Pages that link to "Item:Q3866989"
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The following pages link to Selection of Dose Levels for Estimating a Percentage Point of a Logistic Quantal Response Curve (Q3866989):
Displaying 17 items.
- Adaptive Bayesian compound designs for dose finding studies (Q434557) (← links)
- Design issues for generalized linear models: a review (Q449737) (← links)
- Convergence properties of sequential Bayesian \(D\)-optimal designs (Q958799) (← links)
- Optimal Bayesian design applied to logistic regression experiments (Q1116597) (← links)
- Optimal Bayesian-feasible dose escalation for cancer phase I trials (Q1265963) (← links)
- Some alphabetic optimal designs for the logistic regression model (Q1338354) (← links)
- Bayesian D-optimal designs for the exponential growth model (Q1346666) (← links)
- Optimum designs for estimating \(ED_p\) based on raw optical density data (Q1600749) (← links)
- Bayesian design of experiment for quantal responses: What is promised versus what is delivered (Q1918447) (← links)
- Sequential designs for repeated-measures experiments (Q2323184) (← links)
- Bayesian Optimal Designs for Phase I Clinical Trials (Q3079157) (← links)
- Bayesian design for estimating the turning point of a quadratic regression (Q3474126) (← links)
- Selection of number of dose levels and its robustness for binary response data (Q3591886) (← links)
- A survey of literature on quantal response curves with a view toward application to the problem of selecting the curve with the smallest q-quantile (ediooq) (Q3738453) (← links)
- An approximate Bayesian up-down method for estimating a percentage point on a dose-response curve (Q4521418) (← links)
- Optimum Experimental Designs for Multinomial Logistic Models (Q4666582) (← links)
- Modified D-optimal design for logistic model (Q5219243) (← links)
