FieldTrip

Note that this reference documentation is identical to the help that is displayed in Matlab when you type “help statfun_pooledT”.

  STATFUN_pooledT computes the pooled t-value over a number of
  replications. The idea is that you compute a contrast between two
  conditions per subject The t-values are pooled over subjects and
  compared against the pooled pseudo-values. Since according to H0
  the expected t-value for each subject value is zero, the difference
  between the pooled t-value and the pseudo-value (which is set to
  zero) is a fixed-effects statistic.
  
  The computation of the difference between pooled t-values can be
  repeated after randomly permuting the t-values and pseudo-values
  within the subjects. Each random permutation gives you an estimate
  of the difference. The random permutations build up a randomization
  distributin, against which you can compare the observed pooled
  t-values.
  
  The statistical inference based on the comparison of the observed
  pooled t-values with the randomization distribution is not a
  fixed-effect statistic, one or a few outlier will cause the
  randomization distribution to broaden and result in the conclusion
  of "not significant".
  
  Use this function by calling one of the high-level statistics
  functions as
    [stat] = ft_timelockstatistics(cfg, timelock1, timelock2, ...)
    [stat] = ft_freqstatistics(cfg, freq1, freq2, ...)
    [stat] = ft_sourcestatistics(cfg, source1, source2, ...)
  with the following configuration option:
    cfg.statistic = 'pooledT'
 
  Configuration options that are relevant for this function are
    cfg.ivar = number, index into the design matrix with the independent variable
 
  See FT_TIMELOCKSTATISTICS, FT_FREQSTATISTICS or FT_SOURCESTATISTICS
  for details.