<>
I will assume your conditioning variables Y & Z are binary.
In the -auto- dataset, consider that you want to test the difference
in the 5th percentile of the variable "mpg" if price is greater than
$6000 (condition1, variable "pricedummy") or if the car is of foreign
origin (condition 2, variable "foreign"). Then the code below should
do what you want. Also, it might be a good idea to plot the kernel
density estimates when considering tail-behaviour of distributions.
Else if you only have one conditioning variable (case1, cond_var==1;
case 2, cond_var==0), then Martin's code is probably more useful.
/* More on bootstrapping percentiles */
sysuse auto, clear
g pricedummy=(price>6000)
tab pricedummy
cap prog drop pctile_bs
program define pctile_bs, rclass
version 10
syntax varlist(max=3 min=3) [if] [in]
marksample touse
tokenize `varlist'
local first `1'
macro shift
local second `1'
macro shift
local third `1'
_pctile `first' if (`touse' & `second'==1), percentiles(5)
scalar pc1 = r(r1)
_pctile `first' if (`touse' & `third'==1), percentiles(5)
scalar pc2 = r(r1)
return scalar dpc = pc1-pc2
ereturn post, esample(`touse')
end
bootstrap Dpc = r(dpc), reps(2000) dots: pctile_bs mpg foreign pricedummy
twoway (kdensity mpg if foreign==1) (kdensity mpg if pricedummy==1,
legend(order(1 "foreign" 2 "pricedummy")))
/* end */
Simply substitute your variables in the line as follows:
bootstrap Dpc = r(dpc), reps(2000) dots: pctile_bs X Y Z
T
--- References ---
Statalist discussion:
http://www.stata.com/statalist/archive/2004-02/msg00618.html
On Wed, Jun 10, 2009 at 4:44 PM, Martin Weiss<[email protected]> wrote:
>
> <>
>
> Try:
>
> *************
> clear*
> set obs 10000
> capt prog drop differ
>
> gen x= rnormal()
>
> /*no systematic difference btw
> groups
> THIS IS equivalent to your
> Y and Z conditions*/
> gen condition=runiform()<0.5
>
> pr differ, rclass
> vers 10.1
> qui su x if /*
> */ condition==0,/*
> */ det
> loc first=r(p5)
> qui su x if /*
> */ condition==1,/*
> */ det
> ret sca diff = r(p5)-`first'
> end
>
> bs diff=r(diff), /*
> */ reps(200): differ
>
> *************
>
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected] [mailto:[email protected]] Im Auftrag von Susanne Neckermann
> Gesendet: Mittwoch, 10. Juni 2009 17:38
> An: [email protected]
> Betreff: Re: st: test difference in quintiles
>
> Dear T
>
> thank you very much for the message!!
> I am a real beginner with Stata and I have to admit that I do not
> quite understand how to transfer the code to my case.
> I have a variable X that I observe under two conditions Y and Z. I
> want to see if the fifth percentile of variable X in condition Y is
> different from the fifth percentile of X in condition Z.
>
> Thank you so much for your input!!
> Best
> Susanne
>
> On 10-Jun-09, at 5:26 PM, Tirthankar Chakravarty wrote:
>
>> <>
>>
>> This is a variation of previous advice:
>> http://www.stata.com/statalist/archive/2009-05/msg00311.html
>>
>> I believe you want to test the significance of the difference of the
>> 5th percentile for two variables using a bootstrap. If this is the
>> case, then the code below applies:
>>
>> /* Bootstrap the difference of percentiles */
>> clear
>> webuse nlswork, clear
>> keep idcode year ttl_exp
>> reshape wide ttl_exp, i(idcode) j(year)
>>
>> cap prog drop pctile_bs
>> program define pctile_bs, rclass
>> version 10
>> syntax varlist(max=2 min=2) [if] [in]
>> marksample touse
>> tokenize `varlist'
>> local first `1'
>> macro shift
>> local second `*'
>> _pctile `first' if `touse', percentiles(5)
>> scalar pc1 = r(r1)
>> _pctile `second' if `touse', percentiles(5)
>> scalar pc2 = r(r1)
>> return scalar dpc = pc1-pc2
>> ereturn post, esample(`touse')
>> end
>> bootstrap Dpc = r(dpc), reps(2000) dots: pctile_bs ttl_exp68
>> ttl_exp69
>> /* End */
>>
>> Please also see the reference about pivotal statistics in a bootstrap
>> from the previous message.
>>
>> T
>>
>>
>> On Wed, Jun 10, 2009 at 3:57 PM, Susanne
>> Neckermann<[email protected]> wrote:
>>> Hi!
>>>
>>> I want to test whether the difference in the fifth percentile of two
>>> distributions is significant.
>>> In principle, this test should be similar to the "median" (thats
>>> the name of
>>> the command) test already implemented in Stata, but unfortunately I
>>> cannot
>>> program .ado files and I could not find a user-written procedure.
>>> Any idea how to go about this?
>>> P.S. the number of observations in the fifth percentile is pretty low
>>> (around 6), so one might have to use something with bootstrap or
>>> permutations.
>>>
>>> Thank you so much in advance
>>> susanne
>>>
>>>
>>>
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/statalist/faq
>>> * http://www.ats.ucla.edu/stat/stata/
>>>
>>
>>
>>
>> --
>> To every ω-consistent recursive class κ of formulae there correspond
>> recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
>> belongs to Flg(κ) (where v is the free variable of r).
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/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/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/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
