Controlling Variability
Methods of Experimental Control Constancy/Randomization Comparison Production
Methods of Controlling Variability
Constancy/Randomization If there is a variable that may be related to the DV that you can’t (or don’t want to) manipulate• Control variable: hold it constant• Random variable: let it vary randomly across all of the experimental conditions
But beware of potential confounds, variables that co-vary with both the IV and DV but aren’t controlled
Methods of Controlling Variability
Comparison An experiment always makes a comparison, so it must have at least two groups• Sometimes there are control groups
• This is typically the absence of the treatment
Traininggroup
No training (Control) group
• Without control groups if is harder to see what is really happening in the experiment
• It is easier to be swayed by plausibility or inappropriate comparisons
Methods of Controlling Variability
Comparison An experiment always makes a comparison, so it must have at least two groups• Sometimes there are control groups
• This is typically the absence of the treatment
1 week of Training group
2 weeks of Training group
• Sometimes there are a range of values of the IV
3 weeks of Training group
Methods of Controlling Variability
Production The experimenter selects the specific values of the Independent Variables
1 week of Training group
2 weeks of Training group
3 weeks of Training group
• Need to do this carefully• Suppose that you don’t find a difference in the DV across your different groups
• Is this because the IV and DV aren’t related?• Or is it because your levels of IV weren’t different enough
Experimental designs
So far we’ve covered a lot of the about details experiments generally
Now let’s consider some specific experimental designs. Some bad designs Some good designs
• 1 Factor, two levels• 1 Factor, multi-levels• Factorial (more than 1 factor)• Between & within factors
Poorly designed experiments
Bad design example 1: Does standing close to somebody cause them to move? “hmm… that’s an empirical question. Let’s see what happens if …”
So you stand closely to people and see how long before they move
Problem: no control group to establish the comparison group (this design is sometimes called “one-shot case study design”)
Poorly designed experiments
Bad design example 2: Testing the effectiveness of a stop smoking relaxation program
The participants choose which group (relaxation or no program) to be in
Poorly designed experiments
Non-equivalent control groups
participants
Traininggroup
No training (Control) group
Measure
Measure
Self Assignment
Independent Variable
Dependent Variable
RandomAssignment
Problem: selection bias for the two groups, need to do random assignment to groups
Problem: selection bias for the two groups, need to do random assignment to groups
Bad design example 2:
Poorly designed experiments
Bad design example 3: Does a relaxation program decrease the urge to smoke? Pretest desire level – give relaxation program – posttest desire to smoke
Poorly designed experiments
One group pretest-posttest design
participantsPre-test Training group
Post-testMeasure
Independent Variable
Dependent Variable
Dependent Variable
Problems include: history, maturation, testing, and more
Pre-test No Training group
Post-testMeasure
Add another factor
Bad design example 3:
1 factor - 2 levels
Good design example How does anxiety level affect test performance?• Two groups take the same test
• Grp1 (moderate anxiety group): 5 min lecture on the importance of good grades for success
• Grp2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough 1 Factor (Independent variable), two levels
• Basically you want to compare two treatments (conditions)• The statistics are pretty easy, a t-test
1 factor - 2 levels
participants
Low
Moderate Test
Test
Random Assignment
Anxiety
Dependent Variable
Good design example How does anxiety level affect test performance?
anxiety
low moderate
8060
low moderatetest performance
anxiety
One factor
Two levels
Use a t-test to see if these points are statistically different
T-test = Observed difference between conditions
Difference expected by chance
Good design example How does anxiety level affect test performance?
1 factor - 2 levels
Advantages: Simple, relatively easy to interpret the results
Is the independent variable worth studying?• If no effect, then usually don’t bother with a more complex design
Sometimes two levels is all you need• One theory predicts one pattern and another predicts a different pattern
1 factor - 2 levels
low moderatetest performance
anxiety
What happens within of the ranges that you test?Interpolation
Disadvantages: “True” shape of the function is hard to see
• Interpolation and Extrapolation are not a good idea
1 factor - 2 levels
Extrapolation
low moderate
test performance
anxiety
What happens outside of the ranges that you test?
Disadvantages: “True” shape of the function is hard to see
• Interpolation and Extrapolation are not a good idea
1 factor - 2 levels
high
1 Factor - multilevel experiments
For more complex theories you will typically need more complex designs (more than two levels of one IV)
1 factor - more than two levels Basically you want to compare more than two conditions
The statistics are a little more difficult, an ANOVA (Analysis of Variance)
Good design example (similar to earlier ex.) How does anxiety level affect test performance?• Two groups take the same test
• Grp1 (moderate anxiety group): 5 min lecture on the importance of good grades for success
• Grp2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough
1 Factor - multilevel experiments
• Grp3 (high anxiety group): 5 min lecture on how the students must pass this test to pass the course
1 factor - 3 levels
participants
Low
Moderate Test
Test
Random Assignment
Anxiety
Dependent Variable
High Test
1 Factor - multilevel experiments
anxiety
low mod high
8060 60
low mod
test performance
anxiety
high
1 Factor - multilevel experiments
Advantages Gives a better picture of the relationship (function)
Generally, the more levels you have, the less you have to worry about your range of the independent variable
Relationship between Anxiety and Performance
low moderate
test performance
anxiety
2 levels
highlow mod
test performance
anxiety
3 levels
1 Factor - multilevel experiments
Disadvantages Needs more resources (participants and/or stimuli)
Requires more complex statistical analysis (analysis of variance and pair-wise comparisons)