Existing users, 
 GLMStat - 6.0.0Statistical program for analyzing generalized linear models |
|
||||||||||||||||
|
|||||||||||||||||
Feedback Summary:
| This Version: | |||||
| Overall Rating: | Not rated (0.0) | Features: | Not rated (0.0) | Support: | Not rated (0.0) |
| Ease of Use: | Not rated (0.0) | Quality / Stability: | Not rated (0.0) | Price: | Not rated (0.0) |
Key to Types of Feedback:
Reviews 
Troubleshooting 
Usage Tips 
Developer Notes 
Commentary 
Featured Reviews
I have been… 
- Version: 5.6.2, 12/2/2001 09:17AM PST
DRNash--2008
a registered user of GLMStat since v.1.5 in 1996, and I'd be lost without this program, which makes GLM analysis on the Mac not only possible, but very straightforward and intuitive. Recent updates have added very valuable features to the software (such as sequential fitting and applescript control), making it even better value for money than previously. While GLMs may seem rather an esoteric field for many scientists using statistics, they are actually applicable to many analyses and are frequently preferable to "standard" analyses using transformed data or non-parametric techniques. This is particularly so in my field (biology), where the ability to analyse count data (with poisson errors) and proportional data (with binomial errors) is very important. I've always got very friendly and fast feedback from Ken Beath, and I can't recommend this software too highly.
I have been… - Version: 5.6.2, 11/24/2001 03:44PM PST
JPaolillo
using GLMStat for some time now (though I have switched to mostly using the OS X version) and I have been consistently satisfied with the software. It features a well-designed and intuitive interface that is much easier to use than the GLM modules of SPSS and similar programs. GLMStat's design make it ideal for teaching data analysis using GLM's as well, and the license fees are far more reasonable than the other comparable products. Furthermore, the author's support is fantastic! I have been through several major versions of this software, with consistent improvements in each version. In short, I consider this program a must-have for my statistical modeling toolkit, and I strongly recommend it to anyone looking for an easy-to-use but flexible regression package.
