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Please excuse my naiveté as I am still somewhat new to SNA, but when you talk about log transformations on distance networks,  what are you transforming.  Are you talking about taking the matrix down to an eigenvalue (or trace) measurement and using it as a DV or IV,  or leaving the DV is a matrix form and transforming the individual ties? This is interesting to me because I have attempted the former on a dataset I collected with Family Owned Businesses and was never happy with the effect sizes. In that study I used different degree measurements (different types of networks) at level one and characteristics of the Family system and business system at level two (i.e. a multilevel model).  This might have been the problem I was facing.

Thanks
Brian



Brian Distelberg Ph.D.

Department of Counseling and Family Sciences
113 Griggs Hall
Loma Linda University
Loma Linda, CA 92350

Office: (909) 558-4547 x47019
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-----Original Message-----
From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Vladimir Batagelj
Sent: Wednesday, March 30, 2011 6:49 AM
To: [log in to unmask]
Subject: Re: [SOCNET] logging distance networks

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<<<-------- Zachary P Neal-------->>>
> *****  To join INSNA, visit http://www.insna.org  *****
>
> Barry,
>
> I certainly agree that it typically makes sense to log distances.
> But, I'm curious about your rationale for using log10 rather than loge
> (natural log), which seems more common.  I don't think I've ever seen
> a comparison or an argument about which transformation is more
> appropriate when predicting interaction as a function of distance, but
> perhaps this work is out there.

  It should be irrelevant since the values are linearly related

    log10 x  =  log10 e  *  ln x

  Vlado

-- 
Vladimir Batagelj, University of Ljubljana, FMF, Department of Mathematics
  Jadranska 19, 1000 Ljubljana, Slovenia
http://vlado.fmf.uni-lj.si

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