O'Reilly logo

Analysis of Complex Networks by Frank Emmert-Streib, Matthias Dehmer

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

16.7 Binary Choice Model

We now turn to modeling organizational collaboration choices in order to examine how specific individual characteristics, spatial effects, and network effects determine the choice of collaboration (the theoretical underpinnings are described in Ref. [29]). We will build upon the survey data and the subnetwork constructed there from (Section 16.3). While this restricts us to only 191 organizations, we have considerably more information about these organizations than for the complete networks.

16.7.1 The Empirical Model

In our analytical framework, the constitution of a collaboration Yij between two organizations (i) and (j) will depend on an unobserved continuous variable Y* that corresponds to the profit that two organizations (i) and (j)ij receive when they collaborate. Since we cannot observe Y*ij but only its dichotomous realizations Yij, we assume Yij =1 if Y*ij > 0 and Yij = 0 if (Y*ij ≤ 0. Yij is assumed to follow a Bernoulli distribution so that Yij can take the values one and zero with probabilities πij and 1– πij, respectively. The probability function can be written as

images

with (E [Yij] = μij = πij and (Var [Yij] = σ2 = πij (1– πij)), where μij denotes some mean value.

The next step in defining the model concerns the systematic structure – we would like the probabilities πij to depend on a matrix of observed covariates. Thus, we let the probabilities ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required