FieldTrip

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

  STATFUN_depsamplesregrT calculates dependent samples regression T-statistic 
  on the biological data in dat (the dependent variable), using the information on 
  the independent variable (iv) in design.
 
  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 = 'depsamplesregrT'
  see FT_TIMELOCKSTATISTICS, FT_FREQSTATISTICS or FT_SOURCESTATISTICS for details.
 
  For low-level use, the external interface of this function has to be
    [s,cfg] = statfun_depsamplesregrT(cfg, dat, design);
  where
    dat    contains the biological data, Nsamples x Nreplications
    design contains the independent variable (iv) and the unit-of-observation (UO) 
           factor,  Nreplications x Nvar
 
  Configuration options:
    cfg.computestat    = 'yes' or 'no', calculate the statistic (default='yes')
    cfg.computecritval = 'yes' or 'no', calculate the critical values of the test statistics (default='no')
    cfg.computeprob    = 'yes' or 'no', calculate the p-values (default='no')
 
  The following options are relevant if cfg.computecritval='yes' and/or
  cfg.computeprob='yes'.
    cfg.alpha = critical alpha-level of the statistical test (default=0.05)
    cfg.tail = -1, 0, or 1, left, two-sided, or right (default=1)
               cfg.tail in combination with cfg.computecritval='yes'
               determines whether the critical value is computed at
               quantile cfg.alpha (with cfg.tail=-1), at quantiles
               cfg.alpha/2 and (1-cfg.alpha/2) (with cfg.tail=0), or at
               quantile (1-cfg.alpha) (with cfg.tail=1).
 
  Design specification:
    cfg.ivar        = row number of the design that contains the independent variable.
    cfg.uvar        = row number of design that contains the labels of the UOs (subjects or trials)
                         (default=2). The labels are assumed to be integers ranging from 1 to 
                         the number of UOs.