Efficient experimental design for dose response modelling
| Autor: | Timothy E. O'Brien, Jack W Silcox |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
021103 operations research Binomial (polynomial) Response model Logit 0211 other engineering and technologies Machine Learning and Other Topics 02 engineering and technology Function (mathematics) Logistic regression 01 natural sciences Median lethal dose 010104 statistics & probability Goodness of fit Statistics Bioassay 0101 mathematics Statistics Probability and Uncertainty health care economics and organizations Mathematics |
| Zdroj: | J Appl Stat |
| ISSN: | 1360-0532 0266-4763 |
| DOI: | 10.1080/02664763.2021.1880556 |
| Popis: | The logit binomial logistic dose response model is commonly used in applied research to model binary outcomes as a function of the dose or concentration of a substance. This model is easily tailored to assess the relative potency of two substances. Consequently, in instances where two such dose response curves are parallel so one substance can be viewed as a dilution of the other, the degree of that dilution is captured in the relative potency model parameter. It is incumbent that experimental researchers working in fields including biomedicine, environmental science, toxicology and applied sciences choose efficient experimental designs to run their studies to both fit their dose response curves and to garner important information regarding drug or substance potency. This article provides far-reaching practical design strategies for dose response model fitting and estimation of relative potency using key illustrations. These results are subsequently extended here to handle situations where the assessment of parallelism and the proper dose-scale are also of interest. Conclusions and recommended strategies are supported by both theoretical and simulation results. |
| Databáze: | OpenAIRE |
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