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From |
Maarten buis <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Inverse hyperbolic sine transformation |

Date |
Fri, 29 Jan 2010 17:06:52 +0000 (GMT) |

--- On Fri, 29/1/10, Stephane Mahuteau <[email protected]> wrote: > I estimated a double hurdle model using the Inverse > Hyperbolic sine transformation to my dependent variable in > the second hurdle. From these results I'd like to compute > the expected values of this dependent variable y (given > y>0) rather than using the expected values of the > transformed variable. From what I read in the Cameron & > Trivedi "Microeconometrics using stata" applied to some > other transformations on non linear models, it looks like > getting the expected values of the variable y from the > estimated values of the transformed y would be more complex > than just inversing the transformation. Would anybody have > any idea on how I can perform this? Is it ok to just invert > the transformation? The problem is that that is a non-linear transformation. You can easily see what happens in a simple model: predicting the variable by its mean: *-------- begin example --------- sysuse nlsw88, clear gen asinh_w = asinh(wage) sum asinh_w di sinh(r(mean)) sum wage *-------- end example ------------ You can see here that first transforming the variable and than backtransforming the mean, will not result in the mean of the original variable. Probably the easiest solution to implement, but hard to explain to your audience, is that if you log transform the dependent variable you could interpret the backtransformed predicted values as Geometric means. Alternatively, you can include the transformation as a link function in the likelihood, as happens in -glm-like models. Then you are modeling the mean directly, so the predicted values do represent the conditional means. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Inverse hyperbolic sine transformation***From:*Austin Nichols <[email protected]>

**References**:**st: Inverse hyperbolic sine transformation***From:*Stephane Mahuteau <[email protected]>

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