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Confidence limits for lognormal percentiles and for lognormal mean based on samples with multiple detection limits.

Authors
Krishnamoorthy-K; Xu-Z
Source
Ann Occup Hyg 2011 Jun; 55(5):495-509
NIOSHTIC No.
20040146
Abstract
The problem of assessing occupational exposure using the mean or an upper percentile of a lognormal distribution is addressed. Inferential methods for constructing an upper confidence limit for an upper percentile of a lognormal distribution and for finding confidence intervals for a lognormal mean based on samples with multiple detection limits are proposed. The proposed methods are based on the maximum likelihood estimates. They perform well with respect to coverage probabilities as well as power and are applicable to small sample sizes. The proposed approaches are also applicable for finding confidence limits for the percentiles of a gamma distribution. Computational details and a source for the computer programs are given. An advantage of the proposed approach is the ease of computation and implementation. Illustrative examples with real data sets and a simulated data set are given.
Keywords
Mathematical-models; Statistical-analysis; Exposure-levels; Exposure-limits; Permissible-concentration-limits; Permissible-limits; Sampling; Analytical-processes; Analytical-models; Risk-analysis; Computer-models; Author Keywords: exceedance probability; gamma distribution; left-censored samples; non-central t; ROS method; tolerance limits
Contact
Kalimuthu Krishnamoorthy, Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA 70508-1010, USA
CODEN
AOHYA3
Publication Date
20110601
Document Type
Journal Article
Email Address
krishna@louisiana.edu
Editors
Funding Amount
400453
Funding Type
Grant
Fiscal Year
2011
NTIS Accession No.
NTIS Price
Identifying No.
Grant-Number-R01-OH-003628; B01182012
Issue of Publication
5
ISSN
0003-4878
Priority Area
Research Tools and Approaches: Exposure Assessment Methods
Source Name
Annals of Occupational Hygiene
State
LA; MD
Performing Organization
University of Maryland, Baltimore
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