TY - JOUR

T1 - Upper limits for exceedance probabilities under the one-way random effects model

AU - Krishnamoorthy, K.

AU - Mathew, Thomas

AU - Ramachandran, Gurumurthy

N1 - Funding Information:
Acknowledgements—This research was supported by grant R01-0H03628-01A1 from the National Institute of Occupational Safety and Health (NIOSH). The authors are thankful to Ms. Yanping Xia for providing computational help and SAS code; they are also grateful to two reviewers and assistant editor David Bartley for providing valuable comments and suggestions.

PY - 2007/6

Y1 - 2007/6

N2 - In this article, we propose statistical methods for setting upper limits on (i) the probability that the mean exposure of an individual worker exceeds the occupational exposure limit (OEL) and (ii) the probability that the exposure of a worker exceeds the OEL. The proposed method for (i) is obtained using the generalized variable approach, and the one for (ii) is based on an approximate method for constructing one-sided tolerance limits in the one-way random effects model. Even though tolerance limits can be used to assess the proportion of exposure measurements exceeding the OEL, the upper limits on these probabilities are more informative than tolerance limits. The methods are conceptually as well as computationally simple. Two data sets involving industrial exposure data are used to illustrate the methods.

AB - In this article, we propose statistical methods for setting upper limits on (i) the probability that the mean exposure of an individual worker exceeds the occupational exposure limit (OEL) and (ii) the probability that the exposure of a worker exceeds the OEL. The proposed method for (i) is obtained using the generalized variable approach, and the one for (ii) is based on an approximate method for constructing one-sided tolerance limits in the one-way random effects model. Even though tolerance limits can be used to assess the proportion of exposure measurements exceeding the OEL, the upper limits on these probabilities are more informative than tolerance limits. The methods are conceptually as well as computationally simple. Two data sets involving industrial exposure data are used to illustrate the methods.

KW - Between- and within-worker variability

KW - Generalized P-value

KW - Generalized confidence interval

KW - Tolerance interval

UR - http://www.scopus.com/inward/record.url?scp=34548222237&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548222237&partnerID=8YFLogxK

U2 - 10.1093/annhyg/mem013

DO - 10.1093/annhyg/mem013

M3 - Article

C2 - 17519274

AN - SCOPUS:34548222237

VL - 51

SP - 397

EP - 406

JO - Annals of Work Exposures and Health

JF - Annals of Work Exposures and Health

SN - 2398-7308

IS - 4

ER -