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

Description
TITLE 
Dose INFECTION NOT

INFECTION || Total

0.5 0 4 4
1.5 2 3 5
5 1 4 5
15 4 3 7
150 13 8 21
300 5 2 7
Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 24.3 21.5 5 3.84 
{{{pbPbetter}}}
11.1 
0.000194
Beta Poisson 2.77 4 9.49 
0

selection

Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.
Optimized parameters for the beta-Poisson model, from 10000 bootstrapiterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 1.81E-01 3.92E-02 7.30E-02 9.02E-02 4.00E-01 4.79E-01 7.28E-01
N50 2.22E+01 3.12E+00 5.01E+00 6.38E+00 1.22E+02 2.06E+02 1.26E+03

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
2.22E+01
LD50/ID50
2.22E+01
Dose Units
Response
Exposure Route
Contains Preferred Model
a
1.81E-01
Agent Strain
type 14
Experiment ID
312
Host type
Description

Optimization Output for experiment 311

TITLE 
Dose INFECTION NOT

INFECTION || Total

0.05 0 2 2
0.15 1 3 4
0.5 5 2 7
1.5 18 1 19
5 1 0 1
50 19 1 20
Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 61.7 56.8 5 3.84 
{{{pbPbetter}}}
11.1 
5.32e-12
Beta Poisson 4.95 4 9.49 
0

selection

Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.
Optimized parameters for the beta-Poisson model, from 10000 bootstrapiterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 7.01E-01 2.29E-01 3.14E-01 3.63E-01 1.81E+06 3.82E+06 1.41E+07
N50 1.9E-01 2.27E-02 5.85E-02 7.93E-02 4.20E-01 4.52E-01 5.56E-01

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
1.9E-01
LD50/ID50
1.9E-01
Dose Units
Response
Exposure Route
Contains Preferred Model
a
7.01E-01
Agent Strain
type 39
Experiment ID
311
Host type
Description
TITLE 
Dose INFECTION NOT

INFECTION || Total

0.5 1 4 5
1.5 2 3 5
5 3 2 5
15 2 1 3
150 14 5 19
300 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 29.7 27.3 5 3.84 
{{{pbPbetter}}}
11.1 
1.71e-05
Beta Poisson 2.42 4 9.49 
0

selection

Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.
Optimized parameters for the beta-Poisson model, from 10000 bootstrapiterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 2.52E-01 9.79E-04 9.14E-02 1.16E-01 5.50E-01 6.41E-01 1.06E+00
N50 3.83E+00 9.08E-03 3.23E-01 6.41E-01 1.48E+01 2.04E+01 8.86E+01

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
3.83E+00
LD50/ID50
3.83E+00
Dose Units
Response
Exposure Route
Contains Preferred Model
a
2.52E-01
Agent Strain
type 14
Experiment ID
310
Host type
Description
Human data( Rickettsia rickettsii) 
Dose CLINICAL SIGNS NOT CLINICAL SIGNS Total
13 2 4 6
126 6 1 7
1260 17 1 18

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 13.5 13.2 2 3.84 
0.000277
5.99 
0.00119
Beta Poisson 0.248 1 3.84 
0.618
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 6.75E-01 1.17E-01 2.44E-01 3.31E-01 1.21E+03 3.74E+03 4.98E+03
N50 2.36E+01 2.56E-02 3.35E+00 7.30E+00 6.41E+01 8.91E+01 1.28E+02

 

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
2.36E+01
LD50/ID50
2.36E+01
Dose Units
Response
Exposure Route
Contains Preferred Model
a
6.75E-01
Agent Strain
Sheila Smith
Experiment ID
301
Host type
Description
Pooled data (experiment no. 300 and 301) 
Dose MORBIDITY NOT MORBIDITY Total
13 2 4 6
25 1 3 4
66 2 0 2
83 2 0 2
99 2 0 2
126 6 1 7
182 7 0 7
1110 1 1 2
1260 17 1 18
1770 2 0 2
2290 2 0 2
2590 2 0 2
3170 2 0 2
5060 7 0 7
5520 2 0 2
5650 2 0 2
5670 1 0 1
7460 2 0 2
9200 2 0 2
10800 2 0 2
16800 2 0 2
41000 2 0 2
45500 3 0 3
53200 2 0 2
55200 2 0 2
132000 2 0 2
149000 2 0 2

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 42.2 30.5 26 3.84 
3.41e-08
38.9 
0.0235
Beta Poisson 11.7 25 37.7 
0.989
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 7.77E-01 3.82E-01 4.41E-01 4.90E-01 4.24E+00 3.59E+03 3.25E+04
N50 2.13E+01 5.70E+00 8.34E+00 1.01E+01 4.00E+01 4.16E+01 5.10E+01

 

