This chapter addresses model specifications for the co-evolution of a social network and a discrete ordinal (or dichotomous) behavior variable. As before, this is done by means of an evaluation function composed of effects. Effects here are functions of the behavior, possibly also the network, as seen from the focal actor. Change statistics here are defined as changes in the value of the effect when the behavior variable is increased by one unit. The chapter defines several effects: first, depending only on the behavior of the focal actor; subsequently, depending on the behavior as well as the network. The latter kind of effect represents social influence or generalized social influence. Before such effects are proposed, it is mentioned that three basic aspects of social influence must be chosen: the reference group, the mechanism of social influence in a dyad, and aggregation over multiple dyads in the reference group. For the mechanism of social influence, a distinction is made between distance reduction (assimilation) and correlational influence. Effects are mentioned for both.

Chapter 3 introduced the evaluation function as the skeleton of the model, used to define the probabilities of network change. Chapter 4 gives some flesh on the bones by introducing effects, which are the components of the evaluation function. Effects are functions of the network as seen from the focal actor. They represent mechanisms, or components of mechanisms, of network dynamics. Change statistics are defined as changes in the value of the effect when a particular tie is established. The chapter presents a set of major effects that are often important for modeling. There are many more, for which the reader is referred to the software manual.