LogXact 9

What's new | System Requirements | Further Information

LogXact is an exciting product. No other logistic regression software can match its ability to analyze small, sparse, or imbalanced binary data.

• It provides exact answers for those questionable studies in which you thought you had a reasonably large sample size, but unfortunately observed only a handful of responses.
• It performs both unconditional and conditional maximum likelihood inference for problems that are too difficult for the exact inference.
• Its user manual gives a detailed text-book-like exposition of the theory underlying unconditional maximum likelihood inference, conditional maximum likelihood inference, and conditional exact inference, all illustrated with numerous real examples. The manual is very convenient, with a large index and a detailed table of contents.
• Its friendly spreadsheet-like data editors bring you close to your data and facilitate model building. You can import ASCII, SAS, SPSS, SYSTAT and EGRET data sets directly into LogXact.

What's New in LogXact 9?

Windows® 7 and Vista support
Cytel works continuously to allow our customers a choice of supported operating systems. Cytel's StatXact® and LogXact® are now both approved for use in Windows® 7 and Windows® Vista.

R integration
Users can now use R scripts in conjunction with Cytel’s exact statistics software. Computers with R 2.3 or newer may run existing R files or write and run R programs with the R output displayed in LogXact®.

R programs can also run analyses of either StatXact® or LogXact® datasets. All R outputs are displayed in the Cytel Studio interface (except R plots).

In addition to R, Cytel continues support of its own batch language to for custom analysis and regression calculations automation.

• Best subset selection in binary logistic regression
• Force inclusion of variables to the best subset
• Profile Likelihood Confidence Intervals for parameters of binary logistic regression
• Firth's correction to Profile Likelihood Confidence Intervals
  See Penalized Maximum Likelihood Method (PMLE) example of Firth's correction, the procedure for obtaining the Profile Likelihood-based confidence intervals for the parameters with the Venzon and Moolgavkar algorithm (1988)).

System Requirements

Further Information

• LogXact Homepage.