EXPERIMENTS

1. EXPERIMENTS Research Method Used to Test Causal Relationships Among Variables

2. Experiments • Why engage in experiments?

3. Causal vs. Correlational Relationships • Both causal and correlational relationships specify relationships among variables and concepts. • In both cases, we move from concept to variable to empirically examining relationships by creating an Operational Definition (or operationalizing) • Causal relationships specify Cause- effect relationship • Independent variable causes dependent variable • Correlational relationships specify a relationship between variables but do not specify cause-effect

4. Communication and Causal Relationships • 1) Communication Variable (IV) causes a non-communication variable (DV) • 2) Non-communication variable (IV) causes a communication variable (DV) • 3) Communication Variable (IV) causes a communication variable (DV)

5. 3 Criteria for cause/effect relationship • 1. Cause (Independent variable) must precede effect (Dependent variable) in time. • 2) Cause and effect must by correlated • 3) Rival explanations (factors other than the theorized cause) must be eliminated (ruled out)

6. Internal Validity • In experiments, internal validity is the confidence we have that our independent variable caused our dependent variable (rather than a third variable causing our dependent variable). • To assure internal validity, we control for threats to internal validity.

7. Experimental Designs • Random Assignment • Manipulate Independent variable • Equivalent conditions • More than 1 group (at least treatment and control)

8. Threats to Internal Validity • Researcher-Related Threats • Experimenter effect • Observer Bias • Researcher Attribute Effect • Participant-Related Threats • The Hawthorne effect • Testing effect • Maturation

9. Threats to Internal Validity (cont.) • Participant-Related Threats (cont.) • Experimental mortality • Selection biases • Intersubject biases (diffusion of treatments) • Compensatory rivalry • Demoralization

10. Threats to Internal Validity (cont.) • Procedure-Related Threats • History • Instrumentation • Treatment confound • Statistical regression • Compensation • To control for threats need careful procedures (True Experimental Design)

11. Pre-Experimental Designs • X= application of IV • 0= observation of DV • 1) 1 shot case study • x o • 2) 1 group pretest-posttest • 0 X 0 • 3) Static-group comparison • X 0 • 0

12. Experimental Designs • Random Assignment • Manipulate Independent variable (perhaps conduct manipulation check) • Equivalent conditions (including double blind) • More than 1 group (at least treatment and control)

13. Experimental Designs • Pretest-Posttest Control Group Design • R O X O • R O O • Posttest Only Control Group Design • R X O • R O

14. Experimental designs (cont) • Solomon Four Group • R 0 x 0 • R 0 0 • R x 0 • R 0

15. Factorial Experiments • More than one independent variable • Factorial design statements: 2 X 2 • 3 X 2 X 4 • Main Effects • Interaction effects

16. External Validity • To what extent are experimental results generalizable?

17. Threats to External Validity • Interaction between the testing setting and treatment • Interaction of selection and treatment • Interaction of history and treatment • Interaction between testing and treatment

18. Quasi-experimental designs • Natural setting • Do not meet criteria for true experimental designs • Enhance external validity • Sacrifice internal validity