Sielken & Associates Consulting, Inc. CEB was able to reproduce the BMD analysis from the 

Sielken report and to provide BMD estimates and calculate the associated FQPA factors. 

Background: 

For both the red blood cell (RBC) and brain compartments, Sielken combined male and female 

test subjects to analyze both adult and post-natal day 11 (PND11) rats. Sielken performed two 

different statistical procedures to determine whether or not it was appropriate to combine male 

and female AChE values. The results from the first procedure, the two-sample t-test, are listed in 

Tables 5 and 6 of their submission. These results indicate that the difference between adult male 

and female AChE levels in the brain compartment for the 0.3 mg/kg dose group are statistically 

significant at the alpha=0.05 significance level. The second procedure employed by Sielken to 

decide whether or not to combine sexes was a likelihood ratio test. The results of likelihood ratio 

tests are listed in Tables 7 and 8 of their submission. For the adult brain AChE data, the p-values 

for the likelihood ratio tests are significant for both the BMDS exponential model 3 (p value = 

0.0276) and model 5 (p value = 0.0259) (with a constant variance model). For the adult RBC 

AChE data, the p-value for the likelihood ratio test is significant for the BMDS exponential 

model 5 (p value = 0.0180) (with a non-constant variance model). We conclude from the 

likelihood ratio test that there is significant difference in model parameters between sexes for 

adult RBC data under non-constant variance assumption. However – despite the fact that the 

likelihood ratio test indicated that there is a significant difference in adult RBC AChE inhibition 

values between the sexes -- Sielken did combine male and female samples for both RBC and 

brain AChE in adult and PND11 rats. Exponential model-5 under non-constant variance model 

fitted the data adequately for different organs and different age groups using this combined (sex) 

sample. Sielken calculated the FQPA factor for brain AChE in rats which is the ratio of the adult 

BMD10 to the PND11 BMD10, is 4.3 in the combined sample. The FQPA factor for RBC AChE 

in rats is 3.9 in the combined sample. 

Analysis: 

CEB conducted a confirmatory BMD analysis of the brain and RBC AChE data for adult and 

PND11 rats using the AChE values from the Sielken report using EPA’s BMDS version 2.1.1(1)

. 

Dose-response relationships were modeled using the exponential family of models in BMDS. 

The Akaike Information Criterion (AIC), BMD10, and BMDL10 values from the four exponential 

models for adult and PND11 rats are provided in Tables 1 and 2. The minimum AIC was used to 

select the best model. When combining male and female AChE data, CEB was able to duplicate 

the exact same BMD10 values estimated by Sielken for the adult and pup brain data and the pup 

RBC data. CEB decided not to combine male and female samples for adult RBC data based on 

the likelihood ratio test results provided by Sielken & Associates (MRID 47994306). In addition, 

CEB calculated BMD10 values for each gender separately. FQPA factors for single-sex and 

combined samples are provided in Table 3. The values for the FQPA factors varied between 3.3 

and 4.8 depending on the compartment of interest and whether or not the genders were 

combined. 

 

1

 http://www.epa.gov/ncea/bmds/ 

Page 2 of 42 
Table 1: AIC, BMD10, and BMDL10 Values for Adult AChE Levels. Detailed computer output is 

provided in appendix. All calculations are based on non-constant variance assumption. 

Target

Organ Sex ExponentialModel BMD10 BMDL10 AIC Comments

2 0.0535 0.0484 926.600   

3 0.0535 0.0484 926.600   

4 0.0482 0.0408 927.175    Brain Male

5 0.0555 0.0443 927.125   

2 0.00531 0.00448 714.798

Optimum may not

have been found

for model 2

3 0.00790 Bad

completion 16298.190

Optimum may not

have been found

for model 3

4 0.00399 0.00353 705.471   

RBC Male

5 0.0228 0.0153 679.582   

2 0.0468 0.0426 940.775   

3 0.0615 0.0498 937.553   

4 0.0468 0.0424 940.775    Brain Female

5 0.0672 0.0530 938.210   

2 0.00674 0.00558 736.726   

3 0.0141 0.00619 736.555   

4 0.00575 0.00465 734.135    RBC Female

5 0.0242 0.0144 722.055   

2 0.0502 0.0469 1862.988   

3 0.0559 0.0481 1863.330   

4 0.0502 0.0458 1862.988    Brain Combined

5 0.0607 0.0517 1862.335   

2 0.00599 0.00527 1448.372

Optimum may not

have been found

for model 2

3 0.00917 Bad

completion 10518.420

Optimum may not

have been found

for model 3

4 0.00494 0.00449 1437.768   

RBC Combined

5 0.0223 0.0161 1404.951   

Page 3 of 42 
Table 2: AIC, BMD10, and BMDL10 Values for PND11 AChE Levels. Detailed computer output 

is provided in appendix. All calculations are based on non-constant variance assumption. 

