A comparison of two statistical approaches to estimate long-term exposure distributions from short-term measurements

Risk Analysis

Volumn 16, Issue 2, 1996, Pages 195-200

  Slob, Wout ^a  

^a NATIONAL INSTITUTE FOR PUBLIC HEALTH AND THE ENVIRONMENT   (Netherlands)

Author keywords

ANOVA; interindividual variation; Long term exposure; nonlinear regression; short term exposure

Indexed keywords

COMPUTER SIMULATION; ESTIMATION; REGRESSION ANALYSIS; RISK ASSESSMENT;

INTERINDIVIDUAL VARIATION; LONG TERM EXPOSURE; STANDARD ANOVA APPROACH;

STATISTICAL METHODS;

ARTICLE; CALCULATION; DIAGNOSTIC APPROACH ROUTE; LONG TERM EXPOSURE; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICAL ANALYSIS;

EID: 0030130816     PISSN: 02724332     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1539-6924.1996.tb01449.x     Document Type: Article

References (5)

1. L. A. Wallace, N. Duan, and R. Ziegenfus, "Can Long-Term Exposure Be Predicted from Short-Term Measurements?" Risk Analysis 14, 75-85 (1994).
2. W. Slob, "Modeling Long-Term Exposure of the Whole Population to Chemicals in Food," Risk Analysis 13, 525-530 (1993).
3. R. R. Sokal and F. J. Rohlf, Biometry (W. H. Freeman & Co., San Francisco, 1981).
4. W. Slob, R. v.d. Berg, and M. P. van Veen, "A Statistical Exposure Model (STEM) Applied to Nitrate Intake in the Dutch Population," in Proceedings of the International Workshop on Health Aspects of Nitrate and Its Metabolites, Bilthoven, Council of Europe Press, pp. 75-82 (1995).
5. Slob, Modeling Human Exposure to Chemicals in Food (RIVM, Bilthoven, Report No. 639102002, 1993).