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Description: This OSF project is associated with a study that evaluates the robustness of various dispersion measures. It builds on recent methodological work, which has argued that dispersion should be measured across linguistically meaningful units such as the text files constituting a corpus. This shift to texts as the unit of analysis raises new methodological issues, however. This paper sheds light on the robustness of different measures, i.e. whether they are (overly) sensitive to data situations that can arise when texts differ (considerably) in length. We identify weak spots in existing measures, and then propose modifications to DP- and DA-related indexes to effect more resistant estimators. Along with other measures, these are then evaluated using data drawn from the BNC. We observe that our modified variants perform at least as well as their original versions. We also find that Carroll’s D2 shows the same weakness as Juilland’s D, a noticeable sensitivity to the number of units that enter the analysis.


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