Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: OLS assumptions not met: transformation, gls, or glm as solutions? |

Date |
Tue, 18 Dec 2012 20:02:40 +0100 |

On Tue, Dec 18, 2012 at 7:24 PM, Laura R. wrote: > I thought generalized linear models (this is what I meant with glm) > support different distributions of the dependent variable y, not the > residuals. You are right, it is a model for the conditional distribution of y and not the residuals. This means that the marginal distribution for the dependent variable can deviate considerably from the unconditional distribution that gave your model its name. See: <http://www.maartenbuis.nl/software/margdistfit.html>. This is not a problem, but you do need to take that into account when you diagnose your problem. Only in special cases (e.g. the normal/Gaussian distribution) does the distribution of the residuals correspond to the unconditional distribution. > My dependent variable and the residuals are both right > skewed, so maybe glm with inverse gaussian would be good. Maybe, but I should not get carried away like that. I can very well imagine that it is better in your case to stick to simple linear regression with robust standard errors. I realise that this contradicts some other advise you have been given. This is a sign that you have come at a point where the decision has to be based on the specifics of your study, which means that we can no longer help you. Hope this helps, Maarten --------------------------------- Maarten L. Buis WZB Reichpietschufer 50 10785 Berlin Germany http://www.maartenbuis.nl --------------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"Laura R." <laura.roh@googlemail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"Laura R." <laura.roh@googlemail.com>

**R: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*Ryan Kessler <ryan.kessler.stata@gmail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"Laura R." <laura.roh@googlemail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?***From:*"Laura R." <laura.roh@googlemail.com>

- Prev by Date:
**Re: st: heteroskedasticity between groups, interpretation of -sdtest-** - Next by Date:
**Re: st: how have stata perform and report a likelihood-ratio test after running biprobit** - Previous by thread:
**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?** - Next by thread:
**Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?** - Index(es):