ERF for Frambozadrine in rats
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Question
Frambozadrine dose-response function in rats describes the long-term health impact(s) caused by frambozadrine as a function of dose in rats. This dose-response function applies only to continuous long-term exposures of frambozadrine (like in chronic studies).
Answer
It is not clear which of the plausible methods for estimating the result is the best. The discussion is ongoing. D↷
You have error(s) in your data:
Number of indices and result cells does not match
Non-parametric Bayesian estimation
Males and Females combined
| Dose levels | MLE | Prior | Posterior mean | Variance |
|---|---|---|---|---|
| 0 | 0.053 | 0.125 | 0.0571 | 0.0634 |
| 1.2 | 0.133 | 0.25 | 0.1052 | 0.0348 |
| 1.8 | 0.102 | 0.375 | 0.13 | 0.0241 |
| 15 | 0.091 | 0.5 | 0.154 | 0.021 |
| 21 | 0.064 | 0.625 | 0.1799 | 0.0551 |
| 82 | 0.511 | 0.75 | 0.4969 | 0.2762 |
| 109 | 0.687 | 0.875 | 0.687 | 0.2778 |
Rationale
Causality
Upstream variables not defined.
Data
Toxicological data about frambozadrine in rats.
| Dose(mg/kg-day) | Total no rats | Hyperkeratosis |
|---|---|---|
| Male | ||
| 0 | 47 | 2 |
| 1.2 | 45 | 6 |
| 15 | 44 | 4 |
| 82 | 47 | 24 |
| Female | ||
| 0 | 48 | 3 |
| 1.8 | 49 | 5 |
| 21 | 47 | 3 |
| 109 | 48 | 33 |
Plausible dose-response functions
- Generalized dose-response function
- Multistage model (first order)
- Multistage model (second order)
- Weibull model
Unit
probability of impact
Formula
Methods for estimating dose-responses
- Bootstrap method
- Probabilistic inversion
- Non-parametric Bayesian estimation
- Bayesian model averaging