MultiNet is a data analysis package that can be used for ordinary data (in which you have a file that has one line of data for each case) and for network data (in which there are two files -- the "node" file describes the individuals and the "link" file describes the connections between individuals).

Note: check back periodically if you are interested in news about MultiNet.       ---- updated May 9, 2007 ----

A quick summary description of MultiNet

MultiNet quick start

MultiNet manual July, 2005

2007 Version

To obtain the latest version of MultiNet, please write to and tell us a bit about yourself and what you hope to do with MultiNet. Please say more than "I want to test MultiNet" or "I am getting into SNA."

This version is different from earlier versions in several ways:

Click here to get more information.

Note: Earlier versions of MultiNet are no longer supported.

2002 Version

MultiNet 4.0 for Windows differs from the 2000 version in several ways:

2000 Version

MultiNet 3.0 for Windows will be available here before the end of September, 2000. It is different from the 1999 version in several ways:

Please note: The graphics on the rest of this page are for the 1999 version.

1999 Version

MultiNet 2.11 (1999 version, updated May 9, 1999) is no longer available. It was different from the 1997 version in four ways:

Click here to see what makes MultiNet different from other packages.

Click here to see information about the format of the data MultiNet uses.



In the works...

  • [done] sparse matrix methods for eigen decomposition will increase the size of networks that can be examined with these methods;
  • [done] ability to save ASCII files that contain any new variables created by recoding, partitioning, or defining;
  • [done] ability to import space-, tab-, or comma-delimited files as well as the fixed-format approach now used;
  • ability to import UCINET or KRACKPLOT files;
  • [done] the dot matrix output option will be replaced with .bmp or .gif format for graphic output;
  • [done] improved interactivity of graphic display for spectral analysis;
  • ability to perform multidimensional scaling methods on data other than adjacency matrices;
  • multivariate ANOVA and regression analysis;
  • log linear analysis;
  • graph theoretic measures
  • more
  • Go back.                                                          updated February 24, 2005