Details
| Original language | English |
|---|---|
| Pages (from-to) | 193-207 |
| Number of pages | 15 |
| Journal | Journal of Biopharmaceutical Statistics |
| Volume | 11 |
| Issue number | 3 |
| Publication status | Published - 1 Jan 2001 |
Abstract
Usually, a monotone dose-response dependence can be assumed for the simultaneous comparison of increasing levels of a certain drug. However, sometimes a reversal of the dose-response curve is likely to occur at the higher doses. We investigate such violations of the monotonicity assumption. Adequate alternatives are discussed and the "protected trend alternative" is introduced. Together with the umbrella patterns described in the literature, we introduce new testing approaches for both alternatives. P-values/quantiles and power values/sample sizes are made numerically available and hence are readily computed. A short power study and the analysis of a data set from the literature demonstrate the improved behavior of the new methods.
Keywords
- Dose-response analysis, Multiple contrast tests, Multivariate t-distribution, Nonmonotone shapes, Simultaneous confidence intervals
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Pharmacology, Toxicology and Pharmaceutics(all)
- Pharmacology
- Medicine(all)
- Pharmacology (medical)
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Journal of Biopharmaceutical Statistics, Vol. 11, No. 3, 01.01.2001, p. 193-207.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Testing dose-response relationships with a priori unknown, possibly nonmonotone shapes
AU - Bretz, F.
AU - Hothorn, L. A.
PY - 2001/1/1
Y1 - 2001/1/1
N2 - Usually, a monotone dose-response dependence can be assumed for the simultaneous comparison of increasing levels of a certain drug. However, sometimes a reversal of the dose-response curve is likely to occur at the higher doses. We investigate such violations of the monotonicity assumption. Adequate alternatives are discussed and the "protected trend alternative" is introduced. Together with the umbrella patterns described in the literature, we introduce new testing approaches for both alternatives. P-values/quantiles and power values/sample sizes are made numerically available and hence are readily computed. A short power study and the analysis of a data set from the literature demonstrate the improved behavior of the new methods.
AB - Usually, a monotone dose-response dependence can be assumed for the simultaneous comparison of increasing levels of a certain drug. However, sometimes a reversal of the dose-response curve is likely to occur at the higher doses. We investigate such violations of the monotonicity assumption. Adequate alternatives are discussed and the "protected trend alternative" is introduced. Together with the umbrella patterns described in the literature, we introduce new testing approaches for both alternatives. P-values/quantiles and power values/sample sizes are made numerically available and hence are readily computed. A short power study and the analysis of a data set from the literature demonstrate the improved behavior of the new methods.
KW - Dose-response analysis
KW - Multiple contrast tests
KW - Multivariate t-distribution
KW - Nonmonotone shapes
KW - Simultaneous confidence intervals
UR - http://www.scopus.com/inward/record.url?scp=0035149117&partnerID=8YFLogxK
U2 - 10.1081/BIP-100107657
DO - 10.1081/BIP-100107657
M3 - Article
C2 - 11725931
AN - SCOPUS:0035149117
VL - 11
SP - 193
EP - 207
JO - Journal of Biopharmaceutical Statistics
JF - Journal of Biopharmaceutical Statistics
SN - 1054-3406
IS - 3
ER -