A discriminant analysis extension to mixed models.

@article{Tomasko1999ADA,
  title={A discriminant analysis extension to mixed models.},
  author={Lisa Tomasko and Ronald W. Helms and Steven Snapinn},
  journal={Statistics in medicine},
  year={1999},
  volume={18 10},
  pages={
          1249-60
        }
}
Discriminant analysis is commonly used to classify an observation into one of two (or more) populations on the basis of correlated measurements. Classical discriminant analysis approaches require complete data for all observations. Our extension enables the use of all available longitudinal data, regardless of completeness. Traditionally a linear discriminant function assumes a common unstructured covariance matrix for both populations, which may be taken from a multivariate model. Here, we can… CONTINUE READING
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