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An Overview of the Autoregressive Latent Trajectory (ALT) Model

  • Kenneth A. BollenEmail author
  • Catherine Zimmer
Chapter

Abstract

Autoregressive cross-lagged models and latent growth curve models are frequently applied to longitudinal or panel data. Though often presented as distinct and sometimes competing methods, the Autoregressive Latent Trajectory (ALT) model (Bollen and Curran, 2004) combines the primary features of each into a single model. This chapter: (1) presents the ALT model, (2) describes the situations when this model is appropriate, (3) provides an empirical example of the ALT model, and (4) gives the reader the input and output from an ALT model run on the empirical example. It concludes with a discussion of the limitations and extensions of the ALT model. Our focus is on repeated measures of continuous variables.

Keywords

Growth Curve Model Full Information Maximum Likelihood Random Slope Random Intercept Autoregressive Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgements

Kenneth Bollen gratefully acknowledges the support from NSF SES 0617276 from NIDA 1-RO1-DA13148-01 & DA013148-05A2. We thank the editors and reviewers for valuable comments and thank Shawn Bauldry for research assistance.

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Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Odum Institute for Research in Social Science and Department of SociologyUniversity of North CarolinaChapel HillUSA
  2. 2.Odum Institute for Research in Social ScienceUniversity of North CarolinaChapel HillUSA

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