
The arrival of the first mainframe software and then their PCbased successors has revolutionized multivariate statistical analysis. No longer are analyses limited in size or complexity and the full advantages of these techniques can be utilized. However, even a decade ago, the availability of this software was quite limited and even the available software often only performed basic analyses. But now the emergence of the PC and the recognized viability of commercial multivariate software packages have made these techniques available to everyone.
The software listed below is just a sample of the total packages available, but they have been selected as to what we feel are the best examples of multivariate statistical packages. There are three categories:
Please feel free to send us your comments or let us know of a statistical package for listing in any of these categories.

Complete Multivariate
Packages These statistical packages provide a complete suite of not only the basic multivariate techniques (factor analysis, regression, discriminant analysis, ANOVA/MANOVA, conjoint analysis, canonical correlation, cluster analysis and multidimensional scaling), but many of their variants and extensions. Several of these programs have backgrounds as mainframe applications oriented toward academic research, although several have been developed specifically for the PC environment.
Statistica

Basic Multivariate
Packages
These programs perform the basic multivariate techniques (regression, ANOVA/MANOVA and usually factor analysis), but vary in their inclusion of the other techniques (e.g., discriminant analysis, cluster analysis, MDS or conjoint). Many of these packages may be oriented towards the basic statistics courses.
Developed by Forrest Young, ViSta (Visual Statistics) is a free statistical package that includes regression, principal components, MDS and correspondence analysis. It was developed around a four step process in data analysis: reveal structure in your data; provide guidance; show results; and structure the data analysis procedures. Available for Mac, Windows, and Unix.

Specialized Statistical
Methods
This final set of statistical programs represent the specialized software directed at a limited range of analytical issues, but with more analytical detail and complexity than can be afforded in the more general programs. These programs play an important role in augmenting the more comprehensive packages and providing access to emerging techniques before they are incorporated into the more general programs.
This structural equation modeling package by James Arbuckle is becoming quite popular due to its ease of use and integration with SPSS. A free student version is also available. EViews is an econometrics package with an emphasis on econometrics estimation (single and multiple equation systems, all types of dependent variables), forecasting and simulation. The GAUSS Mathematical and Statistical System is a high level matrix programming language specializing in commands, functions, and procedures for data analysis and statistical applications.
LIMDEP is an econometrics program for linear and nonlinear models, limited and qualitative dependent variable models, models for cross section, time series and panel data. LISREL is perhaps the most widely used structural equation modeling (SEM) program. As one of the "original" SEM packages, it has defined the nomenclature for specifying structural equation models. It has evolved into a generalpurpose latent variable modeling program, with extensions to address such model forms as multilevel, growth curves and time series. RATS is an econometric time series software for analyzing time series and cross sectional data and developing and estimating econometric forecasting models. SORITEC is an econometrics and statistical package for estimation of all forms of dependence relationships, including discriminant analysis and variants of regression and other linear models. It does not address experimental design analyses. These are techniques based on exact tests (or permutation tests), typically used with smallsample categorical data. StatXact is for general permutation tests with smallsample categorical data and LogXact for exact smallsample logistic regression.

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