Longitudinal Research methods in personality
psychology
Longitudinal Research
• One of the “big questions” in personality psychology
concerns stability and change. How do personality
processes play out over time?
– How does self-esteem change over time?
– Are children who are relatively insecure early in
life likely to grow up to be relatively insecure as
adults?
– How does an event like divorce affect personality
functioning?
• To answer these questions, different kinds of
research designs are needed.
• However, they each have one thing in common.
• Namely, they involve treating time as a fundamental
element of the research design.
Normative Stability
• Normative or mean-level stability concerns the
extent to which the average levels of a trait or
attribute change or remain the same over time.
• Two ways to approach questions about normative
stability.
• Cross-sectional design. Participants of varying
ages are studied.
– Acquire a sample of people who vary in age.
– Assess the attribute(s) in question.
– Study the average/mean of the attribute as a
function of age.
Robins, Trzesniewski, Tracy, Gosling, & Potter (2002)
– Pros: Relatively efficient and economical
– Cons: Cohort effects are confounded with true
developmental effects.
• Cohort design. Participants of the same age, but
across different cohorts, are studied.
Twenge & Foster (2010)
• Longitudinal design. The same people are followed
across multiple time points.
– Pros: Allows an in-depth examination of how the
same people change or stay the same over time.
– Cons: Extraordinarily time consuming and
expensive.
Example
• Orth, Trzesniewski, and Robins (2010). Journal of
Personality and Social Psychology
• American’s Changing Lives study. Includes 4
assessments across a 16-year period of a nationally
representative sample of over 3600 people ranging in
age from 25 to 104 years.
• Rank-order stability concerns the extent to which
the rank order of individual differences in an attribute
are preserved over time.
– Assess the attribute in a sample of people at time
1.
– Assess the same people again at Time 2.
– Compute a correlation (test-retest correlation)
between the two measures of the attribute.
Trait
Age 18 to Age 22 test-retest
correlation
Extraversion
.63
Agreeableness
.60
Conscientiousness
.59
Neuroticism
.53
Openness
.70
Robins, Fraley, Roberts, & Trzesniewski (2001)
• It is also possible to study continuity functions.
Continuity functions illustrate the test-retest
correlations over varying test-retest intervals.
• Correlation between Time 1 and Time 1, Time 1 and
Time 2, Time 1 and Time 3, Time 1 and Time 4, and
so on.
5
10
15
20
25
30
In this scenario, the test-retest
correlation gets smaller and smaller
over time. It approaches 0 in the
limit.
1.0
0.8
0.6
0.4
0.2
0.0
Test-retest coefficient
1.0
0.8
0.6
0.4
0.2
0.0
Test-retest coefficient
0
0
5
10
15
20
25
30
In this scenario, the test-retest
correlation gets smaller and smaller
at first, but then stabilizes as a value
of .24. The stability over 10 months
vs. 20 months is identical.
1.0
0.8
0.6
0.4
-0.2
0.0
0.2
Continuity
5
10
Age
Empirical continuity function for
attachment security (Fraley, 2002).
15
20
• Rank-order and mean-level stability are statistically
independent ways to investigate stability and change.
No rank-order
stability
No changes in
mean-level
stability
Changes in
mean-level
stability
High rank-order
stability
Time
Trait score
Time
Trait score
Time
Trait score
Time
Trait score
• Time series intervention designs are designed to
examine the change in an attribute before and after a
specific event takes place.
Lucas (2009)
Multi-level modeling
• Multi-level modeling (aka hierarchical linear
modeling or HLM) is a method that is used to
combine within-person associations and betweenperson differences.
Stress
Depression
1
3
3
2
2
2
3
3
3
4
6
5
5
8
9
6
2
5
7
3
4
6
4
2
Depression
8
Day
2
3
4
5
Stress
r = .84
6
7
8
Person
Cor
Group
1
.84
F
2
.78
F
In this example we see that the
correlation between stress and
depressive symptoms is positive
for some people, but not others.
Thus, there is variation in those
associations.
3
.65
F
4
.01
M
5
.04
M
6
-.02
M
7
.03
M
Moreover, that variation can be
partly understood via sex. In
this example, women tend to
experience these two affects
together. Whereas men’s
experience of stress is less
strongly related to their
experience of depression.