1. Experimental Design: One-Way Correlated Samples Design
Chapter 12
Experimental Design: One-Way Correlated Samples Design
Fundamentals of Behavioral Research

2. Experimental Design: One-Way Correlated Samples Design
Advantages and limitations
Comparing two groups
Comparing t-test to ANOVA
Comparing more than two groups
Fundamentals of Behavioral Research

3. Advantages and limitations
One-way correlated samples
One-way = 1 IV
Correlated samples = no random assignment
Each score in one group (condition) is paired with a score in the other group(s) (condition(s))
Advantages
Can reduce systematic error (confounding)
Can reduce random error (due to indiv diff)
Limitations
Creating pairs of participant scores may be difficult
Repeated measurements can create methodological concerns
Fundamentals of Behavioral Research

4. Advantages and limitations
Natural pairs
Participants’ scores paired for some natural reason
Matched pairs
Participants’ scores paired because researcher matches them on some variable
Repeated measures
Participants’ scores paired because they come from the same participants
Objective is to reduce sources of extraneous variability
Fundamentals of Behavioral Research

5. Advantages and limitations
Advantages of repeated measures design
Controls EVs due to individual differences
Requires fewer participants
Appropriate for studying questions that involve repeated exposure/testing
Appropriate for longitudinal research
Fundamentals of Behavioral Research

6. Advantages and limitations
Methodological issues of repeated measures design
Carryover effects
Transient
Permanent
Sensitization
Carryover effects can often be controlled by:
Randomized order of conditions
counterbalancing
Fundamentals of Behavioral Research

7. Advantages and limitations
Comparing repeated measures design to independent samples design
Effect on random error and inferential statistic
Effect on degrees of freedom
Consider the net effect
Fundamentals of Behavioral Research

8. Fundamentals of Behavioral Research
Comparing two groups
Random sampling
Paired assignment to 2 groups (conditions)
1 IV with 2 levels
Let’s try an experiment involving the Stroop effect
Go to the following website:
Fundamentals of Behavioral Research

9. Fundamentals of Behavioral Research
Comparing two groups
variability within groups (error variability) = random error (extraneous variables)
variability between groups = systematic error (confounds) + systematic variability (effect of IV)
Goals:
Reduce random error
Eliminate systematic error
Maximize systematic variability through manipulation of IV
Fundamentals of Behavioral Research

10. Comparing t-test to ANOVA
Correlated samples t-test
Limited to 2 groups
Independent samples Analysis of Variance (ANOVA)
2 or more groups
Both parametric tests
Require assumptions of:
Normality
Homogeneity of variance
Fundamentals of Behavioral Research

11. Comparing t-test to ANOVA
Correlated samples t-test
difference between the 2 group means
t =
standard error of the difference between means
t values when null hypothesis is true
t values when null hypothesis is false
Larger the t (pos or neg), the lower the probability that the difference is simply due to chance
Alpha level and decision-making
Fundamentals of Behavioral Research

12. Comparing t-test to ANOVA
Correlated samples ANOVA
variability between the two groups
F =
error variability
F values when null hypothesis is true
F values when null hypothesis is false
Larger the F, the lower the probability that the difference is simply due to chance
Alpha level and decision-making
Fundamentals of Behavioral Research

13. Comparing more than 2 groups
Addition of groups often clarifies relationship between IV and DV
ANOVA to determine effect
A priori specific comparison test
Does not require significant F
post hoc specific comparison test
Does require significant F
Fundamentals of Behavioral Research

14. Fundamentals of Behavioral Research
Summary
Correlated samples design
Random sampling
Paired assignment
Natural pairs
Matched pairs
Repeated measures
Paired assignment designed to reduce random error
Manipulation of IV
Analyzed with t-test or ANOVA
Fundamentals of Behavioral Research