***** To join INSNA, visit http://www.insna.org ***** To add to Stanley's notes: The p2 model does not assume dyad independence. It is explicitly a dyad dependence model, although there is conditional independence given the node-specific random effects. The naming of the exponential family models for networks is a bit problematic. Historically, Holland, Leinhardt and others presented them as exponential families of distributions over the space of graphs. The so-called "p1" model was a particularly useful class presented in their seminal paper with an unfortunately uninstructive name (a non-name really!). The generalization by Frank and Strauss is a general statistical exponential family of distributions over graphs. The specification of the statistics constitutes the modeling part. This is the reason recent work references them as (statistical) exponential family models. A number of acronyms or combination of terms to capture this make sense, and constructively describe the statistical roots and connections of the model class. The utility of the "p*" name is unclear to me (perhaps Stanley can describe why he prefers it to the earlier name?). Cheers, Mark ------------------------------------------------- Mark S. Handcock Professor of Statistics Department of Statistics, C014-B Padelford Hall University of Washington, Box 354322 Phone: (206) 221-6930 Seattle, WA 98195-4322. FAX: (360) 365-6324 Web: www.stat.washington.edu/~handcock internet: [log in to unmask] On 2/8/07 9:31 AM, "Stanley Wasserman" <[log in to unmask]> wrote: > ***** To join INSNA, visit http://www.insna.org ***** > > Dear all: > > p1 is now 30 years old, and research has progressed considerably over > the past > two decades ... see for example the chapters on statistical > models in > Carrington, et al. (2005). > > p1, as well as p2, assumes dyadic independence, which is a rather > simplifying assumption. > The new models, all based on the p* framework first proposed by Frank > and Strauss > in 1986, have opened up network research to realistic and > interesting statistical > parametric structures. And we now have good estimation techniques > for the > parameters. > > As Tom says here, p* (which is more accurately an exponential family > of random graphs, rather than > an "ERG" or an "ERGM") is a hot topic and one can do lots of cool > things with it > (if you are careful). > > > SW > > > > On Feb 8, 2007, at 4:53 AM, Tom Snijders wrote: > >> ***** To join INSNA, visit http://www.insna.org ***** >> >> Hi readers, >> >> Christophe, the use of the p1 model for modeling the effects of >> node level independent variables on binary dyadic (relational) >> dependent variables is not such a good idea any more. Better than >> the p1 model is the p2 model, see >> >> Duijn, M.A.J. van, Snijders, T.A.B. & Zijlstra, B.J.H., (2004). P2: >> a random effects model with covariates for directed graphs. >> Statistica Neerlandica, 58, 234-254. >> >> which is part of the Stocnet suite, see http://stat.gamma.rug.nl/ >> stocnet/ >> >> ; and the ERG model, see the papers-in-press of the special issue >> of Social Networks edited by Garry Robins and Martina Morris. The >> ERG model represents network structure such as triadic closure, >> while the p2 model is restricted to modeling differences in >> popularity and acitivity of nodes (like p1). Estimation for the >> ERGM is implemented in SIENA (again, in the Stocnet suite) and in >> Statnet (an R package). >> >> Best wishes, >> >> Tom >> > > _____________________________________________________________________ > 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. _____________________________________________________________________ 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.