Your references are both incomplete and in any
case not necessarily accessible to me.
However, the basic issues here apply to any
nonlinear transformation, so double root
would be included.
An easier way to tackle these problems, and
one consistently overlooked by many users
of statistics, is to use generalized linear
models. So for example, use -glm- with power
link and the error family of choice, presumably
Gaussian.
Nick
[email protected]
Daniel Schneider
> I have a question on statistics and a possible implementation
> in Stata:
>
> I know that generating predicted values from an OLS with a
> log-transformed dependent variable needs some adjustment to generate
> consistent and unbiased values (van Garderen 2001 or Wooldridges
> textbook explain this).
>
> Does anyone know if a similar logic applies to other transformations,
> for example a "root-root" (2x square root) transformation? If
> yes, does
> anyone know how that adjustment would look like and how it would be
> implemented in Stata?
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