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Re: st: Re: Difference between -spearman- and -pwcorr- with ranked variables


From   Owen Gallupe <[email protected]>
To   [email protected]
Subject   Re: st: Re: Difference between -spearman- and -pwcorr- with ranked variables
Date   Mon, 23 Sep 2013 17:18:38 -0400

Thank you for your response, Joseph. That really clarifies things nicely for me!

Owen





On Mon, Sep 23, 2013 at 2:43 AM, Joseph Coveney <[email protected]> wrote:
> Owen Gallupe wrote:
>
> My understanding is that Spearman correlations are simply Pearson
> correlations using ranked data. However, when I run the spearman
> command I get different results from when I convert the variables to
> ranks and then run the pwcorr command with the ranks.
>
> . spearman var1 var2
>
> rho = -0.0112, p = 0.5642
>
>
> . egen rankvar1 = rank(var1)
> . egen rankvar2 = rank(var2)
>
> . pwcorr rankvar1 rankvar2, sig
>
> r = -0.0100, p = 0.6058
>
> I suspect it has something to do with the way I created the ranked
> variables, but I'm not sure.
>
> If someone could point me in the right direction, I would really appreciate it!
>
> --------------------------------------------------------------------------------
>
> You rank the pooled variables.  See below.
>
> Joseph Coveney
>
>
> . sysuse auto, clear
> (1978 Automobile Data)
>
> . rename price var1
>
> . rename gear_ratio var2
>
> . quietly reshape long var, i(make) j(dummy)
>
> . egen double rank = rank(var)
>
> . quietly reshape wide var rank, i(make) j(dummy)
>
> . spearman var1 var2
>
>  Number of obs =      74
> Spearman's rho =      -0.2525
>
> Test of Ho: var1 and var2 are independent
>     Prob > |t| =       0.0299
>
> . pwcorr rank1 rank2, sig
>
>              |    rank1    rank2
> -------------+------------------
>        rank1 |   1.0000
>              |
>              |
>        rank2 |  -0.2525   1.0000
>              |   0.0299
>              |
>
> .
>
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