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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Mon, 17 Dec 2012 14:43:38 +0000 |

On the question directed at me: Let's turn this round. Why do you think that adding an indicator variable to the model will capture heteroskedasticity? It sounds as if you need a different model. David gave several very useful pointers. Nick On Mon, Dec 17, 2012 at 2:29 PM, Laura R. <laura.roh@googlemail.com> wrote: > Thank you very much for your help so far. > > Please let me reply one by one. > > @ Carlo: I conducted your example and with my data it seems the same, > the -robust- option does not seem to change the graphical pictures or > the tests (-estat hettest-, -iqr-) much. So the robust option has to > be visible in the graphics and the tests, that it induced > homoskedasticity? > > > @ Nick: > As to the equality of variances between the cases from the 2 surveys, > a referee seems concerned about inferences one can make from the > descriptive statistics. Therefore, I would like to use -sdtest- to see > whether variances are the same in the two samples. > And for the regression, I think that adding the year-dummy would be > enough to account for it? > > The variances of the regression residuals are another thing, this is > for model validation. Yes, there I plotted the residuals, and the > variances seem to become larger as the dep. var. becomes larger, > especially the lower bound (with negative values) changes. > > > @ Maarten: > So you would not worry about heteroskedasticity or the distribution of > errors. What would you write in the paper then? "There is > heteroskedasticity and non-normal error distribution, but I still use > OLS because ...?" I am very curious, because I would like to keep the > OLS > > @ Maarten & David: > About linearity: as independent variables, I mainly have categorical > variables. So - scatter y x- or -graph matrix y x x- does not help > much, because the cases are only on the lines for 0 and 1. How can I > see whether I have a linear relationship between y and x, if x is > categorical? > > @ David: > Yes, I think about transformation, and will read again about > interpretation. Still, just having minutes to interpret would be > easier, also for readers which are not so familiar with > transformation. Also, I am not sure whether OLS with transformed > dependent variable, or -glm- without transformed variable would be > better. * * 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>

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