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<div class="">Dear Shu,</div>
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<div class="">Tom Snijders, Mark Pickup and myself did something similar for a paper using distance as a dyadic covariate:</div>
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<div style="line-height: 1.35; padding-left: 2em; text-indent:-2em;" class="csl-bib-body">
<div class="csl-entry">Manger, Mark S., Mark A. Pickup, and Tom A. B. Snijders. 2012. “A Hierarchy of Preferences: A Longitudinal Network Analysis Approach to PTA Formation.”
<i class="">Journal of Conflict Resolution</i> 56(5): 852–878.</div>
<span class="Z3988" title="url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fzotero.org%3A2&rft_id=info%3Adoi%2F10.1177%2F0022002712438351&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A%20Hierarchy%20of%20Preferences%3A%20A%20Longitudinal%20Network%20Analysis%20Approach%20to%20PTA%20Formation&rft.jtitle=Journal%20of%20Conflict%20Resolution&rft.volume=56&rft.issue=5&rft.aufirst=Mark%20S.&rft.aulast=Manger&rft.au=Mark%20S.%20Manger&rft.au=Mark%20A.%20Pickup&rft.au=Tom%20A.%20B.%20Snijders&rft.date=2012&rft.pages=852-878&rft.spage=852&rft.epage=878"></span></div>
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<div class="">If you don’t want to recalculate the distances from latitude and longitude, the data for distances between 225 countries and their capitals is from CEPII and available here: <a href="http://www.cepii.fr/CEPII/en/bdd_modele/presentation.asp?id=6" class="">http://www.cepii.fr/CEPII/en/bdd_modele/presentation.asp?id=6</a></div>
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<div class="">Best,</div>
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<div class="">Mark</div>
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Associate Professor of Political Economy and Global Affairs</span></p>
<p class="MsoNormal" style="color: rgb(0, 0, 0); font-family: Helvetica;"><span lang="EN-CA" style="font-size: 7.5pt; font-family: Arial;" class="">Munk School of Global Affairs & Department of Political Science | University of Toronto<br class="">
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<div class="">On Oct 30, 2014, at 03:09, Christian Steglich <<a href="mailto:c.e.g.steglich@rug.nl" class="">c.e.g.steglich@rug.nl</a>> wrote:</div>
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<div class="moz-cite-prefix">Dear Shu He,<br class="">
as I see it, the best way to handle this would be to calculate a matrix of geographical distances from your coordinates independent of RSiena (directly in R), and use this matrix as a dyadic covariate.<br class="">
Hope that helps,<br class="">
Christian<br class="">
<br class="">
<br class="">
On 29-Oct-14 22:10, Shu He wrote:<br class="">
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<blockquote cite="mid:CAM_sWHrzuVeWhxMRcHp8OrRChc4J+cdz7Bf=sBJKptFDVNGOvA@mail.gmail.com" type="cite" class="">
<div dir="ltr" class="">Dear Professor,
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<div class="">I have a question with the covariate-similarity effect. In the RSiena Manual, I think that the original RSiena program uses the difference between two actors to measure the dissimilarity. However, in my dataset, I want to measure the location
distance between two actors. Since my location data includes longitude and latitude data for each point, I think that I cannot directly use the effect function in the RSiena. I opened the CovariateSimilarityEffect.cpp, it seems that there is a function as
similarity( , ). I don't quite understand where the function is from. Could you help me with it? Thank you very much!</div>
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<div class="">Best,</div>
<div class="">Shu<br clear="all" class="">
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</div>
-- <br class="">
<div class="">Shu He<br class="">
Ph.D. Student</div>
<div class="">Department of Economics</div>
<div class="">University of Texas at Austin</div>
<div class="">1-512-983-7578</div>
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<pre wrap="" class="">_______________________________________________
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<pre class="moz-signature" cols="72">--
_ __ ___ ____ ___ __ _ __ ___ ____ ___ __ _
Christian Steglich, University of Groningen
Faculty of Behavioural and Social Sciences
Grote Rozenstraat 31, NL-9712 TG Groningen
<a class="moz-txt-link-freetext" href="http://www.gmw.rug.nl/~steglich/">http://www.gmw.rug.nl/~steglich/</a>
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