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are randomly go or stop trials, where go trials occur with probability .75 and stop trials with probability 0.25. Aside from the GLYPH<133>rst trial in a session, the remaining trials may be classiGLYPH<133>ed into four groups based on the current and previous trial as go-go with probability 0 : 75 2 = 0 : 5625 , stop-go with probability 0 : 25 GLYPH<2> 0 : 75 = 0 : 1875 , go-stop with probability 0 : 75 GLYPH<2> 0 : 25 = 0 : 1875 , and stop-stop with probability 0 : 25 2 = 0 : 0625 . If there is no interference, then the treatment at the current trial may have an e⁄ect, but not the treatment at the previous trial, so go-go should have the same e⁄ect as stop-go, and go-stop should have the same e⁄ect as stop-stop. Table 3 compares the two common cases, go-go to stop-go trials, ignoring other cases, using the same methods as in Table 2, reporting only results for GLYPH<133>ltered data. In Table 3, a di⁄erence indicates a very speciGLYPH<133>c form of interference, namely a lingering e⁄ect from a previous stop trial on a current go trial. There is clearly evidence in Table 3 of a lingering e⁄ect of a previous stop trial, but the magnitudes of e⁄ect are much smaller than in Table 2 for the e⁄ect of the treatment in the current trial. Importantly, the inferences in Table 3 are appropriate for comparing go-go and stop-go trials even if other forms of interference are also present. 

Head movements during the experiment may distort fMRI readings. As discussed and illustrated in Rosenbaum (2007, §6), instead of studying the attributable e⁄ect for the responses themselves, the method in Rosenbaum (2002) may be used as the basis for randomization inference about the attributable e⁄ect on residuals from a robust covariance 

