FT_STATFUN_INDEPSAMPLESZCOH

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

  FT_STATFUN_INDEPSAMPLESCOHZ calculates the independent samples coherence Z-statistic 
  on the biological data in dat (the dependent variable), using the information on 
  the independent variable (ivar) 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 = 'ft_statfun_indepsamplesZcoh'
 
  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] = ft_statfun_indepsamplesZcoh(cfg, dat, design);
  where
    dat    contains the biological data, Nsamples x Nreplications
           dat must contain fourier representations. 
    design contains the independent variable (ivar), Nreplications x Nvar
 
  The samples-dimension of the dat-variable must be the result of a
  reshaping-operation applied to a data structure with dimord
  chan_(freq_time) or pos_(freq_time). The configuration must contain
  channel labels in cfg.label or position information in cfg.pos. This
  information is used to determine the number of channels. 
  The dimord of the output fields is [prod(nchancmb,nfreq,ntime),1]. The
  channel combinations are the elements of the lower diagonal of the
  cross-spectral density matrix.
 
  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  = column number of the design that contains the labels of the conditions that
                must be compared (default=1). The labels are the numbers 1 and 2.

reference/ft_statfun_indepsampleszcoh.txt · Last modified: 2016/08/17 23:02 (external edit)

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