Abstract
D. J. Bauer and P. J. Curran (2003) raised some interesting issues with respect to mixture models of growth curves. Many useful lessons can be learned from their work, and more can be learned by extending the inquiry in related directions. These lessons involve the following issues: (a) what a mixture distribution looks like, (b) the meaning of the term homogeneous distribution, (c) the importance of model checking, (d) advantages and disadvantages of using mixtures and similar procedures to approximate complicated distributions, and (e) intrinsic versus nonintrinsic transformability.

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