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Presenting statistical uncertainty in trends and dose-response relations.

S Greenland1, K B Michels, J M Robins

  • 1Department of Epidemiology, UCLA School of Public Health, Los Angeles, CA, USA.

American Journal of Epidemiology
|June 16, 1999
PubMed
Summary

Estimating polytomous exposure effects often uses a reference level. Alternatives exist, but flexible curves offer valid confidence intervals for continuous data, addressing shortcomings of categorical methods.

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Estimating effects of polytomous exposures commonly uses a reference level.
  • This practice has been challenged, prompting exploration of alternative methods.

Purpose of the Study:

  • To review alternative methods for estimating polytomous exposure effects.
  • To address shortcomings of categorical methods, especially for continuous exposures.

Main Methods:

  • Review of existing literature on exposure effect estimation.
  • Evaluation of the "floating absolute risk" method.
  • Application of flexible curves fitted to uncategorized data.

Main Results:

  • The "floating absolute risk" method provides useful statistics and trend graphs.

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  • This method does not yield valid confidence intervals for relative risks.
  • Flexible curves fitted to uncategorized data can address shortcomings of categorical methods for continuous exposures.

    • Conclusions:

    • Standard reference level methods for polytomous exposures have limitations.
    • Alternative methods like "floating absolute risk" have drawbacks.
    • Flexible curves offer a statistically valid approach for continuous exposure data.