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Dear all,

Nate is right: the Siena model has the aim to find out what determines 
tie formation & termination, and not in the first place to express the 
shape of the curves followed by network descriptives over time.

Best,

Tom

-- 
==============================================
Tom A.B. Snijders
Professor of Statistics in the Social Sciences
Nuffield College
University of Oxford

Professor of Statistics and Methodology
Department of Sociology
University of Groningen
http://www.stats.ox.ac.uk/~snijders/
==============================================



On 15/11/2011 21:00, Nate Doogan wrote:
> ---------------------- Information from the mail header -----------------------
> Sender:       Social Networks Discussion Forum<[log in to unmask]>
> Poster:       Nate Doogan<[log in to unmask]>
> Subject:      Re: longitudinal analysis of social network data - need help
> -------------------------------------------------------------------------------
>
> --20cf307ac3ef59aaf104b1cc48a4
> Content-Type: text/plain; charset=ISO-8859-1
>
> *****  To join INSNA, visit http://www.insna.org  *****
>
> Hey Roy.
>
> Personally, I did not precisely understand what you were hoping to model.
> My response is contingent upon the accuracy with which I understood your
> post. HLM might be nice if you were studying multiple groups within which
> dependencies were expected. But you seem to have just one. Measurements
> within each individual would make for a nice level-one, but you can't
> assume that the individuals themselves (level 2) are independent
> observations--you've captured information about the social network
> connecting them, after all.
>
> I will also provide my opinion that Joe's suggestion to use a squared
> density term in a SIENA analysis would not quite model what you expect. The
> SIENA density effect does not model the shape of density over time. You
> would need to make use of time-dummies to capture such an effect, I believe.
>
> Nathan Doogan
> Doctoral Student
> The Ohio State University
>
> On Tue, Nov 15, 2011 at 3:36 PM, Money, Roy<[log in to unmask]>  wrote:
>
>> *****  To join INSNA, visit http://www.insna.org  *****
>>
>> Thanks to Joe and David and Kathleen for your responses.
>> I will look into ORA and Siena as an alternative to HLM.
>> I was hoping to hear from someone about why a multilevel model was not
>> appropriate before taking on another analysis plan.
>> Anyone have any thoughts on that?
>>
>> Roy
>>
>>
>>
>>
>>
>>
>> Hi Roy,
>>
>> I suppose you could run a SIENA model, include both the density parameter
>> as you would normally do, and then add a square of the density parameter to
>> test for the inverted-U shaped relationship you're expecting.
>>
>> Joe
>> Giuseppe (Joe) Labianca
>> Gatton Endowed Associate Professor of Management
>> Gatton College of Business&  Economics
>> LINKS Center for Social Network Analysis
>> University of Kentucky
>> Lexington, KY 40506
>> 859-257-3741 (office)
>> 404-428-4878 (mobile)
>> http://linkscenter.org/
>>
>>
>>
>> On Mon, Nov 14, 2011 at 1:37 PM, Money, Roy<[log in to unmask]<mailto:
>> [log in to unmask]>>  wrote:
>> *****  To join INSNA, visit http://www.insna.org  *****
>>
>> I made a simiilar post to this list last month that garnered only one
>> response so I am trying again.
>>
>> I have 8 waves (at 6 month intervals) of social network data for a
>> interdisciplinary  research consortium of  scientists where the degree
>> centrality measure peaks at wave 4 (18 months), and the geodesic distance
>> bottoms out at that time point.  It does seem like 18 months represents a
>> maximum effect time for  the aggregate network data.
>>
>> Previously I used UCINET to do bootstrapped t tests for particular
>> pair-wise time comparisons but I want to characterize the longer trajectory
>> and the apparent change in slope at 18 months.
>>
>> I also have associated survey response data for which I have used a
>>   discontinuous level-1 HLM individual growth model to test the hypothesis
>> that the slope changes at  time 4 (18 months).
>>
>> I would like to apply a similar analysis to the individual network
>> measures of degree centrality and geodesic distance. However I have not
>> found in my literature searches any references to the analysis of
>>   longitudinal social network data like I am working with.
>>
>> Is a multilevel or HLM analysis an appropriate method to test for
>> quadratic or piecewise non linear change of the individual newtwork
>> measures ?  If not, what would be optimal ways to evaluate this apparent
>> maxing out of the connectivity of the social network about mid way through
>> the consortium history?
>>
>> Thanks for any suggestions or references.
>>
>> Roy  Money
>>
>> Yale University
>>
> _____________________________________________________________________
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> network researchers (http://www.insna.org). To unsubscribe, send
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>
> --20cf307ac3ef59aaf104b1cc48a4
> Content-Type: text/html; charset=ISO-8859-1
> Content-Transfer-Encoding: quoted-printable
>
> *****  To join INSNA, visit http://www.insna.org  *****
> <div>Hey Roy.</div><div><br></div>Personally, I did not precisely understan=
