Multiple comparisons, interaction effects, and statistical inference: lessons from chronic kidney disease progression among blacks | Zendy

Rajiv Agarwal | Zendy

Open Access

Multiple comparisons, interaction effects, and statistical inference: lessons from chronic kidney disease progression among blacks

Author(s) -

Rajiv Agarwal

Publication year - 2012

Publication title -

kidney international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.499

H-Index - 276

eISSN - 1523-1755

pISSN - 0085-2538

DOI - 10.1038/ki.2011.442

Subject(s) - kidney disease , inference , statistical inference , context (archaeology) , post hoc , medicine , disease , multiple comparisons problem , randomized controlled trial , statistical significance , alternative hypothesis , statistical hypothesis testing , econometrics , statistics , computer science , artificial intelligence , null hypothesis , mathematics , biology , paleontology

A post hoc analysis of a randomized trial comparing progression of chronic kidney disease among blacks and non-blacks provides an opportunity to explore statistical inference. Multiple comparisons without penalizing the P-value can lead to false positive results; this is illustrated using simulation. Tests of statistical interaction are then applied and interpreted to understand effect modification (or lack thereof) in the context of this trial.

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