Optimizing the Fraction of Expensive Direct Measurements in an Exposure Assessment Study

Mahmoud Rezagholi; Apostolos Bantekas

doi:10.6000/1929-6029.2013.02.04.6

Authors

Mahmoud Rezagholi Division of Economics, Department of Business and Economic Studies, University of Gävle, SE-801 76 Gävle, Sweden
Apostolos Bantekas Division of Economics, Department of Business and Economic Studies, University of Gävle, SE-801 76 Gävle, Sweden

DOI:

https://doi.org/10.6000/1929-6029.2013.02.04.6

Keywords:

Statistical efficiency, combined measurement technique, productive efficiency, cost savings, marginal cost-benefit ratio, cost function

Abstract

When designing studies to assess occupational exposures, one persistent decision problem is the selection between two technical methods, where one is expensive and statistically efficient and the other is cheap and statistically inefficient. While a few studies have attempted to determine the relatively more cost-efficient design between two technical methods, no successful study has optimized the fraction of the expensive efficient method in a combined technique intended for long-run exposure assessment studies. The purpose of this study was therefore to optimize the fraction of the expensive efficient measurements by resolving a precision-requiring cost minimization problem. For an indefinite total number of measurements, the total cost of a working posture assessment study was minimized by performing only expensive direct technical measurements. However, for a definite total number of measurements, the use of combined techniques in assessing the posture could be optimal, depending on the constraints placed on the precision and on the research budget.

Author Biographies

Mahmoud Rezagholi, Division of Economics, Department of Business and Economic Studies, University of Gävle, SE-801 76 Gävle, Sweden

Division of Economics, Department of Business and Economic Studies

Apostolos Bantekas, Division of Economics, Department of Business and Economic Studies, University of Gävle, SE-801 76 Gävle, Sweden

Division of Economics, Department of Business and Economic Studies

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