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Online Journal of Bioinformatics ©

Volume 20(2):76-80, 2019

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Schuirmannís versus nonparametric two one-sided tests for non-normal data in pharmacokinetic drug-drug interactions


Zhou J1, He Y2, Yuan Y1


1Department of Clinical Biostatistics, Pfizer Global Research and Development, La Jolla Laboratories, 11085 Torreyana Road, San Diego, California, 92121, USA. 2Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, 48109 USA.




Schuirmannís versus nonparametric two 1-sided tests for non-normal data in pharmacokinetic drug-drug Interaction Studies, Onl J Bioinform., 20(2):76-80, 2019. Schuirmannís two one-sided tests (TOST) approach is widely used in clinical drug-drug interaction studies. However, it requires normality assumption, which may not hold in practice. The objective of this paper was to investigate the statistical performance of Schuirmannís TOST procedure for non-normal data, and then to compare it with nonparametric TOSTs. Monte Carlo simulations were used to generate non-normal data with different skewness and kurtosis. The statistical performances of Schuirmannís TOST and nonparametric method-based TOSTs were compared in terms of empirical power, size and coverage probability. The nonparametric TOST approaches were based on Wilcoxon signed-rank test, Jackknife method, and Bootstrap methods. Our simulations show that Schuirmannís TOST is fairly robust to slightly skewed data, but may have poor performance when data are heavily skewed. In contrast, Bootstrap-T approach consistently yields the best coverage probabilities and reasonable empirical sizes.


KEY-WORDS: drug-drug interaction, two-one sided tests, nonparametric, clinical trial.