***** To join INSNA, visit http://www.insna.org *****
I am rather new to SNA, but I did a study on family businesses using
both network data and multi-level modeling (HLM) the reference is below.
Again I'm not an expert but I can tell you a few problem I had, and ones
that you might want to avoid. I'm not sure if my solutions are the best
or most appropriate, but it might give you some thoughts. I listening
early to the response myself.
First the ego centric level variables never worked well for me at level
one because of two limitations. The first problem was that the
centrality measures were all non-normal distributions. And rather
problematic in reference to positive skewness. Second, my level two was
different sized (N) businesses which brought up the question of
normalized and non normalized centrality measures. Something to wrestle
with conceptually. I have also used group level measures such as
density and measures of joint count analysis at level two to model the
strength of structural boundaries and their effect on level one
variables. This was much more productive, but again the question of
standardized measures across different sized networks come up.
Distelberg, B & Blow, A (2011). Variations in family system boudnaries.
Family Business Review, 24, 28-46
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
Mobile: (616) 481-3524
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-----Original Message-----
From: Social Networks Discussion Forum [mailto:[log in to unmask]] On
Behalf Of Money, Roy
Sent: Tuesday, November 15, 2011 12:37 PM
To: [log in to unmask]
Subject: Re: [SOCNET] longitudinal analysis of social network data -
need help
***** 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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