Adaptive Designs for Dose-Finding Studies Based on SigmoidEmaxModel
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2007/11/08
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Indian UGC (journal)
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Refrences16
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Citations42
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Vladimir Dragalin a Wyeth Research , Collegeville, Pennsylvania, USA
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Francis Hsuan b Department of Statistics , Temple University , Philadelphia, Pennsylvania, USA
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S. Krishna Padmanabhan a Wyeth Research , Collegeville, Pennsylvania, USAb Department of Statistics , Temple University , Philadelphia, Pennsylvania, USA
Cite
Dragalin, Vladimir, et al. “Adaptive Designs for Dose-Finding Studies Based on SigmoidEmaxModel”. Journal of Biopharmaceutical Statistics, vol. 17, no. 6, 2007, pp. 1051-70, https://doi.org/10.1080/10543400701643954.
Dragalin, V., Hsuan, F., & Padmanabhan, S. K. (2007). Adaptive Designs for Dose-Finding Studies Based on SigmoidEmaxModel. Journal of Biopharmaceutical Statistics, 17(6), 1051-1070. https://doi.org/10.1080/10543400701643954
Dragalin, Vladimir, Francis Hsuan, and S. Krishna Padmanabhan. “Adaptive Designs for Dose-Finding Studies Based on SigmoidEmaxModel”. Journal of Biopharmaceutical Statistics 17, no. 6 (2007): 1051-70. https://doi.org/10.1080/10543400701643954.
Dragalin V, Hsuan F, Padmanabhan SK. Adaptive Designs for Dose-Finding Studies Based on SigmoidEmaxModel. Journal of Biopharmaceutical Statistics. 2007;17(6):1051-70.
Journal Categories
Medicine
Public aspects of medicine
Toxicology
Poisons
Medicine
Therapeutics
Pharmacology
Science
Mathematics
Probabilities
Mathematical statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Adaptive designs for dose-finding based on efficacy–toxicity response | Journal of Statistical Planning and Inference |
| 85 | 2006 |
| 10.1093/oso/9780198522546.001.0001 | 1992 | |||
| Dose Finding in Drug Development | 2006 | |||
| Mixed-Effects Models in S and S-Plus | 2004 | |||
| Linear and Nonlinear Models for the Analysis of Repeated Measurements | 1997 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| A new methodology to robustify an experimental design: Application to the Baranyi model | Chemometrics and Intelligent Laboratory Systems |
| 2024 | |
A Bayesian quasi-likelihood design for identifying the minimum effective dose and maximum utility dose in dose-ranging studies | Statistical Methods in Medical Research |
| 2024 | |
Designs for the simultaneous inference of concentration–response curves | BMC Bioinformatics |
| 2023 | |
Optimal adaptive allocation using deep reinforcement learning in a dose‐response study | Statistics in Medicine |
| 2021 | |
Adaptive Designs for Optimal Observed Fisher Information | Journal of the Royal Statistical Society Series B: Statistical Methodology |
| 2 | 2020 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 32
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled The Hill equation: a review of its capabilities in pharmacological modelling and was published in 2008. The most recent citation comes from a 2024 study titled A Bayesian quasi-likelihood design for identifying the minimum effective dose and maximum utility dose in dose-ranging studies. This article reached its peak citation in 2014, with 6 citations. It has been cited in 28 different journals, 3% of which are open access. Among related journals, the Statistics in Medicine cited this research the most, with 7 citations. The chart below illustrates the annual citation trends for this article.