The Tukey trend test: Multiplicity adjustment using multiple marginal models
Research output: Contribution to journal › Journal article › Research › peer-review
Documents
- Schaarschmidt et al_Biometrics_2022_Vol 78(2)_789-797
Final published version, 262 KB, PDF document
In dose-response analysis, it is a challenge to choose appropriate linear or curvilinear shapes when considering multiple, differently scaled endpoints. It has been proposed to fit several marginal regression models that try sets of different transformations of the dose levels as explanatory variables for each endpoint. However, the multiple testing problem underlying this approach, involving correlated parameter estimates for the dose effect between and within endpoints, could only be adjusted heuristically. An asymptotic correction for multiple testing can be derived from the score functions of the marginal regression models. Based on a multivariate t-distribution, the correction provides a one-step adjustment of p-values that accounts for the correlation between estimates from different marginal models. The advantages of the proposed methodology is demonstrated through three example data sets, involving generalized linear models with differently scaled endpoints, differing covariates and a mixed effect model and through simulation results. The methodology is implemented in an R package.
Original language | English |
---|---|
Journal | Biometrics |
Volume | 78 |
Issue number | 2 |
Pages (from-to) | 789-797 |
Number of pages | 9 |
ISSN | 0006-341X |
DOIs | |
Publication status | Published - 2022 |
Bibliographical note
This article is protected by copyright. All rights reserved.
- Faculty of Science - Adjustment of p-values, Dose-response, Multiple endpoints, Multivariate normal, Toxicology
Research areas
Number of downloads are based on statistics from Google Scholar and www.ku.dk
ID: 256626097