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A note on tests for relevant differences with extremely large sample sizes
Author(s) -
Callegaro Andrea,
Ndour Cheikh,
Aris Emmanuel,
Legrand Catherine
Publication year - 2019
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201800195
Subject(s) - sample size determination , statistics , sample (material) , statistical hypothesis testing , mathematics , econometrics , multiple comparisons problem , data set , set (abstract data type) , infinity , large sample , zero (linguistics) , computer science , linguistics , chemistry , philosophy , chromatography , programming language , mathematical analysis
A well‐known problem in classical two‐tailed hypothesis testing is that P ‐values go to zero when the sample size goes to infinity, irrespectively of the effect size. This pitfall can make the testing of data consisting of large sample sizes potentially unreliable. In this note, we propose to test for relevant differences to overcome this issue. We illustrate the proposed test on a real data set of about 40 million privately insured patients.