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

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

Subject |
Re: st: Quantile regression: determine to which quantile an individual belongs |

Date |
Thu, 18 Apr 2013 12:25:19 +0100 |

We agree on the main point. But -round(whatever, 0.01)- is not an especially good idea because most multiples of 0.01 can not be held exactly in binary and people who don't understand that get into awkward small messes. A more systematic approach is explained at FAQ . . . . . . . . . . Calculating percentile ranks or plotting positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox 7/02 How can I calculate percentile ranks? How can I calculate plotting positions? http://www.stata.com/support/faqs/statistics/percentile-ranks-and-plotting-positions/ Nick njcoxstata@gmail.com On 18 April 2013 12:20, Alex Olssen <alex.olssen@gmail.com> wrote: > I also am unclear on what you wish to achieve. You said that you wanted to > know the quantile of each person's residual. I can suggest a way to > calculate this, but I am unsure why you want it. > > sysuse auto, clear > reg price length > predict res, res > sort res > gen quantile = round(_n/_N, 0.01) On 18/04/13 9:12 PM, Nick Cox wrote: >> I can't see that "the quantile each individual belongs to" is a >> well-defined concept. >> >> Clearly you can work out a percentile rank for each response, without >> regard to the predictors. Or you can see where individual residuals >> lie in the distribution of residuals. >> >> But I don't think that either is what you are seeking. >> >> I am not clear whether you are thinking of a point or an interval, but >> that's secondary. >> >> Stripping it down to a minimal example: We have a quantile regression >> for weight versus height. I am a data point with a certain weight and >> height. What quantile do I belong to? What's your definition? On 18 April 2013 11:50, Maria Juul Hansen <maria@lindely.dk> wrote: >>> Thank you for your comment and reference! >>> I am aware of the endogeneity problem. However, the purpose is not to >>> establish causal effects, just to control for the variables of interest. >>> >>> Do you have any recommendations regarding the problem of identifying the >>> quantiles each individual belongs to? * * 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: Quantile regression: determine to which quantile an individual belongs***From:*Alex Olssen <alex.olssen@gmail.com>

**References**:**Re: Re: st: Quantile regression: determine to which quantile an individual belongs***From:*"Maria Juul Hansen" <maria@lindely.dk>

**Re: Re: st: Quantile regression: determine to which quantile an individual belongs***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Quantile regression: determine to which quantile an individual belongs***From:*Alex Olssen <alex.olssen@gmail.com>

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