Target

Organ Sex ExponentialModel BMD10 BMDL10 AIC Comments

2 0.00833 0.00755 771.965

optimum may not

have been found

form model 2  

3 0.790 Bad

completion 893.120   

4 0.00786 0.00687 773.629   

Brain Male

5 0.0143 0.0112 761.629   

2 0.00284 0.00236 653.234

optimum may not

have been found

form model 2  

3 0.00381 Bad

completion 6181.454

optimum may not

have been found

form model 3  

4 0.00197 0.00174 638.955   

RBC Male

5 0.00477 0.00294 633.107   

2 0.00926 0.00840 762.469   

3 0.0113 0.00877 762.593   

4 0.00926 0.00807 762.469    Brain Female

5 0.0136 0.0103 761.157   

2 0.00337 0.00274 657.487   

3 0.00337 0.00274 657.487   

4 0.00244 0.00202 648.741    RBC Female

5 0.00731 0.00387 644.0862   

2 0.00876 0.00817 1530.567   

3 0.0105 0.00865 1529.881   

4 0.00876 0.00771 1530.567    Brain Combined

5 0.0140 0.0116 1517.282   

2 0.00309 0.00268 1305.488   

3 0.00309 0.00268 1305.488   

4 0.00222 0.00195 1283.358   

RBC Combined

5 0.00573 0.00387 1272.576   

 

Page 4 of 42 
Table 3: FQPA Factors 

Adult PND11 Pups

Source Sex Target

Organ BMD10

Exponential

Model

selected

BMD10

Exponential

Model

selected

FQPA

Factor

Brain 0.0535 Model‐2 0.0143 Model‐5 3.741

Male

RBC 0.0228 Model‐5 0.00477 Model‐5 4.780

Brain 0.0615 Model‐3 0.0136 Model‐5 4.522

CEB

Female

RBC 0.0242 Model‐5 0.00731 Model‐5 3.310

Sielken & Brain 0.0607 Model‐5 0.0140 Model‐5 4.336

Associates Combined

RBC 0.0223 Model‐5 0.00573 Model‐5 3.892

References: 

Sielken, R. (2010) Benchmark Doses for Brain and RBC Acetylcholinesterase in Adult and Pups Exposed 

to Aldicarb. Project Number: G202152. Unpublished study prepared by Sielken, Inc.February 18, 2010. 

68 p.p. 

MRID 47994306. 

Page 5 of 42 
Appendix: 

Selected BMDS Output: All model parameters were estimated using non-constant 

variance assumption.

 The form of the response function by Model: 

 Model 2: Y[dose] = a * exp{sign * b * dose} 

 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

 Note: Y[dose] is the median response for exposure = dose; 

 sign = +1 for increasing trend in data; 

 sign = -1 for decreasing trend. 

 Model 2 is nested within Models 3 and 4. 

 Model 3 is nested within Model 5. 

 Model 4 is nested within Model 5. 

Adult Male Brain :

==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 14:28:55 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 5.045e+004 1274 

 0.03 8 4.786e+004 1710 

 0.05 8 4.581e+004 1427 

 0.065 8 4.615e+004 1829 

 0.08 8 4.137e+004 3154 

 0.15 8 3.682e+004 2517 

 0.3 8 2.896e+004 2276 

Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

Page 6 of 42 
 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -453.1118 8 922.2235 

 A2 -448.1513 14 924.3026 

 A3 -451.6047 9 921.2093 

 R -525.2118 2 1054.424 

 2 -459.3004 4 926.6009 

 3 -459.3004 4 926.6009 

 4 -458.5878 5 927.1755 

 5 -457.5626 6 927.1253 

 Additive constant for all log-likelihoods = -51.46. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.0535001 0.048422 

