Download
1 / 28
290 likes | 430 Views
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?
E N D
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.
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.
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.
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.
1.0 1.0 0.8 0.8 0.6 0.6 Test-retest coefficient Test-retest coefficient 0.4 0.4 0.2 0.2 0.0 0.0 0 5 10 15 20 25 30 0 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. 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 Continuity 0.2 0.0 -0.2 5 10 15 20 Age Empirical continuity function for attachment security (Fraley, 2002).
Rank-order and mean-level stability are statistically independent ways to investigate stability and change.
Trait score Time
Trait score Time
Trait score Time
Trait score Time
Time series intervention designs are designed to examine the change in an attribute before and after a specific event takes place.
Multi-level modeling • Multi-level modeling (aka hierarchical linear modeling or HLM) is a method that is used to combine within-person associations and between-person differences.
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. 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.
