$$P(response)=1-[1+dose\frac{2^{\frac{1}{a}}-1}{N^{50}} ]^{-a}$$

Description
Host
black-spotted and spiny frogs
# of Doses
7.00
Μodel
N50
2.37E+05 [1.06E+05, 5.49E+05], β = 86,351 [16,154, 632,550]
LD50/ID50
2.37E+05 [1.06E+05, 5.49E+05]
Dose Units
Response
Contains Preferred Model
Status
pooled
a
0.52 [0.27, 1.53]
Experiment ID
ek_ pooled
Description
intraperitoneal
Host
Spiny Frogs
# of Doses
4.00
Μodel
N50
4.23E+08 (β = 137,348)
LD50/ID50
4.23E+08
Dose Units
Response
Exposure Route
Contains Preferred Model
Status
fitted
a
0.72
Agent Strain
E. miricola
Experiment ID
ek_intraperitoneal
Experiment Dataset
Description

 

Goodness of Fit and Model Selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 9.88 6.48 5 3.84 
0.011
11.1
0.0788
beta Poisson 3.4 4 9.49
0.494
beta-Poisson fits better than exponential; can not reject good fit for beta-Poisson

 

 

 

 

 

 

 

Bootstrapped Parameter Estimates
Parameter MLE Estimate 0.5% 2.5% 5% 95% 97.5% 99.5%
α 6.95E-01 2.69E-01 3.39E-01 3.78E-01 2.56E+0 2.28E+01 1.18E+03
N50 3.39E+03 3.58E+01 2.47E+02 4.67E+02 1.09E+04 1.26E+04 1.85E+04

 

 

 

 

 

 

Host
C57Bl/6J mice
# of Doses
6.00
Μodel
N50
277
Dose Units
Response
Exposure Route
Contains Preferred Model
Status
fitted
a
0.253
Agent Strain
F5817
Experiment ID
292
Experiment Dataset
Dose (CFU) Infected Non-Infected Total
5500 7 3 10
32400 7 3 10
55000 9 1 10
251000 10 0 10
550000 10 0 10
2820000 10 0 10
Description
Strain 81-176 model data 
Dose Campylobacteriosis Non-campylobacteriosis Total
1E+05 3 2 5
1E+07 2 3 5
1E+09 33 3 36

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 50.1 46.6 2 3.84
8.56e-12
5.99
1.29e-11
Beta Poisson 3.51 1 3.84
0.061
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 1.66E-01 2.92E-02 4.29E-02 6.44E-02 3.32E-01 4.07E-01 1.16E+00
N50 1.23E+05 6.24E-10 4.60E-05 9.04E-01 2.00E+06 6.12E+06 3.96E+07

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

 

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
3.00
Μodel
N50
1.23E+05
LD50/ID50
1.23E+05
Dose Units
Exposure Route
Contains Preferred Model
a
1.66E-01
Agent Strain
strain 81-176
Experiment ID
188
Host type
Description
T3 Strain for serotype PEN 3 model data 
Dose Infected Non-infected Total
1E+04 2 3 5
1E+05 4 1 5
1E+06 2 3 5
1E+07 3 2 5
1E+08 5 0 5

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 45.6 40.2 4 3.84
2.25e-10
9.49
2.92e-09
Beta Poisson 5.41 3 7.81
0.144
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 1.17E-01 1.06E-02 1.79E-02 2.48E-02 2.79E-01 3.29E-01 4.72E-01
N50 3.14E+04 3.29E-09 2.55E-05 2.53E-02 4.21E+05 9.69E+05 3.68E+06

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

 

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
5.00
Μodel
N50
3.14E+04
LD50/ID50
3.14E+04
Dose Units
Response
Exposure Route
Contains Preferred Model
a
1.17E-01
Agent Strain
type strain for serotype PEN 3
Experiment ID
186
Host type
Description
T2 Strain for serotype PEN 2 model data 
Dose Infected Non-infected Total
1E+04 1 4 5
1E+05 3 2 5
1E+06 4 1 5
1E+07 4 1 5
1E+08 5 0 5

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 25.4 24.5 4 3.84
7.59e-07
9.49
4.13e-05
Beta Poisson 0.969 3 7.81
0.809
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 3.19E-01 8.29E-02 1.26E-01 1.49E-01 1.05E+01 5.53E+02 1.52E+03
N50 6.68E+04 4.06E+02 5.55E+03 1.04E+04 3.58E+05 4.65E+05 8.48E+05

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

 

