dssg / after-hours

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Restructure generation of longitudinal data #6

Open nsmader opened 11 years ago

nsmader commented 11 years ago

Improve coding structure for generating longitudinal outcomes, e.g. building a growth model starting with an initialized outcome, and building later scores through lagged values, demographic, and latent student factor predictors.

This structure should (if possible) be made general to all outcome types (having a linear, continuously-valued latent value at its core) which can be left as a continuous outcome, or given a non-linear transformation ex post.