Well, I couldn't find that specific website but here is another one. Please let me know if you found any cite-able references for this purpose.
As I had this problem and took me a while to figure it out, I thought it may be useful to someone else.
For anova_rm to be compatible with multcompare function of MATLAB, we need a stat output. I read somewhere (I printed out the webpage about a year ago but I can't find it anymore) that the post-hoc for repeated measures anova is the same as independent measures anova. You just need to replace MS(within) with MS(error) and df(within) with df(error) and then use Tuckey's equation to find the critical value. Thus, as I work with anova_rm as a one-way measure, I added the following lines at the end of anova_rm and added "stat" variable to the output of the function. I can now feed this stat to multcompare and the function sees stat as the output of anova1 and estimates the critical value using Tuckey (if that is your selected ctype) in the same way it does for anova1. As I don't use it for two-way measures, I haven't checked how to define stat for that purpose but I am sure it shouldn't be hard now.
Works (almost) good.
However it does not detect all peaks, I think there is a bug. The index in lines 186ff for finding the valley should be different from ii, e.g. jj:
jj = ii+1; % Move onto the valley
% Come down at least sel from peak
if ~foundPeak && tempMag > sel + x(jj)
foundPeak = true; % We have found a peak
leftMin = x(jj);
peakLoc(cInd) = tempLoc; % Add peak to index
peakMag(cInd) = tempMag;
cInd = cInd+1;
elseif x(jj) < leftMin % New left minima
leftMin = x(jj);