Longitudinal Research: The Theory, Design, and Analysis of Change
Abstract
The purpose of this article is to present cutting-edge research on issues relating to the theory, design, and analysis of change. Rather than a highly technical review, our goal is to provide management scholars with a relatively nontechnical single source useful for helping them develop and evaluate longitudinal research. Toward that end, we provide readers with “checklists” of issues to consider when theorizing and designing a longitudinal study. We also discuss the trade-offs among analytic strategies (repeated measures general linear model, random coefficient modeling, and latent growth modeling), circumstances in which such methods are most appropriate, and ways to analyze data when one is using each approach.
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It is possible to find relationships observed cross-sectionally to be in direct contrast to relationships observed across time.
“It is possible to find relationships observed cross-sectionally to be in direct contrast to relationships observed across time (Ployhart & Vandenberg, 2010).”
From Psychological Processes Underlying the Impact of Gender-Related Discrimination on Psychological Distress in Transgender and Gender Nonconforming People. (2019) · cites this paper as Ployhart & Vandenberg, 2010
Longitudinal studies allow for causal conclusions to be drawn.
“This is why it is reasonable to design a research project that includes longitudinal studies, which record the process of change over time [20], allowing for causal conclusions to be drawn [21].”
Two waves of measurement are not considered longitudinal studies.
“Note that two waves of measurement are not considered longitudinal studies [82,83].”
From What Do We Mean When We Talk about Trust in Social Media? A Systematic Review (2023) · cites this paper as [83]
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- Authors
- Ployhart, R. E., & Vandenberg, R. J.
- Affiliations
- University of South Carolina (US)
- University of Georgia (US)
- Corresponding author
- Ployhart, Robert E.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 2009-12-28
- Volume
- 36
- Issue
- 1
- Pages
- 94-120
- ISSN
- 0149-2063 (ISSN-L)
- 1557-1211
- OpenAlex
- W2141370332
- Cited by
- 1,496
- References
- 62
- Citations by year
- 2026: 155 · 2025: 139 · 2024: 117 · 2023: 109 · 2022: 116 · 2021: 122 · 2020: 84 · 2019: 98 · 2018: 92 · 2017: 85 · 2016: 82 · 2015: 70 · 2014: 77 · 2013: 58 · 2012: 53
- FWCI
- 24.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Management (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Business Strategies and Management Research
- Social Sciences › Decision Sciences › Information Systems and Management › Business and Management Studies
- Keywords
- longitudinal study, change over time, research design, theory development, latent growth curve models
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