> d what you were hoping to model. My response is contingent upon the accurac=
> y with which I understood your post. HLM might be nice if you were studying=
>   multiple groups within which dependencies were expected. But you seem to h=
> ave just one. Measurements within each individual would make for a nice lev=
> el-one, but you can&#39;t assume that the individuals themselves (level 2) =
> are independent observations--you&#39;ve captured information about the soc=
> ial network connecting them, after all.<div>
>
> <br></div><div>I will also provide my opinion that Joe&#39;s suggestion to =
> use a squared density term in a SIENA analysis would not quite model what y=
> ou expect. The SIENA density effect does not model the shape of density ove=
> r time. You would need to make use of time-dummies to capture such an effec=
> t, I believe.</div>
>
> <div><br></div><div>Nathan Doogan</div><div>Doctoral Student</div><div>The =
> Ohio State University<br><br><div class=3D"gmail_quote">On Tue, Nov 15, 201=
> 1 at 3:36 PM, Money, Roy<span dir=3D"ltr">&lt;<a href=3D"mailto:roy.money@=
> yale.edu">[log in to unmask]</a>&gt;</span>  wrote:<br>
>
> <blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
> x #ccc solid;padding-left:1ex;"><div class=3D"im">***** =A0To join INSNA, v=
> isit<a href=3D"http://www.insna.org" target=3D"_blank">http://www.insna.or=
> g</a>  =A0*****<br>
>
>
> <br>
> </div>Thanks to Joe and David and Kathleen for your responses.<br>
> I will look into ORA and Siena as an alternative to HLM.<br>
> I was hoping to hear from someone about why a multilevel model was not appr=
> opriate before taking on another analysis plan.<br>
> Anyone have any thoughts on that?<br>
> <br>
> Roy<br>
> <br>
> <br>
> <br>
> <br>
> <br>
> <br>
> Hi Roy,<br>
> <br>
> I suppose you could run a SIENA model, include both the density parameter a=
> s you would normally do, and then add a square of the density parameter to =
> test for the inverted-U shaped relationship you&#39;re expecting.<br>
> <br>
> Joe<br>
> Giuseppe (Joe) Labianca<br>
> Gatton Endowed Associate Professor of Management<br>
> Gatton College of Business&amp; Economics<br>
> LINKS Center for Social Network Analysis<br>
> University of Kentucky<br>
> Lexington, KY 40506<br>
> <a href=3D"tel:859-257-3741" value=3D"+18592573741">859-257-3741</a>=A0(off=
> ice)<br>
> <a href=3D"tel:404-428-4878" value=3D"+14044284878">404-428-4878</a>=A0(mob=
> ile)<br>
> <a href=3D"http://linkscenter.org/" target=3D"_blank">http://linkscenter.or=
> g/</a><br>
> <div><div class=3D"adm"><div id=3D"q_133a906d61b395d4_2" class=3D"ajR h4"><=
> div class=3D"ajT"></div></div></div><div class=3D"h5"><br>
> <br>
> <br>
> On Mon, Nov 14, 2011 at 1:37 PM, Money, Roy&lt;<a href=3D"mailto:roy.money=
> @yale.edu">[log in to unmask]</a>&lt;mailto:<a href=3D"mailto:roy.money@yal=
> e.edu">[log in to unmask]</a>&gt;&gt; wrote:<br>
> ***** =A0To join INSNA, visit<a href=3D"http://www.insna.org" target=3D"_b=
> lank">http://www.insna.org</a>  =A0*****<br>
> <br>
> I made a simiilar post to this list last month that garnered only one respo=
> nse so I am trying again.<br>
> <br>
> I have 8 waves (at 6 month intervals) of social network data for a interdis=
> ciplinary =A0research consortium of =A0scientists where the degree centrali=
> ty measure peaks at wave 4 (18 months), and the geodesic distance bottoms o=
> ut at that time point. =A0It does seem like 18 months represents a maximum =
> effect time for =A0the aggregate network data.<br>
>
>
> <br>
> Previously I used UCINET to do bootstrapped t tests for particular pair-wis=
> e time comparisons but I want to characterize the longer trajectory and the=
>   apparent change in slope at 18 months.<br>
> <br>
> I also have associated survey response data for which I have used a =A0disc=
> ontinuous level-1 HLM individual growth model to test the hypothesis that t=
> he slope changes at =A0time 4 (18 months).<br>
> <br>
> I would like to apply a similar analysis to the individual network measures=
>   of degree centrality and geodesic distance. However I have not found in my=
>   literature searches any references to the analysis of =A0longitudinal soci=
> al network data like I am working with.<br>
>
>
> <br>
> Is a multilevel or HLM analysis an appropriate method to test for quadratic=
>   or piecewise non linear change of the individual newtwork measures ? =A0If=
>   not, what would be optimal ways to evaluate this apparent maxing out of th=
> e connectivity of the social network about mid way through the consortium h=
> istory?<br>
>
>
> <br>
> Thanks for any suggestions or references.<br>
> <br>
> Roy =A0Money<br>
> <br>
> Yale University<br>
> <br>
> _____________________________________________________________________<br>
> _____________________________________________________________________
> SOCNET is a service of INSNA, the professional association for social
> network researchers (http://www.insna.org). To unsubscribe, send
> an email message to [log in to unmask] containing the line
> UNSUBSCRIBE SOCNET in the body of the message.
>
> --20cf307ac3ef59aaf104b1cc48a4--

_____________________________________________________________________
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