Multivariate equivalence testing for food safety assessment

Leday, Gwenaël G. R.; Engel, Jasper; Vossen, Jack H.; Vos, Ric C. H. de; Voet, Hilko van der

doi:10.1016/j.fct.2022.113446

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…In recent years, bioequivalence studies have garnered significant attention in the literature, reflecting an increasing focus on refining methodologies and addressing nuanced challenges. Notably, [1] delved into the multiple testing problem within the realm of equivalence testing for food safety. Their work critically compared various methods aimed at controlling the family-wise error rate, contributing valuable insights to this crucial area of study.…”

Section: Introductionmentioning

confidence: 99%

Choosing Confidence Intervals in Bioequivalence Studies: 100(1 - 2\(\alpha\) )% and 100(1 - \(\alpha\) )% Approaches

Li,

Sinks,

Sun

et al. 2024

AJPAS

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A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assigned to receive two formulations. The two formulations are then compared with respect to their pharmacokinetic profiles, which encompass the absorption, distribution, metabolism, and elimination of the drug. Under the guidance from Food and Drug Administration (FDA), for a size-\(\alpha\) bioequivalence test, the standard approach is to construct a 100(1 - 2\(\alpha\))% confidence interval and verify if the confidence interval falls with the critical region. In this work, we clarify that 100(1-2\(\alpha\))% confidence interval approach for bioequivalence testing yields a size-\(\alpha\) test only when the two one-sided tests in TOST are "equal-tailed". Furthermore, a 100(1 - \(\alpha\))% confidence interval approach is also discussed in the bioequivalence study.

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Section: Introductionmentioning

confidence: 99%

Choosing Confidence Intervals in Bioequivalence Studies: 100(1 - 2\(\alpha\) )% and 100(1 - \(\alpha\) )% Approaches

Li,

Sinks,

Sun

et al. 2024

AJPAS

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show abstract

“…More recent examples include Goertzen and Cribbie (2010) who highlight the importance of using equivalence tests to establish the independence of two different variables (i.e., for establishing negligible correlations), Counsell et al (2020) who consider equivalence testing methods for measurement invariance, and Marcoulides and Yuan (2017) who consider equivalence testing for assessing structural equation models. Outside of psychology, there is also a growing literature on equivalence testing methods (e.g., Leday et al, 2022; Shen, 2023).…”

mentioning

confidence: 99%

Equivalence testing for linear regression.

Campbell

2024

Psychological Methods

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We introduce equivalence testing procedures for linear regression analyses. Such tests can be very useful for confirming the lack of a meaningful association between a continuous outcome and a continuous or binary predictor. Specifically, we propose an equivalence test for unstandardized regression coefficients and an equivalence test for semipartial correlation coefficients. We review how to define valid hypotheses, how to calculate p values, and how these tests compare to an alternative Bayesian approach with applications to examples in the literature.

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