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***** 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 Van den Bulte, Christophe wrote: > ---------------------- Information from the mail header ----------------------- > Sender: Social Networks Discussion Forum <[log in to unmask]> > Poster: "Van den Bulte, Christophe" <[log in to unmask]> > Subject: Re: models for categorical attributes and dyadic data? > ------------------------------------------------------------------------------- > > ***** To join INSNA, visit http://www.insna.org ***** > > Balasz Vedres asked: > > "Is there a way to model multiple, node level categorical independents, > and a dyadic dependent variable?" > > Yes, there is. One approach is based on the p1 model. See Chapter 15 in > Wasserman & Faust (1994). But the approach may break down when you have > many independent variables with many categories. > > Christophe Van den Bulte > Associate professor of marketing > The Wharton School of the University of Pennsylvania > 759 Jon M. Huntsman Hall > 3730 Walnut Street > Philadelphia PA, 19104-6340 > > T: 215-898-6532 > F: 215-898-2534 > > http://www.wharton.upenn.edu/faculty/vanden.html > > _____________________________________________________________________ > 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. -- ============================================== Tom A.B. Snijders Professor of Statistics in the Social Sciences University of Oxford Professor of Statistics and Methodology Department of Sociology University of Groningen http://stat.gamma.rug.nl/snijders/ ============================================== _____________________________________________________________________ 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.