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"During the past year I have become an avid user of Latent Gold for my
analyses of change processes in a large sample of patients in psychotherapy
and psychoanalyses. LG has proven extremely illuminating, and I applaud the
upgrading/extension to CHAID"
Rolf Sandell, Professor in clinical psychology, Linköping University, Stockholm, Sweden
SI-CHAID 4.0 is now available!
New features include:
- extension to multiple dependent variables in conjunction with either of our sister products Latent GOLD 4.5 and/or Latent GOLD Choice 4.5
- the ability to save entire trees or
tree branches - allows additional applications such as the use
of a holdout sample for validation
Extension to multiple dependent variables
Often segmentation is desired that is predictive of not one but multiple criteria. For example, in database marketing, dependent variables might include 1) response to the most recent mailing (responder vs. nonresponder), 2) response to past mailings, 3) the amount spent, 4) profitability, and possibly others. It is now possible to obtain CHAID segmentation trees that are predictive of multiple dependent variable criteria. In addition, these dependent variables may be continuous, ordinal, nominal, or count variables, or any combination of these!
In the groundbreaking new article An Extension of the CHAID Tree-based Segmentation Algorithm to Multiple Dependent Variables, Magidson and Vermunt (2005) show this is possible. The key is to use latent classes as a proxy for the multiple dependent variables. This can be done with Latent GOLD 4.5 when the dependent variables are used as indicators in a latent class cluster or factor model, or it can be done with Latent GOLD Choice 4.5 when the dependent variables are choices obtained from a discrete choice study.
Each of our flagship modeling tools Latent GOLD 4.5 and Latent GOLD Choice 4.5 provide a direct link to SI-CHAID 4.0. With this option, a CHAID Definition (.chd) file is automatically generated immediately following model estimation which can then be used as input to SI-CHAID 4.0.
To see how this works:
- download the article
- view a tutorial where a CHAID tree is developed that is predictive of 11 dependent variables in conjunction with Latent GOLD 4.5 (SI-CHAID tutorial #4)
- view a tutorial from Latent GOLD 4.5 where a CHAID analysis is used with a discrete factor model to better understand the factors (LG tutorial #4)
More about latent class models
Latent class (LC) modeling, also known as Finite Mixture Modeling, provides a powerful way of identifying latent groups (types) for which parameters in a specified model differ.
Latent GOLDŽ 4.5, the most windows-friendly program for latent class modeling, focuses on the three most important kinds of statistical models used in practice - cluster, factor and regression.
Latent GOLDŽ 4.5 dramatically expands your capacity for identifying latent classes and, through the CHAID link, seamlessly integrates
with SI-CHAID for unprecedented "two-in-one" modeling capability.
Latent GOLDŽ 4.5 has the same easy-to-use layout and structure as SI-CHAID, with intuitive controls, breakthrough graphical displays, and extensive Help structure. Explore and analyze your model,
and then, with a click of a button, save the output as a SI-CHAID input file for further analysis.
Learn more about Latent GOLDŽ 4.5:
Learn more about SI-CHAIDŽ 4.0:
Order SI-CHAID 4.0 for only $995
More information on Latent GOLDŽ 4.5:
1. Latent GOLDŽ 4.5 Demo version & Tutorials
Download a demo version of Latent GOLDŽ 4.5 and see for yourself!
This tutorial demonstrates the use of the CHAID link in Latent GOLD 4.5:
Use these other tutorials to explore the demo version:
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2. Latent GOLDŽ 4.0 User's Guide
The complete user's guide provides a comprehensive look at the program with easy-to-understand, step-by-step instructions and hundreds of screenshots. Download by chapter:
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3. Latent GOLDŽ 4.0 Technical Guide: Basic and Advanced
This is the companion manual for Latent GOLD 4.5, an important work which provides a guide to the proper use of the program.
It introduces the equations for all models, formulae for all statistics, describes all technical options, and discusses applications and proper interpretation of the output.
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More information on SI-CHAIDŽ 4.0:
1. SI-CHAIDŽ 4.0 Demo version & Tutorials
Download a demo version of SI-CHAIDŽ 4.0 and see the new version for yourself!
This tutorial demonstrates the use of the Latent GOLD link in SI-CHAID 4.0:
This tutorial demonstrates the new tree saving option in SI-CHAID 4.0 to evaluate a CHAID segmentation using a holdout sample:
Use these other tutorials to explore the demo version:
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2. SI-CHAIDŽ 4.0 User's Guide
The complete user's guide provides a comprehensive look at the program with easy-to-understand, step-by-step instructions and hundreds of screenshots.
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3. SI-CHAIDŽ 4.0: New Features
This article documents the new multiple dependent variable feature in SI-CHAID 4.0
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4. SI-CHAIDŽ 4.0 Graphical Interface
SI-CHAIDŽ's graphical interface makes it easy to analyze relationships between categories. View trees, gains charts, and tables on the same screen:
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