 3 0.0535001 0.048422 

 4 0.0481827 0.0408124 

 5 0.0555194 0.0442621 

Page 7 of 42 
 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

14:28 04/13 2010

BMDL BMD

 

Exponential

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

14:28 04/13 2010

BMDL BMD

 

Exponential

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

14:28 04/13 2010

BMDL BMD

 

Exponential

 

Page 8 of 42 
 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

14:28 04/13 2010

BMDL BMD

 

Exponential

Adult Female Brain :

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 14:44:56 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 5.043e+004 1460 

 0.03 8 4.784e+004 2819 

 0.05 8 4.736e+004 2454 

 0.065 8 4.558e+004 1642 

 0.08 8 4.379e+004 3036 

 0.15 8 3.623e+004 2600 

 0.3 8 2.53e+004 3199 

Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

Page 9 of 42 
 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -463.2022 8 942.4044 

 A2 -459.3958 14 946.7916 

 A3 -462.2567 9 942.5135 

 R -534.3943 2 1072.789 

 2 -466.3873 4 940.7746 

 3 -463.7764 5 937.5529 

 4 -466.3873 4 940.7746 

 5 -463.1051 6 938.2103 

 Additive constant for all log-likelihoods = -51.46. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.0467726 0.0426385 

 3 0.0614607 0.0498428 

 4 0.0467726 0.0423962 

 5 0.0672431 0.0530345 

Page 10 of 42 
 20000

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

14:44 04/13 2010

BMDL BMD

 

Exponential

 20000

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

14:44 04/13 2010

BMDL BMD

 

Exponential

 20000

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

14:44 04/13 2010

BMDL BMD

 

Exponential

Page 11 of 42 
 20000

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

14:44 04/13 2010

BMDL BMD

 

Exponential

Adult Combined Sample Brain :

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 16:47:34 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 16 5.044e+004 1324 

 0.03 16 4.785e+004 2252 

 0.05 16 4.658e+004 2099 

 0.065 16 4.586e+004 1705 

 0.08 16 4.258e+004 3242 

 0.15 16 3.653e+004 2490 

 0.3 16 2.713e+004 3281 

Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

Page 12 of 42 
 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -925.8769 8 1867.754 

 A2 -916.3648 14 1860.73 

 A3 -921.6568 9 1861.314 

 R -1060.358 2 2124.717 

 2 -927.494 4 1862.988 

 3 -926.6651 5 1863.33 

 4 -927.494 4 1862.988 

 5 -925.1675 6 1862.335 

 Additive constant for all log-likelihoods = -102.9. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.0502089 0.0469231 

 3 0.0558797 0.0481209 

 4 0.0502089 0.0458504 

 5 0.0607085 0.0517358 

Page 13 of 42 
 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

16:47 04/13 2010

BMDL BMD

 

Exponential

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

16:47 04/13 2010

BMDL BMD

 

Exponential

 

 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

16:47 04/13 2010

BMDL BMD

 

Exponential

Page 14 of 42 
 25000

 30000

 35000

 40000

 45000

 50000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

16:47 04/13 2010

BMDL BMD

 

Exponential

Adult Male RBC:

!!! Warning: optimum may not have been found for Model 3 !!! 

!!! Bad completion code in maximum likelihood optimization routine !!! 

!!! Try choosing different initial values !!! 

Warning: optimum may not have been found form model 2 (BMDL). Bad process 

completion in Optimization routine. 

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 15:10:52 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 2466 464 

 0.03 8 2175 788.7 

 0.05 8 993 422.9 

 0.065 8 786 431.8 

 0.08 7 303 221.9 

 0.15 8 24 30.6 

 0.3 8 83 89.5 

Page 15 of 42 
 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -356.9571 8 729.9143 

 A2 -324.2962 14 676.5923 

 A3 -326.2331 9 670.4662 

 R -407.4874 2 818.9749 

 2 -353.3988 4 714.7976 

 3 -8145.093 4 16298.19 

 4 -347.7356 5 705.4712 

 5 -333.7912 6 679.5824 

 Additive constant for all log-likelihoods = -50.54. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00531446 0.00448441 

 3 0.00790546 Bad completion 

 4 0.00399133 0.0035305 

 5 0.0228211 0.0153299 

Page 16 of 42 
 0

 500

 1000

 1500

 2000

 2500

 3000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

15:10 04/13 2010

BMDLBMD

 

