Components of a causal relationship

1. Components of a causal relationship • Does a change in X cause a change in Y? • There are 3 components: • 1) Co‑variation of events • 2) Time‑order relationship • 3) Elimination of alternative causes.

2. Independent Variable • The presumed "cause" of a behavioral effect or change • Manipulated (varied) by experimenter • IV has several levels selected by experimenter • Occurs, or can be "set up" before DV is measured • "Independent" of what the subject does.

3. Dependent Variable • Some measure of behavior that is a measure of the effect of the IV(cause) • What is recorded by the experimenter • The behavior occurs after IV is varied, and DV measures the behavior • "Depends" on manipulation of the IV • DV does not have levels.

4. Confounding Variable • Any variable that is a potential cause for the experimental effect, other than the IV • Any variable whose values change systematically across levels of the IV.

5. Control variable • Variable whose values remain the same across levels of the IV (eg, room temp, light levels, time-of-day, etc).

6. Random variable • Variable whose values vary randomly in an unbiased way across levels of the IV • Random variables are usually created by the process of random assignment.

7. Subject variable • A personal characteristic (eg, height, weight, gender, ethnicity, socio-economic status, etc).

8. Control group • The group that receives “zero” or “the absence of” the IV • Eg, the placebo group in a drug experiment • The group that serves as a baseline to compare with the performances of the experimental groups.

9. Experimental groups • The groups that receive non-zero values of the IV • Eg, the drug groups in a drug study • The performances of these groups are compared with the performance of the control group.

10. Conceptual Definition • Definition of a variable at the conceptual or idea level • Tends not to be very precise • Tends to be more general, more vague.

11. Operational Definition • Specifies the operations or procedures necessary to measure the variable • Very precise • Not general or vague at all • Tells how the variable was measured • There may be many OD’s for a single CD.

12. ODs and CDs - Example 1 • Conceptual - Amount of alcohol • Operational - # of beers in 1 hour (0,1,2,3) • Operational - grams of alc./kg body weight • Operational - BAC (mg alc./deciliter blood).

13. ODs and CDs - Example 2 • Conceptual - Helping behavior • Operational - # of people who help a “victim” • Operational - duration of helping behavior • Operational - # seconds before helping occurs (latency).

14. EXR-intermediate scenarios

15. Complex designs • More than one IV • Eg, Left/Right and 1, 5, or 10 spaces fr. center • More efficient than single IV experiments • Gives more information • Allows analysis of main effects and interactions.

16. Complex designs - terminology • An IV is called a factor • number of numbers = how many IVs there are • values of numbers = how many levels each IV has • “2 X 2 design” (two IVs, each with 2 levels) • “2 X 3 design” (first IV has 2 levels, second IV has 3 levels) • “2 X 8 design” (first IV has 2 levels, second IV has 8 levels) • “2 X 2 X 4 design” (first IV has 2 levels, second IV has 2 levels, third IV has 4 levels).

17. Main effects • There is one potential main effect for each IV • A 2 X 8 design has two possible main effects • A 2 X 2 X 4 has three possible main effects • A main effect is present if an IV had a significant effect on the experiment’s outcome (regardless of the effects of the other IVs).

18. Interactions • Please memorize: “An interaction occurs if the effect of one IV varies depending on the level of the other IV”

19. EXR-horn honks and abstracts

20. Designing experiments • Two general types of designs • Between-subjects (between groups or independent groups) = each group gets one level of the IV  • Within-subjects (within-group or repeated measures) = each subject gets all levels of the IV • Equivalency of groups at each level is built-in for within-subjects and achieved by random assignment for between-subjects • Within - more efficient in terms of # of subjects • Within - zero variability (ind diff) between levels.

21. Order effects • Order effects (practice effects) = experiencing one level affects behavior in another level • Eg, does content (biology text vs. novel) affect proofreading speed? Order is Biology-Novel • Eg, practice, boredom, fatigue • Order effects cannot occur in between-subjects and are controlled in within-subjects by randomization or counterbalancing.

22. Differential carryover effects • (carryover effects, differential/asymmetrical transfer effects) • The effect of the first level on the second level differs depending on which comes first • Effect of B following A ≠ effect of A following B • Confound is due to which level precedes which.

23. FIG: Order effects in proofreading (no practice) (practice) Group 1 Biology Novel 1 2 (no practice) (practice) Group 2 Novel Biology 1 2

24. FIG: Differential carryover effects in problem solving (no practice) (practice) Group 1 Neutral instructions Special instructions 1 2 (no practice) (practice) Group 2 Special instructions Neutral instructions 1 2

25. Other considerations • Mixed designs (some between, some within) • Small-n designs • Matched groups designs • Demand characteristics = cues that tell subjects how they should behave (eg, drug studies) • Blind and double-blind procedures • Internal and external validity • Quasi experiments.

26. (no practice) (practice) Group 1 Neutral instructions Special instructions 1 2 (no practice) (practice) Group 2 Special instructions Neutral instructions 1 2