The cost models and the underlying study data are critical steps in the overarching aim of identifying optimally cost-efficient studies of biomechanical exposure.
Then, the general model is simplified, and procedures are derived for identifying optimally cost-efficient exposure assessment strategies, depending on the shapes of cost functions.
A few studies take on the more challenging task of determining the optimally cost-efficient strategy at a certain budget, on the basis of specified costs for collecting data at different stages, and specified sizes of the corresponding variance components.
Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components.
The determination of the boldface strategy in section a was illustrated in figure 4. As illustrated in table 2, the optimally cost-efficient strategy in many scenarios is to obtain data on one occasion from as many subjects as possible.
Determination of variance components requires, as a minimum, duplicate samples at each stage of the measurement model [ 5], and this may often not be an optimally cost-efficient strategy if the objective is to get a precise group mean (cf. table 2a-c; cases with n d = 1).
Since both bias and precision can, under a number of assumptions, be expressed as mathematical functions of variance components and the number of measurements [ 18], it might be possible to develop closed-form solutions to the problem of finding optimally cost-efficient measurement strategies, but this has not so-far been pursued.
Obviously, both for regression metrics, exceedance, and ICCs, optimally cost-efficient exposure assessment strategies may deviate from those driven by the objective of obtaining precise exposure means, as illustrated by two studies on optimal measurement allocation in reliability studies [ 69, 70].
In theory, a composition of power plants that is optimally adapted to residual load always leads to the most cost efficient supply of electricity.
We need something extremely energy efficient and cost efficient".
