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reference:ft_statistics_analytic [2018/08/23 14:43] (current)
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 +=====  FT_STATISTICS_ANALYTIC =====
 +
 +Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_statistics_analytic"​.
 +
 +<​html><​pre>​
 +  <a href=/​reference/​ft_statistics_analytic><​font color=green>​FT_STATISTICS_ANALYTIC</​font></​a>​ performs a parametric statistical test on the
 +  data, based on a known (i.e. analytic) distribution of the test
 +  statistic. This function should not be called directly, instead
 +  you should call the function that is associated with the type of
 +  data on which you want to perform the test.
 + 
 +  Use as
 +    stat = ft_timelockstatistics(cfg,​ data1, data2, data3, ...)
 +    stat = ft_freqstatistics ​   (cfg, data1, data2, data3, ...)
 +    stat = ft_sourcestatistics ​ (cfg, data1, data2, data3, ...)
 +  where the data is obtained from <a href=/​reference/​ft_timelockanalysis><​font color=green>​FT_TIMELOCKANALYSIS</​font></​a>,​ <a href=/​reference/​ft_freqanalysis><​font color=green>​FT_FREQANALYSIS</​font></​a>​
 +  or <a href=/​reference/​ft_sourceanalysis><​font color=green>​FT_SOURCEANALYSIS</​font></​a>​ respectively,​ or from <a href=/​reference/​ft_timelockgrandaverage><​font color=green>​FT_TIMELOCKGRANDAVERAGE</​font></​a>,​
 +  <a href=/​reference/​ft_freqgrandaverage><​font color=green>​FT_FREQGRANDAVERAGE</​font></​a>​ or <a href=/​reference/​ft_sourcegrandaverage><​font color=green>​FT_SOURCEGRANDAVERAGE</​font></​a>​ respectively.
 + 
 +  The configuration can contain
 +    cfg.statistic ​       = string, statistic to compute for each sample or voxel (see below)
 +    cfg.correctm ​        = string, apply multiple-comparison correction, '​no',​ '​bonferroni',​ '​holm',​ '​hochberg',​ '​fdr'​ (default = '​no'​)
 +    cfg.alpha ​           = number, critical value for rejecting the null-hypothesis (default = 0.05)
 +    cfg.tail ​            = number, -1, 1 or 0 (default = 0)
 +    cfg.ivar ​            = number or list with indices, independent variable(s)
 +    cfg.uvar ​            = number or list with indices, unit variable(s)
 +    cfg.wvar ​            = number or list with indices, within-block variable(s)
 + 
 +  The parametric statistic that is computed for each sample (and for
 +  which the analytic probability of the null-hypothesis is computed) is
 +  specified as
 +    cfg.statistic ​      = '​indepsamplesT' ​          ​independent samples T-statistic,​
 +                          '​indepsamplesF' ​          ​independent samples F-statistic,​
 +                          '​indepsamplesregrT' ​      ​independent samples regression coefficient T-statistic,​
 +                          '​indepsamplesZcoh' ​       independent samples Z-statistic for coherence,
 +                          '​depsamplesT' ​            ​dependent samples T-statistic,​
 +                          '​depsamplesFmultivariate'​ dependent samples F-statistic MANOVA,
 +                          '​depsamplesregrT' ​        ​dependent samples regression coefficient T-statistic,​
 +                          '​actvsblT' ​               activation versus baseline T-statistic.
 +  or you can specify your own low-level statistical function.
 + 
 +  See also <a href=/​reference/​ft_timelockstatistics><​font color=green>​FT_TIMELOCKSTATISTICS</​font></​a>,​ <a href=/​reference/​ft_freqstatistics><​font color=green>​FT_FREQSTATISTICS</​font></​a>,​ <a href=/​reference/​ft_sourcestatistics><​font color=green>​FT_SOURCESTATISTICS</​font></​a>​
 +</​pre></​html>​