1. Independent Variables in Experimental Design
Manipulations and Manipulation Checks
Moderator vs. Mediator

2. Causal research

3. Experiments
Studies in which conditions are controlled so that one or more independent variable(s) can be manipulated to test a hypothesis about a dependent variable
Manipulation of A treatment variable (x), followed by observation of response variable (y)
Experiment must be designed to control for other variables to establish causal relationship

4. Types of Evidence That Supports a Causal Inference
Concomitant variation--evidence of the extent to which X and Y occur together or vary together in the way predicted by the hypothesis
Time order of occurrence of variables--evidence that shows X occurs before Y
Elimination of other possible causal factors—evidence that allows the elimination of factors other than X as the cause of Y
X -- the presumed cause
Y -- the presumed effect

5. Conceptualizing the Independent Variable
Operationalization
Select a particular way of manipulating the conceptual variable
Generalization through systematic replication
Manipulating the independent variable in different ways

6. Conceptualizing the Independent Variable (Cont.)
Direct manipulations
S -> R
Inducing internal states
S -> (R -> S) -> R

7. Example: Mood and Emotion Manipulations
Movies
Sophie‘s Choice, Ordinary People
Pretty Woman, Mrs. Doubtfire
Recalling past experiences
Music
Ein Musikalischer Spass – Mozart
Adagio for Strings - Barber
Associated nonverbal approach / avoid behaviors

8. Decisions What operationalization should be used?
How can the impact of the manipulation be maximized?
How to check whether the manipulation was effective?

9. Types of Manipulations
Instructions
Attention
Understanding
Task requires understanding
Give test of understanding
Keep it simple

10. Types of Manipulations
Instructions
Can be used to induce different mental sets and processing
Example: Memory vs. Impression set
Hamilton, Katz, & Leirer
Better memory for traits when asked to form impression of person than to merely remember them
Induce different motivations
Example: Test of ability vs. game

11. Events Accidents Helping studies Induced compliance dropping pencils
smoke-filled room
Induced compliance

12. Controling for Demand Characteristics
Pacebo effects
Expectations must be controlled for
“Good” subjects
Attempt to behave consistent with the presumed hypothesis
“Bad” subjects
Attempt to behave contrary with the presumed hypothesis
Hide purpose of the study

13. Pretesting Prior to experiment Examine effectiveness of a manipulation
Materials understandable?
Levels of variable are appropriate?
Measurements valid & reliable?

14. Manipulation Checks
Measures to ensure manipulation was effective during actual experiment
Explicit
Implicit
Best placed immediately after manipulation, although not always possible

15. Controlling Experimenter Influence
Naive experimenters
Blind to condition / Double-blind
Automated instructions
Running conditions simultaneously
Partially blind (unaware of one variable)

16. Participant Variables/Individual Differences
Cannot infer causality when the independent variable is not manipulated
Individual differences can complete a model of behavior
Can also remove error variance and make effects of independent variable more clear
Many individual differences can also be situationally manipulated

17. Moderation vs. Mediation
Baron & Kenny (1986). The Moderator-Mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6),
What are the differences between moderation and mediation?
Are the interchangeable terms?

18. Moderation Moderation:
A moderator is a qualitative (e.g., sex, race, SES) or quantitative (e.g., motivation) variable that affects the direction and/or strength of the relation between an independent/predictor variable and a dependent/criterion variable.
A moderator variable partitions a focal independent variable into subgroups that establish its domain of maximal effectiveness with respect to a particular dependent variable.
What other statistical concept does this sound like?

19. Mediation
Mediation:
A given variable may be said to function as a mediator to the extent that it accounts for the relationship between an IV and a DV
A mediator variable represents the generative mechanism through which the focal independent variable is able to influence the particular DV of interest.
Whereas moderator variables specify when certain effects will hold, mediators speak to how or why such effects occur.

20. A variable that changes the impact of one variable on another.
Moderator
A variable that changes the impact of one variable on another.
Predictor Outcome
Moderator

21. Testing a Moderator Hypothesis

22. Don’t Presume Linearity

23. The mechanism by which one variable affects another variable
Mediator
The mechanism by which one variable affects another variable

24. Testing Mediation Step 1: IV DV Step 2: IV Mediator
Step 3: Mediator DV
Step 4: Effect of IV on DV is significantly reduced by controlling for the mediator:
Sobel (1982) test (
Goodman (1960) test
On the exact variance of products. Journal of the American Statistical Association, 55,