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- W2891314889 abstract "Topic set size design is an approach to determining the sample sizes of an experiment (e.g., number of topics) based on a statistical requirement, namely a desired statistical power or a cap on the confidence interval (CI) width for the difference in means. Previous work considered paired data cases for a desired power of the t-test and for a cap on CI width, as well as unpaired data cases for a desired power of one-way ANOVA. In the present study, we consider unpaired (i.e., two-sample) cases for the t-test and for the CI width. Since one-way ANOVA with two groups is strictly equivalent to the two-sample t-test, we compare the outcomes of the topic set size design results based on these two approaches, and show that the one-way ANOVA-based approach actually returns tighter sample sizes than the two-sample t-test approach. Moreover, we compare the paired and unpaired cases for both t-test-based and CI-based topic set size design approaches. Because estimating the variance of the score differences for the paired data setting is problematic, we recommend the use of our unpaired-data versions of t-test-based and CI-based topic set size design tools, as they only require a variance estimate for individual scores and the appropriate sample sizes for unpaired data are also large enough for paired data." @default.
- W2891314889 created "2018-09-27" @default.
- W2891314889 creator A5023595778 @default.
- W2891314889 date "2018-09-10" @default.
- W2891314889 modified "2023-09-26" @default.
- W2891314889 title "Topic Set Size Design for Paired and Unpaired Data" @default.
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- W2891314889 doi "https://doi.org/10.1145/3234944.3234971" @default.
- W2891314889 hasPublicationYear "2018" @default.
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