The TETRAD Project:
Tetrad II Software
Richard Scheines, Peter Spirtes, Clark Glymour, and Christopher Meek (1994). TETRAD II: Tools for Discovery. Lawrence Erlbaum Associates, Hillsdale, NJ.
Tetrad II is a multi-module program that assists in the construction of causal explanations for sample data and their use in prediction. With continuous variables the program will aid in the search for "path models" or "structural equation models;" with discrete data the program will construct and update a Bayes network from sample data and user knowledge of the domain; the program includes Monte Carlo facilities. Proofs of the asymptotic correctness of all but one of the search modules are available in P. Spirtes, C. Glymour and R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, (1993, 2000).
Platform(s): DOS
In the future a Unix version may be available.
The DOS software comes with a ~250 page manual with chapters on theoretical foundations, interpreting output, and a chapter on each of the software modules. Each of the chapters include many detailed example of running Tetrad II.
Ordering information
ISBN# 156321-115-7
Price: $150.00
price includes DOS Program - 2 diskettes, and Manual (~250 pages).
Phone orders :
- 1-201-236-9500
- 1-800-926-6579
- 1-201-236-0072 (fax)
Mail or Web orders:
- Lawrence Erlbaum Associates, Inc.
- 10 Industrial Ave
- Mahwah, NJ 07430 - 22262
Description
TETRAD II has 10 modules, each of which has its own chapter in the manual. They are:
- Build
- Purify
- Makemodel
- Estimate
- MIMbuild
- Monte
- Update
- Search
- STATwriter
- Tetrads
Build, Purify, MIMbuild, and Search are the main inference modules. Using appropriate statistical tests, Build makes a series of decisions about independence and conditional independence relations among measured variables. This information is used to search for a class of models that cannot be distinguished by conditional independence relations alone, and that are compatible with user-entered background knowledge. Purify, MIMbuild, and Search work on normally distributed linear structural equation models with latent variables, and use substantive assumptions provided by the user together with statistical decisions about vanishing correlations and tetrad differences to estimate features of the causal structure. If the variables modeled are all discrete, then the Estimate module can calculate maximum likelihood estimates of the parameters of a Bayesian network that contains no latent variables, and the Update module can use these estimates to calculate conditional distributions. Makemodel and Monte provide a useful Monte Carlo simulation package. Makemodel takes an unparameterized causal structure and, after prompting the user for an interpretation of the structure as either a Bayesian network or a recursive linear structural equation model, parameterizes the structure and writes a fully parameterized statistical model to a TETRAD II readable file. Monte can then be used to generate samples of any size from such a model. Although TETRAD II does not estimate or test linear models, it will automatically write out input files to three popular packages that do: LISREL, EQS, and CALIS. The module takes a path diagram and covariance or raw data and will automatically write out an input file to the package of your choice.
scheines@andrew.cmu.edu