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From |
"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it> |

To |
<statalist@hsphsun2.harvard.edu> |

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

Date |
Mon, 17 Dec 2012 16:17:26 +0100 |

Laura replied to my previous comment: @ 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? The main meaning of my example is that you cannot be sure, after invoking -robust-, that heteroskedasticity is automatically removed. In other words, homoskedasticity should be checked graphically even after - robust -. I would also test whether or not your OLS model suffers from omitted variable bias (-estat ovtest-), which is a more serious issue than heteroskedasticity. Best regards, Carlo Dott. Carlo Lazzaro Studio di Economia Sanitaria Via Stefanardo da Vimercate, 19 20128 Milano Tel/fax: 02/26000516 Portatile: 335/6786741 e-mail: carlo.lazzaro@tiscalinet.it carlo.lazzaro@tin.it The main meaning of my example was that you cannot be sure, after invoking -robust-, that heteroskedasticity is automatically removed. In other words, homoskedasticity should be checked graphically even after - robust -. I would also test whether or not your OLS model suffers from omitted variable bias (-estat ovtest-), which is a more serious issue than heteroskedasticity. Best regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Laura R. Inviato: lunedì 17 dicembre 2012 15:29 A: statalist@hsphsun2.harvard.edu Oggetto: Re: st: OLS assumptions not met: transformation, gls, or glm as solutions? 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. Laura * * 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/ * * 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/

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

**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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