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A Comparison of Two Statistical Approaches to Estimate Long‐Term Exposure Distributions from Short‐Term Measurements
Author(s) -
Slob Wout
Publication year - 1996
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1996.tb01449.x
Subject(s) - term (time) , statistics , analysis of variance , regression , regression analysis , econometrics , statistical model , statistical analysis , variance (accounting) , mathematics , computer science , physics , accounting , quantum mechanics , business
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.