Thank you so much for your reply. Can I ask you please to clarify a few things for me please? I really want to understand this. * When you say "simulate a bunch of values from the appropriate MVN distribution (actually multivariate t)". Do you mean, generate a lot of datasets, say 100 to keep things simple, from a mvt which has means which match the means of your k contrasts/estimates and covariance that matches the covariance of your k contrasts/means? * Then you say "use quantiles of the simulated distribution of estimates to find the critical value (delta) that works simultaneously for all the estimates.". My guess at what this means is, for the each datasets you have simulated, calculate the value of each of the k contrasts, so if k=2, and 100 datasets, you have 100 values for each contrast. Then I'm not sure how you find the critical value. You mention later to use (1-alpha)th quantile. So if alpha is 5%, is the 95th ordered value from the 100 values I have for each k my critical value? *Then "Make a bunch of draws of the form (t1, t2, ..., tk) and for each draw compute the statistic max(|t1|, ..., |tk|).". I'm lost here, am I randomly selecting a value from the 100 values I have for each k, so in my case I would have two values, then select the max of these and build up a distribution of these I guess. Sorry, I'm not sure what happens now.
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