LogXact® 11

Exact Inference for Logistic Regression

The complexity of conducting regression analysis over multiple covariates is well-documented. The challenge only intensifies when coupled with small sample sizes or missing data sets. LogXact aims to provide simple and accurate solutions for such difficulties.

LogXact can handle many varieties of response data including continuous and binary, polytonomous, count, and missing data. Users of the software can be confident of in their results derived from LogXact’s advanced regression techniques.

The Advantages of LogXact 11

LogXact 11 offers pioneering methods in exact inference and regression modeling to provide rapid and accurate analysis. Powerful algorithms are built to analyze stratified and unstratified data sets of all sizes. Cytel-developed algorithms are carefully tested, highly validated in practice, and compliant the guidance found in the FDA's CFR Part 11.

LogXact continues to set the standard in all facets of regression modeling using exact inference. It is the first to offer the widely acclaimed PMLE procedure that minimizes separation bias while exhibiting significantly lower error rates compared to typical maximum likelihood estimators.

The Benefits of LogXact 11


Play a more strategic role in your organization: Perform fast and accurate hypothesis-testing that is responsive to an array of trial needs. Obtain reliable results for smaller sample sizes, allowing for timely and cost-effective trials. Redirect time, attention and critical resources to other vital aspects of study success.


Access LogXact’s selection of exact and Monte Carlos tests to increase the statistical power of trial results. Unnecessary risks associated with conventional (asymptotic) testing are curtailed using performance software tha t is fast and accurate.


LogXact simplifies tests that normally require complex calculation. Findings that should be difficult to compute are easy to identify and communicate.


LogXact has harnessed the immense power of Cytel’s nonparametric and exact inference methods to make enduring contributions to the fields of population health, medical and clinical studies, epidemiology, economics, energy, finance, legal studies, natural sciences, geography and the brain sciences. LogXact has received acclaim from both industry and academia for its high quality performance of complex calculations.

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The Features of LogXact 11

The Full Toolkit

LogXact performs regression analysis for continuous, binary, polytonomous and count data. It can also apply advanced regression techniques to data sets with missing values.

Missing Covariates

Only in LogXact can users accurately fit general linear models in cases of missing categorical covariates (models include Logit, Probit, CLoglog, Poisson and Normal).

Large Data Sets

LogXact provides options to handle large data sets using exact methods, Monte Carlo sampling and Markhov Chain Monte Carlo sampling. A useful ‘Exploration Mode’ allows users to specify parameters to build networks that satisfy analysis needs.

New Developments

LogXact has recently added several features to its world-class toolkit including Firth’s PMLE procedure; the calculation of mid-p corrected confidence intervals for a variety of models; best subset selection in binary logistic regression; the force inclusion of variable to the best subsets; and profile likelihood confidence intervals for parameters of binary logistic regression.

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