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
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U2 - 10.1093/annhyg/mem013
DO - 10.1093/annhyg/mem013
M3 - Article
C2 - 17519274
AN - SCOPUS:34548222237
SN - 0003-4878
VL - 51
SP - 397
EP - 406
JO - Annals of Occupational Hygiene
JF - Annals of Occupational Hygiene
IS - 4
ER -