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Re: st: Quantile regression: determine to which quantile an individual belongs
From
Nick Cox <[email protected]>
To
"[email protected]" <[email protected]>
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
[email protected]
On 18 April 2013 12:20, Alex Olssen <[email protected]> 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 <[email protected]> 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?
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