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Ratios: A short guide to confidence limits and proper use

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arxiv 0710.2024 v1 pith:XCIGPPUA submitted 2007-10-10 stat.AP stat.ME

classification stat.APstat.ME
keywords methodsratiosappropriateconfidencemethodwhenfiellerlimits
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Researchers often calculate ratios of measured quantities. Specifying confidence limits for ratios is difficult and the appropriate methods are often unknown. Appropriate methods are described (Fieller, Taylor, special bootstrap methods). For the Fieller method a simple geometrical interpretation is given. Monte Carlo simulations show when these methods are appropriate and that the most frequently used methods (index method and zero-variance method) can lead to large liberal deviations from the desired confidence level. It is discussed when we can use standard regression or measurement error models and when we have to resort to specific models for heteroscedastic data. Finally, an old warning is repeated that we should be aware of the problems of spurious correlations if we use ratios.

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Cited by 1 Pith paper

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  1. Sample size calculations for the experimental comparison of multiple algorithms on multiple problem instances

    stat.ME 2019-08 conditional novelty 5.0 of 10

    A method for computing the required number of instances and per-instance runs when comparing multiple algorithms, based on pairwise effect sizes, power, and Holm-corrected error rates.

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