Complex Experimental Designs

1. Complex Experimental Designs Chapter 10

2. Increasing the # of levels of an IV • Simple design = 2 levels • Doesn’t provide a lot of information • Level 1: reward • Level 2: no reward • Use a ratio scale • Linear • Monotonic • Curvilinear • Increases in one variable are accompanied by decreases and increases in the other variable • Inverted-U

3. Increasing the # of IVs: factorial designs • Many IVs are closer to real world conditions • Factorial designs – more than 1 IV • 2 x 2 factorial • 2 independent variables w/ 2 levels each • 2 x 2 = 4 experimental conditions • Main effects • Effect the variable has by itself • Averages across the levels of the other IV • Interactions • The effects of one IV is different at different levels of the other IV

4. Outcomes of a 2 x 2 factorial design • There may or may not be a significant main effect for variable A • There may or may not be a significant main effect for variable B • There may or may not be an interaction between both variables • When there is an interaction, next look at simple main effects (differences at each level of the IV) • This allows analysis of results as though there were separate experiments at each level of the other IV

5. Mixed factorial design • Combining independent groups AND repeated measures • Uses combined assignment of participants • Investigates the combined effects of situational factors and subject variables • Common manipulation is looking at gender differences • Below is a 2x3 mixed factorial • 6 total conditions

6. Increasing the # of IVs in a factorial design • Conducting a 2x2x2 design • Can be seen as two 2x2 designs, • i.e. one for males and one for females • Yields main effects for 3 IVs • Also allows us to look at interactions