A robust likelihood approach to inference about the difference between two multinomial distributions in paired designs

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

Pairing serves as a way of lessening heterogeneity but pays the price of introducing more parameters to the model. This complicates the probability structure and makes inference more intricate. We employ the simpler structure of the parallel design to develop a robust score statistic for testing the equality of two multinomial distributions in paired designs. This test incorporates the within-pair correlation in a data-driven manner without a full model specification. In the paired binary data scenario, the robust score statistic turns out to be the McNemar’s test. We provide simulations and real data analysis to demonstrate the advantage of the robust procedure.

原文???core.languages.en_GB???
頁(從 - 到)3077-3091
頁數15
期刊Statistical Methods in Medical Research
27
發行號10
DOIs
出版狀態已出版 - 1 10月 2018

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