Exponential

 0

 500

 1000

 1500

 2000

 2500

 3000

-1 -0.8 -0.6 -0.4 -0.2 0 0.2

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

15:10 04/13 2010

BMDL BMD

 

Exponential

 0

 500

 1000

 1500

 2000

 2500

 3000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

15:10 04/13 2010

BMDLBMD

 

Exponential

Page 17 of 42 
 0

 500

 1000

 1500

 2000

 2500

 3000

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

15:10 04/13 2010

BMDL BMD

 

Exponential

Adult Female RBC:

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 15:17:07 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 2411 315.4 

 0.03 8 1726 753.1 

 0.05 8 1473 568.2 

 0.065 8 777 531.7 

 0.08 8 610 420.1 

 0.15 8 97 116.2 

 0.3 8 153 115.6 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

Page 18 of 42 
 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -367.5027 8 751.0053 

 A2 -348.6014 14 725.2028 

 A3 -353.8902 9 725.7804 

 R -409.369 2 822.738 

 2 -364.3631 4 736.7263 

 3 -363.2777 5 736.5554 

 4 -362.0677 5 734.1353 

 5 -355.0277 6 722.0553 

 Additive constant for all log-likelihoods = -51.46. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00674224 0.00558408 

 3 0.0141009 0.00619242 

 4 0.0057509 0.00465191 

 5 0.0242245 0.0144086 

Page 19 of 42 
 0

 500

 1000

 1500

 2000

 2500

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

15:17 04/13 2010

BMDLBMD

 

Exponential

 0

 500

 1000

 1500

 2000

 2500

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

15:17 04/13 2010

BMDL BMD

 

Exponential

 0

 500

 1000

 1500

 2000

 2500

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

15:17 04/13 2010

BMDLBMD

 

Exponential

Page 20 of 42 
 0

 500

 1000

 1500

 2000

 2500

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

15:17 04/13 2010

BMDL BMD

 

Exponential

Adult Combined Sample RBC:

!!! Warning: optimum may not have been found for Model 3 !!! 

!!! Bad completion code in maximum likelihood optimization routine !!! 

!!! Try choosing different initial values !!! 

Warning: optimum may not have been found form model 2 (BMDL). Bad process 

completion in Optimization routine. 

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 16:52:14 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 16 2439 384.3 

 0.03 16 1950 780.3 

 0.05 16 1233 543.6 

 0.065 16 781.1 467.9 

 0.08 15 466.9 366.7 

 0.15 16 60.13 90.28 

Page 21 of 42 
 0.3 16 117.8 106.2 

 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -730.4818 8 1476.964 

 A2 -688.0723 14 1404.145 

 A3 -694.7847 9 1407.569 

 R -817.1663 2 1638.333 

 2 -720.1858 4 1448.372 

 3 -5255.209 4 10518.42 

 4 -713.8838 5 1437.768 

 5 -696.4756 6 1404.951 

 Additive constant for all log-likelihoods = -102. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00598819 0.00526723 

 3 0.00916555 Bad completion 

 4 0.00494336 0.00449284 

 5 0.0223073 0.0161069 

Page 22 of 42 
 0

 500

 1000

 1500

 2000

 2500

 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

16:52 04/13 2010

BMDLBMD

 

Exponential

 0

 500

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-1 -0.8 -0.6 -0.4 -0.2 0 0.2

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

16:52 04/13 2010

BMDL BMD

 

Exponential

 0

 500

 1000

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 0 0.05 0.1 0.15 0.2 0.25 0.3

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

16:52 04/13 2010

BMDLBMD

 

Exponential

Page 23 of 42 
 0

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Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

16:52 04/13 2010

BMDL BMD

 

Exponential

Pups Male Brain:

Warning: optimum may not have been found form model 2 (BMDL). Bad process 

completion in Optimization routine. 

