Do Different Methods for Modeling Age-Graded Trajectories Yield Consistent and Valid Results?

Data on age-sequenced trajectories of individuals' attributes are used for a growing number of research purposes. However, there is no consensus about which method to use to identify the number of discrete trajectories in a population or to assign individuals to a specific trajectory group. We...

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Bibliographic Details
Published in:The American journal of sociology 2015-05, Vol.120 (6), p.1809-1856
Main Authors: Warren, John R, Luo, Liying, Halpern-Manners, Andrew, Raymo, James M, Palloni, Alberto
Format: Article
Language:English
Subjects:
Group dynamics
Groups
Mathematical models
Membership
Methodology (Data Analysis)
Parameter estimation
Research Methodology
Simulation
Truth
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Summary:Data on age-sequenced trajectories of individuals' attributes are used for a growing number of research purposes. However, there is no consensus about which method to use to identify the number of discrete trajectories in a population or to assign individuals to a specific trajectory group. We modeled real and simulated trajectory data using "naïve" methods, optimal matching, grade of membership models, and three types of finite mixture models. We found that these methods produced inferences about the number of trajectories that frequently differ (1) from and (2) from as represented by simulation parameters. We also found that they differed in the assignment of individuals to trajectory groups. In light of these findings, we argue that researchers should interpret results based on these methods cautiously, neither reifying point estimates about the number of trajectories nor treating individuals' trajectory group assignments as certain.
ISSN:0002-9602
1537-5390
DOI:10.1086/681962