Review During the last lecture we were discussing the use of experiments as a way of answering questions about the causal relationship between variables.

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Presentation transcript:

Review During the last lecture we were discussing the use of experiments as a way of answering questions about the causal relationship between variables If we can systematically manipulate a variable and show that it has an effect on another variable, then we have a strong basis for concluding that one variable affects the other.

Factorial Designs Today we’re going to discuss experimental designs involving more than one independent variable. Why might we want to manipulate more than one variable in an experiment? –economical –we may have reason to believe that the effects of one variable on another are conditional upon a third variable. Example: It may be the case that whether or not people behave aggressively after viewing violent television depends on whether they’ve been provoked or threatened.

Factorial Designs Multiple independent variables Factorial designs [# of levels]  [# of levels] IV#1 IV#2 Example: a 2  3 factorial design 2 levels of the first IV, “violent TV viewing” (e.g., watching violent TV and nonviolent TV) and 3 levels of second IV, “provocation” (e.g., 0 threats, 1 threat, 2 threats)

Factorial Designs Possible outcomes in a 2  2 design main effect: manipulating one of the IV’s produces a change in the DV in a 2  2 design, you can have 0, 1, or 2 main effects interaction: the effect of one IV on the DV is dependent on the other IV

No main effect of A or B, no interaction Aggressive TV viewing ProvocationsA1A2 B120 B220 Aggressive TV viewing Aggressive behavior (DV) Provocations This represents a situation in which the experimental manipulations have no effects on the dependent variable.

Main effect of A, no main effect of B and no interaction Aggressive TV viewing ProvocationsA1A2 B B Aggressive TV viewing Aggressive behavior (DV) Provocations Watching violent TV leads to increases in aggressive behavior.

Main effect of B, no main effect of A and no interaction Aggressive TV viewing ProvocationsA1A2 B120 B Aggressive TV viewing Aggressive behavior (DV) Provocations Being provoked leads to increases in aggressive behavior.

Main effect of A and B, no interaction Aggressive TV viewing ProvocationsA1A2 B B Aggressive TV viewing Aggressive behavior (DV) Provocations Watching violent TV leads to aggressive behavior. and Being provoked leads to increases in aggressive behavior.

No main effect of A or B; interaction Aggressive TV viewing ProvocationsA1A2 B B Aggressive TV viewing Aggressive behavior (DV) Provocations Whether people behave aggressively after watching violent TV depends on whether they’ve been provoked. If provoked, violent TV leads people to behave aggressively. If not provoked, violent TV leads people to behave less aggressively.

Main effect of A, no main effect of B; interaction Aggressive TV viewing ProvocationsA1A2 B B Aggressive TV viewing Aggressive behavior (DV) Provocations Watching violent TV leads to less aggressive behavior. and it depends. Watching violent TV leads people to behave more aggressively when they have not been provoked.

Main effect of B, no main effect of A; interaction Aggressive TV viewing ProvocationsA1A2 B B Aggressive TV viewing Aggressive behavior (DV) Provocations Being provoked leads to more aggressive behavior. and it depends. Being provoked leads to more aggressive behavior when watching violent TV. When not watching violent TV, provoked and non-provoked people are equally aggressive.

Main effect of A and B; interaction Aggressive TV viewing ProvocationsA1A2 B120 B Aggressive TV viewing Aggressive behavior (DV) Provocations Watching violent TV leads to less aggressive behavior. and Being provoked leads to increases in aggressive behavior. and it depends. In the absence of provocation, there is no effect of violent TV viewing on behavior. When provoked, watching violent TV leads people to behave more aggressively.

Experimental Research Between- and within-subjects designs between-subjects: different people are exposed to each level of the IV within-subjects: the same people exposed to each level of the IV Mixed design: one factor is a between- subjects factor and the other is a within- subjects factor

Pros and cons of different designs BetweenWithin Pros(a) Minimize reactance effects(a) Requires fewer research subjects Cons(a) Requires more research subjects (b) The people in the two conditions may vary for reasons that have nothing to do with your manipulation. (a) Awareness of different levels of independent variable (b) Learning & practice effects

Counter-balancing t1 t2 t3 Person 1 T1T2T3 Person 2 T1T3T2 Person 3 T2T1T3 Person 4 T2T3T2 Person 5 T3T1T2 Person 6 T3T2T1 Counter-balancing helps to ensure that the specific test used (T1, T2, T3) is uncorrelated with order of presentation