6533b858fe1ef96bd12b5b1a
RESEARCH PRODUCT
Multivariate equivalence tests for use in pharmaceutical development.
Rüdiger GösslStefan WellekThomas Hoffeldersubject
PharmacologyStatistics and ProbabilityMultivariate statisticsMahalanobis distanceEquivalence testingDrug Industrybusiness.industryUnivariateNormal DistributionMachine learningcomputer.software_genreDelta methodPharmaceutical PreparationsSolubilityResearch DesignData Interpretation StatisticalMultivariate AnalysisEconometricsNuisance parameterPharmacology (medical)Artificial intelligencebusinesscomputerEquivalence (measure theory)Mathematicsdescription
Statistical equivalence analyses are well-established parts of many studies in the biomedical sciences. Also in pharmaceutical development and manufacturing equivalence testing methods are required in order to statistically establish similarities between machines, process components, or complete processes. This article presents a choice of multivariate equivalence testing procedures for normally distributed data as generalizations of existing univariate methods. In all derived methods, variability is interpreted as nuisance parameter. The use of the proposed methods in pharmaceutical development is demonstrated with a comparative analysis of dissolution profiles.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-06-05 | Journal of biopharmaceutical statistics |