RSiena (tutorial): Difference between revisions
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This [[Trails|trail]] illustrates how to analyze longitudinal network data by using [[RSiena | RSiena]] from within visone. We assume that you have installed R on your computer and configured the R connection as it is explained in the [[Installation_(trail)#Installing_the_R_connection|installation trail]]. We also assume that you have basic understanding about how to work with visone as it is, for instance, explained in the trail on [[Visualization_and_analysis_(trail)|visualization and analysis]] and basic knowledge of [http://www.stats.ox.ac.uk/~snijders/siena/SnijdersSteglichVdBunt2009.pdf stochastic actor-oriented models (SOAM)]. | This [[Trails|trail]] illustrates how to analyze longitudinal network data by using [[RSiena | RSiena]] from within visone. We assume that you have installed R on your computer and configured the R connection as it is explained in the [[Installation_(trail)#Installing_the_R_connection|installation trail]]. We also assume that you have basic understanding about how to work with visone as it is, for instance, explained in the trail on [[Visualization_and_analysis_(trail)|visualization and analysis]] and basic knowledge of [http://www.stats.ox.ac.uk/~snijders/siena/SnijdersSteglichVdBunt2009.pdf stochastic actor-oriented models (SOAM)]. | ||
To follow the steps illustrated in this trail you should download the | To follow the steps illustrated in this trail you should download the file [[Media:Classroom_graphmls.zip|Classroom_graphmls.zip]] and extract (unzip) its content (consisting of the network files <code>classroom_graph1.graphml</code> to <code>classroom_graph4.graphml</code> to your hard disk. These files constitute the longitudinal network data explained on page [[Knecht_Classroom_(data)|Knecht Classroom (data)]]. | ||
==Defining longitudinal network data== | ==Defining longitudinal network data== | ||
Stochastic Actor Oriented Models (SAOMs) are designed for analysing longitudinal network data given as network panel data, i.e., a sequence of networks representing one network observed at several moments in time. | Stochastic Actor Oriented Models (SAOMs) are designed for analysing longitudinal network data given as network panel data, i.e., a sequence of networks representing one network observed at several moments in time. Network files <code>classroom_graph1.graphml</code> to <code>classroom_graph4.graphml</code> contain suitable data. | ||
In visone, several networks can be open at the same time - each in its own network tab. In general, you can load networks into visone by (1) starting and editing a [[File_menu#new|new empty network]], (2) by opening a network from a [[File_menu#open|local file]], or (3) by creating a [[File_menu#create|random network]]. To load the set of networks that serves as illustrating example in this trail, click on the menu '''file, open''', navigate in the file browser to the directory where you've put the files <code>newfrat01.graphml</code> to <code>newfrat15.graphml</code> (see above) and select all of them before you click the '''ok''' button. (Selection of these files can be done in different ways, for instance, by keeping the '''Control'''-key pushed while successively selecting the files with a mouse left-click or by clicking on one of the files and then typing '''Control-a''' to select all files in the current directory.) | |||
==Adding individual or dyadic covariates== | ==Adding individual or dyadic covariates== | ||
Revision as of 16:25, 7 September 2011
This trail illustrates how to analyze longitudinal network data by using RSiena from within visone. We assume that you have installed R on your computer and configured the R connection as it is explained in the installation trail. We also assume that you have basic understanding about how to work with visone as it is, for instance, explained in the trail on visualization and analysis and basic knowledge of stochastic actor-oriented models (SOAM).
To follow the steps illustrated in this trail you should download the file Classroom_graphmls.zip and extract (unzip) its content (consisting of the network files classroom_graph1.graphml to classroom_graph4.graphml to your hard disk. These files constitute the longitudinal network data explained on page Knecht Classroom (data).
Defining longitudinal network data
Stochastic Actor Oriented Models (SAOMs) are designed for analysing longitudinal network data given as network panel data, i.e., a sequence of networks representing one network observed at several moments in time. Network files classroom_graph1.graphml to classroom_graph4.graphml contain suitable data.
In visone, several networks can be open at the same time - each in its own network tab. In general, you can load networks into visone by (1) starting and editing a new empty network, (2) by opening a network from a local file, or (3) by creating a random network. To load the set of networks that serves as illustrating example in this trail, click on the menu file, open, navigate in the file browser to the directory where you've put the files newfrat01.graphml to newfrat15.graphml (see above) and select all of them before you click the ok button. (Selection of these files can be done in different ways, for instance, by keeping the Control-key pushed while successively selecting the files with a mouse left-click or by clicking on one of the files and then typing Control-a to select all files in the current directory.)
Adding individual or dyadic covariates
Specifying missing data or structurally fixed values
This option is not yet included in the current release visone-2.6.3 but will be in the next release!