1. Non-Experimental designs: Correlational & Quasi-experimental designs
Psych 231: Research Methods in Psychology

2. Non-Experimental designs
Sometimes you just can’t perform a fully controlled experiment
Because of the issue of interest
Limited resources (not enough subjects, observations are too costly, etc).
Surveys
Correlational
Quasi-Experiments
Developmental designs
Small-N designs
This does NOT imply that they are bad designs
Just remember the advantages and disadvantages of each
Non-Experimental designs

3. Correlational designs
Looking for a co-occurrence relationship between two (or more) variables
Used for
Descriptive research
do behaviors co-occur?
Predictive research
is one behavior predictive of another?
Reliability and Validity
Does your measure correlate with others (and itself)?
Evaluating theories
Look for co-occurrence posited by the theory.
Correlational designs

4. Correlational designs
Looking for a co-occurrence relationship between two (or more) variables
Example 1: Suppose that you notice that the more you study for an exam, the better your score typically is.
This suggests that there is a relationship between study time and test performance.
We call this relationship a correlation.
3 properties: form, direction, strength
Correlational designs

5. Y X 1 2 3 4 5 6
Hours study X
Exam perf. Y 6 1 2 5 3 4
Scatterplot

6. Linear
Non-linear
Form

7. Direction Positive Negative Y X Y X X & Y vary in the same direction
X & Y vary in opposite directions Y X
Direction

8. r = 0.0
“no relationship”
r = 1.0
“perfect positive corr.”
r = -1.0
“perfect negative corr.”
-1.0
0.0
+1.0
The farther from zero, the stronger the relationship
Strength

9. Rel A
Rel B
r = -0.8
r = 0.5
-.8 .5
-1.0
0.0
+1.0
Which relationship is stronger?
Rel A, -0.8 is stronger than +0.5
Strength

10. Y X 1 2 3 4 5 6
For our example, we have a linear relationship, it is positive, and fairly strong
Scatterplot

11. Correlational designs
Looking for a co-occurrence relationship between two (or more) variables
Explanatory variables (Predictor variables)
Response variables (Outcome variables)
Example 1: Suppose that you notice that the more you study for an exam, the better your score typically is
For our example, which variable is explanatory and which is response? And why?
It depends on your theory of the causal relationship between the variables
Correlational designs

12. Scatterplot Y 6 5 4 3 2 1 X Response (outcome) variable
For descriptive case, it doesn’t matter which variable goes where
Correlational analysis
For predictive cases, put the response variable on the Y axis
Regression analysis
Explanatory (predictor) variable
Scatterplot

13. Correlational designs
Advantages:
Doesn’t require manipulation of variable
Sometimes the variables of interest can’t be manipulated
Allows for simple observations of variables in naturalistic settings (increasing external validity)
Can look at a lot of variables at once
Correlational designs

14. Correlational designs
Disadvantages:
Don’t make casual claims
Third variable problem
Temporal precedence
Coincidence (random co-occurence)
Correlational results are often misinterpreted
Correlational designs

15. Misunderstood Correlational designs
Disadvantages:
Example 2: Suppose that you notice that kids who sit in the front of class typically get higher grades.
This suggests that there is a relationship between where you sit in class and grades.
Daily Gazzett
Children who sit in the back of the classroom receive lower grades than those who sit in the front.
Possibly implied: “[All] Children who sit in the back of the classroom [always] receive worse grades than [each and every child] who sits in the front.”
Better: “Researchers X and Y found that children who sat in the back of the classroom were more likely to receive lower grades than those who sat in the front.”
Misunderstood Correlational designs
Example from Owen Emlen (2006)

16. Quasi-experiments What are they? General types
Almost “true” experiments, but with an inherent confounding variable
General types
An event occurs that the experimenter doesn’t manipulate
Something not under the experimenter’s control
(e.g., flashbulb memories for traumatic events)
Interested in subject variables
high vs. low IQ, males vs. females
Time is used as a variable
Quasi-experiments

17. Quasi-experiments Advantages Disadvantages
Allows applied research when experiments not possible
Threats to internal validity can be assessed (sometimes)
Disadvantages
Threats to internal validity may exist
Designs are more complex than traditional experiments
Statistical analysis can be difficult
Most statistical analyses assume randomness
Quasi-experiments

18. Quasi-experiments Program evaluation
Research on programs that is implemented to achieve some positive effect on a group of individuals.
e.g., does abstinence from sex program work in schools
Steps in program evaluation
Needs assessment - is there a problem?
Program theory assessment - does program address the needs?
Process evaluation - does it reach the target population? Is it being run correctly?
Outcome evaluation - are the intended outcomes being realized?
Efficiency assessment- was it “worth” it? The the benefits worth the costs?
Quasi-experiments

19. Quasi-experiments Nonequivalent control group designs
with pretest and posttest (most common)
(think back to the second control lecture)
participants
Experimental
group
Control
Measure
Non-Random
Assignment
Independent Variable
Dependent Variable
But remember that the results may be compromised because of the nonequivalent control group (review threats to internal validity)
Quasi-experiments

20. Quasi-experiments Interrupted & Non-interrupted time series designs
Observe a single group multiple times prior to and after a treatment
Obs Obs Obs Obs Treatment Obs Obs Obs Obs
Look for an instantaneous, permanent change
Interrupted – when treatment was not introduced by researcher, for example some historical event
Variations of basic time series design
Addition of a nonequivalent no-treatment control group time series
O O O T O O O & O O O _ O O O
Interrupted time series with removed treatment
If treatment effect is reversible
Quasi-experiments