Many of the currently available statistical indexes to detect answer copying lack sufficient power at small [alpha] levels or when the amount of copying is relatively small. Furthermore, there is no one index that is uniformly best. Depending on the type or amount of copying, certain indexes are better than others. The purpose of this article was to explore the utility of simultaneously using multiple copying indexes to detect different types and amounts of answer copying. This study compared eight copying indexes: S[1] and S[2] (Sotaridona and Meijer, 2003), K[upper bar] [2] (Sotaridona & Meijer, 2002), [omega] (Wollack, 1997), B and H (Angoff, 1974), and new indexes Runs and MaxStrings, plus all possible pairs and triplets of the 8 indexes using multiple comparison procedures (Dunn, 1961) to adjust the critical a level for each index in a pair or triplet. Empirical Type-I error rates and power of all indexes, pairs, and triplets were examined in a real data simulation (i.e., where actual examinee responses to items [rather than generated item response vectors] were changed to match the actual responses for randomly selected source examinees) for 2 test lengths, 9 sample sizes, 3 types of copying, 4 [alpha] levels, and 4 percentages of items copied. This study found that using both [omega] and H* (i.e., H with empirically derived critical values) can help improve power in the most realistic types of copying situations (strings and mixed copying). The [omega]-H* paired index improved power most particularly for small percentages of items copied and small amounts of copying, two conditions for which copying indexes tend to be underpowered.