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RECORD NUMBER: 18 OF 86

OLS Field Name OLS Field Data
Main Title Confidence Intervals for a Crop Yield Loss Function in Nonlinear Regression.
Author Lee, E. H. ; Tingey, D. T. ; Hogsett, W. E. ;
CORP Author NSI Technology Services Corp., Corvallis, OR.;Corvallis Environmental Research Lab., OR.
Publisher c1990
Year Published 1990
Report Number EPA-68-C8-0006; EPA/600/J-90/294;
Stock Number PB91-146506
Additional Subjects Ozone ; Air pollution effect(Plants) ; Farm crops ; Confidence limits ; Seasonal variations ; Mathematical models ; Dose-response relationships ; Plant growth ; Reprints ; Crop yield
Holdings
Library Call Number Additional Info Location Last
Modified
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Status
NTIS  PB91-146506 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/13/1991
Collation 22p
Abstract
Quantifying the relationship between chronic pollutant exposure and the ensuring biological response requires consideration of nonlinear functions that are flexible enough to generate a wide range of response curves. The linear approximation (i.e., Wald's) interval estimates for ozone-induced relative crop yield loss are sensitive to parameter curvature effects in nonlinear regression. The adequacy of Wald's confidence interval for proportional response is studied using the nonlinearity measures proposed by Bates and Watts (1980), Cook and Goldberg (1986), and Clarke (1987a & b) and the profile t plots of Bates and Watts (1988). Numerical examples comparing Wald's, likelihood ratio, the bootstrap, and Clarke's adjusted 95% confidence intervals for relative crop yield loss are presented for a number of ozone exposure studies conducted by the National Crop Loss Assessment Network (NCLAN) program. At ambient levels of ozone concentration, the effects of nonlinearity were significant and invalidated the adequacy of Wald's confidence interval. Depending upon the severity of the curvature effects, an alternative interval (i.e., Clarke's adjustment to Wald's interval or the likelihood ratio interval) for proportional yield loss should be considered. (Copyright (c) 1990 Marcel Dekker, Inc.)