TY - JOUR
T1 - Nonparametric benchmark analysis in risk assessment
T2 - A comparative study by simulation and data analysis
AU - Bhattacharya, Rabi
AU - Lin, Lizhen
N1 - Funding Information:
Research supported by NIH grant R21-ES016791 and NSF grant DMS 0806011.
Publisher Copyright:
© 2011, Indian Statistical Institute.
PY - 2011/5
Y1 - 2011/5
N2 - We consider the finite sample performance of a new nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages, and whose asymptotic behavior is essentially optimal (Bhattacharya and Lin, Stat Probab Lett 80:1947-1953, 2010). It is compared with three other methods, including the leading kernel-based method, called DNP, due to Dette et al. (J Am Stat Assoc 100:503-510, 2005) and Dette and Scheder (J Stat Comput Simul 80(5):527-544, 2010). In simulation studies, the present method, termed NAM, outperforms the DNP in the majority of cases considered, although both methods generally do well. In small samples, NAM and DNP both outperform the MLE.
AB - We consider the finite sample performance of a new nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages, and whose asymptotic behavior is essentially optimal (Bhattacharya and Lin, Stat Probab Lett 80:1947-1953, 2010). It is compared with three other methods, including the leading kernel-based method, called DNP, due to Dette et al. (J Am Stat Assoc 100:503-510, 2005) and Dette and Scheder (J Stat Comput Simul 80(5):527-544, 2010). In simulation studies, the present method, termed NAM, outperforms the DNP in the majority of cases considered, although both methods generally do well. In small samples, NAM and DNP both outperform the MLE.
KW - Bootstrap
KW - Confidence interval
KW - Effective dosage
KW - Mean integrated squared error
KW - Monotone dose-response curve estimation
KW - Nonparametric method
KW - Pool-adjacent-violators algorithm
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U2 - 10.1007/s13571-011-0019-7
DO - 10.1007/s13571-011-0019-7
M3 - Article
AN - SCOPUS:80755180755
SN - 0972-7671
VL - 73
SP - 144
EP - 163
JO - Sankhya: The Indian Journal of Statistics
JF - Sankhya: The Indian Journal of Statistics
IS - 1
ER -