Hi Amy,

CONN will use T-stats for ANOVAs with two levels for each factor and F-stats for ANOVAs with three or more levels (for details about GLM stats see https://web.conn-toolbox.org/fmri-method...). In reality that is somewhat arbitrary since two-sided T-stats and F- stats are exactly equivalent (and the only reason to use T- instead of F- values in this case is just to also allow directional tests). If you want to transform T-stats to F-stats simply use the equivalence:

T(df) ^2 = F(1,df)

So, for example, if CONN reports in voxel-based analyses |T(15)|>3, you may simply report instead F(1,15)>9; or if in an ROI-to-ROI analysis you are obtaining "T(15) = 2, p = 0.0639 (two-tailed)", you may equivalently report that as "F(1,15) = 4, p =0.0639"

Best
Alfonso

ps. you may check this equivalence with the syntax:
  T=randn;                       % T-stat value
  df=randi([1 10]);            % degrees of freedom
  p1=1-spm_Tcdf(T,df);    % one-sided p-value (T-stat)
  p1=2*min(p1,1-p1);       % two-sided p-value (T-stat)
  p2=1-spm_Fcdf(T^2,1,df); % p-value (F-stat)
  disp([p1 p2])

Originally posted by Amy Bouchard: