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Journal of Bioinformatics ©
Volume
20(2):76-80, 2019
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.
Schuirmann’s versus nonparametric two 1-sided tests for non-normal data in pharmacokinetic
drug-drug Interaction Studies, Onl J Bioinform., 20(2):76-80, 2019. Schuirmann’s 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 Schuirmann’s 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 Schuirmann’s
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 Schuirmann’s
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.