Application of the Pattern-Mixture Latent Trajectory Model in an Epidemiological Study with Non-Ignorable Missingness.

@article{Dodge2008ApplicationOT,
  title={Application of the Pattern-Mixture Latent Trajectory Model in an Epidemiological Study with Non-Ignorable Missingness.},
  author={Hiroko H. Dodge and Changyu Shen and Mary Ganguli},
  journal={Journal of data science : JDS},
  year={2008},
  volume={6 2},
  pages={
          247-259
        }
}
In longitudinal studies where the same individuals are followed over time, bias caused by unobserved data raises a serious concern, particularly when the data are missing in a non-ignorable manner. One approach to deal with non-ignorable missing data is a pattern mixture model. In this paper, we combine the pattern mixture model with latent trajectory analysis using the SAS TRAJ procedure, which offers a practical solution to many problems of the same nature. Our model assumes a stochastic… CONTINUE READING

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