Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Fitting human exposure data with the Johnson S(B) distribution.

Michael R Flynn1

  • 1Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina, CB 7431 Rosenau Hall, Chapel Hill, NC 27599-7431, USA. mike_flynn@unc.edu

Journal of Exposure Science & Environmental Epidemiology
|July 12, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Nigral MRI features of asymptomatic welders.

Parkinsonism & related disorders·2021
Same author

Higher Hippocampal Mean Diffusivity Values in Asymptomatic Welders.

Toxicological sciences : an official journal of the Society of Toxicology·2019
Same author

Welding-related brain and functional changes in welders with chronic and low-level exposure.

Neurotoxicology·2017
Same author

Association of neurobehavioral performance with R2* in the caudate nucleus of asymptomatic welders.

Neurotoxicology·2016
Same author

Longitudinal T1 relaxation rate (R1) captures changes in short-term Mn exposure in welders.

Neurotoxicology·2016
Same author

Editor's Highlight: Lower Fractional Anisotropy in the Globus Pallidus of Asymptomatic Welders, a Marker for Long-Term Welding Exposure.

Toxicological sciences : an official journal of the Society of Toxicology·2016
Same journal

The combined impact of chemical and non-chemical stressors on adverse health outcomes: an overview of reviews from the epidemiological literature and experimental animal studies.

Journal of exposure science & environmental epidemiology·2026
Same journal

Diet and mycoestrogen exposure in a pregnancy cohort: the Jersey Babies pilot study.

Journal of exposure science & environmental epidemiology·2026
Same journal

Source apportionment of fine particulate matter (PM<sub>2.5</sub>) personal exposures: findings from the Household Air Pollution Intervention Network (HAPIN) study in rural Guatemala.

Journal of exposure science & environmental epidemiology·2026
Same journal

The impact of geomagnetic disturbances on mortality from respiratory tract infections in the USA, 2000-2019.

Journal of exposure science & environmental epidemiology·2026
Same journal

Metabolome-wide association study identifies metabolites associated with human exposure to perfluoroalkyl substances.

Journal of exposure science & environmental epidemiology·2026
Same journal

Contribution of non-dietary indoor exposure pathways to total phthalate intake of 324 children in Tianjin, China.

Journal of exposure science & environmental epidemiology·2026
See all related articles

Estimating human exposure and environmental concentrations requires robust statistical methods. This study explores alternative fitting procedures for the S(B) distribution, offering improved parameter estimation for risk assessments.

Area of Science:

  • Environmental Science and Exposure Assessment
  • Biostatistics and Probability Distributions

Background:

  • Accurate estimation of human exposure and environmental concentrations is crucial for epidemiological studies and risk assessments.
  • The S(B) distribution is a theoretically suitable model for bounded variables like human exposures but presents fitting challenges.
  • Maximum likelihood methods for S(B) distribution parameter fitting are often problematic.

Purpose of the Study:

  • To investigate alternative methods for fitting the S(B) distribution parameters.
  • To address the limitations of maximum likelihood estimation for this distribution.
  • To provide reliable methods for estimating population mean, variance, background, and peak exposures.

Main Methods:

  • Exploration of two percentile-based methods: a quantile estimator and a method-of-moments fitting procedure.

Related Experiment Videos

  • Development of new explicit expressions for the first four moments of the S(B) distribution.
  • Comparison of fitting procedures through simulation studies and analysis of real-world human exposure data.

    • Main Results:

    • The quantile and method-of-moments procedures demonstrate viability for S(B) distribution fitting.
    • These alternative methods offer practical solutions where maximum likelihood fails.
    • Performance was evaluated using both simulated data and actual measurements of airborne contaminant exposure.

    Conclusions:

    • The quantile and method-of-moments approaches provide effective alternatives for fitting the S(B) distribution.
    • These methods enhance the ability to estimate key exposure parameters for risk assessment and epidemiology.
    • The study validates these procedures with empirical human exposure data.