SIENA is a program for the statistical analysis of network data, with the focus on social networks. Networks here are understood as entire (complete) networks, not as personal (egocentered) networks: it is assumed that a set of nodes (social actors) is given, and all ties (links) between these nodes are known - except perhaps for a moderate amount of missing data. The name SIENA stands for Simulation Investigation for Empirical Network Analysis. The R package is called RSiena; there also is the development package RSienaTest.
SIENA is designed for analyzing various types of data as dependent variables:
This refers to repeated measures of networks on a given node set (although it is allowed that there are some changes in the node set). Models can be specified with actor-oriented as well as tie-oriented dynamics; but mainly the former.
Practical restrictions are that the number of actors should not be too large; a few hundred already is pretty large.
This is like longitudinal network data, but in addition there are one or more changing nodal variables that are also treated as dependent variables, and referred to as behavior. The network will influence the dynamics of the behavior, and the behavior will influence the dynamics of the network. In other words, this is about the co-evolution of networks and behavior.
Network data sets can be multivariate, i.e., be composed of multiple networks on the same node set. Some or all of these networks can be two-mode networks. The restriction is that the first mode must be the same for all networks; the first mode is defined as the set of actors. The second mode node sets are allowed to differ across the various networks in a given data set. For such multivariate data sets, the model again is about the co-evolution of several networks; and this may be combined with behavior.
We are migrating RSiena development and releases to this repository.
Note that the main manual can still be found here, and the main website is still here for the time being, however we are currently migrating many resources to this website, and you can find a wiki here that holds much of the information on the original website, including background on SAOMs and RSiena, and links to teaching materials, literature, and contributing people and projects.
Perhaps the easiest way to install RSiena is by installing a compiled binary. Binaries for all major OSes -- Windows, Mac, and Linux -- can be found by clicking on the latest release here.
Once the file has been downloaded, unzip the file, and install the binary as appropriate for your binary. For example, for Mac you can use the following line, amending the version number as necessary:
install.packages("~/Downloads/rsiena_AllOS/macOS/rsiena_1.2.3.tgz", repos = NULL)
To install from source the latest main version of RSiena from Github, please install the {remotes} package from CRAN and then enter into the console:
remotes::install_github("snlab-nl/rsiena")
The development version of RSiena can be similarly installed as:
remotes::install_github("snlab-nl/rsiena@develop")