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 15:27:24 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 2.561e+004 846.3 

 0.005 8 2.56e+004 1026 

 0.01 8 2.368e+004 2084 

 0.02 8 2.146e+004 1427 

 0.04 8 1.437e+004 2275 

 0.08 8 1.036e+004 1177 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

Page 24 of 42 
 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -373.8812 7 761.7625 

 A2 -367.8322 12 759.6645 

 A3 -373.5702 8 763.1404 

 R -441.5602 2 887.1204 

 2 -381.9826 4 771.9652 

 3 -441.5602 5 893.1204 

 4 -381.8149 5 773.6297 

 5 -374.8147 6 761.6295 

 Additive constant for all log-likelihoods = -44.11. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00833219 0.0075546 

 3 0.790289 Bad completion 

 4 0.00786261 0.00687095 

 5 0.0143096 0.01124 

Page 25 of 42 
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Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

09:56 06/29 2010

BMDL BMD

 

Exponential

 10000

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-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

09:56 06/29 2010

BMDL BMD

 

Exponential

 10000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

09:56 06/29 2010

BMDL BMD

 

Exponential

Page 26 of 42 
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Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

09:56 06/29 2010

BMDL BMD

 

Exponential

 

Pups Female Brain :

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 15:50:21 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 2.608e+004 1017 

 0.005 8 2.563e+004 1107 

 0.01 8 2.394e+004 830 

 0.02 8 2.207e+004 2190 

 0.04 8 1.614e+004 2206 

 0.08 8 1.068e+004 1745 

 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

Page 27 of 42 
 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -375.3848 7 764.7695 

 A2 -368.8802 12 761.7605 

 A3 -373.7771 8 763.5541 

 R -439.7824 2 883.5649 

 2 -377.2345 4 762.4689 

 3 -376.2967 5 762.5935 

 4 -377.2345 4 762.4689 

 5 -374.5785 6 761.157 

 Additive constant for all log-likelihoods = -44.11. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00925925 0.00839859 

 3 0.0112715 0.00876684 

 4 0.00925925 0.00807613 

 5 0.0136115 0.0103155 

Page 28 of 42 
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Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

15:50 04/13 2010

BMDL BMD

 

Exponential

 10000

 15000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

15:50 04/13 2010

BMDL BMD

 

Exponential

 10000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

15:50 04/13 2010

BMDL BMD

 

Exponential

Page 29 of 42 
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Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

15:50 04/13 2010

BMDL BMD

 

Exponential

Pups Combined Brain :

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 16:58:08 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 16 2.585e+004 935.6 

 0.005 16 2.562e+004 1032 

 0.01 16 2.381e+004 1538 

 0.02 16 2.176e+004 1814 

 0.04 16 1.525e+004 2351 

 0.08 16 1.052e+004 1447 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

Page 30 of 42 
 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -752.7054 7 1519.411 

 A2 -743.4776 12 1510.955 

 A3 -750.5554 8 1517.111 

 R -881.489 2 1766.978 

 2 -761.2836 4 1530.567 

 3 -759.9404 5 1529.881 

 4 -761.2836 4 1530.567 

 5 -752.6409 6 1517.282 

 Additive constant for all log-likelihoods = -88.22. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00876019 0.00816909 

 3 0.0105247 0.00864872 

 4 0.00876019 0.00771366 

 5 0.0139776 0.0116531 

Page 31 of 42 
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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

16:58 04/13 2010

BMDL BMD

 

Exponential

 10000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

16:58 04/13 2010

BMDL BMD

 

Exponential

 10000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

16:58 04/13 2010

BMDL BMD

 

Exponential

Page 32 of 42 
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Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

16:58 04/13 2010

BMDL BMD

 

Exponential

Pups Male RBC :

!!! Warning: optimum may not have been found for Model 3 !!! 

!!! Bad completion code in maximum likelihood optimization routine !!! 

!!! Try choosing different initial values !!! 

Warning: optimum may not have been found form model 2 (BMDL). Bad process 

completion in Optimization routine. 

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 16:18:14 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 5104 795.4 

 0.005 8 4569 929.1 

 0.01 8 3654 1104 

 0.02 7 2153 517.5 

Page 33 of 42 
 0.04 8 931 169.6 

 0.08 7 654 253.8 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -322.9408 7 659.8815 

 A2 -307.5104 12 639.0208 

 A3 -310.4851 8 636.9702 

 R -369.01 2 742.02 

 2 -322.6171 4 653.2342 

 3 -3086.727 4 6181.454 

 4 -314.4776 5 638.9552 

 5 -310.5536 6 633.1071 

 Additive constant for all log-likelihoods = -42.27. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00284479 0.00235863 

