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Re: st: Random permutation test for rank-dependence


From   Tobias Morville <[email protected]>
To   [email protected]
Subject   Re: st: Random permutation test for rank-dependence
Date   Tue, 29 Jan 2013 15:05:15 +0100

Hi Maarten. Yes i did.

If i understand it correctly, -predict- gives me the predicted values
(and se.) for the entire model, and not the parameter values of the
regressors.

2013/1/29 Maarten Buis <[email protected]>:
> Did you take a look at -predict-?
>
> On Tue, Jan 29, 2013 at 9:36 AM, Tobias Morville wrote:
>> Hi Nick. Thanks for pointing out the -permute- command, don't know how
>> i've missed it.
>>
>> Im still on bare ground with regard to Q1. If anyone has any input,
>> ill appriciate it.
>>
>> best,
>> Tobias
>>
>> 2013/1/28 Nick Cox <[email protected]>:
>>> I haven't tried to understand all this, but your opening to Q2 is
>>> incomplete. Stata has a -permute- command that transcends the specific
>>> oldstyle testing commands you mention.
>>>
>>> I won't be able to add more, but if you overlooked that, you probably
>>> overlooked other things too.
>>>
>>> Nick
>>>
>>> On Mon, Jan 28, 2013 at 5:23 PM, Tobias Morville
>>> <[email protected]> wrote:
>>>
>>>> i have a question regarding random permutation testing in stata.
>>>>
>>>> I need to test for rank-dependence and sign-dependence, over several
>>>> variables within each subject, and across subjects. Doing that i have
>>>> two basic questions. But first, this is the (simplified) model I'm
>>>> estimating:
>>>>
>>>>  Model: -xtprobit dummy var1 var2 var3 var1*var2 var1*var3, re-
>>>>
>>>> And I'm doing this for 18 different subjects, that each have ~250
>>>> observations. They are all stacked onto each other, in one dataset.
>>>>
>>>> Q1: How [...] do i add parameter coefficients as new
>>>> variables? I've googled this, and stumbled upon -estimates- module and
>>>> -statsby-. But none of them really satisfy my needs.
>>>>
>>>> What i really want, is a new variable (in a column) where parameter
>>>> estimates are continuously reported to. Lets say subject_1 has 250
>>>> trials, then I want 250 values of b1 - which i assume is the parameter
>>>> coefficient of var1 - to be my new variable. And so forth with all the
>>>> other subjects, resulting in my new b1-parameter-value-variable having
>>>> 18*~250 observations.
>>>>
>>>> I've done, -Estimates store- just produces b1 b2 b3 b4 b5, a "group
>>>> level" coefficient for each of the variables (and interaction terms),
>>>> which is not really satisfying for my need when wanting to do a random
>>>> permutation test.
>>>>
>>>> Q2: For the random permutation test, stata has two non-parametric
>>>> choices. -Ranksum- and -Median-, where the first only allows testing
>>>> between two groups and the latter is an equility-of-median test, which
>>>> is not really useful for me.
>>>>
>>>> Basically i would like to do a -ranksum- test, but between all 18
>>>> subjects, which ranksum does not allow. Is there any alternative way
>>>> of doing this?
>>>>
>>>> Background:
>>>>
>>>> I have a variable that is randomly distributed (it's a die) and i want
>>>> to see if the number of eyes on that die affects how people gamble.
>>>> When i include it as a simple regressor, it shows up significant. But
>>>> not knowing if that (not logical - a rational agent should know its
>>>> random) weigh on the die, is the same across subjects, and within each
>>>> subject. Basically, i want to be able to say something about "how
>>>> much" the die weights for different subjects, but because its
>>>> non-linear, i can't compare a coefficient value of 2 to 4, and say its
>>>> the double effect. Neither can i say that subject 1's coefficient of
>>>> 5, is a lower effect of subject 2's coefficient of 7. And i need to
>>>> find out, if i can at least, say something about the rank of the
>>>> coefficient estimates.
>>>>
>>>> Hope you can help me out as I'm rather lost!
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>
>
>
> --
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
>
> http://www.maartenbuis.nl
> ---------------------------------
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