We present a new application of sampled permutation testing to examine whether two sequential associations are different within a single dyad (e.g., a teacher and a student). A Monte Carlo simulation with the same (i.e., 100 vs. 100) or a different (100 vs. 400) number of event pairs was used to simulate designs that use time-based (typically producing equal-length comparisons) and event-based (typically producing different-length comparisons) data, respectively. For these pairs of simulated data streams, we compared the Type I error rates and the kappa for agreement on significance decisions, using the sampled permutation tests and the more traditional asymptotic log linear analysis. The results provide the first evidence relevant to evaluating the accuracy of log linear analysis and sampled permutation testing for the purpose of comparing sequential associations within a single dyad.