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
5.00
Μodel
N50
6.68E+04
LD50/ID50
6.68E+04
Dose Units
Response
Exposure Route
Contains Preferred Model
a
3.19E-01
Agent Strain
type strain for serotype PEN 2
Experiment ID
185
Host type
Description
Strain A3249 Data 
Dose Infected Non-infected Total
810 5 5 10
8100 6 4 10
91000 11 2 13
810000 8 3 11
1.1E+06 15 4 19
1.1E+08 5 0 5

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 110 108 5 3.84 
0
11.1 
0
Beta Poisson 2.43 4 9.49 
0.658
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 1.44E-01 2.05E-02 3.61E-02 4.99E-02 2.66E-01 2.98E-01 3.71E-01
N50 8.9E+02 6.54E-10 1.47E-04 8.11E-02 6.69E+03 8.97E+03 1.53E+04

 

 

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

 

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
N50
8.9E+02
LD50/ID50
8.9E+02
Dose Units
Response
Exposure Route
Contains Preferred Model
a
1.44E-01
Agent Strain
strain A3249
Experiment ID
106
Host type
Description

The same exposure route and endpoint was evaluated for Experiments 3 and 4 (Cerva, 1967b; Culbertson et al. 1966)[6] [5]. A pooling analysis was attempted and successful. The beta-Poisson model provided a good fit to the pooled data and is shown below in Figure 1. Note: both the exact and approximate beta-Poisson models were fit to the data. The figures shown below and the csv file of bootstrapped parameter replicates are for the best fitting parameters of the exact beta-Poisson model. The successful pooling of multiple datasets generally increases the confidence in the estimated model parameters. 

Figure 1: Plot of the beta-Poisson model fit to the pooled Experiments 3 and 4 with upper and lower 95% and 99% confidence
Figure 1: Plot of the beta-Poisson model fit to the pooled Experiments 3 and 4 with upper and lower 95% and 99% confidence

 

Figure 2: Uncertainty plot of the 10,000 paired bootstrap replicates of alpha and beta for the pooled beta-Poisson model.
Figure 2: Uncertainty plot of the 10,000 paired bootstrap replicates of alpha and beta for the pooled beta-Poisson model.

 

 

[6] Cerva, L. (1967b). Intranasal, Intrapulmonary, and Intracardial Inoculation of Experimental Animals with Hartmanella castellanii. Folia Parasitologica (Praha), 14, 207–215.

[5] Culbertson, C. G., Ensminger, P. W., & Overton, W. M. (1966). Hartmannella (Acanthamoeba): Experimental Chronic, Granulomatous Brain Infections Produced by New Isolates of Low Virulence. The American Journal of Clinical Pathology, 46(3), 305–314.

# of Doses
9.00
Μodel
N50
19357
Dose Units
Response
Exposure Route
Contains Preferred Model
Status
pooled
Resampled Parameters
a
0.245
Agent Strain
A. castellanii HN-3 and A culbertsoni A1
Experiment ID
Acanth_Intranasal_Pooled
Host type
Experiment Dataset
Description
mice (10day old, day1-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
2.5 0 10 10
25 0 16 16
25 0 16 16
250 0 15 15
250 0 15 15
2500 0 13 13
2500 2 11 13
25000 12 4 16
25000 13 3 16
250000 14 3 17
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

48.6 

36.3 11 3.84 
 1.65e-09
19.7
1.09e-06
Beta Poisson

12.3

10 18.3 
0.265
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 500 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 6.01E-01 3.11E-01 3.69E-01 3.97E-01 1.04E+00 1.20E+00 2.01E+00
N50 1.48E+04 8.01E+03 9.07E+03 1.00E+04 2.29E+04 2.55E+04 2.83E+04

 

 

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
12.00
Μodel
N50
1.48E+04
LD50/ID50
1.48E+04
Dose Units
Response
Exposure Route
Contains Preferred Model
a
6.01E-01
Agent Strain
ATCC 19660
Experiment ID
283,284
Description
mice (10day old, day2-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
25 0 16 16
250 0 15 15
2500 2 11 13
25000 13 3 16
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

27.3

23.1 5 3.84 
 1.54e-06
11.1
5.01e-05
Beta Poisson

4.19

4 9.49 
0.381
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 5.49E-01 2.38E-01 2.87E-01 3.17E-01 1.37E+00 1.13E+01 1.15E+04
N50 1.13E+04 4.53E+03 5.70E+03 6.34E+03 2.17E+04 2.46E+04 3.39E+04

 

 

 

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
N50
1.13E+04
LD50/ID50
1.13E+04
Dose Units
Exposure Route
Contains Preferred Model
a
5.49E-01
Agent Strain
ATCC 19660
Experiment ID
284