I. Introduction - Experimental Design Issues

Design = Plan of Experiment ("blueprint")

Ask questions:

1) How many variables to test?  

2) How many levels for each variable?  

3) How to compose groups?

II. (True) experimental design 

A. Levels and variables  

 

 

 

B. Simple, two-group design

•  experimental group 

•   control group

C. Assignment of subjects

1. Random assignment

2. Correlated assignment

a. matched pair

b. natural pairs

c. repeated measures

D. Repeated measures designs

 

 

• Advantages and disadvantages

 

 

E. Increasing the complexity of designs

1. Increase the number of levels of a variable

2. Increase the number of dependent variables

3. Increase the number of Independent Variables – Factorial Designs

 III. Factorial Designs

• Increasing the complexity by increasing the number of Independent Variables 

A. Advantages of factorial designs

B. Main effects vs. interaction effects

MAIN EFFECTS – the effects of one variable, ignoring (averaged across) the other

INTERACTION EFFECTS – the effects of the variables together

Does one variable CHANGE the effects of another?

C. Interaction effects 

an example:...

1. What are some hypotheses we could make?

2. Possible outcomes:

• Main Effects ONLY

• Interaction Effects

3. What would both main effects and interaction effects look like?

D. Interpreting Interaction Effects

   DISCUSSION/ACTIVITY

 

 

  E. Statistics for multiple group means (ANOVA/F test)

 

 

III. Multivariate (correlational) Designs

A. Correlational designs revisited

1. Correlation vs. Causation

 

2. Pearson r - testing linear relationship between TWO variables

• testing r for significance

 

 

 

• coefficient of determination

 

 

 

B. Considering multiple variables

1. Partial correlations

 

 

 

 

2. Multiple regression

 

 

Multiple R/ R²

 

 

 

3. Factor Analysis

 

 

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