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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Beta values in QREG |

Date |
Mon, 24 Jun 2013 16:04:47 +0200 |

I suspect that the real problem would more often be the standard deviation. By standardizing a variable you change the unit of that variable to have a standard deviation of 1. If the shape of the distribution makes you doubt the usefulness of the mean as a measure of central tendency, then I would be doubly worried about the standard deviation as a measure variability. More generally there is a "clash of logics" between standardizing (where you use the moments) and quantile regression (where you use the percentiles). -- Maarten On Mon, Jun 24, 2013 at 3:36 PM, Scott Holupka <scott.holupka@jhu.edu> wrote: > Thanks. I didn't want to ask for coding help until I was sure it was really > a coding problem and not a more fundamental problem with the approach. So > you're first comment answers my more general question. If I'm understanding > it correctly, your point is why I would want to standardize values using a > measure of central tendency if I already believe my measures are not > normally-distributed, which, after all, is the reason for using > quantile/median regression. > > Scott > > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis > Sent: Saturday, June 22, 2013 3:34 PM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Beta values in QREG > > On Fri, Jun 21, 2013 at 10:03 PM, Scott Holupka wrote: >> Does anyone know if there is a statistical reason why the Stata >> quantile regression program "qreg" does not provide an option for >> producing beta values? I know a question about beta values in qreg >> was raised just a few months ago, and the one response suggested that >> there might be a statistical reason why the option wasn't available, >> but I didn't see anything more definitive. > > The logic behind quantile regression is all about avoiding the first (and > second) moments and replacing those by the more robust quantiles. > So substantively it would not make much sense to bring those moments back in > a quantile regression by standardizing your variables. If you thought that > your data was so problematic that you needed the more robust quantile > regression, then it would be weird to use the non-robust standard deviation > to define the scale of your variable. It is technically possible, but I > would not recommend it. > >> I did try standardizing all of my variables and re-running QREG, as >> had been previously suggested, but the results between the >> unstandardized and standardized models seem so different I'm not sure >> if I did something wrong or if there's a more fundamental reason why the > results don't line up. > > In order for us to be able to judge that we would need to see what you have > done. We cannot spot errors in code you don't show us. > > -- 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/ > > * > * 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/ -- --------------------------------- 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: Beta values in QREG***From:*"Scott Holupka" <scott.holupka@jhu.edu>

**Re: st: Beta values in QREG***From:*Maarten Buis <maartenlbuis@gmail.com>

**RE: st: Beta values in QREG***From:*"Scott Holupka" <scott.holupka@jhu.edu>

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