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    <p>The method is working fine. You just don't understand what the algorithm is doing fully apparently. I would suggest reading up a little bit about the procedure <a href="http://en.wikipedia.org/wiki/False_discovery_rate">(Wikipedia Link)</a>.</p> <pre><code>n &lt;- 40 p &lt;- runif(n, 0, 1) adjusted.p &lt;- p.adjust(p, "fdr") #same as p.adjust(p, "BH") ## Let's recreate. Going back to the paper we ## can construct a q-value by sorting the p-values ## and then applying the transformation: ## q_i = p_i*n/i ## Where p_i is the ith smallest p-value ## Sort the p-values and keep track of the order id &lt;- order(p) tmp &lt;- p[id] (q &lt;- tmp*n/(1:n)) # [1] 2.0322183 1.0993436 1.2357457 1.1113084 0.9282536 0.7877181 0.7348436 # [8] 0.7204077 0.6587102 0.6289974 0.9205222 0.8827835 0.8600234 0.8680704 #[15] 1.1532693 1.1055951 1.0451330 1.1314681 1.1167659 1.1453142 1.1012847 #[22] 1.0783747 1.0672471 1.0500311 1.0389407 1.0089661 1.0117881 0.9917817 #[29] 0.9892826 0.9668636 0.9844052 0.9792733 1.0000320 0.9967073 0.9707149 #[36] 0.9747723 0.9968153 0.9813367 1.0058445 0.9942353 ## However there is one more portion to the adjustment ## We don't want a p-value of .02 getting ## a larger q-value than a p-value of .05 ## so we make sure that if a smaller q-value ## shows up in the list we set all of ## the q-values corresponding to smaller p-values ## to that corresponding q-value. ## We can do this by reversing the list ## Keeping a running tally of the minimum value ## and then re-reversing new.q &lt;- rev(cummin(rev(q))) ## Put it back in the original order new.q[order(id)] # [1] 0.6289974 0.9668636 0.6289974 0.6289974 0.6289974 0.9707149 0.9707149 # [8] 0.8600234 0.9668636 0.6289974 0.9707149 0.9668636 0.9668636 0.9813367 #[15] 0.9668636 0.9668636 0.9668636 0.9707149 0.9668636 0.9668636 0.6289974 #[22] 0.9942353 0.8600234 0.6289974 0.9668636 0.6289974 0.6289974 0.8680704 #[29] 0.9668636 0.9668636 0.9668636 0.9942353 0.9707149 0.9813367 0.9668636 #[36] 0.8600234 0.6289974 0.9668636 0.9668636 0.9747723 ## This should match the adjustment adjusted.p # [1] 0.6289974 0.9668636 0.6289974 0.6289974 0.6289974 0.9707149 0.9707149 # [8] 0.8600234 0.9668636 0.6289974 0.9707149 0.9668636 0.9668636 0.9813367 #[15] 0.9668636 0.9668636 0.9668636 0.9707149 0.9668636 0.9668636 0.6289974 #[22] 0.9942353 0.8600234 0.6289974 0.9668636 0.6289974 0.6289974 0.8680704 #[29] 0.9668636 0.9668636 0.9668636 0.9942353 0.9707149 0.9813367 0.9668636 #[36] 0.8600234 0.6289974 0.9668636 0.9668636 0.9747723 </code></pre>
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    1. COYeah, I did a bit of research and found that this was reasonable given the parameters I was handing it. I was not familiar enough with FDR to recognize this. Thanks.
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