Arbeitspapier
Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals
In dose-response studies, the dose range is often restricted due to ethics concerns over drug toxicity and/or efficacy, particularly when human subjects are involved. We present locally optimal designs for the estimation of several percentiles simultaneously on restricted as well as unrestricted design intervals. Our results are applicable to most of the commonly applied link functions with respect to the model under consideration. This work is a generalization of Dai (2000) where he showed that the same results hold for the logit model using Elfving?s approach on trace optimal design (Elfving, 1952).
- Language
-
Englisch
- Bibliographic citation
-
Series: Technical Report ; No. 2005,02
- Subject
-
Dose-response model
link function
percentile estimation
compound optimal design
A-optimality
- Event
-
Geistige Schöpfung
- (who)
-
Dette, Holger
Biedermann, Stefanie
Zhu, Wei
- Event
-
Veröffentlichung
- (who)
-
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
-
Dortmund
- (when)
-
2005
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Dette, Holger
- Biedermann, Stefanie
- Zhu, Wei
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2005
Other Objects (12)
Optimal designs for dose-response models with restricted design spaces
On robust and efficient designs for risk estimation in epidemiologic studies
Optimal discrimination designs
Robust designs for series estimation
Optimal designs for dose finding studies
Efficient experimental designs for sigmoidal growth models
Optimal experimental designs for inverse quadratic regression models
Finite sample performance of sequential designs for model identification
Robust and efficient designs for the Michaelis-Menten model
Optimal designs for estimating the slope of a regression
Constrained D- and D1-optimal designs for polynomial regression
Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals
Optimal designs for dose-response models with restricted design spaces
On robust and efficient designs for risk estimation in epidemiologic studies
Optimal discrimination designs
Robust designs for series estimation
Optimal designs for dose finding studies
Efficient experimental designs for sigmoidal growth models
Optimal experimental designs for inverse quadratic regression models
Finite sample performance of sequential designs for model identification
Robust and efficient designs for the Michaelis-Menten model
Optimal designs for estimating the slope of a regression
Constrained D- and D1-optimal designs for polynomial regression
Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals
Optimal designs for dose-response models with restricted design spaces
On robust and efficient designs for risk estimation in epidemiologic studies
Optimal discrimination designs
Robust designs for series estimation
Optimal designs for dose finding studies
Efficient experimental designs for sigmoidal growth models
Optimal experimental designs for inverse quadratic regression models
Finite sample performance of sequential designs for model identification
Robust and efficient designs for the Michaelis-Menten model
Optimal designs for estimating the slope of a regression
Constrained D- and D1-optimal designs for polynomial regression