2016
DOI: 10.1093/ije/dyw320
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An introduction to multiplicity issues in clinical trials: the what, why, when and how

Abstract: In clinical trials it is not uncommon to face a multiple testing problem which can have an impact on both type I and type II error rates, leading to inappropriate interpretation of trial results. Multiplicity issues may need to be considered at the design, analysis and interpretation stages of a trial. The proportion of trial reports not adequately correcting for multiple testing remains substantial. The purpose of this article is to provide an introduction to multiple testing issues in clinical trials, and to… Show more

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Cited by 229 publications
(235 citation statements)
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“…Hence, the results from the present study should be interpreted cautiously. However, when interpreting these analyses, it is also imperative to consider that (a) multiplicity adjustments primarily apply to confirmatory hypotheses and corresponding analyses, not for exploratory analyses 22,50,51 ; (b) the lack of statistical power have limited us to handle the necessary α-adjustments, 50,51 and (c) the Hochberg procedure is more conservative and less powerful than other semi-parametric and parametric tests. 21,22 Some limitations need to be mentioned: (a) the crosssectional design of the study does not allow us to make causal inferences; (b) the results should be interpreted with caution given the small size of the studied sample; (c) only interested participants were involved in the study; (d) a selfreported survey was used to collect sociodemographic and clinical data.…”
Section: Discussionmentioning
confidence: 99%
“…Hence, the results from the present study should be interpreted cautiously. However, when interpreting these analyses, it is also imperative to consider that (a) multiplicity adjustments primarily apply to confirmatory hypotheses and corresponding analyses, not for exploratory analyses 22,50,51 ; (b) the lack of statistical power have limited us to handle the necessary α-adjustments, 50,51 and (c) the Hochberg procedure is more conservative and less powerful than other semi-parametric and parametric tests. 21,22 Some limitations need to be mentioned: (a) the crosssectional design of the study does not allow us to make causal inferences; (b) the results should be interpreted with caution given the small size of the studied sample; (c) only interested participants were involved in the study; (d) a selfreported survey was used to collect sociodemographic and clinical data.…”
Section: Discussionmentioning
confidence: 99%
“…Data are presented as mean ± standard deviation, and P values less than .05 were considered statistically significant. Because this was a secondary data analysis, no adjustments for multiple comparisons were made …”
Section: Methodsmentioning
confidence: 99%
“…P values were not corrected for multiple testing, as this study was of exploratory nature. [25][26][27]…”
Section: Multi-parameter Regression Modellingmentioning
confidence: 99%