Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 847-858 |
| Seitenumfang | 12 |
| Fachzeitschrift | Statistics in medicine |
| Jahrgang | 22 |
| Ausgabenummer | 6 |
| Publikationsstatus | Veröffentlicht - 21 Feb. 2003 |
Abstract
Typical randomized clinical dose-finding studies consist of the comparison of several doses of a drug versus a placebo. Interest lies in estimating relevant doses among those under investigation for efficacy and safety variables, such as the minimum effective dose or the maximum safe dose (or estimating both doses simultaneously). Step-down procedures have been proposed for comparing the standardized differences of the dose groups against placebo. In this paper we consider the ratio of population means and propose stepwise confidence intervals for these ratios. These confidence intervals do not require multiplicity adjustments and yield the same decisions as the associated test procedures. In addition, several power concepts are investigated within the present framework. The results allow sample size determination in the design phase of a study for the probability of estimating correctly the dose of interest. Auxiliary results of a numerical study show the range of application of these methods.
ASJC Scopus Sachgebiete
- Medizin (insg.)
- Epidemiologie
- Mathematik (insg.)
- Statistik und Wahrscheinlichkeit
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in: Statistics in medicine, Jahrgang 22, Nr. 6, 21.02.2003, S. 847-858.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Identifying effective and/or safe doses by stepwise confidence intervals for ratios
AU - Bretz, Frank
AU - Hothorn, Ludwig A.
AU - Hsu, Jason C.
PY - 2003/2/21
Y1 - 2003/2/21
N2 - Typical randomized clinical dose-finding studies consist of the comparison of several doses of a drug versus a placebo. Interest lies in estimating relevant doses among those under investigation for efficacy and safety variables, such as the minimum effective dose or the maximum safe dose (or estimating both doses simultaneously). Step-down procedures have been proposed for comparing the standardized differences of the dose groups against placebo. In this paper we consider the ratio of population means and propose stepwise confidence intervals for these ratios. These confidence intervals do not require multiplicity adjustments and yield the same decisions as the associated test procedures. In addition, several power concepts are investigated within the present framework. The results allow sample size determination in the design phase of a study for the probability of estimating correctly the dose of interest. Auxiliary results of a numerical study show the range of application of these methods.
AB - Typical randomized clinical dose-finding studies consist of the comparison of several doses of a drug versus a placebo. Interest lies in estimating relevant doses among those under investigation for efficacy and safety variables, such as the minimum effective dose or the maximum safe dose (or estimating both doses simultaneously). Step-down procedures have been proposed for comparing the standardized differences of the dose groups against placebo. In this paper we consider the ratio of population means and propose stepwise confidence intervals for these ratios. These confidence intervals do not require multiplicity adjustments and yield the same decisions as the associated test procedures. In addition, several power concepts are investigated within the present framework. The results allow sample size determination in the design phase of a study for the probability of estimating correctly the dose of interest. Auxiliary results of a numerical study show the range of application of these methods.
KW - Multiple testing
KW - Partitioning principle
KW - Ratios
KW - Stepwise confidence intervals
KW - Therapeutic window
UR - http://www.scopus.com/inward/record.url?scp=0037473223&partnerID=8YFLogxK
U2 - 10.1002/sim.1449
DO - 10.1002/sim.1449
M3 - Article
C2 - 12627404
AN - SCOPUS:0037473223
VL - 22
SP - 847
EP - 858
JO - Statistics in medicine
JF - Statistics in medicine
SN - 0277-6715
IS - 6
ER -