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Here is a paper looking at errors (due to missing data) in snowball sampling under different sampling conditions (fixed choice size and number of sample waves).

J.C. Johnson, J.S. Boster, and D. Holbert. "Estimating Relational Attributes From Snowball Samples Through Simulation," Social Networks 11:135-158, 1989.


-----Original Message-----
From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Kathleen Carley
Sent: Tuesday, February 12, 2013 8:28 AM
To: [log in to unmask]
Subject: Re: Missing network data

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See these papers:

Stephen Borgatti, Kathleen M. Carley and David Krackhardt, 2006, "Robustness of Centrality Measures under Conditions of Imperfect Data,"
Social Networks, 28.2:124-136. DOI: 10.1016/j.socnet.2005.05.001

Terrill L. Frantz and Kathleen M. Carley, 2010, "Toward A Confidence Estimate For The Most-Central-Actor Finding," Sage Publications/RM division Best Student Paper Proceedings of the Academy of Management Annual Conference, Chicago, IL, USA.

Terrill L. Frantz, Marcelo Cataldo and Kathleen M. Carley, 2009, "Robustness of centrality measures under uncertainty: Examining the role of network topology," Computational and Mathematical Organization Theory, 15.4:303-328. DOI: 10.1007/s10588-009-9063-5

On 2/11/2013 10:56 PM, Qian Hu wrote:
> ***** To join INSNA, visit http://www.insna.org ***** Dear SOCNET 
> members, I have two questions about the missing network data.
> what can be done if we cannot get an ideal response rate (say less 
> than
> 70 percent, or even lower)?
> 
>  1. I remember somewhere in the literature that says some centrality
>     measures such as the indegree centrality, are relatively robust for
>     network data that captures over 50% of the data. Am I correct?
>  2. The existing research seems to suggest two methods to deal with
>     missing data: exponential random graph models, and imputation
>     methods. If we know the key actors are captured in the imperfect
>     data set. Can we leave them as they are without using any additional
>     modeling process? Any literature to support this argument?
> 
> 
> 
> 
> Thank you very much. 
> Qian Hu
> University of Central Florida
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