Table 3. Estimated benchmark dose (BMD) and benchmark dose lower limit (BMDL) for different continuous data sets, different models and different levels of BMR using PROAST, BMDS and bmd.
PROAST and BMDS uses profile likelihood intervals for estimating BMDL while the R package bmd uses the delta method, inverse regression or bootstrap. For all data sets, the relative definition of BMD was used.
BMD | BMDL | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Data set |
Std | Rep | Model | BMR | PROAST | BMDS | bmd | PROAST profile |
BMDS profile |
bmd delta |
bmd inverse |
bmd bootstrap |
||
A | 1 | 10 | Log–logistica | 0.05 | 0.088 | 0.144 | 0.144 | 0 | 0.050 | 0.037 | 0.082 | 0.051 | ||
0.1 | 0.129 | 0.200 | 0.200 | 0 | 0.080 | 0.077 | 0.119 | 0.080 | ||||||
Weibull2 | 0.05 | 0.040 | 0.126 | 0.126 | 0 | 0.018 | 0.004 | 0.063 | 0.017 | |||||
0.1 | 0.070 | 0.183 | 0.183 | 0 | 0.034 | 0.038 | 0.097 | 0.032 | ||||||
0.1 | 10 | Log–logistic | 0.05 | 0.101 | 0.107 | 0.107 | 0.091 | 0.105 | 0.097 | 0.097 | 0.096 | |||
0.1 | 0.148 | 0.154 | 0.154 | 0.135 | 0.151 | 0.142 | 0.140 | 0.140 | ||||||
Weibull | 0.05 | 0.049 | 0.074 | 0.074 | 0.041 | 0.060 | 0.061 | 0.061 | 0.061 | |||||
0.1 | 0.086 | 0.115 | 0.115 | 0.073 | 0.097 | 0.099 | 0.098 | 0.098 | ||||||
0.1 | 3 | Log–logistic | 0.05 | 0.092 | 0.097 | 0.097 | 0.080 | 0.078 | 0.075 | 0.077 | 0.079 | |||
0.1 | 0.138 | 0.140 | 0.140 | 0.121 | 0.1156 | 0.114 | 0.114 | 0.117 | ||||||
Weibull | 0.05 | 0.043 | 0.066 | 0.066 | 0.031 | 0.040 | 0.037 | 0.043 | 0.043 | |||||
0.1 | 0.076 | 0.105 | 0.105 | 0.058 | 0.067 | 0.066 | 0.072 | 0.072 | ||||||
B | 1 | 10 | Log–logistic | 0.05 | 0.003 | 0.092 | 0.092 | 0 | 0.005 | 0 | 0.035 | 0.005 | ||
0.1 | 0.008 | 0.148 | 0.149 | 0 | 0.011 | 0 | 0.06 | 0.012 | ||||||
Weibull | 0.05 | 0 | 0.045 | 0.045 | 0 | 0.015 | 0 | 0.014 | 0.003 | |||||
0.1 | 0.002 | 0.085 | 0.085 | 0 | 0.030 | 0 | 0.029 | 0.007 | ||||||
0.1 | 10 | Log–logistic | 0.05 | 0.033 | 0.032 | 0.032 | 0.019 | 0.023 | 0.024 | 0.023 | 0.023 | |||
0.1 | 0.07 | 0.067 | 0.067 | 0.043 | 0.050 | 0.054 | 0.051 | 0.05 | ||||||
Weibull | 0.05 | 0.008 | 0.056 | 0.016 | 0.003 | 0.051 | 0.011 | 0.011 | 0.011 | |||||
0.1 | 0.022 | 0.112 | 0.038 | 0.012 | 0.102 | 0.029 | 0.027 | 0.027 | ||||||
0.1 | 3 | Log–logistic | 0.05 | 0.029 | 0.036 | 0.036 | 0.016 | 0.028 | 0.024 | 0.023 | 0.023 | |||
0.1 | 0.064 | 0.074 | 0.074 | 0.038 | 0.051 | 0.055 | 0.051 | 0.051 | ||||||
Weibull | 0.05 | 0.008 | 0.056 | 0.019 | 0.004 | 0.049 | 0.012 | 0.012 | 0.012 | |||||
0.1 | 0.023 | 0.113 | 0.044 | 0.012 | 0.099 | 0.031 | 0.029 | 0.03 | ||||||
C | 1 | 10 | Log–logisticc | 0.05 | – | 0.717 | 0.717 | – | 0.047 | 0 | 0.261 | 0.079 | ||
0.1 | – | 0.971 | 0.971 | – | 0.098102 | 0 | 0.369 | 0.155 | ||||||
Weibull | 0.05 | – | 0.666 | 0.666 | – | 0.051 | 0 | 0.224 | 0.067 | |||||
0.1 | – | 0.930 | 0.930 | – | 0.102 | 0 | 0.329 | 0.134 | ||||||
0.1 | 10 | Log–logistic | 0.05 | 0.847 | 0.843 | 0.843 | 0.737 | 0.832 | 0.683 | 0.696 | 0.693 | |||
0.1 | 1.137 | 1.126 | 1.126 | 1.010 | 1.111 | 0.954 | 0.953 | 0.957 | ||||||
Weibull | 0.05 | 0.827 | 0.833 | 0.833 | 0.705 | 0.677 | 0.651 | 0.679 | 0.677 | |||||
0.1 | 1.155 | 1.132 | 1.132 | 1.010 | 0.950 | 0.929 | 0.948 | 0.952 | ||||||
0.1 | 3 | Log–logistic | 0.05 | 1.724 | 3.262 | 2.621 | 1.070 | 3.219 | 0 | 1.501 | 0.821 | |||
0.1 | 2.054 | 3.491 | 2.905 | 1.380 | 3.459 | 0 | 1.684 | 1.107 | ||||||
Weibull | 0.05 | 2.007 | 3.533 | 2.647 | 1.090 | 3.431 | 0 | 1.513 | 0.802 | |||||
0.1 | 2.382 | 3.753 | 2.956 | 1.450 | 3.329 | 0 | 1.716 | 1.095 |
Notes.
Hill model for BMDS and PROAST. The Hill model was fitted as an unrestricted model in BMDS.
Exponential model in BMDS and PROAST. The exponential model was fitted as a restricted model in BMDS.
No model fitted for this data set using PROAST.