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A Comparison of Two Statistical Approaches to Estimate Long‐Term Exposure Distributions from Short‐Term Measurements

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  • Wout Slob

Abstract

Two statistical approaches are briefly reviewed, both of which are suitable for estimating interindividual variation in long‐term exposure: a recently published regression approach and the standard ANOVA approach. Simulation studies illustrate the performances of the two approaches in estimating the relevant parameters. Their relative advantages and applicability are discussed. It is concluded that when repeated exposure measurements from the same individuals are available, ANOVA is preferable. The regression approach however has its place because it can be applied to certain data types where ANOVA does not apply.

Suggested Citation

  • Wout Slob, 1996. "A Comparison of Two Statistical Approaches to Estimate Long‐Term Exposure Distributions from Short‐Term Measurements," Risk Analysis, John Wiley & Sons, vol. 16(2), pages 195-200, April.
    • Handle: RePEc:wly:riskan:v:16:y:1996:i:2:p:195-200
    DOI: 10.1111/j.1539-6924.1996.tb01449.x
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    References listed on IDEAS

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    1. Wout Slob, 1993. "Modeling Long‐Term Exposure of the Whole Population to Chemicals in Food," Risk Analysis, John Wiley & Sons, vol. 13(5), pages 525-530, October.
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