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

  FT_TIMELOCKSTATISTICS  computes significance probabilities and/or critical values of a parametric statistical test
  or a non-parametric permutation test.
  Use as
    [stat] = ft_timelockstatistics(cfg, timelock1, timelock2, ...)
  where the input data is the result from either FT_TIMELOCKANALYSIS or
  The configuration can contain the following options for data selection     = Nx1 cell-array with selection of channels (default = 'all'),
                      see FT_CHANNELSELECTION for details
    cfg.latency     = [begin end] in seconds or 'all' (default = 'all')
    cfg.avgoverchan = 'yes' or 'no'                   (default = 'no')
    cfg.avgovertime = 'yes' or 'no'                   (default = 'no')
    cfg.parameter   = string                          (default = 'trial' or 'avg')
  Furthermore, the configuration should contain
    cfg.method       = different methods for calculating the significance probability and/or critical value
                     'montecarlo'    get Monte-Carlo estimates of the significance probabilities and/or critical values from the permutation distribution,
                     'analytic'      get significance probabilities and/or critical values from the analytic reference distribution (typically, the sampling distribution under the null hypothesis),
                     'stats'         use a parametric test from the MATLAB statistics toolbox,
                     'crossvalidate' use crossvalidation to compute predictive performance
  The other cfg options depend on the method that you select. You
  should read the help of the respective subfunction FT_STATISTICS_XXX
  for the corresponding configuration options and for a detailed
  explanation of each method.
  To facilitate data-handling and distributed computing you can use
    cfg.inputfile   =  ...
    cfg.outputfile  =  ...
  If you specify one of these (or both) the input data will be read from a *.mat
  file on disk and/or the output data will be written to a *.mat file. These mat
  files should contain only a single variable, corresponding with the
  input/output structure.