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22 - Dealing with Repeated Measures

Design Decisions and Analytic Strategies for Over-Time Data*

from Part IV - Understanding What Your Data Are Telling You About Psychological Processes

Published online by Cambridge University Press:  12 December 2024

By
Amie M. Gordon  and
Katherine R. Thorson
Edited by
Harry T. Reis ,
Tessa West  and
Charles M. Judd
Harry T. Reis
Affiliation:
University of Rochester, New York
Tessa West
Affiliation:
New York University
Charles M. Judd
Affiliation:
University of Colorado Boulder
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Summary

Over-time, repeated measures, or longitudinal data are terms referring to repeated measurements of the same variables within the same unit (e.g., person, family, team, company). Longitudinal data come from many sources, including self-reports, behaviors, observations, and physiology. Researchers collect repeated measures for a variety of reasons, such as wanting to model change in a process over time or wanting to increase measurement reliability. Whatever the reason for data collection, longitudinal methods pose unique challenges and opportunities. This chapter has three main goals: (1) to help researchers consider design decisions when developing a longitudinal study, (2) to describe the different decisions researchers have to make when analyzing longitudinal data, and (3) to consider the unique properties of longitudinal designs that researchers should be aware of when designing and analyzing longitudinal studies. We aim to provide a comprehensive overview of the major issues that researchers should consider, and we also point to more extensive resources.

Keywords

longitudinal datalongitudinal analysisrepeated measuresanalysis of changenonindependencemultilevel modeling

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Handbook of Research Methods in Social and Personality Psychology , pp. 532 - 564
Publisher: Cambridge University Press
Print publication year: 2024

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References

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