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<title>Annals of the Rheumatic Diseases Viewpoint</title>
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<title><![CDATA[Adjustment of p values for multiple hypotheses: why, when and how]]></title>
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<p>It is quite common to investigate multiple hypotheses in a single study. For example, a researcher may want to investigate the effect on several outcome variables or at different time points, compare more than two groups or undertake separate analyses for subgroups. This increases the probability of type I errors. Different procedures for multiplicity adjustment are available to control the probability of type I errors. In the present article, we describe some methods for multiplicity adjustment, along with recommendations.</p>
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<dc:creator><![CDATA[Lydersen, S.]]></dc:creator>
<dc:date>2024-09-30T06:17:14-07:00</dc:date>
<dc:identifier>info:doi/10.1136/ard-2024-225537</dc:identifier>
<dc:identifier>hwp:master-id:annrheumdis;ard-2024-225537</dc:identifier>
<dc:publisher>BMJ Publishing Group Ltd</dc:publisher>
<dc:subject><![CDATA[Editor's choice, ARD]]></dc:subject>
<dc:title><![CDATA[Adjustment of p values for multiple hypotheses: why, when and how]]></dc:title>
<prism:publicationDate>2024-10-01</prism:publicationDate>
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