Health & Environmental Research Online (HERO)


Print Feedback Export to File
5486603 
Journal Article 
Statistical inferences from serially correlated methylene chloride data 
Klein, M; Neerchal, N; Sinha, B; Chiu, W; White, P 
2012 
1 
Sankhya: Indian Journal of Statistics
ISSN: 0976-8386
EISSN: 0976-8394 
74 
2 
211-237 
English 
While physiologically-based pharmacokinetic (PBPK) modeling has become an important tool in environmental health risk assessment, a rigorous statistical methodology is not routinely incorporated into these analyses. This paper illustrates how to carry out a formal statistical analysis to obtain improved inference upon model parameters from time-dependent, serially correlated methylene chloride data combined from several experiments. Frequentist and Bayesian methods are both considered. We work with a well established PBPK model for disposition of inhaled dichloromethane (DCM, methylene chloride) gas within a closed chamber. 
Dichloromethane (DCM), methylene chloride, nonlinear regression models, ordinary differential equations, PBPK models, serial correlation 
IRIS
• Chloroprene