (Tukey HSD)

29. Control Group Designs
• Placebo Group (aka negative control)
– Alcohol flavored Jello shots
– THC free cigarettes
• Wait List Control Group: depression example

30. Control Example
• Women (N=47) were randomly assigned to:
– Subliminal: tapes consistent with labeling
– Placebo: tapes inconsistent with labeling
– Wait List: received tapes at end of 6 week study
Mirikle & Skanes (1992) J Applied Psychology, 77, 772-776.

31. Yoked Control
• Participant groups matched based on prior trauma
(moderate), sex, and age
• Eye Movement Desensitization & Reprocessing: imagine trauma + follow therapists
rapidly moving finger
• Control: imagine trauma while staring at stationary object (same duration as
experimental
*
*
Dunn et al. (1996). J Behav Therapy Exp Psychiatry, 27, 231-239.

32. Yoked Control
• Part I:
– Experimental: no barrier, light than jump
– Yoked: barrier, gets same # of shocks
• Part II (no barrier)
– Experimental: learned to avoid footshock
– Yoked: learned to not avoid footshock

33. Summary
t-test ANOVA
assumptions Interval/ratio, normal, Interval/ratio, normal,
homogeneity of variance homogeneity of variance
groups 2 3+
statistic t, p < .05 F, p < .05
variations between, within between, within