 3 0.00381536 Bad completion 

 4 0.00196772 0.00174498 

 5 0.00477107 0.00293821 

Page 34 of 42 
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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

16:18 04/13 2010

BMDL BMD

 

Exponential

 0

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 4000

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-1 -0.8 -0.6 -0.4 -0.2 0

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

16:18 04/13 2010

BMDL BMD

 

Exponential

 0

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 4000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

16:18 04/13 2010

BMDLBMD

 

Exponential

Page 35 of 42 
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Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

16:18 04/13 2010

BMDL BMD

 

Exponential

Pups RBC Female:

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 16:23:08 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 8 5279 973.8 

 0.005 7 4823 681.3 

 0.01 8 3493 771.1 

 0.02 7 2881 1017 

 0.04 8 1009 340.1 

 0.08 8 816 145.1 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

Page 36 of 42 
 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -322.4457 7 658.8913 

 A2 -308.6109 12 641.2219 

 A3 -312.6577 8 641.3154 

 R -369.06 2 742.1201 

 2 -324.7433 4 657.4866 

 3 -324.7433 4 657.4866 

 4 -319.3706 5 648.7411 

 5 -316.0431 6 644.0862 

 Additive constant for all log-likelihoods = -42.27. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00336759 0.00274242 

 3 0.00336759 0.00274242 

 4 0.00243774 0.00202279 

 5 0.00731427 0.00387471 

Page 37 of 42 
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Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

16:23 04/13 2010

BMDL BMD

 

Exponential

 1000

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 3000

 4000

 5000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

16:23 04/13 2010

BMDL BMD

 

Exponential

 1000

 2000

 3000

 4000

 5000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

16:23 04/13 2010

BMDL BMD

 

Exponential

Page 38 of 42 
 1000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

16:23 04/13 2010

BMDL BMD

 

Exponential

Pups Combined sample RBC:

 ==================================================================== 

 Exponential Model. (Version: 1.61; Date: 7/24/2009) 

 Input Data File: C:\USEPA\BMDS21\expDax_Setting.(d) 

 Gnuplot Plotting File: 

 Tue Apr 13 17:01:52 2010 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 Table of Stats From Input Data 

 Dose N Obs Mean Obs Std Dev 

 ----- --- ---------- ------------- 

 0 16 5191 863.7 

 0.005 15 4687 804.8 

 0.01 16 3573 923.8 

 0.02 14 2517 862.6 

 0.04 16 970 262.7 

 0.08 15 740.7 212.4 

 

 Other models for which likelihoods are calculated: 

 Model A1: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma^2 

 Model A2: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = Sigma(i)^2 

Page 39 of 42 
 Model A3: Yij = Mu(i) + e(ij) 

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

 Model R: Yij = Mu + e(i) 

 Var{e(ij)} = Sigma^2 

 Likelihoods of Interest 

 Model Log(likelihood) DF AIC 

 ------- ----------------- ---- ------------ 

 A1 -647.9977 7 1309.995 

 A2 -624.8456 12 1273.691 

 A3 -628.4926 8 1272.985 

 R -738.1013 2 1480.203 

 2 -648.744 4 1305.488 

 3 -648.744 4 1305.488 

 4 -636.6791 5 1283.358 

 5 -630.2878 6 1272.576 

 Additive constant for all log-likelihoods = -84.54. This constant 

added to the 

 above values gives the log-likelihood including the term that does not 

 depend on the model parameters. 

 Benchmark Dose Computations: 

 Specified Effect = 0.100000 

 Risk Type = Relative deviation 

 Confidence Level = 0.950000 

 BMD and BMDL by Model 

 Model BMD BMDL 

 ------- ------------ ---------- 

 2 0.00308837 0.00268371 

 3 0.00308837 0.00268371 

 4 0.00222711 0.00195621 

 5 0.00572972 0.00386834 

Page 40 of 42 
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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

17:01 04/13 2010

BMDL BMD

 

Exponential

 1000

 2000

 3000

 4000

 5000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

17:01 04/13 2010

BMDL BMD

 

Exponential

 1000

 2000

 3000

 4000

 5000

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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

17:01 04/13 2010

BMDLBMD

 

Exponential

Page 41 of 42 
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 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

17:01 04/13 2010

BMDL BMD

 

Exponential

Page 42 of 42