Confidence intervals for ratio of two Poisson rates using the method of variance estimates recovery

Hui-Qiong Li, Man-Lai Tang and Weng-Kee Wong ()

Computational Statistics, 2014, vol. 29, issue 3, 869-889

Abstract: Inference based on ratio of two independent Poisson rates is common in epidemiological studies. We study the performance of a variety of unconditional method of variance estimates recovery (MOVER) methods of combining separate confidence intervals for two single Poisson rates to form a confidence interval for their ratio. We consider confidence intervals derived from (1) the Fieller’s theorem, (2) the logarithmic transformation with the delta method and (3) the substitution method. We evaluate the performance of 13 such types of confidence intervals by comparing their empirical coverage probabilities, empirical confidence widths, ratios of mesial non-coverage probability and total non-coverage probabilities. Our simulation results suggest that the MOVER Rao score confidence intervals based on the Fieller’s theorem and the substitution method are preferable. We provide two applications to construct confidence intervals for the ratio of two Poisson rates in a breast cancer study and in a study that examines coronary heart diseases incidences among post menopausal women treated with or without hormones. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Agresti–Coull Binomial method; Bayes interval; Fieller’s theorem; Jeffreys interval; MOVER method; Rao score (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:29:y:2014:i:3:p:869-889

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DOI: 10.1007/s00180-013-0467-9

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