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
27.00
Μodel
N50
2.13E+01
LD50/ID50
2.13E+01
Dose Units
Response
Contains Preferred Model
a
7.77E-01
Agent Strain
R1 and Sheila Smith
Experiment ID
300 and 301
Host type
Description
Rhesus monkey Data 
Dose MORBIDITY NOT MORBIDITY Total
25 1 3 4
66 2 0 2
83 2 0 2
99 2 0 2
182 7 0 7
1110 1 1 2
1770 2 0 2
2290 2 0 2
2590 2 0 2
3170 2 0 2
5060 7 0 7
5520 2 0 2
5650 2 0 2
5670 1 0 1
7460 2 0 2
9200 2 0 2
10800 2 0 2
16800 2 0 2
41000 2 0 2
45500 3 0 3
53200 2 0 2
55200 2 0 2
132000 2 0 2
149000 2 0 2

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 27.6 16.4 23 3.84 
5.12e-05
35.2 
0.232
Beta Poisson 11.2 22 33.9 
0.972
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 8.58E-01 9.77E-04 9.77E-04 9.78E-04 5.70E+06 1.41E+08 1.62E+11
N50 1.88E+01 3.58E-01 1.81E+00 7.74E+00 1.02E+03 4.02E+03 3.71E+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
24.00
Μodel
N50
1.88E+01
LD50/ID50
1.88E+01
Dose Units
Response
Exposure Route
Contains Preferred Model
a
8.58E-01
Agent Strain
R1
Experiment ID
300
Host type
Description
Mice/phase I Ohio strain model data 
Dose Dead Survived Total
0.7 0 30 30
7 0 20 20
70 0 30 30
7000 0 30 30
7E+05 0 30 30
7E+06 1 19 20
7E+07 6 24 30
7E+08 16 14 30
7E+09 23 7 30
7E+10 19 1 20

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 73.9 72.8 9 3.84 
0
16.9 
2.65e-12
Beta Poisson 1.11 8 15.5 
0.997
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 3.57E-01 1.91E-01 2.20E-01 2.38E-01 6.34E-01 7.08E-01 9.84E-01
N50 4.93E+08 1.89E+08 2.41E+08 2.73E+08 9.34E+08 1.06E+09 1.36E+09

 

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
10.00
Μodel
N50
4.93E+08
LD50/ID50
4.93E+08
Dose Units
Response
Exposure Route
Contains Preferred Model
a
3.57E-01
Agent Strain
phase I Ohio
Experiment ID
28
Host type
Description
Dose response data
Dose Infected Non-infected Total
100 6 6 12
1E+05 6 6 12
1E+08 10 2 12

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 193 192 2 3.84 
0
5.99 
0
Beta Poisson 1.43 1 3.84 
0.231
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 5.79E-02 9.94E-04 9.78E-03 1.25E-02 1.27E-01 1.42E-01 1.87E-01
N50 4.8E+02 3.44E-13 5.25E-08 1.89E-05 5.61E+04 1.50E+05 4.41E+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
3.00
Μodel
N50
4.8E+02
LD50/ID50
4.8E+02
Dose Units
Response
Exposure Route
Contains Preferred Model
a
5.79E-02
Agent Strain
sub sp. Paratuberculosis IOI strain
Experiment ID
263
Host type
Description
human/H3N2, A/Washington/897/80 attenuated strain model data [3]
Dose Infected Non-infected Total
1E+05 2 10 12
1E+06 8 5 13
1E+07 16 3 19
31622777 16 4 20
1E+08 19 0 19

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 39.1 34.8 4 3.84 
3.66e-09
9.49 
6.79e-08
Beta Poisson 4.26 3 7.81 
0.235
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 4.29E-01 2.14E-01 2.58E-01 2.83E-01 7.58E-01 8.71E-01 1.20E+00
N50 6.66E+05 1.36E+05 2.19E+05 2.68E+05 1.63E+06 1.87E+06 2.49E+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
6.66E+05
LD50/ID50
6.66E+05
Dose Units
Response
Exposure Route
Contains Preferred Model
a
4.29E-01
Agent Strain
H3N2,A/Washington/897/80 attenuated strain
Experiment ID
258
Host type
Description
Pooled dose response data [1]
Dose Infected Non-infected Total
63095.73 0 15 15
1E+05 2 10 12
630957.3 4 7 11
1E+06 8 5 13
6309573 19 3 22
1E+07 16 3 19
31622777 16 4 20
63095734 24 1 25
1E+08 19 0 19

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential 64 55.4 8 3.84 
9.68e-14
15.5 
7.63e-11
Beta Poisson 8.56 7 14.1 
0.285
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 5.81E-01 3.61E-01 3.98E-01 4.24E-01 9.15E-01 1.02E+00 1.36E+00
N50 9.45E+05 4.38E+05 5.28E+05 5.72E+05 1.62E+06 1.79E+06 2.23E+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
9.00
Μodel
N50
9.45E+05
LD50/ID50
9.45E+05
Dose Units
Response
Exposure Route
Contains Preferred Model
a
5.81E-01
Agent Strain
H1N1,A/California/10/78 attenuated strain,H3N2,A/Washington/897/80 attenuated strain
Experiment ID
257, 258
Host type