Overcoming Model Uncertainty - How Equivalence Tests Can Benefit From Model Averaging.

ABSTRACT: A common problem in numerous research areas, particularly in clinical trials, is to test whether the effect of an explanatory variable on an outcome variable is equivalent across different groups. In practice, these tests are frequently used to compare the effect between patient groups, for example, based on gender, age, or treatments. Equivalence is usually assessed by testing whether the difference between the groups does not exceed a pre-specified equivalence threshold. Classical approaches are based on testing the equivalence of single quantities, for example, the mean, the area under the curve or other values of interest. However, when differences depending on a particular covariate are observed, these approaches can turn out to be not very accurate. Instead, whole regression curves o

SUBMITTER: Hagemann N 

PROVIDER: S-EPMC11923417 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature