BESA Statistics 2.0 is now released. It can be downloaded from the BESA website here. If you already use BESA Statistics 1.0, the upgrade can be purchased at 20% of the BESA Statistics 2.0 list price. If you purchased BESA Statistics 1.0 in the period between 1st June 2014 and 30th June 2015, you are eligible for a free upgrade – simply download the new setup, and the update file for your dongle which has already been placed onto our ftp server.
BESA Statistics boasts the following exciting new features:
- Cluster permutation testing based on Analysis of Variance (ANOVA) or Analysis of Covariance (ANCOVA) for comparing more than 2 groups / conditions, optionally accounting for the influence of a covariate of no interest
- Cluster permutation testing based on Correlation analysis for testing the relationship between covariates of interest and EEG / MEG data
Other new features include:
- Direct reading of the BrainVision Analyzer 2 data format for time and time-frequency data
- Topographic mapping of time-frequency data averages for t-Test and Correlation workflows
- Reading of the BESA generic binary file format for improved accuracy in ERP / ERF data analysis
For all computations, BESA Statistics now also uses parallel computing, which means that multiple cores on customer’s PCs are put to full use, greatly enhancing computation speed of the statistical cluster permutation tests, especially when using the 64bit version of the program.
Cluster permutation testing based on single-factor ANOVA and ANCOVA uses the F-test to compute clusters where the null hypothesis of exchangeability of groups or conditions is rejected. As an additional feature that is unique, BESA Statistics then offers post-hoc testing for the clusters identified by the F-test: A post-hoc permutation Scheffe’s test is computed to determine, which pairwise comparison(s) were responsible for the group / condition main effect. This means that not only does BESA Statistics enable users to find effects in data with a large number of factor levels, it also enables them to then figure out which pairs of factor levels cause the main effect. BESA Statistics takes care of the multiple comparison issue present for the post-hoc tests by means of a Bonferroni-Holm correction.
In the usual fashion, these additional tools are provided in the framework of the BESA Statistics workflow, simply by adding one additional workflow step to the ANOVA / ANCOVA workflow. This ensures maximum user-friendliness.
The new workflows are available for all data types that BESA Statistics supports: ERP / ERF data, source image data, source waveforms, and time-frequency data either in sensor space or in source space.
Example data to test the new features are available as download here. An explanation of the data and how to use them for exploring the features of the program is also part of the download – file BESA Statistics example data.pdf.
For more information and a quotation, please contact firstname.lastname@example.org via e-mail.
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