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

FT_STATFUN_INDEPSAMPLESF calculates the independent samples F-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_indepsamplesF'

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 labels of the conditions that must be
compared (default=1). The labels range from 1 to the number of conditions.