The proposed research is on the development of statistical procedures that are appropriate for analyzing exposure data. The statistical models considered are all directly relevant for exposure assessment. The proposed problems are on the following topics: the univariate, bivariate and multivariate lognormal distributions to describe exposure data, methodology for comparing several test methods or samplers, procedures to analyze samples that include low concentrations of chemicals (in particular, values below the detection limit), regression models for modeling the relationship among exposure variables, statistical techniques for the evaluation of low cost, easy to use and non-invasive test methods, statistical methodology for biological monitoring, in particular, for estimating the concentrations of chemicals and biomarkers in the blood and internal organs based on non-invasive measurements. Difficulties and limitations of some of the currently used statistical techniques will be highlighted, and efficient alternatives will be developed. Novel approaches based on new concepts such as generalized p values and generalized confidence intervals will be pursued for solving some of these problems. The associated computational details will be addressed in detail, and software codes will be provided. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute for Occupational Safety and Health (NIOSH)
Type
Research Project (R01)
Project #
2R01OH003628-04A2
Application #
6899039
Study Section
Safety and Occupational Health Study Section (SOH)
Program Officer
Board, Susan
Project Start
2005-05-01
Project End
2008-04-29
Budget Start
2005-05-01
Budget End
2006-04-30
Support Year
4
Fiscal Year
2005
Total Cost
$297,850
Indirect Cost
Name
University of Maryland Balt CO Campus
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
061364808
City
Baltimore
State
MD
Country
United States
Zip Code
21250
Krishnamoorthy, K; Mathew, Thomas; Xu, Zhao (2014) Comparison of means of two lognormal distributions based on samples with multiple detection limits. J Occup Environ Hyg 11:538-46
Krishnamoorthy, Kalimuthu; Mathew, Thomas; Xu, Zhao (2013) Tests for an upper percentile of a lognormal distribution based on samples with multiple detection limits and sample-size calculation. Ann Occup Hyg 57:1200-12
Krishnamoorthy, Kalimuthu; Mathew, Thomas (2013) The symmetric-range accuracy under a one-way random model with balanced or unbalanced data. Ann Occup Hyg 57:953-61
Krishnamoorthy, Kalimuthu; Xu, Zhao (2011) Confidence limits for lognormal percentiles and for lognormal mean based on samples with multiple detection limits. Ann Occup Hyg 55:495-509
Bebu, Ionut; Mathew, Thomas (2008) Comparing the means and variances of a bivariate log-normal distribution. Stat Med 27:2684-96