Re: st: Grid Search in a Log Plus Constant Model

[Sebastian Baumeister <baum_statal@web.de>]

hi paul,
i am working on a similar problem and the literature (mostly by Manning 
and Mullahy) suggests  two things. 1.  OLS on ln(costs): costs are often 
logged to reduce skewness, but this necessitates a retransformation to 
put the estimates back on the original (unlogged) scale. This 
retransformation can lead to biases if heteroscedasticity is present on 
the log scale - thus requiring "smearing" (Manning 1998). Alternatively, 
some have recommended using generalized linear models (with gamma 
distribution and log link), which do not require retransformations of 
the cost dependent variable after estimation (Buntin et al. 2005, 
Manning et al 2005).


Manning WG. The logged dependent variable, heteroscedasticity, and the 
retransformation problem. J Health Econ 1998;17:283-95.
Manning WG, Basu A, Mullahy J. Generalized modeling approaches to risk 
adjustment of skewed outcomes data. J Health Econ 2005;24:465-88.
Buntin MB, Zaslavsky AM. Too much ado about two-part models and 
transformation? Comparing methods of modeling Medicare expenditures. J 
Health Econ 2004;23:525-42.

paul d jacobs schrieb:


> I am working with health data (MEPS) where
> out-of-pocket medical expenses (OOP) are a dependent
> variable in an OLS regression.  Because of the
> positive skewness of such a variable, I would like to
> use a normalizing transformation, i.e. the log of OOP.
> However, because of the many zero observations for
> OOP, the options are to either add a constant to OOP,
> (some have used $1 arbitrarily), or to model the data
> separately for the zeroes and the positive values,
> which I'd rather not do.  (I have also considered the
> square root transformation, etc., but would like to
> test out the results using a log-constant).
>
> My question is:  do you know of a method for searching
> for the optimal constant to add to a variable so that
> a log-transformation produces the optimal result?  Deb
> et al. (2005), suggest a 'grid search' for this value
> (see link below for document).  I know that grid
> searches are used in the context of maximum
> likelihood; is this a similar process?  Would running
> the model with different values and comparing R2s and
> standard errors be more appropriate?
>
> Thanks very much for your time!
>
> Paul Jacobs
> Ph.D. Candidate, Economics
> American University
>
>
> Link to Deb, et al presentation:
> harrisschool.uchicago.edu/faculty/articles/iHEAminicourse.pdf 
>
>
>
> ____________________________________________________________________________________
> Sponsored Link
>
> Get a free Motorola Razr! Today Only! 
> Choose Cingular, Sprint, Verizon, Alltel, or T-Mobile. 
> http://www.letstalk.com/inlink.htm?to=592913
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>
>  
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/