Review
• Operational definitions • Internal validity• Threats to internal validity • Type I and type II errors
Review: Operational definitions
• For each of these studies, operationalize the IV and DV:– The effect of exposure to other racial
groups on prejudicial attitudes– The effect of word length on speed of
reading– The effect of cognitive therapy on
depression
Review: Internal validity
• What is internal validity?• Ability to make valid inferences
concerning the relationship between the IV and DV in an experiment. (effect on the DV is caused only by the IV)
• The extent to which the results of an experiment can be attributed t the manipulation of the IV rather than to some confounding variable
Review: Threats to Internal Validity
• Nonequivalent control group• History• Maturation• Testing • Regression to the mean• Instrumentation• Mortality/Attrition
Type I and Type II Errors
Accept the Null Hypothesis
Reject the Null Hypothesis
Null is really True(chance is responsible)
Correct Decision
Type I Error
Null is really False(chance is not responsible)
Type II Error
Correct Decision
Power
• Power is the probability of avoiding a Type II error. (Finding an effect if there really is one there to find)
• Power is related to:– Alpha level– Effect size (mean and sd)– Number of participants
Review: Advantages of Multi-level Designs
• What is a multi-level design?• Advantages:
– Efficiency (fewer participants needed and less time)
– Ability to see relationships better
Review: Multifactor Designs
• Factorial design: A design in which all levels of each IV are combined with all levels of the other IVs.
• Advantages of factorial designs:– More efficient (fewer participants and
less experimenter time)– Allows us to see how variables
interact, see complex relationships
Example: Movie Preferences
0
2
4
6
8
10
Romantic Action
Movie Type
Ra
ting
men
women
Men Women Mean
Romantic
3 6 4.5
Action 7 4 5.5
Mean 5 5
What a Factorial Design Tells You
• Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare means of different levels of IV, while ignoring [collapsing across] other IVs [ i.e., compare marginal means])
• Interaction effect: When the effect of one IV on a DV differs depending on the level of a second IV.
• Interpret the interaction first
Examples of Main Effects and Interactions
• A1= morning• A2= late
afternoon
• B1= high fat diet• B2= low fat diet
• DV: 0-50 rating of energy level
More Main Effects and Interactions
• A1= morning• A2= late
afternoon
• B1= high fat diet• B2= low fat diet
• DV: 0-50 rating of energy level
More Main Effects and Interactions
• A1= morning• A2= late
afternoon
• B1= high fat diet• B2= low fat diet
• DV: 0-50 rating of energy level
Example: Psychotherapy Outcome
01
02
0
Pre PostTime
BD
I Sco
re
Cognitve
No Tx
Pre Post MarginalMean
Cognitive
20 10 15
No Tx 20 20 20
MarginalMean
20 15
Group Activity: Main Effects and Interactions
Make graphs of the following situations:
Var A Var B AxB interaction
p < .05 n.s. p < .05
p < .05 p < .05 p < .05
n.s. p < .05 n.s.
n.s. n.s. p < .05
Factorial Designs: Naming Conventions
• The first number is the number of levels in first IV, second number is number of levels in second IV, etc.
• 2 x 2• 2 x 3• 2 x 2 x 3• Between-subjects,
repeated measures (within), mixed