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Does aggregation produce spuriously high estimates of behavior stability?
Journal of Personality and Social Psychology
|June 1, 1986
Summary
Aggregation is a powerful measurement tool that reduces error and enhances reliability. While concerns about spurious correlations exist, proper application guided by psychometric principles ensures accurate findings.
Area of Science:
- Psychometrics
- Measurement Theory
Background:
- Concerns exist regarding aggregation potentially producing spurious correlations.
- Previous research by Day et al. claimed aggregation artifactually inflates stability coefficients.
Purpose of the Study:
- To critically evaluate arguments against aggregation.
- To re-examine computer-simulated studies on aggregation's effects on stability coefficients.
- To clarify the role of aggregation in measurement error reduction and enhancing psychometric properties.
Main Methods:
- Analysis of arguments concerning aggregation and spurious correlations.
- Re-evaluation of computer-simulated data presented by Day et al.
- Examination of the impact of measurement noise on unaggregated data.
Main Results:
- Arguments against aggregation producing spurious correlations were found to be specious.
- Day et al.'s simulated studies used inappropriate methods and conclusions.
- Aggregation effectively detected empirical relations in data, unlike unaggregated data with high measurement noise.
- Aggregation did not create stability where none existed.
Conclusions:
- Aggregation is a potent tool for reducing measurement error, enhancing generality, and improving stability.
- Aggregation does not inherently foster spurious correlations; its effectiveness depends on proper application.
- Psychometric principles and theoretical considerations are crucial for wise application of aggregation techniques.