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

Estimation of relative risk functions.

J F Bithell1

  • 1Department of Statistics, University of Oxford, U.K.

Statistics in Medicine
|November 1, 1991
PubMed
Summary

This study introduces relative risk functions for factors without a natural zero, like age. It details methods for estimating these functions, particularly for continuous variables, aiding in risk assessment for epidemiological data.

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

Childhood cancer research in Oxford I: the Oxford Survey of Childhood Cancers.

British journal of cancer·2018
Same author

Leukaemia in young children in the vicinity of British nuclear power plants: a case-control study.

British journal of cancer·2013
Same author

Childhood leukaemia near British nuclear installations: methodological issues and recent results.

Radiation protection dosimetry·2008
Same author

Childhood leukaemia and non-Hodgkin's lymphoma in relation to proximity to railways.

British journal of cancer·2003
Same author

Population mixing and childhood leukaemia and non-Hodgkin's lymphoma in census wards in England and Wales, 1966-87.

British journal of cancer·2002
Same author

Childhood leukaemia clustering--fact or artefact?

Methods of information in medicine·2001

Area of Science:

  • Epidemiology
  • Biostatistics
  • Quantitative Risk Assessment

Background:

  • Traditional risk assessment often relies on a natural zero point for quantitative factors.
  • Factors like age lack a natural zero, necessitating alternative risk measurement approaches.
  • Existing methods may not adequately address continuous risk factors or confounding variables.

Purpose of the Study:

  • To introduce and discuss methods for estimating relative risk functions when a natural zero for a risk factor is absent.
  • To explore the application of these functions for continuous variables and in multidimensional analyses.
  • To demonstrate the utility of adjusted relative risk functions in epidemiological research, using childhood cancer data.

Main Methods:

  • Development of relative risk functions for quantitative factors without a natural zero.
  • Focus on estimation methods for discrete cases, with extensions to continuous variables.
  • Application of multiplicative risk models and log-linear models for confounding control and adjusted risk estimation.

Main Results:

  • The proposed methods allow for risk assessment relative to the population average, accommodating continuous factors.
  • Joint effects of multiple factors and control for confounding variables are addressed through multiplicative risk models.
  • The methodology is illustrated effectively using childhood cancer data, showing practical application.

Conclusions:

  • Relative risk functions provide a flexible framework for risk assessment when natural zeros are absent.
  • The methods discussed enable robust analysis of continuous risk factors and complex epidemiological data.
  • This approach enhances the understanding of risk factors in public health and medical research.

Related Experiment Videos